{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00000-4f397e5f-b3e8-4968-9527-05cfb274bb53",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "view-in-github"
},
"source": [
"![\"Open](\"https://colab.research.google.com/assets/colab-badge.svg\")
"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00001-34c40f61-06ce-4418-bbce-e2ce90ce485d",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "QC4VVNb6F_yr",
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"\n",
"
![](\"https://www.python.org/static/community_logos/python-logo-master-v3-TM.png\")
\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00004-81e7146e-c6ee-4365-bf24-e91f88b7ecf8",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "ru2dYuqiF_yu"
},
"source": [
"- - - "
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00005-13c84412-9812-4fbe-91e9-226f0e561b93",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "hbVuNve0Lp_-",
"jp-MarkdownHeadingCollapsed": true,
"slideshow": {
"slide_type": "slide"
},
"tags": []
},
"source": [
"## String, Integer, Float\n",
"The basic types of variables in Python are:\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00006-65a6724f-f322-49ed-9e09-6bcbf9457264",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "oO8rcC_aMYXO",
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"`str`:"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00007-e253803b-ed4b-4907-9356-4a83b0039b30",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "POJ9rA7A40WK",
"slideshow": {
"slide_type": "subslide"
},
"tags": [
"popout"
]
},
"source": [
"Illustrated with the `hello world` standard"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00008-91be0a32-abda-4520-a914-714ff10afa93",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "5_KEVfViMOZC",
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [],
"source": [
"#Strings\n",
"hello='hola'"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00009-969a988b-eb14-46a7-816d-4e848b57ed69",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "n6ff3fKrMdHF",
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"`int`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00010-c92b506d-2fe8-417d-bb15-d35301b5e4b3",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "Bm-RxdlxMVGU",
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [],
"source": [
"#Integer\n",
"n=3"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00011-2853f608-5fe9-4ee1-81b5-22c17a614390",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "P6JSYRm_Mh41",
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"`float`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00012-bb0745de-12de-47dc-9a3b-3019d0034d3f",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "XJF1vwxJMlyl"
},
"outputs": [],
"source": [
"x=3.5"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00013-41c6f7d2-9e69-4116-9779-197608446a46",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "wTzMkndjJFZp",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"## Functions I\n",
"Python includes a battery of predefined functions which takes an input and generates an output. For example, to check the type of variable we can used the\n",
"predefined function\n",
"### `isinistance`:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00014-d3d484c8-fe92-4249-823b-33b8cfb50f67",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "4K96FCuENYCd",
"outputId": "2da1940e-179b-4722-c6a2-cdd8e210686c"
},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"isinstance(hello,str)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00015-51d87b6c-cae5-4fe5-adac-13c50bea1679",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "YeFccBUZNggD"
},
"source": [
"**Activity**: In the next cell check if `n` is a `float` type of variable"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00016-72e793a7-fa96-46d6-b80d-6cb00842b564",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "x3mFZU1aNu-U"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00017-787585d6-0d9d-4993-9a1e-77f716393cc8",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "RQJLzZTxNxGb"
},
"source": [
"### `print`"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00018-12f271e5-3695-44c1-8ddb-3dcf95f8c75d",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "N7GTR9AiM5Xm"
},
"source": [
"See: https://pyformat.info/\n",
"\n",
"To write the _Hello world_ program in python we must first introduce the concept of function. It is the same in mathematics, were something called function receives a number and return back another number. For example, the function to square a number is\n",
"\\begin{equation}\n",
"f(x)=x^2\\,,\n",
"\\end{equation}\n",
"$x$ is called the argument of the function $f$, and the _returned_ value is the evaluation of $f(x)$.\n",
"\n",
"In `Python` there are a lot of such a functions.\n",
"In particular there is a function called `print` which takes strings (see below) as input and return the same string as output. In this way, the __hello world__ program in Python is one of the most simple between all the programming languages:"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00019-517c05f6-21d9-426a-a296-d9dde08cab22",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "PJOXAlbAF_yv",
"tags": []
},
"source": [
"## Hello World!"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00020-16a2021c-4785-4ccb-863f-7df6efc8aeae",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "Cmd-Wx7oF_yw",
"outputId": "923773c2-46e1-4f85-9728-30d47dbeff41"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello World!\n"
]
}
],
"source": [
"print('Hello World!')"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00021-28b16aec-3e64-4af4-84d5-78267d544c8c",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "_WerUXfIF_y0"
},
"source": [
"And also allows scripting: *(This code should be copied on a file 'hello.py')*"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00022-a1283afa-00ff-4c65-9fad-59500a590fd6",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "WTvsRsI_F_y1",
"outputId": "37adc2e2-26a0-4e88-fea4-f7289cc8f9b3"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello World!\n"
]
}
],
"source": [
"#! /usr/bin/python\n",
"\n",
"#This is a comment\n",
"print('Hello World!')"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00023-13a8d280-1ab3-4b2d-b467-abcbaafbc948",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "cvkfIERrN6GT"
},
"source": [
"The recommended way to print a variable in Python is to use the `.format` _method_ of the function `print` by preceding the sring with the letter `f`. Inside the string any variable between curly brackets, `{variable}`, can be used"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00024-811d5082-ffdd-42f4-92fd-53ae42eb27da",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1626453090430,
"id": "4iiFnX3GOSix",
"outputId": "189ad787-6654-4205-b084-9b3286a1793f",
"source_hash": "3e036be2"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello World!\n"
]
}
],
"source": [
"hello='Hello World!'\n",
"print(f'{hello}')"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00025-1bac035d-fc1f-4347-a35b-7ed20fd9e7da",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "mAOFOHQtOlYD"
},
"source": [
"__Activity__: Change the values of the previous string variables to print `Hello World!` in Spanish "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"23456.57\n"
]
}
],
"source": [
"x=23456.5678545\n",
"print(f'{x:.2f}')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"__Activity__: Print with 3 decimal places"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00026-4805810c-5c15-4710-8026-bae638fb8f8c",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "markdown",
"id": "lckGJ4UsPBSR",
"tags": []
},
"source": [
"## Functions II"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00027-592d06b0-4e0f-433a-bdeb-a29ddc6ac39d",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "KJTsJ2exKcSQ"
},
"source": [
"In `Python` it is possible also to create new [functions](https://en.wikibooks.org/wiki/Python_Programming/Functions). We illustrate the format to define a function in `Python` with the implementation of the function $f(x)=x^2$, where to write an exponent: ${}^2$, in Python we must use the format: `**2`."
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00028-7b74f015-b720-4b86-b279-41314b94db49",
"deepnote_cell_type": "markdown",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Implicit functions"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00029-d7d95097-f42c-415b-a1bd-9c7704717b9d",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "SLI_RmTIKr_2"
},
"outputs": [],
"source": [
"f=lambda x:x**2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00030-26b39a17-b613-4fc8-94f0-5e6c89e2f50d",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"isinstance(f,str)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00031-79297844-077e-4635-8e17-58b38e1e0ce2",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"function"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(f)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00032-98229684-c9cb-4db0-8998-ca3a47b7de9d",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "kSBRdi67dfD1",
"outputId": "25c8f546-806d-4462-d87a-f8cc63c5d536"
},
"outputs": [
{
"data": {
"text/plain": [
"9"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f(3)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00033-61dd30ec-2a6d-4012-b387-d080d1fd8989",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "R3j70bwqF_1Y",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Explicit functions"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00034-fb1ab9ee-21c4-4421-8b9b-5c48a4c8b7e2",
"deepnote_cell_type": "markdown"
},
"source": [
"The standard function build may include the help for the function"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00035-e180aab0-ab38-489f-ba08-34be6332faa2",
"deepnote_cell_type": "code"
},
"outputs": [],
"source": [
"def f(x):\n",
" '''\n",
" Calculates the square of `x`\n",
" '''\n",
" return x**2"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00036-c65adff0-6b70-4d2c-a011-8fca30c55934",
"deepnote_cell_type": "markdown"
},
"source": [
"f(5)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00037-38b7a17c-cd1d-48fe-b1ea-5a5072610698",
"deepnote_cell_type": "code"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on function f in module __main__:\n",
"\n",
"f(x)\n",
" Calculates the square of `x`\n",
"\n"
]
}
],
"source": [
"help(f)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00038-462d3558-b374-4618-bd59-a80b2d0b111c",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "DJwBYqi440XD"
},
"source": [
"The full list of built-in functions is in https://docs.python.org/3/library/functions.html and the specific help for a function, for example `print` can be checked with https://docs.python.org/3/library/functions.html#print"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00039-22606d64-26bf-44cb-8348-1d4b575937b5",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "z3IAaPwJF_1Z",
"outputId": "f550c7a2-861b-4c92-e5ac-f816531e2b54"
},
"outputs": [
{
"data": {
"text/plain": [
"6"
]
},
"execution_count": 129,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def f(x,y):\n",
" '''\n",
" Multiply two numbers\n",
" '''\n",
" return x*y\n",
"f(3,2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00040-961f1860-4b88-4d6f-9e2c-dfadf8d90088",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "hMkLVbRRF_1a",
"outputId": "1fe169d5-b147-448d-89ba-63063ef02d92"
},
"outputs": [
{
"data": {
"text/plain": [
"6"
]
},
"execution_count": 130,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#It is possible to assign default arguments\n",
"def f(x,y=2):\n",
" '''\n",
" Multiply two numbers. By default the second is 2\n",
" ''' \n",
" return x*y\n",
"#When evaluating, we can omit the default argument\n",
"f(3)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00041-1fd18671-3f9e-4952-9858-17084a1d1a7e",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "Ee_8WkNdnnaj",
"outputId": "4a6511b0-42aa-467c-92a4-b02765b3f741"
},
"outputs": [
{
"data": {
"text/plain": [
"6"
]
},
"execution_count": 131,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f(2,3)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00042-61782059-8e73-432a-8637-7ac4f91820d2",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "uCLluCGVnqWj",
"outputId": "a43bcd34-b8ee-4279-889d-d92ee71618ac"
},
"outputs": [
{
"data": {
"text/plain": [
"10"
]
},
"execution_count": 132,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f(2,y=5)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00043-0d8d6730-9581-4ed8-b5b9-ee99fe9e7713",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 52
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "Eh6jou-TF_1c",
"outputId": "d82b0602-72f2-4e18-9260-78a71ebca88c"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"f(1,2)= 1\n",
"f(2,1)= 2\n"
]
}
],
"source": [
"#It is possible to specify explicitly the order of the arguments\n",
"def f(x,y):\n",
" '''\n",
" evaluates x to the power y\n",
" ''' \n",
" return x**y\n",
"print( 'f(1,2)=',f(1,2) )\n",
"print( 'f(2,1)=',f(y=1,x=2) )"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00044-b18eb58e-48c1-4974-834a-5360ab115abc",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "PYyDcKZ5F_1e"
},
"source": [
"### Implicit functions of several arguments"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00045-b10fb053-57c3-4fba-be8d-f163bf0cf2a9",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "-suvy_mEF_1e"
},
"source": [
"Implicit functions are usdeful when we want to use a function once."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00046-76cd6d35-3e2b-47a0-9edb-5f9a8dc2cb2e",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "FMTOmWFYF_1f",
"outputId": "8e7c1b41-a48e-4a9b-bd3c-4f4a9fd9cf78"
},
"outputs": [
{
"data": {
"text/plain": [
"9"
]
},
"execution_count": 138,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f = lambda x,y: x**y\n",
"f(3,2)"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"### Nested functions"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00047-126140fa-fc08-4d74-874a-d90d37dd86da",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 70
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "mWGO2OHrF_1g",
"outputId": "4532bcfe-9ffc-49cc-bdd2-d3077580246f"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n",
"16\n",
"Implicit: f(2)^2 = 16\n"
]
}
],
"source": [
"#It is possible to pass functions as arguments of other function\n",
"def f2( f, x ):\n",
" return f(x)**2\n",
"\n",
"#We can define a new function explicitly\n",
"def f(x):\n",
" return x+2\n",
"\n",
"print(f(2))\n",
"print(f2(f,2))\n",
"\n",
"\n",
"#Or define the function implicitly\n",
"print (\"Implicit: f(2)^2 =\", f2(lambda x:x+2,2) )"
]
},
{
"cell_type": "markdown",
"metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Inner functions with returned internal function"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"cell_id": "00048-66af3fe0-dd06-4063-aece-2a26de1531db",
"deepnote_cell_type": "code"
},
"outputs": [],
"source": [
"def hola(func):\n",
" def function_wrapper(x):\n",
" res = 'hola mundo '+str(func(x))\n",
" return res\n",
" return function_wrapper\n",
"\n",
"def mundo(n):\n",
" return n+' y despiadado'"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'hola mundo cruel y despiadado'"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"foo=hola(mundo)\n",
"foo('cruel')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"or just"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'hola mundo cruel y despiadado'"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"hola(mundo)('cruel')"
]
},
{
"cell_type": "markdown",
"metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Decorators\n",
"From: [[@]](https://realpython.com/primer-on-python-decorators/) https://realpython.com/primer-on-python-decorators/\n",
"> By definition, a decorator is a function that takes another function and extends the behavior of the latter function without explicitly modifying it.\n",
"\n",
"See also: https://www.python-course.eu/python3_decorators.php.\n",
"\n",
"The previos function `hola` can be used as a decorator, in a such way that it is not necesary to call it directly but only to call its argument"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"@hola\n",
"def mundano(n):\n",
" return n+' y despiadado'\n",
"\n",
"@hola\n",
"def mundito(n):\n",
" return n+' y floreciente'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Instead `of hola(mundano)('cruel')` we can just use directly the new decorated function:"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'hola mundo cruel y despiadado'"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mundano('cruel')"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'hola mundo brillante y floreciente'"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mundito('brillante')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[[@]](https://realpython.com/primer-on-python-decorators/):\n",
"> Put simply: __decorators wrap a function, modifying its behavior.__"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00049-e128fdf5-6d40-4e6d-a8a2-25bd944de81c",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "tmc45kxUF_y4",
"tags": []
},
"source": [
"## Arithmetics"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00050-56a76643-a756-4bd2-946f-8dbd126ebf74",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "ozwFot0rF_y4",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Sum"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00051-74b45186-581d-46f3-be38-38b781b27e99",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "URMyrhmqF_y5",
"outputId": "6b38d80c-b3a3-481d-f835-94d65ac766b5"
},
"outputs": [
{
"data": {
"text/plain": [
"10.78"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"5.89+4.89"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00052-7b94f9d9-d4e1-4a12-a5b9-14142d764d39",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "0DNu3gWKdwIy"
},
"source": [
"**Activity**: Sum strings:\n",
"Hint: use `+' '+`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00053-04becf08-bc65-42cb-b09f-5d7896e58c9a",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "68e7G-PRd86Q"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00054-6e9b2fb1-ad02-44da-a1fc-78acf7f739ee",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "1dE0l0jyd9wJ"
},
"source": [
"**Activity**: Sum integers"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00055-358e4396-8a80-47d3-ac09-2f7596fd02ed",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "TAYYWZwveGfR"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00056-229969a9-1a88-4bfa-94eb-0315f479314a",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "AK5CSon3PDnW"
},
"source": [
"**Example**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00057-9868f3b3-c5f8-41b4-a512-2cb6379346f5",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "WI8fn1qdeWvG",
"outputId": "76fbecd4-37b0-4960-e6d8-7bf33fe03bf6"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hola Mundo!\n"
]
}
],
"source": [
"print(hello+' '+world+'!')"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00058-51897368-a994-44cc-bbac-d59edcaf405d",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "-fCXEiSsF_y8",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Multiplication"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00059-9fb7b1b4-9f96-40f2-b98b-70e101a3eb5c",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "vu7SzdLjF_y9",
"outputId": "563be8e8-08b2-4f5f-92a3-4bc0842e3bb7"
},
"outputs": [
{
"data": {
"text/plain": [
"540.0"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"120*4.5"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00060-da533ec0-10e7-4d04-ba30-cf5e014fe793",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "wC3Jfp4tPR2a"
},
"source": [
"**Example** String multiplied by integer:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00061-c262fd98-8a47-4c8a-85bd-583b5c2ffba5",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "U6X_16Bpelup",
"outputId": "f8017363-25b2-49c9-e222-1821da24ef29"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"================================================================================\n"
]
}
],
"source": [
"print('='*80)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00062-85e7cd59-82e0-4a8f-927e-8c4de20890bf",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "jtskAuqQF_zA",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Division"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00063-eaf6081c-d23e-41a3-b7b0-9b9fc661fa2c",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "QsCpsAd8F_zA",
"outputId": "7dded816-e2c9-4862-ba72-bec93846fc8c"
},
"outputs": [
{
"data": {
"text/plain": [
"33.333333333333336"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Python 3 does support complete division\n",
"100/3"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00064-04572ec2-eccf-49da-b738-3d5dfb1a641f",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "_4K2vuGqF_zD",
"outputId": "e2a3e187-4bea-4580-dd2d-1a8819bd4614"
},
"outputs": [
{
"data": {
"text/plain": [
"33.333333333333336"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"100/3."
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00065-b9748840-0fa4-4767-ae5f-9ae17ffd2ceb",
"deepnote_cell_type": "markdown"
},
"source": [
"Force integer division"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00066-418e827f-e17d-475a-ad48-8c1f159c63cf",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"33"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"100//3"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00067-a2553e7c-3180-49bd-ae9d-b91598376b9b",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "x7xHh9tjF_zJ",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Module"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00068-739595f2-6f11-4c01-8325-7937294b615f",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "R4a7H6dmF_zJ",
"outputId": "4fa12d47-806a-4b49-b521-32ec36986b4a"
},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 8,
"metadata": {
"tags": []
},
"output_type": "execute_result"
}
],
"source": [
"10%2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00069-8542809a-a3a8-4011-976f-cba20d0c8d2c",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "Z9ST9W04F_zM",
"outputId": "6fe779e1-46b9-4621-d99f-e570706c237b"
},
"outputs": [
{
"data": {
"text/plain": [
"2"
]
},
"execution_count": 9,
"metadata": {
"tags": []
},
"output_type": "execute_result"
}
],
"source": [
"20%3"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00070-8ad8abec-b278-45e3-b3a4-aafc43b797cf",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "2iWjCW7tF_zF",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Power"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00071-67f91ae1-5f80-47a8-9283-001b5c4ea750",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "ShgiDMOaF_zG",
"outputId": "8b2f08a8-c273-4e61-b81b-53dbbe0402fb"
},
"outputs": [
{
"data": {
"text/plain": [
"64"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"2**6"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00072-40ada915-f658-4795-8cdb-481dc6f2b7d7",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "8_EWbqIzF_zQ",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Scientific notation"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00073-6fb987c1-e3be-48c1-aa88-8642ff00bf3c",
"deepnote_cell_type": "markdown"
},
"source": [
"$1\\times 10^3=10^3=1000$"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00074-3150bb4a-fa4a-44b5-8950-948a88aed8a5",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"1000.0"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"1E3"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00075-004b6451-067c-4c99-8a72-c0dcd2f58abe",
"deepnote_cell_type": "markdown"
},
"source": [
"$2\\times 10^3=2000$"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00076-fcd6409c-7f6f-401c-8956-e8c1d42b9344",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"2000.0"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"2E3"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00077-75a926f3-b216-4e39-9895-8b62d2e07a49",
"deepnote_cell_type": "markdown"
},
"source": [
"$$\\frac{ \\dfrac{10^{24}}{3}+2.9\\times 10^{23}}{10^2}$$"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00078-3b709032-f2e1-4d3d-b08e-2458850c2ab2",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "1rf2SYTRF_zR",
"outputId": "3054b29a-fa77-4e7e-c0ca-584f52f55ea5"
},
"outputs": [
{
"data": {
"text/plain": [
"6.233333333333333e+25"
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(1.0e24/3. + 2.9e23)/1e-2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00079-829fc58e-d927-4e10-9ffe-acca3f536cbc",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 4,
"execution_start": 1626454198013,
"id": "K0H39NBm40Xz",
"source_hash": "1abb969e"
},
"outputs": [],
"source": [
"sin=0.3"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00080-29f9ddf2-f106-4b9e-af07-9a32efcbb972",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 15,
"execution_start": 1626454198619,
"source_hash": "662fdaec",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"isinstance(sin,float)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00080-cc0e2648-3bac-448d-befc-5f0a4e900a88",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 1,
"execution_start": 1626454747098,
"id": "vWOkR85240X2",
"source_hash": "b00e867f"
},
"outputs": [],
"source": [
"from math import *"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00082-99e102f2-5b26-479a-8cfc-0c7346f024b5",
"deepnote_cell_type": "markdown"
},
"source": [
"Keep the name space"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00083-70b46540-3ac9-4cf3-8270-e51d30c34423",
"deepnote_cell_type": "markdown"
},
"source": [
"Use `name.last_name`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00084-39000ce2-90d5-4536-969e-cb0a66d97e85",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 13,
"execution_start": 1626454762697,
"source_hash": "662fdaec"
},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"isinstance(sin,float)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00085-40c2fbb5-7a0e-4fac-b422-98b2d7bef868",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 15,
"execution_start": 1626454752505,
"source_hash": "2ceac8dc",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sin"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00085-4dd1c9e8-27bb-46c8-a193-9febc40c815b",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "yfYz0zLKNqA4"
},
"outputs": [],
"source": [
"import math as m\n",
"import cmath as cm\n",
"import numpy as np\n",
"#Recommended option:\n",
"import numpy.lib.scimath as sc"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00086-66781195-0577-4bcd-9717-cbbd5ef49e12",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"isinstance(sin,float)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00087-1507b2ca-4e3a-40b9-851f-370969c6ebcd",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"0.479425538604203"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"m.sin(0.5)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00088-01566e4d-82a9-4db8-8efa-40b4829006bb",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"(0.479425538604203+0j)"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cm.sin(0.5)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00089-859202c9-64eb-46c0-983f-a87880c0fb3c",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"0.479425538604203"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sin(0.5)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00090-c84c0fbe-64ce-4eab-8c36-e31213a5207b",
"deepnote_cell_type": "code"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/restrepo/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: DeprecationWarning: scipy.sin is deprecated and will be removed in SciPy 2.0.0, use numpy.sin instead\n",
" \"\"\"Entry point for launching an IPython kernel.\n"
]
},
{
"data": {
"text/plain": [
"0.479425538604203"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sp.sin(0.5)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00091-d49ebd94-56ff-4f1f-a968-52e4efe9dad3",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "rf3I0p_lnix5",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Complex numbers"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00092-b3263a70-7d32-4852-a5d6-7877f102554d",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"(-1+0j)"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"1j**2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00093-1a722771-b290-4e56-9e93-97420e2432e6",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "FV8LAGKJNqA7"
},
"outputs": [],
"source": [
"z=2+3.2j"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00094-3d02d79e-c217-43fd-a8f4-c03e9b6d89b7",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "pNOydNUO40YE",
"outputId": "ea96f74f-c1db-46ff-cb2d-85cf35b533ba"
},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"isinstance(z,complex)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00095-f5a5c7b6-4ad5-49c8-b8d4-730479bec16e",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "y9HbGaRenix8"
},
"source": [
"Attributes and methods:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00096-07b4ca2c-9701-4486-8424-bd8ec52a8c20",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "5nHDx7wLNqA9",
"outputId": "b0dded95-9e31-4a4c-e72e-d307a5aa8302"
},
"outputs": [
{
"data": {
"text/plain": [
"(2.0, 3.2, (2-3.2j))"
]
},
"execution_count": 4,
"metadata": {
"tags": []
},
"output_type": "execute_result"
}
],
"source": [
"z.real,z.imag,z.conjugate()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00097-d50da332-4aec-4410-a0db-cf58ae5caf27",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "WVfLo4mINqBA",
"outputId": "a45257c5-f1f6-4ca8-b32d-0e2f3c30bcf6"
},
"outputs": [
{
"data": {
"text/plain": [
"(8+12.8j)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"z+3*z"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00098-58b18cb4-21e6-48f4-9086-6fb8795770fa",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "cDLf56VpNqBE",
"outputId": "5b55beba-bf25-4a21-c30e-52079fece0c1"
},
"outputs": [
{
"data": {
"text/plain": [
"(-6.240000000000002+12.8j)"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"z*z"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00099-07cadcdf-0781-4f96-9efa-3c753e2fd6d5",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "TAZa5L1RNqBG",
"outputId": "263ad031-f5f7-418c-8e54-2f2f2f85c45e"
},
"outputs": [
{
"data": {
"text/plain": [
"(14.240000000000002+0j)"
]
},
"execution_count": 9,
"metadata": {
"tags": []
},
"output_type": "execute_result"
}
],
"source": [
"z*z.conjugate()"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00100-faa6110d-55de-40a1-86c8-56ce8aa5aa9d",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "markdown",
"id": "nK4EI5bH40YX"
},
"source": [
"`math` does not work with complex numbers"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00101-c9775239-ca6d-42ab-b7fa-7f9189334d40",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 165
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "sPxDr2BSNqBK",
"outputId": "cebcf098-0d46-465a-df9f-a963e77f1d49"
},
"outputs": [
{
"ename": "TypeError",
"evalue": "can't convert complex to float",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m0j\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m: can't convert complex to float"
]
}
],
"source": [
"m.asin(2+0j)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00102-cbbdaece-e706-4de6-98bd-8f43d8d35739",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "tb5p6SxcNqBO",
"outputId": "e403c20a-6804-4742-f39a-aa4b69e8a6bf"
},
"outputs": [
{
"data": {
"text/plain": [
"(1.5707963267948966+1.3169578969248166j)"
]
},
"execution_count": 163,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cm.asin(2)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00103-746e65d9-8d08-4878-b80f-087e11660d00",
"deepnote_cell_type": "markdown"
},
"source": [
"`numpy` requires proper input"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00104-7d842a7e-551f-4b86-8cda-aaf9002436d9",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 88
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "CrFG7Wkko2ry",
"outputId": "996a070c-952c-40e4-c269-aee42e33d081"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: RuntimeWarning: invalid value encountered in arcsin\n",
" \"\"\"Entry point for launching an IPython kernel.\n"
]
},
{
"data": {
"text/plain": [
"nan"
]
},
"execution_count": 164,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.arcsin(2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00105-068cb2e2-67f6-4789-8aa9-8df6cb73f631",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "kzkODWkAsUGH",
"outputId": "27e7fc7c-0357-4d7d-d563-8d91a58bb635"
},
"outputs": [
{
"data": {
"text/plain": [
"(1.5707963267948966+1.3169578969248166j)"
]
},
"execution_count": 165,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.arcsin(2+0j)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00106-6259c1ee-9808-4b0a-ac5d-28c2a35c0c03",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "1CCDk_m0sSH5"
},
"source": [
"`numpy.lib.scimath` imported as `sc` here, is from `sc?`:\n",
"> Wrapper functions to more user-friendly calling of certain math functions\n",
"whose output data-type is different than the input data-type in certain\n",
"domains of the input.\n",
"Function with some parts of its domain in the complex plane like, `sqrt`, `log`, `log2`, `logn`, `log10`, `power`, `arccos`, `arcsin`, and `arctanh`."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00107-d4582586-7946-48c2-b2a1-4e57643deb70",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "ujaLOBc440Yt",
"outputId": "80539b82-7078-4546-c0c7-a01912040bf5"
},
"outputs": [
{
"data": {
"text/plain": [
"(1.5707963267948966+1.3169578969248166j)"
]
},
"execution_count": 166,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.lib.scimath.arcsin(2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00108-21fe7bc7-b62e-419e-8f4a-77c5fcb3eeef",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"(1.5707963267948966+1.3169578969248166j)"
]
},
"execution_count": 167,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sc.arcsin(2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00109-fa35b372-96f9-4949-acbd-3e1dd8b97d6e",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "148M2gp0ul3b"
},
"outputs": [],
"source": [
"import ipywidgets as widgets"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00110-28966f91-cbf3-4e57-9037-3909018ee925",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "OgpSHexV40Y0",
"outputId": "1c74eef5-72ef-43ba-8ba4-7e1a800f6f11",
"tags": [
"interactive"
]
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "c7649e6b09e544169692a5bd523dd0d2",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"interactive(children=(IntSlider(value=1, description='x', max=2), Output()), _dom_classes=('widget-interact',)…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"@widgets.interact\n",
"def f(x=(0,2)):\n",
" print(np.abs(sc.arcsin(x)))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00111-65b42516-574d-47e8-98f2-bb422c3e958a",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 88
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "3tptBZcLNqBT",
"outputId": "4e266e8e-f43c-4c0a-cb2a-bbcce4cb402b"
},
"outputs": [
{
"data": {
"text/plain": [
"array([1.57079633+1.3169579j , 1.57079633+1.76274717j])"
]
},
"execution_count": 170,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sc.arcsin([2,3])"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00112-16b90e2f-1770-4f84-b1fd-e1197c7da6ac",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "WNGKkoW4F_zT",
"tags": []
},
"source": [
"## Lists, Tuples, Dictionaries and Sets"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00113-6ca5b993-d2b8-48df-95e5-92e102a819fc",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "ACaVyEIMF_zU",
"tags": []
},
"source": [
"### Lists"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00114-8627121b-1169-43dc-8a80-c2b50bc7bc23",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "8bU3iP8xF_zV"
},
"source": [
"Lists are useful when you want to store and manipulate a set of elements (even of different types)."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"cell_id": "00115-43993951-a96b-45f5-9aa6-218250de2875",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 19,
"execution_start": 1627053894891,
"id": "xWUtR9EUF_zW",
"outputId": "6526a6f3-1b28-4e2b-e5e4-2b3e346bc37e",
"source_hash": "f35af975"
},
"outputs": [
{
"data": {
"text/plain": [
"['abc', 42, 3.1415]"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#A list is declared using [] and may content different type of objects\n",
"lista = [\"abc\", 42, 3.1415]\n",
"lista"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"cell_id": "00116-f1ac2a71-cd80-4bdf-b55a-36c96d210522",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 12,
"execution_start": 1627053528338,
"id": "HF_XL0MWF_zY",
"outputId": "3117d2de-db39-4d86-ef4a-e7613bb78ac0",
"source_hash": "a16ca4d8"
},
"outputs": [
{
"data": {
"text/plain": [
"'abc'"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#First element of the list\n",
"lista[0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00117-9bee40ba-69b5-45ad-ac99-ded3cebca55a",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 58,
"execution_start": 1627053562906,
"id": "wAPJeJnIF_za",
"outputId": "f173775f-6eec-41b0-e8ad-9b14d218ad61",
"source_hash": "b4dd55f4"
},
"outputs": [
{
"data": {
"text/plain": [
"3.1415"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Last element of the list\n",
"lista[-1]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"cell_id": "00119-4ee37b8f-4184-4968-9344-ce71d1e7bc47",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 18,
"execution_start": 1627053898484,
"id": "Nl-dVEMRF_zc",
"outputId": "8a371e78-9b6b-41b5-9060-74808cf7cac5",
"source_hash": "3d493445"
},
"outputs": [
{
"data": {
"text/plain": [
"['abc', 42, 3.1415, True]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Adding a new element (boolean element)\n",
"lista.append(True)\n",
"lista"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00120-a12d4510-740e-497c-b699-ffd41b801f67",
"deepnote_cell_type": "markdown",
"tags": []
},
"source": [
"WARNING:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"newlista=lista"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"newlista.append('algo')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['abc', 42, 3.1415, True, 'algo']"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"newlista"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['abc', 42, 3.1415, True, 'algo']"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lista"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"cell_id": "00120-d1e762c2-34ba-43de-807e-59500bcab8ef",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 14,
"execution_start": 1627053918373,
"source_hash": "b1a5bc03",
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['abc', 42, 3.1415, True, 'algo', 5]\n"
]
}
],
"source": [
"newlista=lista.copy()\n",
"newlista.append(5)\n",
"print(newlista)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\u001b[0;31mSignature:\u001b[0m \u001b[0mlista\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mDocstring:\u001b[0m Return a shallow copy of the list.\n",
"\u001b[0;31mType:\u001b[0m builtin_function_or_method\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"lista.copy?"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"import copy"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['abc', 42, 3.1415, True, 'algo']"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"copy.copy(lista)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['abc', 42, 3.1415, True, 'algo']"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"copy.deepcopy(lista)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['abc', 42, 3.1415, True, 'algo']"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lista"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"cell_id": "00120-b066d01c-cfd2-4b88-b396-acaa67bae085",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 13,
"execution_start": 1627053977167,
"id": "SevBLsrgF_ze",
"outputId": "70424d0e-4239-4a2a-f653-ee168140e1c2",
"source_hash": "9186f96e"
},
"outputs": [
{
"data": {
"text/plain": [
"['abc', 'I am second', 42, 3.1415, True, 'algo']"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Inserting a new second element \n",
"lista.insert(1, \"I am second\")\n",
"lista"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"cell_id": "00121-8b9c757b-9fb4-4610-b94e-ac2f7ae4e869",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1627054016142,
"id": "nSHDnC2AF_zg",
"outputId": "0116348f-b350-4c54-a5e5-ff02641c31e6",
"source_hash": "8aee6b76"
},
"outputs": [
{
"data": {
"text/plain": [
"['abc', 'I am second', 42, True, 'algo']"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Deleting the third element of the list\n",
"del lista[3]\n",
"lista"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"cell_id": "00122-ffe7df5c-b2da-45ce-bb94-f432ea290b6d",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 39,
"execution_start": 1627054037210,
"id": "vlX6FjRkF_zj",
"outputId": "79a878cc-ee51-43b0-f668-712c487dd005",
"source_hash": "b6a109d0"
},
"outputs": [
{
"data": {
"text/plain": [
"['xyz', 'I am second', 42, True, 'algo']"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Reassign the first element of the list\n",
"lista[0] = \"xyz\"\n",
"lista"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00123-57f91b00-6a13-4568-a840-c95e04b50c68",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "pfNBq-Bj40ZQ",
"tags": []
},
"source": [
"#### Slicing: \n",
"Extract elements from a list, `l` from one given index to another given index. We pass slice instead of index like this: \n",
"```python3\n",
"l[start:end]\n",
"```\n",
"We can also define the step, like this: \n",
"```python3\n",
"l[start:end:step]\n",
"```\n",
"If `start` is not passed it is considered 0. If `end` is not passed it is considered length of array in that dimension. The `end` can given in reverse order by assigning a minus signus to the index. For example `-1` means the last element, while `-2` means the penultimate, and so on and so forth."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"cell_id": "00124-4673fb4b-69a6-44c5-b553-b29ecda18ed3",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 9,
"execution_start": 1627054210718,
"id": "rCgwPFIgF_zl",
"outputId": "81c27ad4-596f-41de-af83-73d69871889d",
"source_hash": "5d30bd51"
},
"outputs": [
{
"data": {
"text/plain": [
"['xyz', 'I am second', 42]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Showing the elements from 0 to 2\n",
"lista[0:3]"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['xyz', 'I am second', 42]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lista[:3]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"cell_id": "00125-f058494c-bb47-4974-93c6-7cb70b3650c3",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 25,
"execution_start": 1627054240750,
"id": "7EnY5Z_A40ZT",
"outputId": "58fe6bbe-5014-4c96-8d55-0ccb52aad24b",
"source_hash": "d90acb3b"
},
"outputs": [
{
"data": {
"text/plain": [
"[True, 'algo']"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Showing the last two elements\n",
"lista[-2:]"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"cell_id": "00126-2c6edb8f-e21a-4c78-bbf8-911ef5d1be11",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1627054255404,
"id": "hFTEHeueF_zn",
"outputId": "8abb0632-4243-4422-8a86-2df841e0a81e",
"source_hash": "8f046dad"
},
"outputs": [
{
"data": {
"text/plain": [
"['xyz', 42, 'algo']"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Showing elements two by two\n",
"lista[::2]"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"cell_id": "00127-088529a1-cdd2-4f2c-a55f-97c24a554d43",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 57,
"execution_start": 1627054269516,
"id": "AmtfO6SE40Zb",
"outputId": "ab306330-6683-401a-d637-ab84747d0b96",
"source_hash": "9349264f"
},
"outputs": [
{
"data": {
"text/plain": [
"['algo', True, 42, 'I am second', 'xyz']"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Reverse order\n",
"newlista=lista[::-1]\n",
"newlista"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"cell_id": "00128-f3e96f1b-30fb-4dc6-8cf5-10f8c0a3bdac",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 14,
"execution_start": 1627054333990,
"source_hash": "8a17b22b"
},
"outputs": [
{
"data": {
"text/plain": [
"['xyz', 'I am second', 42, True, 'algo']"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lista"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"cell_id": "00129-d0c2f7e2-f0b2-492e-9204-dc38f3b0c8d7",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1627054348910,
"id": "JtdcF2L540Ze",
"outputId": "63ec49e9-57e7-47e7-96fe-81373736226e",
"source_hash": "871441e4"
},
"outputs": [
{
"data": {
"text/plain": [
"['algo', True, 42, 'I am second', 'xyz']"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#also as\n",
"lista.reverse()\n",
"lista"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['algo', True, 42, 'I am second', 'xyz']"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(reversed(lista))"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['xyz', 'I am second', 42, True, 'algo']"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lista"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00130-1315bac9-04c4-4e12-bd71-e54c9c188e09",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "-nwqd5OH40Zh",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"#### Embedded lists"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"cell_id": "00131-aaab6b1e-dcd6-448d-9c9c-c58f8a2df353",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1627054580810,
"id": "FZOAGZujF_zp",
"outputId": "fd8d4e2d-ca8d-4779-8a48-a8a9b7acf435",
"source_hash": "a0121d4d"
},
"outputs": [
{
"data": {
"text/plain": [
"[['xyz', 'I am second', 42, True, 'algo'], [True, 42]]"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#It is possible to embed a list within another\n",
"embedded_list = [lista, [True, 42]]\n",
"embedded_list"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"cell_id": "00132-57f0bd10-d081-42bd-992b-712686faa210",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 12,
"execution_start": 1627054613548,
"id": "jYQgFdOYF_zr",
"outputId": "8bb6ca52-7c21-4b9e-b2de-30005c8420ca",
"source_hash": "693c0cdf"
},
"outputs": [
{
"data": {
"text/plain": [
"'I am second'"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Second element of the first list\n",
"embedded_list[0][1]"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"cell_id": "00133-9df3b1ce-f6c3-4be5-b737-949607db44c0",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 14,
"execution_start": 1627055234675,
"id": "uyw-E8VoF_zt",
"outputId": "12473d6c-92e8-491f-a61a-31edcf459253",
"source_hash": "d11f70fc"
},
"outputs": [
{
"data": {
"text/plain": [
"[[1, 2], [3, 4]]"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#A matrix as a list of embedded lists\n",
"A = [ [1,2], [3,4] ]\n",
"A"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00134-e1d5ee2c-0fe9-46c2-85ce-0762e05611bc",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "BYpSrRqlgX6j"
},
"source": [
"**Activity**: Obtain entry $A_{01}$ of the previous matrix, where\n",
"$$\n",
"A=\\begin{pmatrix}\n",
"A_{00} & A_{01}\\\\\n",
"A_{10} & A_{11}\\\\\n",
"\\end{pmatrix}\n",
"$$"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"cell_id": "00135-f5b3c211-9abc-4c21-8806-2f1c4a1e2b14",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 0,
"execution_start": 1627060206310,
"id": "jisAwrcf40Zq",
"source_hash": "b623e53d"
},
"outputs": [
{
"data": {
"text/plain": [
"2"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"A[0][1]"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00136-243850cf-39b5-4c5d-842f-72e235c72269",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "xou55DH140Zs",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"#### Sum of lists"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"cell_id": "00137-d0e5120c-94d6-40e3-8979-a9bdb0bf0794",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "DDYA-n0pF_zv",
"outputId": "6c19cc81-1d0c-46df-ffdc-666d29e1cd30"
},
"outputs": [
{
"data": {
"text/plain": [
"[1, 2, 'ab', True, [1, 2], 3.1415, 'Pi', 'circle']"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#When two list are added, the result is a new concatenated list\n",
"[1,2,\"ab\",True,[1,2]] + [3.1415,\"Pi\",\"circle\"]"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00138-dc6980e6-fb8f-4a83-b98f-9bc41e9fa01d",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "mnXJphqAhSpu"
},
"source": [
"**Activity** Add a third row with integer values to the previous $A$ matrix\n",
""
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {
"cell_id": "00139-5b796ccf-fa09-400b-91e8-ef347d747586",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 0,
"execution_start": 1627060219998,
"id": "cDjXm_LthoWk",
"outputId": "f1bc862b-bf33-4699-b349-a52c94424248",
"source_hash": "b623e53d"
},
"outputs": [],
"source": [
"A.insert(1,[7,8])"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[1, 2], [7, 8], [3, 4], [7, 8]]"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"A"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00140-ede7d349-571e-42fe-b4f5-0963810a6e95",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "7QgsQSv2F_zy"
},
"source": [
"An additional ingredient is the `append` method of a Python list. It update the elements of the list without update explicitly the variable with some equal reasignment."
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"cell_id": "00141-cd443c5b-58be-4308-8fd1-7c9c87b2ba35",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 52
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 1,
"execution_start": 1627055372390,
"id": "ZxLgIuS7F_zy",
"outputId": "2d347140-f163-46ea-d925-1989cbb6f033",
"source_hash": "a8e6b8c3"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"after append 2 to [] : [2]\n",
"after append 5 to [2]: [2, 5]\n"
]
}
],
"source": [
"y=[]\n",
"y.append(2)\n",
"print(f'after append 2 to [] : {y}')\n",
"y.append(5)\n",
"print(f'after append 5 to [2]: {y}')"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00144-953af19d-ca28-4a4e-bee2-d74b5a2ed2bc",
"deepnote_cell_type": "markdown",
"tags": []
},
"source": [
"functions to generate lists:\n",
"* `range`\n"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"cell_id": "00145-0c5d3016-156c-451f-932f-8f9f85498c7c",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 16,
"execution_start": 1627055526138,
"source_hash": "f94a8b9f",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"[0, 1, 2]"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(range(3))"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00146-849cc4fe-5da8-4d42-90c7-a9af3c9a6bf3",
"deepnote_cell_type": "markdown",
"tags": []
},
"source": [
"Conditional in lists:\n",
"* `in`\n",
"* `any`\n",
"* `all`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00147-8be3f9a4-90f7-4d7d-8f26-0d2ed226b968",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 37,
"execution_start": 1627060569158,
"source_hash": "fffd76d",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"3 in [4,5,6]"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[7,8] in [4,5,6,[7,8]] "
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {
"cell_id": "00148-c0099d37-13a9-4cd4-956f-615e5ec21d29",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 30,
"execution_start": 1627061227281,
"source_hash": "f97063ef",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"any([False,False,False])"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"cell_id": "00149-722ef06e-9a14-499f-b6a5-0327a0f3b25f",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 27,
"execution_start": 1627061259749,
"source_hash": "95cdbf30",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"any([False,False,True])"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {
"cell_id": "00150-457d1a36-ff2e-4536-9ed8-93f5a576d699",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 42,
"execution_start": 1627061327173,
"source_hash": "53e77c51",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 59,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"all([False,False,True])"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {
"cell_id": "00151-c4913ce3-2f69-403f-bfcb-ae8ad7b6bcdb",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 83,
"execution_start": 1627061347380,
"source_hash": "2b9de73e",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"all([True,True,True])"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00142-f1e3f95e-52a8-4546-9dfb-e628aee03dad",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "n5PCnFO3F_z1"
},
"source": [
"#### List Comprehension"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00143-cd725699-69ce-4b14-9331-fc3e1b984d0e",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "mels66d2F_z2"
},
"source": [
"Taken from [here](https://docs.python.org/3/tutorial/datastructures.html#list-comprehensions): List comprehensions provide a concise way to create lists. Common applications are to make new lists where each element is the result of some operations applied to each member of another sequence or iterable, or to create a subsequence of those elements that satisfy a certain condition."
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[2, 4, 6, 8]"
]
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[x for x in range(2,10,2)]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00144-d03421d8-09dd-4c54-95fc-ff2e296eb5d3",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 12,
"execution_start": 1627055611742,
"id": "o0BpeNa0F_z3",
"outputId": "0e0430f6-1453-4001-c042-0d0af3ebece2",
"source_hash": "53b8c8a9"
},
"outputs": [
{
"data": {
"text/plain": [
"[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[x**2 for x in range(10)]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00149-1607ced4-e77c-40b9-b275-24353bfaf291",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 11,
"execution_start": 1627056290818,
"source_hash": "b593dd3d",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"[4, 16, 36, 64]"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[x**2 for x in range(2,10,2)]"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {
"cell_id": "00145-27cc9103-afe6-4897-ab89-e7e1d0f34741",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 21,
"execution_start": 1627055632524,
"id": "AQW_kdviF_z5",
"outputId": "893ef954-32f9-4822-ccce-55fafdb21f8d",
"source_hash": "ffd3f664"
},
"outputs": [
{
"data": {
"text/plain": [
"[[1, 3], [1, 4], [2, 3], [2, 1], [2, 4], [3, 1], [3, 4]]"
]
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[[x, y] for x in [1,2,3] for y in [3,1,4] if x != y]"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[1, 2], [1, 3], [2, 1], [2, 3], [3, 1], [3, 2]]"
]
},
"execution_count": 65,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[[x, y] for x in [1,2,3] for y in [1,2,3] if x != y]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"__Activity__: Tuplas con pares diferentes sólo"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {
"cell_id": "00146-be9ef7b8-23ce-4681-94cb-53e349445bb7",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 6,
"execution_start": 1627055660948,
"id": "2Zl1DwNy40Z7",
"source_hash": "2b33c16d"
},
"outputs": [],
"source": [
"l=[ ['A','B','C'],['D','E','F'],['G','H','I'] ]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"_¡Filtered lists!_:"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00147-e91196c0-77fc-4b30-a17c-9617e71f5937",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "MMPgcuo_40Z-"
},
"source": [
"we can extract the list that contains `'H'`"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {
"cell_id": "00153-0cf5909e-7024-4676-a97b-770f9e396b18",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 14,
"execution_start": 1627055872147,
"source_hash": "8e79fb42",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"[['G', 'H', 'I']]"
]
},
"execution_count": 69,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[ll for ll in l if 'H' in ll]"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {
"cell_id": "00154-b8a38b7b-ceca-4e7b-9251-b920e7ba902c",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1627055957594,
"source_hash": "7a5cfca9",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"'H' in l"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00154-592b9433-ca61-4ddc-b70d-23fab88c4d11",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 14,
"execution_start": 1627055938471,
"source_hash": "c3ba2c1d",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"['G','H','I'] in l"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00149-ba2b3d50-e292-42a0-b183-849aad668e48",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "J0-SP0qP40aB"
},
"source": [
"#### Reversed comprehension\n",
"We can use the method `reversed(...)` to generate an iterator with the revesersed list so that the original list is kept."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00150-a8e26da0-94cf-4991-8a4a-f7ed1dd218d2",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 15,
"execution_start": 1627056013024,
"source_hash": "8a17b22b"
},
"outputs": [
{
"data": {
"text/plain": [
"['xyz', 'I am second', 42, True]"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lista"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {
"cell_id": "00151-c5f30d41-9775-4dbb-a741-bd2947f8f444",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 52
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 0,
"execution_start": 1627056026414,
"id": "1XNRSTG040aF",
"outputId": "9b66acdf-9bb9-48e7-9fbc-4ed653e4afbd",
"source_hash": "ec1b4107"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"reversed: ['algo', True, 42, 'I am second', 'xyz']\n",
"original: ['xyz', 'I am second', 42, True, 'algo']\n"
]
}
],
"source": [
"print('reversed: {}'.format( list(reversed(lista)) ))\n",
"print('original: {}'.format(lista))"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00153-98fee61f-e155-45ea-ae9a-59845ba49a0a",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "txgjCoaIF_z7",
"tags": []
},
"source": [
"### Tuples"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00154-5a0084bd-f33e-47e1-a5a1-3e513e36368a",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "OtJzxOFtF_z8"
},
"source": [
"A tuple is almost equal to a list, except that once declared its elements, it is not possible to modify them. Therefore, tuples are useful only when you want to store some elements but not modify them."
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {
"cell_id": "00155-256f5c89-6a1b-474d-91c2-982e7bb4f433",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "f3skilG2F_z8",
"outputId": "1b1ba135-88ba-4bbd-a489-29b6458a45f7"
},
"outputs": [
{
"data": {
"text/plain": [
"('abc', 42, 3.1415)"
]
},
"execution_count": 72,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#A tuple is declared using ()\n",
"tupla = (\"abc\", 42, 3.1415)\n",
"tupla"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00156-44f08913-fa8d-45ad-b1b7-29bfec4bcdd6",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "uhv7dS2Q-2uh"
},
"source": [
"Note: single element tuple"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {
"cell_id": "00157-0bf093c5-fcd7-4037-bebf-e6da8d4a84c6",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 1,
"execution_start": 1627056061261,
"source_hash": "36ea1d96"
},
"outputs": [
{
"data": {
"text/plain": [
"2"
]
},
"execution_count": 73,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(2) #equivalent to 2"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {
"cell_id": "00158-e728a1f9-7751-45e2-8143-436b36f676b8",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 4,
"execution_start": 1627056074298,
"id": "gZlzseaI-8Xm",
"source_hash": "fc89a494"
},
"outputs": [],
"source": [
"t=(2,)"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {
"cell_id": "00159-ad542ff7-19c9-4aff-99a3-baac96e5ecb1",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "Fu11CK1L_TYA",
"outputId": "d691f670-c11c-4882-9a1b-143b48853075"
},
"outputs": [
{
"data": {
"text/plain": [
"1"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(t)"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {
"cell_id": "00160-b811c8ab-f84a-46b9-bc19-fb607985fbfc",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 166
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 18,
"execution_start": 1627056079374,
"id": "slJ7Lrfh_XAb",
"outputId": "17090d2e-f4c0-43ac-e1fd-ddf02e26df1c",
"source_hash": "5a4849fa"
},
"outputs": [
{
"data": {
"text/plain": [
"2"
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t[0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For creating an empty tuple\n",
"```\n",
"(,)\n",
"```\n",
"or creating the instance of the class `tuple`"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [],
"source": [
"t=tuple()"
]
},
{
"cell_type": "code",
"execution_count": 81,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"()"
]
},
"execution_count": 81,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00161-3f420b93-2467-4cd1-a97b-15b274dcc657",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "x3M6C67140aW"
},
"source": [
"The comprenhension tuple also works"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00162-a415fe35-389c-414c-a715-b680e65d3f41",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "PYlzClDB40aX",
"outputId": "c10f27e1-fb96-4760-9ab9-0eafcdb55a03"
},
"outputs": [
{
"data": {
"text/plain": [
"('abc', 42, 3.1415)"
]
},
"execution_count": 71,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tuple( (t for t in tupla) )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00172-928ae2c5-c92b-4ec5-b7ff-d3c8195dc2f9",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "uAiixodKF_z-",
"outputId": "4e199236-94c9-486f-a792-956923d3f6d5"
},
"outputs": [
{
"ename": "AttributeError",
"evalue": "'tuple' object has no attribute 'append'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#It is not possible to add more elements\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mtupla\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"xy\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m: 'tuple' object has no attribute 'append'"
]
}
],
"source": [
"#It is not possible to add more elements\n",
"tupla.append(\"xy\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00173-b004a635-74e6-4739-88a8-ffab9d845090",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "GiY-kyfHF_0A",
"outputId": "76c602ca-e8f6-4608-fd5a-dff8cfdaf7a4"
},
"outputs": [
{
"ename": "TypeError",
"evalue": "'tuple' object doesn't support item deletion",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#It is not possible to delete an element\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mdel\u001b[0m \u001b[0mtupla\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m: 'tuple' object doesn't support item deletion"
]
}
],
"source": [
"#It is not possible to delete an element\n",
"del tupla[0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00174-30f10522-e562-422a-af00-376cce233822",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "jwJPysSkF_0D",
"outputId": "f99022e1-245d-4534-fa4f-b4584786e768"
},
"outputs": [
{
"ename": "TypeError",
"evalue": "'tuple' object does not support item assignment",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#It is not possible to modify an existing element\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mtupla\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"xy\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
]
}
],
"source": [
"#It is not possible to modify an existing element\n",
"tupla[0] = \"xy\""
]
},
{
"cell_type": "markdown",
"metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"#### Some list functions"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00163-6ec69b7f-7fc2-451e-9672-7a13487adb97",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "gh7KXCGH40aa"
},
"source": [
"`any` can extract a true value from a comprension tuple (see also `all`: https://docs.python.org/3/library/functions.html#all). \n",
"In fact, for the following nested list:"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {
"cell_id": "00164-358dc760-b8e8-4585-bfcd-93d6241b7144",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "gM2YlwEF40aa"
},
"outputs": [],
"source": [
"l=[ ['A','B','C'],['D','E','F'],['G','H','I'] ]"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00165-7820b06a-4910-4efd-90d2-37e9738bbef6",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "-3ZrGX6K40ac"
},
"source": [
"we can extract the list that contains `'H'` more easily"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {
"cell_id": "00166-1f463c7a-074e-42be-ae04-2d4f44be198d",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"[['A', 'B', 'C'], ['D', 'E', 'F'], ['G', 'H', 'I']]"
]
},
"execution_count": 83,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[ll for ll in l]"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {
"cell_id": "00167-0a3f82b7-bcab-4f03-ae92-8a3f1a450853",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 84,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"any((s=='L' for s in ['G', 'H', 'I']))"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {
"cell_id": "00168-14ee9a7d-a062-410d-b932-0eab109beac8",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "_ltlDGMz40ad",
"outputId": "44950aec-0c22-4bf9-c442-9f22dfc3ec6a"
},
"outputs": [
{
"data": {
"text/plain": [
"[['G', 'H', 'I']]"
]
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[ll for ll in l if any( s=='H' for s in ll ) ]"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00169-803fda79-7313-4eaa-b867-b4748e3bb3b1",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "J9rPXb0a40ag"
},
"source": [
"With the function `zip` we can generate dictionary-like tuple from two lists:"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {
"cell_id": "00170-3a093a73-05f4-40ee-82b8-8bc36637618b",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "13619Vve_qNE",
"outputId": "ce6b81b4-c6e0-4a88-ef7b-f383e55d730a"
},
"outputs": [
{
"data": {
"text/plain": [
"[('A', 1), ('B', 2), ('C', 3)]"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(zip( ['A','B','C'],[1,2,3] ))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00171-0474af69-315e-402d-8775-19f56274b0ef",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "qVT1k-en40ag",
"outputId": "96f56944-57cc-471c-c16f-857aa41e2377"
},
"outputs": [
{
"data": {
"text/plain": [
"[('A', 1), ('B', 2), ('C', 3)]"
]
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(zip( ['A','B','C'],[1,2,3] ))"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00175-acb86315-216f-43fd-b3f1-6b1d62f8e1ee",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "rafwug2SF_0F",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Dictionaries"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00176-0dee92e2-0919-4509-ab7b-8c4ae026afe2",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "7vlLjdVRF_0G"
},
"source": [
"Dictionaries are labeled lists: with keys and values. They are extremely useful when manipulating complex data. In Wolfram Alpha the equivalent object is called [Associations](https://reference.wolfram.com/language/guide/Associations.html)"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {
"cell_id": "00177-2aad3f22-aeba-4264-9e09-82f40f9a9052",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 55
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1628262626619,
"id": "vUXMEigkF_0G",
"outputId": "c806d219-32bd-40f9-bbc6-16102e4514ef",
"source_hash": "7abfe7bf"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'Kenia': 'Nairobi', 'Noruega': 'Oslo', 'Finlandia': 'Helsinski', 'Rusia': 'Moscú', 'Rio de Janeiro': 'Rio', 'Japón': 'Tokio', 'Colorado': 'Denver', 'Alemania': 'Berlin', 'Colombia': 'Bogotá'}\n"
]
}
],
"source": [
"#A dictionary is declared using {}, and specifying the name of the component, then the character : followed by the element to store.\n",
"dictionary={ 'Kenia' :'Nairobi',\n",
" 'Noruega' :'Oslo',\n",
" 'Finlandia' :'Helsinski',\n",
" 'Rusia' :'Moscú',\n",
" 'Rio de Janeiro':'Rio',\n",
" 'Japón' :'Tokio',\n",
" 'Colorado' :'Denver',\n",
" 'Alemania' :'Berlin',\n",
" 'Colombia' :'Bogotá'}\n",
"print(dictionary)\n",
"#Note the order in a dictionary does not matter as one identifies a single element through a string, not a number"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00178-f0530215-2bee-40ff-b000-f658b73c3fa9",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "IWoHFWTx40av"
},
"source": [
"Instead of a number, an element of a dictionary is accessed with the key of the component"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {
"cell_id": "00179-cf329bd3-ad70-480b-bbad-53f885000c47",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 17,
"execution_start": 1628262629960,
"source_hash": "1dd6b4f7"
},
"outputs": [
{
"data": {
"text/plain": [
"{'Kenia': 'Nairobi',\n",
" 'Noruega': 'Oslo',\n",
" 'Finlandia': 'Helsinski',\n",
" 'Rusia': 'Moscú',\n",
" 'Rio de Janeiro': 'Rio',\n",
" 'Japón': 'Tokio',\n",
" 'Colorado': 'Denver',\n",
" 'Alemania': 'Berlin',\n",
" 'Colombia': 'Bogotá'}"
]
},
"execution_count": 88,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dictionary"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {
"cell_id": "00180-03d84b01-c18b-4ff8-ba65-fab7292576b3",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "bVHKdCigF_0K",
"outputId": "0cd39b16-fb1d-4a41-d079-ea099257efb8"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tokio ♥ Rio\n"
]
}
],
"source": [
"print('{} ♥ {}'.format( dictionary['Japón'], dictionary['Rio de Janeiro']) )"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {
"cell_id": "00181-721e1c8d-559d-4dec-9f51-16f1b699838c",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 54,
"execution_start": 1628262732927,
"id": "QK-1FnAnF_0M",
"outputId": "da43655e-b6f8-4740-e3cc-c0cb430fd4e6",
"source_hash": "e6b0b2a6"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Azul\n"
]
}
],
"source": [
"#The elements of the dictionary may be of any type\n",
"dictionary2 = { \"Enteros\":[1,2,3,4,5], \n",
" \"Ciudad\" :\"Medellin\", \n",
" \"Cédula\" :1128400433, \n",
" \"Colores\":[\"Amarillo\", \"Azul\", \"Rojo\"] }\n",
"print(dictionary2[\"Colores\"][1])"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {
"cell_id": "00182-b05c88f3-8661-4d19-8786-4b6480f96ffb",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_start": 1628262776687,
"id": "j5epa2zcF_05",
"outputId": "49dc833e-cff1-4990-c933-250c75072679",
"source_hash": "7b0dd9f0"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'Enteros': [1, 2, 3, 4, 5], 'Ciudad': 'Bogota', 'Cédula': 1128400433, 'Colores': ['Amarillo', 'Azul', 'Rojo']}\n"
]
}
],
"source": [
"#The elements of the dictionary can be modified only by changing directly such an element\n",
"dictionary2[\"Ciudad\"] = \"Bogota\"\n",
"print(dictionary2)"
]
},
{
"cell_type": "code",
"execution_count": 92,
"metadata": {
"cell_id": "00183-98bdbade-02ef-4c96-9274-7cdf846e87a9",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 55
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 0,
"execution_start": 1628262810808,
"id": "fTtrGPXsF_08",
"outputId": "b4eb22a4-2f18-4761-aafa-2b90be7e8041",
"source_hash": "bb0e866d"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'Enteros': [1, 2, 3, 4, 5], 'Ciudad': 'Bogota', 'Cédula': 1128400433, 'Colores': ['Amarillo', 'Azul', 'Rojo'], 'Pais': 'Colombia', 'País': 'Chile'}\n"
]
}
],
"source": [
"#Adding a new element is possible by only defining the new component\n",
"dictionary2[\"Pais\"] = \"Colombia\"\n",
"dictionary2[\"País\"] = \"Chile\"\n",
"print( dictionary2 )"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {
"cell_id": "00184-4935b754-28ed-45b9-bfbf-4d87d820ddd9",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "qhMqpewqkxaF"
},
"outputs": [],
"source": [
"dictionary2.update({'Continente':'América'})"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'Enteros': [1, 2, 3, 4, 5],\n",
" 'Ciudad': 'Bogota',\n",
" 'Cédula': 1128400433,\n",
" 'Colores': ['Amarillo', 'Azul', 'Rojo'],\n",
" 'Pais': 'Colombia',\n",
" 'País': 'Chile',\n",
" 'Continente': 'América'}"
]
},
"execution_count": 95,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dictionary2"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00198-08eff87f-6fa8-44b6-be20-20e993a3bb7e",
"deepnote_cell_type": "markdown",
"tags": []
},
"source": [
"List-like dictionary"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {
"cell_id": "00199-79ff680b-ea8f-4894-903f-1e662b463163",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 13,
"execution_start": 1628262965489,
"source_hash": "63b2cce9",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"45"
]
},
"execution_count": 106,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"l={0:45,1:345,2:987}\n",
"l[0]"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {
"cell_id": "00200-12fd4aac-1894-4ddb-a7fc-4df171c6deef",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 5,
"execution_start": 1628263125325,
"source_hash": "b7fc3f07",
"tags": []
},
"outputs": [],
"source": [
"l={0.3:45}"
]
},
{
"cell_type": "code",
"execution_count": 103,
"metadata": {
"cell_id": "00201-7e3b1869-8cd3-4be6-b7b4-c660839ad1ac",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 13,
"execution_start": 1628263144179,
"source_hash": "662f52b",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"45"
]
},
"execution_count": 103,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"l[0.3]"
]
},
{
"cell_type": "code",
"execution_count": 109,
"metadata": {},
"outputs": [],
"source": [
"l={0:45,1:345,2:987}\n",
"l[3]=2022"
]
},
{
"cell_type": "code",
"execution_count": 110,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{0: 45, 1: 345, 2: 987, 3: 2022}"
]
},
"execution_count": 110,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"l"
]
},
{
"cell_type": "code",
"execution_count": 111,
"metadata": {
"cell_id": "00202-43aafd17-e1b3-4041-968f-5c5aac384a40",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 14,
"execution_start": 1628263189146,
"source_hash": "7217c2d4",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"'Verdadero'"
]
},
"execution_count": 111,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"d={True:'Verdadero'}\n",
"d[True]"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"cell_id": "00185-dd7f8b7a-a84c-43cc-94bf-920eff10ceed",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1628263226763,
"id": "X3Knds5oF_0_",
"outputId": "41cd14f7-f549-49e6-ff3c-97cece9c2481",
"source_hash": "1bb3d1ae"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'Enteros': [1, 2, 3, 4, 5], 'Ciudad': 'Bogota', 'Cédula': 1128400433, 'Colores': ['Amarillo', 'Azul', 'Rojo'], 'País': 'Chile'}\n"
]
}
],
"source": [
"#The command del can be also used for deleting an element, as a list\n",
"del dictionary2[\"Pais\"]\n",
"print(dictionary2)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00186-8e520c46-2726-484a-84d8-e27f8d5b912f",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "U51G2o8M40a7"
},
"source": [
"With the previous `zip` function to create tuples from lists, we can create a dictionary from the two lists:"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"cell_id": "00205-ad5efcef-41d1-4613-8439-a0b2ee077304",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 13,
"execution_start": 1628263341184,
"source_hash": "27b839db",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"[('A', 1), ('B', 2), ('C', 3)]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(zip( ['A','B','C'],[1,2,3] ))"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"cell_id": "00187-ac485a4d-8749-4147-9498-5b3df3fdeb78",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 21,
"execution_start": 1628263330801,
"id": "h_mODhqZ40a7",
"outputId": "b42b9750-6b54-4eae-d225-c175fcdcf28a",
"source_hash": "98167189"
},
"outputs": [
{
"data": {
"text/plain": [
"{'A': 1, 'B': 2, 'C': 3}"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dict(zip( ['A','B','C'],[1,2,3] ))"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00188-7ad8d760-6220-48a9-bcff-9e5a1b3535bd",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "LxMk7Iq3kAJm"
},
"source": [
"**Activity**: Creates a diccionary for the values: `['xyz',3,4.5]` with integer keys starting with zero. In this way, the dictionary could behave as list"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"cell_id": "00189-3ef32f75-5897-4dc1-872a-d7815babd6bb",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 5,
"execution_start": 1628263759228,
"id": "UKRSPIQe40a9",
"source_hash": "84df6609"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00206-924ed65c-1523-4caa-a508-2189973fbfb5",
"deepnote_cell_type": "markdown",
"tags": []
},
"source": [
"### JSON object\n",
"A list of dictionaries is simple example of a non-relational database which can be represented as a JSON object. Their main advantage is that with the proper glosary for the keys of the dictionaries the data analysis is well expressed through the impledmented code"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Two basic concepts"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* list"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'dog'"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"l=['cat','dog','cow']\n",
"l[1]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* dictionary"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'mango'"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"d={'animal':'cat','fruit':'mango'}\n",
"d['fruit']"
]
},
{
"cell_type": "markdown",
"metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"#### They can be nested!"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'dog'"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"farm={'animals':l,'fruits':['mango','banana']}\n",
"farm['animals'][1]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"They can be saved"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"import json"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [],
"source": [
"f=open('farm.json','w')\n",
"json.dump(farm,f)\n",
"f.close()"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\u001b[0;34m{\u001b[0m\u001b[0;34m\"animals\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m\"cat\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"dog\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"cow\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"fruits\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m\"mango\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"banana\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%pycat farm.json"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"They can be read"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'animals': ['cat', 'dog', 'cow'], 'fruits': ['mango', 'banana']}"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f=open('farm.json','r')\n",
"farm=json.load(f)\n",
"f.close()\n",
"farm"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"They can be visualized (in [Firefox](./ds.json) ) or from any advanced editor"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"from IPython.display import JSON"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"application/json": {
"animals": [
"cat",
"dog",
"cow"
],
"fruits": [
"mango",
"banana"
]
},
"text/plain": [
""
]
},
"execution_count": 49,
"metadata": {
"application/json": {
"expanded": false,
"root": "root"
}
},
"output_type": "execute_result"
}
],
"source": [
"JSON(farm)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The can be diagramatically represented: ovals are dictionaries and squares are lists"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"See the [tweet object]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Any information set can be represented as a single JSON scheme (JSON object)\n",
"* Spreadsheet\n",
"* SQL Relational database\n",
"* [Tweet](https://www.researchgate.net/profile/Giridhar-Maji/publication/332222158/figure/fig1/AS:817207873392641@1571848948669/Tweet-object-structure-with-major-attributes.png)\n",
"* Facebook post\n",
"* Jupyter notebook\n",
"* Scientific article\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In practice, any information set can be represented as a few as possible JSON objects:\n",
"\n",
"__Non-Relational database (MongoDB)__\n",
"\n",
"> A non-relational database is a database that does not use the tabular schema of rows and columns found in most traditional database systems. Instead, non-relational databases use a storage model that is optimized for the specific requirements of the type of data being stored.\n",
"\n",
"[From microsoft](https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"#### Example:\n",
"Extract information from a JSON object"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"cell_id": "00207-42f59028-7745-4a48-8040-90954edb5d78",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 1,
"execution_start": 1628263979443,
"source_hash": "1bba42f3",
"tags": []
},
"outputs": [],
"source": [
"people=[{'name':'Juan', 'last_name':'Valdez','age':25},\n",
" {'name':'Álvaro','last_name':'Uribe', 'age':69}\n",
" ]"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00208-faf835dd-994f-497c-8138-61e65fe4c29f",
"deepnote_cell_type": "markdown",
"tags": []
},
"source": [
"Extract the last names from the `people` data base (Note the very expressive sintaxis!)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"cell_id": "00209-2a51149d-f947-4107-bbd9-6afa6881ecd9",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 14,
"execution_start": 1628263982113,
"source_hash": "2606fa3f",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"['Valdez', 'Uribe']"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[d.get('last_name') for d in people]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"`d.get('last_name')` is safer than `d['last_name']`"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00210-46baa099-4abe-486c-8b35-8bc442826702",
"deepnote_cell_type": "markdown",
"tags": []
},
"source": [
"Sum the ages"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"cell_id": "00211-cb9b466e-e45a-4de4-b98b-8f313026df6a",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 55,
"execution_start": 1627063246851,
"source_hash": "dc263bbf",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"94"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum([d.get('age') for d in people])"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00194-4b3af145-7feb-45c8-8c51-c7ffa719210f",
"deepnote_cell_type": "markdown",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Sets"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"cell_id": "00195-591e8c38-1833-4206-96c8-f0c6d9b7a54f",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1628264118499,
"source_hash": "c59caa7b",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"{0, 1}"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Z2={0,1}\n",
"Z3={0,1,2}\n",
"Z2.intersection(Z3)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"cell_id": "00196-fd5bfdda-5af2-4faf-bd13-bca4b6bbde32",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 16,
"execution_start": 1628264138245,
"source_hash": "ce4b41e8",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"{0, 1, 2}"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Z2.union(Z3)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"cell_id": "00197-6ba20ea9-c862-4182-886e-4a76eeb25a27",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 15,
"execution_start": 1628264144436,
"source_hash": "fef88faf",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Z2.issubset(Z3)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00198-43b77bb5-1850-4a49-b697-3968c1701891",
"deepnote_cell_type": "markdown",
"tags": []
},
"source": [
"The elements of the set must be unique and sorted"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"cell_id": "00199-43c0fa17-d593-4a45-a5f8-d8677893d730",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 19,
"execution_start": 1628264176162,
"source_hash": "8a290927",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"{-2, 1, 2, 4}"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"U={1,2,2,2,4,4,-2}\n",
"U"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00224-b4f9c550-357a-460a-a61a-e739edb86a3c",
"deepnote_cell_type": "markdown",
"tags": []
},
"source": [
"Aplicación: Obtenga los elementos únicos de una lista"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"cell_id": "00224-4fc00209-be18-4234-b674-fad7a3b729a5",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1628264330405,
"source_hash": "edbb9604",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"[1, 3, 4, 6, 7, 9]"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"l=[3,7,1,9,4,6,6]\n",
"list(set(l))"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00193-7e91df8a-eda1-4c27-81f3-31632f1f9d02",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "oMhSjbqYF_1C"
},
"source": [
"## Conditionals"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00194-ccd82614-c309-4aae-888a-0699cfc1f46f",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "JRx2uDsXF_1C"
},
"source": [
"### if"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00195-1c81bf06-b638-401d-812d-b79c9171eaa1",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "lOnnZSRpF_1D"
},
"source": [
"Conditionals are useful when we want to check some condition.\n",
"The statements `elif` and `else` can be used when more than one condition need to be used, or when there is something to do when some condition is not fulfilled."
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"cell_id": "00196-034330d1-5b3b-4539-86db-8350e8778936",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1628265146080,
"id": "RLzAJUYrF_1D",
"outputId": "3454e51b-5dbf-4470-8192-1005c1d3cbdf",
"source_hash": "f31783ce"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n"
]
}
],
"source": [
"x = 10\n",
"y = 2\n",
"if x > 5 and y==2:\n",
" print( \"True\" )"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"cell_id": "00197-bd759858-0df5-4352-ab75-f1c10c129b36",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 12,
"execution_start": 1628265185707,
"id": "Ec7sFHSmF_1H",
"outputId": "5e5a77ce-f453-45a1-a3d5-58194cd371ee",
"source_hash": "a3b20567"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True 2\n"
]
}
],
"source": [
"x = 4\n",
"y = 3\n",
"if x>5 or y<2:\n",
" print( \"True 1\" )\n",
"elif x==4:\n",
" print( \"True 2\" )\n",
"else:\n",
" print( \"False\" )"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00205-8a1bdbef-3870-4272-a37f-797627cd74e5",
"deepnote_cell_type": "markdown",
"tags": []
},
"source": [
"## Loops"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00198-ed773f4e-f08e-43d6-970f-7c4e7019a757",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "RKDoomeWF_1J",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### for"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00199-b44658ce-9e0d-4402-adee-82a657d3411f",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "8MS64bApF_1J"
},
"source": [
"`For` cycles are specially useful when we want to sweep a set of elements with a known size."
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"cell_id": "00200-6566e5ac-b506-4fb4-a8ed-503ef2f5591b",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 104
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 18,
"execution_start": 1628265210358,
"id": "BGnKwruIF_1K",
"outputId": "2f93c5e8-66a6-4e74-f268-523891a23892",
"source_hash": "183ce532"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 0\n",
"1 1\n",
"2 4\n",
"3 9\n",
"4 16\n"
]
}
],
"source": [
"for i in range(0,5,1):\n",
" print( i, i**2)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00201-848f61f8-1f0f-4b60-ba67-52f8c6c0f914",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "77PbzyH9EW_J"
},
"source": [
"__Activity__: change print with format"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00202-2c2be090-0f25-4d95-b790-b0f637d79d6f",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "CEj1vWu_ElkK"
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {
"cell_id": "00203-fe979c0c-86a7-4d7e-856c-e04e71e11d84",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 13,
"execution_start": 1628265363274,
"id": "haLnqdCZF_1N",
"outputId": "ba064e9c-e8e6-407b-8a9d-b63820f5397e",
"source_hash": "804b79d9"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The result is 285\n"
]
}
],
"source": [
"suma = 0\n",
"for i in range(10):\n",
" suma += i**2 # suma = suma + i**2\n",
"print ( f\"The result is {suma}\" )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00204-04d50356-3b05-44ab-b8da-c2038d6a5b0d",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 104
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "QmjcgnNbF_1P",
"outputId": "08564dc9-b4da-4f21-ea97-0de3904aa9b8"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Python\n",
"C\n",
"C++\n",
"Ruby\n",
"Java\n"
]
}
],
"source": [
"for language in ['Python', 'C', 'C++', 'Ruby', 'Java']:\n",
" print ( language )"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00205-5ad00505-214e-479e-a2f8-1466c27b9fad",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "C48dKFMC40bN"
},
"source": [
"As we see before, `for` can be used to build comprenhension lists"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00206-06d3ac31-79de-4718-9d7f-524115f21017",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "lrkdxlQdF_1R",
"outputId": "bad56fc0-48f2-4219-8b27-e8f6a2f05be9"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1, 4, 9, 16, 25, 36, 49, 64, 81]\n"
]
}
],
"source": [
"serie = [ i**2 for i in range(1,10) ]\n",
"print( serie )"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00207-40757f14-9255-462c-b874-9aaab23a721d",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "Vk6CUxqjF_1S",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### while"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00208-4de1938d-8c8b-424d-93cc-760a1599630f",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "kys-BDH-F_1T"
},
"source": [
"`While` cycles are specially useful when we want to sweep a set of elements with an unknown size."
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00209-46a116c6-c95f-4c88-b54b-12323ddf1b8f",
"deepnote_cell_type": "markdown"
},
"source": [
"Before we check the functions `input` and `int` of Python"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"cell_id": "00210-7d5f306b-eadb-41c8-a7a5-8620a9911e9c",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 4472,
"execution_start": 1628265392026,
"source_hash": "ea774bd8"
},
"outputs": [],
"source": [
"edad=input('¿What is your age, Jesus?:\\n')"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"cell_id": "00211-445d9a7e-1813-495e-ac39-78c7ffdb3a06",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 13,
"execution_start": 1628265412246,
"source_hash": "99514191"
},
"outputs": [
{
"data": {
"text/plain": [
"33"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"int(edad)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00212-a1f22d10-3b95-4b8b-9346-b872991e56c2",
"deepnote_cell_type": "markdown"
},
"source": [
"Bonus: some time the input must be hidden"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {
"cell_id": "00213-b115e9d4-16aa-4611-833a-bdbc56c614ea",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 0,
"execution_start": 1628265423279,
"source_hash": "60de103a"
},
"outputs": [],
"source": [
"import getpass"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"cell_id": "00214-e953a155-b8d1-4805-8c7d-f12307d109cc",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 8198,
"execution_start": 1628265432333,
"source_hash": "3329a22"
},
"outputs": [],
"source": [
"c=getpass.getpass('Contraseña')"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {
"cell_id": "00215-667d4637-b341-4aeb-bfa6-5490014d13ca",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 28,
"execution_start": 1628265452887,
"source_hash": "957caa7e"
},
"outputs": [
{
"data": {
"text/plain": [
"'secreto'"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"c"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00216-d72e43af-8ec6-4ded-b701-72f337954cea",
"deepnote_cell_type": "markdown"
},
"source": [
"Now the `while` examples"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"cell_id": "00217-eee4cc13-f730-43a2-8649-dc08b7c92874",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 156
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 16758,
"execution_start": 1628265490576,
"id": "7n0eZTTGF_1T",
"outputId": "284cf3c9-294c-4282-f6ee-fb587b5439c4",
"source_hash": "3a149021"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"You wrote a positive number. Do it again\n",
"You wrote a positive number. Do it again\n",
"Thank you!\n"
]
}
],
"source": [
"#! /usr/bin/python\n",
"number = int(input(\"Write a negative number: \"))\n",
"while number > 0:\n",
" print(\"You wrote a positive number. Do it again\")\n",
" number = int(input(\"Write a negative number: \"))\n",
"print(\"Thank you!\")"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {
"cell_id": "00218-3d0f8da9-272b-4f29-8dc4-a879189eabd9",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 173
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 3,
"execution_start": 1628265574287,
"id": "qB2KXTVwF_1W",
"outputId": "b81f4c44-2cca-4e23-8cf1-7c7a9fbd7b33",
"source_hash": "bfa297c2"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.2752802751365522\n",
"0.454951670912941\n",
"0.5693802843954813\n",
"0.40177621529970386\n",
"0.5723817621908507\n",
"0.07290420456928348\n",
"0.8490188174025372\n",
"0.7299725403288975\n",
"0.643209656068515\n",
"0.489899543622623\n",
"0.2264889834942161\n",
"0.20635090393901312\n",
"0.09683376918376296\n",
"0.14509871628728777\n",
"0.016240658000300057\n",
"0.7959386412781978\n",
"0.4201817808266113\n",
"0.461661957674957\n",
"0.8050501425691475\n",
"0.35466072752783484\n",
"0.46678267891050707\n",
"0.21167232860716456\n",
"0.4891465944627792\n",
"0.36677308439573475\n",
"0.7677369600825966\n",
"0.16631714193575065\n",
"0.0017489053343822114\n",
"0.819215365205134\n",
"0.9499334082744344\n",
"The selected number was 0.9499334082744344\n"
]
}
],
"source": [
"import random\n",
"x = 0\n",
"while x<0.9:\n",
" x = random.random()\n",
" print( x )\n",
"print (\"The selected number was\", x )"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00219-7c989cbb-908a-46ad-948f-2e7ad27c80c1",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "MpuXWP76PRkT"
},
"source": [
"## Methods and attributes of objects in Python\n",
"All the objects in `Python`, including the function and variable types discussed here, are enhanced with special functions called _methods_, which are implemented after a point of the name of the variable, in the format:\n",
"```python\n",
"variable.method()\n",
"```\n",
"Some times, the method can even accept some arguments. \n",
"\n",
"The objects have also attributes which describe some property of the object. They do not end up with parenthesis:\n",
"```python\n",
"variable.attribute\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00220-5bbd289e-7ad7-4874-b6bc-3be16881cfcd",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "999oCdgfPZOM",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Methods\n",
"For example. The method `.keys()` of a variable dictionary allows to obtain the list of keys of the dictionary. For example"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {
"cell_id": "00221-45c8146f-c770-45d5-8eb3-8b192124fe7a",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 11,
"execution_start": 1628265625027,
"id": "nJZOnhPfPb8b",
"outputId": "e12624c2-f546-4501-a318-1c2a45a18026",
"source_hash": "b6ec19fd"
},
"outputs": [
{
"data": {
"text/plain": [
"dict_keys(['Kenia', 'Noruega', 'Finlandia', 'Rusia', 'Rio de Janeiro', 'Japón', 'Colorado', 'Alemania', 'Colombia'])"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dictionary.keys()"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00222-bff0bb8f-70c0-4128-9671-42b03bb292e4",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "4gvGokFJPejs"
},
"source": [
"And the list of values:"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {
"cell_id": "00223-76ea55a3-546d-40a4-83dc-d6d59b51fecd",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 23,
"execution_start": 1628265634377,
"id": "KcWbTzfjPiKL",
"outputId": "66d78276-552e-4efb-bb7e-3433a091de62",
"source_hash": "296aa203"
},
"outputs": [
{
"data": {
"text/plain": [
"dict_values(['Nairobi', 'Oslo', 'Helsinski', 'Moscú', 'Rio', 'Tokio', 'Denver', 'Berlin', 'Bogotá'])"
]
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dictionary.values()"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00224-9ebc6649-40f0-4730-877f-77db92a215cd",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "op4UiMHFPkek"
},
"source": [
"For strings we have for example the conversion to lower case"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {
"cell_id": "00225-5dde53e2-d039-4597-9d7d-974a3e815cb7",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 0,
"execution_start": 1628265681193,
"id": "yMXxDJymPsi7",
"outputId": "8d517979-7568-442d-ceea-296ad29f10f7",
"source_hash": "cd9af8b1"
},
"outputs": [
{
"data": {
"text/plain": [
"'juan valdez'"
]
},
"execution_count": 64,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s=\"Juan Valdez\"\n",
"s.lower()"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {
"cell_id": "00226-04aecf5a-3a55-4557-aee7-620233fab762",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 14,
"execution_start": 1628265692276,
"source_hash": "6a1e684f"
},
"outputs": [
{
"data": {
"text/plain": [
"'Juan Valdez'"
]
},
"execution_count": 65,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\"juan valdez\".title()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00227-71f0c11e-b4d8-4ade-ac9b-12db09299a3f",
"deepnote_cell_type": "code"
},
"outputs": [
{
"data": {
"text/plain": [
"'JUAN VALDEZ'"
]
},
"execution_count": 178,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\"juan valdez\".upper()"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00228-1201df6f-5487-4fb1-a596-4b1a123eae7f",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "NaWNpAh8PtAD",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"### Attributes"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {
"cell_id": "00229-2bc92544-1312-423e-ab22-712683d1e348",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 0,
"execution_start": 1628265704401,
"id": "yWVg_HMVP4li",
"source_hash": "b3c0e02"
},
"outputs": [],
"source": [
"a=1j"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {
"cell_id": "00230-c21184cd-2172-45ed-9b28-244db6ef4d53",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 16,
"execution_start": 1628265708612,
"id": "TZLoLjFKP6gT",
"outputId": "bfb38dc9-dce8-4816-ff63-f4215ac9d36f",
"source_hash": "899b6bb5"
},
"outputs": [
{
"data": {
"text/plain": [
"1.0"
]
},
"execution_count": 67,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a.imag"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {
"cell_id": "00231-95095040-ece2-48db-a372-8a310f6fc62a",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 14,
"execution_start": 1628265712855,
"source_hash": "eb5812a6"
},
"outputs": [
{
"data": {
"text/plain": [
"0.0"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a.real"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {
"cell_id": "00232-d9027365-efdb-4ce2-993b-b10a4030bffe",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 1,
"execution_start": 1628265724255,
"id": "4YDuZvgbqQTh",
"source_hash": "f331e88a"
},
"outputs": [],
"source": [
"z=3+5j"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00233-e9601ee1-45fd-4eb1-b2d8-fd3cb23fa5f6",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "bwin2MdGRGI5"
},
"source": [
"with attributes"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {
"cell_id": "00234-39ca7c2d-fd8a-4105-95ad-ec463a38dbb5",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 13,
"execution_start": 1628265725782,
"id": "vXiWuELxqS-u",
"outputId": "d53786d9-1421-4e22-b7d3-00629bdb711a",
"source_hash": "91d63406"
},
"outputs": [
{
"data": {
"text/plain": [
"3.0"
]
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"z.real"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {
"cell_id": "00235-0407aed1-af85-4a4c-9910-a8c1e0a5462b",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 15,
"execution_start": 1628265726560,
"id": "twft_75iqUXd",
"outputId": "e6cc0c3d-d882-432d-93c9-cc11edfb59aa",
"source_hash": "a3b5f781"
},
"outputs": [
{
"data": {
"text/plain": [
"5.0"
]
},
"execution_count": 71,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"z.imag"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00236-10a55c4e-8019-48c7-836c-d27ad9f2962c",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "3S4SCByKRInH"
},
"source": [
"and the method:"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {
"cell_id": "00237-de90673c-4803-426b-8c12-185c54ad9294",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"deepnote_to_be_reexecuted": false,
"execution_millis": 10,
"execution_start": 1628265731069,
"id": "FtsN8LmERK8_",
"outputId": "894b51eb-34fd-4fce-c3d6-3ff382a1c25c",
"source_hash": "a7c71621"
},
"outputs": [
{
"data": {
"text/plain": [
"(3-5j)"
]
},
"execution_count": 72,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"z.conjugate()"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00238-c110becb-a3b2-4f5a-8adf-cf0b68e9e9c4",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "mqPXQ2THP-Kz"
},
"source": [
"In the notebook, All the methods and attributes of an object can be accessed by using the `` key after write down the point:\n",
"```python\n",
"variable.\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00239-980daca3-f063-4cb8-b9e1-b5a9918208fe",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "IKvhvPBEIhb7"
},
"outputs": [],
"source": [
"z."
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00240-095cdf89-d7a1-4e9d-ae28-7f7499718117",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "iBQGxzuFQCID"
},
"source": [
"__Activity__: Check the methods and attributes of the dictionary `dictonary`. HINT: Check the help for some of them by using a question mark, \"?\", at the end:\n",
"```\n",
"variable.method?\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00241-8546677a-b493-4719-a269-af0277736ecb",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "xJBhkIFf40bz",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"## Unicode\n",
"Is an standard to encode characters. In Python 3, around [120.000 characters](https://stackoverflow.com/a/17043983) can be used to define variables. For example, one right to left arabic variable can be defined as"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00242-a2d5676f-9e67-445a-838c-128e2dc6249e",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "E2GeG8HZ40bz",
"outputId": "579f4e15-ea31-41aa-d8ca-ae1a3baca18e"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Arabic character values is: 2\n"
]
}
],
"source": [
"ࢶ=2\n",
"print('Arabic character values is: {}'.format(ࢶ))"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00243-997768d1-b304-4300-b5cc-d0cb595f6dc2",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "sdVB50fe40b0"
},
"source": [
"Spanish example"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00244-b53637d7-91bd-4f03-bc28-8ac9ec50515f",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "DznrKWaDjv8W"
},
"outputs": [],
"source": [
"mamá='Lola'"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00245-b9eb3447-2fb3-47bb-9c5f-8abe85ef4f62",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "PftXYj-K40b2"
},
"source": [
"In Jupyter lab greek symbols can be accessed by using its LaTeX command follow by the `` key. \n",
"\n",
"`\\alpha+=0.5` could convert on the fly to "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00246-7e355b2b-397d-4174-aa93-2ad6e1981a74",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "s-HaoMaN40b2"
},
"outputs": [],
"source": [
"α=0.5"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00247-82438024-40c5-455b-b423-9f19cdfef009",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "-FDXnyJD40b3",
"outputId": "9cb517f1-cc0b-4ad4-f18b-d52b110329a3"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.5\n"
]
}
],
"source": [
"print(α)"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00248-7cd60ec8-729d-4af2-8a95-600cc07c3785",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "7NgyW2Sv40b4"
},
"source": [
"Alternatively yuo can copy the character from some list of unicode symbols, like [this one](https://en.wikipedia.org/wiki/List_of_Unicode_characters#Greek_and_Coptic).\n",
"\n",
"__Activity__: Define a Greek variable by using a symbol from the previous list"
]
},
{
"cell_type": "markdown",
"metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"## Stop exection\n",
"Stop the program if a condition is not satisfied\n",
"\n",
"See: https://realpython.com/python-exceptions/"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"cell_id": "00249-85eb53c1-6765-4d62-b074-52bf7af37cab",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "Ym0NpCWxKJQB"
},
"outputs": [
{
"ename": "Exception",
"evalue": "x should not exceed 5. The value of x was: 6",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mException\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/tmp/ipykernel_30232/2136376697.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m6\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'x should not exceed 5. The value of x was: {}'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf'codo continues here: {x}<=5'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mException\u001b[0m: x should not exceed 5. The value of x was: 6"
]
}
],
"source": [
"x = 6\n",
"if x > 5:\n",
" raise Exception('x should not exceed 5. The value of x was: {}'.format(x))\n",
"\n",
"print(f'codo continues here: {x}<=5')"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00250-278fdad9-ce65-4221-89fb-ade632e04fc3",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "9MgMakz7jhml",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"## Final remarks\n",
"Make your google Python questions in English and check specially the https://stackoverflow.com/ results.\n",
"\n",
"__Activity__: Make some Python query in Google and paste the example code below"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00251-7f042922-3e62-4e71-809f-26bc971c1edf",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "iEtlCAbZ40b6"
},
"outputs": [],
"source": [
"input('What was the Google query that you ask?:\\n')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00252-f20faff6-23e0-4933-9348-b6b7a9fbe414",
"colab": {},
"colab_type": "code",
"deepnote_cell_type": "code",
"id": "DZG2Mb8cbHur"
},
"outputs": [],
"source": [
"β"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00253-27ad1dc9-d0c4-4c8c-9d2b-2c6a404419d3",
"colab_type": "text",
"deepnote_cell_type": "markdown",
"id": "_fIw7E_a40b7"
},
"source": [
"Sample code:"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00254-2ad05951-d3e8-4ca1-a8f1-ab7cd8194550",
"deepnote_cell_type": "markdown"
},
"source": [
"## Parallel\n",
"```python\n",
"foo(x) → delayed(foo)(x)\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cell_id": "00255-3b6d8bea-7285-4f2c-b484-4fe59b794fc3",
"deepnote_cell_type": "code"
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"outputs": [
{
"data": {
"text/plain": [
"[0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]"
]
},
"execution_count": 160,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
">>> from joblib import Parallel, delayed\n",
">>> from math import sqrt\n",
">>> Parallel(n_jobs=8)(delayed(sqrt)(i**2) for i in range(10))"
]
},
{
"cell_type": "markdown",
"metadata": {
"cell_id": "00256-175d7309-fc80-45cb-9898-fa05efbdeb88",
"deepnote_cell_type": "markdown"
},
"source": [
"See also: https://docs.python.org/3/library/multiprocessing.html"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## [Scientific libraries](https://restrepo.github.io/ComputationalMethods/material/scientific-libraries.html)\n",
"\n",
"## [Pandas](https://restrepo.github.io/ComputationalMethods/material/Pandas.html)\n",
"\n",
"## [Matplotlib](https://restrepo.github.io/ComputationalMethods/material/matplotlib.html)\n",
"\n",
"## [Jupyter notebooks](https://restrepo.github.io/ComputationalMethods/material/ipython-notebooks.html)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Appendix"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Summary with ChatGPT](https://htmlpreview.github.io/?https://github.com/restrepo/ComputationalMethods/blob/master/material/ChatGPT-2023-02-11T02-21-44.html)\n",
"\n"
]
},
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"cell_type": "code",
"execution_count": null,
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"outputs": [],
"source": []
}
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