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Prueba de francisco #2

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249 changes: 249 additions & 0 deletions ...on Foundations for Data Visualization/.ipynb_checkpoints/01A_Foundations-checkpoint.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "9770afb4-2609-4152-a3d5-9ba337927fb9",
"metadata": {},
"source": [
"# Python Foundations for Data Visualization"
]
},
{
"cell_type": "markdown",
"id": "c37b2f3e-2439-4e9f-8611-1ade1202d0a6",
"metadata": {},
"source": [
"## Create objects with data"
]
},
{
"cell_type": "markdown",
"id": "ed9e451e-7f65-430b-8e18-a738dcb92b2c",
"metadata": {},
"source": [
"### Football Teams"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "460c007d-a40b-47a4-b6cd-906644a8f634",
"metadata": {},
"outputs": [],
"source": [
"football_teams = ['Real Madrid', 'Barcelona', 'Bayern Munich']"
]
},
{
"cell_type": "markdown",
"id": "db095953-5695-4b52-90ea-e1347986cd56",
"metadata": {},
"source": [
"### Champions Leagues"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a9a90ee9-8196-471a-89d6-99e868e8a581",
"metadata": {},
"outputs": [],
"source": [
"champions_leagues = [14, 5, 6]"
]
},
{
"cell_type": "markdown",
"id": "65f455ae-544f-42eb-a4d6-8159d70d8db7",
"metadata": {},
"source": [
"<div class=\"alert alert-info\">\n",
" The <b>function</b> processes data to give you the result you want.\n",
" <br><b>Libraries</b> store functions to give you results of a particular topic.\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "104283e9-d324-41cf-97fd-3fa6d6594032",
"metadata": {},
"source": [
"## Import matplotlib library\n",
"\n",
"> **Mat**hematical **Plot**ting **Lib**rary\n",
"\n",
"Matplotlib is a Python library that contains functions to create Data Visualizations"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cc78e6bc-2140-4d0e-977e-a4f598f50914",
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"id": "5d51e871-8fdb-4478-b663-e6c1a8109001",
"metadata": {},
"source": [
"### Scatter plot (points)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "40de7996-eba0-4b57-85f8-be0cde16cb26",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "b5c3a074-741c-4c16-bf18-d54d575227e5",
"metadata": {},
"source": [
"### Bar plot"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d9e0edb2-9b0a-46e6-8d6a-c9bcdd78a0c4",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "c09b202b-a617-43c9-a354-826b1a613cf7",
"metadata": {},
"source": [
"### Many others"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fed6c908-9c89-4b75-b0fd-32c5faac2759",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "e500aec9-79c2-471f-85ec-b418b18eea95",
"metadata": {},
"source": [
"https://matplotlib.org/stable/plot_types/index"
]
},
{
"cell_type": "markdown",
"id": "254f8c0f-370b-40bc-9881-2b2c7c7a8b16",
"metadata": {},
"source": [
"## Customize the plot"
]
},
{
"cell_type": "markdown",
"id": "03706466-9435-4e24-864b-150d062276ff",
"metadata": {},
"source": [
"### Change the size"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1222fa3b-88ad-42c6-8585-f8ba4069d9b7",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "dfa1bed9-66ac-40e1-aef0-d919005b5999",
"metadata": {
"tags": []
},
"source": [
"### Change the color"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ae49fc8a-edbd-4fe6-b941-9e1c44ba2275",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "17793a56-96e4-48aa-8784-74fcfb361f41",
"metadata": {},
"source": [
"### Change the marker"
]
},
{
"cell_type": "markdown",
"id": "e7c1226c-781d-4d6e-8eba-7f5a0262cb80",
"metadata": {},
"source": [
"https://matplotlib.org/stable/api/markers_api.html"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c1df3c9d-2aa3-4540-9926-1185df12cd1c",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "13a02cd9-eaa8-4524-89b7-1a1d7d3f11a5",
"metadata": {},
"source": [
"### Change the border"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "11b12c16-6992-4111-8168-4cc87e621e6b",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
},
"toc-autonumbering": true
},
"nbformat": 4,
"nbformat_minor": 5
}
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