{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "name": "Lesson_2.ipynb", "version": "0.3.2", "provenance": [], "collapsed_sections": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" } }, "cells": [ { "metadata": { "id": "1FHqVcFeIwTo", "colab_type": "text" }, "cell_type": "markdown", "source": [ "# Analizando Datos con PyData \n", "\n", " * PyData\n", " * Relación entre Bibliotecas\n", " * Objetivos de la Lección\n", "\n", "## Pandas\n", "\n", " * Relación Numpy y Pandas\n", " * DataFrame y Series\n", " * Entorno y bibliotecas Auxiliares\n", " * Una vista las funcionalidades en Pandas (api)\n", " \n", "## Básico 1: Carga de Datos y Exploración \n", " \n", " * Carga de Datos\n", " * Mínimas funciones para explorar los datos\n", " * Mínima manipulación de datos.\n", "\n", "\n" ] }, { "metadata": { "id": "iXJ-wPp4CVnA", "colab_type": "text" }, "cell_type": "markdown", "source": [ "## PyData\n", "\n", "Se usa el nombre **PyData** para referirce a las bibliotecas de Python que se usan para cómputo científico. Pero no es la definición en si; eso es el \"stack\", PyData es un programa respaldado por una organización sin fines de lucro que lo que busca a apoyar el uso y desarrollo del open source y en especial el uso e implementación del stack de Python para cómputo científico. \n", "\n", "La organización [NumFocus](https://numfocus.org/), dentro de sus programas [PyData](https://numfocus.org/programs) le da nombre a los eventos relacionados con la enseñanza y divulgación del uso de tecnologías en Python.\n", "\n", "En nuestro caso, siguiendo las corrientes diremos PyData para referirnos al conjunto de bibliotecas que conforman el ecosistema de Python para computo científico. \n", "\n", "La evolución y estado actual se pueden ver en la siguiente presentación de [Travis Oliphant](https://en.wikipedia.org/wiki/Travis_Oliphant)\n", "\n", "[Presentación](https://drive.google.com/file/d/1mHzSIefPnM8O3j85B0hoxTme-qYmKJJ1/view)\n", "\n", "\n" ] }, { "metadata": { "id": "5rZSS0AdK18q", "colab_type": "text" }, "cell_type": "markdown", "source": [ "## Relación entre bibliotecas\n", "\n", "Para tener una idea de la relación entre proyectos resulta ilustrativo explorar la lista de proyectos relacionados entre 4 bibliotecas:\n", "\n", "* [ Numpy](https://www.scipy.org/install.html)\n", "* [Pandas](http://pandas.pydata.org/pandas-docs/stable/ecosystem.html)\n", "* [Scikit-Learn](https://scikit-learn.org/stable/related_projects.html)\n", "* [Tensorflow](https://www.tensorflow.org/resources/)\n", "\n", "*¿Cuál es la relación entre las bibliotecas?*" ] }, { "metadata": { "id": "x3zBafKcKlwL", "colab_type": "text" }, "cell_type": "markdown", "source": [ "## Objetivo \n", "\n", "* Conocer el entorno de trabajo.\n", "* Conocer un mímino del ecosistema de trabajo.\n", "* Un primer análisis." ] }, { "metadata": { "id": "dMtcJlzBKVNf", "colab_type": "text" }, "cell_type": "markdown", "source": [ "# Pandas\n", "\n", "De manera rápida se pude explorar la documentación de los proyectos; Pandas y Numpy, pero desde la documentación de la biblioteca. Esto se puede hacer desde una orden en la consola." ] }, { "metadata": { "id": "zZVuXaa4-LE_", "colab_type": "text" }, "cell_type": "markdown", "source": [ "## Entorno\n" ] }, { "metadata": { "id": "zDgb7dFyCUqh", "colab_type": "code", "outputId": "b4bf02b0-7353-4385-d682-341bbcc959dd", "colab": { "base_uri": "https://localhost:8080/", "height": 51 } }, "cell_type": "code", "source": [ "#Se cargan Pandas y Numpy\n", "import pandas as pd\n", "import numpy as np\n", "\n", "print(\"Version de Pandas:\",pd.__version__)\n", "print(\"Version de Numpy:\",np.__version__)\n" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "Version de Pandas: 0.22.0\n", "Version de Numpy: 1.14.6\n" ], "name": "stdout" } ] }, { "metadata": { "id": "37dN4FVnO31f", "colab_type": "code", "outputId": "e4a10110-aa00-437e-f565-b0782ad0abb4", "colab": { "base_uri": "https://localhost:8080/", "height": 703 } }, "cell_type": "code", "source": [ "#Se imprime la documentación de Pandas\n", "print(pd.__doc__)\n" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "\n", "pandas - a powerful data analysis and manipulation library for Python\n", "=====================================================================\n", "\n", "**pandas** is a Python package providing fast, flexible, and expressive data\n", "structures designed to make working with \"relational\" or \"labeled\" data both\n", "easy and intuitive. It aims to be the fundamental high-level building block for\n", "doing practical, **real world** data analysis in Python. Additionally, it has\n", "the broader goal of becoming **the most powerful and flexible open source data\n", "analysis / manipulation tool available in any language**. It is already well on\n", "its way toward this goal.\n", "\n", "Main Features\n", "-------------\n", "Here are just a few of the things that pandas does well:\n", "\n", " - Easy handling of missing data in floating point as well as non-floating\n", " point data\n", " - Size mutability: columns can be inserted and deleted from DataFrame and\n", " higher dimensional objects\n", " - Automatic and explicit data alignment: objects can be explicitly aligned\n", " to a set of labels, or the user can simply ignore the labels and let\n", " `Series`, `DataFrame`, etc. automatically align the data for you in\n", " computations\n", " - Powerful, flexible group by functionality to perform split-apply-combine\n", " operations on data sets, for both aggregating and transforming data\n", " - Make it easy to convert ragged, differently-indexed data in other Python\n", " and NumPy data structures into DataFrame objects\n", " - Intelligent label-based slicing, fancy indexing, and subsetting of large\n", " data sets\n", " - Intuitive merging and joining data sets\n", " - Flexible reshaping and pivoting of data sets\n", " - Hierarchical labeling of axes (possible to have multiple labels per tick)\n", " - Robust IO tools for loading data from flat files (CSV and delimited),\n", " Excel files, databases, and saving/loading data from the ultrafast HDF5\n", " format\n", " - Time series-specific functionality: date range generation and frequency\n", " conversion, moving window statistics, moving window linear regressions,\n", " date shifting and lagging, etc.\n", "\n" ], "name": "stdout" } ] }, { "metadata": { "id": "DZwoBopaPQRq", "colab_type": "code", "outputId": "6bc40610-40bb-4efb-df30-36fb336901e6", "colab": { "base_uri": "https://localhost:8080/", "height": 1834 } }, "cell_type": "code", "source": [ "#Se imprime la documentación de Numpy\n", "print(np.__doc__)" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "\n", "NumPy\n", "=====\n", "\n", "Provides\n", " 1. An array object of arbitrary homogeneous items\n", " 2. Fast mathematical operations over arrays\n", " 3. Linear Algebra, Fourier Transforms, Random Number Generation\n", "\n", "How to use the documentation\n", "----------------------------\n", "Documentation is available in two forms: docstrings provided\n", "with the code, and a loose standing reference guide, available from\n", "`the NumPy homepage `_.\n", "\n", "We recommend exploring the docstrings using\n", "`IPython `_, an advanced Python shell with\n", "TAB-completion and introspection capabilities. See below for further\n", "instructions.\n", "\n", "The docstring examples assume that `numpy` has been imported as `np`::\n", "\n", " >>> import numpy as np\n", "\n", "Code snippets are indicated by three greater-than signs::\n", "\n", " >>> x = 42\n", " >>> x = x + 1\n", "\n", "Use the built-in ``help`` function to view a function's docstring::\n", "\n", " >>> help(np.sort)\n", " ... # doctest: +SKIP\n", "\n", "For some objects, ``np.info(obj)`` may provide additional help. This is\n", "particularly true if you see the line \"Help on ufunc object:\" at the top\n", "of the help() page. Ufuncs are implemented in C, not Python, for speed.\n", "The native Python help() does not know how to view their help, but our\n", "np.info() function does.\n", "\n", "To search for documents containing a keyword, do::\n", "\n", " >>> np.lookfor('keyword')\n", " ... # doctest: +SKIP\n", "\n", "General-purpose documents like a glossary and help on the basic concepts\n", "of numpy are available under the ``doc`` sub-module::\n", "\n", " >>> from numpy import doc\n", " >>> help(doc)\n", " ... # doctest: +SKIP\n", "\n", "Available subpackages\n", "---------------------\n", "doc\n", " Topical documentation on broadcasting, indexing, etc.\n", "lib\n", " Basic functions used by several sub-packages.\n", "random\n", " Core Random Tools\n", "linalg\n", " Core Linear Algebra Tools\n", "fft\n", " Core FFT routines\n", "polynomial\n", " Polynomial tools\n", "testing\n", " NumPy testing tools\n", "f2py\n", " Fortran to Python Interface Generator.\n", "distutils\n", " Enhancements to distutils with support for\n", " Fortran compilers support and more.\n", "\n", "Utilities\n", "---------\n", "test\n", " Run numpy unittests\n", "show_config\n", " Show numpy build configuration\n", "dual\n", " Overwrite certain functions with high-performance Scipy tools\n", "matlib\n", " Make everything matrices.\n", "__version__\n", " NumPy version string\n", "\n", "Viewing documentation using IPython\n", "-----------------------------------\n", "Start IPython with the NumPy profile (``ipython -p numpy``), which will\n", "import `numpy` under the alias `np`. Then, use the ``cpaste`` command to\n", "paste examples into the shell. To see which functions are available in\n", "`numpy`, type ``np.`` (where ```` refers to the TAB key), or use\n", "``np.*cos*?`` (where ```` refers to the ENTER key) to narrow\n", "down the list. To view the docstring for a function, use\n", "``np.cos?`` (to view the docstring) and ``np.cos??`` (to view\n", "the source code).\n", "\n", "Copies vs. in-place operation\n", "-----------------------------\n", "Most of the functions in `numpy` return a copy of the array argument\n", "(e.g., `np.sort`). In-place versions of these functions are often\n", "available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``.\n", "Exceptions to this rule are documented.\n", "\n", "\n" ], "name": "stdout" } ] }, { "metadata": { "id": "ToiKfUxCVbK_", "colab_type": "text" }, "cell_type": "markdown", "source": [ "## Magic Commands\n", "\n", "Como se mensionó en la lección 1, el entorno ayuda agílizar el proceso de códificación y sobre todo de desarrollo de un análisis de datos. Con entorno me refiero a Jupyter y sus derivados.\n", "\n", "Jupyter, como heredero de Ipython tiene varias caracterísicas interesantes:\n", "\n", "* Autocompletado\n", "* Magic Commands\n", "\n", "Los siguientes comandos son ejemplos de las utilidades de los magic commands." ] }, { "metadata": { "id": "6g8uOlxBQDEn", "colab_type": "code", "outputId": "47eeb3f0-2456-4d44-a3b4-9861edef5838", "colab": { "base_uri": "https://localhost:8080/", "height": 86 } }, "cell_type": "code", "source": [ "#Si se desea conocer lo que se tiene en la sección de trabajo\n", "# se puede usar el siguiente comando.\n", "%whos" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "Variable Type Data/Info\n", "------------------------------\n", "np module kages/numpy/__init__.py'>\n", "pd module ages/pandas/__init__.py'>\n" ], "name": "stdout" } ] }, { "metadata": { "id": "-DDZ12NHQK-C", "colab_type": "code", "outputId": "50ee2bb9-0d0c-4a47-9f2e-c47eefa36ffc", "colab": { "base_uri": "https://localhost:8080/", "height": 157 } }, "cell_type": "code", "source": [ "# Si se desea conocer la lista completa de magic commmands disponibles\n", "%lsmagic" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "application/json": { "cell": { "prun": "ExecutionMagics", "file": "Other", "!": "OSMagics", "capture": "ExecutionMagics", "timeit": "ExecutionMagics", "script": "ScriptMagics", "pypy": "Other", "system": "OSMagics", "perl": "Other", "html": "DisplayMagics", "bash": "Other", "shell": "Other", "HTML": "Other", "python": "Other", "SVG": "Other", "javascript": "DisplayMagics", "bigquery": "Other", "js": "DisplayMagics", "writefile": "OSMagics", "ruby": "Other", "python3": "Other", "python2": "Other", "latex": "DisplayMagics", "sx": "OSMagics", "svg": "DisplayMagics", "sh": "Other", "time": "ExecutionMagics", "debug": "ExecutionMagics" }, "line": { "psource": "NamespaceMagics", "logstart": "LoggingMagics", "popd": "OSMagics", "loadpy": "CodeMagics", "colors": "BasicMagics", "who_ls": "NamespaceMagics", "lf": "Other", "ll": "Other", "pprint": "BasicMagics", "lk": "Other", "ls": "Other", "save": "CodeMagics", "tb": "ExecutionMagics", "lx": "Other", "pylab": "PylabMagics", "killbgscripts": "ScriptMagics", "quickref": "BasicMagics", "magic": "BasicMagics", "dhist": "OSMagics", "edit": "KernelMagics", "logstop": "LoggingMagics", "gui": "BasicMagics", "prun": "ExecutionMagics", "debug": "ExecutionMagics", "page": "BasicMagics", "logstate": "LoggingMagics", "ed": "Other", "pushd": "OSMagics", "timeit": "ExecutionMagics", "set_env": "OSMagics", "rehashx": "OSMagics", "hist": "Other", "qtconsole": "KernelMagics", "rm": "Other", "dirs": "OSMagics", "run": "ExecutionMagics", "reset_selective": "NamespaceMagics", "pinfo2": "NamespaceMagics", "matplotlib": "PylabMagics", "unload_ext": "ExtensionMagics", "doctest_mode": "BasicMagics", "logoff": "LoggingMagics", "reload_ext": "ExtensionMagics", "pdb": "ExecutionMagics", "load": "CodeMagics", "lsmagic": "BasicMagics", "autosave": "KernelMagics", "cd": "OSMagics", "pastebin": "CodeMagics", "alias_magic": "BasicMagics", "cp": "Other", "autocall": "AutoMagics", "ldir": "Other", "bookmark": "OSMagics", "connect_info": "KernelMagics", "mkdir": "Other", "system": "OSMagics", "whos": "NamespaceMagics", "rmdir": "Other", "automagic": "AutoMagics", "store": "StoreMagics", "more": "KernelMagics", "shell": "Other", "pdef": "NamespaceMagics", "precision": "BasicMagics", "pinfo": "NamespaceMagics", "pwd": "OSMagics", "psearch": "NamespaceMagics", "reset": "NamespaceMagics", "recall": "HistoryMagics", "xdel": "NamespaceMagics", "xmode": "BasicMagics", "cat": "Other", "mv": "Other", "rerun": "HistoryMagics", "logon": "LoggingMagics", "history": "HistoryMagics", "pycat": "OSMagics", "unalias": "OSMagics", "env": "OSMagics", "load_ext": "ExtensionMagics", "config": "ConfigMagics", "profile": "BasicMagics", "pfile": "NamespaceMagics", "less": "KernelMagics", "who": "NamespaceMagics", "notebook": "BasicMagics", "man": "KernelMagics", "sx": "OSMagics", "macro": "ExecutionMagics", "clear": "KernelMagics", "alias": "OSMagics", "time": "ExecutionMagics", "sc": "OSMagics", "rep": "Other", "pdoc": "NamespaceMagics" } }, "text/plain": [ "Available line magics:\n", "%alias %alias_magic %autocall %automagic %autosave %bookmark %cat %cd %clear %colors %config %connect_info %cp %debug %dhist %dirs %doctest_mode %ed %edit %env %gui %hist %history %killbgscripts %ldir %less %lf %lk %ll %load %load_ext %loadpy %logoff %logon %logstart %logstate %logstop %ls %lsmagic %lx %macro %magic %man %matplotlib %mkdir %more %mv %notebook %page %pastebin %pdb %pdef %pdoc %pfile %pinfo %pinfo2 %popd %pprint %precision %profile %prun %psearch %psource %pushd %pwd %pycat %pylab %qtconsole %quickref %recall %rehashx %reload_ext %rep %rerun %reset %reset_selective %rm %rmdir %run %save %sc %set_env %shell %store %sx %system %tb %time %timeit %unalias %unload_ext %who %who_ls %whos %xdel %xmode\n", "\n", "Available cell magics:\n", "%%! %%HTML %%SVG %%bash %%bigquery %%capture %%debug %%file %%html %%javascript %%js %%latex %%perl %%prun %%pypy %%python %%python2 %%python3 %%ruby %%script %%sh %%shell %%svg %%sx %%system %%time %%timeit %%writefile\n", "\n", "Automagic is ON, % prefix IS NOT needed for line magics." ] }, "metadata": { "tags": [] }, "execution_count": 5 } ] }, { "metadata": { "id": "NS26Qv3CRCTT", "colab_type": "code", "colab": {} }, "cell_type": "code", "source": [ "# Si se tiene dudas respecto al funcionamiento de cualquier objeto\n", "?%lsmagic\n" ], "execution_count": 0, "outputs": [] }, { "metadata": { "id": "8EXnLf-CRJIp", "colab_type": "code", "colab": {} }, "cell_type": "code", "source": [ "?pd" ], "execution_count": 0, "outputs": [] }, { "metadata": { "id": "wjrgUr7_RQGj", "colab_type": "code", "outputId": "44412b1f-ed12-4081-97e1-4f732afec10d", "colab": { "base_uri": "https://localhost:8080/", "height": 51 } }, "cell_type": "code", "source": [ "#También se puede hacer uso de los comandos del sistema\n", "!ls -l -h" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "total 4.0K\n", "drwxr-xr-x 2 root root 4.0K Nov 29 18:21 sample_data\n" ], "name": "stdout" } ] }, { "metadata": { "id": "CJ2gsg3zRSuF", "colab_type": "code", "outputId": "a08d1621-90d6-4dc1-d33f-b121f2cde318", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "cell_type": "code", "source": [ "#Se pide ver la dirección o ubicación de trabajo\n", "!pwd" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "/content\n" ], "name": "stdout" } ] }, { "metadata": { "id": "4OpxBZMyt-RS", "colab_type": "code", "outputId": "ae56bc11-d799-4bbf-ada1-aa8c1918f2de", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "cell_type": "code", "source": [ "# Igual que el anterior pero usando un mag-comm\n", "%pwd" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "'/content'" ] }, "metadata": { "tags": [] }, "execution_count": 9 } ] }, { "metadata": { "id": "ODDPu3BwWeAJ", "colab_type": "code", "outputId": "23f9f2cd-2666-4149-f564-c2425a4c27f1", "colab": { "base_uri": "https://localhost:8080/", "height": 651 } }, "cell_type": "code", "source": [ "#Para ver los procesos que se ejecutan \n", "!top" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "\u001b[?1h\u001b=\u001b[H\u001b[2J\u001b[mtop - 00:22:58 up 1:11, 0 users, load average: 0.00, 0.01, 0.00\u001b[m\u001b[m\u001b[m\u001b[m\u001b[K\n", "Tasks:\u001b[m\u001b[m\u001b[1m 11 \u001b[m\u001b[mtotal,\u001b[m\u001b[m\u001b[1m 1 \u001b[m\u001b[mrunning,\u001b[m\u001b[m\u001b[1m 10 \u001b[m\u001b[msleeping,\u001b[m\u001b[m\u001b[1m 0 \u001b[m\u001b[mstopped,\u001b[m\u001b[m\u001b[1m 0 \u001b[m\u001b[mzombie\u001b[m\u001b[m\u001b[m\u001b[m\u001b[K\n", "%Cpu(s):\u001b[m\u001b[m\u001b[1m 0.5 \u001b[m\u001b[mus,\u001b[m\u001b[m\u001b[1m 0.3 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\u001b[m\u001b[m\u001b[K\n", "\u001b[m 1 root 20 0 39196 6312 4828 S 0.0 0.0 0:00.05 run.sh \u001b[m\u001b[m\u001b[K\n", "\u001b[m 7 root 20 0 679236 44192 24428 S 0.0 0.3 0:01.15 node \u001b[m\u001b[m\u001b[K\n", "\u001b[m 28 root 20 0 683112 55048 24980 S 0.0 0.4 0:03.21 node \u001b[m\u001b[m\u001b[K\n", "\u001b[m 53 root 20 0 187712 58848 12520 S 0.0 0.4 0:05.01 jupyter-+ \u001b[m\u001b[m\u001b[K\n", "\u001b[m 60 root 20 0 783272 206804 40060 S 0.0 1.6 0:06.78 python3 \u001b[m\u001b[m\u001b[K\n", "\u001b[m 82 root 20 0 54376 14556 7516 S 0.0 0.1 0:00.07 python3 \u001b[m\u001b[m\u001b[K\n", "\u001b[m 108 root 20 0 711676 135524 39976 S 0.0 1.0 0:02.46 python3 \u001b[m\u001b[m\u001b[K\n", "\u001b[m 124 root 20 0 54376 14572 7536 S 0.0 0.1 0:00.06 python3 \u001b[m\u001b[m\u001b[K\n", "\u001b[m 188 root 20 0 720332 136040 40020 S 0.0 1.0 0:02.35 python3 \u001b[m\u001b[m\u001b[K\n", "\u001b[m 204 root 20 0 54376 14532 7496 S 0.0 0.1 0:00.07 python3 \u001b[m\u001b[m\u001b[K\n", 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jupyter-+ \u001b[m\u001b[m\u001b[K\n", "\u001b[m 60 root 20 0 783272 206804 40060 S 0.0 1.6 0:06.78 python3 \u001b[m\u001b[m\u001b[K\n", "\u001b[m 82 root 20 0 54376 14556 7516 S 0.0 0.1 0:00.07 python3 \u001b[m\u001b[m\u001b[K\n", "\u001b[m 108 root 20 0 711676 135524 39976 S 0.0 1.0 0:02.46 python3 \u001b[m\u001b[m\u001b[K\n", "\u001b[m 124 root 20 0 54376 14572 7536 S 0.0 0.1 0:00.06 python3 \u001b[m\u001b[m\u001b[K\n", "\n", "\n", "\u001b[J\u001b[?1l\u001b>\u001b[25;1H\n", "\u001b[K" ], "name": "stdout" } ] }, { "metadata": { "id": "NTot73uKR4_r", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Estos comandos por simples que parecen ayudan a concentrarte en tu código y hacer más fluido tu trabajo.\n", "\n", "Se pueden desarrollar tus propios \"Magic commands\".Ejemplos de otros fuera de los estandar son los siguientes proyectos:\n", " \n", " * [sparkmagic](https://github.com/jupyter-incubator/sparkmagic).\n", " * [toree](http://toree.apache.org/docs/current/user/quick-start/).\n", " * [Fortran Magic](https://pypi.org/project/fortran-magic/).\n", " \n", "\n", "El siguiente ejemplo trata de ilustrar un problema común, tener un error y tratar de entender la secuencia de errores. Para eso se puede usar un magic commands que nos dice donde está el origen de nuestro problema." ] }, { "metadata": { "id": "6FS_n5GTRvHf", "colab_type": "code", "outputId": "fabe6b86-fced-45c8-9d4a-796babd3f447", "colab": { "base_uri": "https://localhost:8080/", "height": 904 } }, "cell_type": "code", "source": [ "#Tratamos de correr un test de pandas\n", "pd.test()" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "running: pytest --skip-slow --skip-network /usr/local/lib/python3.6/dist-packages/pandas\n", "============================= test session starts ==============================\n", "platform linux -- Python 3.6.7, pytest-3.10.1, py-1.7.0, pluggy-0.8.0\n", "rootdir: /usr/local/lib/python3.6/dist-packages/pandas, inifile:\n", "collected 0 items / 1 errors\n", "\n", "==================================== ERRORS ====================================\n", "______________________________ ERROR collecting _______________________________\n", "/usr/local/lib/python3.6/dist-packages/_pytest/config/__init__.py:430: in _importconftest\n", " return self._conftestpath2mod[conftestpath]\n", "E KeyError: local('/usr/local/lib/python3.6/dist-packages/pandas/tests/io/conftest.py')\n", "\n", "During handling of the above exception, another exception occurred:\n", "/usr/local/lib/python3.6/dist-packages/_pytest/config/__init__.py:436: in _importconftest\n", " mod = conftestpath.pyimport()\n", "/usr/local/lib/python3.6/dist-packages/py/_path/local.py:668: in pyimport\n", " __import__(modname)\n", "/usr/local/lib/python3.6/dist-packages/_pytest/assertion/rewrite.py:294: in load_module\n", " six.exec_(co, mod.__dict__)\n", "/usr/local/lib/python3.6/dist-packages/pandas/tests/io/conftest.py:3: in \n", " import moto\n", "E ModuleNotFoundError: No module named 'moto'\n", "\n", "During handling of the above exception, another exception occurred:\n", "/usr/local/lib/python3.6/dist-packages/py/_path/common.py:377: in visit\n", " for x in Visitor(fil, rec, ignore, bf, sort).gen(self):\n", "/usr/local/lib/python3.6/dist-packages/py/_path/common.py:429: in gen\n", " for p in self.gen(subdir):\n", "/usr/local/lib/python3.6/dist-packages/py/_path/common.py:418: in gen\n", " dirs = self.optsort([p for p in entries\n", "/usr/local/lib/python3.6/dist-packages/py/_path/common.py:419: in \n", " if p.check(dir=1) and (rec is None or rec(p))])\n", "/usr/local/lib/python3.6/dist-packages/_pytest/main.py:601: in _recurse\n", " ihook = self.gethookproxy(dirpath)\n", "/usr/local/lib/python3.6/dist-packages/_pytest/main.py:418: in gethookproxy\n", " my_conftestmodules = pm._getconftestmodules(fspath)\n", "/usr/local/lib/python3.6/dist-packages/_pytest/config/__init__.py:414: in _getconftestmodules\n", " mod = self._importconftest(conftestpath)\n", "/usr/local/lib/python3.6/dist-packages/_pytest/config/__init__.py:453: in _importconftest\n", " raise ConftestImportFailure(conftestpath, sys.exc_info())\n", "E _pytest.config.ConftestImportFailure: (local('/usr/local/lib/python3.6/dist-packages/pandas/tests/io/conftest.py'), (, ModuleNotFoundError(\"No module named 'moto'\",), ))\n", "!!!!!!!!!!!!!!!!!!! Interrupted: 1 errors during collection !!!!!!!!!!!!!!!!!!!!\n", "=========================== 1 error in 0.64 seconds ============================\n" ], "name": "stdout" }, { "output_type": "error", "ename": "SystemExit", "evalue": "ignored", "traceback": [ "An exception has occurred, use %tb to see the full traceback.\n", "\u001b[0;31mSystemExit\u001b[0m\u001b[0;31m:\u001b[0m 2\n" ] }, { "output_type": "stream", "text": [ "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py:2890: UserWarning: To exit: use 'exit', 'quit', or Ctrl-D.\n", " warn(\"To exit: use 'exit', 'quit', or Ctrl-D.\", stacklevel=1)\n" ], "name": "stderr" } ] }, { "metadata": { "id": "zQh1RhlpXnf7", "colab_type": "code", "outputId": "739b6d31-d532-405d-94e5-b3a998691857", "colab": { "base_uri": "https://localhost:8080/", "height": 284 } }, "cell_type": "code", "source": [ "# Pedimos ver la trata o razón de nuestro problema.\n", "%tb" ], "execution_count": 0, "outputs": [ { "output_type": "error", "ename": "SystemExit", "evalue": "ignored", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mSystemExit\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[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtest\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[0;32m/usr/local/lib/python3.6/dist-packages/pandas/util/_tester.py\u001b[0m in \u001b[0;36mtest\u001b[0;34m(extra_args)\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[0mcmd\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mPKG\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"running: pytest {}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m' '\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcmd\u001b[0m\u001b[0;34m)\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;32m---> 22\u001b[0;31m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpytest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcmd\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 23\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 24\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mSystemExit\u001b[0m: 2" ] } ] }, { "metadata": { "id": "aqDzo_MNvetW", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Para conocer más respecto a las funcionalidades de Jupyter o IPython se puede revisar la siguiente liga:\n", "\n", "* https://ipython.readthedocs.io/en/stable/index.html" ] }, { "metadata": { "id": "1ESjhXuWZp2R", "colab_type": "text" }, "cell_type": "markdown", "source": [ "## Pandas en 10 minutos (... y alta velocidad)\n", "\n", "Pandas es una biblioteca de alto performance para la manipulación y procesamiento de datos estructurados.\n", "\n", "Consiste en general de los siguientes elementos:\n", "\n", "* Dos tipos de objetos principales: Series y DataFrames.\n", "* Indexación de los ejes simples como la multi - nivel y jerárquica.\n", "* Operaciones optimizadas para crear agrupaciones y transformaciones en los datos.\n", "* Capacidad para generar rangos de fechas con total facilidad para ser modificadas a conveniencia.\n", "* Herramientas para Input/Output de archivos con diversos formatos y tecnologías.\n", "* Eficiente administración de memoria. Capacidad para generar estructuras \"sparse\" para hacer más eficiente el procesamiento de los datos.\n", "* Funciones y herramientas para hacer estadistica sobre los datos.\n", "\n", "Las dos estructuras de datos fundamentales en Pandas son:\n", "\n", "* Series: arrays de 1D con tipos de datos homogeneos.\n", "* DataFrame: \tarrays 2D, objetos con estructura tabular de tamaño mutable y con la capacidad de tener columnas de tipos heterogenios.\n", "\n", "Una idea para entender a relación entre los objetos en Pandas es pensarlos como estructuras o contenedores de estructuras de datos menores dimensiones. Los Dataframes se pueden pensar como contenedores de Series y las Series como contenedores de números o cadenas.\n", "\n", "**Nota Avanzada: ** Todos los objetos en Pandas son mutables ( los valores que contienen pueden ser alterados). Pero todos los métodos o funciones producen nuevos objetos y dejan los objetos iniciales sin cambios.\n" ] }, { "metadata": { "id": "zDN_M-Raf_xd", "colab_type": "text" }, "cell_type": "markdown", "source": [ "El siguiente \"tour\" en Pandas es una versión de la que se puede encontrar en la página oficial:\n", "\n", "* [10 minutes to pandas](http://pandas.pydata.org/pandas-docs/stable/10min.html)" ] }, { "metadata": { "id": "dVGRwvBfYL3i", "colab_type": "code", "colab": {} }, "cell_type": "code", "source": [ "# Se modifica el entorno para hacer más \n", "# rápida la revisión\n", "\n", "from IPython.core.interactiveshell import InteractiveShell\n", "\n", "InteractiveShell.ast_node_interactivity = \"all\"\n", " \n", "%matplotlib inline\n", "\n", "import matplotlib.pyplot as plt" ], "execution_count": 0, "outputs": [] }, { "metadata": { "id": "CRda0FpPgkNf", "colab_type": "text" }, "cell_type": "markdown", "source": [ "### Series y DataFrames\n", "\n", "Se define una Serie y un DataFrame" ] }, { "metadata": { "id": "-GBO1xUUgi03", "colab_type": "code", "outputId": "e795404d-06e8-4e54-95ed-b0445f2b6a06", "colab": { "base_uri": "https://localhost:8080/", "height": 354 } }, "cell_type": "code", "source": [ "#Se define la serie s\n", "s = pd.Series([1,3,5,np.nan,6,8])\n", "dates = pd.date_range('20130101', periods=6)\n", "\n", "#Se define un DataFrame\n", "df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))\n", "\n", "#Se visualizan\n", "s\n", "df\n" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "0 1.0\n", "1 3.0\n", "2 5.0\n", "3 NaN\n", "4 6.0\n", "5 8.0\n", "dtype: float64" ] }, "metadata": { "tags": [] }, "execution_count": 16 }, { "output_type": "execute_result", "data": { "text/html": [ "
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ABCD
2013-01-01-2.662312-0.930931-1.0690791.103445
2013-01-022.770103-0.032381-0.1143390.289050
2013-01-03-0.742892-1.4259460.994186-0.266048
2013-01-04-0.891284-0.695291-0.9245491.942704
2013-01-050.4266660.3809990.486457-1.035013
2013-01-06-0.2117960.3510171.557697-1.496206
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" ], "text/plain": [ " A B C D\n", "2013-01-01 -2.662312 -0.930931 -1.069079 1.103445\n", "2013-01-02 2.770103 -0.032381 -0.114339 0.289050\n", "2013-01-03 -0.742892 -1.425946 0.994186 -0.266048\n", "2013-01-04 -0.891284 -0.695291 -0.924549 1.942704\n", "2013-01-05 0.426666 0.380999 0.486457 -1.035013\n", "2013-01-06 -0.211796 0.351017 1.557697 -1.496206" ] }, "metadata": { "tags": [] }, "execution_count": 16 } ] }, { "metadata": { "id": "4peBgG2qxMt6", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Se crea otro DataFrame, pero como ejemplo se muestra como crearlo con diferentes tipos de datos." ] }, { "metadata": { "id": "YM5-Vv6Sg3Xi", "colab_type": "code", "outputId": "ad3746b8-4eaf-4474-bb2b-b98554faebe0", "colab": { "base_uri": "https://localhost:8080/", "height": 566 } }, "cell_type": "code", "source": [ "#Se crea el DF con diferentes tipos de Series\n", "df2 = pd.DataFrame({ 'A' : 1.,\n", " 'B' : pd.Timestamp('20130102'),\n", " 'C' : pd.Series(1,index=list(range(4)),dtype='float32'),\n", " 'D' : np.array([3] * 4,dtype='int32'),\n", " 'E' : pd.Categorical([\"test\",\"train\",\"test\",\"train\"]),\n", " 'F' : 'foo' })\n", "\n", "print(\"Se visualiza el DF\")\n", "\n", "df2\n", "\n", "print(\"=\"*50)\n", "print(\"¿Qué tipo de datos tiene?\")\n", "\n", "df2.dtypes\n", "#Para tener un resumen completo del DF\n", "print()\n", "print(\"=\"*50)\n", "print(\"Resumen\")\n", "df2.info()" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "Se visualiza el DF\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/html": [ "
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" ], "text/plain": [ " A B C D E F\n", "0 1.0 2013-01-02 1.0 3 test foo\n", "1 1.0 2013-01-02 1.0 3 train foo\n", "2 1.0 2013-01-02 1.0 3 test foo\n", "3 1.0 2013-01-02 1.0 3 train foo" ] }, "metadata": { "tags": [] }, "execution_count": 17 }, { "output_type": "stream", "text": [ "==================================================\n", "¿Qué tipo de datos tiene?\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "A float64\n", "B datetime64[ns]\n", "C float32\n", "D int32\n", "E category\n", "F object\n", "dtype: object" ] }, "metadata": { "tags": [] }, "execution_count": 17 }, { "output_type": "stream", "text": [ "\n", "==================================================\n", "Resumen\n", "\n", "Int64Index: 4 entries, 0 to 3\n", "Data columns (total 6 columns):\n", "A 4 non-null float64\n", "B 4 non-null datetime64[ns]\n", "C 4 non-null float32\n", "D 4 non-null int32\n", "E 4 non-null category\n", "F 4 non-null object\n", "dtypes: category(1), datetime64[ns](1), float32(1), float64(1), int32(1), object(1)\n", "memory usage: 260.0+ bytes\n" ], "name": "stdout" } ] }, { "metadata": { "id": "syXsxppyyWAy", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Para un DataFrame largo, es recomendable visualizar solo algunas filas." ] }, { "metadata": { "id": "BsCalx_FhUH-", "colab_type": "code", "outputId": "93a5ffeb-b02f-4320-868f-fb3d93485d75", "colab": { "base_uri": "https://localhost:8080/", "height": 265 } }, "cell_type": "code", "source": [ "#Se muestran las 3 primeras filas\n", "df.head(3)\n", "#Se muestran las 3 últimas filas\n", "df.tail(3)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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ABCD
2013-01-01-2.662312-0.930931-1.0690791.103445
2013-01-022.770103-0.032381-0.1143390.289050
2013-01-03-0.742892-1.4259460.994186-0.266048
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ABCD
2013-01-04-0.891284-0.695291-0.9245491.942704
2013-01-050.4266660.3809990.486457-1.035013
2013-01-06-0.2117960.3510171.557697-1.496206
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" ], "text/plain": [ " A B C D\n", "2013-01-04 -0.891284 -0.695291 -0.924549 1.942704\n", "2013-01-05 0.426666 0.380999 0.486457 -1.035013\n", "2013-01-06 -0.211796 0.351017 1.557697 -1.496206" ] }, "metadata": { "tags": [] }, "execution_count": 18 } ] }, { "metadata": { "id": "EC5CQEk-yxEb", "colab_type": "text" }, "cell_type": "markdown", "source": [ "### Relación Pandas y NumPy\n", "\n", "De manera general, todo DataFrame tiene 3 elementos: index, columnas y valores." ] }, { "metadata": { "id": "dbnvZnSshl2E", "colab_type": "code", "outputId": "f05eac68-894a-4055-d35c-18f13261bbe3", "colab": { "base_uri": "https://localhost:8080/", "height": 257 } }, "cell_type": "code", "source": [ "#Se visualizan los índices\n", "df.index\n", "print(\"\\n\")\n", "#Se revisan las columnas\n", "print(\"Columndas\\n\")\n", "df.columns\n", "\n", "#Se visualizan los valores\n", "print(\"\\n\")\n", "df.values" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04',\n", " '2013-01-05', '2013-01-06'],\n", " dtype='datetime64[ns]', freq='D')" ] }, "metadata": { "tags": [] }, "execution_count": 19 }, { "output_type": "stream", "text": [ "\n", "\n", "Columndas\n", "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "Index(['A', 'B', 'C', 'D'], dtype='object')" ] }, "metadata": { "tags": [] }, "execution_count": 19 }, { "output_type": "stream", "text": [ "\n", "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "array([[-2.66231197, -0.93093083, -1.06907874, 1.10344508],\n", " [ 2.77010318, -0.03238136, -0.11433878, 0.28905019],\n", " [-0.74289222, -1.42594597, 0.99418636, -0.26604766],\n", " [-0.89128408, -0.69529057, -0.92454875, 1.94270435],\n", " [ 0.4266665 , 0.38099875, 0.48645678, -1.03501286],\n", " [-0.2117956 , 0.35101741, 1.55769736, -1.49620624]])" ] }, "metadata": { "tags": [] }, "execution_count": 19 } ] }, { "metadata": { "id": "-S8u8vTVzgJb", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Los comandos anteriores muestran la relación que existe entre Numpy y Pandas. " ] }, { "metadata": { "id": "TlqWPQj-z0_9", "colab_type": "code", "outputId": "fd5bbebf-5ebb-4059-d331-7faf5b50bd9f", "colab": { "base_uri": "https://localhost:8080/", "height": 68 } }, "cell_type": "code", "source": [ "type(df.index)\n", "print()\n", "type(df.columns)\n", "print()\n", "type(df.values)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "pandas.core.indexes.datetimes.DatetimeIndex" ] }, "metadata": { "tags": [] }, "execution_count": 20 }, { "output_type": "stream", "text": [ "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "pandas.core.indexes.base.Index" ] }, "metadata": { "tags": [] }, "execution_count": 20 }, { "output_type": "stream", "text": [ "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "numpy.ndarray" ] }, "metadata": { "tags": [] }, "execution_count": 20 } ] }, { "metadata": { "id": "QTHYq3sY0Mkq", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Se observa que el tipo de dato que para los valores de un DataFrame es un arreglo o array de Numpy. Entonces, eso implica que toda función que tiene un arreglo en Numpy la hereda un DataFrame." ] }, { "metadata": { "id": "HFT91F760gj3", "colab_type": "code", "outputId": "5e69f228-05e2-4b82-b382-9cb0a1f27a21", "colab": { "base_uri": "https://localhost:8080/", "height": 51 } }, "cell_type": "code", "source": [ "df.values.argmax()\n", "print()\n", "df.values.diagonal()\n" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "7" ] }, "metadata": { "tags": [] }, "execution_count": 35 }, { "output_type": "stream", "text": [ "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "array([-0.05463496, 0.40983999, -1.13152355, -0.44288347])" ] }, "metadata": { "tags": [] }, "execution_count": 35 } ] }, { "metadata": { "id": "56goVFeB06mg", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Lo mismo ocurre con las series." ] }, { "metadata": { "id": "pFzDNCr707sA", "colab_type": "code", "outputId": "35ece473-94d4-4e3e-e85d-6f4300b9afcf", "colab": { "base_uri": "https://localhost:8080/", "height": 51 } }, "cell_type": "code", "source": [ "type(s)\n", "print()\n", "type(s.values)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "pandas.core.series.Series" ] }, "metadata": { "tags": [] }, "execution_count": 38 }, { "output_type": "stream", "text": [ "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "numpy.ndarray" ] }, "metadata": { "tags": [] }, "execution_count": 38 } ] }, { "metadata": { "id": "3Ajx_9Y41K1c", "colab_type": "text" }, "cell_type": "markdown", "source": [ "### Exploración\n", "\n", "Algunas funciones útiles para explora los datos del DataFrame son las siguientes:" ] }, { "metadata": { "id": "cnYrg8ENhby8", "colab_type": "code", "outputId": "5c93e9cb-9d12-408e-da09-88be230f2343", "colab": { "base_uri": "https://localhost:8080/", "height": 295 } }, "cell_type": "code", "source": [ "#Se pide la estádistica básica\n", "df.describe()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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ABCD
count6.0000006.0000006.0000006.000000
mean0.4694520.142528-0.7650560.125801
std0.7932820.8793750.6360241.171310
min-0.797758-1.191412-1.604023-1.657919
25%0.044665-0.090017-1.137977-0.418734
50%0.6661540.127492-0.8724360.128347
75%1.0992340.349461-0.1947100.920442
max1.2010681.530666-0.0461491.572652
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" ], "text/plain": [ " A B C D\n", "count 6.000000 6.000000 6.000000 6.000000\n", "mean 0.469452 0.142528 -0.765056 0.125801\n", "std 0.793282 0.879375 0.636024 1.171310\n", "min -0.797758 -1.191412 -1.604023 -1.657919\n", "25% 0.044665 -0.090017 -1.137977 -0.418734\n", "50% 0.666154 0.127492 -0.872436 0.128347\n", "75% 1.099234 0.349461 -0.194710 0.920442\n", "max 1.201068 1.530666 -0.046149 1.572652" ] }, "metadata": { "tags": [] }, "execution_count": 39 } ] }, { "metadata": { "id": "DTF6lVyihzHx", "colab_type": "code", "outputId": "76e53e7c-19ba-42fe-e17c-11b161e94ac0", "colab": { "base_uri": "https://localhost:8080/", "height": 450 } }, "cell_type": "code", "source": [ "#Quizás se necesita ordenar los datos\n", "# de algun modo. \n", "df.sort_index(axis=1, ascending=False)\n", "df.sort_values(by='B')" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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DCBA
2013-01-01-1.657919-1.1401280.168322-0.054635
2013-01-021.572652-0.6133490.4098400.342567
2013-01-030.602979-1.131524-0.148911-0.797758
2013-01-04-0.442883-1.6040231.5306661.135732
2013-01-05-0.346286-0.046149-1.1914121.201068
2013-01-061.026263-0.0551640.0866620.989741
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ABCD
2013-01-051.201068-1.191412-0.046149-0.346286
2013-01-03-0.797758-0.148911-1.1315240.602979
2013-01-060.9897410.086662-0.0551641.026263
2013-01-01-0.0546350.168322-1.140128-1.657919
2013-01-020.3425670.409840-0.6133491.572652
2013-01-041.1357321.530666-1.604023-0.442883
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" ], "text/plain": [ " A B C D\n", "2013-01-05 1.201068 -1.191412 -0.046149 -0.346286\n", "2013-01-03 -0.797758 -0.148911 -1.131524 0.602979\n", "2013-01-06 0.989741 0.086662 -0.055164 1.026263\n", "2013-01-01 -0.054635 0.168322 -1.140128 -1.657919\n", "2013-01-02 0.342567 0.409840 -0.613349 1.572652\n", "2013-01-04 1.135732 1.530666 -1.604023 -0.442883" ] }, "metadata": { "tags": [] }, "execution_count": 40 } ] }, { "metadata": { "id": "luC3UaJj1tB8", "colab_type": "text" }, "cell_type": "markdown", "source": [ "### Álgebra Lineal\n", "\n", "Si bien los DataFrame son arreglos de dos dimensiones y su valores son un array de Numpy. Por consecuencia las operaciones de matrices pueden ser aplicables." ] }, { "metadata": { "id": "E9uY6xRS17Rb", "colab_type": "code", "outputId": "6d11b198-1e40-4778-ba31-df69ad790c95", "colab": { "base_uri": "https://localhost:8080/", "height": 240 } }, "cell_type": "code", "source": [ "#Se estima la transpuesta\n", "df.T\n", "print()\n", "df.values.diagonal()\n", "print()\n", "df.values.max()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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2013-01-01 00:00:002013-01-02 00:00:002013-01-03 00:00:002013-01-04 00:00:002013-01-05 00:00:002013-01-06 00:00:00
A-0.0546350.342567-0.7977581.1357321.2010680.989741
B0.1683220.409840-0.1489111.530666-1.1914120.086662
C-1.140128-0.613349-1.131524-1.604023-0.046149-0.055164
D-1.6579191.5726520.602979-0.442883-0.3462861.026263
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" ], "text/plain": [ " 2013-01-01 2013-01-02 2013-01-03 2013-01-04 2013-01-05 2013-01-06\n", "A -0.054635 0.342567 -0.797758 1.135732 1.201068 0.989741\n", "B 0.168322 0.409840 -0.148911 1.530666 -1.191412 0.086662\n", "C -1.140128 -0.613349 -1.131524 -1.604023 -0.046149 -0.055164\n", "D -1.657919 1.572652 0.602979 -0.442883 -0.346286 1.026263" ] }, "metadata": { "tags": [] }, "execution_count": 42 }, { "output_type": "stream", "text": [ "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "array([-0.05463496, 0.40983999, -1.13152355, -0.44288347])" ] }, "metadata": { "tags": [] }, "execution_count": 42 }, { "output_type": "stream", "text": [ "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "1.5726523256536802" ] }, "metadata": { "tags": [] }, "execution_count": 42 } ] }, { "metadata": { "id": "dFcv0_gn2VlH", "colab_type": "text" }, "cell_type": "markdown", "source": [ "En los comandos anteriores se pide la transpuesta del DataFrame, la cual es una operacion diferentes a la siguiente:" ] }, { "metadata": { "id": "n5uX_Oed2SgH", "colab_type": "code", "outputId": "63c4118b-b956-4cc5-c194-7cc42dcd9716", "colab": { "base_uri": "https://localhost:8080/", "height": 154 } }, "cell_type": "code", "source": [ "#¿cuál es la diferencia con df.T?\n", "df.values.T" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "array([[-0.05463496, 0.34256677, -0.79775845, 1.13573175, 1.20106755,\n", " 0.98974133],\n", " [ 0.16832219, 0.40983999, -0.14891052, 1.53066581, -1.19141211,\n", " 0.08666247],\n", " [-1.14012769, -0.61334922, -1.13152355, -1.60402263, -0.04614857,\n", " -0.05516379],\n", " [-1.65791871, 1.57265233, 0.60297925, -0.44288347, -0.34628572,\n", " 1.02626349]])" ] }, "metadata": { "tags": [] }, "execution_count": 43 } ] }, { "metadata": { "id": "NVyjNYck8glJ", "colab_type": "text" }, "cell_type": "markdown", "source": [ "### Selección de Columnas y Filas\n", "\n", "Como se mencionó, los objetos de Pandas son mutables. En el sentido de que pueden ser modificados, por lo cual se puede seleccionar solo las columnas o parte de los datos que a uno le interesan.\n", "\n", "La selección de columnas y filas tiene 3 modos de ser realizada:\n", "* Slicing\n", "* Referencia \n", "* Posición\n", "\n", "*¿Por qué tantos modos de hacer lo **mismo**?*" ] }, { "metadata": { "id": "wuMDMOm8iYhu", "colab_type": "code", "outputId": "8bad441a-a16d-4c20-fcc0-5f5ca3f93327", "colab": { "base_uri": "https://localhost:8080/", "height": 385 } }, "cell_type": "code", "source": [ "#Por slicing\n", "df['A']\n", "df[0:3]\n", "df['20130102':'20130104']\n" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "2013-01-01 -0.054635\n", "2013-01-02 0.342567\n", "2013-01-03 -0.797758\n", "2013-01-04 1.135732\n", "2013-01-05 1.201068\n", "2013-01-06 0.989741\n", "Freq: D, Name: A, dtype: float64" ] }, "metadata": { "tags": [] }, "execution_count": 48 }, { "output_type": "execute_result", "data": { "text/html": [ "
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ABCD
2013-01-01-0.0546350.168322-1.140128-1.657919
2013-01-020.3425670.409840-0.6133491.572652
2013-01-03-0.797758-0.148911-1.1315240.602979
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" ], "text/plain": [ " A B C D\n", "2013-01-01 -0.054635 0.168322 -1.140128 -1.657919\n", "2013-01-02 0.342567 0.409840 -0.613349 1.572652\n", "2013-01-03 -0.797758 -0.148911 -1.131524 0.602979" ] }, "metadata": { "tags": [] }, "execution_count": 48 }, { "output_type": "execute_result", "data": { "text/html": [ "
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ABCD
2013-01-020.3425670.409840-0.6133491.572652
2013-01-03-0.797758-0.148911-1.1315240.602979
2013-01-041.1357321.530666-1.604023-0.442883
\n", "
" ], "text/plain": [ " A B C D\n", "2013-01-02 0.342567 0.409840 -0.613349 1.572652\n", "2013-01-03 -0.797758 -0.148911 -1.131524 0.602979\n", "2013-01-04 1.135732 1.530666 -1.604023 -0.442883" ] }, "metadata": { "tags": [] }, "execution_count": 48 } ] }, { "metadata": { "id": "i31ONFvB9dKZ", "colab_type": "code", "colab": {} }, "cell_type": "code", "source": [ "#Por referencia\n", "df.loc[dates[0]]\n", "df.loc[:,['A','B']]\n", "df.loc['20130102':'20130104',['A','B']]\n", "df.loc['20130102',['A','B']]" ], "execution_count": 0, "outputs": [] }, { "metadata": { "id": "TyAQdOi5i3yp", "colab_type": "code", "outputId": "f260a3bf-45ef-41a0-fa5a-fe44284e9ea1", "colab": { "base_uri": "https://localhost:8080/", "height": 51 } }, "cell_type": "code", "source": [ "#¿Cuál es la diferencia?\n", "df.loc[dates[0],'A']\n", "\n", "print()\n", "\n", "df.at[dates[0],'A']\n" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "1.3604942373447584" ] }, "metadata": { "tags": [] }, "execution_count": 40 }, { "output_type": "stream", "text": [ "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "1.3604942373447584" ] }, "metadata": { "tags": [] }, "execution_count": 40 } ] }, { "metadata": { "id": "m_0M59iki_oD", "colab_type": "code", "outputId": "08c7dde5-4824-4187-f598-328f49027d2b", "colab": { "base_uri": "https://localhost:8080/", "height": 630 } }, "cell_type": "code", "source": [ "#Por posición\n", "df.iloc[3]\n", "df.iloc[3:5,0:2]\n", "df.iloc[[1,2,4],[0,2]]\n", "df.iloc[1:3,:]\n", "df.iloc[:,1:3]\n" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "A 1.135732\n", "B 1.530666\n", "C -1.604023\n", "D -0.442883\n", "Name: 2013-01-04 00:00:00, dtype: float64" ] }, "metadata": { "tags": [] }, "execution_count": 49 }, { "output_type": "execute_result", "data": { "text/html": [ "
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AB
2013-01-041.1357321.530666
2013-01-051.201068-1.191412
\n", "
" ], "text/plain": [ " A B\n", "2013-01-04 1.135732 1.530666\n", "2013-01-05 1.201068 -1.191412" ] }, "metadata": { "tags": [] }, "execution_count": 49 }, { "output_type": "execute_result", "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
AC
2013-01-020.342567-0.613349
2013-01-03-0.797758-1.131524
2013-01-051.201068-0.046149
\n", "
" ], "text/plain": [ " A C\n", "2013-01-02 0.342567 -0.613349\n", "2013-01-03 -0.797758 -1.131524\n", "2013-01-05 1.201068 -0.046149" ] }, "metadata": { "tags": [] }, "execution_count": 49 }, { "output_type": "execute_result", "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ABCD
2013-01-020.3425670.409840-0.6133491.572652
2013-01-03-0.797758-0.148911-1.1315240.602979
\n", "
" ], "text/plain": [ " A B C D\n", "2013-01-02 0.342567 0.409840 -0.613349 1.572652\n", "2013-01-03 -0.797758 -0.148911 -1.131524 0.602979" ] }, "metadata": { "tags": [] }, "execution_count": 49 }, { "output_type": "execute_result", "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
BC
2013-01-010.168322-1.140128
2013-01-020.409840-0.613349
2013-01-03-0.148911-1.131524
2013-01-041.530666-1.604023
2013-01-05-1.191412-0.046149
2013-01-060.086662-0.055164
\n", "
" ], "text/plain": [ " B C\n", "2013-01-01 0.168322 -1.140128\n", "2013-01-02 0.409840 -0.613349\n", "2013-01-03 -0.148911 -1.131524\n", "2013-01-04 1.530666 -1.604023\n", "2013-01-05 -1.191412 -0.046149\n", "2013-01-06 0.086662 -0.055164" ] }, "metadata": { "tags": [] }, "execution_count": 49 } ] }, { "metadata": { "id": "zK39zVhJ-SsI", "colab_type": "code", "outputId": "a8c286f8-c9fb-4ba6-8aee-4b2ab8f364d6", "colab": { "base_uri": "https://localhost:8080/", "height": 51 } }, "cell_type": "code", "source": [ "#¿Cuál es la diferencia?\n", "df.iloc[1,1]\n", "print()\n", "df.iat[1,1]" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "0.4098399942252009" ] }, "metadata": { "tags": [] }, "execution_count": 50 }, { "output_type": "stream", "text": [ "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "0.4098399942252009" ] }, "metadata": { "tags": [] }, "execution_count": 50 } ] }, { "metadata": { "id": "PNQwsfNx-2EF", "colab_type": "text" }, "cell_type": "markdown", "source": [ "### Condiciones Lógicas\n", "\n", "Cuando se manipulan datos resulta lógico hacer pregunta \"lógicas\" o comparativos, como desear saber cuantos elementos cumplen una condición, por ejemplo:\n", "\n", "~~~python\n", "#Cuantos elementos tienen valor\n", "# mayor a cero\n", "\n", "df.C>0\n", "\n", "~~~\n", "\n", "Para ayudar con este tipo de casos, se tienen la selección por índices booleanos." ] }, { "metadata": { "id": "NtA3JQYz_lbP", "colab_type": "code", "outputId": "61f45bf7-623b-468a-cdb0-a0d663669300", "colab": { "base_uri": "https://localhost:8080/", "height": 340 } }, "cell_type": "code", "source": [ "#Se visualizan los datos\n", "df.head()\n", "\n", "print()\n", "#La condicion a pedir\n", "df.D>0" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ABCD
2013-01-01-0.0546350.168322-1.140128-1.657919
2013-01-020.3425670.409840-0.6133491.572652
2013-01-03-0.797758-0.148911-1.1315240.602979
2013-01-041.1357321.530666-1.604023-0.442883
2013-01-051.201068-1.191412-0.046149-0.346286
\n", "
" ], "text/plain": [ " A B C D\n", "2013-01-01 -0.054635 0.168322 -1.140128 -1.657919\n", "2013-01-02 0.342567 0.409840 -0.613349 1.572652\n", "2013-01-03 -0.797758 -0.148911 -1.131524 0.602979\n", "2013-01-04 1.135732 1.530666 -1.604023 -0.442883\n", "2013-01-05 1.201068 -1.191412 -0.046149 -0.346286" ] }, "metadata": { "tags": [] }, "execution_count": 55 }, { "output_type": "stream", "text": [ "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "2013-01-01 False\n", "2013-01-02 True\n", "2013-01-03 True\n", "2013-01-04 False\n", "2013-01-05 False\n", "2013-01-06 True\n", "Freq: D, Name: D, dtype: bool" ] }, "metadata": { "tags": [] }, "execution_count": 55 } ] }, { "metadata": { "id": "hEBKuD-7_qg9", "colab_type": "code", "outputId": "d2765c6a-06a1-4635-e510-c586d9fdf6e0", "colab": { "base_uri": "https://localhost:8080/", "height": 141 } }, "cell_type": "code", "source": [ "#Se eligen los que cumplen esta condición\n", "df[df.D>0]" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ABCD
2013-01-020.3425670.409840-0.6133491.572652
2013-01-03-0.797758-0.148911-1.1315240.602979
2013-01-060.9897410.086662-0.0551641.026263
\n", "
" ], "text/plain": [ " A B C D\n", "2013-01-02 0.342567 0.409840 -0.613349 1.572652\n", "2013-01-03 -0.797758 -0.148911 -1.131524 0.602979\n", "2013-01-06 0.989741 0.086662 -0.055164 1.026263" ] }, "metadata": { "tags": [] }, "execution_count": 56 } ] }, { "metadata": { "id": "RCTNXo_iAX-D", "colab_type": "text" }, "cell_type": "markdown", "source": [ "De manera similar a las codiciones lógicas en programación, se desea quizás ver que se cumplan más de una condicion. Para ello se usan los conectores lógicos." ] }, { "metadata": { "id": "26PwKgdGAnj9", "colab_type": "code", "outputId": "56689a99-8d8e-41b2-8cd8-a648c96f40e3", "colab": { "base_uri": "https://localhost:8080/", "height": 203 } }, "cell_type": "code", "source": [ "#Conector lógico \"and\"\n", "df[(df.C<-1.0)& (df.D>0)]\n", "\n", "# Conector lógico \"or\"\n", "df[(df.B<-1.0) | (df.D>1)]\n" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ABCD
2013-01-03-0.797758-0.148911-1.1315240.602979
\n", "
" ], "text/plain": [ " A B C D\n", "2013-01-03 -0.797758 -0.148911 -1.131524 0.602979" ] }, "metadata": { "tags": [] }, "execution_count": 61 }, { "output_type": "execute_result", "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ABCD
2013-01-020.3425670.409840-0.6133491.572652
2013-01-051.201068-1.191412-0.046149-0.346286
2013-01-060.9897410.086662-0.0551641.026263
\n", "
" ], "text/plain": [ " A B C D\n", "2013-01-02 0.342567 0.409840 -0.613349 1.572652\n", "2013-01-05 1.201068 -1.191412 -0.046149 -0.346286\n", "2013-01-06 0.989741 0.086662 -0.055164 1.026263" ] }, "metadata": { "tags": [] }, "execution_count": 61 } ] }, { "metadata": { "id": "VmNLeXu5DEEN", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Se puede dar el caso que solo se quiere ver aquellos elementos que son parte de un subcojunto de elementos." ] }, { "metadata": { "id": "Ul8dtu7ABc13", "colab_type": "code", "outputId": "9d0f862c-a623-42d2-9f5c-ab05226d0a63", "colab": { "base_uri": "https://localhost:8080/", "height": 203 } }, "cell_type": "code", "source": [ "#Se crea otro DataFrame y se agrega una nueva columna\n", "df2 = df.copy()\n", "\n", "df2['E'] = ['one', 'one','two','three','four','three']\n", "\n", "df2.head() " ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ABCDE
2013-01-01-0.0546350.168322-1.140128-1.657919one
2013-01-020.3425670.409840-0.6133491.572652one
2013-01-03-0.797758-0.148911-1.1315240.602979two
2013-01-041.1357321.530666-1.604023-0.442883three
2013-01-051.201068-1.191412-0.046149-0.346286four
\n", "
" ], "text/plain": [ " A B C D E\n", "2013-01-01 -0.054635 0.168322 -1.140128 -1.657919 one\n", "2013-01-02 0.342567 0.409840 -0.613349 1.572652 one\n", "2013-01-03 -0.797758 -0.148911 -1.131524 0.602979 two\n", "2013-01-04 1.135732 1.530666 -1.604023 -0.442883 three\n", "2013-01-05 1.201068 -1.191412 -0.046149 -0.346286 four" ] }, "metadata": { "tags": [] }, "execution_count": 78 } ] }, { "metadata": { "id": "jx4-JiSbC7yC", "colab_type": "code", "outputId": "96d89d98-b28b-4f34-f2f2-e35615fe7eb4", "colab": { "base_uri": "https://localhost:8080/", "height": 110 } }, "cell_type": "code", "source": [ "# De manera afirmativa\n", "df2[df2['E'].isin(['two','four'])]" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ABCDE
2013-01-03-0.797758-0.148911-1.1315240.602979two
2013-01-051.201068-1.191412-0.046149-0.346286four
\n", "
" ], "text/plain": [ " A B C D E\n", "2013-01-03 -0.797758 -0.148911 -1.131524 0.602979 two\n", "2013-01-05 1.201068 -1.191412 -0.046149 -0.346286 four" ] }, "metadata": { "tags": [] }, "execution_count": 76 } ] }, { "metadata": { "id": "TknUkq7HBsvb", "colab_type": "code", "outputId": "0cd7c8e1-5134-4010-83e5-fd98acc80ac0", "colab": { "base_uri": "https://localhost:8080/", "height": 110 } }, "cell_type": "code", "source": [ "# La condicion negativa de la anterior\n", "df2[~df2.E.isin(['one','three'])]" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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ABCDE
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" ], "text/plain": [ " A B C D E\n", "2013-01-03 -0.797758 -0.148911 -1.131524 0.602979 two\n", "2013-01-05 1.201068 -1.191412 -0.046149 -0.346286 four" ] }, "metadata": { "tags": [] }, "execution_count": 74 } ] }, { "metadata": { "id": "NCgiUk7zE6X8", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Con los anteriores ejemplos se muestra que se tiene lo necesario para construir expresiones lógicas sobre los DataFrame (and, or , not).\n", "\n", "### Cambiando datos\n", "\n", "Cuando se desea modificar un DataFrame en general, se puede eliminar una columna, agregar una nueva columna o modificar los valores actuales." ] }, { "metadata": { "id": "WJFH4WYmFazQ", "colab_type": "code", "colab": {} }, "cell_type": "code", "source": [ "#Se elimina la columna D\n", "del df2['D']" ], "execution_count": 0, "outputs": [] }, { "metadata": { "id": "4k7XsnCZFhUf", "colab_type": "code", "outputId": "027ee1a8-4ae8-4cd0-e8af-4bcdc97d05df", "colab": { "base_uri": "https://localhost:8080/", "height": 203 } }, "cell_type": "code", "source": [ "df2.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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ABCDFE
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ABCFE
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" ], "text/plain": [ " A B C F E\n", "2013-01-01 False False False True True\n", "2013-01-02 False False False False True\n", "2013-01-03 False False False False True\n", "2013-01-04 False False False False True\n", "2013-01-05 False False False False True\n", "2013-01-06 False False False False True" ] }, "metadata": { "tags": [] }, "execution_count": 108 } ] }, { "metadata": { "id": "hFUdyDJuI9H2", "colab_type": "code", "outputId": "7e68e90f-2de6-4297-dff6-540272648bef", "colab": { "base_uri": "https://localhost:8080/", "height": 234 } }, "cell_type": "code", "source": [ "df2.isna()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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ABCFE
2013-01-01FalseFalseFalseTrueTrue
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" ], "text/plain": [ " A B C F E\n", "2013-01-01 False False False True True\n", "2013-01-02 False False False False True\n", "2013-01-03 False False False False True\n", "2013-01-04 False False False False True\n", "2013-01-05 False False False False True\n", "2013-01-06 False False False False True" ] }, "metadata": { "tags": [] }, "execution_count": 109 } ] }, { "metadata": { "id": "9aawylPMKP_w", "colab_type": "text" }, "cell_type": "markdown", "source": [ "### Temas Pendientes\n", "\n", "Restan los siguientes aspectos básicos:\n", "\n", "* Estadísticos\n", "* Aplicar funciones o transformaciones sobre los datos\n", "* Operaciones entre DataFrames (merge, join)\n", "* Cambios de forma (melt y tablas pivot)\n", "* Agrupaciones\n", "* Variables tipo Categorical\n", "* Tratamiento de indices de tiempo o timestamp\n", "\n", "Se veran en otras lecciones, pero por ahora pasamos a un aspecto visual.\n" ] }, { "metadata": { "id": "fvmIiBC1_5O1", "colab_type": "text" }, "cell_type": "markdown", "source": [ "### Visualizaciones\n", "\n", "Pandas cuenta con métodos para generar un conjunto de gráficas que son las más usadas o requeridas al momento de hacer un análsis de datos, estas gráficas son originadas con las funciones de matplotlib." ] }, { "metadata": { "id": "gpBd6r0MKGz7", "colab_type": "code", "outputId": "b84b6e47-4121-44ca-9f78-89761fe6ac3b", "colab": { "base_uri": "https://localhost:8080/", "height": 387 } }, "cell_type": "code", "source": [ "#Se gráfica la columna A\n", "df['A'].plot()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 112 }, { "output_type": "display_data", "data": { "image/png": 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vNaGptQtTI/0hlXJqnGggDG0iEhUbhBANHkObiESVXWCAQi5FLBuEEN0SQ5uIRHOlrg2X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\nExMDo9EIQRCgUCh6PefKlSt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"text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "1WR7iIioK8N6", "colab_type": "code", "outputId": "e905d464-0a63-4350-97f7-f6ec63e8e0ee", "colab": { "base_uri": "https://localhost:8080/", "height": 282 } }, "cell_type": "code", "source": [ "plt.plot(df['A'])" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "[]" ] }, "metadata": { "tags": [] }, "execution_count": 117 }, { "output_type": "display_data", "data": { "image/png": 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w/9r5dF7v570j9VaHY4mbvZd07CUVofxugzDGPDdq0YkR6/YyRhfWMfZRQez+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\nlFJj+r+XHp/Cp0XRNwAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "pRKMuTOoLhVX", "colab_type": "code", "colab": {} }, "cell_type": "code", "source": [ "ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))\n", "\n", "ts = ts.cumsum()" ], "execution_count": 0, "outputs": [] }, { "metadata": { "id": "K6cfFMd4LxWf", "colab_type": "code", "outputId": "6066eac8-4e6f-40ee-80b5-eb6d98362c87", "colab": { "base_uri": "https://localhost:8080/", "height": 294 } }, "cell_type": "code", "source": [ "ts.plot()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 119 }, { "output_type": "display_data", "data": { "image/png": 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EyjQhjsVTlrT0LRS3y6EUQBEEUR3u/tGLAICffHpNzkLEcDShGk9ZKeq6olSv0bzb5cTn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\nM7L7p5cCf6KLcKL+3PYTSpo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ABCD
2000-01-01-1.644883-1.6142220.237673-0.212443
2000-01-020.375091-0.1879830.2747470.736999
2000-01-03-1.6985350.7305290.5377860.791468
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eHmkcPVgv2XKXXDAOQQmNTXaWXT6Jjzv9pO3t7gH93565bCyvPbc1ok1QCjHP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"text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "-2YFEDHwMKCi", "colab_type": "code", "outputId": "c4470d4f-52f6-44dd-8486-21ed4eff553d", "colab": { "base_uri": "https://localhost:8080/", "height": 282 } }, "cell_type": "code", "source": [ "df.plot.hist(alpha=0.5)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 124 }, { "output_type": "display_data", "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "QSpfZKYqMu9q", "colab_type": "code", "outputId": "c649f378-8af2-4526-9446-3f8c7d874e58", "colab": { "base_uri": "https://localhost:8080/", "height": 575 } }, "cell_type": "code", "source": [ "from pandas.plotting import scatter_matrix\n", "\n", "scatter_matrix(df,diagonal='kde',alpha=0.2)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "array([[,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ]],\n", " dtype=object)" ] }, "metadata": { "tags": [] }, "execution_count": 126 }, { "output_type": "display_data", "data": { "image/png": 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VfX75syc/1de+h3leM5wUTOYl33nDKoHToqaQCldAIw5oRT7LvYgXnxmw0ks+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IWuc09dV4UQuLbOqcNdLu36vHBhQHLVfF5X5SJZCUm51DWFTtPGtXXprnuX8K4t+k3XIMkKOk0L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\n6EdEtEiKfkREi6ToR0S0yC+KcDUrPfKhaQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "BjRVRaA2Mf1v", "colab_type": "code", "outputId": "c0ef4f7f-1ab1-41b9-f2c4-9ff80bbd8c43", "colab": { "base_uri": "https://localhost:8080/", "height": 742 } }, "cell_type": "code", "source": [ "#Ejemplo de seaborn para generar scatter matrix\n", "import seaborn as sns\n", "\n", "\n", "sns.pairplot(df)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 127 }, { "output_type": "display_data", "data": { "image/png": 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3l6MEI+uKLhvvt/1D1m11PHeD+x0R9gIvA39ae2FoaEgF9M7MzFxYe+l14GuA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2+L3Aehy20ROcKPOrU5OrB2U4S5aIbu1kY+vh6U/x+IZOTXOGx6CsUKs5EMNosOfziNu9kh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\nDquQ6b0wERCv915j+aNM3hISEhJPIt5IBm8ow3d/5hGVr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6tVT7tNj0IhZ3I+RjQpvDVm\noyCIPetLcGjYRSZXIBLP0WE3oFTIOHdd2AEOdt/RD67ppM76U+zd3spwr3VL1/5IfHKon6B9yxlx\nAQjFcozucHBtOtJQU/fW5UVeeX47N+einBjtIJUt4ItksFu0aFRKrkyGGdneCkBfm4lUNo9Jq+L3\nv7FvQwa602YgGM9xftzPxO14gwaxhISExMPgbvru/W3NnBrzMbK9lVazlsBylk6HgbZWA6+enuHQ\nkJOFQBqjTiXa1deai32hDM4WHflCmXK5QlurnrHpCM/us23JIBgeQyDsdrtPAMMej+ew2+1uAcYQ\nGu7+2OPx/JPb7f5PwG8Cf/Kor+1RsRjJ8PbYHQOBei9wi0nD5Zth9u904AulcbbosBjVRJN5wT3m\nqS5kMjnLiZyY8Y3EcyxFMsRTeRxWHSqlgjNjPkDYAR5a0w+uN+ho1qu5eCPEbX+KZ/a2M9xteTxv\nhoTEQ2AumBZVVmrfkYNDDrKrJdF6XN+kJBRbWVOKyJDNFdneaSEcE35/Zm87kfgKLx3tIRBd4fRV\nH29c8vHtb46KXdeVSpWFUJq/feMWM4sJbBYtHXYDv7i0+ESL0T/JSBlkCYmPRpfdwIl9HZwZ80MV\ndvZayeXLvHp6BpVCjkmvJhzP0eMyMT4bbZCWdLXqsRjV3FpM0mzQ4GoVlHC2sg/B48gIvw28t/Zz\nAtADzwL/Zu22HwH/E1s4EJ6YixGO32luExUhRHUIA6+dnuHY7nZUShm3FpOYjRpeOtrDmas+ntnX\nQZNaydlrS4DQJRqKr9BhN9DjamYhkKTLYcRu0dLX3sz4XIzpxQQyGYwO2rl0MwQgWixOzEalBVti\nyyCXy7gyFaHDYRAzwO+MBzg87EKlkNNqFjqoyxVBTigUy4mbUpkMQrEcGpUCjVrBVU8YuVxOlSpN\nGiWr+RKn3l9ChozbS0mcrXo67QZ0TUrCiZxYc1cz9JDq8yUkJB4HXTYDeq0CnVZFNJHDv5wVjYei\nyRwGrYqx6XhDGaVGpaDdpieazGM2ajDp1MSSOT53rG9Lz2OPPBD2eDxlILv2628BPwE+XVcKEQZc\n93oMi0WHUqm41588Mmw244e+z9itZVEWDYSMlc3c1KAOoVLIOTPmEwWuw/EVhvqs7OixEomvCDs9\nhIzvcH8LxkDNSzxDLJVnoMtMsVTle6dm2DtgY9obZ++ADbtFy6FhFyqljDl/inabgSa1kkueMKND\n93zbnzju571/1DxJY/Vx8Lg+o529VhQKGVcmw+SLZSqVKuev+zHqVBzf28Eb73kB2L/D0VA/ZzNr\nGd1hx6RTE03mxO7rDpuBk/s7ef38HHNLKQqlMvFUnkKpzORclJMHunhqp4NyucqFiYBYc+fxxhve\ngyd5zH5cx+r9vqdP2mchXc8H58OO1Sf1tTzs6zq2t5P//b9cAO4kvgAODjnosBsoVyrYrTrGpiKM\nDtpFdYn3bgY5sMOOUinn6niEpUiWb72086Fe6wflYbxnj61Zzu12fx4hEP4UcKvuv2S/7L7x+EYB\n/ceBzWYkEtmo4/fL6G8zkck1Ol9NzSc4eaCTRDovqkMEl1eYD6TodBjo72hmZjFBm81IIJqhy2Gk\n22nCZdORyKxy+qpf3NE5rDqKpapYHhGJ59BrVWRXS6gyQqf8nD+LzaKlSa3kqifMM/s6iEYzH5sa\noA/73j+uifBJGauPg/v9fjwIdnSZOT8R4EsntzHnT+ELZehpM+Fs0fHeRIjRQTs7e61MeeN0OYw4\nW3UYtSrKlQrjM8votSriqXyDDmc0IWSKbRYthjVJtUg8R3uXAYVcRrFYRqNW8uKRHibnYlhMGga7\nLeJ78EHfD2msfjjuZ4w9zrG5GR/X6/k4jNUn7b2t8Siuy2ZQ8ztfHuHyVJjbSyn2DNjodAjz1Wqx\nSIfdwEIgjdXchEmnQdukYDGU5jOHu4nEc7x5eZFKpUqX88l4Dz/Ke3avsfq4muU+DfxvwGc8Hk/S\n7XZn3G631uPx5IB2wP84rutRcXjIyR9+9yr7dzhYLQg1i84WHUqlIHi9WiwRTaxitzaxWigxtRBj\ndilJPJXnylSEQ8MuCqUyMjmMTUVwd1twWLV4Q5k1x7k0NotWDLRr9T9qpYJqFfzLmQYHrf07HGRW\nCh+bIFhC4pfRaTMwss3GqSs+zAYN9jVB+UKhxGC3hVu+BCqlgmvTEfRaFdemBZem43vaKBQrpFfu\nLLS1o8PFUBqHVUdvWzM/OntbDJK9oTQTs1GO723n7bElTox24LDqUK91aP/5T6Y4OOTgxBOalZKQ\nkNi6pFcKmA1qntpp57Y/RTyV59w1Py3mJpRyIeawmDTcysX5yvMDeBbijHkalSae2rl164Ph8TTL\nNQP/J/C8x+OJrd38BvBF4G/X/v2XR31dj5Iuu4Hf/8Y+3rjiI5HOs6PXgtOqJxDNYDZqmF1KEo7n\nOLLLRbvdgEwmI7Cc5dCwE7tVx6unZqhUqqiVCp7b38HkfJz1ifRaF2g8lRfrf2ruMvHUHUGOmnRK\nMlPYstIoEp9MdnaaqVSq/Mlr4+xz20lk8ixFMrQ0a5ldSjIXSHF42MVqoSQ60PW2mXC26pn1JcWm\nuia1kgsTAQ4NOemwG5jzJzfodteslwEiiZx4BHlgp6DPeXkyhFKpYLDd9MjfBwkJiU8mcrmMUCxL\nOJFHLpdx43aMYrnC4WEX5XKFCsJGvmbT/Fc/meRfHe/H0aLDF8rQ5TTy1E7Hlm+mfxwZ4VeAVuAf\n3W537bZfB/5ft9v93wMLwF89hut6pPQ4jQSjK2RXi0zOxZAh4+z7AV462svEbJR8scy5a/415zgD\no4M2fvLOAsP9LaLmqc2iZSGYwaBVEYo1HhW5WvXIgP52ORcmAqK7TLnChkVc6Kh3SkGwxJZjuNvC\n739jH+/eDBGOr7Bnu40uh4HLkyHyxbIoIu+w6uhvMzHjS9FuNzDtjaPXqsTvokalQKmQkV0tberi\nCIL1ck0BpiZFlMvfKYG6cN0vBcISEhKPjEqlSpNGhS8cxRfOcHjYRaFYYjGUpt2mZ++2Vq7V6QyX\nShV+dPY2v/f1UQY7TZRKlcf8Ch4Nj6NZ7s+AP9vkv1541NfyOKlUqvS3m/jZRe/aQpxjn9vOQiDJ\nyQOdpLIFvME0HQ4DSoWcH56do1Kpbsj0zvoS7BmwbTDTOL6njWszEabmExzY4aDdpgcZ/ODMRgct\nu0XLcO/D3fFJ2WaJ9TyqMbGZ4cZmbnQA3zs1i1wOrzw/wM35GD6lkBUxaFX8/D0vapWCfW5bgx5x\njVoJ0ugOO1cmwwANQfFCME0sU8BqUD/01ywhISHhDWdYTqzS6zLhDabFjb/FpOGqJ0K5UhGda33h\nDB12g+BQN+J6ImqCHxWSs9xj5PCQk9NXBT1htUrJ5cmarJmgaWoxNtGkUvDWFZ94n/WZ3udGOxkd\naCVfKDdazNoN3JyL0ttmpNmo4fXz8+zf4djUQev43vb7MtX4IIGMN5zh0lSIYCyH06rlwKCDHqdR\nCoo/wdSPiQ6bjoNDLpxm7UN/3voxdzc3uppZxtn3l/jskV4Gu/Pc9qWIpfNUKlVW8yVkyO7q5Ajg\nsOrE2+v1OTvsBv7gby7xO1/cvaWliCQkJJ4MLtwIcnMuxvNPdaKZEOasfLFMMLoizln/uOZe2+My\n4fHG6G838R/+6wVxvb6fuerjlviSAuHHSJfdwLe/NcpP3/WyFM7w4tEeQjHB2aW9y4DNrOX6zLL4\n9xqVApNeLZpxaFQKnt7lpNNm4JUTjYu6XC5j4nacYDTLNz87CMCFiYBYExmJ59jW0Uy7zfCh638W\nIxkm5mKMTS/T3266q4OWN5zhras+0cQA4K2rPlotWsqlMgd3umhr0W1qESmxNamNiVy+hMOqI5Ep\n8b1Ts5iNGkbdNnZ0mh/p9awfc+sD5H84NcNtf4J9g447JQ4TAU7uF05tAstZOuwGTHpBbm3/Dgdj\nU5EN9fkalYI2m4F3xgOStrCEhMRDRy6XMbWQIJpcZXIuxm+8vJMxT4TAsqAYpdUoqVQFb4FIPIfV\n1MTooIMbt5fF9frta36e39+J0/LBEhUbEl87HHR9DJxrpUD4MdNlM9DarGEhmOIn5+eBO3p/h4ad\ndDmMKBVybBYtvW2CWYbDqsNh1XJsT3vDglq/qFcqVQa7zSwEU0wvxvnap9xML8ZZDKXpaTNxaNjF\n5HyUs9f8vLC/g1Kp8oGC0YmFOO9cD1AoVWhtbiKTK/GH373K739j34bFfdqX4OKNUEN3fbNBzTc+\nPcjEbJQ///FNhnqtaJtUXLwRxN0l2dJudaYWE1ybWealoz34QhmyqyWWEzlkMrh4I8hiOMNgp1kc\nA+vH5KPaMNWe4/CQk3fGAyyF0w0qL+lsAY1aQaFUZny2UW7t4JATg1YlukQeGXHR1mrgB2/PAuDx\nxqWNn4SExEOlPgZQq5R8//QMO3tbKJTKYu8DCAm2Tx/qpt2m4y9fnyKXLyGXy+h0GElmC/z56zfZ\nN2BjuNfacHK8fg5bjGS4Oh0hmszfSXxd8dHpMLC93fxEr+tSIPwEcGDQwRuXfOLArB1bjA7a+a8/\nnBCbdq5MhTHqVHztBTftrbpfWs5QK704dy1AuQxqhYL9O+xkckXen45wYSLA0V0u/vj7EzSplei1\nSgxaJUM91k0fO5TIMbuUBARHLptFi1olZ3TQzrnrAb7+/Hbxb+VyGbNLKfE1aTVKnt7dxspqkR+f\nm6PTYeTQsJNZXxIQMmmvnZ6RbGm3MKFEjkqlyq8c7SWXL23YJBl1Knramvnj71/nm5/ZwY3bUaYW\nEuzoMTPU28LE7RhTC3EGux/8hulugWmX3cDvfXUv074kr56aAYSN6th0hINDDjH4Ta8UAWFR6W9v\nZtaXRKOWc3jExevvzPHO9YD4mO4uixQES0hIPHRqMUDtNLjTYeCd64ENDfMmvYqrnmWxuff43nbO\nXfOzz23HbICLN0IshjI8d6CTJqWMuWCadydCdDkMHB5yAsJp73xAkG7tdBi56gljM2uxt+j4o78f\n4/e+uveJXdelQPgJoMtu2LR5p7YIN9w+/MGPGmqPe+56gGlfgrYWPfmiirff97O6NuBbLVquTIax\nWbRUqxWq1Sr/fH6eZ/a2M9JrpVKpshjJMBfMMONL4A3eGegXJgKoFHJePNrD9ZnlDcFEYDmLXC7j\n8LALu1UrZrxbzE0oFXKmFuJEEjk67AbC8RWO7XZxZkyypf048WEym3PBNP5IFkuzhnCdrXFtjKwW\nSpy+4mOw28r1mWXi6Tw6nQKbRcf/873r4t8vBFMPbMPkDWe4cCPI1EJiQ4Bde221comBzmYuTAjf\nxROjNg7tdPDcvg4u3AgxtRCj3W7ApFMz50+ys89KJlfgtVMzG2qJh/qsH+maJSQkJDZjfXlkLQZ4\n+7qfmcUk1WqFX/vsIJNzMXzhDJ0OA+1r810ousLRkTbK5QqpbIF9bjuXJ0Oi3Fq1WmE5nuPGXExQ\nnbDrMeo1nHp/iXfHgw1JDY1Kweef6WdmMUEomuPoiIt3bz6567oUCD8h3K155263fxgu3gxi1KvR\nqJUEo1nsZi297SaqlSo/fPs2lUpVHLwvHu1hYjbKxGyUzxzswmnTE47n+Mn5ebHWsVAqk80VOTzs\n4vx1P8vxHDt7NtYZb+s009vWjC+cplKpNBwtZ3IFmtRKfOEM3qDw3C893Sva0kpHx0829wogN/37\nSIap+RhNGgWh6IqoWwlweNglypnJ5TK6nEZMejW5gjDO5vypTXV7P+qGyRvO8Ad/c0Uc1/liiXdv\nBPmtl4fEbHT9a+uyGZANC9mTsellqtUqh4ecvHKin19cUbMYyvL+rQjuLiv/3888FMsVvvDsNub9\ngi54TZP4T14b37SUSELig/Kb//mtD/X33/l3zz2kK5F4EqjNx9PeJId3OQjGcswtpTi8y0GlKrgM\n7NneSjie4xcXvXQ5jBzb08ZyYoWlcJZqtcrR3S6+99YMFpMGfZMKs1FDvljm2X0dNBtUuFr1fPdf\nPGIZmBAzRHj5WO+m87MvnGao14rHG0NGFb1O/cSu61Ig/IRxt0Fyv4Pnwo0g6ZUi6ZUi/khWlE6p\nVoTjjvrHzRfL+CNZ0aUuvVri9vUATWoFxXKFoyNtYiDb3mXA1aqj12XCv5xlj9sG3PlCzvlTPHeg\nA89aMGFv0ZHOFvjx+QVW8yVCsRUcVh3HdrdzZkwoC/GHMzisWuno+AmnPoCEjRna9VmJSqXKfCBN\nJldiYS7K9g4LHQ6DuPlaLZTExzo87EIug59eWGCf206H3cC0NyGO21opgkalYDmZ+0gT69nrgQ3j\n+vAuF398l+wz0PC6Z3wJTl9d4t//5lNMLwoGHPFUnkyuIF7jnD/JxGxUrPuv3Vc69ZCQkHgQ1M/H\nR0faePXUrPjzj87NMdTbQqlc4c3LPnEevTQZ4tx1P6ODdlQKOZFEjr72ZhxWHc0GNYeGHUzOJXhu\ntINiucLNuTgqpYKBLguReI7h/hbRaEgwHmoiEl9tuC5fKIM/kmX/Dgc/Onubzx3re2LXdSkQ3sLU\nukbrqUmnqJUKUd+0nsBylppL3cxigi+c6OO107cbsnZwx1b2a59y4/HGyK4UefXtWd645GOf286u\n7S2kswV6201MzccZn43R7TLxWy/vJJZaFY5MYjkKpRLH97Rx7noAfzSLSqkQNV0lPjxyufDZPcwJ\n58KNoBjo1YLTYrnCtC/ZkJUIx3PMLaV5Zl8b074Ey4kcO3tb2Ou2c3MuKt6/1lihUSkolyvkCxXx\nWE4ul/GZw914g2ki8Rz73DYGe6xMzsXwL2f5uzdnxDKiD0MwnuPWYqJhXBt1KpYimQ2lDBaThrFb\nEVYL5U0zH+fHAzitQld1oVQWX0/ttdW+c/VIpx4SEluPRzH/1rMYyfDGFZ84H9eSCkadimK5jF6r\nolCqsJwQ5qT1c1EknqPVrGWwx0IwKpQyurst3JxPEIxm2dlrJZ0r0tdu4kdn5zaUPxwedjHnT/GV\nkwOE4zm+f2ZWNOGwW7TotWr8kQxqlRxvKP3EznlSILyFqe8aXU+X08ilm6ENt3c4DKIZgKtVD8jo\nsBsEG1qVnIEuM/OBFOmVIvlimWlvnInZKFenInzxRD/73HYmbi+zo2c75UqFNy4ukszmeWqnk1hq\nlR+dnaPbZaTb1cwVT6ThC6VWyXl2bxudrVKm7MPiDWeY9iWYWUoRXM6yrdPM8RHXA886yuUypr3J\nhizqcH8LvW3NvLpWD1uflfjSc9v57lqZwOFhFyurJX5wepbeNhNf+9QAs74k+VIFbyiNxaShUKqQ\nzOQxGxEf6yfn5ymWKzy/v4NWs44L4wH0WhWdDiO/uOTl9FUfv/2lkQ8lA3h+3E9bq57VQoliucLx\nPW1oNco1u/LGuuVIPMdqscLkQnzTx7oxF+NfvzjIW1d8ZHNF2ruEbHc8lWe4v2VT8w3p1ENCYuvw\nqObf9c/5ndcnxd8tJg3RxCpHR9rQahRMexPEU3n62pqxWbR3NQFSKf5/9t48uM0zz/P74L5BACQu\nErwpHiIlWaQOy5RkSb7adnv67pnpmZ6p3f1jqzK72UpNJbNTSTbJ/rGzW6kkldrKOZlOMr3Tnd7p\n6dNHu9unLJm2dVOUeIgnCOIkCJC4iDt/gHhFkJRsqe3WwedT5TIFgsCDF+/7vN/n9/x+35+cOoOG\ndyYW6W628Nr5+UqRnEnDzbkVBjptVINjm8nmi6znCjQ2GBibiaJSyvnul3r5wZuTAGjUSpKZHPFE\nlja3mUA09YUdi98WIYQfczY37aiiUSl4an/jNiGsUSmQy2TS6rLFZeL7b4zzned7iSXWUavkLIVT\n7OtsoM1t4tZiHBky9jRbuDwZYWk5hVwGxw80MudfJV8s02DR0empI5srcGUqUpOPfHy/m7NX/RWT\n71yBnpZ6IYLvg6o3b9WFoZrHfeFm8HOv1C2Vyhzb55SELkBoJY0MdoxK+CNJAF45Xmkd7gtXIq7e\nUIKPxoJ8+5kuiuUy0XiGcCyNWimnvdEspUMUiyUc9XpeOtbG9ellJhb8eBxGGu1G3hiZlyK616eX\nsRhUeD7l/KlGbMZmYwx01nNjJsrXT3Xxyw8qHRerwnXrDkhoJV35XXBnUdtiN3Jm0IPHYSJfKElp\nEFq1csfmG2LXQyB4PNg6/0JlvphejPNPvtx3X82qPgsjN4K356WNhfdLw25ePz+PTC6TOmAqFTKU\nip3nIYNWSYfHQmY9T4vTBMgY7HFweTLM0wcbOdTnYCmcYnw+ykBnPQatkmnfKtHVdbL5yu7Xvq4G\nrs8sM9htZ2ohzpMb7hQ/eX+GBrOWgc56Pri6xNF+10O7+BdC+DFnR0eKASdDe93oVXJGboQYX1ih\nxWnCYdNzeTzMUK8Dg1YJlEmmC1ydiuBfTtWImEsTYU4PeVhN5RjobMCgU7HgT/Dy8TbS63lml1ZJ\nZW57xBq0Sp7a5+bcNT+wsZqUipSKhOMZupp+t80UHgfkchkXJkKk1gs75nFP+VZrhPDnsXUX2uT4\nAJVIRHhLOgBAR6OZOqOal4bbWIqkyBdKDPU5kMtkfHQjyKE+J9NLqyxFUrjqDRzssaNRKQhGK3nq\ne9utxJM5ZMDF8VCluDKSlBZS33pmD+v5AgO5eia9cdbzRZ4Z9Nyxucvm4r7h/S5+9sEcrwy3Mbu0\nKn0erVqJSa+qyVsGPpOo3VzY2uY28dFYkMVQkt870UF0LcPs0lqNI4xAIHj0qc6/1WLfzTtJv77o\n4/lDHlqdJuDzS5mopj1unpegIsCrO2kqpRyNSsG50QDfON3Fy8NtRGIZFoIJ3A0Gmp1GVEo5f/v6\nOMcPNOKw6lheXafJbuC7X+olVyhyaSJMeOV2oe+F8TBnhjwEV9KVTpqyMm9fXGSw204kvo7RoEKv\nVbIYWuNLT7ZAGdQqBbl8ieP73J/LZ/8iEEJ4F1C9QQdjGd67usT3Xh3n9Y+8dDWZObLXSXQ1g0Iu\nxx9OYqvTolLIKZbgwo0wVrOGhWCCBosOi0kjJchn80Ui8cxGWkSYr5zswG7R8bevjzPU66RchksT\nlRSLzY4Um4VEcDkt5Sl3eyyfuXuN4LawW15dp1yu+DrvlMc95Y0x0GEjlytydjTA9GIcV4OBriYz\n3Z7bJudKpfwzNVWRy2VM+1ZrHtucArD5Z6tZRyqT552LvpoxaVQKvnqyk19+MHs7ghJNV7YUPXV0\nbXSX+39fG7/9d8HbKTTnRyu7CAuBNfLFUo1A/uRGaJut2k7FfRqVguEDbox6FaGVjPTckbEAL25E\nn7cyMhbg+SMtFIplpn3xO4raUqlMX7OFvmaLdFwB7HYTkcj2iLJAIHg0kctlBFcy0uL/2ICb0ekI\nBp2KYqmEu17P2WsBYol5tBolbS5jzbx7v2xOe6x6BFfTIaq7cnP+FKeHPETiGS7cCDF8wE2dUU2z\n04hJryISW+eDa0uVYmb/GiqlHFe9gVfPzfPVpzv52fsz2+btw3udxJJZHFYdH14P8NyRVsqlMBaT\nBqVCzntXfGSzRY72VzTAW594+dKTrfyzb+5/qBf/QgjvEraKAW8owbWpCMP73WjUSt6/cruitFqZ\nP9TrYGymsiVS3erdLEYisYwkZH3hJHVGFQCZbAEZ1IjerY4UAK4GPdemlqU0CcFnY6vt18Fuu5Tv\nupM379mrft695Nv23R/b52Sg086VqQiLwQQeZ8UHF8o8uXdnO7Sd8s63RkulqGq2EqXeW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PkC+WJNF8Y3aFl4fb7tgYoRoBrkY0oZLHGo1nWI5XCruqPG52V3K5jPOjQUKxNM8caia4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\nU6FYSS1wz7Y6aqvNxBLL9O904Z2J01Bjx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"text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "TGHO6Oc6kNBw", "colab_type": "text" }, "cell_type": "markdown", "source": [ "## API de Pandas\n", "\n", "Una vista a la API de Pandas.\n", "\n", "Nunca es el objetivo para aprender una biblioteca el conocer todos los métodos, pero si resulta recomendable saber donde se puede ver información. Con la práctica se va conociendo mejor todas las funcionalidades de los métodos y se vuelve más familiar el api.\n", "\n", "La información sobre el api de Pandas se puede encontrar [aquí]( http://pandas.pydata.org/pandas-docs/stable/api.html)." ] }, { "metadata": { "id": "g9badUUrAMBD", "colab_type": "text" }, "cell_type": "markdown", "source": [ "# Basico 1: Carga de Datos y Exploración\n", "\n", "Primero se limpia el entorno y después de cargan las bibliotecas requeridas." ] }, { "metadata": { "id": "SxTPTle3jl91", "colab_type": "code", "outputId": "08356bb4-e79c-4f86-a515-02b1419be9ee", "colab": { "base_uri": "https://localhost:8080/", "height": 35 } }, "cell_type": "code", "source": [ "%clear" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "\u001b[H\u001b[2J" ], "name": "stdout" } ] }, { "metadata": { "id": "vm_xaTsOlQP5", "colab_type": "code", "colab": {} }, "cell_type": "code", "source": [ "%reset -f" ], "execution_count": 0, "outputs": [] }, { "metadata": { "id": "izMKKSE1lR1z", "colab_type": "code", "outputId": "115e2434-cbf8-4af5-9e34-b1370a60130e", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "cell_type": "code", "source": [ "%whos" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "Interactive namespace is empty.\n" ], "name": "stdout" } ] }, { "metadata": { "id": "R15Tuh3olidW", "colab_type": "code", "colab": {} }, "cell_type": "code", "source": [ "#Se cargan las bibliotecas que e usarán \n", "# además se modifica el entorno para trabajar\n", "%matplotlib inline\n", "\n", "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "from IPython.core.interactiveshell import InteractiveShell\n", "\n", "InteractiveShell.ast_node_interactivity = \"all\"\n", " " ], "execution_count": 0, "outputs": [] }, { "metadata": { "id": "3LdiMVhSlzJz", "colab_type": "code", "outputId": "96ebe0c4-633a-4967-a12f-c69130079812", "colab": { "base_uri": "https://localhost:8080/", "height": 223 } }, "cell_type": "code", "source": [ "#Carga de datos\n", "data=pd.read_csv(\"sample_data/california_housing_train.csv\")\n", "data.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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" ], "text/plain": [ " longitude latitude housing_median_age total_rooms total_bedrooms \\\n", "0 -114.31 34.19 15.0 5612.0 1283.0 \n", "1 -114.47 34.40 19.0 7650.0 1901.0 \n", "2 -114.56 33.69 17.0 720.0 174.0 \n", "3 -114.57 33.64 14.0 1501.0 337.0 \n", "4 -114.57 33.57 20.0 1454.0 326.0 \n", "\n", " population households median_income median_house_value \n", "0 1015.0 472.0 1.4936 66900.0 \n", "1 1129.0 463.0 1.8200 80100.0 \n", "2 333.0 117.0 1.6509 85700.0 \n", "3 515.0 226.0 3.1917 73400.0 \n", "4 624.0 262.0 1.9250 65500.0 " ] }, "metadata": { "tags": [] }, "execution_count": 25 } ] }, { "metadata": { "id": "l7_TgFc7Chot", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Las primeras preguntas que pueden hacerse sobre los datos son:\n", "\n", "* ¿Qué tamaño tiene la muestra?\n", "* ¿Qué tipo de variables se tienen?\n", "* ¿Tiene missing values?\n", "* ¿Cuáles son los nombres de las columnas?\n", "...etc.\n" ] }, { "metadata": { "id": "feq2nBMRNxxA", "colab_type": "code", "outputId": "c8c032de-3045-405f-b9e1-f819e3257517", "colab": { "base_uri": "https://localhost:8080/", "height": 343 } }, "cell_type": "code", "source": [ "#Cuantos nulos tiene el DF?\n", "data.isnull().sum()\n", "#Qué tipo de variables se tiene\n", "data.dtypes\n", "#Cuál es el tamaño\n", "data.shape" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "longitude 0\n", "latitude 0\n", "housing_median_age 0\n", "total_rooms 0\n", "total_bedrooms 0\n", "population 0\n", "households 0\n", "median_income 0\n", "median_house_value 0\n", "dtype: int64" ] }, "metadata": { "tags": [] }, "execution_count": 26 }, { "output_type": "execute_result", "data": { "text/plain": [ "longitude float64\n", "latitude float64\n", "housing_median_age float64\n", "total_rooms float64\n", "total_bedrooms float64\n", "population float64\n", "households float64\n", "median_income float64\n", "median_house_value float64\n", "dtype: object" ] }, "metadata": { "tags": [] }, "execution_count": 26 }, { "output_type": "execute_result", "data": { "text/plain": [ "(17000, 9)" ] }, "metadata": { "tags": [] }, "execution_count": 26 } ] }, { "metadata": { "id": "6SbJ0FsXORSR", "colab_type": "code", "outputId": "75675bfa-ed6c-4b02-f0d4-d2497196ad1a", "colab": { "base_uri": "https://localhost:8080/", "height": 206 } }, "cell_type": "code", "source": [ "#Cuanta memoria ocupa?\n", "data.memory_usage(index=False,deep=True)\n", "print()\n", "data.memory_usage(index=False,deep=True).sum()\n" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "longitude 136000\n", "latitude 136000\n", "housing_median_age 136000\n", "total_rooms 136000\n", "total_bedrooms 136000\n", "population 136000\n", "households 136000\n", "median_income 136000\n", "median_house_value 136000\n", "dtype: int64" ] }, "metadata": { "tags": [] }, "execution_count": 27 }, { "output_type": "stream", "text": [ "\n" ], "name": "stdout" }, { "output_type": "execute_result", "data": { "text/plain": [ "1224000" ] }, "metadata": { "tags": [] }, "execution_count": 27 } ] }, { "metadata": { "id": "ZpOjlL8gDLrC", "colab_type": "code", "outputId": "04331847-8de7-45bc-9a7a-7f5b0dbef976", "colab": { "base_uri": "https://localhost:8080/", "height": 257 } }, "cell_type": "code", "source": [ "#Resumen general de los datos\n", "data.info()" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "\n", "RangeIndex: 17000 entries, 0 to 16999\n", "Data columns (total 9 columns):\n", "longitude 17000 non-null float64\n", "latitude 17000 non-null float64\n", "housing_median_age 17000 non-null float64\n", "total_rooms 17000 non-null float64\n", "total_bedrooms 17000 non-null float64\n", "population 17000 non-null float64\n", "households 17000 non-null float64\n", "median_income 17000 non-null float64\n", "median_house_value 17000 non-null float64\n", "dtypes: float64(9)\n", "memory usage: 1.2 MB\n" ], "name": "stdout" } ] }, { "metadata": { "id": "7n0XwxiKDSuT", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Lo mínimo que se puede hacer es ver algunos registros de la tabla o DataFrame y ver las estadísticas generales de los datos." ] }, { "metadata": { "id": "57VD_c0cl480", "colab_type": "code", "outputId": "522de365-26a5-4e46-b844-3619747e0464", "colab": { "base_uri": "https://localhost:8080/", "height": 501 } }, "cell_type": "code", "source": [ "data.head()\n", "data.describe()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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longitudelatitudehousing_median_agetotal_roomstotal_bedroomspopulationhouseholdsmedian_incomemedian_house_value
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" ], "text/plain": [ " longitude latitude housing_median_age total_rooms total_bedrooms \\\n", "0 -114.31 34.19 15.0 5612.0 1283.0 \n", "1 -114.47 34.40 19.0 7650.0 1901.0 \n", "2 -114.56 33.69 17.0 720.0 174.0 \n", "3 -114.57 33.64 14.0 1501.0 337.0 \n", "4 -114.57 33.57 20.0 1454.0 326.0 \n", "\n", " population households median_income median_house_value \n", "0 1015.0 472.0 1.4936 66900.0 \n", "1 1129.0 463.0 1.8200 80100.0 \n", "2 333.0 117.0 1.6509 85700.0 \n", "3 515.0 226.0 3.1917 73400.0 \n", "4 624.0 262.0 1.9250 65500.0 " ] }, "metadata": { "tags": [] }, "execution_count": 6 }, { "output_type": "execute_result", "data": { "text/html": [ "
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longitudelatitudehousing_median_agetotal_roomstotal_bedroomspopulationhouseholdsmedian_incomemedian_house_value
count17000.00000017000.00000017000.00000017000.00000017000.00000017000.00000017000.00000017000.00000017000.000000
mean-119.56210835.62522528.5893532643.664412539.4108241429.573941501.2219413.883578207300.912353
std2.0051662.13734012.5869372179.947071421.4994521147.852959384.5208411.908157115983.764387
min-124.35000032.5400001.0000002.0000001.0000003.0000001.0000000.49990014999.000000
25%-121.79000033.93000018.0000001462.000000297.000000790.000000282.0000002.566375119400.000000
50%-118.49000034.25000029.0000002127.000000434.0000001167.000000409.0000003.544600180400.000000
75%-118.00000037.72000037.0000003151.250000648.2500001721.000000605.2500004.767000265000.000000
max-114.31000041.95000052.00000037937.0000006445.00000035682.0000006082.00000015.000100500001.000000
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" ], "text/plain": [ " longitude latitude housing_median_age total_rooms \\\n", "count 17000.000000 17000.000000 17000.000000 17000.000000 \n", "mean -119.562108 35.625225 28.589353 2643.664412 \n", "std 2.005166 2.137340 12.586937 2179.947071 \n", "min -124.350000 32.540000 1.000000 2.000000 \n", "25% -121.790000 33.930000 18.000000 1462.000000 \n", "50% -118.490000 34.250000 29.000000 2127.000000 \n", "75% -118.000000 37.720000 37.000000 3151.250000 \n", "max -114.310000 41.950000 52.000000 37937.000000 \n", "\n", " total_bedrooms population households median_income \\\n", "count 17000.000000 17000.000000 17000.000000 17000.000000 \n", "mean 539.410824 1429.573941 501.221941 3.883578 \n", "std 421.499452 1147.852959 384.520841 1.908157 \n", "min 1.000000 3.000000 1.000000 0.499900 \n", "25% 297.000000 790.000000 282.000000 2.566375 \n", "50% 434.000000 1167.000000 409.000000 3.544600 \n", "75% 648.250000 1721.000000 605.250000 4.767000 \n", "max 6445.000000 35682.000000 6082.000000 15.000100 \n", "\n", " median_house_value \n", "count 17000.000000 \n", "mean 207300.912353 \n", "std 115983.764387 \n", "min 14999.000000 \n", "25% 119400.000000 \n", "50% 180400.000000 \n", "75% 265000.000000 \n", "max 500001.000000 " ] }, "metadata": { "tags": [] }, "execution_count": 6 } ] }, { "metadata": { "id": "Sd4h8ZiqDe1Z", "colab_type": "text" }, "cell_type": "markdown", "source": [ "En apariencia se pueden graficar las Latitudes y Longitudes." ] }, { "metadata": { "id": "_BZgeeW4m3pK", "colab_type": "code", "outputId": "fd926c38-7465-425e-9857-8f21d4707e39", "colab": { "base_uri": "https://localhost:8080/", "height": 282 } }, "cell_type": "code", "source": [ "plt.scatter(data.longitude,data.latitude)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 29 }, { "output_type": "display_data", "data": { "image/png": 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TO38kV25KDhv9g0HOtfXxo1+dxOsbmyUhOawEQoU1qpUeJ3NmlHPktHYV62Sh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\nzNEX1YLRNw+1ePAzL5zSTTesr3Mzd2Y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"text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "bfPJ_H_mm-rs", "colab_type": "code", "outputId": "47fd8895-faa2-4968-98b8-dd597bbb2244", "colab": { "base_uri": "https://localhost:8080/", "height": 86 } }, "cell_type": "code", "source": [ "data.columns" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Index(['longitude', 'latitude', 'housing_median_age', 'total_rooms',\n", " 'total_bedrooms', 'population', 'households', 'median_income',\n", " 'median_house_value'],\n", " dtype='object')" ] }, "metadata": { "tags": [] }, "execution_count": 8 } ] }, { "metadata": { "id": "KbPIyWZDnSsX", "colab_type": "code", "outputId": "1cfd68b1-e9d1-4ba1-847f-ebfbd4c5bb9e", "colab": { "base_uri": "https://localhost:8080/", "height": 265 } }, "cell_type": "code", "source": [ "data.plot.scatter(x='longitude', y='latitude',c='median_income',\n", " colormap='viridis')\n" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 30 }, { "output_type": "display_data", "data": { "image/png": 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1WjI0LLdtAC1VQMzC9Lptd1JLFGFIRCcfNLQRDdtfaw47FDOvexZX33EuTXUt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\nKzZy3Q+ufNWeq+tXb0F0leIN5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"text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "KhpVPYMDShlL", "colab_type": "code", "outputId": "bbd9987d-b67f-4324-c121-fc6c1f5b781c", "colab": { "base_uri": "https://localhost:8080/", "height": 520 } }, "cell_type": "code", "source": [ "data.plot.scatter(x='longitude', y='latitude',c='median_house_value',\n", " colormap='viridis')\n", "\n", "data.plot.scatter(x='longitude', y='latitude',c='population',\n", " colormap='viridis')\n", "\n" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 11 }, { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 11 }, { "output_type": "display_data", "data": { "image/png": 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VB1dWEr56Hy6HQnpGAmVHqqPnWVZcg98Xwt1JhcCWBPwh3nzuM6orGsjpl8YN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yjj9z9+ko0feCoKi+esp9fI7s3GAiCWsiCoI3WN/dUxfvK1B/n9P2+krPOJ9eDI8Slz8oLeDwCH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\nq5SLNvPffxLRN3lq375xN7/50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Rc4L/rZHMX+LMWOPv71yu9z27P//IbnTkrJJ79+Odm+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\nKELBCAkJCQkZFKFghISEhIQMiv8DZ1DQsaBK4JsAAAAASUVORK5CYII=\n", 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zHgK0NptfTJ/JzhV78fhFMAWEjKoqWK0ILieKV0UNsmPxKmycv51TmVq00oZ5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uhEmqSzfk0+L9z1bi1Rwio2LN2YCgwAicoEG1dsqfM4j98GIet/+6Pj7Rw8dsnJlx5L09bZrF+6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\nAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "ocPllVzmDpfS", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Quizás alguna variable parece relevante, se puede explorar sola." ] }, { "metadata": { "id": "okeFWjNZnxEA", "colab_type": "code", "outputId": "b12c7735-fd6b-4b9d-cfc2-a9c7387d2bec", "colab": { "base_uri": "https://localhost:8080/", "height": 282 } }, "cell_type": "code", "source": [ "data.housing_median_age.plot.hist(bins=40)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 147 }, { "output_type": "display_data", "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "udxaCWa5Q31g", "colab_type": "code", "outputId": "efb12e8f-f31a-4814-b62b-e039e08aacfe", "colab": { "base_uri": "https://localhost:8080/", "height": 206 } }, "cell_type": "code", "source": [ "#¿Cuáles son los 10 años más frecuentes? \n", "data.housing_median_age.value_counts().head(10)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "52.0 1052\n", "36.0 715\n", "35.0 692\n", "16.0 635\n", "17.0 576\n", "34.0 567\n", "33.0 513\n", "26.0 503\n", "18.0 478\n", "25.0 461\n", "Name: housing_median_age, dtype: int64" ] }, "metadata": { "tags": [] }, "execution_count": 23 } ] }, { "metadata": { "id": "trqw2v1feveH", "colab_type": "code", "outputId": "c3ddead8-cb21-466d-b5ed-b661bd21674b", "colab": { "base_uri": "https://localhost:8080/", "height": 206 } }, "cell_type": "code", "source": [ "data['housing_median_age'].value_counts().head(10)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "52.0 1052\n", "36.0 715\n", "35.0 692\n", "16.0 635\n", "17.0 576\n", "34.0 567\n", "33.0 513\n", "26.0 503\n", "18.0 478\n", "25.0 461\n", "Name: housing_median_age, dtype: int64" ] }, "metadata": { "tags": [] }, "execution_count": 31 } ] }, { "metadata": { "id": "PH8k2XPCPX7j", "colab_type": "code", "outputId": "c49a7963-9ad3-4978-96d9-0507e2e0a054", "colab": { "base_uri": "https://localhost:8080/", "height": 287 } }, "cell_type": "code", "source": [ "data[['total_rooms','total_bedrooms']].plot.hist(bins=40,alpha=0.5)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 153 }, { "output_type": "display_data", "data": { "image/png": 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WxepZJWr7dh07FpCfnxctYLy1UNCudcJFlfW0p0NRUWFG+jYH5UuN8qVG+dKv\nOQbHfwrcBJzo7mVmtsnM2oaXpLoBq8M/xXGrdQNej2tfGg6Ux9x9W0P7Ky3dknLmLZvLE7ZX1NOe\nDiUlG5PqV1RUmHTf5qB8qVG+1Chf0zVU0LI9ON4emASc6u5fh83zgWHh52HAPGAxcJSZdTCzvQjG\nMl4FXuTbMZIhwMJsZRcRkUC2zzh+DnQB/mxmtW3nAveZ2UXAp8BD7l5hZjcALwA1wPjw7GQOcIKZ\nLQLKgfOynF9EZI+X1cLh7rOAWQkWnZCg71xgbp22KmB0ZtIl9t5HX1FRUZlw2cEpDJ2IiOyq9OS4\niIhEormqUvBx1ZIGlx+cd1SWkoiIZI/OOEREJBIVDhERiUSFQ0REIlHhEBGRSFQ4REQkEt1VlaP0\nhkARyVU64xARkUhUOEREJBIVDhERiUSFQ0REIlHhEBGRSFQ4REQkEt2Ou4uqvV23XbvWbK7zJkLd\nqisimaQzDhERiUSFQ0REItGlqt2QnjoXkUzaJQuHmU0FjiZ4H/lV7t7wG5VERCRtdrnCYWbHAd9z\n9x+Z2aHAA8CPmjlWQg29IbA53w7Y0BmJzkZEpDG7XOEABgF/BXD3FWbW0cz2dvcNzZxrt6DLXCLS\nmF2xcBQDb8Z9LwnbdqnCsau+r7yxwlJXotuFm0IFSyR37IqFo65YQwuLigobXN6Y35x+Xiqryy6g\nqKiwuSM0SPlSo3zptyvejrua4Ayj1neAL5spi4jIHmdXLBwvAmcAmNkRwGp339i8kURE9hyxmpqa\n5s4QmZn9DjgWqAYuc/elzRxJRGSPsUsWDhERaT674qUqERFpRiocIiISye5wO25GNOe0JmY2EHgC\nWBY2vQfcDjwC5BHcRXa2u5eb2UhgDMF4zyx3v9/MWgKzge5AFTDa3aM9gJE4Vy/gaWCqu88ws/1T\nzWRmvYF7CI7zu+5+SZozzgaOBP5f2GWSuz/XHBnN7HZgAMHfu4nAEnLv+NXN+L/JneNXEG6/K9AG\n+A2wlBw5hvXkO4McOX7ppDOOBOKnNQEuAO5qhhgvu/vA8M8VwK3A3e4+APgION/M2gHjgMHAQGCs\nmXUCRgDr3b0/MIHgXwApCfc1HVgQ15yOTNMICnM/oL2ZnZTmjAA3xh3L55ojo5kdD/QK/5k6Mdxm\nrh2/RBkhB45faAjwhrsfB5wJTCG3jmGifJA7xy9tVDgS22FaE6Cjme3dvJEYCDwTfn6W4B+6vsAS\ndy9z963Aa0A/gvxPhX3nh22pKgdOJniOJi2ZzKwV0CPubK52G+nMmEhzZHwFGB5+Xg+0I/eOX6KM\neQn6NUtGd5/j7reHX/cHPidws6QQAAACj0lEQVSHjmE9+RJpzv+P00KFI7FigqlMatVOa5JNPc3s\nGTNbZGYnAO3cvXbujnXAvgly7tTu7tVATfgPYJO5e2X4D3m8lDKFbaUJ+qYzI8DlZvYPM3vczLo0\nR0Z3r3L3zeHXC4C/k3vHL1HGKnLg+MUzs38CjxFc6smpY5ggH+TY8UsHFY7kpDRtSRN8CIwHTgPO\nBe5nx/Go+vJEbU+ndGTKRM5HgBvc/cfAO8AtEfab9oxmdhrBv5QvTyFDfe1pOX51MubU8QNw92MI\nxl7+VGd7OXEM6+TLueOXDiociTXrtCbu/kV42lvj7h8Dawgul7UNu3QLM9bNuVN7OOAWc/dtGYi6\nKZVMBMe0c4K+aePuC9z9nfDrM8B/NFdGM/spcBNwkruXkYPHr27GHDt+R4Y3ZBBmygc25soxrCff\ne7ly/NJJhSOxZp3WxMxGmtmvws/FBHdpPAgMC7sMA+YBi4GjzKyDme1FcJ301TB/7bXqIcDCDEWd\nn0omd68AVppZ/7B9aLiNtDGzJ82sdmrdgcD7zZHRzNoDk4BT3f3rsDmnjl+ijLly/ELHAteEuboC\ne5FbxzBRvpk5dPzSRk+O18OacVoTMyskuEbaAWhFcNnqbeBhgtv8PiW4Va/CzM4AriW4Hjrd3R81\nszzgPuB7BAPG57n7ZylmOhKYDBwIVABfACMJbh9sciYz6wnMJPiPmMXufnWaM04HbgC2AJvCjOuy\nndHMLiS4TPFBXPO54f5y5fglyvggwSWrZj1+Yb62BJdt9wfaEvy9eIMU/15kON8mglvpm/34pZMK\nh4iIRKJLVSIiEokKh4iIRKLCISIikahwiIhIJCocIiISiQqHiIhEosIhIiKRqHCIiEgk/x8PA3u6\nSVcpdQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "2nUaB6_9P0c8", "colab_type": "code", "outputId": "7bea9d2a-da10-4e8d-ad96-fa2716576040", "colab": { "base_uri": "https://localhost:8080/", "height": 188 } }, "cell_type": "code", "source": [ "data.skew()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "longitude -0.304003\n", "latitude 0.471801\n", "housing_median_age 0.064894\n", "total_rooms 4.002730\n", "total_bedrooms 3.322637\n", "population 5.187212\n", "households 3.342668\n", "median_income 1.626693\n", "median_house_value 0.973037\n", "dtype: float64" ] }, "metadata": { "tags": [] }, "execution_count": 154 } ] }, { "metadata": { "id": "ZmxiXVgfGzgt", "colab_type": "code", "outputId": "956f7f93-dd17-46ee-8e4d-54cb5942a174", "colab": { "base_uri": "https://localhost:8080/", "height": 282 } }, "cell_type": "code", "source": [ "data2=data[['total_rooms','total_bedrooms']].sum(axis=1)\n", "plt.scatter(data2,data['median_income'])" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 31 }, { "output_type": "display_data", "data": { "image/png": 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z9l6BVi+hoHfa9wugs83LimUdhe9lo5nNeakVtmzWbL7fGYQQnwKuUVX180KI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\n3m+/O9ToIUiqwO2Eosbt2G3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"text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "metadata": { "id": "-F4Yia8E7auW", "colab_type": "text" }, "cell_type": "markdown", "source": [ "Los ejemplos anteriores tratan de ilustrar como se puede ir trabajando con Pandas y las gráficas en Matplotlib para explorar y conocer nuestros datos. No es un análisis exhaustivo o concluyente, es solo ilustrivo." ] }, { "metadata": { "id": "zpSY8-ZPhloH", "colab_type": "text" }, "cell_type": "markdown", "source": [ "## Notas finales:\n", "\n", "El entorno de trabajo de Jupyter y Pandas, permite hacer una manipulación de datos fácil y rápida. Algunos de los comandos auxiliales de Jupyter ( Ipython) resultan sumamente útiles para trabajar con datos y supervisar nuestro entorno.\n", "\n", "Pandas cuenta con 2 objetos principales, Series y DataFrames. Sobre ellos se tienen ciertas funcionalidades estandar, como seleccion, modificacion , transformación, etc. Resulta importante siempre recordar que un objeto en pandas esta formado por un conjunto de índices y de valores, los cuales son arrays.\n", "\n", "## Referencias y Créditos:\n", "\n", "Libros:\n", "\n", "* [Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython](https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1449319793)\n", "* [Data Science from Scratch: First Principles with Python](https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X)\n", "* [Python Data Science Handbook: Essential Tools for Working with Data](https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1491912057)\n", "\n", "Sitios Web:\n", "\n", "* https://pandas.pydata.org/pandas-docs/stable/10min.html\n" ] } ] }