Getting Started Part 1 – Setup and The Series Object

gistfile1.txt

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   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Getting Started With Pandas Part 1: <br/>\n",
      "Setup & The Series Object<br/>\n",
      "============================"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**Author**: Rory Creedon (with input from Bangladesh IPA team)<br/>\n",
      "**Date**: Feb 2014<br/>\n",
      "**Contact**: rcreedon@poverty-action.org (comments/questions/corrections welcome)<br/>\n",
      "**Purpose**: To give a general introduction to some of the basic features of pandas. The notebook is split into three parts parts:<br/>\n",
      "\n",
      "+ Part 1: Setup and The Series Object\n",
      "+ Part 2: The Data Frame Object\n",
      "+ Part 3: Other Basic Topics\n",
      "\n",
      "**Documents**: Note in order to view the pictures in this notebook you will need to download all associated files is you are using the dynamic version (see 'Using this Notebook'). All of the documents, the .ipynb files and other associated files can be downloaded from here:https://www.dropbox.com/sh/fezb1jdbwsmjwrq/6-Y9l32xQ1 <br/>\n",
      "<br/>\n",
      "**Required Background**: The notebook will not make much sense unless you have a reasonable working knowledge of python language. In particular lists, dictionaries, iterations, control statements. I also make use of the following libraries: NumPy, random, itertools. Pandas is built on NumPy. It is not essential to understand NumPy, but it helps. A separate notebook will be prepared to give basic NumPy functionality instructions. Do not hesitate to get started with pandas solely because you are not familiar with NumPy. Just treat NumPy like any other library to be explored alongside pandas<br/>\n",
      "<br/>\n",
      "**Using this Notebook**: If you are viewing the HMTL version of this notebook, then it is non-interactive i.e. you cannot execute the code in the code cells, you can only observe the output. You could of course copy the code into your python shell. If you have downloaded the .ipynb file then open your command line, change the working directory to that of the downloaded file and open the ipython notebook interface (as described below). You will then be able to interactively use the notebook, execute code cells, add your own code etc. This method is highly recommended\n",
      "\n",
      "**Disclaimer** Much of the text and many of the examples in this notebook are indirectly or directly plagiarized from the pandas documentation, and the Wes McKinney book *Python for Data Analysis*.\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#This should allow for the images to be viewable so is important if using the dynamic version of this notebook:\n",
      "import os\n",
      "os.chdir(os.getcwd())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.core.display import Image\n",
      "Image(filename = 'pandas.jpg')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
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XLkVeBlDHqk+IwrOEUiTFmHWp6n4YxbYxs23lH8v0mnTCdxMeJHoXTTM5VxVLpDGd2SoI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Ztv8AcPkcfE90sA+27Tbz7n6dtI0cly6yoAJ3fUKgNoVgoIB8ca6c4FZeTZPcPiJitrjcL1Z7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\nXsN7W35sxf8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       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "<IPython.core.display.Image at 0x39b9730>"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Contents <br/>\n",
      "#--------------\n",
      "\n",
      "+ Installing Pandas\n",
      "+ The Development Environment\n",
      "+ Importing Pandas\n",
      "+ Series\n",
      "    + Creating Series - The Basic Way\n",
      "    + Creating Series - Lists\n",
      "    + Creating Series - Dictionaries\n",
      "    + Creating Series - NumPy Arrays\n",
      "    + Some Useful things about Series Objects\n",
      "        + Getting and Assigning Values\n",
      "        + Boolean Filtering\n",
      "        + Detecting Null Values\n",
      "        + Boolean Filtering\n",
      "        + Arithmetic Operations and Vectorized Operations - a note\n",
      "        + Reassigning Index Values\n",
      "        + Name Attributes\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br/>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Installing Pandas<br/>\n",
      "#-----------------------<br/>\n",
      "There are many ways to install pandas. If you are an experienced python user then you will need no extra instruction, use `easy_install` or whatever method you generally employ to install new python libraries. \n",
      "\n",
      "If you are new to python, or you are looking for a way to get all the best scientific computing libraries available in one very easy experience then I highly recommend downloading the Enthought Canopy distribution of Python. This comes with pandas, SciPy, Ipython etc. The package is totally free and can be downloaded here: https://www.enthought.com/downloads/\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br/>\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#The Development Environment\n",
      "#----------------------------------------------\n",
      "How you decide to work in python/pandas is entirely up to you. If you decide to download the Canopy Distribution as recommended above, this comes with a very capable and useful Interactive Development Environment that is worth exploring. It is not however my preferred option. \n",
      "\n",
      "I prefer to do one of two things:\n",
      "\n",
      "1. Use a combination of an iPython terminal with a text editor\n",
      "2. Use iPython Notebooks\n",
      "\n",
      "<br/>\n",
      "**Option 1: Accessing the iPython Terminal**<br/>\n",
      "`---------------------------------`<br/>\n",
      "In order to access the ipython terminal simply open up your command line and type `ipython`. Of course, this will not work if you do not have iPython installed. It comes with the Canopy Distribution. When you do this, your command line will look like this:\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Image(filename = 'Ipython.jpg')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "jpeg": 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7I/xC8H/s0eHvjDqPh/7P8OfFWoPpWlav9utn+1XKtcK0fkLIZlwbWflowP3f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UgylmjlRFSPAYK5AOP8U/2Cfiz8FvAGo+JfEnhT7Dp2ifYP7Zhj1OzudQ8Pfbo/MtP7Qs4pWubH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\nFHv+CgXxB+K+geIPD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       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "<IPython.core.display.Image at 0x39b9750>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This is now a fully functioning ipython terminal. You can type commands directly into the terminal. However, the terminal should really be thought of as a tool for testing code that you are writing elsewhere. In any event programming directly into the terminal would be fruitless and frustrating as you can only write one line at a time, and there is no way to get the code out (i.e. preserve what you have done). This is where the text editor comes in. \n",
      "\n",
      "You may think of text editors simply as Microsoft's basic notepad. Well, there are text editors out there that are designed especially for programmers. My preferred one (which is free) is NotePad++. This supports a great number of programming languages, will help with indentation, syntax highlighting etc. \n",
      "\n",
      "The idea is that you write your program in notepad, and then copy across the lines you want to test to the iPython terminal. So my work-screen will typically look like this:\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Image(filename = 'workflow.jpg')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "jpeg": 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Jucj49th4Z8K3GrSyTQ6fpZW61FoJ4ILj7InM3kyTo8KyhclfNXYxG0lN29dT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\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Ya8Kf+pPpVAH81/7Gf/JvvxQ/69H/APUV8W1+n3/BBT/kyTQf+x88Jf8AqRa7X5hfsZf8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\nu8W/tj3+g/G/UIofiB8IH8EabqehWbWrof7Tmj1PCqftP27yk2j96je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ZaFWZjGS2b4v/Y4sdf/AGUNb0Pwz8AdW8G+E7u18JW+oeGIPBWl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\n2Q==\n",
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "<IPython.core.display.Image at 0x39b9650>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The text editor is on the right, and the ipython terminal on the left. I have selected the code I want to test from the notepad and copied it into the terminal. Let's face it though, if you have not already got two screens, get one - it is thought to improve efficiency by up to 40%!\n",
      "\n",
      "You can paste a single line into the iPython terminal by doing a regular Crl-V. If you want to paste multiple lines then you type the word `paste` of `%paste` depending upon how your terminal is configured. \n",
      "\n",
      "The iPython terminal is a wonderful thing, and is worth exploring in great detail. You can find more information here: http://ipython.org/, and there is a very useful chapter on this in the Wes McKinney book *Python for Data Analysis*.\n",
      "\n",
      "\n",
      "<br/>\n",
      "**Option 2: Ipython Notebooks **<br/>\n",
      "`-----------------------`<br/>\n",
      "The iPython notebook is a thing of rare beauty. If you are unsure what one is, then let it be known that you are looking at one right now. They can be either dynamic (i.e. you can execute code) or static (a presentation of the work done). In terms of presenting data flow there is in my opinion no better tool out there. You can use pictures, graphs, code, link to webpages. The possibilities are mind blowing. If you want to present your data work to the outside world then this is the place to do it. It is a command window, log file and do file wrapped into one turbo charged presentation format. \n",
      "\n",
      "To get started creating notebooks then open up your command line and type `ipython notebook`. This will create the .ipynb files associated with the notebook in whichever working directory the command line open in. In order to change that working directory use the `cd` command as normal. \n",
      "\n",
      "These notebooks are well worth getting to know, see the ipython link above for more information.\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br/>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Importing Pandas<br/>\n",
      "#------------------------\n",
      "How you decide to import pandas is largely up to you. However, I follow the following convention"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "import numpy as np\n",
      "from pandas import DataFrame, Series\n",
      "from numpy import nan as NA"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Importing pandas as pd seems to be industry standard. This means rather than writing `pandas.function()` you can simply write `pd.function()` which will save you many hours in the long run. \n",
      "\n",
      "Separately importing the Series and DataFrame functions makes sense as these are the two most common data types. By importing them as above rather than continually writing `pd.DataFrame(data)` you can simply write `DataFrame(data)`, which may stave of carpel tunnel for another year or so. \n",
      "\n",
      "The way that pandas handles missing values is as type np.nan (NaN - \"Not a Number\"). I import the np.nan function as NA. Do not worry about this for now. All it means is that I can write missing values as NA in the code to come. There will be a lot more to say about missing values in future notebooks. Missing values will be dealt with in Part 3.\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br/>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Data Types - Series<br/>\n",
      "#-----------------------------\n",
      "The main innovation of pandas are its data types. The first is Series the second is the DataFrame. We will look at both in turn. \n",
      "\n",
      "<br/>\n",
      "##Creating Series - The Basic Way<br/>\n",
      "A pandas series is a one dimensional array of data. Any object type that is supported by NumPy can be stored in a pandas series. This may not mean much to you practically, but essentially you can store floats, integers, strings, other arrays and of course all NumPy types in a series. If that means nothing to you, worry not. The series is an array of data is what it boils down to. \n",
      "\n",
      "There are many ways to create a series but the most simple is by calling the Series function and placing the data in `([])` parentheses with the data points being separated by commas. See the following example:\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_object1 = Series([4, -7, 5, 3])\n",
      "series_object1 "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "0    4\n",
        "1   -7\n",
        "2    5\n",
        "3    3\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Notice that the series is indexed (the numbers down the left hand column) from 0 to N-1. When no explicit alternative index is passed to the Series creator the series will always be indexed in this manner (i.e. an integer range from 0 to N-1) \n",
      "\n",
      "The values and the index of a series can be accessed by using the values method, and the index method respectively:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_object1.values"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "array([ 4, -7,  5,  3], dtype=int64)"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_object1.index"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "Int64Index([0, 1, 2, 3], dtype=int64)"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In order to pass a customized index other than the default, pass an index within the Series creator in the following manner (noting the comma between the data argument and the index argument):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_object2 = Series([4, -7, 5, 3], index = ['a', 'b', 'c', 'd'])\n",
      "series_object2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "a    4\n",
        "b   -7\n",
        "c    5\n",
        "d    3\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Beware though, the index you pass must be the same length as the series to be created, otherwise you will receive an error:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bad_series = Series([-7, 5, 3], index = ['a', 'b', 'c', 'd'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "AssertionError",
       "evalue": "Index length did not match values",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-10-2dd84c3f6746>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mbad_series\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSeries\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m5\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindex\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;34m'a'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'b'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'c'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'd'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\core\\series.pyc\u001b[0m in \u001b[0;36m__new__\u001b[1;34m(cls, data, index, dtype, name, copy)\u001b[0m\n\u001b[0;32m    490\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    491\u001b[0m             \u001b[0msubarr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msubarr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mview\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mSeries\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 492\u001b[1;33m         \u001b[0msubarr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mindex\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    493\u001b[0m         \u001b[0msubarr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mname\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    494\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\lib.pyd\u001b[0m in \u001b[0;36mpandas.lib.SeriesIndex.__set__ (pandas\\lib.c:29541)\u001b[1;34m()\u001b[0m\n",
        "\u001b[1;31mAssertionError\u001b[0m: Index length did not match values"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Creating Series - Lists<br/>\n",
      "As you may have noticed both the data and the index passed to the Series creator look suspiciously like they are in list format. The upshot of that means that you can also create Series objects from lists in the following manner:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "names_list = ['Rory', 'Cameron', 'Niall', 'Jessica']\n",
      "ipa_code = ['IPA4', 'IPA3', 'IPA2', 'IPA1']\n",
      "ipa_series = Series(names_list, index = ipa_code)\n",
      "ipa_series"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "IPA4       Rory\n",
        "IPA3    Cameron\n",
        "IPA2      Niall\n",
        "IPA1    Jessica\n",
        "dtype: object"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This of course means that you can make use of the incredibly handy list comprehension syntax provided by python. In this more complex example I create a Series of random data that are indexed by a unique code (could be a UID for example):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import random\n",
      "import itertools\n",
      "random_numbers = [random.random() for x in xrange(1, 101)]\n",
      "UIDs = [['UID00' + str(x) for x in xrange(1, 10)], ['UID0' + str(x) for x in xrange(10, 100)], ['UID100']]\n",
      "\n",
      "random_series = Series(random_numbers, index = list(itertools.chain(*UIDs)))\n",
      "random_series"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "UID001    0.558002\n",
        "UID002    0.070470\n",
        "UID003    0.471070\n",
        "UID004    0.373464\n",
        "UID005    0.834773\n",
        "UID006    0.856495\n",
        "UID007    0.335185\n",
        "UID008    0.465316\n",
        "UID009    0.999313\n",
        "UID010    0.891125\n",
        "UID011    0.594083\n",
        "UID012    0.477164\n",
        "UID013    0.719402\n",
        "UID014    0.366637\n",
        "UID015    0.431083\n",
        "...\n",
        "UID086    0.265681\n",
        "UID087    0.602370\n",
        "UID088    0.299581\n",
        "UID089    0.372964\n",
        "UID090    0.686555\n",
        "UID091    0.999915\n",
        "UID092    0.259033\n",
        "UID093    0.066518\n",
        "UID094    0.782167\n",
        "UID095    0.730126\n",
        "UID096    0.441953\n",
        "UID097    0.583702\n",
        "UID098    0.385316\n",
        "UID099    0.099698\n",
        "UID100    0.145814\n",
        "Length: 100, dtype: float64"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Notice that when you attempt to display a large Series, only the first few and last few index values will be displayed. This is an issue that will be discussed in Part 3. \n",
      "\n",
      "<br/>\n",
      "##Creating Series - Dictionaries<br/>\n",
      "As a final convenience python dictionaries can also be passed to the Series creator. The sorted keys becomes the index, and the values becomes the series data. See the following example:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_dict = {'Ohio': 35000, 'Texas': 71000, 'Oregon': 16000, 'Utah': 5000}\n",
      "series_object3 = Series(series_dict)\n",
      "series_object3 "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "Ohio      35000\n",
        "Oregon    16000\n",
        "Texas     71000\n",
        "Utah       5000\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Although it seems unlikely that you would want to do this, you can also separately pass an index to the Series creator when calling it with a python dictionary. When this method is used if any of the values in the index do not match the keys in the dictionary, then a `NaN` value will be entered into the Series (`NaN` means not a number, like the stata `.` - more on this later). See the following example (note that the series_dict object is the same as that created above):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "states = ['California', 'Ohio', 'Oregon', 'Texas']\n",
      "series_object4 = Series(series_dict, index=states)\n",
      "series_object4"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "California      NaN\n",
        "Ohio          35000\n",
        "Oregon        16000\n",
        "Texas         71000\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "'Utah' was not in the list passed as the index so the dictionary entry for Utah was replaced with NaN."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Creating Series - NumPy Arrays<br/>\n",
      "Of course you can also create Series from numpy arrays. If you are not aware of NumPy, then please see accompanying notebook (in production). "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "npArray = np.arange(10, 15.25, 0.25)\n",
      "series_object5 = Series(npArray)\n",
      "series_object5"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "0     10.00\n",
        "1     10.25\n",
        "2     10.50\n",
        "3     10.75\n",
        "4     11.00\n",
        "5     11.25\n",
        "6     11.50\n",
        "7     11.75\n",
        "8     12.00\n",
        "9     12.25\n",
        "10    12.50\n",
        "11    12.75\n",
        "12    13.00\n",
        "13    13.25\n",
        "14    13.50\n",
        "15    13.75\n",
        "16    14.00\n",
        "17    14.25\n",
        "18    14.50\n",
        "19    14.75\n",
        "20    15.00\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Note that the Series object behaves very similarly to the NumPy ndarray and a Series is a valid argument to most NumPy functions (pandas is built on NumPy). For those that are interested in one of the differences (ignore this if not familiar with NumPy), whilst indexing/slicing an NumPy ndarray slices only the value(s), indexing/slicing a pandas Series also slices the index. Compare the two cells below:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "array_slice = npArray = np.arange(10, 12, 0.25)\n",
      "array_slice[4:8]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "array([ 11.  ,  11.25,  11.5 ,  11.75])"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_slice = Series(array_slice)\n",
      "series_slice[4:8]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "4    11.00\n",
        "5    11.25\n",
        "6    11.50\n",
        "7    11.75\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Some Useful things about Series Objects<br/>\n",
      "###Getting and Assigning Values<br/>\n",
      "Series objects behave like python dictionaries in that values can be accessed and assigned by index label. If the following examples do not make sense to you, then consider revisiting what you know about python dictionaries:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_object6 = Series([random.randint(1, 100) for x in xrange(4)], index = ['a', 'b', 'c', 'd'])\n",
      "series_object6                                                       "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "a     70\n",
        "b     90\n",
        "c    100\n",
        "d     52\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Get a value by passing index label:\n",
      "series_object6['a']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "70"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Assign a value by passing index label\n",
      "series_object6['b'] = 1000\n",
      "series_object6"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "a      70\n",
        "b    1000\n",
        "c     100\n",
        "d      52\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "If a label is passed that is not in the index then an exception is raised. In other words, you cannot add an index point by assigning in this manner:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_object6['e'] = 1000"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "KeyError",
       "evalue": "'e not in this series!'",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-21-eefc82b43bc1>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mseries_object6\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'e'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1000\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[1;32mC:\\Anaconda\\lib\\site-packages\\pandas\\core\\series.pyc\u001b[0m in \u001b[0;36m__setitem__\u001b[1;34m(self, key, value)\u001b[0m\n\u001b[0;32m    829\u001b[0m                 \u001b[1;32mreturn\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    830\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 831\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'%s not in this series!'\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    832\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    833\u001b[0m             \u001b[1;31m# python 3 type errors should be raised\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;31mKeyError\u001b[0m: 'e not in this series!'"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can use the `get` method to get a value from the series. If the index label passed to `get` is not in the series index `None` is returned, or whatever you specify as the optional second paramter to the `get` method:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_object6.get('c')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 22,
       "text": [
        "100"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_object6.get('e') is None"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 23,
       "text": [
        "True"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "series_object6.get('e', 'Nothing to See Here')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 24,
       "text": [
        "'Nothing to See Here'"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Also like a dictionary you can test membership of the series"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "'d' in series_object6"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 25,
       "text": [
        "True"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "'e' in series_object6"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "False"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "###Boolean Filtering<br/>\n",
      "Similar to the syntax displayed above (and unlike with python dicts) it is possible to filter a series using Boolean logic. If you conceptualize the above as filtering data, but filtering out all but one value of data, then consider that using Boolean logic we might filter out none up to all of the data. \n",
      "\n",
      "The syntax for Boolean filtering seems odd at first: `object[object condition]`. The resulting view of the series will be indexed as the original series but will only contain those values that pass the Boolean condition:\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bool_series = Series([4, 7, -5, 3, NA, NA, -8], index=['d', 'b', 'a', 'c', 'd', 'e', 'f'])\n",
      "bool_series[bool_series > 3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 27,
       "text": [
        "d    4\n",
        "b    7\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here you have filtered out data in the series that is not greater than three."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "###Detecting Null Values<br/>\n",
      "Recall that missing values in pandas as represented as NumPy type np.nan i.e. NaN i.e. Not a number. Do not worry about how these behave in general. More will be said about these values in Part 3. Recall also, that as I imported the np.nan function as NA, I can represent a missing value in data as NA when writing code:\n",
      "\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "null_series = Series([1, NA, 23, NA, '.', 2.3], index = ['q', 'w', 'e', 'r', 't', 'y'])\n",
      "null_series"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 28,
       "text": [
        "q      1\n",
        "w    NaN\n",
        "e     23\n",
        "r    NaN\n",
        "t      .\n",
        "y    2.3\n",
        "dtype: object"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Sometimes it is very useful to be able to detect null values in a series. There are two ways to do this, and they are the polar opposites of each other. The `pd.isnull()` function returns a new series indexed in the same manner as the function passed as argument, who's values are Booleans that state whether the value at the same index point in the series passed is null. The `pd.notnull()` does the opposite. In the following example (STATA users beware!) notice that '.' is NOT a missing value:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pd.isnull(null_series)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 29,
       "text": [
        "q    False\n",
        "w     True\n",
        "e    False\n",
        "r     True\n",
        "t    False\n",
        "y    False\n",
        "dtype: bool"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pd.notnull(null_series)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 30,
       "text": [
        "q     True\n",
        "w    False\n",
        "e     True\n",
        "r    False\n",
        "t     True\n",
        "y     True\n",
        "dtype: bool"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "One useful way to make use of this is to convert the resulting series to a list, and use the built in list method `count` to understand how many null values there are:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "list(pd.isnull(null_series)).count(False)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 31,
       "text": [
        "4"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Note that both of these functions are available as instance methods which allows for the following syntax:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "null_series.notnull()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 32,
       "text": [
        "q     True\n",
        "w    False\n",
        "e     True\n",
        "r    False\n",
        "t     True\n",
        "y     True\n",
        "dtype: bool"
       ]
      }
     ],
     "prompt_number": 32
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "###Arithmetic Operations and Vectorized Operations<br/>\n",
      "What the above few sections should indicate to you is that it is not necessary to explicitly loop through each value in a Series in order to perform operation on them. This has important consequences when doing arithmetic with series objects. This will be explored further in Part 3. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "###Reassigning an Index<br/>\n",
      "An index can be reassigned very simply. Let's stick with the null_series object created above. Simply assign a list of values as the new index to the index attribute of the series to be altered. Clearly the new index must be the same length as the original index that is being changed otherwise an exception will be raised.\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "null_series.index = ['UID01', 'UID02', 'UID03', 'UID04', 'UID05', 'UID06']\n",
      "null_series"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 33,
       "text": [
        "UID01      1\n",
        "UID02    NaN\n",
        "UID03     23\n",
        "UID04    NaN\n",
        "UID05      .\n",
        "UID06    2.3\n",
        "dtype: object"
       ]
      }
     ],
     "prompt_number": 33
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "###Name Attributes<br/>\n",
      "The series object has name attributes for the values and the index and these can be assigned should that be desired. Continuing with the null_series object created above this is achieved as follows:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "null_series.name = \"Possibly Null Data\"\n",
      "null_series.index.name = \"UID\"\n",
      "null_series"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 34,
       "text": [
        "UID\n",
        "UID01      1\n",
        "UID02    NaN\n",
        "UID03     23\n",
        "UID04    NaN\n",
        "UID05      .\n",
        "UID06    2.3\n",
        "Name: Possibly Null Data, dtype: object"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br/>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**Congratulations you now know about Series objects in Pandas!!! But this is just the beginning. In part two we will look at the Data Frame which is where your mind will really start to get blown! Stick with it..... **"
     ]
    }
   ],
   "metadata": {}
  }
 ]
}