{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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   "outputs": [],
   "source": [
    "# IMPORT\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas Data Structure - Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1\n",
      "1    2\n",
      "2    3\n",
      "3   -3\n",
      "4    4\n",
      "5    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "sr = pd.Series([1,2,3,-3,4,0])\n",
    "print(sr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 1  2  3 -3  4  0]\n"
     ]
    }
   ],
   "source": [
    "# get values frm Series\n",
    "print(sr.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RangeIndex(start=0, stop=6, step=1)\n"
     ]
    }
   ],
   "source": [
    "# get indexes from Series\n",
    "print(sr.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2nd indexed value: 3 \n",
      "adding 2nd + 4rd index: 7\n"
     ]
    }
   ],
   "source": [
    "# some calc on Seires\n",
    "print(\"2nd indexed value:\",sr[2],\n",
    "      \"\\nadding 2nd + 4rd index:\", sr[2]+sr[4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a    1\n",
      "b    2\n",
      "c    0\n",
      "d   -3\n",
      "e    4\n",
      "f   -6\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# creating Series with named index\n",
    "sr1 = pd.Series([1,2,0,-3,4,-6], index=['a','b','c','d','e','f'])\n",
    "print(sr1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a \t 1\n",
      "b \t 2\n",
      "c \t 0\n",
      "d \t -3\n",
      "e \t 4\n",
      "f \t -6\n"
     ]
    }
   ],
   "source": [
    "for e in sr1.index:\n",
    "    print(e, \"\\t\", sr1[e])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a    1\n",
      "b    2\n",
      "c    0\n",
      "e    4\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# getting only positive values from Series\n",
    "print(sr1[sr1>=0])   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Texas': 71000, 'Oregon': 16000, 'Ohio': 35000, 'Utah': 5000} <class 'dict'>\n"
     ]
    }
   ],
   "source": [
    "# we can convert a dictionary into Series\n",
    "sdata = {'Ohio': 35000, 'Texas': 71000, 'Oregon': 16000, 'Utah': 5000}\n",
    "print(sdata, type(sdata))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ohio      35000\n",
      "Oregon    16000\n",
      "Texas     71000\n",
      "Utah       5000\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "sr2 = pd.Series(sdata)\n",
    "print(sr2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "California        NaN\n",
      "Alabama           NaN\n",
      "Oregon        16000.0\n",
      "Texas         71000.0\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "ind = ['California', 'Alabama', 'Oregon', 'Texas']\n",
    "sr3 = pd.Series(sdata, index=ind)\n",
    "print(sr3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "California     True\n",
      "Alabama        True\n",
      "Oregon        False\n",
      "Texas         False\n",
      "dtype: bool\n"
     ]
    }
   ],
   "source": [
    "# Californica and Alabama's value is NaN (Not a Number) cause there is no value for these index in sdata\n",
    "# let's check for NULLability\n",
    "print(pd.isnull(sr3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "California    False\n",
      "Alabama       False\n",
      "Oregon         True\n",
      "Texas          True\n",
      "dtype: bool\n"
     ]
    }
   ],
   "source": [
    "print(pd.notnull(sr3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Alabama            NaN\n",
      "California         NaN\n",
      "Ohio               NaN\n",
      "Oregon         32000.0\n",
      "Texas         142000.0\n",
      "Utah               NaN\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(sr2+sr3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Population\n",
      "California        NaN\n",
      "Alabama           NaN\n",
      "Oregon        16000.0\n",
      "Texas         71000.0\n",
      "Name: States, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# Series object can have Name and index Name\n",
    "sr3.name = \"States\"\n",
    "sr3.index.name = \"Population\"\n",
    "print(sr3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "States \t (4,) \t 4\n"
     ]
    }
   ],
   "source": [
    "# Stats about Series\n",
    "print(sr3.name,\"\\t\",sr3.shape,\"\\t\",len(sr3))  #print name, shape and length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['California', 'Alabama', 'Oregon', 'Texas'], dtype='object', name='Population') \t Population\n"
     ]
    }
   ],
   "source": [
    "print(sr3.index,\"\\t\",sr3.index.name)  #print indexes and index name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "float64\n"
     ]
    }
   ],
   "source": [
    "print(sr3.dtype)  #print data type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[    nan     nan  16000.  71000.]\n"
     ]
    }
   ],
   "source": [
    "print(sr3.values) #print Series values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
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