30-June-19.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1505]\n",
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      "[1505, 1540, 1575, 1610]\n",
      "[1505, 1540, 1575, 1610, 1645]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345, 2380]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345, 2380, 2415]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345, 2380, 2415, 2450]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345, 2380, 2415, 2450, 2485]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345, 2380, 2415, 2450, 2485, 2520]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345, 2380, 2415, 2450, 2485, 2520, 2555]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345, 2380, 2415, 2450, 2485, 2520, 2555, 2590]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345, 2380, 2415, 2450, 2485, 2520, 2555, 2590, 2625]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345, 2380, 2415, 2450, 2485, 2520, 2555, 2590, 2625, 2660]\n",
      "[1505, 1540, 1575, 1610, 1645, 1680, 1715, 1750, 1785, 1820, 1855, 1890, 1925, 1960, 1995, 2030, 2065, 2100, 2135, 2170, 2205, 2240, 2275, 2310, 2345, 2380, 2415, 2450, 2485, 2520, 2555, 2590, 2625, 2660, 2695]\n"
     ]
    }
   ],
   "source": [
    "l=[]\n",
    "for i in range(1500,2700+1):\n",
    "    if(i%7==0 and i%5==0):\n",
    "        l.append(i)\n",
    "        print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9\n",
      "1\n",
      "2\n",
      "9\n",
      "w\n"
     ]
    }
   ],
   "source": [
    "from random import randint\n",
    "x,z=randint(1,9),0\n",
    "print(x)\n",
    "\n",
    "while x!=z:\n",
    "    z=int(input())\n",
    "print(\"w\")\n",
    "\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Guess a number between 1 and 10 until you get it right : 5\n",
      "Guess a number between 1 and 10 until you get it right : 2\n",
      "Guess a number between 1 and 10 until you get it right : 1\n",
      "Well guessed!\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "target_num, guess_num = random.randint(1, 10), 0\n",
    "while target_num != guess_num:\n",
    "    guess_num = int(input('Guess a number between 1 and 10 until you get it right : '))\n",
    "print('Well guessed!')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rty\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'ytr'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=input()\n",
    "y=x[::-1]\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n",
      "5\n"
     ]
    }
   ],
   "source": [
    "x=(1,2,3,4,5,6,7,8,9)\n",
    "x1=0\n",
    "x2=0\n",
    "for i in x:\n",
    "    if i%2==0:\n",
    "        x1+=1\n",
    "    else:\n",
    "        x2+=1\n",
    "print(x1)\n",
    "print(x2)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 1 2 4 5 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "for i in range(6):\n",
    "    if(i==3 or i==6):\n",
    "        continue\n",
    "    print(i,end=\" \")\n",
    "print(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "1\n",
      "2\n",
      "3\n",
      "5\n",
      "8\n",
      "13\n",
      "21\n",
      "34\n"
     ]
    }
   ],
   "source": [
    "x,y=0,1\n",
    "while y<50:\n",
    "    print(y)\n",
    "    x,y=y,x+y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ert\n",
      "ERT\n"
     ]
    }
   ],
   "source": [
    "l1=[]\n",
    "while 1:\n",
    "    s=input()\n",
    "    if s:\n",
    "        l1.append(s.upper())\n",
    "    break\n",
    "for i in l1:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas\n",
    "## Python library for Data Analysis\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Pandas - Data Analysis\n",
    "Series Object - one-dimensional data\n",
    "DataFrame Object - two-dimensional data\n",
    "Reading Data from CSV files into DataFrames\n",
    "Processing/Accessing DataFrames\n",
    "Columns\n",
    "Rows\n",
    "Updating DataFrames\n",
    "Writing DataFrame back to CSV files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# # Function to read csv data into data frame and returns dataframe object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GEOID</th>\n",
       "      <th>State</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>04000US01</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>37150</td>\n",
       "      <td>37952</td>\n",
       "      <td>42212</td>\n",
       "      <td>44476</td>\n",
       "      <td>39980</td>\n",
       "      <td>40933</td>\n",
       "      <td>42590</td>\n",
       "      <td>43464</td>\n",
       "      <td>41381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>04000US02</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>55891</td>\n",
       "      <td>56418</td>\n",
       "      <td>62993</td>\n",
       "      <td>63989</td>\n",
       "      <td>61604</td>\n",
       "      <td>57848</td>\n",
       "      <td>57431</td>\n",
       "      <td>63648</td>\n",
       "      <td>61137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>04000US04</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>45245</td>\n",
       "      <td>46657</td>\n",
       "      <td>47215</td>\n",
       "      <td>46914</td>\n",
       "      <td>2345</td>\n",
       "      <td>46896</td>\n",
       "      <td>48621</td>\n",
       "      <td>47044</td>\n",
       "      <td>50602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>04000US05</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>36658</td>\n",
       "      <td>37057</td>\n",
       "      <td>40795</td>\n",
       "      <td>39586</td>\n",
       "      <td>36538</td>\n",
       "      <td>38587</td>\n",
       "      <td>41302</td>\n",
       "      <td>39018</td>\n",
       "      <td>39919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>04000US06</td>\n",
       "      <td>California</td>\n",
       "      <td>51755</td>\n",
       "      <td>55319</td>\n",
       "      <td>55734</td>\n",
       "      <td>57014</td>\n",
       "      <td>56134</td>\n",
       "      <td>54283</td>\n",
       "      <td>53367</td>\n",
       "      <td>57020</td>\n",
       "      <td>57528</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       GEOID       State   2005   2006   2007   2008   2009   2010   2011  \\\n",
       "0  04000US01     Alabama  37150  37952  42212  44476  39980  40933  42590   \n",
       "1  04000US02      Alaska  55891  56418  62993  63989  61604  57848  57431   \n",
       "2  04000US04     Arizona  45245  46657  47215  46914   2345  46896  48621   \n",
       "3  04000US05    Arkansas  36658  37057  40795  39586  36538  38587  41302   \n",
       "4  04000US06  California  51755  55319  55734  57014  56134  54283  53367   \n",
       "\n",
       "    2012   2013  \n",
       "0  43464  41381  \n",
       "1  63648  61137  \n",
       "2  47044  50602  \n",
       "3  39018  39919  \n",
       "4  57020  57528  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filepath=\"data files/income.csv\"\n",
    "import pandas as pd\n",
    "def readcsvdataframe(filepath):       #displaying the csv file\n",
    "    return pd.read_csv(filepath)   \n",
    "readcsvdataframe(filepath)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# print only columns in a format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GEOID State 2005 2006 2007 2008 2009 2010 2011 2012 2013 "
     ]
    }
   ],
   "source": [
    "\n",
    "incomedf=readcsvdataframe(filepath)\n",
    "#Function to print all column names in a single line\n",
    "def printdataframecolumns(df):\n",
    "    columns=df.columns\n",
    "    for i in columns:\n",
    "        print(i,end=\" \")\n",
    "    return \n",
    "df=incomedf\n",
    "printdataframecolumns(df)\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Function to acesses a specific row based on state name(unique column value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "04000US02 Alaska 55891 56418 62993 63989 61604 57848 57431 63648 61137 None\n",
      "04000US06 California 51755 55319 55734 57014 56134 54283 53367 57020 57528 None\n"
     ]
    }
   ],
   "source": [
    "\n",
    "def acessesdataframerow(df,key):\n",
    "    for row in df.values:\n",
    "        if key in row:\n",
    "            for item in row:\n",
    "                print(item,end=\" \")\n",
    "    return\n",
    "                \n",
    "print(acessesdataframerow(incomedf,'Alaska')) \n",
    "print(acessesdataframerow(incomedf,'04000US06'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "46657"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "incomedf.values[2][3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(incomedf.values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  Function to accessing unique value based on row,column information\n",
    "# income of a state in a year by using Index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "56134\n",
      "39586\n"
     ]
    }
   ],
   "source": [
    "def getrowindex(df,rowkey):\n",
    "    for i in range(len(df.values)):\n",
    "        if df.values[1][0]==rowkey or df.values[i][1]==rowkey:\n",
    "            rowindex=i\n",
    "    return rowindex\n",
    "\n",
    "\n",
    "def getcolumnindex(df,columnkey):\n",
    "    for i in range(len(df.columns)):\n",
    "        if df.columns[i]==columnkey:\n",
    "            columnindex=i\n",
    "    return columnindex\n",
    "\n",
    "                \n",
    "def Valuefromrowcolumn(df,rowkey,columnkey):\n",
    "    rowindex=getrowindex(df,rowkey)\n",
    "    columnindex=getcolumnindex(df,columnkey)\n",
    "    return df.values[rowindex][columnindex]\n",
    "print(Valuefromrowcolumn(incomedf,'California','2009'))\n",
    "print(Valuefromrowcolumn(incomedf,'Arkansas','2008'))\n",
    "    \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Function to update data based on rowkey and columnkey"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GEOID</th>\n",
       "      <th>State</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>04000US01</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>37150</td>\n",
       "      <td>37952</td>\n",
       "      <td>42212</td>\n",
       "      <td>44476</td>\n",
       "      <td>39980</td>\n",
       "      <td>40933</td>\n",
       "      <td>42590</td>\n",
       "      <td>43464</td>\n",
       "      <td>41381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>04000US02</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>55891</td>\n",
       "      <td>56418</td>\n",
       "      <td>62993</td>\n",
       "      <td>63989</td>\n",
       "      <td>61604</td>\n",
       "      <td>57848</td>\n",
       "      <td>57431</td>\n",
       "      <td>63648</td>\n",
       "      <td>61137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>04000US04</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>45245</td>\n",
       "      <td>46657</td>\n",
       "      <td>47215</td>\n",
       "      <td>46914</td>\n",
       "      <td>2345</td>\n",
       "      <td>46896</td>\n",
       "      <td>48621</td>\n",
       "      <td>47044</td>\n",
       "      <td>50602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>04000US05</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>36658</td>\n",
       "      <td>37057</td>\n",
       "      <td>40795</td>\n",
       "      <td>39586</td>\n",
       "      <td>36538</td>\n",
       "      <td>38587</td>\n",
       "      <td>41302</td>\n",
       "      <td>39018</td>\n",
       "      <td>39919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>04000US06</td>\n",
       "      <td>California</td>\n",
       "      <td>51755</td>\n",
       "      <td>55319</td>\n",
       "      <td>55734</td>\n",
       "      <td>57014</td>\n",
       "      <td>56134</td>\n",
       "      <td>54283</td>\n",
       "      <td>53367</td>\n",
       "      <td>57020</td>\n",
       "      <td>57528</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       GEOID       State   2005   2006   2007   2008   2009   2010   2011  \\\n",
       "0  04000US01     Alabama  37150  37952  42212  44476  39980  40933  42590   \n",
       "1  04000US02      Alaska  55891  56418  62993  63989  61604  57848  57431   \n",
       "2  04000US04     Arizona  45245  46657  47215  46914   2345  46896  48621   \n",
       "3  04000US05    Arkansas  36658  37057  40795  39586  36538  38587  41302   \n",
       "4  04000US06  California  51755  55319  55734  57014  56134  54283  53367   \n",
       "\n",
       "    2012   2013  \n",
       "0  43464  41381  \n",
       "1  63648  61137  \n",
       "2  47044  50602  \n",
       "3  39018  39919  \n",
       "4  57020  57528  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Function to update data based on rowkey and columnkey\n",
    "def updatedatafromrowcolumn(df,rowkey,columnkey,newdata):\n",
    "    rowindex=getrowindex(df,rowkey)\n",
    "    columnindex=getcolumnindex(df,columnkey)\n",
    "    row=df.values[rowindex]\n",
    "    row[columnindex]=newdata\n",
    "    df.loc[rowindex]=row\n",
    "    return \n",
    "\n",
    "updatedatafromrowcolumn(incomedf,'Arizona','2009',2345)\n",
    "incomedf  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "04000US02 Alaska 55891 56418 62993 63989 61604 57848 57431 63648 61137 "
     ]
    }
   ],
   "source": [
    "acessesdataframerow(incomedf,62993)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to write dtat frame to csv\n",
    "incomedf.to_csv(filepath,index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Function to add a new row of data to DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GEOID</th>\n",
       "      <th>State</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>04000US01</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>37150</td>\n",
       "      <td>37952</td>\n",
       "      <td>42212</td>\n",
       "      <td>44476</td>\n",
       "      <td>39980</td>\n",
       "      <td>40933</td>\n",
       "      <td>42590</td>\n",
       "      <td>43464</td>\n",
       "      <td>41381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>04000US02</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>55891</td>\n",
       "      <td>56418</td>\n",
       "      <td>62993</td>\n",
       "      <td>63989</td>\n",
       "      <td>61604</td>\n",
       "      <td>57848</td>\n",
       "      <td>57431</td>\n",
       "      <td>63648</td>\n",
       "      <td>61137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>04000US04</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>45245</td>\n",
       "      <td>46657</td>\n",
       "      <td>47215</td>\n",
       "      <td>46914</td>\n",
       "      <td>2345</td>\n",
       "      <td>46896</td>\n",
       "      <td>48621</td>\n",
       "      <td>47044</td>\n",
       "      <td>50602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>04000US05</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>36658</td>\n",
       "      <td>37057</td>\n",
       "      <td>40795</td>\n",
       "      <td>39586</td>\n",
       "      <td>36538</td>\n",
       "      <td>38587</td>\n",
       "      <td>41302</td>\n",
       "      <td>39018</td>\n",
       "      <td>39919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>04000US06</td>\n",
       "      <td>California</td>\n",
       "      <td>51755</td>\n",
       "      <td>55319</td>\n",
       "      <td>55734</td>\n",
       "      <td>57014</td>\n",
       "      <td>56134</td>\n",
       "      <td>54283</td>\n",
       "      <td>53367</td>\n",
       "      <td>57020</td>\n",
       "      <td>57528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>56</td>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>313</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       GEOID       State   2005   2006   2007   2008   2009   2010   2011  \\\n",
       "0  04000US01     Alabama  37150  37952  42212  44476  39980  40933  42590   \n",
       "1  04000US02      Alaska  55891  56418  62993  63989  61604  57848  57431   \n",
       "2  04000US04     Arizona  45245  46657  47215  46914   2345  46896  48621   \n",
       "3  04000US05    Arkansas  36658  37057  40795  39586  36538  38587  41302   \n",
       "4  04000US06  California  51755  55319  55734  57014  56134  54283  53367   \n",
       "5          1           2      3      4      5     56     13     14    313   \n",
       "\n",
       "    2012   2013  \n",
       "0  43464  41381  \n",
       "1  63648  61137  \n",
       "2  47044  50602  \n",
       "3  39018  39919  \n",
       "4  57020  57528  \n",
       "5     12      0  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "def addRowDataDataFrame(df, rowdata):\n",
    "    lastrowindex = len(df.values)-1\n",
    "    df.loc[lastrowindex+1] = rowdata\n",
    "    return\n",
    "\n",
    "rowdata = [1,2,3,4,5,56,13,14,313,12,0]\n",
    "addRowDataDataFrame(incomedf, rowdata)\n",
    "incomedf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Function to delete a row in a DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "ename": "UnboundLocalError",
     "evalue": "local variable 'rowindex' referenced before assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mUnboundLocalError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-51-65aea27edc09>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrowindex\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m \u001b[0mincomedf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdeleteRowDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mincomedf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\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      7\u001b[0m \u001b[0mincomedf\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-51-65aea27edc09>\u001b[0m in \u001b[0;36mdeleteRowDataFrame\u001b[1;34m(df, rowkey)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# Function to delete a row in a DataFrame\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdeleteRowDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrowkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[0mrowindex\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mgetrowindex\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrowkey\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      4\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrowindex\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-42-537c8fae3691>\u001b[0m in \u001b[0;36mgetrowindex\u001b[1;34m(df, rowkey)\u001b[0m\n\u001b[0;32m      3\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m==\u001b[0m\u001b[0mrowkey\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m==\u001b[0m\u001b[0mrowkey\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m             \u001b[0mrowindex\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mrowindex\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mUnboundLocalError\u001b[0m: local variable 'rowindex' referenced before assignment"
     ]
    }
   ],
   "source": [
    "\n",
    "def deleteRowDataFrame(df, rowkey):\n",
    "    rowindex=getrowindex(df,rowkey)\n",
    "    return df.drop(rowindex) \n",
    "\n",
    "incomedf = deleteRowDataFrame(incomedf, 1)\n",
    "incomedf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "m=np.random.randint(2,5,size=(3,1,3,2))\n",
    "m[1][0][2][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[[3, 4],\n",
       "         [4, 2],\n",
       "         [3, 4]]],\n",
       "\n",
       "\n",
       "       [[[4, 2],\n",
       "         [3, 3],\n",
       "         [2, 4]]],\n",
       "\n",
       "\n",
       "       [[[2, 2],\n",
       "         [3, 4],\n",
       "         [4, 3]]]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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 },
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