pandas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Object-Creation\" data-toc-modified-id=\"Object-Creation-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Object Creation</a></span></li><li><span><a href=\"#Veiwing-Data\" data-toc-modified-id=\"Veiwing-Data-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Veiwing Data</a></span></li><li><span><a href=\"#Selection\" data-toc-modified-id=\"Selection-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Selection</a></span></li><li><span><a href=\"#Missing-Data\" data-toc-modified-id=\"Missing-Data-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Missing Data</a></span></li></ul></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# pandas\n",
    "pandas is an open source, BSD-licensed library providing high-performance, easy-to-use **data structures and data analysis tools** for the Python programming language.\n",
    "\n",
    "you can refer to [pandas cheat sheet](http://pandas.pydata.org/Pandas_Cheat_Sheet.pdf) and [pandas tutorial](https://pandas.pydata.org/pandas-docs/stable/getting_started/tutorials.html) for details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Object Creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "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"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating a Series by passing a list of values, letting pandas create a default integer index:\n",
    "\n",
    "s = pd.Series([1,3,5, np.nan, 6, 8]) \n",
    "\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>-1.444036</td>\n",
       "      <td>0.004337</td>\n",
       "      <td>-2.584044</td>\n",
       "      <td>0.051296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-0.544770</td>\n",
       "      <td>-0.149141</td>\n",
       "      <td>-0.991055</td>\n",
       "      <td>-1.342031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>1.364917</td>\n",
       "      <td>-0.035276</td>\n",
       "      <td>1.513094</td>\n",
       "      <td>1.694041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.999942</td>\n",
       "      <td>0.421217</td>\n",
       "      <td>-0.704924</td>\n",
       "      <td>1.157883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.370461</td>\n",
       "      <td>2.342387</td>\n",
       "      <td>-1.316925</td>\n",
       "      <td>-0.437568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>0.204145</td>\n",
       "      <td>0.121449</td>\n",
       "      <td>0.716255</td>\n",
       "      <td>-0.951278</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01 -1.444036  0.004337 -2.584044  0.051296\n",
       "2013-01-02 -0.544770 -0.149141 -0.991055 -1.342031\n",
       "2013-01-03  1.364917 -0.035276  1.513094  1.694041\n",
       "2013-01-04 -0.999942  0.421217 -0.704924  1.157883\n",
       "2013-01-05 -1.370461  2.342387 -1.316925 -0.437568\n",
       "2013-01-06  0.204145  0.121449  0.716255 -0.951278"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating a DataFrame by passing a NumPy array, with a datetime index and labeled columns:\n",
    "\n",
    "dates = pd.date_range('20130101', periods=6)\n",
    "\n",
    "dates\n",
    "\n",
    "df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     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\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "A           float64\n",
       "B    datetime64[ns]\n",
       "C           float32\n",
       "D             int32\n",
       "E          category\n",
       "F            object\n",
       "dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating a DataFrame by passing a dict of objects that can be converted to series-like.\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(df2)\n",
    "df2.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Veiwing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>A</th>\n",
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       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-0.544770</td>\n",
       "      <td>-0.149141</td>\n",
       "      <td>-0.991055</td>\n",
       "      <td>-1.342031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>1.364917</td>\n",
       "      <td>-0.035276</td>\n",
       "      <td>1.513094</td>\n",
       "      <td>1.694041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.999942</td>\n",
       "      <td>0.421217</td>\n",
       "      <td>-0.704924</td>\n",
       "      <td>1.157883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.370461</td>\n",
       "      <td>2.342387</td>\n",
       "      <td>-1.316925</td>\n",
       "      <td>-0.437568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>0.204145</td>\n",
       "      <td>0.121449</td>\n",
       "      <td>0.716255</td>\n",
       "      <td>-0.951278</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-02 -0.544770 -0.149141 -0.991055 -1.342031\n",
       "2013-01-03  1.364917 -0.035276  1.513094  1.694041\n",
       "2013-01-04 -0.999942  0.421217 -0.704924  1.157883\n",
       "2013-01-05 -1.370461  2.342387 -1.316925 -0.437568\n",
       "2013-01-06  0.204145  0.121449  0.716255 -0.951278"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.999942</td>\n",
       "      <td>0.421217</td>\n",
       "      <td>-0.704924</td>\n",
       "      <td>1.157883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.370461</td>\n",
       "      <td>2.342387</td>\n",
       "      <td>-1.316925</td>\n",
       "      <td>-0.437568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>0.204145</td>\n",
       "      <td>0.121449</td>\n",
       "      <td>0.716255</td>\n",
       "      <td>-0.951278</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-04 -0.999942  0.421217 -0.704924  1.157883\n",
       "2013-01-05 -1.370461  2.342387 -1.316925 -0.437568\n",
       "2013-01-06  0.204145  0.121449  0.716255 -0.951278"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "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')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1.44403566,  0.00433673, -2.58404448,  0.05129626],\n",
       "       [-0.54477013, -0.1491408 , -0.99105485, -1.34203082],\n",
       "       [ 1.36491709, -0.03527627,  1.51309416,  1.69404076],\n",
       "       [-0.99994231,  0.42121657, -0.70492418,  1.15788298],\n",
       "       [-1.37046126,  2.342387  , -1.31692542, -0.43756772],\n",
       "       [ 0.20414505,  0.12144924,  0.71625519, -0.95127831]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.0, Timestamp('2013-01-02 00:00:00'), 1.0, 3, 'test', 'foo'],\n",
       "       [1.0, Timestamp('2013-01-02 00:00:00'), 1.0, 3, 'train', 'foo'],\n",
       "       [1.0, Timestamp('2013-01-02 00:00:00'), 1.0, 3, 'test', 'foo'],\n",
       "       [1.0, Timestamp('2013-01-02 00:00:00'), 1.0, 3, 'train', 'foo']],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.465025</td>\n",
       "      <td>0.450829</td>\n",
       "      <td>-0.561267</td>\n",
       "      <td>0.028724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.083259</td>\n",
       "      <td>0.946887</td>\n",
       "      <td>1.469901</td>\n",
       "      <td>1.192107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.444036</td>\n",
       "      <td>-0.149141</td>\n",
       "      <td>-2.584044</td>\n",
       "      <td>-1.342031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-1.277832</td>\n",
       "      <td>-0.025373</td>\n",
       "      <td>-1.235458</td>\n",
       "      <td>-0.822851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-0.772356</td>\n",
       "      <td>0.062893</td>\n",
       "      <td>-0.847990</td>\n",
       "      <td>-0.193136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.016916</td>\n",
       "      <td>0.346275</td>\n",
       "      <td>0.360960</td>\n",
       "      <td>0.881236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.364917</td>\n",
       "      <td>2.342387</td>\n",
       "      <td>1.513094</td>\n",
       "      <td>1.694041</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              A         B         C         D\n",
       "count  6.000000  6.000000  6.000000  6.000000\n",
       "mean  -0.465025  0.450829 -0.561267  0.028724\n",
       "std    1.083259  0.946887  1.469901  1.192107\n",
       "min   -1.444036 -0.149141 -2.584044 -1.342031\n",
       "25%   -1.277832 -0.025373 -1.235458 -0.822851\n",
       "50%   -0.772356  0.062893 -0.847990 -0.193136\n",
       "75%    0.016916  0.346275  0.360960  0.881236\n",
       "max    1.364917  2.342387  1.513094  1.694041"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# describe() shows a quick statistic summary of your data:\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2013-01-01 00:00:00</th>\n",
       "      <th>2013-01-02 00:00:00</th>\n",
       "      <th>2013-01-03 00:00:00</th>\n",
       "      <th>2013-01-04 00:00:00</th>\n",
       "      <th>2013-01-05 00:00:00</th>\n",
       "      <th>2013-01-06 00:00:00</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>-1.444036</td>\n",
       "      <td>-0.544770</td>\n",
       "      <td>1.364917</td>\n",
       "      <td>-0.999942</td>\n",
       "      <td>-1.370461</td>\n",
       "      <td>0.204145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.004337</td>\n",
       "      <td>-0.149141</td>\n",
       "      <td>-0.035276</td>\n",
       "      <td>0.421217</td>\n",
       "      <td>2.342387</td>\n",
       "      <td>0.121449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>-2.584044</td>\n",
       "      <td>-0.991055</td>\n",
       "      <td>1.513094</td>\n",
       "      <td>-0.704924</td>\n",
       "      <td>-1.316925</td>\n",
       "      <td>0.716255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>0.051296</td>\n",
       "      <td>-1.342031</td>\n",
       "      <td>1.694041</td>\n",
       "      <td>1.157883</td>\n",
       "      <td>-0.437568</td>\n",
       "      <td>-0.951278</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   2013-01-01  2013-01-02  2013-01-03  2013-01-04  2013-01-05  2013-01-06\n",
       "A   -1.444036   -0.544770    1.364917   -0.999942   -1.370461    0.204145\n",
       "B    0.004337   -0.149141   -0.035276    0.421217    2.342387    0.121449\n",
       "C   -2.584044   -0.991055    1.513094   -0.704924   -1.316925    0.716255\n",
       "D    0.051296   -1.342031    1.694041    1.157883   -0.437568   -0.951278"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>D</th>\n",
       "      <th>C</th>\n",
       "      <th>B</th>\n",
       "      <th>A</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>0.051296</td>\n",
       "      <td>-2.584044</td>\n",
       "      <td>0.004337</td>\n",
       "      <td>-1.444036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-1.342031</td>\n",
       "      <td>-0.991055</td>\n",
       "      <td>-0.149141</td>\n",
       "      <td>-0.544770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>1.694041</td>\n",
       "      <td>1.513094</td>\n",
       "      <td>-0.035276</td>\n",
       "      <td>1.364917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>1.157883</td>\n",
       "      <td>-0.704924</td>\n",
       "      <td>0.421217</td>\n",
       "      <td>-0.999942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-0.437568</td>\n",
       "      <td>-1.316925</td>\n",
       "      <td>2.342387</td>\n",
       "      <td>-1.370461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>-0.951278</td>\n",
       "      <td>0.716255</td>\n",
       "      <td>0.121449</td>\n",
       "      <td>0.204145</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   D         C         B         A\n",
       "2013-01-01  0.051296 -2.584044  0.004337 -1.444036\n",
       "2013-01-02 -1.342031 -0.991055 -0.149141 -0.544770\n",
       "2013-01-03  1.694041  1.513094 -0.035276  1.364917\n",
       "2013-01-04  1.157883 -0.704924  0.421217 -0.999942\n",
       "2013-01-05 -0.437568 -1.316925  2.342387 -1.370461\n",
       "2013-01-06 -0.951278  0.716255  0.121449  0.204145"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_index(axis=1, ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-0.544770</td>\n",
       "      <td>-0.149141</td>\n",
       "      <td>-0.991055</td>\n",
       "      <td>-1.342031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>1.364917</td>\n",
       "      <td>-0.035276</td>\n",
       "      <td>1.513094</td>\n",
       "      <td>1.694041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>-1.444036</td>\n",
       "      <td>0.004337</td>\n",
       "      <td>-2.584044</td>\n",
       "      <td>0.051296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>0.204145</td>\n",
       "      <td>0.121449</td>\n",
       "      <td>0.716255</td>\n",
       "      <td>-0.951278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.999942</td>\n",
       "      <td>0.421217</td>\n",
       "      <td>-0.704924</td>\n",
       "      <td>1.157883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.370461</td>\n",
       "      <td>2.342387</td>\n",
       "      <td>-1.316925</td>\n",
       "      <td>-0.437568</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-02 -0.544770 -0.149141 -0.991055 -1.342031\n",
       "2013-01-03  1.364917 -0.035276  1.513094  1.694041\n",
       "2013-01-01 -1.444036  0.004337 -2.584044  0.051296\n",
       "2013-01-06  0.204145  0.121449  0.716255 -0.951278\n",
       "2013-01-04 -0.999942  0.421217 -0.704924  1.157883\n",
       "2013-01-05 -1.370461  2.342387 -1.316925 -0.437568"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by='B')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2013-01-01   -1.444036\n",
       "2013-01-02   -0.544770\n",
       "2013-01-03    1.364917\n",
       "2013-01-04   -0.999942\n",
       "2013-01-05   -1.370461\n",
       "2013-01-06    0.204145\n",
       "Freq: D, Name: A, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>-1.444036</td>\n",
       "      <td>0.004337</td>\n",
       "      <td>-2.584044</td>\n",
       "      <td>0.051296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-0.544770</td>\n",
       "      <td>-0.149141</td>\n",
       "      <td>-0.991055</td>\n",
       "      <td>-1.342031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>1.364917</td>\n",
       "      <td>-0.035276</td>\n",
       "      <td>1.513094</td>\n",
       "      <td>1.694041</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01 -1.444036  0.004337 -2.584044  0.051296\n",
       "2013-01-02 -0.544770 -0.149141 -0.991055 -1.342031\n",
       "2013-01-03  1.364917 -0.035276  1.513094  1.694041"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-0.544770</td>\n",
       "      <td>-0.149141</td>\n",
       "      <td>-0.991055</td>\n",
       "      <td>-1.342031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>1.364917</td>\n",
       "      <td>-0.035276</td>\n",
       "      <td>1.513094</td>\n",
       "      <td>1.694041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.999942</td>\n",
       "      <td>0.421217</td>\n",
       "      <td>-0.704924</td>\n",
       "      <td>1.157883</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-02 -0.544770 -0.149141 -0.991055 -1.342031\n",
       "2013-01-03  1.364917 -0.035276  1.513094  1.694041\n",
       "2013-01-04 -0.999942  0.421217 -0.704924  1.157883"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['20130102': '20130104']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A   -1.444036\n",
       "B    0.004337\n",
       "C   -2.584044\n",
       "D    0.051296\n",
       "Name: 2013-01-01 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[dates[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>-1.444036</td>\n",
       "      <td>0.004337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-0.544770</td>\n",
       "      <td>-0.149141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>1.364917</td>\n",
       "      <td>-0.035276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.999942</td>\n",
       "      <td>0.421217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.370461</td>\n",
       "      <td>2.342387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>0.204145</td>\n",
       "      <td>0.121449</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B\n",
       "2013-01-01 -1.444036  0.004337\n",
       "2013-01-02 -0.544770 -0.149141\n",
       "2013-01-03  1.364917 -0.035276\n",
       "2013-01-04 -0.999942  0.421217\n",
       "2013-01-05 -1.370461  2.342387\n",
       "2013-01-06  0.204145  0.121449"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[:, ['A', 'B']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-0.544770</td>\n",
       "      <td>-0.149141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>1.364917</td>\n",
       "      <td>-0.035276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.999942</td>\n",
       "      <td>0.421217</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B\n",
       "2013-01-02 -0.544770 -0.149141\n",
       "2013-01-03  1.364917 -0.035276\n",
       "2013-01-04 -0.999942  0.421217"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['20130102':'20130104', ['A', 'B']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A   -0.544770\n",
       "B   -0.149141\n",
       "Name: 2013-01-02 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['20130102', ['A', 'B']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.4440356648732384"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[dates[0], 'A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.4440356648732384"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.at[dates[0], 'A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A   -0.999942\n",
       "B    0.421217\n",
       "C   -0.704924\n",
       "D    1.157883\n",
       "Name: 2013-01-04 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[3]"
   ]
  },
  {
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       "                   A         C\n",
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       "                   B         C\n",
       "2013-01-01  0.004337 -2.584044\n",
       "2013-01-02 -0.149141 -0.991055\n",
       "2013-01-03 -0.035276  1.513094\n",
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       "                   A         B         C         D\n",
       "2013-01-01       NaN  0.004337       NaN  0.051296\n",
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       "2013-01-06  0.204145  0.121449  0.716255       NaN"
      ]
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     "execution_count": 46,
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      "text/plain": [
       "                   A         B         C         D      E\n",
       "2013-01-01 -1.444036  0.004337 -2.584044  0.051296    one\n",
       "2013-01-02 -0.544770 -0.149141 -0.991055 -1.342031    one\n",
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       "2013-01-06  0.204145  0.121449  0.716255 -0.951278  three"
      ]
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     "execution_count": 47,
     "metadata": {},
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   ],
   "source": [
    "df2 = df.copy()\n",
    "df2['E'] = ['one', 'one', 'two', 'three', 'four', 'three']\n",
    "\n",
    "df2"
   ]
  },
  {
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   "execution_count": 50,
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       "                   A         B         C         D     E\n",
       "2013-01-03  1.364917 -0.035276  1.513094  1.694041   two\n",
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    "df2[df2['E'].isin(['two', 'four'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "s1 = pd.Series([1,2,3,4,5,6], index=pd.date_range('20130102', periods=6))\n",
    "s1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['F'] = s1"
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       "                   A         B         C  D    F\n",
       "2013-01-01  0.000000  0.000000 -2.584044  5  NaN\n",
       "2013-01-02 -0.544770 -0.149141 -0.991055  5  1.0\n",
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       "2013-01-04 -0.999942  0.421217 -0.704924  5  3.0\n",
       "2013-01-05 -1.370461  2.342387 -1.316925  5  4.0\n",
       "2013-01-06  0.204145  0.121449  0.716255  5  5.0"
      ]
     },
     "execution_count": 57,
     "metadata": {},
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    }
   ],
   "source": [
    "df.at[dates[0], 'A'] = 0\n",
    "df.iat[0,1] = 0\n",
    "df.loc[:, 'D'] = np.array([5] * len(df))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-2.584044</td>\n",
       "      <td>-5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-0.544770</td>\n",
       "      <td>-0.149141</td>\n",
       "      <td>-0.991055</td>\n",
       "      <td>-5</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.364917</td>\n",
       "      <td>-0.035276</td>\n",
       "      <td>-1.513094</td>\n",
       "      <td>-5</td>\n",
       "      <td>-2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.999942</td>\n",
       "      <td>-0.421217</td>\n",
       "      <td>-0.704924</td>\n",
       "      <td>-5</td>\n",
       "      <td>-3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.370461</td>\n",
       "      <td>-2.342387</td>\n",
       "      <td>-1.316925</td>\n",
       "      <td>-5</td>\n",
       "      <td>-4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>-0.204145</td>\n",
       "      <td>-0.121449</td>\n",
       "      <td>-0.716255</td>\n",
       "      <td>-5</td>\n",
       "      <td>-5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C  D    F\n",
       "2013-01-01  0.000000  0.000000 -2.584044 -5  NaN\n",
       "2013-01-02 -0.544770 -0.149141 -0.991055 -5 -1.0\n",
       "2013-01-03 -1.364917 -0.035276 -1.513094 -5 -2.0\n",
       "2013-01-04 -0.999942 -0.421217 -0.704924 -5 -3.0\n",
       "2013-01-05 -1.370461 -2.342387 -1.316925 -5 -4.0\n",
       "2013-01-06 -0.204145 -0.121449 -0.716255 -5 -5.0"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df.copy()\n",
    "df2[df2>0] = -df2\n",
    "\n",
    "df2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Missing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<PandasArray>\n",
      "[array([[ 0.05096022, -1.12149973, -0.00764756, -1.21029032],\n",
      "       [-0.40859699, -0.62506821, -0.63566376, -0.22387273],\n",
      "       [-1.03127088,  1.01415313, -1.33815226, -0.34013302]])]\n",
      "Length: 1, dtype: object\n"
     ]
    }
   ],
   "source": [
    "a = np.random.randn(3,4)\n",
    "b = np.arange(3)\n",
    "\n",
    "data = [a,b]\n",
    "\n",
    "df = pd.DataFrame(data, index=[0,1], columns=list('A'))\n",
    "print(df.iloc[0].array)\n",
    "\n",
    "df.to_csv('example.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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