10 Minutes to Pandas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# creating a series\n",
    "s = pd.Series([1,3,5,np.nan, 6,8])\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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": 6,
     "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",
    "dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <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>2.105264</td>\n",
       "      <td>0.841475</td>\n",
       "      <td>0.852049</td>\n",
       "      <td>0.440189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>0.830835</td>\n",
       "      <td>-0.295906</td>\n",
       "      <td>0.409144</td>\n",
       "      <td>-0.144940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-0.681008</td>\n",
       "      <td>0.208177</td>\n",
       "      <td>0.994045</td>\n",
       "      <td>0.441474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.682114</td>\n",
       "      <td>-0.362428</td>\n",
       "      <td>-0.268454</td>\n",
       "      <td>-0.497651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>0.759389</td>\n",
       "      <td>-0.472352</td>\n",
       "      <td>-0.133386</td>\n",
       "      <td>0.693099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>1.560171</td>\n",
       "      <td>1.434012</td>\n",
       "      <td>-0.907497</td>\n",
       "      <td>-0.662624</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01  2.105264  0.841475  0.852049  0.440189\n",
       "2013-01-02  0.830835 -0.295906  0.409144 -0.144940\n",
       "2013-01-03 -0.681008  0.208177  0.994045  0.441474\n",
       "2013-01-04 -0.682114 -0.362428 -0.268454 -0.497651\n",
       "2013-01-05  0.759389 -0.472352 -0.133386  0.693099\n",
       "2013-01-06  1.560171  1.434012 -0.907497 -0.662624"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <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",
       "      <th>E</th>\n",
       "      <th>F</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>train</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>train</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     A          B    C  D      E    F\n",
       "0  1.0 2013-01-02  1.0  3   test  foo\n",
       "1  1.0 2013-01-02  1.0  3  train  foo\n",
       "2  1.0 2013-01-02  1.0  3   test  foo\n",
       "3  1.0 2013-01-02  1.0  3  train  foo"
      ]
     },
     "execution_count": 7,
     "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",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "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": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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>2.105264</td>\n",
       "      <td>0.841475</td>\n",
       "      <td>0.852049</td>\n",
       "      <td>0.440189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>0.830835</td>\n",
       "      <td>-0.295906</td>\n",
       "      <td>0.409144</td>\n",
       "      <td>-0.144940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-0.681008</td>\n",
       "      <td>0.208177</td>\n",
       "      <td>0.994045</td>\n",
       "      <td>0.441474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.682114</td>\n",
       "      <td>-0.362428</td>\n",
       "      <td>-0.268454</td>\n",
       "      <td>-0.497651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>0.759389</td>\n",
       "      <td>-0.472352</td>\n",
       "      <td>-0.133386</td>\n",
       "      <td>0.693099</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01  2.105264  0.841475  0.852049  0.440189\n",
       "2013-01-02  0.830835 -0.295906  0.409144 -0.144940\n",
       "2013-01-03 -0.681008  0.208177  0.994045  0.441474\n",
       "2013-01-04 -0.682114 -0.362428 -0.268454 -0.497651\n",
       "2013-01-05  0.759389 -0.472352 -0.133386  0.693099"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <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>-0.682114</td>\n",
       "      <td>-0.362428</td>\n",
       "      <td>-0.268454</td>\n",
       "      <td>-0.497651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>0.759389</td>\n",
       "      <td>-0.472352</td>\n",
       "      <td>-0.133386</td>\n",
       "      <td>0.693099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>1.560171</td>\n",
       "      <td>1.434012</td>\n",
       "      <td>-0.907497</td>\n",
       "      <td>-0.662624</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-04 -0.682114 -0.362428 -0.268454 -0.497651\n",
       "2013-01-05  0.759389 -0.472352 -0.133386  0.693099\n",
       "2013-01-06  1.560171  1.434012 -0.907497 -0.662624"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the index, columns:\n",
    "df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['A', 'B', 'C', 'D'], dtype='object')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2.10526401,  0.84147546,  0.85204949,  0.44018875],\n",
       "       [ 0.83083456, -0.29590649,  0.40914357, -0.1449395 ],\n",
       "       [-0.68100755,  0.20817652,  0.99404503,  0.44147419],\n",
       "       [-0.68211363, -0.36242849, -0.26845424, -0.49765058],\n",
       "       [ 0.75938931, -0.47235182, -0.13338563,  0.69309917],\n",
       "       [ 1.56017138,  1.4340116 , -0.90749684, -0.66262448]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>0.648756</td>\n",
       "      <td>0.225496</td>\n",
       "      <td>0.157650</td>\n",
       "      <td>0.044925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.143413</td>\n",
       "      <td>0.767431</td>\n",
       "      <td>0.727434</td>\n",
       "      <td>0.559406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.682114</td>\n",
       "      <td>-0.472352</td>\n",
       "      <td>-0.907497</td>\n",
       "      <td>-0.662624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.320908</td>\n",
       "      <td>-0.345798</td>\n",
       "      <td>-0.234687</td>\n",
       "      <td>-0.409473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.795112</td>\n",
       "      <td>-0.043865</td>\n",
       "      <td>0.137879</td>\n",
       "      <td>0.147625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.377837</td>\n",
       "      <td>0.683151</td>\n",
       "      <td>0.741323</td>\n",
       "      <td>0.441153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.105264</td>\n",
       "      <td>1.434012</td>\n",
       "      <td>0.994045</td>\n",
       "      <td>0.693099</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   0.648756  0.225496  0.157650  0.044925\n",
       "std    1.143413  0.767431  0.727434  0.559406\n",
       "min   -0.682114 -0.472352 -0.907497 -0.662624\n",
       "25%   -0.320908 -0.345798 -0.234687 -0.409473\n",
       "50%    0.795112 -0.043865  0.137879  0.147625\n",
       "75%    1.377837  0.683151  0.741323  0.441153\n",
       "max    2.105264  1.434012  0.994045  0.693099"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# quick summary of your data\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>2.105264</td>\n",
       "      <td>0.830835</td>\n",
       "      <td>-0.681008</td>\n",
       "      <td>-0.682114</td>\n",
       "      <td>0.759389</td>\n",
       "      <td>1.560171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.841475</td>\n",
       "      <td>-0.295906</td>\n",
       "      <td>0.208177</td>\n",
       "      <td>-0.362428</td>\n",
       "      <td>-0.472352</td>\n",
       "      <td>1.434012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>0.852049</td>\n",
       "      <td>0.409144</td>\n",
       "      <td>0.994045</td>\n",
       "      <td>-0.268454</td>\n",
       "      <td>-0.133386</td>\n",
       "      <td>-0.907497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>0.440189</td>\n",
       "      <td>-0.144940</td>\n",
       "      <td>0.441474</td>\n",
       "      <td>-0.497651</td>\n",
       "      <td>0.693099</td>\n",
       "      <td>-0.662624</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    2.105264    0.830835   -0.681008   -0.682114    0.759389    1.560171\n",
       "B    0.841475   -0.295906    0.208177   -0.362428   -0.472352    1.434012\n",
       "C    0.852049    0.409144    0.994045   -0.268454   -0.133386   -0.907497\n",
       "D    0.440189   -0.144940    0.441474   -0.497651    0.693099   -0.662624"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# transposing data\n",
    "df.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>0.440189</td>\n",
       "      <td>0.852049</td>\n",
       "      <td>0.841475</td>\n",
       "      <td>2.105264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-0.144940</td>\n",
       "      <td>0.409144</td>\n",
       "      <td>-0.295906</td>\n",
       "      <td>0.830835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>0.441474</td>\n",
       "      <td>0.994045</td>\n",
       "      <td>0.208177</td>\n",
       "      <td>-0.681008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.497651</td>\n",
       "      <td>-0.268454</td>\n",
       "      <td>-0.362428</td>\n",
       "      <td>-0.682114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>0.693099</td>\n",
       "      <td>-0.133386</td>\n",
       "      <td>-0.472352</td>\n",
       "      <td>0.759389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>-0.662624</td>\n",
       "      <td>-0.907497</td>\n",
       "      <td>1.434012</td>\n",
       "      <td>1.560171</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   D         C         B         A\n",
       "2013-01-01  0.440189  0.852049  0.841475  2.105264\n",
       "2013-01-02 -0.144940  0.409144 -0.295906  0.830835\n",
       "2013-01-03  0.441474  0.994045  0.208177 -0.681008\n",
       "2013-01-04 -0.497651 -0.268454 -0.362428 -0.682114\n",
       "2013-01-05  0.693099 -0.133386 -0.472352  0.759389\n",
       "2013-01-06 -0.662624 -0.907497  1.434012  1.560171"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sorting by an axis\n",
    "df.sort_index(axis=1, ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <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>-0.682114</td>\n",
       "      <td>-0.362428</td>\n",
       "      <td>-0.268454</td>\n",
       "      <td>-0.497651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-0.681008</td>\n",
       "      <td>0.208177</td>\n",
       "      <td>0.994045</td>\n",
       "      <td>0.441474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>0.759389</td>\n",
       "      <td>-0.472352</td>\n",
       "      <td>-0.133386</td>\n",
       "      <td>0.693099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>0.830835</td>\n",
       "      <td>-0.295906</td>\n",
       "      <td>0.409144</td>\n",
       "      <td>-0.144940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>1.560171</td>\n",
       "      <td>1.434012</td>\n",
       "      <td>-0.907497</td>\n",
       "      <td>-0.662624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>2.105264</td>\n",
       "      <td>0.841475</td>\n",
       "      <td>0.852049</td>\n",
       "      <td>0.440189</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-04 -0.682114 -0.362428 -0.268454 -0.497651\n",
       "2013-01-03 -0.681008  0.208177  0.994045  0.441474\n",
       "2013-01-05  0.759389 -0.472352 -0.133386  0.693099\n",
       "2013-01-02  0.830835 -0.295906  0.409144 -0.144940\n",
       "2013-01-06  1.560171  1.434012 -0.907497 -0.662624\n",
       "2013-01-01  2.105264  0.841475  0.852049  0.440189"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sorting by values\n",
    "df.sort_values(by='A')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2013-01-01    2.105264\n",
       "2013-01-02    0.830835\n",
       "2013-01-03   -0.681008\n",
       "2013-01-04   -0.682114\n",
       "2013-01-05    0.759389\n",
       "2013-01-06    1.560171\n",
       "Freq: D, Name: A, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# selecting a column\n",
    "df['A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <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>2.105264</td>\n",
       "      <td>0.841475</td>\n",
       "      <td>0.852049</td>\n",
       "      <td>0.440189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>0.830835</td>\n",
       "      <td>-0.295906</td>\n",
       "      <td>0.409144</td>\n",
       "      <td>-0.144940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-0.681008</td>\n",
       "      <td>0.208177</td>\n",
       "      <td>0.994045</td>\n",
       "      <td>0.441474</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01  2.105264  0.841475  0.852049  0.440189\n",
       "2013-01-02  0.830835 -0.295906  0.409144 -0.144940\n",
       "2013-01-03 -0.681008  0.208177  0.994045  0.441474"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# selecting via [] which slices the rows\n",
    "df[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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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",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>0.830835</td>\n",
       "      <td>-0.295906</td>\n",
       "      <td>0.409144</td>\n",
       "      <td>-0.144940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-0.681008</td>\n",
       "      <td>0.208177</td>\n",
       "      <td>0.994045</td>\n",
       "      <td>0.441474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.682114</td>\n",
       "      <td>-0.362428</td>\n",
       "      <td>-0.268454</td>\n",
       "      <td>-0.497651</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-02  0.830835 -0.295906  0.409144 -0.144940\n",
       "2013-01-03 -0.681008  0.208177  0.994045  0.441474\n",
       "2013-01-04 -0.682114 -0.362428 -0.268454 -0.497651"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['20130102':'20130104']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    2.105264\n",
       "B    0.841475\n",
       "C    0.852049\n",
       "D    0.440189\n",
       "Name: 2013-01-01 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# selecting by label\n",
    "df.loc[dates[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>2.105264</td>\n",
       "      <td>0.841475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>0.830835</td>\n",
       "      <td>-0.295906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-0.681008</td>\n",
       "      <td>0.208177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.682114</td>\n",
       "      <td>-0.362428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>0.759389</td>\n",
       "      <td>-0.472352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>1.560171</td>\n",
       "      <td>1.434012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B\n",
       "2013-01-01  2.105264  0.841475\n",
       "2013-01-02  0.830835 -0.295906\n",
       "2013-01-03 -0.681008  0.208177\n",
       "2013-01-04 -0.682114 -0.362428\n",
       "2013-01-05  0.759389 -0.472352\n",
       "2013-01-06  1.560171  1.434012"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# selecting on multi-axis by label\n",
    "df.loc[:, ['A', 'B']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>0.830835</td>\n",
       "      <td>-0.295906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-0.681008</td>\n",
       "      <td>0.208177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.682114</td>\n",
       "      <td>-0.362428</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B\n",
       "2013-01-02  0.830835 -0.295906\n",
       "2013-01-03 -0.681008  0.208177\n",
       "2013-01-04 -0.682114 -0.362428"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# showing label slicing, both endpoints are included:\n",
    "df.loc['20130102':'20130104', ['A', 'B']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A   -0.682114\n",
       "B   -0.362428\n",
       "C   -0.268454\n",
       "D   -0.497651\n",
       "Name: 2013-01-04 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# selection by position\n",
    "df.iloc[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>2013-01-04</th>\n",
       "      <td>-0.682114</td>\n",
       "      <td>-0.362428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>0.759389</td>\n",
       "      <td>-0.472352</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B\n",
       "2013-01-04 -0.682114 -0.362428\n",
       "2013-01-05  0.759389 -0.472352"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# selection by position slices, similar to numpy/python\n",
    "df.iloc[3:5, 0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>A</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>0.830835</td>\n",
       "      <td>0.409144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-0.681008</td>\n",
       "      <td>0.994045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>0.759389</td>\n",
       "      <td>-0.133386</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         C\n",
       "2013-01-02  0.830835  0.409144\n",
       "2013-01-03 -0.681008  0.994045\n",
       "2013-01-05  0.759389 -0.133386"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# selection by lists of integer position locations, similar to numpy/python\n",
    "df.iloc[[1,2,4], [0,2]]"
   ]
  },
  {
   "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": []
  },
  {
   "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": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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