Pandas DataFrames.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Two-dimensional, size-mutable, potentially heterogeneous tabular data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy.random import randn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Example 1**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.03051361,  0.40485706, -0.19399817],\n",
       "       [ 1.37759238,  0.06427273,  0.85608887],\n",
       "       [ 0.73982799,  0.00797723,  0.9738352 ]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "randn(3,3)  # Gauss distibution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data=randn(3,3),index=[\"A\",\"B\",\"C\"],columns=[\"Column1\",\"Column2\",\"Column3\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Column1</th>\n",
       "      <th>Column2</th>\n",
       "      <th>Column3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.418827</td>\n",
       "      <td>-0.328528</td>\n",
       "      <td>0.657367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.442301</td>\n",
       "      <td>0.871548</td>\n",
       "      <td>1.204701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>-1.109078</td>\n",
       "      <td>0.612968</td>\n",
       "      <td>-0.197021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Column1   Column2   Column3\n",
       "A  0.418827 -0.328528  0.657367\n",
       "B  0.442301  0.871548  1.204701\n",
       "C -1.109078  0.612968 -0.197021"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Access**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    0.418827\n",
       "B    0.442301\n",
       "C   -1.109078\n",
       "Name: Column1, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Column1\"]  # column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Column1    0.418827\n",
       "Column2   -0.328528\n",
       "Column3    0.657367\n",
       "Name: A, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[\"A\"]  # row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Column1</th>\n",
       "      <th>Column3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.418827</td>\n",
       "      <td>0.657367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.442301</td>\n",
       "      <td>1.204701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>-1.109078</td>\n",
       "      <td>-0.197021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Column1   Column3\n",
       "A  0.418827  0.657367\n",
       "B  0.442301  1.204701\n",
       "C -1.109078 -0.197021"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"Column1\",\"Column3\"]] # column1 and column3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Column1    0.418827\n",
       "Column2   -0.328528\n",
       "Column3    0.657367\n",
       "Column4    0.374432\n",
       "Name: A, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[0]  # index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4188270062266488"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[\"A\",\"Column1\"] # index and column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# or"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4188270062266488"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[\"A\"][\"Column1\"] # index and column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# or "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4188270062266488"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[0][\"Column1\"]  # index number and column"
   ]
  },
  {
   "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>Column1</th>\n",
       "      <th>Column2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.418827</td>\n",
       "      <td>-0.328528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.442301</td>\n",
       "      <td>0.871548</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Column1   Column2\n",
       "A  0.418827 -0.328528\n",
       "B  0.442301  0.871548"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[[\"A\",\"B\"]][[\"Column1\",\"Column2\"]]  # multi index and multi column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# or"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Column1</th>\n",
       "      <th>Column2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.418827</td>\n",
       "      <td>-0.328528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.442301</td>\n",
       "      <td>0.871548</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Column1   Column2\n",
       "A  0.418827 -0.328528\n",
       "B  0.442301  0.871548"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[[\"A\",\"B\"],[\"Column1\",\"Column2\"]] # multi index and multi column"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create new Column**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Column4\"] = pd.Series(randn(3),[\"A\",\"B\",\"C\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Column1</th>\n",
       "      <th>Column2</th>\n",
       "      <th>Column3</th>\n",
       "      <th>Column4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.418827</td>\n",
       "      <td>-0.328528</td>\n",
       "      <td>0.657367</td>\n",
       "      <td>-1.584046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.442301</td>\n",
       "      <td>0.871548</td>\n",
       "      <td>1.204701</td>\n",
       "      <td>-0.353688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>-1.109078</td>\n",
       "      <td>0.612968</td>\n",
       "      <td>-0.197021</td>\n",
       "      <td>-0.595171</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "    Column1   Column2   Column3   Column4\n",
       "A  0.418827 -0.328528  0.657367 -1.584046\n",
       "B  0.442301  0.871548  1.204701 -0.353688\n",
       "C -1.109078  0.612968 -0.197021 -0.595171"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Column5\"] = df[\"Column1\"] + df[\"Column2\"] + df[\"Column3\"] # create column from sum of (Column1,Column2,Column3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Column1</th>\n",
       "      <th>Column2</th>\n",
       "      <th>Column3</th>\n",
       "      <th>Column4</th>\n",
       "      <th>Column5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.418827</td>\n",
       "      <td>-0.328528</td>\n",
       "      <td>0.657367</td>\n",
       "      <td>-1.584046</td>\n",
       "      <td>0.747666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.442301</td>\n",
       "      <td>0.871548</td>\n",
       "      <td>1.204701</td>\n",
       "      <td>-0.353688</td>\n",
       "      <td>2.518550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>-1.109078</td>\n",
       "      <td>0.612968</td>\n",
       "      <td>-0.197021</td>\n",
       "      <td>-0.595171</td>\n",
       "      <td>-0.693131</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "    Column1   Column2   Column3   Column4   Column5\n",
       "A  0.418827 -0.328528  0.657367 -1.584046  0.747666\n",
       "B  0.442301  0.871548  1.204701 -0.353688  2.518550\n",
       "C -1.109078  0.612968 -0.197021 -0.595171 -0.693131"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Column6\"] = randn(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Column1</th>\n",
       "      <th>Column2</th>\n",
       "      <th>Column3</th>\n",
       "      <th>Column4</th>\n",
       "      <th>Column5</th>\n",
       "      <th>Column6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.418827</td>\n",
       "      <td>-0.328528</td>\n",
       "      <td>0.657367</td>\n",
       "      <td>-1.584046</td>\n",
       "      <td>0.747666</td>\n",
       "      <td>-0.946836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.442301</td>\n",
       "      <td>0.871548</td>\n",
       "      <td>1.204701</td>\n",
       "      <td>-0.353688</td>\n",
       "      <td>2.518550</td>\n",
       "      <td>-1.050297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>-1.109078</td>\n",
       "      <td>0.612968</td>\n",
       "      <td>-0.197021</td>\n",
       "      <td>-0.595171</td>\n",
       "      <td>-0.693131</td>\n",
       "      <td>0.171853</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Column1   Column2   Column3   Column4   Column5   Column6\n",
       "A  0.418827 -0.328528  0.657367 -1.584046  0.747666 -0.946836\n",
       "B  0.442301  0.871548  1.204701 -0.353688  2.518550 -1.050297\n",
       "C -1.109078  0.612968 -0.197021 -0.595171 -0.693131  0.171853"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Drop**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
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       "        vertical-align: top;\n",
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       "\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>Column1</th>\n",
       "      <th>Column2</th>\n",
       "      <th>Column3</th>\n",
       "      <th>Column5</th>\n",
       "      <th>Column6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.418827</td>\n",
       "      <td>-0.328528</td>\n",
       "      <td>0.657367</td>\n",
       "      <td>0.747666</td>\n",
       "      <td>-0.946836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.442301</td>\n",
       "      <td>0.871548</td>\n",
       "      <td>1.204701</td>\n",
       "      <td>2.518550</td>\n",
       "      <td>-1.050297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>-1.109078</td>\n",
       "      <td>0.612968</td>\n",
       "      <td>-0.197021</td>\n",
       "      <td>-0.693131</td>\n",
       "      <td>0.171853</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Column1   Column2   Column3   Column5   Column6\n",
       "A  0.418827 -0.328528  0.657367  0.747666 -0.946836\n",
       "B  0.442301  0.871548  1.204701  2.518550 -1.050297\n",
       "C -1.109078  0.612968 -0.197021 -0.693131  0.171853"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(\"Column4\",axis=1)  # drop by column -> axis=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>Column1</th>\n",
       "      <th>Column2</th>\n",
       "      <th>Column3</th>\n",
       "      <th>Column4</th>\n",
       "      <th>Column5</th>\n",
       "      <th>Column6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.418827</td>\n",
       "      <td>-0.328528</td>\n",
       "      <td>0.657367</td>\n",
       "      <td>-1.584046</td>\n",
       "      <td>0.747666</td>\n",
       "      <td>-0.946836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.442301</td>\n",
       "      <td>0.871548</td>\n",
       "      <td>1.204701</td>\n",
       "      <td>-0.353688</td>\n",
       "      <td>2.518550</td>\n",
       "      <td>-1.050297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>-1.109078</td>\n",
       "      <td>0.612968</td>\n",
       "      <td>-0.197021</td>\n",
       "      <td>-0.595171</td>\n",
       "      <td>-0.693131</td>\n",
       "      <td>0.171853</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Column1   Column2   Column3   Column4   Column5   Column6\n",
       "A  0.418827 -0.328528  0.657367 -1.584046  0.747666 -0.946836\n",
       "B  0.442301  0.871548  1.204701 -0.353688  2.518550 -1.050297\n",
       "C -1.109078  0.612968 -0.197021 -0.595171 -0.693131  0.171853"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note:** df.drop(\"Column4\",axis=1) -> dataframe not update. If updated, using inplace=True property"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(\"Column4\",axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Column1</th>\n",
       "      <th>Column2</th>\n",
       "      <th>Column3</th>\n",
       "      <th>Column5</th>\n",
       "      <th>Column6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.418827</td>\n",
       "      <td>-0.328528</td>\n",
       "      <td>0.657367</td>\n",
       "      <td>0.747666</td>\n",
       "      <td>-0.946836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.442301</td>\n",
       "      <td>0.871548</td>\n",
       "      <td>1.204701</td>\n",
       "      <td>2.518550</td>\n",
       "      <td>-1.050297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>-1.109078</td>\n",
       "      <td>0.612968</td>\n",
       "      <td>-0.197021</td>\n",
       "      <td>-0.693131</td>\n",
       "      <td>0.171853</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Column1   Column2   Column3   Column5   Column6\n",
       "A  0.418827 -0.328528  0.657367  0.747666 -0.946836\n",
       "B  0.442301  0.871548  1.204701  2.518550 -1.050297\n",
       "C -1.109078  0.612968 -0.197021 -0.693131  0.171853"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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