Pandas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "53e58edb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f60679d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df= pandas.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ca033e83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
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       "        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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: []"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "232fc815",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 0 entries\n",
      "Empty DataFrame"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d3e9d94e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Berlin', 'Elrangen', 'Daka']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city=['Berlin','Elrangen','Daka']  # this is list\n",
    "city"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b950e7d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Berlin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Elrangen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Daka</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0\n",
       "0    Berlin\n",
       "1  Elrangen\n",
       "2      Daka"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# List convert to DataFrame\n",
    "df= pandas.DataFrame(city)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8e754853",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df)  #chek type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "57ee7d1a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(city)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6ad154c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "row,col = df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "60573586",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7e7e22f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e9429da7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 1)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape  #first row then col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "aaff56a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Berlin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Elrangen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Daka</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0\n",
       "0    Berlin\n",
       "1  Elrangen\n",
       "2      Daka"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ac18e196",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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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>City_in_Europ</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Berlin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Elrangen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Daka</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  City_in_Europ\n",
       "0        Berlin\n",
       "1      Elrangen\n",
       "2          Daka"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df= pandas.DataFrame(city,columns=['City_in_Europ'])   #set col name\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "eea6433c",
   "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>City in_Europ</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>c1</th>\n",
       "      <td>Berlin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c2</th>\n",
       "      <td>Elrangen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c3</th>\n",
       "      <td>Daka</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   City in_Europ\n",
       "c1        Berlin\n",
       "c2      Elrangen\n",
       "c3          Daka"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df= pandas.DataFrame(city,columns=['City in_Europ'],index=['c1','c2','c3'])   #set row name\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "15019d37",
   "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",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City in_Europ</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>c1</th>\n",
       "      <td>Berlin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c2</th>\n",
       "      <td>Elrangen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c3</th>\n",
       "      <td>Daka</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   City in_Europ\n",
       "c1        Berlin\n",
       "c2      Elrangen\n",
       "c3          Daka"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df= pandas.DataFrame(city,columns=['City in_Europ'],index=['c1','c2','c3'])   #set row name\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "462639bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "city2 =['Daka','Rajshahi','Chittagong']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "1ddaba01",
   "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>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Daka</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rajshahi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Chittagong</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            0\n",
       "0        Daka\n",
       "1    Rajshahi\n",
       "2  Chittagong"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2=pandas.DataFrame(city2)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5c8455d3",
   "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>Division of BD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>Daka</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>Rajshahi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Chittagong</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Division of BD\n",
       "a           Daka\n",
       "b       Rajshahi\n",
       "c     Chittagong"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2=pandas.DataFrame(city2,index=['a','b','c'],columns=['Division of BD'])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "bdfd412c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city1</th>\n",
       "      <th>city2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Berlin</td>\n",
       "      <td>Daka</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Elrangen</td>\n",
       "      <td>Rajshahi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Daka</td>\n",
       "      <td>Chittagong</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      city1       city2\n",
       "0    Berlin        Daka\n",
       "1  Elrangen    Rajshahi\n",
       "2      Daka  Chittagong"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3=pandas.DataFrame(zip(city,city2),columns=['city1','city2'])   # zip\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8a8dde2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 2)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "6b4e258c",
   "metadata": {},
   "outputs": [],
   "source": [
    "city3 = [['Bavaria','Erlangen'],['NRW','Doctmund']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "063382ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['Bavaria', 'Erlangen'], ['NRW', 'Doctmund']]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "cf79eecb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>0</th>\n",
       "      <th>1</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bavaria</td>\n",
       "      <td>Erlangen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NRW</td>\n",
       "      <td>Doctmund</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         0         1\n",
       "0  Bavaria  Erlangen\n",
       "1      NRW  Doctmund"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4=pandas.DataFrame(city3) # Two Dimensional\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "2fced5cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>city</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bavaria</td>\n",
       "      <td>Erlangen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NRW</td>\n",
       "      <td>Doctmund</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     state      city\n",
       "0  Bavaria  Erlangen\n",
       "1      NRW  Doctmund"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4=pandas.DataFrame(city3,columns=['state','city']) # Two Dimensional\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "63d5063c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dictionary use second {} bracket\n",
    "dict1={\n",
    "    'city1': city,\n",
    "    'city2': city2\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b0335619",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'city1': ['Berlin', 'Elrangen', 'Daka'],\n",
       " 'city2': ['Daka', 'Rajshahi', 'Chittagong']}"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "4abcec6c",
   "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",
       "        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>city1</th>\n",
       "      <th>city2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Berlin</td>\n",
       "      <td>Daka</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Elrangen</td>\n",
       "      <td>Rajshahi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Daka</td>\n",
       "      <td>Chittagong</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      city1       city2\n",
       "0    Berlin        Daka\n",
       "1  Elrangen    Rajshahi\n",
       "2      Daka  Chittagong"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df5 =pandas.DataFrame(dict1)\n",
    "df5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "619b298a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(dict1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7334b392",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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