mani.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "m=[]\r\n",
    "for a in range(10):\r\n",
    "    m.append(int(input('enter the elements')))\r\n",
    "    a=a+1\r\n",
    "x=int(input('enter the number to be searched'))\r\n",
    "i=0\r\n",
    "while i < len(m):\r\n",
    "    if x==m[i]:\r\n",
    "        print('true')\r\n",
    "    else:\r\n",
    "        print('false')\r\n",
    "    i=i+1"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "false\n",
      "false\n",
      "false\n",
      "false\n",
      "true\n",
      "false\n",
      "false\n",
      "false\n",
      "false\n",
      "false\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "# Python 3 program for recursive binary search.\r\n",
    "# Modifications needed for the older Python 2 are found in comments.\r\n",
    "\r\n",
    "# Returns index of x in arr if present, else -1\r\n",
    "def binary_search(arr, low, high, x):\r\n",
    "\r\n",
    "\t# Check base case\r\n",
    "\tif high >= low:\r\n",
    "\r\n",
    "\t\tmid = (high + low) // 2\r\n",
    "\r\n",
    "\t\t# If element is present at the middle itself\r\n",
    "\t\tif arr[mid] == x:\r\n",
    "\t\t\treturn mid\r\n",
    "\r\n",
    "\t\t# If element is smaller than mid, then it can only\r\n",
    "\t\t# be present in left subarray\r\n",
    "\t\telif arr[mid] > x:\r\n",
    "\t\t\treturn binary_search(arr, low, mid - 1, x)\r\n",
    "\r\n",
    "\t\t# Else the element can only be present in right subarray\r\n",
    "\t\telse:\r\n",
    "\t\t\treturn binary_search(arr, mid + 1, high, x)\r\n",
    "\r\n",
    "\telse:\r\n",
    "\t\t# Element is not present in the array\r\n",
    "\t\treturn -1\r\n",
    "\r\n",
    "# Test array\r\n",
    "arr = [ 2, 3, 4, 10, 40 ]\r\n",
    "x = 10\r\n",
    "\r\n",
    "# Function call\r\n",
    "result = binary_search(arr, 0, len(arr)-1, x)\r\n",
    "\r\n",
    "if result != -1:\r\n",
    "\tprint(\"Element is present at index\", str(result))\r\n",
    "else:\r\n",
    "\tprint(\"Element is not present in array\")\r\n"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Element is present at index 3\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "source": [
    "b=int(input(\"enter the base length\"))\r\n",
    "h=int(input(\"enter the height length\"))\r\n",
    "area=0.5*b*h\r\n",
    "print(\"area of the triangle is\",area)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "area of the triangle is 96.0\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "source": [
    "a,b,c=14,22,333665544\r\n",
    "if a>b:\r\n",
    "    print(\"greatest among these\",a)\r\n",
    "elif b>c:\r\n",
    "      print(\"greatest among these\",b)\r\n",
    "else:\r\n",
    "    print(\"greatest among these\",c)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "greatest amoung these 333665544\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "source": [
    "#ax^2+bx+c\r\n",
    "a = int(input('Enter a: '))  \r\n",
    "b = int(input('Enter b: '))  \r\n",
    "c = int(input('Enter c: '))  \r\n",
    "d = (b**2) - (4*a*c)  \r\n",
    "m = (-b-((d))**0.5) /(2*a) \r\n",
    "n = (-b+((d))**0.5) /(2*a) \r\n",
    "print(\"roots 1:-\",m,\"root 2:-\",n)\r\n",
    "print(type(m))\r\n",
    "print(type(n))"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "for i in range(1,11):\r\n",
    "    print(\"12 * \",i,\" = \",12*i)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "12 *  1  =  12\n",
      "12 *  2  =  24\n",
      "12 *  3  =  36\n",
      "12 *  4  =  48\n",
      "12 *  5  =  60\n",
      "12 *  6  =  72\n",
      "12 *  7  =  84\n",
      "12 *  8  =  96\n",
      "12 *  9  =  108\n",
      "12 *  10  =  120\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "source": [
    "m=\"mani teja bhumaraju\"\r\n",
    "n=list(m)\r\n",
    "print(max(m))\r\n",
    "print()\r\n",
    "k=range(30,51)\r\n",
    "print(type(k))\r\n",
    "z=list(k)\r\n",
    "print(type(z))\r\n",
    "print(z[:])"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "u\n",
      "\n",
      "<class 'range'>\n",
      "<class 'list'>\n",
      "[30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "source": [
    "m=[1,1,12,15,15,11]\r\n",
    "n=[]\r\n",
    "for i in m:\r\n",
    "    if i not in n:\r\n",
    "        n.append(i)\r\n",
    "print(n[:])"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "[1, 12, 15, 11]\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "source": [
    "st='m*a*n*i*t*e*j*a'\r\n",
    "print(st.split('*'))\r\n",
    "st=\"maniteja\"\r\n",
    "print(\"#\".join(st))"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "['m', 'a', 'n', 'i', 't', 'e', 'j', 'a']\n",
      "m#a#n#i#t#e#j#a\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "m=[1,2,3,4,5,6,7,8,9]\r\n",
    "for i in len(m):\r\n",
    "    m[i]+=5\r\n",
    "print(m[:])\r\n"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "st=\"mani teja\"\r\n",
    "freq={}\r\n",
    "for i in st:\r\n",
    "    if i in freq:\r\n",
    "        freq[i]+=1\r\n",
    "    else:\r\n",
    "        freq[i]=1\r\n",
    "print(freq)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "{'m': 1, 'a': 2, 'n': 1, 'i': 1, ' ': 1, 't': 1, 'e': 1, 'j': 1}\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "source": [
    "m=[1,2,3,4,5,6,7,8,9]\r\n",
    "m.append(23)\r\n",
    "def gtn(e):\r\n",
    "    f=max(e)\r\n",
    "    print(f)\r\n",
    "gtn(m)\r\n"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "23\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "source": [
    "a,b=5,9\r\n",
    "def swap(m,n):\r\n",
    "    temp = m\r\n",
    "    m = n\r\n",
    "    n = temp\r\n",
    "    print(m,n)\r\n",
    "swap(a,b)\r\n"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "9 5\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "source": [
    "m=3+1j\r\n",
    "print(type(m))"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "<class 'complex'>\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "import pandas as pd\r\n",
    "import numpy as np\r\n",
    "df=pd.read_csv(\"titanic.tab\",sep =\"\\t\")\r\n",
    "df\r\n",
    "#df.head(10)\r\n",
    "#df.tail(4)\r\n",
    "#df.info(verbose=False)\r\n",
    "#df.index\r\n",
    "#print(type(df.index))\r\n",
    "#df.columns\r\n",
    "#col_values=df.columns.tolist()\r\n",
    "#print(col_values)\r\n",
    "#print(type(col_values))\r\n",
    "#df.shape\r\n",
    "#df.drop('sex',axis=1,inplace=True)\r\n",
    "#df.rename(columns={'survived':'live'},inplace=True)\r\n",
    "#df.columns\r\n",
    "#df.describe()\r\n",
    "#df.head(10)\r\n",
    "#df.loc[[0,1,2,4,5,6,7,8,2202]]\r\n",
    "df.loc[0:1]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "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>status</th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>survived</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>d</td>\n",
       "      <td>d</td>\n",
       "      <td>d</td>\n",
       "      <td>d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>class</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  status  age  sex survived\n",
       "0      d    d    d        d\n",
       "1    NaN  NaN  NaN    class"
      ]
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "import pandas as pd\r\n",
    "import numpy as np\r\n",
    "df=pd.read_excel(\"Canada.xlsx\",skiprows=range(20))\r\n",
    "#df.head(20)\r\n",
    "#df.tail(4)\r\n",
    "#df.info(verbose=False)\r\n",
    "#df.index\r\n",
    "#print(type(df.index))\r\n",
    "#df.columns\r\n",
    "#col_values=df.columns.tolist()\r\n",
    "#print(col_values)\r\n",
    "#print(type(col_values))\r\n",
    "#df.shape\r\n",
    "#df.drop('RegName',axis=1,inplace=True)\r\n",
    "#df.rename(columns={'AreaName':'localitity','Regname':'country'},inplace=True)\r\n",
    "#df\r\n",
    "#df.columns\r\n",
    "#df.describe()\r\n",
    "#df.head(10)\r\n",
    "#df.loc[[0,1,2,28]]\r\n",
    "#df.loc[3]['AreaName']\r\n",
    "#df['total']=df.sum(axis=1,numeric_only=True)\r\n",
    "#df\r\n",
    "#df.isnull(),sum(),type\r\n",
    "#df.AreaName.tolist\r\n",
    "#df[[\"Coverage\",\"AreaName\"]]\r\n",
    "#df['AreaName'][3]\r\n",
    "#df.set_index('AreaName',inplace=True)\r\n",
    "#df.iloc[4]\r\n",
    "#df.loc[\"Africa\",2006]\r\n",
    "#df.iloc[4,30]\r\n",
    "#df.iloc[:,:-1]\r\n"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "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>Type</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>AreaName</th>\n",
       "      <th>RegName</th>\n",
       "      <th>1980</th>\n",
       "      <th>1981</th>\n",
       "      <th>1982</th>\n",
       "      <th>1983</th>\n",
       "      <th>1984</th>\n",
       "      <th>1985</th>\n",
       "      <th>...</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Citizens</td>\n",
       "      <td>Northern America</td>\n",
       "      <td>Northern America</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>...</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Eastern Africa</td>\n",
       "      <td>1471</td>\n",
       "      <td>1641</td>\n",
       "      <td>1426</td>\n",
       "      <td>1094</td>\n",
       "      <td>1187</td>\n",
       "      <td>1134</td>\n",
       "      <td>...</td>\n",
       "      <td>7726</td>\n",
       "      <td>7083</td>\n",
       "      <td>6750</td>\n",
       "      <td>6669</td>\n",
       "      <td>6705</td>\n",
       "      <td>6922</td>\n",
       "      <td>8591</td>\n",
       "      <td>8956</td>\n",
       "      <td>8846</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Middle Africa</td>\n",
       "      <td>33</td>\n",
       "      <td>27</td>\n",
       "      <td>44</td>\n",
       "      <td>32</td>\n",
       "      <td>42</td>\n",
       "      <td>30</td>\n",
       "      <td>...</td>\n",
       "      <td>2452</td>\n",
       "      <td>2802</td>\n",
       "      <td>2834</td>\n",
       "      <td>2951</td>\n",
       "      <td>3034</td>\n",
       "      <td>3255</td>\n",
       "      <td>3369</td>\n",
       "      <td>3146</td>\n",
       "      <td>4602</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Northern Africa</td>\n",
       "      <td>1100</td>\n",
       "      <td>1268</td>\n",
       "      <td>1348</td>\n",
       "      <td>936</td>\n",
       "      <td>842</td>\n",
       "      <td>840</td>\n",
       "      <td>...</td>\n",
       "      <td>12478</td>\n",
       "      <td>11323</td>\n",
       "      <td>12705</td>\n",
       "      <td>11750</td>\n",
       "      <td>13456</td>\n",
       "      <td>16320</td>\n",
       "      <td>19271</td>\n",
       "      <td>15712</td>\n",
       "      <td>15453</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Southern Africa</td>\n",
       "      <td>1041</td>\n",
       "      <td>1126</td>\n",
       "      <td>791</td>\n",
       "      <td>387</td>\n",
       "      <td>297</td>\n",
       "      <td>327</td>\n",
       "      <td>...</td>\n",
       "      <td>1203</td>\n",
       "      <td>1012</td>\n",
       "      <td>1148</td>\n",
       "      <td>1230</td>\n",
       "      <td>1184</td>\n",
       "      <td>1235</td>\n",
       "      <td>1306</td>\n",
       "      <td>1049</td>\n",
       "      <td>1348</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Western Africa</td>\n",
       "      <td>306</td>\n",
       "      <td>301</td>\n",
       "      <td>210</td>\n",
       "      <td>222</td>\n",
       "      <td>271</td>\n",
       "      <td>319</td>\n",
       "      <td>...</td>\n",
       "      <td>4333</td>\n",
       "      <td>5303</td>\n",
       "      <td>5751</td>\n",
       "      <td>5684</td>\n",
       "      <td>5511</td>\n",
       "      <td>6802</td>\n",
       "      <td>8355</td>\n",
       "      <td>6578</td>\n",
       "      <td>7834</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Africa Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3951</td>\n",
       "      <td>4363</td>\n",
       "      <td>3819</td>\n",
       "      <td>2671</td>\n",
       "      <td>2639</td>\n",
       "      <td>2650</td>\n",
       "      <td>...</td>\n",
       "      <td>28192</td>\n",
       "      <td>27523</td>\n",
       "      <td>29188</td>\n",
       "      <td>28284</td>\n",
       "      <td>29890</td>\n",
       "      <td>34534</td>\n",
       "      <td>40892</td>\n",
       "      <td>35441</td>\n",
       "      <td>38083</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Central Asia</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>...</td>\n",
       "      <td>995</td>\n",
       "      <td>1134</td>\n",
       "      <td>903</td>\n",
       "      <td>936</td>\n",
       "      <td>805</td>\n",
       "      <td>962</td>\n",
       "      <td>905</td>\n",
       "      <td>769</td>\n",
       "      <td>1029</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Eastern Asia</td>\n",
       "      <td>6836</td>\n",
       "      <td>8895</td>\n",
       "      <td>5481</td>\n",
       "      <td>3254</td>\n",
       "      <td>2624</td>\n",
       "      <td>2979</td>\n",
       "      <td>...</td>\n",
       "      <td>43550</td>\n",
       "      <td>50306</td>\n",
       "      <td>41763</td>\n",
       "      <td>35591</td>\n",
       "      <td>39602</td>\n",
       "      <td>37497</td>\n",
       "      <td>37954</td>\n",
       "      <td>35159</td>\n",
       "      <td>40449</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Asia</td>\n",
       "      <td>South-Eastern Asia</td>\n",
       "      <td>8693</td>\n",
       "      <td>9191</td>\n",
       "      <td>9022</td>\n",
       "      <td>8845</td>\n",
       "      <td>12161</td>\n",
       "      <td>9787</td>\n",
       "      <td>...</td>\n",
       "      <td>18056</td>\n",
       "      <td>22809</td>\n",
       "      <td>25105</td>\n",
       "      <td>27256</td>\n",
       "      <td>30614</td>\n",
       "      <td>34166</td>\n",
       "      <td>44199</td>\n",
       "      <td>40494</td>\n",
       "      <td>37695</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Southern Asia</td>\n",
       "      <td>11315</td>\n",
       "      <td>11566</td>\n",
       "      <td>11591</td>\n",
       "      <td>10157</td>\n",
       "      <td>9607</td>\n",
       "      <td>7654</td>\n",
       "      <td>...</td>\n",
       "      <td>58521</td>\n",
       "      <td>69510</td>\n",
       "      <td>66742</td>\n",
       "      <td>56032</td>\n",
       "      <td>54154</td>\n",
       "      <td>53083</td>\n",
       "      <td>62284</td>\n",
       "      <td>53673</td>\n",
       "      <td>60568</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Western Asia</td>\n",
       "      <td>4181</td>\n",
       "      <td>4662</td>\n",
       "      <td>4120</td>\n",
       "      <td>2440</td>\n",
       "      <td>2882</td>\n",
       "      <td>3430</td>\n",
       "      <td>...</td>\n",
       "      <td>13728</td>\n",
       "      <td>15494</td>\n",
       "      <td>14541</td>\n",
       "      <td>13644</td>\n",
       "      <td>14719</td>\n",
       "      <td>15726</td>\n",
       "      <td>18503</td>\n",
       "      <td>16799</td>\n",
       "      <td>12477</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Asia Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31025</td>\n",
       "      <td>34314</td>\n",
       "      <td>30214</td>\n",
       "      <td>24696</td>\n",
       "      <td>27274</td>\n",
       "      <td>23850</td>\n",
       "      <td>...</td>\n",
       "      <td>134850</td>\n",
       "      <td>159253</td>\n",
       "      <td>149054</td>\n",
       "      <td>133459</td>\n",
       "      <td>139894</td>\n",
       "      <td>141434</td>\n",
       "      <td>163845</td>\n",
       "      <td>146894</td>\n",
       "      <td>152218</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Eastern Europe</td>\n",
       "      <td>1467</td>\n",
       "      <td>3698</td>\n",
       "      <td>6873</td>\n",
       "      <td>5459</td>\n",
       "      <td>4433</td>\n",
       "      <td>3969</td>\n",
       "      <td>...</td>\n",
       "      <td>18360</td>\n",
       "      <td>16724</td>\n",
       "      <td>14389</td>\n",
       "      <td>13886</td>\n",
       "      <td>11988</td>\n",
       "      <td>11759</td>\n",
       "      <td>11803</td>\n",
       "      <td>9612</td>\n",
       "      <td>9464</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Northern Europe</td>\n",
       "      <td>23721</td>\n",
       "      <td>26608</td>\n",
       "      <td>22134</td>\n",
       "      <td>10725</td>\n",
       "      <td>10845</td>\n",
       "      <td>10212</td>\n",
       "      <td>...</td>\n",
       "      <td>8486</td>\n",
       "      <td>8153</td>\n",
       "      <td>7969</td>\n",
       "      <td>9186</td>\n",
       "      <td>10042</td>\n",
       "      <td>9846</td>\n",
       "      <td>9816</td>\n",
       "      <td>7285</td>\n",
       "      <td>7616</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>7762</td>\n",
       "      <td>7037</td>\n",
       "      <td>5222</td>\n",
       "      <td>3083</td>\n",
       "      <td>3033</td>\n",
       "      <td>2868</td>\n",
       "      <td>...</td>\n",
       "      <td>3200</td>\n",
       "      <td>2806</td>\n",
       "      <td>2417</td>\n",
       "      <td>2290</td>\n",
       "      <td>2692</td>\n",
       "      <td>2948</td>\n",
       "      <td>2661</td>\n",
       "      <td>2466</td>\n",
       "      <td>2854</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>6810</td>\n",
       "      <td>7459</td>\n",
       "      <td>8491</td>\n",
       "      <td>5371</td>\n",
       "      <td>3976</td>\n",
       "      <td>3795</td>\n",
       "      <td>...</td>\n",
       "      <td>8036</td>\n",
       "      <td>8272</td>\n",
       "      <td>8278</td>\n",
       "      <td>8133</td>\n",
       "      <td>9970</td>\n",
       "      <td>10525</td>\n",
       "      <td>9145</td>\n",
       "      <td>7415</td>\n",
       "      <td>9243</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Europe Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39760</td>\n",
       "      <td>44802</td>\n",
       "      <td>42720</td>\n",
       "      <td>24638</td>\n",
       "      <td>22287</td>\n",
       "      <td>20844</td>\n",
       "      <td>...</td>\n",
       "      <td>38082</td>\n",
       "      <td>35955</td>\n",
       "      <td>33053</td>\n",
       "      <td>33495</td>\n",
       "      <td>34692</td>\n",
       "      <td>35078</td>\n",
       "      <td>33425</td>\n",
       "      <td>26778</td>\n",
       "      <td>29177</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Latin America and the Caribbean</td>\n",
       "      <td>Caribbean</td>\n",
       "      <td>7045</td>\n",
       "      <td>8310</td>\n",
       "      <td>8326</td>\n",
       "      <td>6998</td>\n",
       "      <td>5553</td>\n",
       "      <td>6048</td>\n",
       "      <td>...</td>\n",
       "      <td>6630</td>\n",
       "      <td>6816</td>\n",
       "      <td>6652</td>\n",
       "      <td>7826</td>\n",
       "      <td>8862</td>\n",
       "      <td>8847</td>\n",
       "      <td>10549</td>\n",
       "      <td>11958</td>\n",
       "      <td>11898</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Latin America and the Caribbean</td>\n",
       "      <td>Central America</td>\n",
       "      <td>734</td>\n",
       "      <td>921</td>\n",
       "      <td>1612</td>\n",
       "      <td>3648</td>\n",
       "      <td>4087</td>\n",
       "      <td>4862</td>\n",
       "      <td>...</td>\n",
       "      <td>3346</td>\n",
       "      <td>3990</td>\n",
       "      <td>4140</td>\n",
       "      <td>5039</td>\n",
       "      <td>4891</td>\n",
       "      <td>4814</td>\n",
       "      <td>5692</td>\n",
       "      <td>5821</td>\n",
       "      <td>6019</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Latin America and the Caribbean</td>\n",
       "      <td>South America</td>\n",
       "      <td>5302</td>\n",
       "      <td>5984</td>\n",
       "      <td>6831</td>\n",
       "      <td>4781</td>\n",
       "      <td>4038</td>\n",
       "      <td>4261</td>\n",
       "      <td>...</td>\n",
       "      <td>12205</td>\n",
       "      <td>13941</td>\n",
       "      <td>13884</td>\n",
       "      <td>13146</td>\n",
       "      <td>12794</td>\n",
       "      <td>13206</td>\n",
       "      <td>12577</td>\n",
       "      <td>10077</td>\n",
       "      <td>9256</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Latin America and the Caribbean Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13081</td>\n",
       "      <td>15215</td>\n",
       "      <td>16769</td>\n",
       "      <td>15427</td>\n",
       "      <td>13678</td>\n",
       "      <td>15171</td>\n",
       "      <td>...</td>\n",
       "      <td>22181</td>\n",
       "      <td>24747</td>\n",
       "      <td>24676</td>\n",
       "      <td>26011</td>\n",
       "      <td>26547</td>\n",
       "      <td>26867</td>\n",
       "      <td>28818</td>\n",
       "      <td>27856</td>\n",
       "      <td>27173</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Northern America</td>\n",
       "      <td>Northern America</td>\n",
       "      <td>9378</td>\n",
       "      <td>10030</td>\n",
       "      <td>9074</td>\n",
       "      <td>7100</td>\n",
       "      <td>6661</td>\n",
       "      <td>6543</td>\n",
       "      <td>...</td>\n",
       "      <td>6990</td>\n",
       "      <td>8394</td>\n",
       "      <td>9613</td>\n",
       "      <td>9463</td>\n",
       "      <td>10190</td>\n",
       "      <td>8995</td>\n",
       "      <td>8142</td>\n",
       "      <td>7676</td>\n",
       "      <td>7891</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Australia and New Zealand</td>\n",
       "      <td>1304</td>\n",
       "      <td>1119</td>\n",
       "      <td>848</td>\n",
       "      <td>457</td>\n",
       "      <td>481</td>\n",
       "      <td>467</td>\n",
       "      <td>...</td>\n",
       "      <td>1280</td>\n",
       "      <td>1279</td>\n",
       "      <td>1193</td>\n",
       "      <td>1383</td>\n",
       "      <td>1498</td>\n",
       "      <td>1538</td>\n",
       "      <td>1423</td>\n",
       "      <td>1226</td>\n",
       "      <td>1399</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Melanesia</td>\n",
       "      <td>632</td>\n",
       "      <td>707</td>\n",
       "      <td>816</td>\n",
       "      <td>558</td>\n",
       "      <td>391</td>\n",
       "      <td>448</td>\n",
       "      <td>...</td>\n",
       "      <td>497</td>\n",
       "      <td>300</td>\n",
       "      <td>278</td>\n",
       "      <td>304</td>\n",
       "      <td>331</td>\n",
       "      <td>313</td>\n",
       "      <td>401</td>\n",
       "      <td>316</td>\n",
       "      <td>273</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Micronesia</td>\n",
       "      <td>1</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>1</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>..</td>\n",
       "      <td>..</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Polynesia</td>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Oceania Total</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1942</td>\n",
       "      <td>1839</td>\n",
       "      <td>1675</td>\n",
       "      <td>1018</td>\n",
       "      <td>878</td>\n",
       "      <td>920</td>\n",
       "      <td>...</td>\n",
       "      <td>1788</td>\n",
       "      <td>1585</td>\n",
       "      <td>1473</td>\n",
       "      <td>1693</td>\n",
       "      <td>1834</td>\n",
       "      <td>1860</td>\n",
       "      <td>1834</td>\n",
       "      <td>1548</td>\n",
       "      <td>1679</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>44000</td>\n",
       "      <td>18078</td>\n",
       "      <td>16904</td>\n",
       "      <td>13635</td>\n",
       "      <td>14855</td>\n",
       "      <td>14368</td>\n",
       "      <td>...</td>\n",
       "      <td>3739</td>\n",
       "      <td>4785</td>\n",
       "      <td>4583</td>\n",
       "      <td>4348</td>\n",
       "      <td>4197</td>\n",
       "      <td>3402</td>\n",
       "      <td>3731</td>\n",
       "      <td>2554</td>\n",
       "      <td>1681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Type    Coverage                               AreaName  \\\n",
       "0   Immigrants    Citizens                       Northern America   \n",
       "1   Immigrants  Foreigners                                 Africa   \n",
       "2   Immigrants  Foreigners                                 Africa   \n",
       "3   Immigrants  Foreigners                                 Africa   \n",
       "4   Immigrants  Foreigners                                 Africa   \n",
       "5   Immigrants  Foreigners                                 Africa   \n",
       "6   Immigrants  Foreigners                           Africa Total   \n",
       "7   Immigrants  Foreigners                                   Asia   \n",
       "8   Immigrants  Foreigners                                   Asia   \n",
       "9   Immigrants  Foreigners                                   Asia   \n",
       "10  Immigrants  Foreigners                                   Asia   \n",
       "11  Immigrants  Foreigners                                   Asia   \n",
       "12  Immigrants  Foreigners                             Asia Total   \n",
       "13  Immigrants  Foreigners                                 Europe   \n",
       "14  Immigrants  Foreigners                                 Europe   \n",
       "15  Immigrants  Foreigners                                 Europe   \n",
       "16  Immigrants  Foreigners                                 Europe   \n",
       "17  Immigrants  Foreigners                           Europe Total   \n",
       "18  Immigrants  Foreigners        Latin America and the Caribbean   \n",
       "19  Immigrants  Foreigners        Latin America and the Caribbean   \n",
       "20  Immigrants  Foreigners        Latin America and the Caribbean   \n",
       "21  Immigrants  Foreigners  Latin America and the Caribbean Total   \n",
       "22  Immigrants  Foreigners                       Northern America   \n",
       "23  Immigrants  Foreigners                                Oceania   \n",
       "24  Immigrants  Foreigners                                Oceania   \n",
       "25  Immigrants  Foreigners                                Oceania   \n",
       "26  Immigrants  Foreigners                                Oceania   \n",
       "27  Immigrants  Foreigners                          Oceania Total   \n",
       "28  Immigrants  Foreigners                                Unknown   \n",
       "\n",
       "                      RegName   1980   1981   1982   1983   1984   1985  ...  \\\n",
       "0            Northern America     ..     ..     ..     ..     ..     ..  ...   \n",
       "1              Eastern Africa   1471   1641   1426   1094   1187   1134  ...   \n",
       "2               Middle Africa     33     27     44     32     42     30  ...   \n",
       "3             Northern Africa   1100   1268   1348    936    842    840  ...   \n",
       "4             Southern Africa   1041   1126    791    387    297    327  ...   \n",
       "5              Western Africa    306    301    210    222    271    319  ...   \n",
       "6                         NaN   3951   4363   3819   2671   2639   2650  ...   \n",
       "7                Central Asia     ..     ..     ..     ..     ..     ..  ...   \n",
       "8                Eastern Asia   6836   8895   5481   3254   2624   2979  ...   \n",
       "9          South-Eastern Asia   8693   9191   9022   8845  12161   9787  ...   \n",
       "10              Southern Asia  11315  11566  11591  10157   9607   7654  ...   \n",
       "11               Western Asia   4181   4662   4120   2440   2882   3430  ...   \n",
       "12                        NaN  31025  34314  30214  24696  27274  23850  ...   \n",
       "13             Eastern Europe   1467   3698   6873   5459   4433   3969  ...   \n",
       "14            Northern Europe  23721  26608  22134  10725  10845  10212  ...   \n",
       "15            Southern Europe   7762   7037   5222   3083   3033   2868  ...   \n",
       "16             Western Europe   6810   7459   8491   5371   3976   3795  ...   \n",
       "17                        NaN  39760  44802  42720  24638  22287  20844  ...   \n",
       "18                  Caribbean   7045   8310   8326   6998   5553   6048  ...   \n",
       "19            Central America    734    921   1612   3648   4087   4862  ...   \n",
       "20              South America   5302   5984   6831   4781   4038   4261  ...   \n",
       "21                        NaN  13081  15215  16769  15427  13678  15171  ...   \n",
       "22           Northern America   9378  10030   9074   7100   6661   6543  ...   \n",
       "23  Australia and New Zealand   1304   1119    848    457    481    467  ...   \n",
       "24                  Melanesia    632    707    816    558    391    448  ...   \n",
       "25                 Micronesia      1     ..     ..      1     ..     ..  ...   \n",
       "26                  Polynesia      5     13     11      2      6      5  ...   \n",
       "27                        NaN   1942   1839   1675   1018    878    920  ...   \n",
       "28                    Unknown  44000  18078  16904  13635  14855  14368  ...   \n",
       "\n",
       "      2004    2005    2006    2007    2008    2009    2010    2011    2012  \\\n",
       "0       ..      ..      ..      ..      ..      ..      ..       1       1   \n",
       "1     7726    7083    6750    6669    6705    6922    8591    8956    8846   \n",
       "2     2452    2802    2834    2951    3034    3255    3369    3146    4602   \n",
       "3    12478   11323   12705   11750   13456   16320   19271   15712   15453   \n",
       "4     1203    1012    1148    1230    1184    1235    1306    1049    1348   \n",
       "5     4333    5303    5751    5684    5511    6802    8355    6578    7834   \n",
       "6    28192   27523   29188   28284   29890   34534   40892   35441   38083   \n",
       "7      995    1134     903     936     805     962     905     769    1029   \n",
       "8    43550   50306   41763   35591   39602   37497   37954   35159   40449   \n",
       "9    18056   22809   25105   27256   30614   34166   44199   40494   37695   \n",
       "10   58521   69510   66742   56032   54154   53083   62284   53673   60568   \n",
       "11   13728   15494   14541   13644   14719   15726   18503   16799   12477   \n",
       "12  134850  159253  149054  133459  139894  141434  163845  146894  152218   \n",
       "13   18360   16724   14389   13886   11988   11759   11803    9612    9464   \n",
       "14    8486    8153    7969    9186   10042    9846    9816    7285    7616   \n",
       "15    3200    2806    2417    2290    2692    2948    2661    2466    2854   \n",
       "16    8036    8272    8278    8133    9970   10525    9145    7415    9243   \n",
       "17   38082   35955   33053   33495   34692   35078   33425   26778   29177   \n",
       "18    6630    6816    6652    7826    8862    8847   10549   11958   11898   \n",
       "19    3346    3990    4140    5039    4891    4814    5692    5821    6019   \n",
       "20   12205   13941   13884   13146   12794   13206   12577   10077    9256   \n",
       "21   22181   24747   24676   26011   26547   26867   28818   27856   27173   \n",
       "22    6990    8394    9613    9463   10190    8995    8142    7676    7891   \n",
       "23    1280    1279    1193    1383    1498    1538    1423    1226    1399   \n",
       "24     497     300     278     304     331     313     401     316     273   \n",
       "25       1       2       1       3       1       2      ..      ..       2   \n",
       "26      10       4       1       3       4       7      10       6       5   \n",
       "27    1788    1585    1473    1693    1834    1860    1834    1548    1679   \n",
       "28    3739    4785    4583    4348    4197    3402    3731    2554    1681   \n",
       "\n",
       "    2013  \n",
       "0    NaN  \n",
       "1    NaN  \n",
       "2    NaN  \n",
       "3    NaN  \n",
       "4    NaN  \n",
       "5    NaN  \n",
       "6    NaN  \n",
       "7    NaN  \n",
       "8    NaN  \n",
       "9    NaN  \n",
       "10   NaN  \n",
       "11   NaN  \n",
       "12   NaN  \n",
       "13   NaN  \n",
       "14   NaN  \n",
       "15   NaN  \n",
       "16   NaN  \n",
       "17   NaN  \n",
       "18   NaN  \n",
       "19   NaN  \n",
       "20   NaN  \n",
       "21   NaN  \n",
       "22   NaN  \n",
       "23   NaN  \n",
       "24   NaN  \n",
       "25   NaN  \n",
       "26   NaN  \n",
       "27   NaN  \n",
       "28   NaN  \n",
       "\n",
       "[29 rows x 38 columns]"
      ]
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "for row in range(6):\r\n",
    "    for col in range(7):\r\n",
    "        if (row==0 and (col%3)!=0 )or( row==1 and col%3==0) or (row-col==2) or (row+col==8):\r\n",
    "            print(\"*\",end=\" \")\r\n",
    "        else:\r\n",
    "            print(\" \",end=\" \") \r\n",
    "    print()"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [],
   "outputs": [],
   "metadata": {}
  }
 ],
 "metadata": {
  "orig_nbformat": 4,
  "language_info": {
   "name": "python",
   "version": "3.9.6",
   "mimetype": "text/x-python",
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "pygments_lexer": "ipython3",
   "nbconvert_exporter": "python",
   "file_extension": ".py"
  },
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.9.6 64-bit"
  },
  "interpreter": {
   "hash": "0c7853acb995686280b13684d9fe2f5bce0c6f4b9d4ccebf3930ab9878453c91"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}