firstpanda.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6b5222e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "daae5aa6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    2\n",
       "2    3\n",
       "3    4\n",
       "4    5\n",
       "5    6\n",
       "6    7\n",
       "dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = pd.Series([1,2,3,4,5,6,7])\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "189bfb0b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.3.4\n"
     ]
    }
   ],
   "source": [
    "print(pd.__version__) #to discover the version of pandas!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc1682ee",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "name": "python3"
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    "name": "ipython",
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   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
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 "nbformat": 4,
 "nbformat_minor": 5
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