Keywords-Copy1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pytrends\n",
    "import pandas as pd                        \n",
    "from pytrends.request import TrendReq\n",
    "pytrend = TrendReq()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = input(\"Compare Search Trends (Provide keywords seperated by commas):\")\n",
    "kw_list=a.split(',')\n",
    "print(kw_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pytrend.build_payload(kw_list=kw_list, timeframe='today 5-y', geo='IN')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "interest_over_time_df=pytrend.interest_over_time()\n",
    "print(interest_over_time_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt  \n",
    "import time\n",
    "import datetime\n",
    "from datetime import datetime, date, time\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dx= interest_over_time_df.plot.line(figsize=(12,8), title=\"Interest over time\",colormap=\"Set1\", linewidth=3)\n",
    "dx.set_xlabel(\"Date\", fontsize=22)\n",
    "dx.set_ylabel(\"Interest Over Time\", fontsize=22)\n",
    "dx.tick_params(axis='both', which='major', labelsize=22)\n",
    "dx.set_title('Comparison Across Keywords',fontsize=30)\n",
    "dx.legend(fontsize=15)\n",
    "\n",
    "dx.text(2640,-2,'Machine Generated Insights', style='italic', bbox={'facecolor': 'grey', 'alpha': 0.5, 'pad': 3}, rotation=270)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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requirements.txt

pytrends==4.7.3
matplotlib==3.2.1
pandas==1.0.4