google_trends.py

# Essentials
import pandas as pd
import numpy as np
from time import sleep
from random import randint

# Trends API
from pytrends.request import TrendReq

# Optional
from tqdm import notebook as tqdm

# For Data Visualization
import plotly.graph_objects as go

pytrends = TrendReq(hl='en-US', tz=360)

### Establish Keyword List and Build Payload ###
kw_list = [
  'Keywords go here'
]
frame = []
for i in tqdm.tqdm(kw_list):
    try:
        pytrends.build_payload([i], cat=0, geo='US', gprop='')
        interest = pytrends.get_historical_interest([i], year_start=2020, month_start=4, 
                                                    day_start=12, hour_start=0, year_end=2020, 
                                                    month_end=4, day_end=19, hour_end=0, cat=0,
                                                    geo='', gprop='', sleep=0)
        gr = interest
        hold = gr.columns[0]
        name = gr.columns[0]
        gr = gr.rename(columns={name: 'Search Popularity'})
        gr = gr[['Search Popularity']]
        gr['Term'] = hold
        sleep(randint(5,20))
        frame.append(gr)
    except:
        pass
    
final = pd.concat(frame)
final.index = pd.MultiIndex.from_arrays([final.index.date, final.index.time], names=['Date','Time'])

pivot = final.pivot_table(index=['Time'],
                         values=['Search Popularity'], 
                         aggfunc=np.mean)

layout = go.Layout(
    title='Aggregated Time of Day Demand: Office Supplies',
    yaxis=dict(title='Search Popularity Index'),
    xaxis=dict(title='Time of Day'))

fig = go.Figure(data=go.Scatter(x=pivot.index, y=pivot['Search Popularity']), 
               layout=layout)
fig.show()


final.to_csv('raw_data.csv')