Example of how to take search interest around multiple keywords and align it to stock activity

htz_search_comparison.py

import pandas as pd
from time import sleep
from random import randint
from tqdm import notebook as tqdm

### Import Modules and Set Perimeters for Pytrends ###
from pytrends.request import TrendReq

### For Ticker Information
import yfinance as yf

### For Data Visualization ###
import plotly.graph_objects as go
from plotly.subplots import make_subplots


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

df = pd.read_excel('htz_stock.xlsx') #Contained 45 Relevant Search Terms
kw_list = df.Keyword.to_list()

### Establish Keyword List and Build Payload ###

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=5, 
                                                    day_start=10, hour_start=0, year_end=2020, 
                                                    month_end=6, day_end=10, hour_end=0, cat=0,
                                                    geo='US', gprop='', sleep=20)
        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=['Date'],
                         values=['Search Popularity'], 
                         aggfunc=np.mean)

htz = yf.Ticker("HTZ")
df_htz = pd.DataFrame(htz.history(period="1mo"))

fig = make_subplots(specs=[[{"secondary_y": True}]])

fig.add_trace(go.Candlestick(x=df_htz.index,
                                     open=df_htz['Open'],
                                     high=df_htz['High'],
                                     low=df_htz['Low'],
                                     close=df_htz['Close'],
                            name='HTZ Stock'), 
             secondary_y=False)
fig.update(layout_xaxis_rangeslider_visible=False)

fig.add_trace(go.Scatter(x=pivot.index, y=pivot['Search Popularity'], 
                         name='Search Interest', 
                        line=dict(color='royalblue')), 
             secondary_y=True)

fig.update_layout(
    title='Hertz Market Activity vs. Retail Investor Search Interest',
    yaxis_title='HTZ Stock',
    yaxis_tickprefix = '$', yaxis_tickformat = ',.',
    shapes = [dict(
        x0='2020-05-22', x1='2020-05-22', y0=0, y1=1, xref='x', yref='paper',
        line_width=2)],
    annotations=[dict(
        x='2020-05-22', y=0.05, xref='x', yref='paper',
        showarrow=False, xanchor='right', text='<b>Hertz Files for Bankruptcy</b>')]
)

# Set x-axis title
fig.update_xaxes(title_text="Date")

# Set y-axes titles
fig.update_yaxes(title_text="HTZ Stock", secondary_y=False)
fig.update_yaxes(title_text="Search Interest", secondary_y=True)

fig.show()