How To Extract App Store Reviews Data In 4 Easy Steps With Python?

July 27, 2021

Depending on the scraping process you choose, web scraping can be simple or complex. Fortunately, there is an easy and great software available for extracting Product Store reviews that may help you scrape evaluations of your applications for sentiment analysis.

Step 1: Installing the applicable package i.e. app_store_scraper

pip install app_store_scraper
Step 2: Import applicable packages

from app_store_scraper import AppStore
import pandas as pd
import numpy as np
import json
tiktok = AppStore(country="us", app_name="tiktok")

This can be accomplished with the help of a simple script. We’ll utilize BeautifulSoup and Python to assist us to extract data, and we’ll keep an eye on eBay prices.

To begin, this is the basic code we’ll need to create an Amazon page and set up BeautifulSoup to enable us search the page for useful data using CSS selectors.

# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import requestsheaders = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'}
url = ' &_sacat=0&LH_TitleDesc=0&Model=Apple%20iPhone%208&_sop=12&LH_PrefLoc=0&rt=nc&Storage%20Capacity=64%20GB&_dcat=9355'response=requests.get(url,headers=headers)
  • ‘app_store_scraper’ packages are for extracting the reviews
  • ‘pandas’ to scrape reviews in the data frames
  • ‘numpy’ to do data transformation

You should see something similar after executing the command. In the first run, we were able to scrape 120 TikTok reviews.


We will be able to retrieve 220 reviews in the second round. Execute this command several times to get various evaluations


It is the most significant step, the reviews get stored in a ‘tiktok’ variable as well as if you are running a command ‘’ for checking them, you could see they get stored in a JSON format.
Step 3: Format Transformation (JSON to Panda Data frame)

df = pd.DataFrame(np.array(,columns=['review'])
df2 = df.join(pd.DataFrame(df.pop('review').tolist()))

The result will look like that.

sample data
Step 4: Save that as CSV

df2.to_csv('/Users/Desktop/App Store Review tiktok.csv')

“/Users/Desktop/” in a pathway of your computer, a location where you need to save a CSV file.

The of the saved CSV file is “/App Store Review tiktok.csv”.

For more information, you can always contact X-Byte Enterprise Crawling!