Restaurant Review Data Analysis with Python and pyecharts

The article demonstrates how to collect restaurant review data from online platforms such as Dazhong Dianping, clean the JSON‑like response (converting true/false/null to Python True/False/None), and store it in a Python dictionary named review_data saved in data.py .

It then creates an analysis.py script that imports the data, extracts summary information, and visualizes it with pyecharts bar and pie charts. The bar chart shows overall impression categories (e.g., “菜品健康”, “牛肉赞”, “回头客”) using X‑axis labels and Y‑axis counts derived via list comprehensions.

For the pie chart, the script extracts the star rating field from each review, builds a list all_star , counts occurrences with Counter , converts the result to a dictionary stars , and zips the keys and values to feed pyecharts.

Key code snippets include:

#获取整体评价名称
summary_name_list = [i.get('summaryString') for i in summarys]
#获取整体评价次数统计
summary_count_list = [i.get('summaryCount') for i in summarys]

all_star = [i.get('reviewDataVO').get('reviewData').get('star') for i in all_review]
stars = dict(Counter(all_star))
data = zip(list(stars.keys()), list(stars.values()))

Finally, four charts (two bar charts and two pie charts) are generated to provide an initial analytical view of the restaurant, illustrating how Python’s standard libraries and pyecharts can be combined for practical business intelligence.