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Analyze Stack Overflow Trends With Python
Use pandas to analyze Stack Overflow question volume, tags, engagement, and answer status while preserving site and snapshot context.
Jul 21, 2026 · 1 min read · 97 words
Load the output from the Stack Exchange Questions Scraper and make the composite key explicit:
import pandas as pd
questions = pd.read_json("dataset_items.json")
questions = questions.drop_duplicates(["site", "question_id"])
tags = questions[["site", "question_id", "tags"]].explode("tags")
print(tags["tags"].value_counts().head(20))Use creation dates for question-volume trends and last-activity dates for discussion activity. Normalize by the number of collected questions when run limits differ. Analyze views with question age and keep accepted status separate from answer count.
Every chart should state sites, queries, tags, sort order, result limits, and snapshot date. Those choices shape the sample as much as the code does.
Frequently asked questions
Can rows from different sites share an ID?
Yes. Treat site plus question ID as the composite key.
Should views be compared across old and new questions directly?
No. Account for question age and the selected search scope.