Pandas, Seaborn, and the Stack Overflow Survey

This notebook series uses the Stack Overflow Developer Survey to practice real-world data work. You’ll load the dataset, clean and cast columns, explore with filters and groupby, and build simple visuals.

Pandas is the go-to library for tabular data in Python (I/O, selection, missing data, grouping). Seaborn sits on Matplotlib and makes common plots—histograms, scatter/line charts, pairplots, jointplots—quick to produce and easy to style.

The data comes from the annual Stack Overflow Developer Survey: https://survey.stackoverflow.co/ The 2024 annual survey files are already present in the data folder. After unzipping, you’ll typically use survey_results_public.csv (one row per respondent) plus the schema file that maps column codes to their questions.

Install¶

Using pip:

python -m pip install --upgrade pandas seaborn matplotlib

Using conda:

conda install pandas seaborn matplotlib

Quick check:

import pandas as pd, seaborn as sns, matplotlib
print(pd.__version__, sns.__version__, matplotlib.__version__)

Then: load the CSV, inspect with df.info() / df.head(), clean types and missing values, aggregate (e.g., salary by country, language usage by age), and visualize with Seaborn.