Python for Data Analysis¶
Python is the de-facto language for data analysis. This section covers EDA, the core libraries, and copy-paste snippets.
Pages¶
- EDA — exploratory data analysis workflow
- Libraries — pandas, numpy, matplotlib, seaborn, plotly, scipy, statsmodels
- Snippets — ready-to-use code blocks
Why Python¶
- Free, open source, huge ecosystem
- One language for ETL, analysis, visualization, modeling, deployment
- Reproducible (notebooks, scripts, version control)
- Active community on Kaggle, Stack Overflow, Towards Data Science
Setup with uv¶
uv init my-analysis
cd my-analysis
uv add pandas numpy matplotlib seaborn jupyter
uv run jupyter lab
Reading and writing data¶
import pandas as pd
df = pd.read_csv('file.csv')
df = pd.read_excel('file.xlsx', sheet_name='Sheet1')
df = pd.read_parquet('file.parquet')
df = pd.read_json('file.json')
df = pd.read_sql('SELECT * FROM users', conn)
df.to_csv('out.csv', index=False)
df.to_parquet('out.parquet')