← NumPy & Pandas learning pathNumPy & Pandas · Module 10 of 10
Performance and real analysis
Handle bigger data and complete an analysis project.
📖 Key ideas
- Use vectorised operations; avoid loops over rows.
- Choose efficient dtypes (category, int32).
- Read big files in chunks or use Parquet.
- Plot quickly with df.plot().
- Project flow: load, clean, explore, analyse, visualise, report.
💡 Real-life example: An analysis project is cooking a full meal: shopping (load), washing (clean), cooking (analyse), serving (report).
ParquetFast columnar file format
category dtypeMemory-efficient labels
chunksizeRead files in pieces
EDAExploratory Data Analysis