C3PythonIntermediateAbout 110 min to complete
Reading CSV, Excel & JSON
Reliable ingestion from every format you will meet — and the parameters that prevent silent corruption.
Notebook
About 110 minutes to complete
Enrol to read the notebook and download it to run.
What this module covers
Reliable ingestion from every format you will meet — and the parameters that prevent silent corruption.
By the end of it
- Use the read_csv parameters that matter: dtype, parse_dates, na_values,
- Prevent the leading-zero and dtype-inference failures that corrupt IDs
- Read Excel workbooks with multiple sheets and header offsets
- Flatten nested JSON with json_normalize
- Query SQL databases with SQLAlchemy
- Write formatted Excel output with XlsxWriter
- Load large files with chunksize and reduced memory
- Validate every load before trusting it