Answer
Use chunking or lazy loading.
Use vectorized NumPy/pandas operations.
Use Dask or PySpark for distributed computing.
Use vectorized NumPy/pandas operations.
Use Dask or PySpark for distributed computing.
Quick Answer
Large dataset handling in Python: pandas chunking: pd.read_csv(file, chunksize=10000) reads in chunks. Dask (parallel pandas on multiple cores or clusters). Polars (Rust-based, much faster than pandas for large files). Vaex (lazy evaluation, out-of-core computation). Parquet format (columnar, compressed) instead of CSV. PySpark for distributed processing at very large scale.
S
SugharaIQ Editorial Team
Verified Answer
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Source: SugharaIQ