How can I efficiently handle large CSV files in Python?

How can I efficiently handle large CSV files in Python?

You can use libraries like pandas or Dask. Pandas is great for smaller datasets, while Dask can handle larger ones.

What are the advantages of using Dask over pandas?

Dask allows for parallel computing and can handle datasets that don't fit into memory, making it more scalable.

Can you show me a simple example of using Dask to read a large CSV?

Sure! Here's a basic example:

import dask.dataframe as dd

df = dd.read_csv('large_file.csv')
print(df.head())

This reads the CSV in chunks.

What if I want to perform some data manipulation on the Dask DataFrame?

You can use similar methods as pandas. For example, you can filter, group, or aggregate data using Dask DataFrame methods.