How can I optimize memory usage in Pandas?
An example of an AI chatbot conversation about optimizing memory usage in Pandas.
How can I optimize memory usage in Pandas?
You can optimize memory usage in Pandas by using appropriate data types, dropping unnecessary columns, and using chunking.
What data types should I consider for optimization?
Consider using 'category' for categorical data, 'float32' instead of 'float64', and 'int32' instead of 'int64'.
How do I drop unnecessary columns?
You can drop columns using the drop() method, like this: df.drop(columns=['column_name'], inplace=True).
What is chunking and how can it help?
Chunking allows you to read large datasets in smaller pieces, reducing memory load. Use pd.read_csv() with the chunksize parameter.
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