How can I reduce the memory usage of a pandas DataFrame?
An example of an AI chatbot conversation about reducing memory usage in pandas DataFrames.
How can I reduce the memory usage of a pandas DataFrame?
You can reduce memory usage by changing data types, dropping unnecessary columns, and using efficient storage formats.
What data types should I consider changing?
Consider converting float64 to float32, int64 to int32, and using category for string columns with limited unique values.
Are there any specific functions in pandas to help with this?
Yes, you can use astype() to change data types and memory_usage(deep=True) to check memory usage before and after.
Can you give me an example of how to use these functions?
Sure! You can use df['column'] = df['column'].astype('category') to convert a column to category type.
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