Performancewarning: dropping on a non-lexsorted multi-index without a level parameter may impact performance.

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A performance warning is being raised because you are attempting to drop values from a non-lexsorted multi-index without specifying a level parameter. This can potentially have an impact on performance. To understand this warning further, let’s first define a non-lexsorted multi-index.

Non-Lexsorted Multi-Index

In pandas, a multi-index (also known as hierarchical index) allows you to have multiple levels of row or column indices. By default, these indices are expected to be sorted in lexsort order, which means that the outermost level is sorted first, followed by the next level, and so on. However, if your multi-index is not sorted in this order, it is considered as a non-lexsorted multi-index.

For example, consider the following non-lexsorted multi-index:

    
import pandas as pd

# Create a non-lexsorted multi-index DataFrame
data = {
    'A': [1, 2, 3, 4],
    'B': [5, 6, 7, 8]
}

df = pd.DataFrame(data, index=pd.MultiIndex.from_tuples([(2, 1), (1, 2), (2, 2), (1, 1)], names=['A', 'B']))
df

The above code will create a DataFrame with a non-lexsorted multi-index where the indices (2, 1) and (1, 2) are not in the expected lexsort order.

Dropping on a Non-Lexsorted Multi-Index without Level Parameter

When you attempt to drop values from a non-lexsorted multi-index without specifying a level parameter, pandas will raise a performance warning. This is because pandas will have to perform additional sorting operations internally to handle the non-lexsorted index, which can have an impact on performance.

For example, consider the following code:

    
# Drop rows with index values (2, 1) and (1, 2)
df.drop([(2, 1), (1, 2)])

Running the above code on the DataFrame with a non-lexsorted multi-index will result in a performance warning. To avoid the warning and potential performance impact, you should specify the level parameter while dropping.

Dropping on a Non-Lexsorted Multi-Index with Level Parameter

To drop values from a non-lexsorted multi-index without triggering the performance warning, you should provide the level parameter with the appropriate index level. The level parameter specifies the level(s) at which the dropping operation should be performed.

For example, consider the following code:

    
# Drop rows with index values (2, 1) and (1, 2) at level 0
df.drop([(2, 1), (1, 2)], level=0)

In the above code, we specify level=0 to indicate that the dropping operation should be performed at the outermost level of the multi-index. This will avoid the performance warning and ensure efficient dropping of values from the DataFrame.

Now you should be able to understand the performance warning that is being raised in your case and how to address it by specifying the level parameter while dropping values from a non-lexsorted multi-index.

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