QST: About the meaning of ~ used in dfs = dfs.loc[:, ~dfs.columns.str.contains('^Unnamed', na=False)].

[hongyi-zhao]

• I have searched the [pandas] tag on StackOverflow for similar questions.

• I have asked my usage related question on StackOverflow.

Link to question on StackOverflow

https://stackoverflow.com/a/64335734

Question about pandas

Currently, I'm using the following method to get rid of Unnamed: 0 column in a pandas DataFrame according to the comments noted here and here:

import pandas as pd

excel='2021-2022-1.xlsx'
dfs = pd.read_excel(excel)
dfs = dfs.loc[:, ~dfs.columns.str.contains('^Unnamed', na=False)]

But I am puzzled by the meaning of the ~ symbol used above. I try to find some relevant explanations by googling or digging into the source code of pandas, but still got nothing. Any hints for this question will be greatly appreciated.

Regards,
HZ

[phofl]

This has nothing to do with pandas. It is a python operator

https://docs.python.org/3/reference/expressions.html#unary-arithmetic-and-bitwise-operations

[hongyi-zhao]

Based on your notes, I would like to add some relevant validations as follows:

In [1]: import pandas as pd
In [3]: dfs =pd.read_excel('2020-2021-2.xlsx')
In [11]: import numpy as np

In [17]: dfs.columns.str.contains('^Unnamed', na=False)
Out[17]: 
array([ True, False, False, False, False, False, False, False, False,
       False])

In [18]: ~dfs.columns.str.contains('^Unnamed', na=False)
Out[18]: 
array([False,  True,  True,  True,  True,  True,  True,  True,  True,
        True])

In [19]: bool_arr = np.array([True, False, False, False, False, False, False, False, False, False], dtype=bool)
In [20]: ~bool_arr
Out[20]: 
array([False,  True,  True,  True,  True,  True,  True,  True,  True,
        True])

So, the Unnamed column will be filtered out by the above expression. See here, here, here, here, and here for some additional explanations.