How to drop all strings in a column using a wildcard?

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I have some data that changes regularly but the column headers need to be consistent (so I cant drop the headers) but I need to clear our the strings in a given column.

This is what I have now but this only seems to work for where I know what the string is called and one at a time?

    df1= pd.read_csv(r'C:\Users\Test.csv')
df2 = df1.drop(df1[~(df1['column'] != 'String1')].index)
pandas python-3.x python
1 Answers

You can use the pd.drop function which removes rows having a specific index from a dataframe.

for i in df.index:
    if type(df.loc[i, 'Aborted Reason']) ==  str:
        df.drop(i, inplace = True)

df.drop will remove the index having a string in the relevant column from the dataframe.

user_142747780
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