I'm trying to remove everything in a dataframe not equal to elements in a list, but I'm getting the following warning:
C:/Users/jalco/PycharmProjects/project/main.py:119: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[sample'] = ''
C:/Users/jalco/PycharmProjects/project/main.py:120: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['sample'] = np.where((df['num'] > 0) &
Here is my code causing the warning:
if not config_dict['admin']:
df = df[~df['transtype'].isin(transtype['admin'])]
if 'sample' in config_dict['links']:
df['sample'] = ''
df['sample'] = np.where((df['num'] > 0) &
(df['transtype'] == df['coll']),
df['num'], df['sample'])
My question is "is there a better way to drop the rows I don't need or do I just silence the warning manually?"
Thanks
I would add .copy()
when actually creating df
because that seems to be the root of the problem, and then you can try assigning the column with .loc[]
. Also you can save a line of code, by simply using:
df.loc[:,'sample'] = np.where((df['num'] > 0) &
(df['transtype'] == df['coll']),
df['num'], ''])
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