如何使用columns值作为字典的键，根据返回的值过滤pandas df的行

Question

I have a dataframe which I need to filter rows out when the value returned by a dictionary using the value of the specific column is used as a dictionary key to return the keys value.

I have been able to filter the rows based on the columns value but when i try to use the columns value in a dictionary in a similar fashion iit returns an error.

TypeError: 'Series' objects are mutable, thus they cannot be hashed

indexNames = df[ accounting_type_dict[df['fund_id']] == 'ETFs' ].index
df.drop(indexNames , inplace=True)

Answer 1

使用map然后过滤

newdf=df[df['fund_id'].map(accounting_type_dict) == 'ETFs'].copy()

Answer 2

You could try replacing the column with the corresponding values from the dict. (You may need to use map instead of replace depending on how large the DataFrame is.)

indexNames = df[ df['fund_id'].replace(accounting_type_dict) == 'ETFs' ].index
df.drop(indexNames , inplace=True)