I need to filter a data frame with a dict, constructed with the key being the column name and the value being the value that I want to filter:
filter_v = {'A':1, 'B':0, 'C':'This is right'}
# this would be the normal approach
df[(df['A'] == 1) & (df['B'] ==0)& (df['C'] == 'This is right')]
But I want to do something on the lines
for column, value in filter_v.items():
df[df[column] == value]
but this will filter the data frame several times, one value at a time, and not apply all filters at the same time. Is there a way to do it programmatically?
EDIT: an example:
df1 = pd.DataFrame({'A':[1,0,1,1, np.nan], 'B':[1,1,1,0,1], 'C':['right','right','wrong','right', 'right'],'D':[1,2,2,3,4]})
filter_v = {'A':1, 'B':0, 'C':'right'}
df1.loc[df1[filter_v.keys()].isin(filter_v.values()).all(axis=1), :]
gives
A B C D
0 1 1 right 1
1 0 1 right 2
3 1 0 right 3
but the expected result was
A B C D
3 1 0 right 3
only the last one should be selected.
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