CODEWITHSUNDEEP
pythonpandasdictionaryfilter
BAC83
BAC83

Reputation: 891

Filtering pandas dataframe using dictionary for column values

Premise

I need to use a dictionary as a filter on a large dataframe, where the key-value pairs are values in different columns. This dictionary is obtained from a separate dataframe, using dict(zip(df.id_col, df.rank_col)) so if a dictionary isn't the best way to go, that is open to change.

This is very similar to this question: Filter a pandas dataframe using values from a dict but fundamentally (I think) different because my dictionary contains column-paired values:

Example data

df_x = pd.DataFrame({'id':[1,1,1,2,2,2,3,3,3], 
'B':[1,1,1,0,1,0,1,0,1], 'Rank':['1','2','3','1', '2','3','1','2','3'],'D':[1,2,3,4,5,6,7,8,9]})
filter_dict = {'1':'1', '2':'3', '3':'2'}

For this dataframe df_x I would want to be able to look at the filter dictionary and apply it to a set of columns, here id and Rank, so the dataframe is pared down to:

enter image description here

The actual source dataframe is approx 1M rows, and the dictionary is >100 key-value pairs. Thanks for any help.

Upvotes: 2

Views: 2581

Answers (1)

BENY
BENY

Reputation: 323226

You can check with isin 

df_x[df_x[['id','Rank']].astype(str).apply(tuple,1).isin(filter_dict.items())]
Out[182]: 
   id  B Rank  D
0   1  1    1  1
5   2  0    3  6
7   3  0    2  8

Upvotes: 5

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