CODEWITHSUNDEEP
pythonpandasdictionary
Tony
Tony

Reputation: 45

Compare dataframe to list of dictionary values

I have a dataframe:

d = {'col1':['2q','48', '48-49']}
test = pd.DataFrame(d)


col1

0 2q
1 48 
2 48-49

And a dictionary for mapping:

mupcs_to_pc_mapping = {'24': ['48-49', '48', '49'], #M2
                   '23': ['50-51', '50', '51'], #M3
                   '22': ['52-53', '52', '53'], #M4
                   '21': ['54-55', '54', '55'], #M5
                  }

I would like to test each value of the test dataframe to see if it exists in the mupcs_to_pc_mapping dict values.

So the final result is something like:

0 False
1 True
2 True

I tried a variation of:

test['col1'].isin(mupcs_to_pc_mapping.values())

and

test['col1'].any(value for value in mupcs_to_pc_mapping.values())

but both of them result in an error.

Does anyone know what is wrong with my code?

Upvotes: 2

Views: 1774

Answers (4)

piRSquared
piRSquared

Reputation: 294278

Create a set that is the union of all dictionary values

test.col1.isin(set.union(*map(set, mupcs_to_pc_mapping.values())))

0    False
1     True
2     True
Name: col1, dtype: bool

Upvotes: 3

BENY
BENY

Reputation: 323266

I think you need 

test.col1.isin(sum(mupcs_to_pc_mapping.values(),[]))
Out[477]: 
0    False
1     True
2     True
Name: col1, dtype: bool

Mentioned by cold in the comment itertools.chain

list(itertools.chain.from_iterable(mupcs_to_pc_mapping.values()))

Upvotes: 4

cs95
cs95

Reputation: 402523

First, invert your mapping:

m = {v : k for k in mupcs_to_pc_mapping for v in  mupcs_to_pc_mapping[k]}

Now, use map and test for NaNs.

test.col1.map(m).notnull()

0    False
1     True
2     True
Name: col1, dtype: bool

Upvotes: 3

Bharath M Shetty
Bharath M Shetty

Reputation: 30605

You can also do :

test.isin(pd.DataFrame(mupcs_to_pc_mapping).stack().values)

   col1
0  False
1  True
2  True

Upvotes: 5

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