CODEWITHSUNDEEP
python-3.xpandas
Pao0
Pao0

Reputation: 13

Matching ID between two pandas series

I have, I guess a simple question but I cannot find the right answer. I have two pandas series (let's say "A" and "B") with ID in there (string). Series A is bigger than series B. What I am looking for is a way to have a resulting dataframe with 2 columns where the matching elements are on the same row and if there is a value in A that don't exist in B, to add a NaN.

A            B
10368        10368
12567        NaN
13456        13456
...          ...

and so on.

I guess the merge function in pandas can be helpful but I could not manage to make it work

Thanks in advance

Upvotes: 1

Views: 110

Answers (2)

Chris Adams
Chris Adams

Reputation: 18647

You could use pd.concat and boolean index using isin:

a = pd.Series(['10368', '12567', '13456'])
b = pd.Series(['10368', '13456'])

pd.concat([a, a[a.isin(b)]], axis=1)

[out]

       0      1
0  10368  10368
1  12567    NaN
2  13456  13456

Upvotes: 1

talatccan
talatccan

Reputation: 743

You can try this:

df.loc[df['A'].isin(df['B']), 'B'] = df['A']
df.loc[~df['A'].isin(df['B']), 'B'] = np.nan

Before:

   A  B
0  1  2
1  2  1
2  3  4
3  7  0

After:

   A    B
0  1  1.0
1  2  2.0
2  3  NaN
3  7  NaN

Upvotes: 2

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