How to join Panda DataFrames based on List values in a column [duplicate]











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  • How do I unnest a column in a pandas DataFrame?

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There are two Pandas DataFrame



df_A = pd.DataFrame([['r1', ['a','b']], ['r2',['aabb','b']], ['r3', ['xyz']]], columns=['col1', 'col2'])



 col1     col2

 r1     [a, b]

 r2  [aabb, b]

 r3      [xyz]





df_B = pd.DataFrame([['a', 10], ['b',2]], columns=['C1', 'C2'])



  C1  C2

   a  10

   b   2


I want to join both dataframes such as df_C is



col1 C1  C2

r1   a   10

r1   b    2

r2   aabb 0

r2   b    2

r3   xyz  0





python pandas







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marked as duplicate by Sandeep Kadapa, coldspeed pandas
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 17 hours ago


This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.















  • Thanks, I guess, it might need expert-level knowledge to understand "unsetting" is the same as what I was looking for.
    – Watt
    5 hours ago

















up vote
0
down vote

favorite













This question already has an answer here:




  • How do I unnest a column in a pandas DataFrame?

    3 answers




There are two Pandas DataFrame



df_A = pd.DataFrame([['r1', ['a','b']], ['r2',['aabb','b']], ['r3', ['xyz']]], columns=['col1', 'col2'])



 col1     col2

 r1     [a, b]

 r2  [aabb, b]

 r3      [xyz]





df_B = pd.DataFrame([['a', 10], ['b',2]], columns=['C1', 'C2'])



  C1  C2

   a  10

   b   2


I want to join both dataframes such as df_C is



col1 C1  C2

r1   a   10

r1   b    2

r2   aabb 0

r2   b    2

r3   xyz  0





python pandas







share|improve this question













marked as duplicate by Sandeep Kadapa, coldspeed pandas
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 17 hours ago


This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.















  • Thanks, I guess, it might need expert-level knowledge to understand "unsetting" is the same as what I was looking for.
    – Watt
    5 hours ago















up vote
0
down vote

favorite









up vote
0
down vote

favorite












This question already has an answer here:




  • How do I unnest a column in a pandas DataFrame?

    3 answers




There are two Pandas DataFrame



df_A = pd.DataFrame([['r1', ['a','b']], ['r2',['aabb','b']], ['r3', ['xyz']]], columns=['col1', 'col2'])



 col1     col2

 r1     [a, b]

 r2  [aabb, b]

 r3      [xyz]





df_B = pd.DataFrame([['a', 10], ['b',2]], columns=['C1', 'C2'])



  C1  C2

   a  10

   b   2


I want to join both dataframes such as df_C is



col1 C1  C2

r1   a   10

r1   b    2

r2   aabb 0

r2   b    2

r3   xyz  0





python pandas







share|improve this question














This question already has an answer here:




  • How do I unnest a column in a pandas DataFrame?

    3 answers




There are two Pandas DataFrame



df_A = pd.DataFrame([['r1', ['a','b']], ['r2',['aabb','b']], ['r3', ['xyz']]], columns=['col1', 'col2'])



 col1     col2

 r1     [a, b]

 r2  [aabb, b]

 r3      [xyz]





df_B = pd.DataFrame([['a', 10], ['b',2]], columns=['C1', 'C2'])



  C1  C2

   a  10

   b   2


I want to join both dataframes such as df_C is



col1 C1  C2

r1   a   10

r1   b    2

r2   aabb 0

r2   b    2

r3   xyz  0




This question already has an answer here:




  • How do I unnest a column in a pandas DataFrame?

    3 answers







python pandas




python pandas






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked 18 hours ago









Watt

1,59184165




1,59184165




marked as duplicate by Sandeep Kadapa, coldspeed pandas
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 17 hours ago


This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.






marked as duplicate by Sandeep Kadapa, coldspeed pandas
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 17 hours ago


This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.














  • Thanks, I guess, it might need expert-level knowledge to understand "unsetting" is the same as what I was looking for.
    – Watt
    5 hours ago




















  • Thanks, I guess, it might need expert-level knowledge to understand "unsetting" is the same as what I was looking for.
    – Watt
    5 hours ago


















Thanks, I guess, it might need expert-level knowledge to understand "unsetting" is the same as what I was looking for.
– Watt
5 hours ago






Thanks, I guess, it might need expert-level knowledge to understand "unsetting" is the same as what I was looking for.
– Watt
5 hours ago














1 Answer
1






active

oldest

votes

















up vote
1
down vote













You need:



df = pd.DataFrame([['r1', ['a','b']], ['r2',['aabb','b']], ['r3', ['xyz']]], columns=['col1', 'col2'])



df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()),

                        'C1':np.concatenate(df.col2.values)})



df_B = pd.DataFrame([['a', 10], ['b',2]], columns=['C1', 'C2'])

df_B = dict(zip(df_B.C1, df_B.C2))

# {'a': 10, 'b': 2}



df['C2']= df['C1'].apply(lambda x: df_B[x] if x in df_B.keys() else 0)



print(df)


Output:



    col1  C1    C2

0   r1    a     10

1   r1    b     2

2   r2    aabb  0

3   r2    b     2

4   r3    xyz   0





share|improve this answer





















  • Thanks, can you please explain what you are doing here df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
    – Watt
    5 hours ago


















1 Answer
1






active

oldest

votes








1 Answer
1






active

oldest

votes









active

oldest

votes






active

oldest

votes








up vote
1
down vote













You need:



df = pd.DataFrame([['r1', ['a','b']], ['r2',['aabb','b']], ['r3', ['xyz']]], columns=['col1', 'col2'])



df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()),

                        'C1':np.concatenate(df.col2.values)})



df_B = pd.DataFrame([['a', 10], ['b',2]], columns=['C1', 'C2'])

df_B = dict(zip(df_B.C1, df_B.C2))

# {'a': 10, 'b': 2}



df['C2']= df['C1'].apply(lambda x: df_B[x] if x in df_B.keys() else 0)



print(df)


Output:



    col1  C1    C2

0   r1    a     10

1   r1    b     2

2   r2    aabb  0

3   r2    b     2

4   r3    xyz   0





share|improve this answer





















  • Thanks, can you please explain what you are doing here df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
    – Watt
    5 hours ago















up vote
1
down vote













You need:



df = pd.DataFrame([['r1', ['a','b']], ['r2',['aabb','b']], ['r3', ['xyz']]], columns=['col1', 'col2'])



df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()),

                        'C1':np.concatenate(df.col2.values)})



df_B = pd.DataFrame([['a', 10], ['b',2]], columns=['C1', 'C2'])

df_B = dict(zip(df_B.C1, df_B.C2))

# {'a': 10, 'b': 2}



df['C2']= df['C1'].apply(lambda x: df_B[x] if x in df_B.keys() else 0)



print(df)


Output:



    col1  C1    C2

0   r1    a     10

1   r1    b     2

2   r2    aabb  0

3   r2    b     2

4   r3    xyz   0





share|improve this answer





















  • Thanks, can you please explain what you are doing here df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
    – Watt
    5 hours ago













up vote
1
down vote










up vote
1
down vote









You need:



df = pd.DataFrame([['r1', ['a','b']], ['r2',['aabb','b']], ['r3', ['xyz']]], columns=['col1', 'col2'])



df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()),

                        'C1':np.concatenate(df.col2.values)})



df_B = pd.DataFrame([['a', 10], ['b',2]], columns=['C1', 'C2'])

df_B = dict(zip(df_B.C1, df_B.C2))

# {'a': 10, 'b': 2}



df['C2']= df['C1'].apply(lambda x: df_B[x] if x in df_B.keys() else 0)



print(df)


Output:



    col1  C1    C2

0   r1    a     10

1   r1    b     2

2   r2    aabb  0

3   r2    b     2

4   r3    xyz   0





share|improve this answer












You need:



df = pd.DataFrame([['r1', ['a','b']], ['r2',['aabb','b']], ['r3', ['xyz']]], columns=['col1', 'col2'])



df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()),

                        'C1':np.concatenate(df.col2.values)})



df_B = pd.DataFrame([['a', 10], ['b',2]], columns=['C1', 'C2'])

df_B = dict(zip(df_B.C1, df_B.C2))

# {'a': 10, 'b': 2}



df['C2']= df['C1'].apply(lambda x: df_B[x] if x in df_B.keys() else 0)



print(df)


Output:



    col1  C1    C2

0   r1    a     10

1   r1    b     2

2   r2    aabb  0

3   r2    b     2

4   r3    xyz   0






share|improve this answer












share|improve this answer



share|improve this answer










answered 18 hours ago









Sociopath

2,92161331




2,92161331












  • Thanks, can you please explain what you are doing here df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
    – Watt
    5 hours ago


















  • Thanks, can you please explain what you are doing here df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
    – Watt
    5 hours ago
















Thanks, can you please explain what you are doing here df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
– Watt
5 hours ago




Thanks, can you please explain what you are doing here df= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
– Watt
5 hours ago



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