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
asked 18 hours ago
Watt
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.
add a comment |
up vote
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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
asked 18 hours ago
Watt
1,59184165
marked as duplicate by Sandeep Kadapa, coldspeed pandas
Users with the pandas badge can single-handedly close pandas questions as duplicates and reopen them as needed.
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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
add a comment |
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
asked 18 hours ago
Watt
1,59184165
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
asked 18 hours ago
Watt
1,59184165
asked 18 hours ago
Watt
1,59184165
asked 18 hours ago
Watt
1,59184165
asked 18 hours ago
Watt
1,59184165
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
add a comment |
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
add a comment |
1 Answer
1
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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
answered 18 hours ago
Sociopath
2,92161331
Thanks, can you please explain what you are doing heredf= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
– Watt
5 hours ago
add a comment |
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
answered 18 hours ago
Sociopath
2,92161331
Thanks, can you please explain what you are doing heredf= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
– Watt
5 hours ago
add a comment |
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
answered 18 hours ago
Sociopath
2,92161331
Thanks, can you please explain what you are doing heredf= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
– Watt
5 hours ago
add a comment |
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
answered 18 hours ago
Sociopath
2,92161331
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
answered 18 hours ago
Sociopath
2,92161331
answered 18 hours ago
Sociopath
2,92161331
answered 18 hours ago
Sociopath
2,92161331
answered 18 hours ago
Sociopath
2,92161331
2,92161331
Thanks, can you please explain what you are doing heredf= pd.DataFrame({'col1':np.repeat(df.col1.values, df.col2.str.len()), 'C1':np.concatenate(df.col2.values)})
– Watt
5 hours ago
add a comment |
Thanks, can you please explain what you are doing heredf= 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
add a comment |
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