Pandas Dataframe Merging
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Multi tool use
I have a bit of a weird pandas question.
I have a master Dataframe:
a b c
0 22 44 55
1 22 45 22
2 44 23 56
3 45 22 33
I then have a dataframe in a different dimension which has some over lapping index's and column names
index col_name new_value
0 a 111
3 b 234
I'm trying to then say if you find a match on index and col_name in the master dataframe, then replace the value.
So the output would be
a b c
0 111 44 55
1 22 45 22
2 44 23 56
3 45 234 33
I've found "Combine_first" but this doesn't work unless I pivot the second dataframe (which I can't do in this scenario)
pandas merge
add a comment |
I have a bit of a weird pandas question.
I have a master Dataframe:
a b c
0 22 44 55
1 22 45 22
2 44 23 56
3 45 22 33
I then have a dataframe in a different dimension which has some over lapping index's and column names
index col_name new_value
0 a 111
3 b 234
I'm trying to then say if you find a match on index and col_name in the master dataframe, then replace the value.
So the output would be
a b c
0 111 44 55
1 22 45 22
2 44 23 56
3 45 234 33
I've found "Combine_first" but this doesn't work unless I pivot the second dataframe (which I can't do in this scenario)
pandas merge
add a comment |
I have a bit of a weird pandas question.
I have a master Dataframe:
a b c
0 22 44 55
1 22 45 22
2 44 23 56
3 45 22 33
I then have a dataframe in a different dimension which has some over lapping index's and column names
index col_name new_value
0 a 111
3 b 234
I'm trying to then say if you find a match on index and col_name in the master dataframe, then replace the value.
So the output would be
a b c
0 111 44 55
1 22 45 22
2 44 23 56
3 45 234 33
I've found "Combine_first" but this doesn't work unless I pivot the second dataframe (which I can't do in this scenario)
pandas merge
I have a bit of a weird pandas question.
I have a master Dataframe:
a b c
0 22 44 55
1 22 45 22
2 44 23 56
3 45 22 33
I then have a dataframe in a different dimension which has some over lapping index's and column names
index col_name new_value
0 a 111
3 b 234
I'm trying to then say if you find a match on index and col_name in the master dataframe, then replace the value.
So the output would be
a b c
0 111 44 55
1 22 45 22
2 44 23 56
3 45 234 33
I've found "Combine_first" but this doesn't work unless I pivot the second dataframe (which I can't do in this scenario)
pandas merge
pandas merge
asked Dec 27 '18 at 16:34
fred.schwartz
3048
3048
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
This is update
problem
df.update(updated.pivot(*updated.columns))
df
Out[479]:
a b c
0 111.0 44.0 55
1 22.0 45.0 22
2 44.0 23.0 56
3 45.0 234.0 33
Or
df.values[updated['index'].values,df.columns.get_indexer(updated.col_name)]=updated.new_value.values
df
Out[495]:
a b c
0 111 44 55
1 22 45 22
2 44 23 56
3 45 234 33
Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
– fred.schwartz
Dec 27 '18 at 16:40
1
Wow. This is cool. +1
– Scott Boston
Dec 27 '18 at 16:40
1
@ScottBoston thank you man
– W-B
Dec 27 '18 at 16:41
1
@fred.schwartz yes , it is
– W-B
Dec 27 '18 at 16:42
1
@coldspeed thank you so much ! Without your support, this would not have been possible!
– W-B
Dec 27 '18 at 16:51
|
show 3 more comments
Your Answer
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
This is update
problem
df.update(updated.pivot(*updated.columns))
df
Out[479]:
a b c
0 111.0 44.0 55
1 22.0 45.0 22
2 44.0 23.0 56
3 45.0 234.0 33
Or
df.values[updated['index'].values,df.columns.get_indexer(updated.col_name)]=updated.new_value.values
df
Out[495]:
a b c
0 111 44 55
1 22 45 22
2 44 23 56
3 45 234 33
Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
– fred.schwartz
Dec 27 '18 at 16:40
1
Wow. This is cool. +1
– Scott Boston
Dec 27 '18 at 16:40
1
@ScottBoston thank you man
– W-B
Dec 27 '18 at 16:41
1
@fred.schwartz yes , it is
– W-B
Dec 27 '18 at 16:42
1
@coldspeed thank you so much ! Without your support, this would not have been possible!
– W-B
Dec 27 '18 at 16:51
|
show 3 more comments
This is update
problem
df.update(updated.pivot(*updated.columns))
df
Out[479]:
a b c
0 111.0 44.0 55
1 22.0 45.0 22
2 44.0 23.0 56
3 45.0 234.0 33
Or
df.values[updated['index'].values,df.columns.get_indexer(updated.col_name)]=updated.new_value.values
df
Out[495]:
a b c
0 111 44 55
1 22 45 22
2 44 23 56
3 45 234 33
Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
– fred.schwartz
Dec 27 '18 at 16:40
1
Wow. This is cool. +1
– Scott Boston
Dec 27 '18 at 16:40
1
@ScottBoston thank you man
– W-B
Dec 27 '18 at 16:41
1
@fred.schwartz yes , it is
– W-B
Dec 27 '18 at 16:42
1
@coldspeed thank you so much ! Without your support, this would not have been possible!
– W-B
Dec 27 '18 at 16:51
|
show 3 more comments
This is update
problem
df.update(updated.pivot(*updated.columns))
df
Out[479]:
a b c
0 111.0 44.0 55
1 22.0 45.0 22
2 44.0 23.0 56
3 45.0 234.0 33
Or
df.values[updated['index'].values,df.columns.get_indexer(updated.col_name)]=updated.new_value.values
df
Out[495]:
a b c
0 111 44 55
1 22 45 22
2 44 23 56
3 45 234 33
This is update
problem
df.update(updated.pivot(*updated.columns))
df
Out[479]:
a b c
0 111.0 44.0 55
1 22.0 45.0 22
2 44.0 23.0 56
3 45.0 234.0 33
Or
df.values[updated['index'].values,df.columns.get_indexer(updated.col_name)]=updated.new_value.values
df
Out[495]:
a b c
0 111 44 55
1 22 45 22
2 44 23 56
3 45 234 33
answered Dec 27 '18 at 16:36
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W-B
101k73163
101k73163
Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
– fred.schwartz
Dec 27 '18 at 16:40
1
Wow. This is cool. +1
– Scott Boston
Dec 27 '18 at 16:40
1
@ScottBoston thank you man
– W-B
Dec 27 '18 at 16:41
1
@fred.schwartz yes , it is
– W-B
Dec 27 '18 at 16:42
1
@coldspeed thank you so much ! Without your support, this would not have been possible!
– W-B
Dec 27 '18 at 16:51
|
show 3 more comments
Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
– fred.schwartz
Dec 27 '18 at 16:40
1
Wow. This is cool. +1
– Scott Boston
Dec 27 '18 at 16:40
1
@ScottBoston thank you man
– W-B
Dec 27 '18 at 16:41
1
@fred.schwartz yes , it is
– W-B
Dec 27 '18 at 16:42
1
@coldspeed thank you so much ! Without your support, this would not have been possible!
– W-B
Dec 27 '18 at 16:51
Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
– fred.schwartz
Dec 27 '18 at 16:40
Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
– fred.schwartz
Dec 27 '18 at 16:40
1
1
Wow. This is cool. +1
– Scott Boston
Dec 27 '18 at 16:40
Wow. This is cool. +1
– Scott Boston
Dec 27 '18 at 16:40
1
1
@ScottBoston thank you man
– W-B
Dec 27 '18 at 16:41
@ScottBoston thank you man
– W-B
Dec 27 '18 at 16:41
1
1
@fred.schwartz yes , it is
– W-B
Dec 27 '18 at 16:42
@fred.schwartz yes , it is
– W-B
Dec 27 '18 at 16:42
1
1
@coldspeed thank you so much ! Without your support, this would not have been possible!
– W-B
Dec 27 '18 at 16:51
@coldspeed thank you so much ! Without your support, this would not have been possible!
– W-B
Dec 27 '18 at 16:51
|
show 3 more comments
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