Pandas merging two dataframes with different number of multiindices
Welcome, I have a simple question, to which I haven't found a solution.
I have two dataframes df1
and df2
:
df1
contains several columns and a multiindex asyear-month-week
df2
contains the multiindexyear-week
with only one column in the df.
I would like to create an inner join
of df1
and df2
, joining on 'year'
and 'week'
.
I have tried to do the following:
df1['newcol'] = df1.index.get_level_values(2).map(lambda x: df2.newcol[x])
Which only joins on month (or year?), is there any way to expand it so that the merge is actually right?
Thanks in advance!
df1
df2
python pandas dataframe
|
show 1 more comment
Welcome, I have a simple question, to which I haven't found a solution.
I have two dataframes df1
and df2
:
df1
contains several columns and a multiindex asyear-month-week
df2
contains the multiindexyear-week
with only one column in the df.
I would like to create an inner join
of df1
and df2
, joining on 'year'
and 'week'
.
I have tried to do the following:
df1['newcol'] = df1.index.get_level_values(2).map(lambda x: df2.newcol[x])
Which only joins on month (or year?), is there any way to expand it so that the merge is actually right?
Thanks in advance!
df1
df2
python pandas dataframe
2
Can you provide a sample dataframe via a Minimal, Complete, and Verifiable example.
– jpp
Nov 22 '18 at 15:10
2
Show us some sample of the datasets. Refer to the guide on how to add code snippets.
– Shiv_90
Nov 22 '18 at 15:11
I added some pictures to represent the dataset, i hope it helps!
– acronis011
Nov 22 '18 at 15:22
We can't copy/paste pictures into python :D
– user3471881
Nov 22 '18 at 15:32
1
Did you trypd.merge([df1, df2], how = 'inner', on = ['year', 'week']
?
– maow
Nov 22 '18 at 15:38
|
show 1 more comment
Welcome, I have a simple question, to which I haven't found a solution.
I have two dataframes df1
and df2
:
df1
contains several columns and a multiindex asyear-month-week
df2
contains the multiindexyear-week
with only one column in the df.
I would like to create an inner join
of df1
and df2
, joining on 'year'
and 'week'
.
I have tried to do the following:
df1['newcol'] = df1.index.get_level_values(2).map(lambda x: df2.newcol[x])
Which only joins on month (or year?), is there any way to expand it so that the merge is actually right?
Thanks in advance!
df1
df2
python pandas dataframe
Welcome, I have a simple question, to which I haven't found a solution.
I have two dataframes df1
and df2
:
df1
contains several columns and a multiindex asyear-month-week
df2
contains the multiindexyear-week
with only one column in the df.
I would like to create an inner join
of df1
and df2
, joining on 'year'
and 'week'
.
I have tried to do the following:
df1['newcol'] = df1.index.get_level_values(2).map(lambda x: df2.newcol[x])
Which only joins on month (or year?), is there any way to expand it so that the merge is actually right?
Thanks in advance!
df1
df2
python pandas dataframe
python pandas dataframe
edited Nov 22 '18 at 15:20
acronis011
asked Nov 22 '18 at 15:09
acronis011acronis011
83
83
2
Can you provide a sample dataframe via a Minimal, Complete, and Verifiable example.
– jpp
Nov 22 '18 at 15:10
2
Show us some sample of the datasets. Refer to the guide on how to add code snippets.
– Shiv_90
Nov 22 '18 at 15:11
I added some pictures to represent the dataset, i hope it helps!
– acronis011
Nov 22 '18 at 15:22
We can't copy/paste pictures into python :D
– user3471881
Nov 22 '18 at 15:32
1
Did you trypd.merge([df1, df2], how = 'inner', on = ['year', 'week']
?
– maow
Nov 22 '18 at 15:38
|
show 1 more comment
2
Can you provide a sample dataframe via a Minimal, Complete, and Verifiable example.
– jpp
Nov 22 '18 at 15:10
2
Show us some sample of the datasets. Refer to the guide on how to add code snippets.
– Shiv_90
Nov 22 '18 at 15:11
I added some pictures to represent the dataset, i hope it helps!
– acronis011
Nov 22 '18 at 15:22
We can't copy/paste pictures into python :D
– user3471881
Nov 22 '18 at 15:32
1
Did you trypd.merge([df1, df2], how = 'inner', on = ['year', 'week']
?
– maow
Nov 22 '18 at 15:38
2
2
Can you provide a sample dataframe via a Minimal, Complete, and Verifiable example.
– jpp
Nov 22 '18 at 15:10
Can you provide a sample dataframe via a Minimal, Complete, and Verifiable example.
– jpp
Nov 22 '18 at 15:10
2
2
Show us some sample of the datasets. Refer to the guide on how to add code snippets.
– Shiv_90
Nov 22 '18 at 15:11
Show us some sample of the datasets. Refer to the guide on how to add code snippets.
– Shiv_90
Nov 22 '18 at 15:11
I added some pictures to represent the dataset, i hope it helps!
– acronis011
Nov 22 '18 at 15:22
I added some pictures to represent the dataset, i hope it helps!
– acronis011
Nov 22 '18 at 15:22
We can't copy/paste pictures into python :D
– user3471881
Nov 22 '18 at 15:32
We can't copy/paste pictures into python :D
– user3471881
Nov 22 '18 at 15:32
1
1
Did you try
pd.merge([df1, df2], how = 'inner', on = ['year', 'week']
?– maow
Nov 22 '18 at 15:38
Did you try
pd.merge([df1, df2], how = 'inner', on = ['year', 'week']
?– maow
Nov 22 '18 at 15:38
|
show 1 more comment
1 Answer
1
active
oldest
votes
Eventually i solved with with removing the multiindex and doing a good old inner join on the two columns and then recreating the multiindex at the end.
Here are the sniplets:
df=df.reset_index()
df2=df2.reset_index()
df['year']=df['year'].apply(int)
df2['year']=df2['year'].apply(int)
df['week']=df['week'].apply(int)
df2['week']=df2['week'].apply(int)
result = pd.merge(df, df2, how='left', left_on= ['year','week'],right_on= ['year','week'])
result=result.set_index(['year', 'month','week','day'])
Since flattening index is not that intuitive for many, I'd suggest that you could add the actual code that you used, so that others could benefit from your experience ;) stackoverflow.blog/2011/07/01/…
– leoburgy
Nov 22 '18 at 16:08
add a comment |
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1 Answer
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active
oldest
votes
1 Answer
1
active
oldest
votes
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oldest
votes
active
oldest
votes
Eventually i solved with with removing the multiindex and doing a good old inner join on the two columns and then recreating the multiindex at the end.
Here are the sniplets:
df=df.reset_index()
df2=df2.reset_index()
df['year']=df['year'].apply(int)
df2['year']=df2['year'].apply(int)
df['week']=df['week'].apply(int)
df2['week']=df2['week'].apply(int)
result = pd.merge(df, df2, how='left', left_on= ['year','week'],right_on= ['year','week'])
result=result.set_index(['year', 'month','week','day'])
Since flattening index is not that intuitive for many, I'd suggest that you could add the actual code that you used, so that others could benefit from your experience ;) stackoverflow.blog/2011/07/01/…
– leoburgy
Nov 22 '18 at 16:08
add a comment |
Eventually i solved with with removing the multiindex and doing a good old inner join on the two columns and then recreating the multiindex at the end.
Here are the sniplets:
df=df.reset_index()
df2=df2.reset_index()
df['year']=df['year'].apply(int)
df2['year']=df2['year'].apply(int)
df['week']=df['week'].apply(int)
df2['week']=df2['week'].apply(int)
result = pd.merge(df, df2, how='left', left_on= ['year','week'],right_on= ['year','week'])
result=result.set_index(['year', 'month','week','day'])
Since flattening index is not that intuitive for many, I'd suggest that you could add the actual code that you used, so that others could benefit from your experience ;) stackoverflow.blog/2011/07/01/…
– leoburgy
Nov 22 '18 at 16:08
add a comment |
Eventually i solved with with removing the multiindex and doing a good old inner join on the two columns and then recreating the multiindex at the end.
Here are the sniplets:
df=df.reset_index()
df2=df2.reset_index()
df['year']=df['year'].apply(int)
df2['year']=df2['year'].apply(int)
df['week']=df['week'].apply(int)
df2['week']=df2['week'].apply(int)
result = pd.merge(df, df2, how='left', left_on= ['year','week'],right_on= ['year','week'])
result=result.set_index(['year', 'month','week','day'])
Eventually i solved with with removing the multiindex and doing a good old inner join on the two columns and then recreating the multiindex at the end.
Here are the sniplets:
df=df.reset_index()
df2=df2.reset_index()
df['year']=df['year'].apply(int)
df2['year']=df2['year'].apply(int)
df['week']=df['week'].apply(int)
df2['week']=df2['week'].apply(int)
result = pd.merge(df, df2, how='left', left_on= ['year','week'],right_on= ['year','week'])
result=result.set_index(['year', 'month','week','day'])
edited Nov 22 '18 at 16:20
answered Nov 22 '18 at 15:51
acronis011acronis011
83
83
Since flattening index is not that intuitive for many, I'd suggest that you could add the actual code that you used, so that others could benefit from your experience ;) stackoverflow.blog/2011/07/01/…
– leoburgy
Nov 22 '18 at 16:08
add a comment |
Since flattening index is not that intuitive for many, I'd suggest that you could add the actual code that you used, so that others could benefit from your experience ;) stackoverflow.blog/2011/07/01/…
– leoburgy
Nov 22 '18 at 16:08
Since flattening index is not that intuitive for many, I'd suggest that you could add the actual code that you used, so that others could benefit from your experience ;) stackoverflow.blog/2011/07/01/…
– leoburgy
Nov 22 '18 at 16:08
Since flattening index is not that intuitive for many, I'd suggest that you could add the actual code that you used, so that others could benefit from your experience ;) stackoverflow.blog/2011/07/01/…
– leoburgy
Nov 22 '18 at 16:08
add a comment |
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2
Can you provide a sample dataframe via a Minimal, Complete, and Verifiable example.
– jpp
Nov 22 '18 at 15:10
2
Show us some sample of the datasets. Refer to the guide on how to add code snippets.
– Shiv_90
Nov 22 '18 at 15:11
I added some pictures to represent the dataset, i hope it helps!
– acronis011
Nov 22 '18 at 15:22
We can't copy/paste pictures into python :D
– user3471881
Nov 22 '18 at 15:32
1
Did you try
pd.merge([df1, df2], how = 'inner', on = ['year', 'week']
?– maow
Nov 22 '18 at 15:38