Pandas: issues with groupby. Error: 'ValueError: Grouper for not 1-dimensional'
I've been looking for this error here, but I only found this solution 1 (which doesn't work in my case). Does anybody can guide me on how to solve it?.
My dataset (df2) looks like this:
id_cl id_sup total_t cl_ind cl_city sup_ind sup_city same_city
0 1000135 1797029 414.85 I5610 11308.0 G4711 10901.0 no
1 1000135 1798069 19.76 I5610 11308.0 G4719 10901.0 no
2 1000135 1923186 302.73 I5610 11308.0 G4630 10901.0 no
3 1000135 2502927 1262.86 I5610 11308.0 G4630 11308.0 yes
4 1000135 2504288 155.04 I5610 11308.0 G4711 11308.0 yes
I need to group this dataset as follows:
df_sup = df2.groupby(['cl_city','cl_ind','same_city']).agg({'id_sup':'nunique', 'total_t':'sum'})
But when performing this, I'm getting this error!:
ValueError: Grouper for 'cl_city' not 1-dimensional
As a result I need something like this:
id_sup total_t
cl_city cl_ind same_city
10701 A0112 no 2 21964.22
yes 31 3530.40
A0122 no 2374 23328061.47
yes 1228 2684408.12
A0127 no 11 19962.68
yes 7 915.44
A0163 no 357 574827.97
yes 140 60385.7
python pandas
asked Nov 21 '18 at 22:37
PAstudilloEPAstudilloE
142111
|
show 5 more comments
I've been looking for this error here, but I only found this solution 1 (which doesn't work in my case). Does anybody can guide me on how to solve it?.
My dataset (df2) looks like this:
id_cl id_sup total_t cl_ind cl_city sup_ind sup_city same_city
0 1000135 1797029 414.85 I5610 11308.0 G4711 10901.0 no
1 1000135 1798069 19.76 I5610 11308.0 G4719 10901.0 no
2 1000135 1923186 302.73 I5610 11308.0 G4630 10901.0 no
3 1000135 2502927 1262.86 I5610 11308.0 G4630 11308.0 yes
4 1000135 2504288 155.04 I5610 11308.0 G4711 11308.0 yes
I need to group this dataset as follows:
df_sup = df2.groupby(['cl_city','cl_ind','same_city']).agg({'id_sup':'nunique', 'total_t':'sum'})
But when performing this, I'm getting this error!:
ValueError: Grouper for 'cl_city' not 1-dimensional
As a result I need something like this:
id_sup total_t
cl_city cl_ind same_city
10701 A0112 no 2 21964.22
yes 31 3530.40
A0122 no 2374 23328061.47
yes 1228 2684408.12
A0127 no 11 19962.68
yes 7 915.44
A0163 no 357 574827.97
yes 140 60385.7
python pandas
asked Nov 21 '18 at 22:37
PAstudilloEPAstudilloE
142111
What is the output ofdf2.columns?
– Peter Leimbigler
Nov 21 '18 at 22:47
as an output I need to know: how many unique 'id_sup' and the sum of 'total_t' of every item of cl_city, cl_ind and same_city. Basically a table with columns: cl_city | cl_ind | same_city | count of unique id_sup | sum of total_T
– PAstudilloE
Nov 21 '18 at 22:54
Possible duplicate of stackoverflow.com/questions/43298192/…
– Kevin Fang
Nov 21 '18 at 22:58
1
@PAstudilloE, thanks! This does reveal the immediate cause of the error: for some terrible reason, the columns ofdf2are a highly nested MultiIndex, where instead of each string being a label, each string is actually the name of a separate *index level*(!) The fix for this comes from stackoverflow.com/q/14507794, and is this:df.columns = [' '.join(col).strip() for col in df.columns.values]. You mentioneddf2is the result of many merges; I suspect those merges are not written optimally, leading to this pathological MultiIndex situation.
– Peter Leimbigler
Nov 21 '18 at 23:21
1
Thanks @PeterLeimbigler!! That's exactly what happened. I solved the issue as you recommended.
– PAstudilloE
Nov 21 '18 at 23:26
|
show 5 more comments
I've been looking for this error here, but I only found this solution 1 (which doesn't work in my case). Does anybody can guide me on how to solve it?.
My dataset (df2) looks like this:
id_cl id_sup total_t cl_ind cl_city sup_ind sup_city same_city
0 1000135 1797029 414.85 I5610 11308.0 G4711 10901.0 no
1 1000135 1798069 19.76 I5610 11308.0 G4719 10901.0 no
2 1000135 1923186 302.73 I5610 11308.0 G4630 10901.0 no
3 1000135 2502927 1262.86 I5610 11308.0 G4630 11308.0 yes
4 1000135 2504288 155.04 I5610 11308.0 G4711 11308.0 yes
I need to group this dataset as follows:
df_sup = df2.groupby(['cl_city','cl_ind','same_city']).agg({'id_sup':'nunique', 'total_t':'sum'})
But when performing this, I'm getting this error!:
ValueError: Grouper for 'cl_city' not 1-dimensional
As a result I need something like this:
id_sup total_t
cl_city cl_ind same_city
10701 A0112 no 2 21964.22
yes 31 3530.40
A0122 no 2374 23328061.47
yes 1228 2684408.12
A0127 no 11 19962.68
yes 7 915.44
A0163 no 357 574827.97
yes 140 60385.7
python pandas
asked Nov 21 '18 at 22:37
PAstudilloEPAstudilloE
142111
I've been looking for this error here, but I only found this solution 1 (which doesn't work in my case). Does anybody can guide me on how to solve it?.
My dataset (df2) looks like this:
id_cl id_sup total_t cl_ind cl_city sup_ind sup_city same_city
0 1000135 1797029 414.85 I5610 11308.0 G4711 10901.0 no
1 1000135 1798069 19.76 I5610 11308.0 G4719 10901.0 no
2 1000135 1923186 302.73 I5610 11308.0 G4630 10901.0 no
3 1000135 2502927 1262.86 I5610 11308.0 G4630 11308.0 yes
4 1000135 2504288 155.04 I5610 11308.0 G4711 11308.0 yes
I need to group this dataset as follows:
df_sup = df2.groupby(['cl_city','cl_ind','same_city']).agg({'id_sup':'nunique', 'total_t':'sum'})
But when performing this, I'm getting this error!:
ValueError: Grouper for 'cl_city' not 1-dimensional
As a result I need something like this:
id_sup total_t
cl_city cl_ind same_city
10701 A0112 no 2 21964.22
yes 31 3530.40
A0122 no 2374 23328061.47
yes 1228 2684408.12
A0127 no 11 19962.68
yes 7 915.44
A0163 no 357 574827.97
yes 140 60385.7
python pandas
python pandas
asked Nov 21 '18 at 22:37
PAstudilloEPAstudilloE
142111
asked Nov 21 '18 at 22:37
PAstudilloEPAstudilloE
142111
edited Nov 21 '18 at 23:03
PAstudilloE
asked Nov 21 '18 at 22:37
PAstudilloEPAstudilloE
142111
asked Nov 21 '18 at 22:37
PAstudilloEPAstudilloE
142111
asked Nov 21 '18 at 22:37
PAstudilloEPAstudilloE
142111
142111
What is the output ofdf2.columns?
– Peter Leimbigler
Nov 21 '18 at 22:47
as an output I need to know: how many unique 'id_sup' and the sum of 'total_t' of every item of cl_city, cl_ind and same_city. Basically a table with columns: cl_city | cl_ind | same_city | count of unique id_sup | sum of total_T
– PAstudilloE
Nov 21 '18 at 22:54
Possible duplicate of stackoverflow.com/questions/43298192/…
– Kevin Fang
Nov 21 '18 at 22:58
1
@PAstudilloE, thanks! This does reveal the immediate cause of the error: for some terrible reason, the columns ofdf2are a highly nested MultiIndex, where instead of each string being a label, each string is actually the name of a separate *index level*(!) The fix for this comes from stackoverflow.com/q/14507794, and is this:df.columns = [' '.join(col).strip() for col in df.columns.values]. You mentioneddf2is the result of many merges; I suspect those merges are not written optimally, leading to this pathological MultiIndex situation.
– Peter Leimbigler
Nov 21 '18 at 23:21
1
Thanks @PeterLeimbigler!! That's exactly what happened. I solved the issue as you recommended.
– PAstudilloE
Nov 21 '18 at 23:26
|
show 5 more comments
What is the output ofdf2.columns?
– Peter Leimbigler
Nov 21 '18 at 22:47
as an output I need to know: how many unique 'id_sup' and the sum of 'total_t' of every item of cl_city, cl_ind and same_city. Basically a table with columns: cl_city | cl_ind | same_city | count of unique id_sup | sum of total_T
– PAstudilloE
Nov 21 '18 at 22:54
Possible duplicate of stackoverflow.com/questions/43298192/…
– Kevin Fang
Nov 21 '18 at 22:58
1
@PAstudilloE, thanks! This does reveal the immediate cause of the error: for some terrible reason, the columns ofdf2are a highly nested MultiIndex, where instead of each string being a label, each string is actually the name of a separate *index level*(!) The fix for this comes from stackoverflow.com/q/14507794, and is this:df.columns = [' '.join(col).strip() for col in df.columns.values]. You mentioneddf2is the result of many merges; I suspect those merges are not written optimally, leading to this pathological MultiIndex situation.
– Peter Leimbigler
Nov 21 '18 at 23:21
1
Thanks @PeterLeimbigler!! That's exactly what happened. I solved the issue as you recommended.
– PAstudilloE
Nov 21 '18 at 23:26
What is the output of
df2.columns?– Peter Leimbigler
Nov 21 '18 at 22:47
What is the output of
df2.columns?– Peter Leimbigler
Nov 21 '18 at 22:47
as an output I need to know: how many unique 'id_sup' and the sum of 'total_t' of every item of cl_city, cl_ind and same_city. Basically a table with columns: cl_city | cl_ind | same_city | count of unique id_sup | sum of total_T
– PAstudilloE
Nov 21 '18 at 22:54
as an output I need to know: how many unique 'id_sup' and the sum of 'total_t' of every item of cl_city, cl_ind and same_city. Basically a table with columns: cl_city | cl_ind | same_city | count of unique id_sup | sum of total_T
– PAstudilloE
Nov 21 '18 at 22:54
Possible duplicate of stackoverflow.com/questions/43298192/…
– Kevin Fang
Nov 21 '18 at 22:58
Possible duplicate of stackoverflow.com/questions/43298192/…
– Kevin Fang
Nov 21 '18 at 22:58
1
1
@PAstudilloE, thanks! This does reveal the immediate cause of the error: for some terrible reason, the columns of
df2 are a highly nested MultiIndex, where instead of each string being a label, each string is actually the name of a separate *index level*(!) The fix for this comes from stackoverflow.com/q/14507794, and is this: df.columns = [' '.join(col).strip() for col in df.columns.values]. You mentioned df2 is the result of many merges; I suspect those merges are not written optimally, leading to this pathological MultiIndex situation.– Peter Leimbigler
Nov 21 '18 at 23:21
@PAstudilloE, thanks! This does reveal the immediate cause of the error: for some terrible reason, the columns of
df2 are a highly nested MultiIndex, where instead of each string being a label, each string is actually the name of a separate *index level*(!) The fix for this comes from stackoverflow.com/q/14507794, and is this: df.columns = [' '.join(col).strip() for col in df.columns.values]. You mentioned df2 is the result of many merges; I suspect those merges are not written optimally, leading to this pathological MultiIndex situation.– Peter Leimbigler
Nov 21 '18 at 23:21
1
1
Thanks @PeterLeimbigler!! That's exactly what happened. I solved the issue as you recommended.
– PAstudilloE
Nov 21 '18 at 23:26
Thanks @PeterLeimbigler!! That's exactly what happened. I solved the issue as you recommended.
– PAstudilloE
Nov 21 '18 at 23:26
|
show 5 more comments
1 Answer
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I don't know why python is showing me that error, df2 is the result of merging several previous datasets and it does not have any duplicate columns.
I solve this issue in a silly way but it worked. I converted df2 to a CSV file and then I load it again. After that, everything is working fine. [But I can't figure out, why python is showing that error]. Hope it helps.
answered Nov 21 '18 at 23:09
PAstudilloEPAstudilloE
142111
add a comment |
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I don't know why python is showing me that error, df2 is the result of merging several previous datasets and it does not have any duplicate columns.
I solve this issue in a silly way but it worked. I converted df2 to a CSV file and then I load it again. After that, everything is working fine. [But I can't figure out, why python is showing that error]. Hope it helps.
answered Nov 21 '18 at 23:09
PAstudilloEPAstudilloE
142111
add a comment |
I don't know why python is showing me that error, df2 is the result of merging several previous datasets and it does not have any duplicate columns.
I solve this issue in a silly way but it worked. I converted df2 to a CSV file and then I load it again. After that, everything is working fine. [But I can't figure out, why python is showing that error]. Hope it helps.
answered Nov 21 '18 at 23:09
PAstudilloEPAstudilloE
142111
add a comment |
I don't know why python is showing me that error, df2 is the result of merging several previous datasets and it does not have any duplicate columns.
I solve this issue in a silly way but it worked. I converted df2 to a CSV file and then I load it again. After that, everything is working fine. [But I can't figure out, why python is showing that error]. Hope it helps.
answered Nov 21 '18 at 23:09
PAstudilloEPAstudilloE
142111
I don't know why python is showing me that error, df2 is the result of merging several previous datasets and it does not have any duplicate columns.
I solve this issue in a silly way but it worked. I converted df2 to a CSV file and then I load it again. After that, everything is working fine. [But I can't figure out, why python is showing that error]. Hope it helps.
answered Nov 21 '18 at 23:09
PAstudilloEPAstudilloE
142111
answered Nov 21 '18 at 23:09
PAstudilloEPAstudilloE
142111
answered Nov 21 '18 at 23:09
PAstudilloEPAstudilloE
142111
answered Nov 21 '18 at 23:09
PAstudilloEPAstudilloE
142111
142111
add a comment |
add a comment |
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What is the output of
df2.columns?– Peter Leimbigler
Nov 21 '18 at 22:47
as an output I need to know: how many unique 'id_sup' and the sum of 'total_t' of every item of cl_city, cl_ind and same_city. Basically a table with columns: cl_city | cl_ind | same_city | count of unique id_sup | sum of total_T
– PAstudilloE
Nov 21 '18 at 22:54
Possible duplicate of stackoverflow.com/questions/43298192/…
– Kevin Fang
Nov 21 '18 at 22:58
1
@PAstudilloE, thanks! This does reveal the immediate cause of the error: for some terrible reason, the columns of
df2are a highly nested MultiIndex, where instead of each string being a label, each string is actually the name of a separate *index level*(!) The fix for this comes from stackoverflow.com/q/14507794, and is this:df.columns = [' '.join(col).strip() for col in df.columns.values]. You mentioneddf2is the result of many merges; I suspect those merges are not written optimally, leading to this pathological MultiIndex situation.– Peter Leimbigler
Nov 21 '18 at 23:21
1
Thanks @PeterLeimbigler!! That's exactly what happened. I solved the issue as you recommended.
– PAstudilloE
Nov 21 '18 at 23:26