How to fix the order of columns in dict
I have a series which I grouped and now I want to save that series as csv file with both index and values as two columns(Index followed by values).
So I first tried to covert the series as dataframe and then save the data frame as csv.
s_group_count=df_page_concat.groupby(df_page_concat).count()
df_grouped_values=pd.DataFrame({"page_path":s_group_count.index,"count":s_group_count.values})
Problem is since it is using dict to create a dataframe and that dicts are not ordered, it is adding the count which is the value of series as the first column in dataframe while I want the Index as first column and values (count) as second column.
Any advise how to fix the order and if this is the most optimal way to create a csv out of series with index stored as another column?
python pandas
asked Nov 14 '18 at 18:24
BaktaawarBaktaawar
1,74493165
add a comment |
I have a series which I grouped and now I want to save that series as csv file with both index and values as two columns(Index followed by values).
So I first tried to covert the series as dataframe and then save the data frame as csv.
s_group_count=df_page_concat.groupby(df_page_concat).count()
df_grouped_values=pd.DataFrame({"page_path":s_group_count.index,"count":s_group_count.values})
Problem is since it is using dict to create a dataframe and that dicts are not ordered, it is adding the count which is the value of series as the first column in dataframe while I want the Index as first column and values (count) as second column.
Any advise how to fix the order and if this is the most optimal way to create a csv out of series with index stored as another column?
python pandas
asked Nov 14 '18 at 18:24
BaktaawarBaktaawar
1,74493165
Not sure I understand. Why I would covert the dataframe to dict when I am converting a dict to dataframe and then to csv?
– Baktaawar
Nov 14 '18 at 18:27
1
You can reorder your columns withdf=df[['Col1','Col2','Col3']]etc
– G. Anderson
Nov 14 '18 at 18:30
Why not useOrderedDict?
– l'L'l
Nov 14 '18 at 18:32
OrderedDict sa in
– Baktaawar
Nov 14 '18 at 18:44
add a comment |
I have a series which I grouped and now I want to save that series as csv file with both index and values as two columns(Index followed by values).
So I first tried to covert the series as dataframe and then save the data frame as csv.
s_group_count=df_page_concat.groupby(df_page_concat).count()
df_grouped_values=pd.DataFrame({"page_path":s_group_count.index,"count":s_group_count.values})
Problem is since it is using dict to create a dataframe and that dicts are not ordered, it is adding the count which is the value of series as the first column in dataframe while I want the Index as first column and values (count) as second column.
Any advise how to fix the order and if this is the most optimal way to create a csv out of series with index stored as another column?
python pandas
asked Nov 14 '18 at 18:24
BaktaawarBaktaawar
1,74493165
I have a series which I grouped and now I want to save that series as csv file with both index and values as two columns(Index followed by values).
So I first tried to covert the series as dataframe and then save the data frame as csv.
s_group_count=df_page_concat.groupby(df_page_concat).count()
df_grouped_values=pd.DataFrame({"page_path":s_group_count.index,"count":s_group_count.values})
Problem is since it is using dict to create a dataframe and that dicts are not ordered, it is adding the count which is the value of series as the first column in dataframe while I want the Index as first column and values (count) as second column.
Any advise how to fix the order and if this is the most optimal way to create a csv out of series with index stored as another column?
python pandas
python pandas
asked Nov 14 '18 at 18:24
BaktaawarBaktaawar
1,74493165
asked Nov 14 '18 at 18:24
BaktaawarBaktaawar
1,74493165
asked Nov 14 '18 at 18:24
BaktaawarBaktaawar
1,74493165
asked Nov 14 '18 at 18:24
BaktaawarBaktaawar
1,74493165
asked Nov 14 '18 at 18:24
BaktaawarBaktaawar
1,74493165
1,74493165
Not sure I understand. Why I would covert the dataframe to dict when I am converting a dict to dataframe and then to csv?
– Baktaawar
Nov 14 '18 at 18:27
1
You can reorder your columns withdf=df[['Col1','Col2','Col3']]etc
– G. Anderson
Nov 14 '18 at 18:30
Why not useOrderedDict?
– l'L'l
Nov 14 '18 at 18:32
OrderedDict sa in
– Baktaawar
Nov 14 '18 at 18:44
add a comment |
Not sure I understand. Why I would covert the dataframe to dict when I am converting a dict to dataframe and then to csv?
– Baktaawar
Nov 14 '18 at 18:27
1
You can reorder your columns withdf=df[['Col1','Col2','Col3']]etc
– G. Anderson
Nov 14 '18 at 18:30
Why not useOrderedDict?
– l'L'l
Nov 14 '18 at 18:32
OrderedDict sa in
– Baktaawar
Nov 14 '18 at 18:44
Not sure I understand. Why I would covert the dataframe to dict when I am converting a dict to dataframe and then to csv?
– Baktaawar
Nov 14 '18 at 18:27
Not sure I understand. Why I would covert the dataframe to dict when I am converting a dict to dataframe and then to csv?
– Baktaawar
Nov 14 '18 at 18:27
1
1
You can reorder your columns with
df=df[['Col1','Col2','Col3']] etc– G. Anderson
Nov 14 '18 at 18:30
You can reorder your columns with
df=df[['Col1','Col2','Col3']] etc– G. Anderson
Nov 14 '18 at 18:30
Why not use
OrderedDict?– l'L'l
Nov 14 '18 at 18:32
Why not use
OrderedDict?– l'L'l
Nov 14 '18 at 18:32
OrderedDict sa in
– Baktaawar
Nov 14 '18 at 18:44
OrderedDict sa in
– Baktaawar
Nov 14 '18 at 18:44
add a comment |
1 Answer
1
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oldest
votes
from collections import OrderedDict
This has been particularly helpful for me in groupby.agg operations, to enforce column order
So pass in
OrderedDict([("page_path",s_group_count.index),("count",s_group_count.values)])
answered Nov 14 '18 at 18:47
spinodalspinodal
502410
add a comment |
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1 Answer
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1 Answer
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active
oldest
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oldest
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from collections import OrderedDict
This has been particularly helpful for me in groupby.agg operations, to enforce column order
So pass in
OrderedDict([("page_path",s_group_count.index),("count",s_group_count.values)])
answered Nov 14 '18 at 18:47
spinodalspinodal
502410
add a comment |
from collections import OrderedDict
This has been particularly helpful for me in groupby.agg operations, to enforce column order
So pass in
OrderedDict([("page_path",s_group_count.index),("count",s_group_count.values)])
answered Nov 14 '18 at 18:47
spinodalspinodal
502410
add a comment |
from collections import OrderedDict
This has been particularly helpful for me in groupby.agg operations, to enforce column order
So pass in
OrderedDict([("page_path",s_group_count.index),("count",s_group_count.values)])
answered Nov 14 '18 at 18:47
spinodalspinodal
502410
from collections import OrderedDict
This has been particularly helpful for me in groupby.agg operations, to enforce column order
So pass in
OrderedDict([("page_path",s_group_count.index),("count",s_group_count.values)])
answered Nov 14 '18 at 18:47
spinodalspinodal
502410
answered Nov 14 '18 at 18:47
spinodalspinodal
502410
answered Nov 14 '18 at 18:47
spinodalspinodal
502410
answered Nov 14 '18 at 18:47
spinodalspinodal
502410
502410
add a comment |
add a comment |
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Not sure I understand. Why I would covert the dataframe to dict when I am converting a dict to dataframe and then to csv?
– Baktaawar
Nov 14 '18 at 18:27
1
You can reorder your columns with
df=df[['Col1','Col2','Col3']]etc– G. Anderson
Nov 14 '18 at 18:30
Why not use
OrderedDict?– l'L'l
Nov 14 '18 at 18:32
OrderedDict sa in
– Baktaawar
Nov 14 '18 at 18:44