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Preferred pandas code for selecting all rows and a subset of columns
How to deal with SettingWithCopyWarning in Pandas?Python: Pandas Series - Why use loc?Selecting multiple columns in a pandas dataframeRenaming columns in pandasAdding new column to existing DataFrame in Python pandasDelete column from pandas DataFrame“Large data” work flows using pandasChange data type of columns in PandasHow to iterate over rows in a DataFrame in Pandas?Select rows from a DataFrame based on values in a column in pandasCombine two columns of text in dataframe in pandas/pythonHow to check if a column exists in Pandas
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Suppose that you have a pandas DataFrame named df with columns ['a','b','c','d','e'] and you want to create a new DataFrame newdf with columns 'b' and 'd'. There are two possible ways to do this:
newdf = df[['b','d']]
or
newdf = df.loc[:,['b','d']]
The first is using the indexing operator. The second is using .loc. Is there a reason to prefer one over the other?
pandas
asked Mar 25 at 20:40
IrvIrv
667 bronze badges
add a comment |
Suppose that you have a pandas DataFrame named df with columns ['a','b','c','d','e'] and you want to create a new DataFrame newdf with columns 'b' and 'd'. There are two possible ways to do this:
newdf = df[['b','d']]
or
newdf = df.loc[:,['b','d']]
The first is using the indexing operator. The second is using .loc. Is there a reason to prefer one over the other?
pandas
asked Mar 25 at 20:40
IrvIrv
667 bronze badges
stackoverflow.com/questions/38886080/…
– WeNYoBen
Mar 25 at 20:42
Depending on what you do with the slices once you obtain them, you might run into a SettingWithCopyWarning which might prevent you from being able to make updates depending on whether you're dealing with a view or copy.
– cs95
Mar 25 at 20:43
@coldspeed I think both operations produce a copy of the data, so you won't get that warning with operations onnewdf. (Note - I modified the code a little to be able to referencenewdf)
– Irv
Mar 25 at 21:07
v = df[['b']]; v['b'] = 3throwsSettingWithCopyWarning. The warning is raised on chained assignments, regardless of whether you have a view or copy. You don't have this issue withloc. That's my point.
– cs95
Mar 25 at 21:09
add a comment |
Suppose that you have a pandas DataFrame named df with columns ['a','b','c','d','e'] and you want to create a new DataFrame newdf with columns 'b' and 'd'. There are two possible ways to do this:
newdf = df[['b','d']]
or
newdf = df.loc[:,['b','d']]
The first is using the indexing operator. The second is using .loc. Is there a reason to prefer one over the other?
pandas
asked Mar 25 at 20:40
IrvIrv
667 bronze badges
Suppose that you have a pandas DataFrame named df with columns ['a','b','c','d','e'] and you want to create a new DataFrame newdf with columns 'b' and 'd'. There are two possible ways to do this:
newdf = df[['b','d']]
or
newdf = df.loc[:,['b','d']]
The first is using the indexing operator. The second is using .loc. Is there a reason to prefer one over the other?
pandas
pandas
asked Mar 25 at 20:40
IrvIrv
667 bronze badges
asked Mar 25 at 20:40
IrvIrv
667 bronze badges
edited Mar 25 at 21:06
Irv
asked Mar 25 at 20:40
IrvIrv
667 bronze badges
asked Mar 25 at 20:40
IrvIrv
667 bronze badges
asked Mar 25 at 20:40
IrvIrv
667 bronze badges
667 bronze badges
stackoverflow.com/questions/38886080/…
– WeNYoBen
Mar 25 at 20:42
Depending on what you do with the slices once you obtain them, you might run into a SettingWithCopyWarning which might prevent you from being able to make updates depending on whether you're dealing with a view or copy.
– cs95
Mar 25 at 20:43
@coldspeed I think both operations produce a copy of the data, so you won't get that warning with operations onnewdf. (Note - I modified the code a little to be able to referencenewdf)
– Irv
Mar 25 at 21:07
v = df[['b']]; v['b'] = 3throwsSettingWithCopyWarning. The warning is raised on chained assignments, regardless of whether you have a view or copy. You don't have this issue withloc. That's my point.
– cs95
Mar 25 at 21:09
add a comment |
stackoverflow.com/questions/38886080/…
– WeNYoBen
Mar 25 at 20:42
Depending on what you do with the slices once you obtain them, you might run into a SettingWithCopyWarning which might prevent you from being able to make updates depending on whether you're dealing with a view or copy.
– cs95
Mar 25 at 20:43
@coldspeed I think both operations produce a copy of the data, so you won't get that warning with operations onnewdf. (Note - I modified the code a little to be able to referencenewdf)
– Irv
Mar 25 at 21:07
v = df[['b']]; v['b'] = 3throwsSettingWithCopyWarning. The warning is raised on chained assignments, regardless of whether you have a view or copy. You don't have this issue withloc. That's my point.
– cs95
Mar 25 at 21:09
stackoverflow.com/questions/38886080/…
– WeNYoBen
Mar 25 at 20:42
stackoverflow.com/questions/38886080/…
– WeNYoBen
Mar 25 at 20:42
Depending on what you do with the slices once you obtain them, you might run into a SettingWithCopyWarning which might prevent you from being able to make updates depending on whether you're dealing with a view or copy.
– cs95
Mar 25 at 20:43
Depending on what you do with the slices once you obtain them, you might run into a SettingWithCopyWarning which might prevent you from being able to make updates depending on whether you're dealing with a view or copy.
– cs95
Mar 25 at 20:43
@coldspeed I think both operations produce a copy of the data, so you won't get that warning with operations on
newdf. (Note - I modified the code a little to be able to reference newdf)– Irv
Mar 25 at 21:07
@coldspeed I think both operations produce a copy of the data, so you won't get that warning with operations on
newdf. (Note - I modified the code a little to be able to reference newdf)– Irv
Mar 25 at 21:07
v = df[['b']]; v['b'] = 3 throws SettingWithCopyWarning. The warning is raised on chained assignments, regardless of whether you have a view or copy. You don't have this issue with loc. That's my point.– cs95
Mar 25 at 21:09
v = df[['b']]; v['b'] = 3 throws SettingWithCopyWarning. The warning is raised on chained assignments, regardless of whether you have a view or copy. You don't have this issue with loc. That's my point.– cs95
Mar 25 at 21:09
add a comment |
1 Answer
1
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Thanks to @coldspeed, it seems that newdf = df.loc[:,['b','d']] is preferred to avoid the dreaded SettingWithCopyWarning.
answered Mar 25 at 22:13
IrvIrv
667 bronze badges
add a comment |
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Thanks to @coldspeed, it seems that newdf = df.loc[:,['b','d']] is preferred to avoid the dreaded SettingWithCopyWarning.
answered Mar 25 at 22:13
IrvIrv
667 bronze badges
add a comment |
Thanks to @coldspeed, it seems that newdf = df.loc[:,['b','d']] is preferred to avoid the dreaded SettingWithCopyWarning.
answered Mar 25 at 22:13
IrvIrv
667 bronze badges
add a comment |
Thanks to @coldspeed, it seems that newdf = df.loc[:,['b','d']] is preferred to avoid the dreaded SettingWithCopyWarning.
answered Mar 25 at 22:13
IrvIrv
667 bronze badges
Thanks to @coldspeed, it seems that newdf = df.loc[:,['b','d']] is preferred to avoid the dreaded SettingWithCopyWarning.
answered Mar 25 at 22:13
IrvIrv
667 bronze badges
answered Mar 25 at 22:13
IrvIrv
667 bronze badges
answered Mar 25 at 22:13
IrvIrv
667 bronze badges
answered Mar 25 at 22:13
IrvIrv
667 bronze badges
667 bronze badges
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stackoverflow.com/questions/38886080/…
– WeNYoBen
Mar 25 at 20:42
Depending on what you do with the slices once you obtain them, you might run into a SettingWithCopyWarning which might prevent you from being able to make updates depending on whether you're dealing with a view or copy.
– cs95
Mar 25 at 20:43
@coldspeed I think both operations produce a copy of the data, so you won't get that warning with operations on
newdf. (Note - I modified the code a little to be able to referencenewdf)– Irv
Mar 25 at 21:07
v = df[['b']]; v['b'] = 3throwsSettingWithCopyWarning. The warning is raised on chained assignments, regardless of whether you have a view or copy. You don't have this issue withloc. That's my point.– cs95
Mar 25 at 21:09