Change column name with a .0 in Pandas
1
I have a dataframe with columns as Country, 2015.0,2016.0,2017.0 these are suppose to be years. But the column name has .0 in it. I tried to rename them but rename is not working. I am not able to remove the .0 at the end.
Any suggestions.
pandas dataframe rename
asked Nov 12 '18 at 21:08
SAM244776
1456717
add a comment |
1
I have a dataframe with columns as Country, 2015.0,2016.0,2017.0 these are suppose to be years. But the column name has .0 in it. I tried to rename them but rename is not working. I am not able to remove the .0 at the end.
Any suggestions.
pandas dataframe rename
asked Nov 12 '18 at 21:08
SAM244776
1456717
dataframe.columns = ['Country', '2015', '2016', '2017']doesn't work?
– CJ59
Nov 12 '18 at 21:11
This will work but I have last 50 years of data, is there a better way to do it?
– SAM244776
Nov 12 '18 at 21:14
dflst = dataframe.columns.tolist()will get you a list of columns, you could do something likedflist.pop('Country'),dflst = ['Country'] + list(map(int, dflist))and then put them back withdataframe.columns = dflst. Just make sure your columns are lined up right afterwards.
– CJ59
Nov 12 '18 at 21:18
add a comment |
1
1
1
I have a dataframe with columns as Country, 2015.0,2016.0,2017.0 these are suppose to be years. But the column name has .0 in it. I tried to rename them but rename is not working. I am not able to remove the .0 at the end.
Any suggestions.
pandas dataframe rename
asked Nov 12 '18 at 21:08
SAM244776
1456717
I have a dataframe with columns as Country, 2015.0,2016.0,2017.0 these are suppose to be years. But the column name has .0 in it. I tried to rename them but rename is not working. I am not able to remove the .0 at the end.
Any suggestions.
pandas dataframe rename
pandas dataframe rename
asked Nov 12 '18 at 21:08
SAM244776
1456717
asked Nov 12 '18 at 21:08
SAM244776
1456717
asked Nov 12 '18 at 21:08
SAM244776
1456717
asked Nov 12 '18 at 21:08
SAM244776
1456717
asked Nov 12 '18 at 21:08
SAM244776
1456717
1456717
dataframe.columns = ['Country', '2015', '2016', '2017']doesn't work?
– CJ59
Nov 12 '18 at 21:11
This will work but I have last 50 years of data, is there a better way to do it?
– SAM244776
Nov 12 '18 at 21:14
dflst = dataframe.columns.tolist()will get you a list of columns, you could do something likedflist.pop('Country'),dflst = ['Country'] + list(map(int, dflist))and then put them back withdataframe.columns = dflst. Just make sure your columns are lined up right afterwards.
– CJ59
Nov 12 '18 at 21:18
add a comment |
dataframe.columns = ['Country', '2015', '2016', '2017']doesn't work?
– CJ59
Nov 12 '18 at 21:11
This will work but I have last 50 years of data, is there a better way to do it?
– SAM244776
Nov 12 '18 at 21:14
dflst = dataframe.columns.tolist()will get you a list of columns, you could do something likedflist.pop('Country'),dflst = ['Country'] + list(map(int, dflist))and then put them back withdataframe.columns = dflst. Just make sure your columns are lined up right afterwards.
– CJ59
Nov 12 '18 at 21:18
dataframe.columns = ['Country', '2015', '2016', '2017'] doesn't work?– CJ59
Nov 12 '18 at 21:11
dataframe.columns = ['Country', '2015', '2016', '2017'] doesn't work?– CJ59
Nov 12 '18 at 21:11
This will work but I have last 50 years of data, is there a better way to do it?
– SAM244776
Nov 12 '18 at 21:14
This will work but I have last 50 years of data, is there a better way to do it?
– SAM244776
Nov 12 '18 at 21:14
dflst = dataframe.columns.tolist() will get you a list of columns, you could do something like dflist.pop('Country'), dflst = ['Country'] + list(map(int, dflist)) and then put them back with dataframe.columns = dflst. Just make sure your columns are lined up right afterwards.– CJ59
Nov 12 '18 at 21:18
dflst = dataframe.columns.tolist() will get you a list of columns, you could do something like dflist.pop('Country'), dflst = ['Country'] + list(map(int, dflist)) and then put them back with dataframe.columns = dflst. Just make sure your columns are lined up right afterwards.– CJ59
Nov 12 '18 at 21:18
add a comment |
1 Answer
1
active
oldest
votes
4
rename
def f(x):
try:
return int(float(x))
except ValueError:
return x
df.rename(columns=f)
answered Nov 12 '18 at 21:11
piRSquared
152k22144286
add a comment |
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active
oldest
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oldest
votes
4
rename
def f(x):
try:
return int(float(x))
except ValueError:
return x
df.rename(columns=f)
answered Nov 12 '18 at 21:11
piRSquared
152k22144286
add a comment |
4
rename
def f(x):
try:
return int(float(x))
except ValueError:
return x
df.rename(columns=f)
answered Nov 12 '18 at 21:11
piRSquared
152k22144286
add a comment |
4
4
4
rename
def f(x):
try:
return int(float(x))
except ValueError:
return x
df.rename(columns=f)
answered Nov 12 '18 at 21:11
piRSquared
152k22144286
rename
def f(x):
try:
return int(float(x))
except ValueError:
return x
df.rename(columns=f)
answered Nov 12 '18 at 21:11
piRSquared
152k22144286
edited Nov 12 '18 at 21:17
answered Nov 12 '18 at 21:11
piRSquared
152k22144286
answered Nov 12 '18 at 21:11
piRSquared
152k22144286
answered Nov 12 '18 at 21:11
piRSquared
152k22144286
152k22144286
add a comment |
add a comment |
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dataframe.columns = ['Country', '2015', '2016', '2017']doesn't work?– CJ59
Nov 12 '18 at 21:11
This will work but I have last 50 years of data, is there a better way to do it?
– SAM244776
Nov 12 '18 at 21:14
dflst = dataframe.columns.tolist()will get you a list of columns, you could do something likedflist.pop('Country'),dflst = ['Country'] + list(map(int, dflist))and then put them back withdataframe.columns = dflst. Just make sure your columns are lined up right afterwards.– CJ59
Nov 12 '18 at 21:18