Python, pandas: how to sort dataframe by index
55
When there is an DataFrame like the following:
import pandas as pd
df = pd.DataFrame([1, 1, 1, 1, 1], index=[100, 29, 234, 1, 150], columns=['A'])
How can I sort this dataframe by index with each combination of index and column value intact?
python pandas
edited Mar 5 '14 at 23:42
Paul H
31k9101110
asked Mar 5 '14 at 23:35
midtowngurumidtownguru
7412919
add a comment |
55
When there is an DataFrame like the following:
import pandas as pd
df = pd.DataFrame([1, 1, 1, 1, 1], index=[100, 29, 234, 1, 150], columns=['A'])
How can I sort this dataframe by index with each combination of index and column value intact?
python pandas
edited Mar 5 '14 at 23:42
Paul H
31k9101110
asked Mar 5 '14 at 23:35
midtowngurumidtownguru
7412919
add a comment |
55
55
55
4
When there is an DataFrame like the following:
import pandas as pd
df = pd.DataFrame([1, 1, 1, 1, 1], index=[100, 29, 234, 1, 150], columns=['A'])
How can I sort this dataframe by index with each combination of index and column value intact?
python pandas
edited Mar 5 '14 at 23:42
Paul H
31k9101110
asked Mar 5 '14 at 23:35
midtowngurumidtownguru
7412919
When there is an DataFrame like the following:
import pandas as pd
df = pd.DataFrame([1, 1, 1, 1, 1], index=[100, 29, 234, 1, 150], columns=['A'])
How can I sort this dataframe by index with each combination of index and column value intact?
python pandas
python pandas
edited Mar 5 '14 at 23:42
Paul H
31k9101110
asked Mar 5 '14 at 23:35
midtowngurumidtownguru
7412919
edited Mar 5 '14 at 23:42
Paul H
31k9101110
asked Mar 5 '14 at 23:35
midtowngurumidtownguru
7412919
edited Mar 5 '14 at 23:42
Paul H
31k9101110
edited Mar 5 '14 at 23:42
Paul H
31k9101110
edited Mar 5 '14 at 23:42
Paul H
31k9101110
31k9101110
asked Mar 5 '14 at 23:35
midtowngurumidtownguru
7412919
asked Mar 5 '14 at 23:35
midtowngurumidtownguru
7412919
asked Mar 5 '14 at 23:35
midtowngurumidtownguru
7412919
7412919
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
90
Dataframes have a sort_index method which returns a copy by default. Pass inplace=True to operate in place.
import pandas as pd
df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150], columns=['A'])
df.sort_index(inplace=True)
print(df.to_string())
Gives me:
A
1 4
29 2
100 1
150 5
234 3
answered Mar 5 '14 at 23:41
Paul HPaul H
31k9101110
Thanks! It works!
– midtownguru
Mar 5 '14 at 23:43
add a comment |
8
Slightly more compact:
df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150], columns=['A'])
df = df.sort()
print(df)
Note:
- the standard
sortwill do the same thing as sort_index if a sort column isn't specified. - preferable not to use
inplaceas it is usually harder to read and prevents chaining. See the answer here:
Pandas: peculiar performance drop for inplace rename after dropna
Edit sort has now been deprecated leaving sort_index as the replacement for this scenario.
edited May 23 '17 at 11:46
Community♦
11
answered Jul 20 '14 at 2:14
fantabolousfantabolous
8,04032837
6
.sort()docstring saysDEPRECATED: use DataFrame.sort_values()
– endolith
Jul 3 '16 at 17:47
1
@endolith Indeed.sort()has since been deprecated. The replacement would be.sort_index()as Paul H uses in his answer, in which case the only difference between our answers is I don't useinplace=True.
– fantabolous
Jan 16 '17 at 23:52
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
90
Dataframes have a sort_index method which returns a copy by default. Pass inplace=True to operate in place.
import pandas as pd
df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150], columns=['A'])
df.sort_index(inplace=True)
print(df.to_string())
Gives me:
A
1 4
29 2
100 1
150 5
234 3
answered Mar 5 '14 at 23:41
Paul HPaul H
31k9101110
Thanks! It works!
– midtownguru
Mar 5 '14 at 23:43
add a comment |
90
Dataframes have a sort_index method which returns a copy by default. Pass inplace=True to operate in place.
import pandas as pd
df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150], columns=['A'])
df.sort_index(inplace=True)
print(df.to_string())
Gives me:
A
1 4
29 2
100 1
150 5
234 3
answered Mar 5 '14 at 23:41
Paul HPaul H
31k9101110
Thanks! It works!
– midtownguru
Mar 5 '14 at 23:43
add a comment |
90
90
90
Dataframes have a sort_index method which returns a copy by default. Pass inplace=True to operate in place.
import pandas as pd
df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150], columns=['A'])
df.sort_index(inplace=True)
print(df.to_string())
Gives me:
A
1 4
29 2
100 1
150 5
234 3
answered Mar 5 '14 at 23:41
Paul HPaul H
31k9101110
Dataframes have a sort_index method which returns a copy by default. Pass inplace=True to operate in place.
import pandas as pd
df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150], columns=['A'])
df.sort_index(inplace=True)
print(df.to_string())
Gives me:
A
1 4
29 2
100 1
150 5
234 3
answered Mar 5 '14 at 23:41
Paul HPaul H
31k9101110
answered Mar 5 '14 at 23:41
Paul HPaul H
31k9101110
answered Mar 5 '14 at 23:41
Paul HPaul H
31k9101110
answered Mar 5 '14 at 23:41
Paul HPaul H
31k9101110
31k9101110
Thanks! It works!
– midtownguru
Mar 5 '14 at 23:43
add a comment |
Thanks! It works!
– midtownguru
Mar 5 '14 at 23:43
Thanks! It works!
– midtownguru
Mar 5 '14 at 23:43
Thanks! It works!
– midtownguru
Mar 5 '14 at 23:43
add a comment |
8
Slightly more compact:
df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150], columns=['A'])
df = df.sort()
print(df)
Note:
- the standard
sortwill do the same thing as sort_index if a sort column isn't specified. - preferable not to use
inplaceas it is usually harder to read and prevents chaining. See the answer here:
Pandas: peculiar performance drop for inplace rename after dropna
Edit sort has now been deprecated leaving sort_index as the replacement for this scenario.
edited May 23 '17 at 11:46
Community♦
11
answered Jul 20 '14 at 2:14
fantabolousfantabolous
8,04032837
6
.sort()docstring saysDEPRECATED: use DataFrame.sort_values()
– endolith
Jul 3 '16 at 17:47
1
@endolith Indeed.sort()has since been deprecated. The replacement would be.sort_index()as Paul H uses in his answer, in which case the only difference between our answers is I don't useinplace=True.
– fantabolous
Jan 16 '17 at 23:52
add a comment |
8
Slightly more compact:
df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150], columns=['A'])
df = df.sort()
print(df)
Note:
- the standard
sortwill do the same thing as sort_index if a sort column isn't specified. - preferable not to use
inplaceas it is usually harder to read and prevents chaining. See the answer here:
Pandas: peculiar performance drop for inplace rename after dropna
Edit sort has now been deprecated leaving sort_index as the replacement for this scenario.
edited May 23 '17 at 11:46
Community♦
11
answered Jul 20 '14 at 2:14
fantabolousfantabolous
8,04032837
6
.sort()docstring saysDEPRECATED: use DataFrame.sort_values()
– endolith
Jul 3 '16 at 17:47
1
@endolith Indeed.sort()has since been deprecated. The replacement would be.sort_index()as Paul H uses in his answer, in which case the only difference between our answers is I don't useinplace=True.
– fantabolous
Jan 16 '17 at 23:52
add a comment |
8
8
8
Slightly more compact:
df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150], columns=['A'])
df = df.sort()
print(df)
Note:
- the standard
sortwill do the same thing as sort_index if a sort column isn't specified. - preferable not to use
inplaceas it is usually harder to read and prevents chaining. See the answer here:
Pandas: peculiar performance drop for inplace rename after dropna
Edit sort has now been deprecated leaving sort_index as the replacement for this scenario.
edited May 23 '17 at 11:46
Community♦
11
answered Jul 20 '14 at 2:14
fantabolousfantabolous
8,04032837
Slightly more compact:
df = pd.DataFrame([1, 2, 3, 4, 5], index=[100, 29, 234, 1, 150], columns=['A'])
df = df.sort()
print(df)
Note:
- the standard
sortwill do the same thing as sort_index if a sort column isn't specified. - preferable not to use
inplaceas it is usually harder to read and prevents chaining. See the answer here:
Pandas: peculiar performance drop for inplace rename after dropna
Edit sort has now been deprecated leaving sort_index as the replacement for this scenario.
edited May 23 '17 at 11:46
Community♦
11
answered Jul 20 '14 at 2:14
fantabolousfantabolous
8,04032837
edited May 23 '17 at 11:46
Community♦
11
edited May 23 '17 at 11:46
Community♦
11
edited May 23 '17 at 11:46
Community♦
11
11
answered Jul 20 '14 at 2:14
fantabolousfantabolous
8,04032837
answered Jul 20 '14 at 2:14
fantabolousfantabolous
8,04032837
answered Jul 20 '14 at 2:14
fantabolousfantabolous
8,04032837
8,04032837
6
.sort()docstring saysDEPRECATED: use DataFrame.sort_values()
– endolith
Jul 3 '16 at 17:47
1
@endolith Indeed.sort()has since been deprecated. The replacement would be.sort_index()as Paul H uses in his answer, in which case the only difference between our answers is I don't useinplace=True.
– fantabolous
Jan 16 '17 at 23:52
add a comment |
6
.sort()docstring saysDEPRECATED: use DataFrame.sort_values()
– endolith
Jul 3 '16 at 17:47
1
@endolith Indeed.sort()has since been deprecated. The replacement would be.sort_index()as Paul H uses in his answer, in which case the only difference between our answers is I don't useinplace=True.
– fantabolous
Jan 16 '17 at 23:52
6
6
.sort() docstring says DEPRECATED: use DataFrame.sort_values()– endolith
Jul 3 '16 at 17:47
.sort() docstring says DEPRECATED: use DataFrame.sort_values()– endolith
Jul 3 '16 at 17:47
1
1
@endolith Indeed
.sort() has since been deprecated. The replacement would be .sort_index() as Paul H uses in his answer, in which case the only difference between our answers is I don't use inplace=True.– fantabolous
Jan 16 '17 at 23:52
@endolith Indeed
.sort() has since been deprecated. The replacement would be .sort_index() as Paul H uses in his answer, in which case the only difference between our answers is I don't use inplace=True.– fantabolous
Jan 16 '17 at 23:52
add a comment |
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