How to pivot a dataframe with two columns with no index
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I am trying to pivot my current two column dataframe which currently looks like this:
one two
a 12
b 32
c 12
I want to pivot this resulting in neither column becoming the index. My expected result is:
a b c
12 32 12
a, b, and c are the new columns. 12, 32, 12 are the values in the row.
Thanks
python pandas
add a comment |
I am trying to pivot my current two column dataframe which currently looks like this:
one two
a 12
b 32
c 12
I want to pivot this resulting in neither column becoming the index. My expected result is:
a b c
12 32 12
a, b, and c are the new columns. 12, 32, 12 are the values in the row.
Thanks
python pandas
add a comment |
I am trying to pivot my current two column dataframe which currently looks like this:
one two
a 12
b 32
c 12
I want to pivot this resulting in neither column becoming the index. My expected result is:
a b c
12 32 12
a, b, and c are the new columns. 12, 32, 12 are the values in the row.
Thanks
python pandas
I am trying to pivot my current two column dataframe which currently looks like this:
one two
a 12
b 32
c 12
I want to pivot this resulting in neither column becoming the index. My expected result is:
a b c
12 32 12
a, b, and c are the new columns. 12, 32, 12 are the values in the row.
Thanks
python pandas
python pandas
edited Mar 1 at 19:26
asked Mar 1 at 19:16
user11132841
add a comment |
add a comment |
3 Answers
3
active
oldest
votes
Use set_index to move column 'one' into the index, then use T to transpose.
a.set_index('one').T
Output:
one a b c
two 12 32 12
Info:
<class 'pandas.core.frame.DataFrame'>
Index: 1 entries, two to two
Data columns (total 3 columns):
a 1 non-null int64
b 1 non-null int64
c 1 non-null int64
dtypes: int64(3)
memory usage: 28.0+ bytes
None
answered Mar 1 at 19:30
Scott BostonScott Boston
57.5k73258
add a comment |
If this is your input:
a = pd.DataFrame([("a", 12), ("b", 32), ("c", 12)], columns=["one", "two"])
one two
0 a 12
1 b 32
2 c 12
Then a.transpose() results in this:
0 1 2
one a b c
two 12 32 12
Is this what you were looking for?
answered Mar 1 at 19:23
Niklas MertschNiklas Mertsch
500316
You can usea.Tfor short.
– Scott Boston
Mar 1 at 19:26
add a comment |
Giving everything the same index with .pivot_table
df.pivot_table(columns='one', index=df.index//len(df), values='two').rename_axis(None, axis=1)
#or with pivot
df = df.pivot(columns='one', index=df.index//len(df)).rename_axis([None, None], axis=1)
df.columns = [y for _,y in df.columns]
a b c
0 12 32 12
answered Mar 1 at 20:12
ALollzALollz
15.8k31738
add a comment |
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3 Answers
3
active
oldest
votes
3 Answers
3
active
oldest
votes
active
oldest
votes
active
oldest
votes
Use set_index to move column 'one' into the index, then use T to transpose.
a.set_index('one').T
Output:
one a b c
two 12 32 12
Info:
<class 'pandas.core.frame.DataFrame'>
Index: 1 entries, two to two
Data columns (total 3 columns):
a 1 non-null int64
b 1 non-null int64
c 1 non-null int64
dtypes: int64(3)
memory usage: 28.0+ bytes
None
answered Mar 1 at 19:30
Scott BostonScott Boston
57.5k73258
add a comment |
Use set_index to move column 'one' into the index, then use T to transpose.
a.set_index('one').T
Output:
one a b c
two 12 32 12
Info:
<class 'pandas.core.frame.DataFrame'>
Index: 1 entries, two to two
Data columns (total 3 columns):
a 1 non-null int64
b 1 non-null int64
c 1 non-null int64
dtypes: int64(3)
memory usage: 28.0+ bytes
None
answered Mar 1 at 19:30
Scott BostonScott Boston
57.5k73258
add a comment |
Use set_index to move column 'one' into the index, then use T to transpose.
a.set_index('one').T
Output:
one a b c
two 12 32 12
Info:
<class 'pandas.core.frame.DataFrame'>
Index: 1 entries, two to two
Data columns (total 3 columns):
a 1 non-null int64
b 1 non-null int64
c 1 non-null int64
dtypes: int64(3)
memory usage: 28.0+ bytes
None
answered Mar 1 at 19:30
Scott BostonScott Boston
57.5k73258
Use set_index to move column 'one' into the index, then use T to transpose.
a.set_index('one').T
Output:
one a b c
two 12 32 12
Info:
<class 'pandas.core.frame.DataFrame'>
Index: 1 entries, two to two
Data columns (total 3 columns):
a 1 non-null int64
b 1 non-null int64
c 1 non-null int64
dtypes: int64(3)
memory usage: 28.0+ bytes
None
answered Mar 1 at 19:30
Scott BostonScott Boston
57.5k73258
answered Mar 1 at 19:30
Scott BostonScott Boston
57.5k73258
answered Mar 1 at 19:30
Scott BostonScott Boston
57.5k73258
answered Mar 1 at 19:30
Scott BostonScott Boston
57.5k73258
57.5k73258
add a comment |
add a comment |
If this is your input:
a = pd.DataFrame([("a", 12), ("b", 32), ("c", 12)], columns=["one", "two"])
one two
0 a 12
1 b 32
2 c 12
Then a.transpose() results in this:
0 1 2
one a b c
two 12 32 12
Is this what you were looking for?
answered Mar 1 at 19:23
Niklas MertschNiklas Mertsch
500316
You can usea.Tfor short.
– Scott Boston
Mar 1 at 19:26
add a comment |
If this is your input:
a = pd.DataFrame([("a", 12), ("b", 32), ("c", 12)], columns=["one", "two"])
one two
0 a 12
1 b 32
2 c 12
Then a.transpose() results in this:
0 1 2
one a b c
two 12 32 12
Is this what you were looking for?
answered Mar 1 at 19:23
Niklas MertschNiklas Mertsch
500316
You can usea.Tfor short.
– Scott Boston
Mar 1 at 19:26
add a comment |
If this is your input:
a = pd.DataFrame([("a", 12), ("b", 32), ("c", 12)], columns=["one", "two"])
one two
0 a 12
1 b 32
2 c 12
Then a.transpose() results in this:
0 1 2
one a b c
two 12 32 12
Is this what you were looking for?
answered Mar 1 at 19:23
Niklas MertschNiklas Mertsch
500316
If this is your input:
a = pd.DataFrame([("a", 12), ("b", 32), ("c", 12)], columns=["one", "two"])
one two
0 a 12
1 b 32
2 c 12
Then a.transpose() results in this:
0 1 2
one a b c
two 12 32 12
Is this what you were looking for?
answered Mar 1 at 19:23
Niklas MertschNiklas Mertsch
500316
answered Mar 1 at 19:23
Niklas MertschNiklas Mertsch
500316
answered Mar 1 at 19:23
Niklas MertschNiklas Mertsch
500316
answered Mar 1 at 19:23
Niklas MertschNiklas Mertsch
500316
500316
You can usea.Tfor short.
– Scott Boston
Mar 1 at 19:26
add a comment |
You can usea.Tfor short.
– Scott Boston
Mar 1 at 19:26
You can use
a.T for short.– Scott Boston
Mar 1 at 19:26
You can use
a.T for short.– Scott Boston
Mar 1 at 19:26
add a comment |
Giving everything the same index with .pivot_table
df.pivot_table(columns='one', index=df.index//len(df), values='two').rename_axis(None, axis=1)
#or with pivot
df = df.pivot(columns='one', index=df.index//len(df)).rename_axis([None, None], axis=1)
df.columns = [y for _,y in df.columns]
a b c
0 12 32 12
answered Mar 1 at 20:12
ALollzALollz
15.8k31738
add a comment |
Giving everything the same index with .pivot_table
df.pivot_table(columns='one', index=df.index//len(df), values='two').rename_axis(None, axis=1)
#or with pivot
df = df.pivot(columns='one', index=df.index//len(df)).rename_axis([None, None], axis=1)
df.columns = [y for _,y in df.columns]
a b c
0 12 32 12
answered Mar 1 at 20:12
ALollzALollz
15.8k31738
add a comment |
Giving everything the same index with .pivot_table
df.pivot_table(columns='one', index=df.index//len(df), values='two').rename_axis(None, axis=1)
#or with pivot
df = df.pivot(columns='one', index=df.index//len(df)).rename_axis([None, None], axis=1)
df.columns = [y for _,y in df.columns]
a b c
0 12 32 12
answered Mar 1 at 20:12
ALollzALollz
15.8k31738
Giving everything the same index with .pivot_table
df.pivot_table(columns='one', index=df.index//len(df), values='two').rename_axis(None, axis=1)
#or with pivot
df = df.pivot(columns='one', index=df.index//len(df)).rename_axis([None, None], axis=1)
df.columns = [y for _,y in df.columns]
a b c
0 12 32 12
answered Mar 1 at 20:12
ALollzALollz
15.8k31738
answered Mar 1 at 20:12
ALollzALollz
15.8k31738
answered Mar 1 at 20:12
ALollzALollz
15.8k31738
answered Mar 1 at 20:12
ALollzALollz
15.8k31738
15.8k31738
add a comment |
add a comment |
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