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How to pivot a dataframe with two columns with no index

How to merge two dictionaries in a single expression?How do I check whether a file exists without exceptions?Finding the index of an item given a list containing it in PythonAccessing the index in 'for' loops?Add one row to pandas DataFrameAdding new column to existing DataFrame in Python pandas“Large data” work flows using pandasChange data type of columns in PandasSelect rows from a DataFrame based on values in a column in pandasHow to pivot a dataframe

8

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

share|improve this question

edited 5 hours ago

macyyy33

asked 5 hours ago

macyyy33macyyy33

585

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add a comment | 

8

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

share|improve this question

edited 5 hours ago

macyyy33

asked 5 hours ago

macyyy33macyyy33

585

New contributor

macyyy33 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

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

share|improve this question

edited 5 hours ago

macyyy33

asked 5 hours ago

macyyy33macyyy33

585

New contributor

macyyy33 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

one   two

 a    12

 b    32

 c    12

 a   b   c 

12  32  12

share|improve this question

edited 5 hours ago

macyyy33

asked 5 hours ago

macyyy33macyyy33

585

New contributor

macyyy33 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

edited 5 hours ago

macyyy33

asked 5 hours ago

macyyy33macyyy33

585

New contributor

macyyy33 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 5 hours ago

macyyy33macyyy33

585

New contributor

macyyy33 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 5 hours ago

macyyy33macyyy33

585

3 Answers
3

active

oldest

votes

4

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

share|improve this answer

answered 5 hours ago

Scott BostonScott Boston

55.8k73156

add a comment | 

3

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?

share|improve this answer

answered 5 hours ago

Niklas MertschNiklas Mertsch

473115

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  You can use a.T for short.
  
  – Scott Boston
  5 hours ago
  
  
  

  
  
  
  

add a comment | 

2

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

share|improve this answer

answered 4 hours ago

ALollzALollz

14.2k31636

add a comment | 

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4

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

share|improve this answer

answered 5 hours ago

Scott BostonScott Boston

55.8k73156

add a comment | 

4

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

share|improve this answer

answered 5 hours ago

Scott BostonScott Boston

55.8k73156

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

share|improve this answer

answered 5 hours ago

Scott BostonScott Boston

55.8k73156

a.set_index('one').T

one   a   b   c

two  12  32  12

<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

share|improve this answer

answered 5 hours ago

Scott BostonScott Boston

55.8k73156

answered 5 hours ago

Scott BostonScott Boston

55.8k73156

answered 5 hours ago

Scott BostonScott Boston

55.8k73156

3

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?

share|improve this answer

answered 5 hours ago

Niklas MertschNiklas Mertsch

473115

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  You can use a.T for short.
  
  – Scott Boston
  5 hours ago
  
  
  

  
  
  
  

add a comment | 

3

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?

share|improve this answer

answered 5 hours ago

Niklas MertschNiklas Mertsch

473115

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  You can use a.T for short.
  
  – Scott Boston
  5 hours ago
  
  
  

  
  
  
  

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?

share|improve this answer

answered 5 hours ago

Niklas MertschNiklas Mertsch

473115

a = pd.DataFrame([("a", 12), ("b", 32), ("c", 12)], columns=["one", "two"])

  one  two

0   a   12

1   b   32

2   c   12

      0   1   2

one   a   b   c

two  12  32  12

share|improve this answer

answered 5 hours ago

Niklas MertschNiklas Mertsch

473115

answered 5 hours ago

Niklas MertschNiklas Mertsch

473115

answered 5 hours ago

Niklas MertschNiklas Mertsch

473115

2

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

share|improve this answer

answered 4 hours ago

ALollzALollz

14.2k31636

add a comment | 

2

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

share|improve this answer

answered 4 hours ago

ALollzALollz

14.2k31636

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

share|improve this answer

answered 4 hours ago

ALollzALollz

14.2k31636

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

share|improve this answer

answered 4 hours ago

ALollzALollz

14.2k31636

answered 4 hours ago

ALollzALollz

14.2k31636

answered 4 hours ago

ALollzALollz

14.2k31636