How to Transpose a Pandas DataFrame without index

# How to Transpose a Pandas DataFrame without index

To transpose a Pandas DataFrame without the index:

Use the DataFrame.set_index() method to set the index to your first DataFrame column (or your preferred column).
Use the DataFrame.transpose() method to transpose the DataFrame.

main.py

Copied!
import pandas as pd


df = pd.DataFrame({
    'name': ['Alice', 'Bobby', 'Carl', 'Dan'],
    'experience': [1, 3, 5, 7],
    'salary': [175.1, 180.2, 190.3, 205.4],
})

print(df)

df.set_index('name', inplace=True)

df = df.transpose()

print('-' * 50)

print(df)

The code for this article is available on GitHub

Running the code sample produces the following output.

shell

Copied!
    name  experience  salary
0  Alice           1   175.1
1  Bobby           3   180.2
2   Carl           5   190.3
3    Dan           7   205.4
--------------------------------------------------
name        Alice  Bobby   Carl    Dan
experience    1.0    3.0    5.0    7.0
salary      175.1  180.2  190.3  205.4

pandas transpose dataframe without index

You can call the DataFrame.set_index() method with the first column of your DataFrame or another column name that you'd rather use as the index.

main.py

Copied!
df.set_index('name', inplace=True)

We used the name column as the index, however, you can use any other column by passing its name to the set_index() method.

Notice that we also set the inplace argument to True.

When the inplace argument is set to True, the DataFrame is modified in place, rather than creating a new one.

The last step is to use the DataFrame.transpose() method.

main.py

Copied!
# name        Alice  Bobby   Carl    Dan
# experience    1.0    3.0    5.0    7.0
# salary      175.1  180.2  190.3  205.4
df = df.transpose()

The transpose() method returns the transposed DataFrame.

In other words, it writes the rows as columns and vice-versa.

# Transpose a Pandas DataFrame without index by using the `T` accessor

We used the DataFrame.transpose() method in the example above, however, you can also use the T accessor to achieve the same result.

main.py

Copied!
import pandas as pd


df = pd.DataFrame({
    'name': ['Alice', 'Bobby', 'Carl', 'Dan'],
    'experience': [1, 3, 5, 7],
    'salary': [175.1, 180.2, 190.3, 205.4],
})

print(df)

df = df.set_index('name').T

print('-' * 50)

print(df)

The code for this article is available on GitHub

Running the code sample produces the following output.

shell

Copied!
    name  experience  salary
0  Alice           1   175.1
1  Bobby           3   180.2
2   Carl           5   190.3
3    Dan           7   205.4
--------------------------------------------------
name        Alice  Bobby   Carl    Dan
experience    1.0    3.0    5.0    7.0
salary      175.1  180.2  190.3  205.4

transpose dataframe without index using t accessor

The T property is an accessor to the transpose() method.

main.py

Copied!
df = df.set_index('name').T

Notice that we didn't pass the inplace argument to set_index().

This way, the set_index method returns the DataFrame, on which we can directly access the T attribute.

The code sample above is equivalent to the following code sample.

main.py

Copied!
import pandas as pd


df = pd.DataFrame({
    'name': ['Alice', 'Bobby', 'Carl', 'Dan'],
    'experience': [1, 3, 5, 7],
    'salary': [175.1, 180.2, 190.3, 205.4],
})

print(df)

df = df.set_index('name').transpose()

print('-' * 50)

print(df)

The code for this article is available on GitHub

Running the Python script produces the following output.

shell

Copied!
    name  experience  salary
0  Alice           1   175.1
1  Bobby           3   180.2
2   Carl           5   190.3
3    Dan           7   205.4
--------------------------------------------------
name        Alice  Bobby   Carl    Dan
experience    1.0    3.0    5.0    7.0
salary      175.1  180.2  190.3  205.4

using transpose method instead of t attribute

As shown in the code sample, using the T attribute is equivalent to calling the transpose() method on the DataFrame.

# Additional Resources

You can learn more about the related topics by checking out the following tutorials:

I wrote a book in which I share everything I know about how to become a better, more efficient programmer.

You can use the search field on my Home Page to filter through all of my articles.

How to Transpose a Pandas DataFrame without index