How to Convert Row to Column and Column to Row of Dataframe in Python

October 02, 2024

To convert a row to a column and a column to a row in a dataframe in Python, you can use the melt() function and the transpose() function, respectively.

The following examples show how to convert rows to columns and columns to rows in Python.

Using melt() Function

We can use the melt() function to convert rows to columns.

Suppose we have the following dataframe:

# Import pandas library
import pandas as pd

# Define data  
df = pd.DataFrame({'Price': [4500, 550, 250, 50, 350, 50], 'Status': [1, 1, 1, 0, 1, 1]})

# Convert rows to columns
converted_df = df.melt(var_name='Column', value_name='Value')   

# Show dataframe
print(converted_df)

Output: 👇️

    Column  Value
0    Price   4500
1    Price    550
2    Price    250
3    Price     50
4    Price    350
5    Price     50
6   Status      1
7   Status      1
8   Status      1
9   Status      0
10  Status      1
11  Status      1

In this example, we use the melt() function to convert rows to columns in the dataframe df. The output shows the dataframe with rows converted to columns.

Using transpose() Function

We can use the transpose() function to convert columns to rows.

Suppose we have the following dataframe:

# Import pandas library
import pandas as pd

# Define data  
df = pd.DataFrame({'Price': [4500, 550, 250, 50, 350, 50], 'Status': [1, 1, 1, 0, 1, 1]})

# Convert columns to rows
converted_df = df.T

# Show dataframe
print(converted_df)

Output: 👇️

           0    1    2   3    4   5
Price   4500  550  250  50  350  50
Status     1    1    1   0    1   1

In this example, we use the transpose() function to convert columns to rows in the dataframe df. The output shows the dataframe with columns converted to rows.

Conclusion

We can use the melt() function to convert rows to columns and the transpose() function to convert columns to rows in a dataframe in Python. These methods provide a convenient way to reshape dataframes.