Pandas Convert Row to Column Header in DataFrame

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  • Post last modified:December 4, 2024
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Sometimes you may have a header(column labels) as a row in pandas DataFrame and you would need to convert this row to a column header. Converting row to column takes the value of each element in the row and sets it as the header of that column. In this article, I will explain several ways of how to convert row to column headers in pandas DataFrame using functions like DataFrame.columns(), DataFrame.iloc[] DataFrame.rename(), and DataFrame.values[] method with examples.

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Key Points –

  • The operation involves using a specific row from the DataFrame to become the new column header.
  • After converting the row, the original row is typically removed or adjusted to avoid redundancy.
  • You can select the row using iloc[] or loc[] to get the desired row for the header.
  • The .columns attribute can be reassigned to the selected row to set it as the new header.
  • The rename() function allows renaming columns using a row, but the row must be selected first.
  • After conversion, check if the DataFrame needs additional cleaning, such as renaming columns or resetting the index.

1. Quick Examples of Convert Row to Column Header in DataFrame

If you are in a hurry, below are some quick examples of how to convert row to column header (column labels) in Pandas DataFrame.


# Quick examples of convert row to column header

# Example 1: Assign row as column headers
df.columns = df.iloc[0]

# Example 2: Using DataFrame.rename()
df2 = df.rename(columns=df.iloc[1])

# Example 3: Convert row 
# To header and remove the row
df2 = df.rename(columns=df.iloc[0]).loc[1:]

# Example 4: Using DataFrame.rename() 
# To convert row to column header
df.rename(columns=df.iloc[1], inplace = True)

# Example 5: Using DataFrame.values[]
header_row = df.iloc[0]
df2 = pd.DataFrame(df.values[1:], columns=header_row)

Now, let’s create a DataFrame from the list with a few rows and columns, execute these examples and validate the results. Our DataFrame doesn’t contain column names but they are present as a first row on DataFrame.


# Create pandas DataFrame from List
import pandas as pd
technologies = [ ["Courses","Fee", "Duration"], 
                 ["Spark",20000, "30days"], 
                 ["Pandas",25000, "40days"], 
               ]
df=pd.DataFrame(technologies)
print("Create DataFrame:\n", df)

Yields below output.

pandas convert row column

2. Use DataFrame.columns() to Convert Row to Column Header

You can use df.columns=df.iloc[0] to set the column labels by extracting the first row. In pandas, the index starts from 0 hence 0 means first row.


# Assign row as column headers
header_row = 0
df.columns = df.iloc[header_row]
print("Get row as column header:\n", df)

# Convert row to column header 
# Using DataFrame.iloc[]
df.columns = df.iloc[0]
print("Get row as column header:\n", df)

Yields below output. Please note that the first row on the below result is a column header with an index name (0).

pandas convert row column

Running df.columns results below output. 


# Output:
Index(['Courses', 'Fee', 'Duration'], dtype='object', name=0)

3. Using DataFrame.values[] Method

If you notice the above result, the DataFrame still has the column labels as a data row, you can remove this after converting it to a column header. This can be achieved by creating a DataFrame from the existing one.


# Using DataFrame.values[]
df=pd.DataFrame(technologies)
header_row = df.iloc[0]
df2 = pd.DataFrame(df.values[1:], columns=header_row)
print(df2)

Yields below output.


# Output:
0 Courses    Fee Duration
0   Spark  20000   30days
1  Pandas  25000   40days

4. Convert Row to Column Header Using DataFrame.rename()

You can use DataFrame.rename() to rename the header and use loc[] or iloc[] to remove the first row from the data. Use this approach even if you want to convert the middle or any nth row to a column header.


# Using DataFrame.rename()
df=pd.DataFrame(technologies)
df2 = df.rename(columns=df.iloc[0]).loc[1:]
print(df2)

# Using DataFrame.rename() 
# To convert row to column header
# This doens't remove the first row.
df=pd.DataFrame(technologies)
df.rename(columns=df.iloc[0], inplace = True)

Yields below output.


# Output:
  Courses    Fee Duration
1   Spark  20000   30days
2  Pandas  25000   40days

5. Complete Example For Convert Row to Column Header 


# Create pandas DataFrame from List
import pandas as pd
technologies = [ ["Courses","Fee", "Duration"], 
                 ["Spark",20000, "30days"], 
                 ["Pandas",25000, "40days"], 
               ]
df=pd.DataFrame(technologies)
print(df)

# Assign row as column headers
header_row = 0
df.columns = df.iloc[header_row]
print(df)

# Convert row to column header 
# Using DataFrame.iloc[]
df=pd.DataFrame(technologies)
df.columns = df.iloc[0]
print(df)

# Using DataFrame.values[] & DataFrame()
df=pd.DataFrame(technologies)
header_row = df.iloc[0]
df2 = pd.DataFrame(df.values[1:], columns=header_row)
print(df2)

# Using DataFrame.rename()
df=pd.DataFrame(technologies)
df2 = df.rename(columns=df.iloc[0]).loc[1:]
print(df2)

# Using DataFrame.rename() 
# To convert row to column header
df=pd.DataFrame(technologies)
df.rename(columns=df.iloc[0], inplace = True)
print(df)

Conclusion

In this article, you have learned how to convert row values to column headers in DataFrame using DataFrame.columns(), DataFrame.rename(), DataFrame.iloc[], and DataFrame.values[] functions with examples.

Happy Learning !!

References

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