Add a new row to a Pandas DataFrame with specific index name

Add a new row to a Pandas DataFrame with specific index name

To add a new row to a Pandas DataFrame with a specific index name, you can use the .loc[] indexer. Here's how you can do it:

import pandas as pd # Create a sample DataFrame data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 28]} df = pd.DataFrame(data) # Create a new row with specific index name new_row = pd.DataFrame({'Name': 'David', 'Age': 22}, index=['IndexName']) # Add the new row to the DataFrame using .loc[] df = df.append(new_row) print(df)

In this example, the new_row DataFrame is created with the desired values and the specified index name ('IndexName'). Then, the .append() method is used to add the new_row DataFrame to the original DataFrame df.

The output will be:

 Name Age 0 Alice 25 1 Bob 30 2 Charlie 28 IndexName David 22

Make sure to replace 'IndexName' with your desired index name and provide appropriate values for the new row.

Examples

  1. How to add a new row to a Pandas DataFrame with specific index name?

    Description: This query aims to understand the process of appending a new row with a particular index name to a Pandas DataFrame.

    import pandas as pd # Create a sample DataFrame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['index1', 'index2']) # New row data new_data = {'A': 5, 'B': 6} # Append the new row with a specific index name df = df.append(pd.Series(new_data, name='index3')) print(df)

  2. Pandas DataFrame add row with specific index name example

    Description: This query provides an example of how to add a new row with a specified index name to a Pandas DataFrame.

    import pandas as pd # Create a sample DataFrame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['index1', 'index2']) # New row data new_row = pd.Series({'A': 5, 'B': 6}, name='index3') # Append the new row with a specific index name df = df.append(new_row) print(df)

  3. Appending a row with a specific index name in Pandas DataFrame

    Description: This search query explores how to append a new row with a designated index name to a Pandas DataFrame.

    import pandas as pd # Create a sample DataFrame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['index1', 'index2']) # New row data new_data = {'A': 5, 'B': 6} # Append the new row with a specific index name df.loc['index3'] = new_data print(df)

  4. How to add a row to a Pandas DataFrame with a custom index name?

    Description: This query seeks a method to add a row with a personalized index name to a Pandas DataFrame.

    import pandas as pd # Create a sample DataFrame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['index1', 'index2']) # New row data new_row = pd.Series({'A': 5, 'B': 6}, name='index3') # Append the new row with a specific index name df = df.append(new_row) print(df)

  5. Pandas DataFrame add row with specific index name and data

    Description: This query looks for a way to add a row to a Pandas DataFrame, specifying both the index name and the data for the new row.

    import pandas as pd # Create a sample DataFrame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['index1', 'index2']) # New row data new_data = {'A': 5, 'B': 6} # Append the new row with a specific index name df = df.append(pd.DataFrame(new_data, index=['index3'])) print(df)

  6. Pandas DataFrame add row with custom index name using loc method

    Description: This query explores adding a row with a specific index name to a Pandas DataFrame using the loc method.

    import pandas as pd # Create a sample DataFrame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['index1', 'index2']) # New row data new_data = {'A': 5, 'B': 6} # Append the new row with a specific index name df.loc['index3'] = new_data print(df)

  7. Adding a row with a custom index name to a Pandas DataFrame

    Description: This query aims to find a method to add a row with a personalized index name to a Pandas DataFrame.

    import pandas as pd # Create a sample DataFrame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['index1', 'index2']) # New row data new_data = {'A': 5, 'B': 6} # Append the new row with a specific index name df = df.append(pd.DataFrame(new_data, index=['index3'])) print(df)

  8. How to insert a row with specific index name into a Pandas DataFrame?

    Description: This query looks for a way to insert a row with a specified index name into a Pandas DataFrame.

    import pandas as pd # Create a sample DataFrame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['index1', 'index2']) # New row data new_row = pd.Series({'A': 5, 'B': 6}, name='index3') # Append the new row with a specific index name df = df.append(new_row) print(df)

  9. Adding a new row with specific index name in Pandas DataFrame

    Description: This query explores methods to add a new row with a particular index name to a Pandas DataFrame.

    import pandas as pd # Create a sample DataFrame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['index1', 'index2']) # New row data new_row = pd.Series({'A': 5, 'B': 6}, name='index3') # Append the new row with a specific index name df = df.append(new_row) print(df)

  10. How to add a row with specific index name in Pandas DataFrame using loc method?

    Description: This query aims to understand the process of adding a row with a particular index name to a Pandas DataFrame using the loc method.

    import pandas as pd # Create a sample DataFrame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['index1', 'index2']) # New row data new_data = {'A': 5, 'B': 6} # Append the new row with a specific index name df.loc['index3'] = new_data print(df)

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