Valueerror: specifying the columns using strings is only supported for pandas dataframes

Explanation of “ValueError: Specifying the columns using strings is only supported for Pandas DataFrames”

This error occurs when trying to specify columns using strings in a context where only Pandas DataFrames are supported. Let’s see an example to better understand the issue.

    import pandas as pd
    
    # Creating a list of dictionaries
    data = [
        {'Name': 'John', 'Age': 25, 'Role': 'Manager'},
        {'Name': 'Jane', 'Age': 30, 'Role': 'Supervisor'},
        {'Name': 'Sarah', 'Age': 35, 'Role': 'Assistant'},
    ]
    
    # Converting the list of dictionaries to a Pandas DataFrame
    df = pd.DataFrame(data)
    
    # Trying to access columns using strings
    df['Name']  # This would work fine
    
    # But if we try to access multiple columns using a list of strings
    columns = ['Name', 'Age']
    df[columns]  # This would raise the ValueError
    
    # The correct way to access multiple columns would be using a list of column names
    df[['Name', 'Age']]  # This would work as expected
  

In the example above, we create a Pandas DataFrame from a list of dictionaries. By default, the keys of the dictionaries become the column names in the DataFrame. Accessing a single column using a string, like df['Name'], works fine. However, when we try to access multiple columns using a list of strings, like df[columns], a ValueError is raised.

The reason for this error is that accessing multiple columns using a list of strings is not a supported syntax in contexts other than Pandas DataFrames. To access multiple columns, we need to use a list of column names enclosed in double square brackets, as shown in df[['Name', 'Age']].

It’s important to note that this error doesn’t occur when the input object is a Pandas DataFrame. The error arises when trying to use the same syntax on a different type of object or in a context that doesn’t support it.