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.