Bringing it all together (2)

Sometimes, we make mistakes when calling functions - even ones you made yourself. But don't fret! In this exercise, you will improve on your previous work with the count_entries() function in the last chapter by adding a try-except block to it. This will allow your function to provide a helpful message when the user calls your count_entries() function but provides a column name that isn't in the DataFrame.

Once again, for your convenience, pandas has been imported as pd and the 'tweets.csv' file has been imported into the DataFrame tweets_df. Parts of the code from your previous work are also provided.

This exercise is part of the course

Introduction to Functions in Python

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Exercise instructions

Add a try block so that when the function is called with the correct arguments, it processes the DataFrame and returns a dictionary of results.
Add an except block so that when the function is called incorrectly, it displays the following error message: 'The DataFrame does not have a ' + col_name + ' column.'.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Define count_entries()
def count_entries(df, col_name='lang'):
    """Return a dictionary with counts of
    occurrences as value for each key."""

    # Initialize an empty dictionary: cols_count
    cols_count = {}

    # Add try block
    ____:
        # Extract column from DataFrame: col
        col = df[col_name]
        
        # Iterate over the column in DataFrame
        for entry in col:
    
            # If entry is in cols_count, add 1
            if entry in cols_count.keys():
                cols_count[entry] += 1
            # Else add the entry to cols_count, set the value to 1
            else:
                cols_count[entry] = 1
    
        # Return the cols_count dictionary
        return cols_count

    # Add except block
    ____:
        ____

# Call count_entries(): result1
result1 = count_entries(tweets_df, 'lang')

# Print result1
print(result1)

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