Bringing it all together (3)

In the previous exercise, you built on your function count_entries() to add a try-except block. This was so that users would get helpful messages when calling your count_entries() function and providing a column name that isn't in the DataFrame. In this exercise, you'll instead raise a ValueError in the case that the user 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

If col_name is not a column in the DataFrame df, raise a ValueError 'The DataFrame does not have a ' + col_name + ' column.'.
Call your new function count_entries() to analyze the 'lang' column of tweets_df. Store the result in result1.
Print result1. This has been done for you, so hit 'Submit Answer' to check out the result. In the next exercise, you'll see that it raises the necessary ValueErrors.

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."""
    
    # Raise a ValueError if col_name is NOT in DataFrame
    if col_name not in df.columns:
        ____

    # Initialize an empty dictionary: cols_count
    cols_count = {}
    
    # 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

# Call count_entries(): result1
____

# Print result1
print(result1)

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