Python Data Science Toolbox (Part 1)

Bringing it all together (1)
Recall the Bringing it all together exercise in the previous chapter where you did a simple Twitter analysis by developing a function that counts how many tweets are in certain languages. The output of your function was a dictionary that had the language as the keys and the counts of tweets in that language as the value.

In this exercise, we will generalize the Twitter language analysis that you did in the previous chapter. You will do that by including a default argument that takes a column name.

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.

# 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 = {}

    # 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
result1 = count_entries(tweets_df, col_name='lang')

# Call count_entries(): result2
result2 = count_entries(tweets_df, col_name='source')

# Print result1 and result2
print(result1)
print(result2)

Bringing it all together (2)
Wow, you’ve just generalized your Twitter language analysis that you did in the previous chapter to include a default argument for the column name. You’re now going to generalize this function one step further by allowing the user to pass it a flexible argument, that is, in this case, as many column names as the user would like!

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.

# Define count_entries()
def count_entries(df, *args):
    """Return a dictionary with counts of
    occurrences as value for each key."""
    
    #Initialize an empty dictionary: cols_count
    cols_count = {}
    
    # Iterate over column names in args
    for col_name in args:
    
        # 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
result1 = count_entries(tweets_df, 'lang')

# Call count_entries(): result2
result2 = count_entries(tweets_df, 'lang', 'source')

# Print result1 and result2
print(result1)
print(result2)

{'en': 97, 'et': 1, 'und': 2}
{'en': 97, 'et': 1, 'und': 2, '<a href="http://twitter.com" rel="nofollow">Twitter Web Client</a>': 24, '<a href="http://www.facebook.com/twitter" rel="nofollow">Facebook</a>': 1, '<a href="http://twitter.com/download/android" rel="nofollow">Twitter for Android</a>': 26, '<a href="http://twitter.com/download/iphone" rel="nofollow">Twitter for iPhone</a>': 33, '<a href="http://www.twitter.com" rel="nofollow">Twitter for BlackBerry</a>': 2, '<a href="http://www.google.com/" rel="nofollow">Google</a>': 2, '<a href="http://twitter.com/#!/download/ipad" rel="nofollow">Twitter for iPad</a>': 6, '<a href="http://linkis.com" rel="nofollow">Linkis.com</a>': 2, '<a href="http://rutracker.org/forum/viewforum.php?f=93" rel="nofollow">newzlasz</a>': 2, '<a href="http://ifttt.com" rel="nofollow">IFTTT</a>': 1, '<a href="http://www.myplume.com/" rel="nofollow">Plume\xa0for\xa0Android</a>': 1}