Hashtags and mentions in Russian tweets

Let's revisit the tweets dataframe containing the Russian tweets. In this exercise, you will compute the number of hashtags and mentions in each tweet by defining two functions count_hashtags() and count_mentions() respectively and applying them to the content feature of tweets.

In case you don't recall, the tweets are contained in the content feature of tweets.

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Feature Engineering for NLP in Python

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Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Function that returns numner of hashtags in a string
def count_hashtags(string):
	# Split the string into words
    words = string.split()
    
    # Create a list of words that are hashtags
    hashtags = [word for word in words if ____.____(____)]
    
    # Return number of hashtags
    return(len(hashtags))

# Create a feature hashtag_count and display distribution
tweets['hashtag_count'] = tweets['content'].apply(count_hashtags)
tweets['hashtag_count'].hist()
plt.title('Hashtag count distribution')
plt.show()

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