Data Visualization

Now that we've covered the key features of the nltk package, let's move on to visualizing our data. We'll begin by calculating word frequencies and then displaying these frequencies using a bar plot.

Tehtävä

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Calculate the frequency distribution of the tokenized words from your text.
Find the top 30 most common words in this distribution.

Ratkaisu

# Import matplotlib for data visualization

import matplotlib.pyplot as plt

# Create a subplot for a bar chart

fig, axs = plt.subplots(nrows=1, ncols=1, figsize=(18,5),

gridspec_kw={"height_ratios": [1],

"hspace": 0.7})

# Calculate frequency distribution of the tokenized words

fdist = nltk.FreqDist(story_tokenized)

# Find the top 30 most common words

top_30_words = fdist.most_common(30)

# Plot a bar chart for the top 30 words

axs.bar([word[0] for word in top_30_words], [word[1] for word in top_30_words])

# Add text labels for each bar with the count of the words

for i in range(len(top_30_words)):

axs.text(i, top_30_words[i][1], str(top_30_words[i][1]))

axs.set_xticklabels([word[0] for word in top_30_words], rotation=45)

axs.set_title("Top 30 Words")

axs.set_xlabel("Word")

axs.set_ylabel("Count of Words")

plt.show()

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