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Simplifying Machine Learning with PyCaret in Python

Exploratory Data Analysis

Explore how to conduct exploratory data analysis on the BBC News dataset for natural language processing tasks. Understand class distribution through bar charts, visualize word prominence using word clouds, and analyze word frequencies with charts to prepare for effective classification modeling.

We'll cover the following...

We’ll perform EDA on the BBC News dataset.

Bar chart

By using the value_counts() and plot() pandas functions, we can create a bar chart that visualizes class proportions.

C++
# Plotting the bar chart
color = ['C0', 'C1', 'C2', 'C3', 'C4']
categories = data['category'].value_counts()
categories.plot(kind = 'bar', figsize = (12,8), color = color)
plt.show()

As we can see in the output, the dataset is imbalanced because the classes aren’t evenly distributed. We’ll deal with this issue later because right now it may cause problems with classification model training. The two most common ...