Plotting the distribution of a variable refers to creating a visual representation of the distribution of values for that variable. Several types of plots can be used to display the distribution of a variable, each with its strengths and weaknesses.

For this chapater, we will use histograms. A histogram is a plot that shows the frequency of different values in a dataset. It is a useful way to visualize the distribution of a continuous variable. The x-axis represents the variable of interest and the y-axis represents the frequency.

Methods description

• matplotlib.pyplot: This module provides a MATLAB-like plotting framework. In this code, it's used to create and customize the plot;
• seaborn: Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Here, it's used to create the count plot;
• plt.figure(figsize=(12, 6)): This method creates a new figure with a specified size. The figsize parameter sets the width and height of the figure in inches;
• sns.countplot(x="sentiment", data=data): This method from seaborn generates a count plot. It plots the count of observations in each category of the specified categorical variable ("sentiment" in this case) using data from the provided DataFrame data;
• plt.show(): This method displays the plot. It's typically used when creating plots in non-interactive environments (like scripts or Jupyter notebooks) to show the generated plot.