Welcome to the second section! You've done great work so far! In this section, we will consider another common type of chart - this is a **bar chart**.

The concept for creating a bar chart is the same as for line plot: initialize `Axes` and `Figure` objects using the `.subplots()` method and then apply `.bar()` function to `Axes` object. The first argument (`x`) of the function is the x coordinates of the bar, the second (`height`) - the heights of the bars. For example, let's visualize some abstract subject grades.

# Import library
import matplotlib.pyplot as plt

# Create data for chart
subjects = ['Math', 'Literature', 'History', 'Physics', 'Arts']
grades = [95, 76, 83, 92, 68]

# Create Axes and Figure objects
fig, ax = plt.subplots()

# Initialize bar chart
ax.bar(subjects, grades)

# Display the plot
plt.show()

In this section, we will be introduced to the very basics of matplotlib - creating empty Figure and Axes, how to build a line plot, display multiple lines on one plot, add a legend, customize line type, and so on...

In this section, we will learn about other chart types, such as bar plots, histograms, box plots, how to set necessary parameters and customize them.

In this section, we will learn the scatter plots - one of the easiest ways to discover the relationships in your data.

Visualization in Python with matplotlib

Simple Bar Chart