**Horizontal bar charts** are the same as bar charts, but have axes 'swapped': this time bars are horizontal, and values are labeled on the x-axis.

To build horizontal bar chart. use the `.barh()` function. This function can also be used to build stacked bars, but this time instead of the `bottom` parameter we should use the `left` parameter, and instead of `width` we should use `height`. For example, we can rebuild the stacked bar chart from example as a horizontal one:

# Import library
import matplotlib.pyplot as plt

# Create data for chart
countries = ['United States', 'India', 'Brazil']
agricultural = [333600, 1458996, 214368]
industrial = [3722590, 2179020, 672336]
services = [15592000, 5826510, 2361296]

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

# Initialize bar chart
ax.barh(countries, agricultural, label = 'Agricultural', height = 0.4)
ax.barh(countries, industrial, label = 'Industrial', left = agricultural, height = 0.4)
ax.barh(countries, services, label = 'Services', left = industrial, height = 0.4)

# Display the plot
plt.legend()
plt.show()

Visualization is one of the most common ways of representing data. By using different kinds of plots (like scatter-plot, histogram, bar charts, and so on) you can find some insights in your data, or approve/reject some assumption/hypothesis. In this course, you will be introduced to the matplotlib library, and learn how to build different charts.

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.

Horizontal Bar Chart

Visualization in Python with matplotlib

Horizontal Bar Chart