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Visualization in Python with matplotlib
Visualization in Python with matplotlib
Customizing Bar Charts
Nicely done! You've built many interesting bar charts. Now it's time to add some information to make the plots informative.
Like, in the previous chapters, we can use the .set()
function applied to the Axes
object to set the following parameters: xlabel
, ylabel
for labels on the axes, xlim
, ylim
to limit values on the axes (this parameters must have list/tuple as a value), title
for chart title. Also, to improve the readability we can add values above (or right/left) to each bar. To do it, we should save in separate variable each call of .bar()
(or .barh()
) function, and then call the .bar_label()
applied to Axes
object, passing saved .bar()
function call as the first argument, and padding
as the second (optional, the distance between bar and text). For example,
# 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 bar1 = ax.bar(subjects, grades) # Add labels above bars ax.bar_label(bar1, padding = 0) # Display the plot plt.show()
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