Introduction
Matplotlib is a graphing and plotting library that can be useful for creating
different types of graphs and plots. Such as line charts, pie charts, scatter
plots and 3D plots. Matplotlib can also be used for creating animated and
interactive visualizations. It can also generate output in a variety of
formats which includes PNG, SVG and PDF etc.
Installing Matplotlib
Matplotlib is not built into python. First, we need to install Matplotlib
using the PIP package manager.
If you are using Conda you can use the below command.
You can refer to more about installation options on the Matplotlib
installation page.
Plotting Simple Graph using Matplotlib
First, we need to import pyplot from Matplotlib library. After
that line, we give 2 python lists as arguments to plot() function
specifying Y values and X values for the graph. then we set the label for both
the x and y axis and the title. Finally, we call the show() function
that displays our plot in a window.
import matplotlib.pyplot as pyplot
pyplot.plot(
[1, 2, 3, 4],
[0.5, 1.0, 1.5, 2.0]
)
pyplot.xlabel('x-axis-label')
pyplot.ylabel('y-axis-label')
pyplot.title('This is the title')
pyplot.show()
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simple graph using matplotlib
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Plotting Multiple Graphs Same Plane.
When plotting multiple graphs we need to add different styles, and colours,
and more importantly, we need to add a legend to identify each graph clearly.
In the below code sample, we add a legend using legend() method and
pass arguments for legend background colour, location and title. we also add a
descriptive label for each graph, change the colour and set the style of the
one graph to a dashed line.
import matplotlib.pyplot as pyplot
pyplot.plot(
[0, 1, 2, 3],
[1, 3, 5, 7],
label = 'y = 2x + 1',
color = 'blue'
)
pyplot.plot(
[0, 1, 2, 3],
[3, 6, 9, 12],
ls = '--',
label = 'y = 3x + 3',
color = '#995789'
)
pyplot.xlabel('x-axis-label')
pyplot.ylabel('y-axis-label')
pyplot.title('This is the title')
pyplot.legend(
facecolor = 'gray',
title = 'legend',
loc = 'upper left'
)
pyplot.grid(True)
pyplot.show()
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multiple graphs in the same plane
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Plotting Bar Chart
We use the matplotlib pyplot bar() function to draw bar graphs. In
the below examples, we pass the x-coordinates, heights of each bar, bar
width, and colours of each bar.
import matplotlib.pyplot as plt
languages= ['Rust', 'Python', 'Kotlin', 'Javascript', 'C#']
Salary = [76000, 60000, 55000, 56000, 61000]
bar_colors = ['blue', 'orange', 'cyan', 'brown', 'purple']
plt.bar(
languages,
Salary,
width = 0.7,
color = bar_colors
)
plt.xlabel('Language')
plt.ylabel('Salary')
plt.title('Median Developer Salary By Language')
plt.show()
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Bar chart matplotlib
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Horizontal Bar Charts
You can create the above graph horizontal by using
barh() matplotlib pyplot function instead of bar() function. The
below code demonstrates it.
import matplotlib.pyplot as plt
languages= ['Rust', 'Python', 'Kotlin', 'Javascript', 'C#']
Salary = [76000, 60000, 55000, 56000, 61000]
bar_colors = ['blue', 'orange', 'cyan', 'brown', 'purple']
plt.barh(
languages,
Salary,
height = 0.7,
color = bar_colors
)
plt.xlabel('Salary')
plt.ylabel('Language')
plt.title('Median Developer Salary By Language')
plt.show()
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Horizontal bar graph matplotlib
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Line Graphs using Matplotlib
In the below line graph example, we pass the argument '
bo-' to the
function. in this argument '
bo-' first character '
b' indicates
the
colour of the line and second character '
o' indicates the
marker
of each point being plotted and the third character
'
-' indicates the
line style
of the graph. In our case, it sets to a blue solid line with circle markers.
import matplotlib.pyplot as plt
month = ['January', 'February', 'March', 'April', 'May', 'June']
profit = [10000, 28000, 13400, 14000, 24400, 21000]
plt.title('Profit in year 2022')
plt.xlabel('Month')
plt.ylabel('Profit')
plt.plot(
month,
profit,
'bo-'
)
plt.show()
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Line Graph Matplotlib
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Scatter plot
we use Matplotlib scatter() function to draw a scatter plot. below code
sample demonstrates a scatter plot.
import matplotlib.pyplot as plt
iq = [
[43, 45, 57, 20, 30, 75, 29, 60, 27, 80],
[22, 46, 43, 23, 45, 76, 44, 56, 41, 62]
]
maths = [
[29, 70, 20, 57, 30, 44, 60, 25, 32, 62],
[40, 23, 90, 55, 80, 39, 74, 65, 87, 48]
]
plt.scatter(
x = iq[0],
y = iq[1],
color='darkorange',
marker='o',
label='IQ'
)
plt.scatter(
x = maths[0],
y = maths[1],
color='green',
marker='^',
label='Mathematics'
)
plt.xlabel('Age')
plt.ylabel('Score')
plt.title('Marks Two Subjects')
plt.legend()
plt.show()
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| Scatter Plot |
Pie chart
Matplotlib pyplot pie() function was used to draw below the pie
chart.
import matplotlib.pyplot as plt
language = ['Python', 'Rust', 'Java', 'C#', 'Javascript']
precentage = [33.50, 15.30, 22.30, 12.45, 16.45]
plt.pie(
precentage,
labels = language,
autopct = '%1.2f%%',
counterclock = False,
startangle = 90
)
plt.title('Language Popularity')
plt.show()
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| Pie chart |
Conclusion
In this article, we show you how to draw simple graphs using the Matplotlib
library. Matplotlib is a very flexible option for creating graphs in
python.
References
