mathlab

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Python Programming: Matplotlib
Course Title: Programming Methodology for Mechanical Engineering
Course Code: MEE 07151241
Md. Syamul Bashar
Assistant Professor, MEE, SUST

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Python Programming: Library
Python Programming Language: Library

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Topics
• Matplotlib
Python Programming: Library Syllabus

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Link: Essential Python Libraries for Machine Learning and Data Science
Python Programming: Library

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Python Programming: Library
Python Programming Language: Matplotlib

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Python Programming: Library
Matplotlib
Need: Data visualization.
Use Case: Creating static, animated, and interactive plots and charts.

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Python Programming: Library Matplotlib
Types of Plots
Matplotlib supports a variety of plot types, including:
● Line Plots: Used to visualize data points as connected lines.
● Scatter Plots: Ideal for showing individual data points.
● Bar Charts: Suitable for comparing categorical data.
● Histograms: Used to display the distribution of a dataset.
● Pie Charts: For displaying proportions of a whole.
● Box Plots: Show the distribution and spread of data.

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Python Programming: Library Matplotlib
Installation
# pip install matplotlib

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Python Programming: Library Matplotlib
Line Plotting
import matplotlib.pyplot as plt
# Sample data
x = [1, 2, 3, 4, 5]
y = [10, 8, 6, 4, 2]
# Create a line plot
plt.plot(x, y)
# Display the plot
plt.show()

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Python Programming: Library Matplotlib
Multiple Lines in One Figure
import matplotlib.pyplot as plt
# Sample data
x1 = [1, 2, 3, 4, 5]
y1 = [10, 8, 6, 4, 2]
x2 = [1, 2, 3, 4, 5]
y2 = [1, 2, 3, 4, 5]
plt.plot(x1, y1)
plt.scatter(x2, y2)
plt.show()

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Python Programming: Library Matplotlib
Adding Labels and Title
import matplotlib.pyplot as
plt
x1 = [1, 2, 3, 4, 5]
y1 = [10, 8, 6, 4, 2]
plt.plot(x1, y1)
plt.xlabel("X-axis Label")
plt.ylabel("Y-axis Label")
plt.title("Title of the
Setting Axis Limits
# Set x-axis limits
plt.xlim(0, 6)
# Set y-axis limits
plt.ylim(0, 12)

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Adding Legends
import matplotlib.pyplot as
plt
x = [1, 2, 3, 4, 5]
y = [10, 8, 6, 4, 2]
plt.plot(x, y, label="Line
1")
plt.legend()
Changing Line Styles and Colors
import matplotlib.pyplot as
plt
x = [1, 2, 3, 4, 5]
y = [10, 8, 6, 4, 2]
plt.plot(x, y,
linestyle='--', color='red')
plt.show()
Python Programming: Library Matplotlib

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Subplots
import matplotlib.pyplot as
plt
# Sample data
x = [1, 2, 3, 4, 5]
y = [10, 8, 6, 4, 2]
# Create a 2x2 grid of
subplots, select the first
# Select the second subplot
plt.subplot(2, 2, 2)
plt.scatter(x, y)
plt.show()
Python Programming: Library Matplotlib

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Saving Plot
import matplotlib.pyplot as
plt
# Sample data
x = [1, 2, 3, 4, 5]
y = [10, 8, 6, 4, 2]
# Create a 2x2 grid of
subplots, select the first
# Select the second subplot
plt.subplot(2, 2, 2)
plt.scatter(x, y)
plt.savefig("my_plot.png")
Python Programming: Library Matplotlib

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Plotting From xlsx File
# pip install openpyxl
import pandas as pd
import numpy as np
import matplotlib.pyplot as
plt
# Read data from Excel file
df = pd.read_excel('inlet
velocity.xlsx')
# Extract columns from the
DataFrame and convert to
NumPy arrays
x = np.array(df['Time'])
y = np.array(df['Velocity'])
# Create a line plot
plt.plot(x, y)
Python Programming: Library Matplotlib

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Plotting From xlsx File
# Customize the plot (labels,
title, etc.)
plt.xlabel('Time')
plt.ylabel('Velocity')
plt.title('Cardiac Cycle')
# # Display the plot
plt.show()
Python Programming: Library Matplotlib