Master Matplotlib Visualization Basics in Python 📊
1. Creating a simple line plot
Matplotlib is the most widely used Python library for data visualization. A basic line plot can be drawn with plot().
Long form
import matplotlib.pyplot as plt
x = [1,2,3,4,5]
y = [2,4,6,8,10]
plt.plot(x,y)
plt.show()
One-liner
__import__('matplotlib.pyplot').plot([1,2,3,4,5],[2,4,6,8,10]); __import__('matplotlib.pyplot').show()
This creates a simple line chart showing the relationship between x and y.
2. Adding titles, labels & legends
To make plots understandable, add titles, x/y labels, and legends.
Long form
import matplotlib.pyplot as plt
x = [1,2,3,4]
y = [1,4,9,16]
plt.plot(x,y,label="Squares")
plt.title("Line Plot Example")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.legend()
plt.show()
One-liner
plt=__import__('matplotlib.pyplot');plt.plot([1,2,3,4],[1,4,9,16],label="Squares");plt.title("Line Plot Example");plt.xlabel("X-axis");plt.ylabel("Y-axis");plt.legend();plt.show()
Titles and legends make visualizations more professional and explanatory.
3. Plotting multiple lines
You can plot multiple datasets on the same figure.
Long form
import matplotlib.pyplot as plt
x = [1,2,3,4,5]
y1 = [1,2,3,4,5]
y2 = [1,4,9,16,25]
plt.plot(x,y1,label="Linear")
plt.plot(x,y2,label="Quadratic")
plt.legend()
plt.show()
One-liner
plt=__import__('matplotlib.pyplot');x=[1,2,3,4,5];plt.plot(x,x,label="Linear");plt.plot(x,[i**2 for i in x],label="Quadratic");plt.legend();plt.show()
This is useful for comparing multiple datasets in one visualization.
4. Bar chart & pie chart basics
Matplotlib supports many chart types like bar and pie charts.
Long form
import matplotlib.pyplot as plt
x = ['A','B','C']
y = [10,20,15]
plt.bar(x,y)
plt.show()
One-liner
plt=__import__('matplotlib.pyplot');plt.bar(['A','B','C'],[10,20,15]);plt.show()
Bar charts and pie charts are essential for categorical data visualization.
5. Customizing plots (colors, styles, grid)
You can customize plots with different colors, line styles, and grids.
Long form
import matplotlib.pyplot as plt
x = [1,2,3,4,5]
y = [2,4,6,8,10]
plt.plot(x,y,'r--',linewidth=2)
plt.grid(True)
plt.show()
One-liner
plt=__import__('matplotlib.pyplot');plt.plot([1,2,3,4,5],[2,4,6,8,10],'r--',linewidth=2);plt.grid(True);plt.show()
This makes your charts visually appealing and easier to interpret.
5 Interview Questions (with Answers):
Q: What is the difference between plot() and bar() in Matplotlib?
A: plot() is used for line charts, while bar() is used for bar charts.
Q: How do you add a legend to a plot in Matplotlib?
A: By using plt.legend().
Q: How can you plot multiple datasets on the same figure?
A: Call plot() multiple times with different datasets before plt.show().
Q: How do you change the line color and style in a Matplotlib plot?
A: By passing format strings like 'r--' (red dashed line) to plot().
Q: Why is plt.show() used in Matplotlib?
A: It displays the figure window with the plotted visualization.
#matplotlib #Python #DataScience #Visualization #MachineLearning #CodingTips #InterviewPrep
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