If we want to distinguish multiple plots in the same figure in matplotlib, we use the legend function()

#softwaredevelopment #python #datascience

Due to work responsibilities, I was unavailable for 11 days thereabout. I'm back now.
I started yesterday (October 22) and completed today (October 23).

Day 64 [October 22, 2025]
I completed day 2 goals, as extracted from the 'Python for Software Development' textbook by Halvorsen (n.d.):

I need to buckle down, as I'm still lagging on day day 3 & 4 goals, "Day 3-4: Control structures (if-else, loops)", as well as day 5 (and 6) goals, "Day 5-6: Functions and modules", and Day 7 target (exercises) (Meta AI, personal communication, August 8, 2025). If I haven't covered this, I can't make progress on day 8 - 63 goals.

Goals:
As extracted from the 'Python for Software Development' textbook by Halvorsen (n.d.):

The New Age of Programming ✅
What is Python? ✅
Introduction to Python ✅
Interpreted vs. Compiled ✅
Python Packages ✅
Python Packages for Science and Numerical Computations ✅
Python Editors ✅
Python IDLE ✅
Visual Studio Code ✅
Variables ✅
Numbers ✅
Strings ✅
String Input✅
Built-in Functions✅
Python Standard Library✅
Using Python Libraries, Packages and Modules✅
Python Packages✅
Plotting in Python ✅
Subplots✅
Exercises✅
If ... Else
Arrays
For Loops
Nested
For Loops
While Loops
Exercises
Creating Functions in Python - Introduction
Functions with multiple return values
Exercises
Creating Classes in Python
The init () Function
Exercises
Creating Python Modules
Exercises

Notes:
'Python for Software Development' textbook by Halvorsen (n.d.):
On day 62, I worked on the exercise in Halvorsen, n.d., page 51, and came to this solution after corrections:

import matplotlib.pyplot as plt
import numpy as np

xStart = 0
xEnd = 2*np.pi
increment = 0.5

x = np.arange(xStart, xEnd, increment)
y = np.sin(x)
plt.subplot(2,1,1)
plt.plot(x,y,'g')
plt.xlabel('x')
plt.ylabel('sin(x)')
plt.title('SINE GRAPH')
plt.grid()
plt.show()

x = np.arange(xStart, xEnd, increment)
y = np.cos(x)
plt.subplot(2,1,2)
plt.plot(x,y,'r')
plt.xlabel('x')
plt.ylabel('cos(x)')
plt.title('COSINE GRAPH')
plt.grid()
plt.show()

But the functions axis() and legend() were not used in my code. I learnt what axis() does basically, but today I will look at legend().

plt.legend() (geeksforgeeks, 2025):

To detail the elements in a graph, we set out a space, known as Legend.
To place this Legend in matplotlib we use the legend() function.
If we want to distinguish multiple plots in the same figure, we use the legend function().
To specify the location of the legend, the loc attribute is used, e.g. loc = "upper left", loc = "lower right", etc.
For multiple plots, the name of the labels are put in a list, e.g. plt.legend(["Bus Fee", "Salary"], loc = "lower right") [Code extracted from geeksforgeeks, 2025; and adjusted a bit]: import numpy as np import matplotlib.pyplot as plt