Class 10 · Unit 4
Programming in
& Python
A friendly Python guide for class 10 students, with simple explanations of functions,
libraries, files, and charts.
🐍 Python Basics
🧩 Functions
📚 Libraries
📁 CSV Files
📊 Charts
🛠️ Practice Tasks
Programming gets easier the moment you stop trying to remember every rule and start
practising small programs. In this unit, short exercises and tiny projects build confidence quickly.
We focus on clear, friendly explanations for functions, libraries, and file handling. Try the code examples,
change them, and see what happens — that experimentation is how you learn.
When you prepare your project, keep it simple and explain each step. Writing a short note about what you did
helps the ideas stick.
Before learning the new parts of Python, it helps to remember the basics: variables, data types, if
statements, loops, and input/output. These are the building blocks of every program.
💡 Easy analogy
Python is like a language, and the basic rules are the alphabet and grammar. Once you know them, you can
write bigger programs without getting lost.
Variable
A named place to store data.
Condition
A decision based on yes/no or true/false.
Loop
A way to repeat work without writing the same code again and again.
Input/Output
Input means taking data from the user. Output means showing results.
Basics — try these
num = 5
name = "Asha"
print("Hello", name)
if num > 3:
print("Greater than three")
for i in range(3):
print(i)
age = int(input("Enter your age: "))
print("In five years you'll be", age + 5)
A function is a block of code that does one job. A user-defined
function is a function you write yourself. It helps you avoid repetition and keeps code
neat.
Functions — examples to try
def greet(name):
"""Return a hello message for name."""
return "Hello, " + name
print(greet("Asha"))
def add(a, b=0):
"""Return sum of a and b. b has a default value."""
return a + b
print(add(4, 5))
print(add(3))
def factorial(n):
result = 1
for i in range(2, n+1):
result *= i
return result
print(factorial(5))
A library is a collection of useful code that someone else already made. A
package helps organize those tools so you can import them into your program.
math
Helps with square roots, powers, and other math work.
random
Gives random numbers or random choices.
pandas
Good for working with tables and CSV files.
turtle
Used for drawing shapes and patterns on the screen.
matplotlib
Used to make graphs and charts.
Remember You do not need to create everything from scratch. Python
libraries are like ready-made tools in a toolbox.
Turtle graphics lets you draw by giving commands to a small cursor called a turtle. It
is a fun way to learn coding because you can see the result immediately.
forward()
Moves the turtle ahead.
left() / right()
Turns the turtle left or right.
color()
Changes the drawing color.
begin_fill() / end_fill()
Used to color the inside of a shape.
💡 Easy analogy
Turtle is like a small robot pen. You tell it where to move, and it draws the path for you.
Turtle — draw a square
import turtle
screen = turtle.Screen()
pen = turtle.Turtle()
pen.color("blue")
for _ in range(4):
pen.forward(100)
pen.left(90)
screen.bye()
Sometimes a program makes a mistake. Instead of stopping suddenly, we can use try-except
to handle the error politely.
Example — safe division
try:
num = int(input("Enter a number: "))
print(10 / num)
except ValueError:
print("That was not a number. Please enter digits only.")
except ZeroDivisionError:
print("Cannot divide by zero — try a different number.")
except Exception:
print("Something went wrong.")
Example — file open error handling
try:
with open('data.txt', 'r') as f:
print(f.read())
except FileNotFoundError:
print('data.txt not found — create the file and try again.')
Pandas is a Python library that makes it easy to read and write table-like data. A CSV
file is a simple text file where data is stored in columns separated by commas.
Read CSV
Bring file data into Python.
Write CSV
Save Python data into a CSV file.
Append CSV
Add new rows to an existing file.
DataFrame
A table-like structure used by Pandas.
Pandas example
import pandas as pd
df = pd.read_csv("students.csv")
print(df)
Pandas — write & append
import pandas as pd
# write a new CSV
df = pd.DataFrame({
'student_id': [1001, 1002],
'name': ['Asha', 'Ramesh']
})
df.to_csv('students_out.csv', index=False)
# append a new row
new = pd.DataFrame({'student_id': [1003], 'name': ['Sita']})
new.to_csv('students_out.csv', mode='a', header=False, index=False)
Memory tip CSV is a simple table file. Pandas helps Python read it
like a real table.
Data becomes easier to understand when we turn it into a chart. A chart can quickly show patterns,
comparisons, and changes.
Project idea Make a small program that reads CSV data and shows it
using a bar, line, or pie chart.
Matplotlib — quick charts
import matplotlib.pyplot as plt
# line chart
x = [1, 2, 3, 4]
y = [10, 20, 15, 30]
plt.plot(x, y)
plt.title('Line Chart')
plt.show()
# bar chart
names = ['Asha', 'Ramesh', 'Sita']
scores = [80, 75, 92]
plt.bar(names, scores)
plt.title('Scores')
plt.show()
# pie chart
parts = [40, 30, 30]
labels = ['A', 'B', 'C']
plt.pie(parts, labels=labels, autopct='%1.1f%%')
plt.title('Parts of a Whole')
plt.show()
🧠 Quick Quiz
Question 1
Why do we use user-defined functions?
To reuse code, reduce repetition, and keep programs neat.
Question 2
What does Pandas help us do?
It helps us work with table-like data and CSV files.
Question 3
What is try-except used for?
It handles errors so the program does not crash suddenly.
Question 4
Which chart is useful for showing parts of a whole?
A pie chart is best for showing parts of a whole.
