Learn Jupyter-notebook - 10 Code Examples & CST Typing Practice Test
Jupyter Notebook is an open-source interactive web-based environment that allows users to create and share documents containing live code, equations, visualizations, and narrative text. It is widely used for data science, scientific computing, and machine learning.
View all 10 Jupyter-notebook code examples →
Learn JUPYTER-NOTEBOOK with Real Code Examples
Updated Nov 26, 2025
Code Sample Descriptions
Hello World in Jupyter Notebook (Python)
print("Hello World")
A simple Jupyter Notebook cell that prints 'Hello World'.
Hello World with Markdown in Jupyter Notebook
# Hello World
A Markdown cell in Jupyter Notebook displaying 'Hello World' as formatted text.
Jupyter Notebook Math Example
a = 5
b = 10
print(f"Sum: {a + b}")
A Python cell performing a simple math operation and printing the result.
Jupyter Notebook List Example
fruits = ['apple', 'banana', 'cherry']
for fruit in fruits:
print(fruit)
A Python cell creating a list and iterating over it.
Jupyter Notebook Function Example
def greet(name):
return f"Hello, {name}!"
print(greet('Alice'))
Defines a function and calls it within a Jupyter cell.
Jupyter Notebook Plot Example
import matplotlib.pyplot as plt
x = [1,2,3,4]
y = [10,20,25,30]
plt.plot(x,y)
plt.title('Line Graph')
plt.show()
Uses matplotlib to plot a simple line graph.
Jupyter Notebook Pandas DataFrame Example
import pandas as pd
data = {'Name':['Alice','Bob'],'Age':[25,30]}
df = pd.DataFrame(data)
df
Creates a simple Pandas DataFrame and displays it.
Jupyter Notebook Markdown Header Example
# Main Header
## Sub Header
**Bold Text** and *Italic Text*
A Markdown cell with multiple headers and text formatting.
Jupyter Notebook Import NumPy Example
import numpy as np
arr = np.array([1,2,3,4,5])
print(arr)
Imports NumPy and creates a simple array.
Jupyter Notebook Markdown List Example
- Item 1
- Item 2
- Item 3
A Markdown cell displaying a bulleted list.
Frequently Asked Questions about Jupyter-notebook
What is Jupyter-notebook?
Jupyter Notebook is an open-source interactive web-based environment that allows users to create and share documents containing live code, equations, visualizations, and narrative text. It is widely used for data science, scientific computing, and machine learning.
What are the primary use cases for Jupyter-notebook?
Data analysis and visualization. Machine learning experiments. Teaching programming, statistics, and data science. Documenting scientific research workflows. Interactive tutorials and demonstrations
What are the strengths of Jupyter-notebook?
Supports interactive exploration and experimentation. Combines code, documentation, and visuals in one document. Highly extensible with kernels and plugins. Encourages reproducible research and collaborative learning. Strong ecosystem of libraries and community support
What are the limitations of Jupyter-notebook?
Not ideal for developing production-grade software. Performance can be limited for very large datasets. Requires knowledge of environment setup for certain libraries. Version control can be complex with notebook format. Execution order issues can cause hidden state problems
How can I practice Jupyter-notebook typing speed?
CodeSpeedTest offers 10+ real Jupyter-notebook code examples for typing practice. You can measure your WPM, track accuracy, and improve your coding speed with guided exercises.