Report generation (notebooks to HTML/PDF) in Data Analysis Python - Mini Project: Build & Apply

Report generation (notebooks to HTML/PDF)

📖 Scenario: You work as a data analyst. Your manager wants a clean report of your analysis. You will create a simple data summary and then generate a report from it. The report will be saved as an HTML file, which can also be converted to PDF later.

🎯 Goal: Build a small Python script that creates a data summary dictionary, sets a report title, generates an HTML report string using the data, and finally saves the report to an HTML file.

📋 What You'll Learn

Create a dictionary with data summary values

Create a variable for the report title

Generate an HTML string using the data and title

Save the HTML string to a file named 'report.html'

Print a confirmation message with the file name

💡 Why This Matters

🌍 Real World

Data analysts often need to share their findings in easy-to-read reports. Generating HTML reports is a simple way to create visually clear summaries that anyone can open in a web browser.

💼 Career

Knowing how to automate report generation saves time and ensures consistent presentation of data insights, a valuable skill for data analysts and scientists.

1

Create the data summary dictionary

Create a dictionary called data_summary with these exact entries: 'total_sales': 1500, 'total_customers': 300, and 'average_sale': 5.0.

Data Analysis Python

# Create the data_summary dictionary with the exact keys and values
# Your code here

Hint

Use curly braces {} to create a dictionary. Separate keys and values with colons.

2

Set the report title

Create a variable called report_title and set it to the string 'Monthly Sales Report'.

Data Analysis Python

data_summary = {'total_sales': 1500, 'total_customers': 300, 'average_sale': 5.0}
# Create the report_title variable with the exact string
# Your code here

Hint

Use an equals sign = to assign the string to the variable.

3

Generate the HTML report string

Create a variable called html_report that stores a string with HTML content. Use an f-string to include report_title inside an <h1> tag and the values from data_summary inside <p> tags. The HTML should look like this exactly:

<h1>Monthly Sales Report</h1>
<p>Total Sales: 1500</p>
<p>Total Customers: 300</p>
<p>Average Sale: 5.0</p>

Data Analysis Python

data_summary = {'total_sales': 1500, 'total_customers': 300, 'average_sale': 5.0}
report_title = 'Monthly Sales Report'
# Create the html_report string using an f-string with the exact HTML structure
# Your code here

Hint

Use an f-string with triple quotes or escaped newlines \n to format the HTML string.

4

Save the HTML report and print confirmation

Write the html_report string to a file named 'report.html' using open with mode 'w'. Then print the exact message "Report saved to report.html".

Data Analysis Python

data_summary = {'total_sales': 1500, 'total_customers': 300, 'average_sale': 5.0}
report_title = 'Monthly Sales Report'
html_report = f"{report_title}\nTotal Sales: {data_summary['total_sales']}\nTotal Customers: {data_summary['total_customers']}\nAverage Sale: {data_summary['average_sale']}"
# Save html_report to 'report.html' and print confirmation
# Your code here

Hint

Use with open('report.html', 'w') as file: and file.write(html_report). Then use print for the message.

Practice

1. What is the main purpose of using jupyter nbconvert in data science?

easy

A. To convert Jupyter notebooks into HTML or PDF reports for easy sharing

B. To run Python code faster inside notebooks

C. To create new Jupyter notebooks automatically

D. To debug errors in Python code within notebooks

Solution

1. Step 1: Understand the function of nbconvert

   jupyter nbconvert is a tool that converts notebooks into other formats like HTML or PDF.

2. Step 2: Identify the main benefit

   Converting notebooks to HTML or PDF helps share results with people who don't use Jupyter notebooks.

3. Final Answer:

   To convert Jupyter notebooks into HTML or PDF reports for easy sharing -> Option A

4. Quick Check:

   nbconvert purpose = convert notebooks to shareable reports [OK]

Hint: Remember nbconvert = notebook to report file [OK]

Common Mistakes:

• Thinking nbconvert runs code faster
• Confusing nbconvert with notebook creation
• Assuming nbconvert is for debugging

2. Which of the following is the correct command to convert a notebook named analysis.ipynb to an HTML file using the terminal?

easy

A. jupyter convert --to html analysis.ipynb

B. jupyter nbconvert --to html analysis.ipynb

C. nbconvert --convert html analysis.ipynb

D. jupyter nbconvert analysis.ipynb --html

Solution

1. Step 1: Recall the correct nbconvert syntax

   The correct command uses jupyter nbconvert --to html filename.ipynb.

2. Step 2: Match the command to options

   jupyter nbconvert --to html analysis.ipynb matches the correct syntax exactly.

3. Final Answer:

   jupyter nbconvert --to html analysis.ipynb -> Option B

4. Quick Check:

   Correct nbconvert syntax = jupyter nbconvert --to html analysis.ipynb [OK]

Hint: Use '--to html' right after nbconvert [OK]

Common Mistakes:

• Using 'jupyter convert' instead of 'jupyter nbconvert'
• Placing options in wrong order
• Using '--html' instead of '--to html'

3. Consider this Python code snippet to convert a notebook to PDF programmatically:

import os
os.system('jupyter nbconvert --to pdf report.ipynb')

What will be the output after running this code if report.ipynb exists and conversion succeeds?

medium

A. Nothing happens; the command runs silently without output

B. The notebook report.ipynb is deleted

C. An error message about missing PDF converter appears

D. A PDF file named report.pdf is created in the current directory

Solution

1. Step 1: Understand os.system command

   The command runs jupyter nbconvert --to pdf report.ipynb in the terminal from Python.

2. Step 2: Know nbconvert PDF output behavior

   If the notebook exists and conversion works, a PDF file report.pdf is created in the same folder.

3. Final Answer:

   A PDF file named report.pdf is created in the current directory -> Option D

4. Quick Check:

   nbconvert PDF output = report.pdf file created [OK]

Hint: nbconvert creates output file with same base name [OK]

Common Mistakes:

• Thinking the notebook file is deleted
• Expecting no output file
• Assuming error without checking converter installation

4. You run this command in terminal:
jupyter nbconvert --to pdf my_notebook.ipynb
but get an error saying PDF conversion failed: 'xelatex' not found.
What is the most likely fix?

medium

A. Install a LaTeX distribution like TeX Live or MiKTeX on your system

B. Rename the notebook file to have a .pdf extension

C. Run the command with --to html instead of pdf

D. Update Jupyter to the latest version

Solution

1. Step 1: Understand the error message

   The error says xelatex is missing, which is a LaTeX tool needed for PDF conversion.

2. Step 2: Identify the fix

   Installing a LaTeX distribution like TeX Live or MiKTeX provides xelatex and fixes the error.

3. Final Answer:

   Install a LaTeX distribution like TeX Live or MiKTeX on your system -> Option A

4. Quick Check:

   Missing xelatex = install LaTeX distribution [OK]

Hint: PDF needs LaTeX; install it if missing [OK]

Common Mistakes:

• Renaming files instead of installing LaTeX
• Switching to HTML without reason
• Assuming Jupyter update fixes LaTeX errors

5. You want to automate generating HTML reports from multiple notebooks in a folder using Python. Which code snippet correctly converts all .ipynb files to HTML?

hard

A. import os
for file in os.listdir():
os.system(f'jupyter nbconvert --to html "{file}"')

B. import os
for file in os.listdir():
if file.endswith('.html'):
os.system(f'jupyter nbconvert --to ipynb "{file}"')

C. import os
for file in os.listdir():
if file.endswith('.ipynb'):
os.system(f'jupyter nbconvert --to html "{file}"')

D. import os
for file in os.listdir():
if file.endswith('.ipynb'):
os.system(f'jupyter convert --to html "{file}"')

Solution

1. Step 1: Filter files with .ipynb extension

   We want to convert only notebook files, so check if filename ends with '.ipynb'.

2. Step 2: Use correct nbconvert command inside loop

   Use jupyter nbconvert --to html "{file}" to convert each notebook to HTML.

3. Final Answer:

   import os for file in os.listdir(): if file.endswith('.ipynb'): os.system(f'jupyter nbconvert --to html "{file}"') -> Option C

4. Quick Check:

   Filter .ipynb and run nbconvert to html [OK]

Hint: Check file extension before converting [OK]

Common Mistakes:

• Trying to convert .html files instead of .ipynb
• Missing file extension check causing errors
• Using wrong command 'jupyter convert' instead of 'nbconvert'