Exporting to Excel in Data Analysis Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this code when exporting a DataFrame to Excel?

Consider the following Python code that exports a DataFrame to an Excel file. What will be the content of the Excel file sheet named 'Data'?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({'Name': ['Alice', 'Bob'], 'Age': [25, 30]})
df.to_excel('output.xlsx', sheet_name='Data', index=False)

A An Excel file with a sheet named 'Data' containing columns 'Name' and 'Age' with two rows of data, without row indices.

B An Excel file with a sheet named 'Sheet1' containing the data including row indices.

C An Excel file with a sheet named 'Data' but the data will include row indices as a separate column.

D The code will raise a FileNotFoundError because the file path is not specified.

💡 Hint

Check the parameters used in the to_excel function, especially sheet_name and index.

The code exports the DataFrame to an Excel file named 'output.xlsx' with the sheet named 'Data'. The parameter index=False means row indices are not saved as a separate column.

❓ data_output

intermediate

How many sheets will the Excel file contain after running this code?

This code exports two DataFrames to the same Excel file using ExcelWriter. How many sheets will the file have?

Data Analysis Python

import pandas as pd

df1 = pd.DataFrame({'A': [1, 2]})
df2 = pd.DataFrame({'B': [3, 4]})

with pd.ExcelWriter('multi_sheet.xlsx') as writer:
    df1.to_excel(writer, sheet_name='First')
    df2.to_excel(writer, sheet_name='Second')

A 1

B 0

C Raises an error because ExcelWriter is not closed explicitly.

D 2

💡 Hint

Each to_excel call with a different sheet_name adds a new sheet.

Using ExcelWriter with context manager writes both DataFrames to separate sheets named 'First' and 'Second', resulting in 2 sheets.

🔧 Debug

advanced

What error does this code raise when exporting to Excel?

Identify the error raised by this code snippet:

Data Analysis Python

import pandas as pd

df = pd.DataFrame({'X': [1, 2]})
df.to_excel('test.xlsx', sheet_name='Sheet1', index='False')

A TypeError: to_excel() got an unexpected keyword argument 'index'

B ValueError: index parameter must be a boolean, not a string

C No error, file is saved with row indices included

D FileNotFoundError: No such file or directory

💡 Hint

Check the type of the index parameter value.

The index parameter expects a boolean value True or False, but a string 'False' is passed, causing a ValueError.

🚀 Application

advanced

Which option correctly exports a DataFrame with a custom header and without the default index?

You want to export this DataFrame to Excel with column headers renamed to ['ID', 'Score'] and no row indices saved. Which code does this correctly?

Data Analysis Python

import pandas as pd
df = pd.DataFrame({'A': [101, 102], 'B': [88, 92]})

A df.rename(columns={'A': 'ID', 'B': 'Score'}).to_excel('custom.xlsx', index=False)

B df.to_excel('custom.xlsx', columns=['ID', 'Score'], index=False)

C df.to_excel('custom.xlsx', header=['ID', 'Score'], index=False)

D df.to_excel('custom.xlsx', header=True, index=False)

💡 Hint

To rename headers, you must rename columns before exporting.

The header parameter does not rename columns; renaming must be done on the DataFrame before export. Option A renames columns correctly and exports without index.

🧠 Conceptual

expert

Why might you use the ExcelWriter engine 'openpyxl' explicitly when exporting to Excel?

Select the best reason to specify the engine='openpyxl' parameter in pd.ExcelWriter when exporting DataFrames to Excel files.

A To speed up the export process by using a compiled engine instead of Python code.

B Because openpyxl is the only engine that can write CSV files.

C To enable writing to .xlsx files with support for advanced Excel features like cell styling and multiple sheets.

D To automatically convert all numeric columns to text format in Excel.

💡 Hint

Think about Excel file formats and features supported by different engines.

The openpyxl engine supports writing .xlsx files and advanced features like styling and multiple sheets. It is commonly used for Excel exports.

Practice

1. What does the to_excel() function do in pandas?

easy

A. Reads data from an Excel file

B. Saves a DataFrame to an Excel file

C. Creates a new DataFrame

D. Deletes an Excel file

Solution

1. Step 1: Understand the function purpose

   The to_excel() function is used to export data from a pandas DataFrame to an Excel file format.

2. Step 2: Differentiate from similar functions

   Functions like read_excel() are used to read Excel files, not save them.

3. Final Answer:

   Saves a DataFrame to an Excel file -> Option B

4. Quick Check:

   to_excel() = Save DataFrame to Excel [OK]

Hint: Remember: 'to' means saving/exporting [OK]

Common Mistakes:

• Confusing to_excel() with read_excel()
• Thinking it creates a DataFrame
• Assuming it deletes files

2. Which of the following is the correct syntax to save a DataFrame df to an Excel file named data.xlsx without row numbers?

easy

A. df.to_excel('data.xlsx', no_index=True)

B. df.to_excel('data.xlsx', row_numbers=False)

C. df.to_excel('data.xlsx', include_index=False)

D. df.to_excel('data.xlsx', index=False)

Solution

1. Step 1: Identify the parameter to exclude row numbers

   The parameter to exclude row numbers in to_excel() is index=False.

2. Step 2: Check syntax correctness

   df.to_excel('data.xlsx', index=False) correctly uses index=False. Other options use incorrect or non-existent parameters.

3. Final Answer:

   df.to_excel('data.xlsx', index=False) -> Option D

4. Quick Check:

   Exclude row numbers = index=False [OK]

Hint: Use index=False to hide row numbers [OK]

Common Mistakes:

• Using wrong parameter names like row_numbers or no_index
• Forgetting to set index=False to hide row numbers
• Confusing index with header

3. Given the code:

import pandas as pd
df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df.to_excel('output.xlsx', sheet_name='Sheet2', index=True)

What will be the name of the Excel sheet and will row numbers be included?

medium

A. Sheet name is 'Sheet2' and row numbers are included

B. Sheet name is 'Sheet1' and row numbers are included

C. Sheet name is 'Sheet2' and row numbers are excluded

D. Sheet name is 'Sheet1' and row numbers are excluded

Solution

1. Step 1: Check the sheet_name parameter

   The code sets sheet_name='Sheet2', so the Excel sheet will be named 'Sheet2'.

2. Step 2: Check the index parameter

   The code sets index=True, so row numbers will be included in the Excel file.

3. Final Answer:

   Sheet name is 'Sheet2' and row numbers are included -> Option A

4. Quick Check:

   sheet_name='Sheet2' and index=True [OK]

Hint: sheet_name sets tab name; index=True includes row numbers [OK]

Common Mistakes:

• Assuming default sheet name 'Sheet1' when sheet_name is set
• Forgetting index=True includes row numbers
• Confusing index with header

4. What is wrong with this code snippet?

df.to_excel('file.xlsx', sheet='Data', index=False)

medium

A. index=False is not a valid parameter

B. The file extension should be '.xls' not '.xlsx'

C. The parameter 'sheet' is invalid; it should be 'sheet_name'

D. The DataFrame must be converted to CSV before saving as Excel

Solution

1. Step 1: Check parameter names for to_excel()

   The correct parameter to set the sheet name is sheet_name, not sheet.

2. Step 2: Validate other parts of the code

   The file extension '.xlsx' is correct, and index=False is valid. No need to convert to CSV first.

3. Final Answer:

   The parameter 'sheet' is invalid; it should be 'sheet_name' -> Option C

4. Quick Check:

   Use sheet_name, not sheet [OK]

Hint: Use sheet_name to name Excel sheet [OK]

Common Mistakes:

• Using 'sheet' instead of 'sheet_name'
• Thinking index=False is invalid
• Confusing file extensions for Excel

5. You have a DataFrame df with columns ['Name', 'Age', 'Score']. You want to export it to Excel with the sheet named 'Results', exclude row numbers, and save it as results.xlsx. Which code snippet correctly does this?

hard

A. df.to_excel('results.xlsx', sheet_name='Results', index=False)

B. df.to_excel('results.xlsx', sheet='Results', index=False)

C. df.to_excel('results.xlsx', sheet_name='Results', no_index=True)

D. df.to_excel('results.xlsx', sheet_name='Results', include_index=False)

Solution

1. Step 1: Set the correct file name and sheet name

   The file name should be 'results.xlsx' and the sheet name parameter is sheet_name='Results'.

2. Step 2: Exclude row numbers correctly

   To exclude row numbers, use index=False. Other options use invalid parameters.

3. Final Answer:

   df.to_excel('results.xlsx', sheet_name='Results', index=False) -> Option A

4. Quick Check:

   sheet_name='Results' and index=False [OK]

Hint: Use sheet_name and index=False to customize Excel export [OK]

Common Mistakes:

• Using 'sheet' instead of 'sheet_name'
• Using invalid parameters like no_index or include_index
• Forgetting to exclude row numbers with index=False