Writing to CSV with to_csv in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the content of the CSV file after running this code?

Consider the following Python code using pandas to write a DataFrame to a CSV file. What will be the content of the CSV file?

Pandas

import pandas as pd

df = pd.DataFrame({'Name': ['Alice', 'Bob'], 'Age': [25, 30]})
df.to_csv('output.csv', index=False)

A "Name;Age\nAlice;25\nBob;30\n"

B ",Name,Age\n0,Alice,25\n1,Bob,30\n"

C "Name,Age\n0,Alice,25\n1,Bob,30\n"

D "Name,Age\nAlice,25\nBob,30\n"

💡 Hint

Check the index parameter in to_csv and the default separator.

Since index=False, the row numbers are not saved. The default separator is a comma, so the CSV content has columns Name and Age separated by commas.

❓ data_output

intermediate

How many rows will the CSV file contain after this code runs?

This code writes a DataFrame to a CSV file. How many rows (including header) will the CSV file have?

Pandas

import pandas as pd

df = pd.DataFrame({'City': ['NY', 'LA', 'Chicago'], 'Population': [8000000, 4000000, 2700000]})
df.to_csv('cities.csv', index=True)

A 3

B 4

C 5

D 2

💡 Hint

Remember that index=True adds an index column and the header row is also counted.

The DataFrame has 3 rows. With index=True, the index is saved as a column. The CSV includes a header row, so total rows = 3 data rows + 1 header = 4.

🔧 Debug

advanced

What error does this code raise when writing to CSV?

Look at this code snippet. What error will it raise when executed?

Pandas

import pandas as pd

df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df.to_csv('data.csv', sep=';')
df.to_csv('data.csv', sep=',', header=False, index=False, mode='x')

A FileExistsError

B ValueError

C No error, runs successfully

D TypeError

💡 Hint

Check the meaning of mode='x' when opening files.

The first to_csv creates 'data.csv'. The second call uses mode='x', which tries to create a new file but fails if the file exists, raising FileExistsError.

🚀 Application

advanced

Which option correctly writes a DataFrame to CSV with tab separator and no header?

You want to save a DataFrame to a CSV file using a tab character as separator and without writing the header row. Which code does this correctly?

Pandas

import pandas as pd

df = pd.DataFrame({'X': [10, 20], 'Y': [30, 40]})

A df.to_csv('file.tsv', sep='\t', header=False)

B df.to_csv('file.tsv', sep='\t', index=False, header=True)

C df.to_csv('file.tsv', sep='\t', header=False, index=True)

D df.to_csv('file.tsv', sep='\t', index=False)

💡 Hint

Check the parameters sep and header in to_csv.

Option A sets sep='\t' for tab separator and header=False to omit the header row. This matches the requirement exactly.

🧠 Conceptual

expert

What is the effect of using line_terminator='\r\n' in to_csv?

When writing a CSV file with pandas to_csv, what does setting line_terminator='\r\n' do?

A It adds extra blank lines between rows in the CSV file.

B It causes an error because <code>line_terminator</code> only accepts single characters.

C It changes the line ending to Windows style CRLF instead of the default LF.

D It removes all line breaks, writing the CSV as a single line.

💡 Hint

Think about different operating systems and their line ending conventions.

Windows uses carriage return + line feed (\r\n) as line endings. Setting line_terminator='\r\n' makes the CSV use Windows-style line breaks instead of the default Unix-style \n.

Practice

1.

What does the to_csv function in pandas do?

easy

A. Converts a CSV file to Excel format

B. Reads a CSV file into a DataFrame

C. Deletes a CSV file from disk

D. Saves a DataFrame to a CSV file

Solution

1. Step 1: Understand the purpose of to_csv

   The to_csv function is used to save or export a pandas DataFrame to a CSV file format.

2. Step 2: Differentiate from other file operations

   Reading CSV files uses read_csv, deleting files is done by OS commands, and converting formats requires other tools.

3. Final Answer:

   Saves a DataFrame to a CSV file -> Option D

4. Quick Check:

   to_csv = Save DataFrame [OK]

Hint: Remember: 'to_csv' means saving data out [OK]

Common Mistakes:

• Confusing to_csv with read_csv
• Thinking it deletes files
• Assuming it converts file formats automatically

2.

Which of the following is the correct syntax to save a DataFrame df to a CSV file named data.csv without saving the row index?

import pandas as pd
df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
# Save df to CSV here

easy

A. df.to_csv('data.csv', index=False)

B. df.to_csv('data.csv', save_index=False)

C. df.to_csv('data.csv', no_index=True)

D. df.to_csv('data.csv', index=0)

Solution

1. Step 1: Recall the parameter to exclude row index

   The parameter to exclude the row index when saving is index=False.

2. Step 2: Check the syntax correctness

   df.to_csv('data.csv', index=False) uses index=False correctly. Other options use invalid parameter names or values.

3. Final Answer:

   df.to_csv('data.csv', index=False) -> Option A

4. Quick Check:

   Exclude index = index=False [OK]

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

Common Mistakes:

• Using wrong parameter names like save_index or no_index
• Passing index=0 instead of index=False
• Forgetting to set index=False to exclude row numbers

3.

What will be the content of the file output.csv after running this code?

import pandas as pd
df = pd.DataFrame({'Name': ['Anna', 'Bob'], 'Age': [28, 34]})
df.to_csv('output.csv', index=False)

Choose the correct CSV content:

medium

A. 0,"Anna",28
1,"Bob",34

B. Name,Age
Anna,28
Bob,34

C. "Name","Age"
0,"Anna",28
1,"Bob",34

D. "Name","Age"
"Anna",28
"Bob",34

Solution

1. Step 1: Understand the effect of index=False

   Setting index=False means row numbers (0,1) are not saved in the CSV file.

2. Step 2: Check the CSV formatting

   By default, pandas writes headers and values without quotes unless needed. So names appear without quotes, and no index column is present.

3. Final Answer:

   Name,Age Anna,28 Bob,34 -> Option B

4. Quick Check:

   index=False means no row numbers in CSV [OK]

Hint: index=False removes row numbers from CSV output [OK]

Common Mistakes:

• Expecting row numbers to be saved when index=False
• Confusing quotes around strings in CSV
• Assuming index is saved by default without setting

4.

Identify the error in this code snippet that tries to save a DataFrame df to CSV without the index:

import pandas as pd
df = pd.DataFrame({'X': [10, 20], 'Y': [30, 40]})
df.to_csv('file.csv', index=No)

medium

A. The parameter index should be False, not No

B. The filename must be a full path, not just 'file.csv'

C. DataFrame df is not defined correctly

D. The to_csv function cannot exclude the index

Solution

1. Step 1: Check the parameter value for index

   The index parameter expects a boolean: True or False. Using No is invalid and causes an error.

2. Step 2: Validate other parts of the code

   The filename 'file.csv' is valid, and the DataFrame is correctly defined. The to_csv function supports excluding the index.

3. Final Answer:

   The parameter index should be False, not No -> Option A

4. Quick Check:

   Use True/False for boolean parameters [OK]

Hint: Boolean parameters need True or False, not No/Yes [OK]

Common Mistakes:

• Using 'No' or 'Yes' instead of False/True
• Thinking filename must be full path
• Assuming to_csv can't exclude index

5.

You have a DataFrame df with columns ['Name', 'Score']. You want to save it as a CSV file named results.csv using a semicolon ; as the separator, UTF-8 encoding, and without saving the row index. Which code snippet correctly does this?

hard

A. df.to_csv('results.csv', sep=';', encoding='utf-8')

B. df.to_csv('results.csv', separator=';', encoding='utf8')

C. df.to_csv('results.csv', sep=';', encoding='utf-8', index=False)

D. df.to_csv('results.csv', sep=';', encoding='utf-8', no_index=True)

Solution

1. Step 1: Set separator and encoding parameters correctly

   The separator parameter is sep, and encoding should be 'utf-8'. df.to_csv('results.csv', sep=';', encoding='utf-8', index=False) uses both correctly.

2. Step 2: Exclude the index if not needed

   To exclude row numbers, use index=False. df.to_csv('results.csv', sep=';', encoding='utf-8', index=False) includes this correctly; df.to_csv('results.csv', sep=';', encoding='utf-8') misses it, so index will be saved.

3. Final Answer:

   df.to_csv('results.csv', sep=';', encoding='utf-8', index=False) -> Option C

4. Quick Check:

   Use sep and encoding with index=False to customize CSV [OK]

Hint: Use sep=';' and encoding='utf-8' with index=False [OK]

Common Mistakes:

• Using 'separator' instead of 'sep'
• Forgetting index=False to exclude row numbers
• Using no_index=True which is invalid