read_csv parameters (sep, header, index_col) in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this code reading CSV with custom separator?

Given the CSV content below and the code reading it with pandas, what will be the output DataFrame?

Pandas

import pandas as pd
from io import StringIO
csv_data = '''name|age|city
Alice|30|New York
Bob|25|Los Angeles
'''
df = pd.read_csv(StringIO(csv_data), sep='|')
print(df)

A

    name|age|city
0  Alice|30|New York
1    Bob|25|Los Angeles

B

    name  age         city
0  Alice   30     New York
1    Bob   25  Los Angeles

C

    name  age  city
0  Alice   30  New York
1    Bob   25  Los Angeles

D Error: ParserError due to wrong separator

💡 Hint

Check how the separator parameter affects how pandas splits columns.

The separator '|' tells pandas to split columns at the pipe character. Without it, pandas treats the whole line as one column.

❓ data_output

intermediate

What is the index of the DataFrame after reading CSV with index_col?

Given this CSV and code, what will be the index values of the resulting DataFrame?

Pandas

import pandas as pd
from io import StringIO
csv_data = '''id,name,score
101,Alice,88
102,Bob,92
'''
df = pd.read_csv(StringIO(csv_data), index_col='id')
print(df.index.tolist())

A [101, 102]

B [0, 1]

C ['id', 'name', 'score']

D Error: KeyError for index_col

💡 Hint

index_col sets which column becomes the row labels (index).

Setting index_col='id' makes the 'id' column the index, so index values are 101 and 102.

🔧 Debug

advanced

Why does this code raise a ParserError?

This code tries to read a CSV but raises a ParserError. What is the cause?

Pandas

import pandas as pd
from io import StringIO
csv_data = '''name,age,city
Alice,30
Bob,25,Los Angeles
'''
df = pd.read_csv(StringIO(csv_data))

A Because the separator is incorrect

B Because header is set to None

C Because index_col is missing

D Because the second row has fewer columns than the header

💡 Hint

Check if all rows have the same number of columns as the header.

The second row has only two values but the header has three columns, causing a parsing error.

🧠 Conceptual

advanced

How does the header parameter affect reading CSV files?

Which statement correctly describes the effect of setting header=None in pd.read_csv?

A The first row is skipped and not read

B The first row is treated as column names

C The first row is treated as data, and pandas assigns default integer column names

D The file is read without any columns

💡 Hint

Think about what happens if pandas does not use the first row as headers.

Setting header=None tells pandas not to treat the first row as column names, so it uses default numbers as column names and reads the first row as data.

🚀 Application

expert

Which code produces a DataFrame with 'date' as index and columns 'temp' and 'humidity' from a semicolon-separated CSV?

You have a CSV with columns: date;temp;humidity. Which code correctly reads it with 'date' as index?

A pd.read_csv('file.csv', sep=';', index_col='date')

B pd.read_csv('file.csv', sep=',', index_col='date')

C pd.read_csv('file.csv', sep=';', header=None, index_col=0)

D pd.read_csv('file.csv', index_col='date')

💡 Hint

Check the separator and index_col parameters carefully.

The CSV uses semicolon separator, so sep=';' is needed. index_col='date' sets the 'date' column as index. Option A uses wrong separator, C ignores header, D uses default separator.