Reading CSV files with read_csv in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

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

Consider a CSV file named data.csv with the following content:

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

What will be the output of this code snippet?

Pandas

import pandas as pd
from io import StringIO
csv_data = "name|age|city\nAlice|30|New York\nBob|25|Los Angeles"
df = pd.read_csv(StringIO(csv_data), delimiter='|')
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: delimiter parameter is invalid

💡 Hint

Check how the delimiter parameter changes how pandas splits columns.

The delimiter '|' tells pandas to split columns at the pipe character. So the DataFrame has columns 'name', 'age', and 'city' with correct values.

❓ data_output

intermediate

How many rows does this DataFrame have after reading a CSV with skiprows?

Given a CSV content:

id,value
1,100
2,200
3,300
4,400

What is the number of rows in the DataFrame after running this code?

Pandas

import pandas as pd
from io import StringIO
csv_data = "id,value\n1,100\n2,200\n3,300\n4,400"
df = pd.read_csv(StringIO(csv_data), skiprows=1)
print(len(df))

A 3

B 4

C 1

D 0

💡 Hint

skiprows=1 skips the first line of the file.

skiprows=1 skips the first line which is the header, so pandas treats the second line as header and reads 3 data rows.

🔧 Debug

advanced

What error does this code raise when reading a CSV with wrong header parameter?

This code tries to read a CSV but sets header=5:

import pandas as pd
from io import StringIO
csv_data = "a,b,c\n1,2,3\n4,5,6"
df = pd.read_csv(StringIO(csv_data), header=5)

What error will it raise?

Pandas

import pandas as pd
from io import StringIO
csv_data = "a,b,c\n1,2,3\n4,5,6"
df = pd.read_csv(StringIO(csv_data), header=5)

A pandas.errors.ParserError

B IndexError

C No error, DataFrame with empty columns

D ValueError: Passed header row index 5 is out of range

💡 Hint

Check what happens if header row index is beyond file lines.

Setting header=5 means pandas looks for the header at line 6 (0-based), but the file has only 3 lines, so it raises a ValueError.

🚀 Application

advanced

Which option correctly reads a CSV file ignoring the first two rows and using the third row as header?

You have a CSV file where the first two rows are metadata and the third row contains column names. Which code reads the file correctly?

A pd.read_csv('file.csv', header=2)

B pd.read_csv('file.csv', skiprows=[0,1], header=0)

C pd.read_csv('file.csv', skiprows=2, header=2)

D pd.read_csv('file.csv', skiprows=2, header=0)

💡 Hint

Remember skiprows can take a list of rows to skip.

skiprows=[0,1] skips the first two rows, then header=0 uses the next row as header. This correctly reads the third row as header.

🧠 Conceptual

expert

What is the effect of setting index_col=False in pd.read_csv?

When reading a CSV file, what happens if you set index_col=False?

A The CSV file is read but all columns become index columns.

B The first column is used as the index of the DataFrame.

C No column is used as the index; pandas uses default integer index.

D Raises a TypeError because index_col must be int or str.

💡 Hint

Check pandas documentation for index_col parameter behavior.

Setting index_col=False tells pandas not to use any column as index, so it uses the default integer index.