head() and tail() in Data Analysis Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of head() with default parameter

What will be the output of the following code snippet?

Data Analysis Python

import pandas as pd

data = {'Name': ['Anna', 'Bob', 'Charlie', 'David', 'Eva'], 'Age': [23, 35, 45, 28, 32]}
df = pd.DataFrame(data)
print(df.head())

A [{'Name': 'Anna', 'Age': 23}, {'Name': 'Bob', 'Age': 35}, {'Name': 'Charlie', 'Age': 45}, {'Name': 'David', 'Age': 28}, {'Name': 'Eva', 'Age': 32}]

B [{'Name': 'Anna', 'Age': 23}, {'Name': 'Bob', 'Age': 35}, {'Name': 'Charlie', 'Age': 45}]

C [{'Name': 'Anna', 'Age': 23}, {'Name': 'Bob', 'Age': 35}, {'Name': 'Charlie', 'Age': 45}, {'Name': 'David', 'Age': 28}]

D [{'Name': 'Anna', 'Age': 23}, {'Name': 'Bob', 'Age': 35}]

💡 Hint

head() by default shows the first 5 rows of the DataFrame.

The head() method without any argument returns the first 5 rows of the DataFrame. Since the DataFrame has exactly 5 rows, all rows are shown.

❓ Predict Output

intermediate

Output of tail() with parameter 3

What will be the output of this code?

Data Analysis Python

import pandas as pd

data = {'City': ['NY', 'LA', 'Chicago', 'Houston', 'Phoenix'], 'Population': [8.4, 4.0, 2.7, 2.3, 1.7]}
df = pd.DataFrame(data)
print(df.tail(3))

A [{'City': 'Chicago', 'Population': 2.7}, {'City': 'Houston', 'Population': 2.3}, {'City': 'Phoenix', 'Population': 1.7}]

B [{'City': 'NY', 'Population': 8.4}, {'City': 'LA', 'Population': 4.0}, {'City': 'Chicago', 'Population': 2.7}]

C [{'City': 'Houston', 'Population': 2.3}, {'City': 'Phoenix', 'Population': 1.7}]

D [{'City': 'Phoenix', 'Population': 1.7}]

💡 Hint

tail(3) shows the last 3 rows of the DataFrame.

The tail(3) method returns the last 3 rows of the DataFrame, which are Chicago, Houston, and Phoenix.

❓ data_output

advanced

Number of rows returned by head() and tail() combined

Given a DataFrame with 10 rows, what is the total number of rows returned when you combine df.head(7) and df.tail(5)?

A 7

B 10

C 12

D 5

💡 Hint

head(7) returns first 7 rows, tail(5) returns last 5 rows. Some rows overlap.

The first 7 rows and last 5 rows overlap on rows 3 to 7, so total unique rows are 10.

🔧 Debug

advanced

Identify the error in using head()

What error will this code produce and why? import pandas as pd data = {'A': [1,2,3,4,5]} df = pd.DataFrame(data) print(df.head(-3))

Data Analysis Python

import pandas as pd

data = {'A': [1,2,3,4,5]}
df = pd.DataFrame(data)
print(df.head(-3))

A ValueError: negative value not allowed

B SyntaxError

C Empty DataFrame with 0 rows

D TypeError

💡 Hint

head() with a negative argument returns an empty DataFrame.

pandas treats a negative value passed to head() as 0, so df.head(-3) returns an empty DataFrame with 0 rows. No error or exception is raised.

🚀 Application

expert

Using head() and tail() to sample data

You have a DataFrame with 1000 rows sorted by date ascending. You want to create a new DataFrame that contains the first 10 and last 10 rows combined without duplicates. Which code snippet correctly achieves this?

A pd.concat([df.head(10), df.tail(10)])

B df.head(10).append(df.tail(10))

C df.head(10) + df.tail(10)

D pd.concat([df.head(10), df.tail(10)]).drop_duplicates()

💡 Hint

Use concat and drop_duplicates to avoid repeated rows.

Option D concatenates first 10 and last 10 rows and removes duplicates, ensuring no repeated rows if overlap exists.