Importing Pandas conventions - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this code importing pandas?

Consider the following code snippet importing pandas and creating a DataFrame. What will be the output when printing df.head()?

Pandas

import pandas as pd

data = {'Name': ['Anna', 'Bob', 'Cara'], 'Age': [28, 34, 29]}
df = pd.DataFrame(data)
print(df.head())

A

Name Age
0 Anna 28
1 Bob 34
2 Cara 29

B

Name  Age
Anna  28
Bob   34
Cara  29

C

   Name  Age
1  Anna   28
2   Bob   34
3  Cara   29

D

   Name  Age
0  Anna   28
1   Bob   34
2  Cara   29

💡 Hint

Remember that df.head() shows the first 5 rows with index and columns.

The pd.DataFrame creates a table with columns 'Name' and 'Age'. The head() method shows the first rows with their index starting at 0. The output includes the column headers and row indices.

❓ data_output

intermediate

What is the shape of the DataFrame after importing pandas and creating it?

Given this code, what is the shape (rows, columns) of the DataFrame df?

Pandas

import pandas as pd

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

A (4, 2)

B (2, 4)

C (3, 2)

D (4, 1)

💡 Hint

Shape shows (number of rows, number of columns).

The dictionary has 4 cities, so 4 rows, and 2 keys, so 2 columns. The shape is (4, 2).

🔧 Debug

advanced

Which option causes an error when importing pandas?

Which of the following import statements will cause an error?

A import pandas

B from pandas import DataFrame

C import panda as pd

D import pandas as pd

💡 Hint

Check the spelling of the library name.

Option C uses 'panda' instead of 'pandas', which is not a valid module name and causes a ModuleNotFoundError.

🧠 Conceptual

advanced

Why do we use import pandas as pd instead of just import pandas?

What is the main reason for importing pandas with an alias like pd?

A To shorten the code and make it easier to type pandas functions.

B Because pandas cannot be imported without an alias.

C To avoid conflicts with other libraries named pandas.

D To automatically load all pandas functions into the global namespace.

💡 Hint

Think about typing convenience and code readability.

Using as pd creates a short alias so you can write pd.DataFrame() instead of pandas.DataFrame(), making code shorter and easier to read.

🚀 Application

expert

What is the output of this code using pandas import conventions?

Given the code below, what will be printed?

Pandas

import pandas as pd

s = pd.Series([10, 20, 30], index=['a', 'b', 'c'])
print(s['b'])

A 10

B 20

C b

D KeyError

💡 Hint

Accessing a Series by index label returns the value at that label.

The Series s has values 10, 20, 30 with labels 'a', 'b', 'c'. Accessing s['b'] returns 20.

Practice

1. Why do we usually import pandas using import pandas as pd in Python?

easy

A. To avoid importing other libraries

B. Because pandas only works if imported as pd

C. To use a shorter name pd for easier coding

D. To automatically load data files

Solution

1. Step 1: Understand the import statement

   The statement import pandas as pd assigns the short name pd to the pandas library.

2. Step 2: Reason why short names help

   Using pd makes code shorter and easier to write, especially when calling pandas functions repeatedly.

3. Final Answer:

   To use a shorter name pd for easier coding -> Option C

4. Quick Check:

   Short alias = easier code [OK]

Hint: Short alias pd saves typing pandas repeatedly [OK]

Common Mistakes:

• Thinking pandas only works if imported as pd
• Confusing import alias with library functionality
• Believing import loads data automatically

2. Which of the following is the correct way to import pandas with the common alias?

easy

A. import pd as pandas

B. import pandas pd

C. from pandas import pd

D. import pandas as pd

Solution

1. Step 1: Recall correct import syntax

   The correct syntax to import a library with an alias is import library_name as alias.

2. Step 2: Check each option

   Only import pandas as pd follows this syntax correctly: import pandas as pd. Others have syntax errors or wrong order.

3. Final Answer:

   import pandas as pd -> Option D

4. Quick Check:

   Correct import syntax = import pandas as pd [OK]

Hint: Remember: import library as alias [OK]

Common Mistakes:

• Omitting 'as' keyword
• Swapping alias and library names
• Using 'from' incorrectly for aliasing

3. What will be the output of this code?

import pandas as pd
df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
print(df.head())

medium

A. Prints the first 5 rows of the DataFrame

B. Prints an error because head() needs arguments

C. Prints the entire DataFrame regardless of size

D. Prints only the column names

Solution

1. Step 1: Understand what pd.DataFrame does

   This creates a small table with columns 'A' and 'B' and two rows of data.

2. Step 2: Understand df.head() behavior

   The head() method prints the first 5 rows by default. Since the DataFrame has only 2 rows, it prints both rows.

3. Final Answer:

   Prints the first 5 rows of the DataFrame -> Option A

4. Quick Check:

   head() shows first 5 rows [OK]

Hint: head() shows first 5 rows by default [OK]

Common Mistakes:

• Thinking head() requires arguments
• Expecting an error for small DataFrame
• Confusing head() with printing columns only

4. Identify the error in this code snippet:

import pandas pd
df = pd.DataFrame({'x': [1,2,3]})
print(df)

medium

A. Missing 'as' keyword in import statement

B. DataFrame is not a pandas function

C. Dictionary keys must be strings

D. print() cannot display DataFrames

Solution

1. Step 1: Check the import statement syntax

   The import statement is written as import pandas pd, which is missing the as keyword for aliasing.

2. Step 2: Understand correct import syntax

   The correct syntax is import pandas as pd. Without as, Python raises a syntax error.

3. Final Answer:

   Missing 'as' keyword in import statement -> Option A

4. Quick Check:

   Import alias needs 'as' keyword [OK]

Hint: Always use 'as' when aliasing imports [OK]

Common Mistakes:

• Forgetting 'as' keyword
• Assuming DataFrame is not from pandas
• Thinking print() can't show DataFrames

5. You want to import pandas and read a CSV file named 'data.csv' into a DataFrame using the common alias. Which code snippet is correct?

hard

A. import pandas
read_csv = pandas('data.csv')

B. import pandas as pd
df = pd.read_csv('data.csv')

C. import pandas as pd
df = pd.read('data.csv')

D. from pandas import read_csv
df = read_csv('data.csv')

Solution

1. Step 1: Check import and alias usage

   import pandas as pd df = pd.read_csv('data.csv') imports pandas as pd, which is the common convention.

2. Step 2: Verify reading CSV syntax

   import pandas as pd df = pd.read_csv('data.csv') uses pd.read_csv('data.csv'), the correct function to read CSV files into a DataFrame.

3. Step 3: Review other options for errors

   import pandas read_csv = pandas('data.csv') misses function call syntax; import pandas as pd df = pd.read('data.csv') uses wrong function name; from pandas import read_csv df = read_csv('data.csv') imports without alias but is valid but not the common alias convention.

4. Final Answer:

   import pandas as pd df = pd.read_csv('data.csv') -> Option B

5. Quick Check:

   Common alias + read_csv = import pandas as pd df = pd.read_csv('data.csv') [OK]

Hint: Use import pandas as pd then pd.read_csv() [OK]

Common Mistakes:

• Using wrong function name like read()
• Not using alias when calling functions
• Incorrect import syntax