Box plots in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a box plot of the 'age' column using pandas.

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'age': [23, 45, 31, 35, 22, 40, 29, 50]}
df = pd.DataFrame(data)
df.boxplot(column=[1])
plt.show()

Drag options to blanks, or click blank then click option'

Aage

B'age'

C'Age'

Ddf['age']

Attempts:

3 left

💡 Hint

Common Mistakes

Using the column variable without quotes causes an error.

Passing the entire series instead of the column name.

The boxplot method requires the column name as a string, so we use 'age'.

2fill in blank

medium

Complete the code to create a box plot for the 'score' column with a grid.

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'score': [88, 92, 79, 93, 85, 90, 87, 95]}
df = pd.DataFrame(data)
df.boxplot(column=[1], grid=True)
plt.show()

Drag options to blanks, or click blank then click option'

A'score'

Bscore

C'Score'

Ddf['score']

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the column name without quotes.

Using the wrong case for the column name.

The column name must be a string, so 'score' is correct.

3fill in blank

hard

Fix the error in the code to plot a box plot for the 'height' column.

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'height': [160, 170, 165, 180, 175, 168, 172, 169]}
df = pd.DataFrame(data)
df.boxplot(column=[1])
plt.show()

Drag options to blanks, or click blank then click option'

A'height'

Bheight

Cdf['height']

D'Height'

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the column variable without quotes.

Using the wrong case for the column name.

The boxplot method needs the column name as a string, so 'height' is correct.

4fill in blank

hard

Fill both blanks to create a box plot for the 'weight' column and set the color to 'green'.

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'weight': [70, 80, 75, 85, 90, 78, 82, 77]}
df = pd.DataFrame(data)
df.boxplot(column=[1], color=[2])
plt.show()

Drag options to blanks, or click blank then click option'

A'weight'

B'blue'

C'green'

D'Weight'

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong case for column name.

Passing color without quotes.

The column name must be a string 'weight', and the color string 'green' sets the box plot color.

5fill in blank

hard

Fill all three blanks to create a box plot for the 'salary' column, set the grid to True, and change the box color to 'red'.

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'salary': [50000, 60000, 55000, 65000, 70000, 62000, 58000, 63000]}
df = pd.DataFrame(data)
df.boxplot(column=[1], grid=[2], color=[3])
plt.show()

Drag options to blanks, or click blank then click option'

A'Salary'

BTrue

C'red'

D'salary'

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong case for column name.

Passing grid as a string instead of boolean.

Forgetting quotes around color.

The column name must be 'salary', grid set to True enables the grid, and color 'red' changes the box color.

Practice

1. What does a box plot primarily show about a dataset?

easy

A. Only the average value of the data

B. The spread, median, and outliers of the data

C. The exact values of all data points

D. The correlation between two variables

Solution

1. Step 1: Understand box plot components

   A box plot shows the median line, the box representing the middle 50% of data, and whiskers for spread.

2. Step 2: Identify what it reveals

   It highlights the data spread, median, and any outliers beyond whiskers.

3. Final Answer:

   The spread, median, and outliers of the data -> Option B

4. Quick Check:

   Box plot = spread + median + outliers [OK]

Hint: Box plots show spread and outliers, not just averages [OK]

Common Mistakes:

• Thinking box plots show all data points exactly
• Confusing box plots with scatter plots
• Assuming box plots show correlation

2. Which of the following is the correct way to create a box plot for a pandas DataFrame named df?

easy

A. boxplot(df)

B. df.plot.boxplot()

C. df.boxplot()

D. df.box()

Solution

1. Step 1: Recall pandas box plot syntax

   The pandas DataFrame method to create a box plot is boxplot().

2. Step 2: Check each option

   df.boxplot() uses df.boxplot(), which is correct. df.plot.boxplot() is invalid syntax. boxplot(df) is not a pandas function. df.box() is invalid.

3. Final Answer:

   df.boxplot() -> Option C

4. Quick Check:

   Use df.boxplot() to plot box plots [OK]

Hint: Use df.boxplot() to create box plots in pandas [OK]

Common Mistakes:

• Using df.plot.boxplot() which is invalid
• Trying to call boxplot as a standalone function
• Using df.box() which does not exist

3. Given the following code, what will be the output type of ax?

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({
    'A': [1, 2, 5, 7, 9],
    'B': [2, 3, 5, 8, 10]
})
ax = df.boxplot()

medium

A. A matplotlib AxesSubplot object

B. A list of numbers

C. A pandas DataFrame

D. A matplotlib Figure object

Solution

1. Step 1: Understand df.boxplot() return type

   The boxplot() method returns a matplotlib AxesSubplot object representing the plot area.

2. Step 2: Check options against expected type

   The return type is a matplotlib AxesSubplot object. This is not a pandas DataFrame, not a list of numbers, and not a matplotlib Figure object.

3. Final Answer:

   A matplotlib AxesSubplot object -> Option A

4. Quick Check:

   df.boxplot() returns AxesSubplot [OK]

Hint: df.boxplot() returns a matplotlib Axes object [OK]

Common Mistakes:

• Expecting a DataFrame or list as output
• Confusing Figure and Axes objects
• Assuming no return value

4. What is wrong with this code snippet that tries to create a box plot grouped by a column?

import pandas as pd
df = pd.DataFrame({
    'Category': ['X', 'X', 'Y', 'Y'],
    'Value': [10, 15, 10, 20]
})
df.boxplot(column='Value', by='Category', groupby='Category')

medium

A. The argument 'groupby' is invalid for boxplot()

B. The 'by' argument should be 'groupby'

C. The 'column' argument should be a list, not a string

D. The DataFrame is missing numeric columns

Solution

1. Step 1: Check boxplot() arguments

   The pandas boxplot method accepts 'column' and 'by' arguments, but not 'groupby'.

2. Step 2: Identify invalid argument

   The code incorrectly uses 'groupby' which causes an error. 'by' is correct for grouping.

3. Final Answer:

   The argument 'groupby' is invalid for boxplot() -> Option A

4. Quick Check:

   Use 'by' to group, no 'groupby' argument [OK]

Hint: Use 'by' to group in boxplot(), not 'groupby' [OK]

Common Mistakes:

• Using 'groupby' instead of 'by' argument
• Passing column as list when string is allowed
• Thinking numeric columns are missing

5. You have a DataFrame df with columns "Group" and "Score". You want to compare the score distributions for each group side by side using box plots. Which code correctly achieves this?

hard

A. df.boxplot(by='Score', column='Group')

B. df.groupby('Group').boxplot(column='Score')

C. df.plot.box(by='Group', column='Score')

D. df.boxplot(column='Score', by='Group')

Solution

1. Step 1: Understand grouping in boxplot()

   To compare groups side by side, use boxplot() with column as the numeric data and by as the grouping column.

2. Step 2: Evaluate each option

   df.boxplot(column='Score', by='Group') correctly uses column='Score' and by='Group'. df.groupby('Group').boxplot(column='Score') tries to group then boxplot, which returns multiple plots, not side by side. df.plot.box(by='Group', column='Score') uses invalid syntax. df.boxplot(by='Score', column='Group') swaps column and by incorrectly.

3. Final Answer:

   df.boxplot(column='Score', by='Group') -> Option D

4. Quick Check:

   Use column=score and by=group for grouped boxplots [OK]

Hint: Use df.boxplot(column='Score', by='Group') for grouped box plots [OK]

Common Mistakes:

• Using groupby().boxplot() which plots separately
• Swapping column and by arguments
• Using invalid plot syntax