Box plots in Pandas - Mini Project: Build & Apply

Box plots

📖 Scenario: You work as a data analyst for a small company. You have collected sales data for different products over several months. You want to understand the spread and distribution of sales numbers to find out if there are any unusual values or differences between products.

🎯 Goal: Build a simple program that creates a box plot to visualize the sales data for different products using pandas.

📋 What You'll Learn

Create a pandas DataFrame with sales data for three products over five months.

Set a configuration variable for the column names to plot.

Use pandas box plot function to create the box plot for the selected products.

Print the box plot object to confirm the plot was created.

💡 Why This Matters

🌍 Real World

Box plots help analysts quickly see the distribution, spread, and outliers in sales or other numeric data, which is useful for business decisions.

💼 Career

Data analysts and scientists often use box plots to summarize data distributions and detect unusual values before deeper analysis.

1

Create the sales data DataFrame

Create a pandas DataFrame called sales_data with these exact values: columns 'Month', 'Product_A', 'Product_B', 'Product_C'. The 'Month' column should have values ['Jan', 'Feb', 'Mar', 'Apr', 'May']. The sales numbers for 'Product_A' are [100, 120, 130, 90, 110], for 'Product_B' are [80, 85, 88, 90, 95], and for 'Product_C' are [150, 160, 170, 165, 155]. Import pandas as pd first.

Pandas

import pandas as pd
# Create the sales_data DataFrame with the exact columns and values
# Your code here

Hint

Use pd.DataFrame with a dictionary where keys are column names and values are lists of data.

2

Set the columns to plot

Create a list variable called products that contains the exact strings 'Product_A', 'Product_B', and 'Product_C'. This list will be used to select columns for the box plot.

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Month': ['Jan', 'Feb', 'Mar', 'Apr', 'May'],
    'Product_A': [100, 120, 130, 90, 110],
    'Product_B': [80, 85, 88, 90, 95],
    'Product_C': [150, 160, 170, 165, 155]
})
# Create a list called products with 'Product_A', 'Product_B', 'Product_C'
# Your code here

Hint

Just create a list with the exact product column names.

3

Create the box plot

Use the boxplot method on sales_data to create a box plot for the columns in the products list. Save the result in a variable called boxplot_result.

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Month': ['Jan', 'Feb', 'Mar', 'Apr', 'May'],
    'Product_A': [100, 120, 130, 90, 110],
    'Product_B': [80, 85, 88, 90, 95],
    'Product_C': [150, 160, 170, 165, 155]
})
products = ['Product_A', 'Product_B', 'Product_C']
# Create a box plot for the products columns and save it to boxplot_result
# Your code here

Hint

Use sales_data.boxplot(column=products) to create the box plot.

4

Display the box plot result

Print the boxplot_result variable to show the box plot object.

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Month': ['Jan', 'Feb', 'Mar', 'Apr', 'May'],
    'Product_A': [100, 120, 130, 90, 110],
    'Product_B': [80, 85, 88, 90, 95],
    'Product_C': [150, 160, 170, 165, 155]
})
products = ['Product_A', 'Product_B', 'Product_C']
boxplot_result = sales_data.boxplot(column=products)
# Print the boxplot_result variable
# Your code here

Hint

Use print(boxplot_result) to display the plot object.

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