Violin plot with plt.violinplot in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a violin plot of the data list.

Matplotlib

import matplotlib.pyplot as plt

data = [1, 2, 3, 4, 5, 6, 7]
plt.[1](data)
plt.show()

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

Aviolinplot

Bboxplot

Chist

Dscatter

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.boxplot instead of plt.violinplot.

Using plt.hist which creates a histogram, not a violin plot.

The plt.violinplot() function creates a violin plot, which shows the distribution of the data.

2fill in blank

medium

Complete the code to add a title to the violin plot.

Matplotlib

import matplotlib.pyplot as plt

data = [5, 10, 15, 20, 25]
plt.violinplot(data)
plt.[1]('My Violin Plot')
plt.show()

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

Axlabel

Btitle

Clegend

Dylabel

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.xlabel or plt.ylabel instead of plt.title.

Trying to add a legend when there is only one data set.

The plt.title() function adds a title to the plot.

3fill in blank

hard

Fix the error in the code to correctly plot multiple violin plots for two data sets.

Matplotlib

import matplotlib.pyplot as plt

data1 = [1, 2, 3, 4, 5]
data2 = [2, 3, 4, 5, 6]
plt.violinplot([1])
plt.show()

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

A[data1, data2]

Bdata1, data2

Cdata1 + data2

D[data1]

Attempts:

3 left

💡 Hint

Common Mistakes

Passing data1 and data2 as separate arguments instead of a list.

Concatenating the lists which merges data instead of plotting separately.

To plot multiple violin plots, the data must be passed as a list of lists, like [data1, data2].

4fill in blank

hard

Fill both blanks to create a violin plot with custom positions and show the plot.

Matplotlib

import matplotlib.pyplot as plt

data = [[1, 2, 3], [4, 5, 6]]
plt.violinplot(data, positions=[1])
plt.[2]()

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

A[1, 2]

Bshow

Cplot

D[0, 1]

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect positions that don't match data sets.

Forgetting to call plt.show() to display the plot.

The positions argument sets where the violins appear on the x-axis. plt.show() displays the plot.

5fill in blank

hard

Fill all three blanks to create a violin plot with custom widths, show means, and display the plot.

Matplotlib

import matplotlib.pyplot as plt

data = [3, 5, 7, 9, 11]
plt.violinplot(data, widths=[1], showmeans=[2])
plt.[3]()

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

A0.5

BTrue

Cshow

DFalse

Attempts:

3 left

💡 Hint

Common Mistakes

Using showmeans=False which hides the mean marker.

Forgetting to call plt.show() to display the plot.

Using invalid width values like strings.

The widths argument controls the width of the violin plot. showmeans=True shows the mean marker. plt.show() displays the plot.

Practice

1. What does the plt.violinplot() function in matplotlib primarily show?

easy

A. The exact data points as dots

B. The distribution shape and spread of data

C. The correlation between two variables

D. Only the mean value of the data

Solution

1. Step 1: Understand the purpose of violin plots

   Violin plots visualize the distribution shape and spread of data, combining boxplot and kernel density estimation.

2. Step 2: Identify what plt.violinplot() shows

   This function creates violin plots that display data distribution, not just summary statistics or correlations.

3. Final Answer:

   The distribution shape and spread of data -> Option B

4. Quick Check:

   Violin plot = distribution shape [OK]

Hint: Violin plots show data spread and shape, not just averages [OK]

Common Mistakes:

• Thinking it shows only mean or median
• Confusing with scatter or line plots
• Assuming it shows correlation

2. Which of the following is the correct way to create a violin plot for a list of data data using matplotlib?

easy

A. plt.plot.violinplot(data)

B. plt.violin(data)

C. plt.violinplot(data)

D. plt.violinplot(data, kind='violin')

Solution

1. Step 1: Recall the correct function name and usage

   The correct function to create violin plots in matplotlib is plt.violinplot() and it takes the data as the first argument.

2. Step 2: Check each option for syntax correctness

   plt.violinplot(data) uses the correct function and syntax. plt.plot.violinplot(data) has incorrect chaining, plt.violin(data) uses the wrong function name, and plt.violinplot(data, kind='violin') adds an invalid parameter kind.

3. Final Answer:

   plt.violinplot(data) -> Option C

4. Quick Check:

   Correct function call = plt.violinplot(data) [OK]

Hint: Use plt.violinplot(data) directly to plot violin plots [OK]

Common Mistakes:

• Using plt.violin instead of plt.violinplot
• Adding unsupported parameters
• Incorrect function chaining like plt.plot.violinplot

3. What will the following code output?

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(0)
data = [np.random.normal(0, 1, 100), np.random.normal(5, 1, 100)]
plt.violinplot(data)
plt.show()

medium

A. Two violin plots side by side showing distributions centered near 0 and 5

B. A single violin plot combining both datasets

C. An error because data is a list of arrays

D. A scatter plot of all data points

Solution

1. Step 1: Understand the input data structure

   The data is a list containing two arrays, each with 100 values from normal distributions centered at 0 and 5 respectively.

2. Step 2: Know how plt.violinplot handles list of datasets

   When given a list of arrays, plt.violinplot creates separate violins for each dataset side by side.

3. Final Answer:

   Two violin plots side by side showing distributions centered near 0 and 5 -> Option A

4. Quick Check:

   List of arrays = multiple violins [OK]

Hint: List of arrays creates multiple violins side by side [OK]

Common Mistakes:

• Thinking it merges all data into one violin
• Expecting a scatter plot instead
• Assuming it causes an error with list input

4. Identify the error in this code snippet:

import matplotlib.pyplot as plt
data = [1, 2, 3, 4, 5]
plt.violinplot(data, positions=3)
plt.show()

medium

A. plt.show() is missing

B. data must be a numpy array, not a list

C. plt.violinplot does not accept positions argument

D. positions must be a list or array, not a single integer

Solution

1. Step 1: Check the use of the positions parameter

   The positions argument expects a list or array of positions for each violin, not a single integer.

2. Step 2: Verify the data type and function usage

   Data can be a list, and plt.violinplot accepts positions, but it must match the number of violins as a list or array.

3. Final Answer:

   positions must be a list or array, not a single integer -> Option D

4. Quick Check:

   positions needs list/array [OK]

Hint: positions must be list/array matching violins count [OK]

Common Mistakes:

• Passing single int to positions
• Thinking data must be numpy array
• Ignoring plt.show() call

5. You have three groups of exam scores stored as lists: group1, group2, and group3. You want to compare their score distributions side by side using violin plots with custom positions at 1, 3, and 5. Which code correctly creates this plot?

hard

A. plt.violinplot([group1, group2, group3], positions=[1, 3, 5])

B. plt.violinplot(group1, group2, group3, positions=[1, 3, 5])

C. plt.violinplot([group1, group2, group3], position=[1, 3, 5])

D. plt.violinplot([group1, group2, group3], positions=1,3,5)

Solution

1. Step 1: Understand the input format for multiple violins

   Multiple datasets must be passed as a single list containing each group's data.

2. Step 2: Use the correct parameter name and format for positions

   The parameter is positions and it must be a list or array matching the number of violins.

3. Step 3: Check each option for syntax correctness

   plt.violinplot([group1, group2, group3], positions=[1, 3, 5]) correctly passes a list of groups and a list of positions. plt.violinplot(group1, group2, group3, positions=[1, 3, 5]) incorrectly passes multiple arguments instead of a list. plt.violinplot([group1, group2, group3], position=[1, 3, 5]) uses wrong parameter name position. plt.violinplot([group1, group2, group3], positions=1,3,5) passes positions as separate arguments, which is invalid.

4. Final Answer:

   plt.violinplot([group1, group2, group3], positions=[1, 3, 5]) -> Option A

5. Quick Check:

   List of groups + positions list = correct call [OK]

Hint: Pass groups as list and positions as list for multiple violins [OK]

Common Mistakes:

• Passing groups as separate arguments
• Using wrong parameter name 'position'
• Passing positions as separate arguments