Histograms in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the library needed to create histograms.

Data Analysis Python

import [1] as plt

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

Anumpy

Bmatplotlib.pyplot

Cpandas

Dseaborn

Attempts:

3 left

💡 Hint

Common Mistakes

Importing the wrong library like pandas or numpy for plotting.

Forgetting to import matplotlib.pyplot.

We use matplotlib.pyplot to create histograms in Python.

2fill in blank

medium

Complete the code to create a histogram of the data list.

Data Analysis Python

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

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

Ahist

Bplot

Cscatter

Dbar

Attempts:

3 left

💡 Hint

Common Mistakes

Using plot or scatter instead of hist for histograms.

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

The hist function creates a histogram from data.

3fill in blank

hard

Fix the error in the code to set the number of bins to 5 in the histogram.

Data Analysis Python

data = [1, 2, 2, 3, 3, 3, 4]
plt.hist(data, bins=[1])
plt.show()

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

A5

B5.0

C'5'

Dbins=5

Attempts:

3 left

💡 Hint

Common Mistakes

Passing bins as a string like '5' instead of an integer.

Using an expression like bins=5 inside the argument list.

The bins parameter expects an integer number, not a string or expression.

4fill in blank

hard

Fill both blanks to create a histogram with 4 bins and set the color to blue.

Data Analysis Python

plt.hist(data, bins=[1], color=[2])
plt.show()

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

A4

B'red'

C'blue'

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Using color without quotes.

Setting bins to a string instead of a number.

We set bins to 4 and color to 'blue' as a string to customize the histogram.

5fill in blank

hard

Fill all three blanks to create a histogram with 6 bins, green color, and add a title 'My Histogram'.

Data Analysis Python

plt.hist(data, bins=[1], color=[2])
plt.title([3])
plt.show()

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

A6

B'green'

C'My Histogram'

D'Histogram'

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting quotes around color or title strings.

Using wrong number of bins.

Set bins to 6, color to 'green', and title to 'My Histogram' as a string.

Practice

1. What does a histogram primarily show when analyzing data?

easy

A. The average value of the dataset

B. The exact values of each data point

C. The relationship between two variables

D. The frequency distribution of data values grouped into bins

Solution

1. Step 1: Understand histogram purpose

   A histogram groups data into bins and counts how many data points fall into each bin.

2. Step 2: Identify what histogram shows

   This grouping shows the frequency distribution, not exact values or relationships.

3. Final Answer:

   The frequency distribution of data values grouped into bins -> Option D

4. Quick Check:

   Histogram = frequency distribution [OK]

Hint: Histograms show counts per bin, not individual values [OK]

Common Mistakes:

• Confusing histogram with scatter plot
• Thinking histogram shows exact data points
• Assuming histogram shows averages

2. Which of the following is the correct way to create a histogram using matplotlib in Python?

easy

A. plt.plot(data)

B. plt.hist(data)

C. plt.bar(data)

D. plt.scatter(data)

Solution

1. Step 1: Recall matplotlib histogram function

   Matplotlib uses plt.hist() to create histograms from data arrays.

2. Step 2: Differentiate from other plot types

   plt.plot() is for line plots, plt.bar() for bar charts, plt.scatter() for scatter plots.

3. Final Answer:

   plt.hist(data) -> Option B

4. Quick Check:

   Histogram function = plt.hist() [OK]

Hint: Use plt.hist() to plot histograms in matplotlib [OK]

Common Mistakes:

• Using plt.plot() instead of plt.hist()
• Confusing bar chart with histogram
• Trying plt.scatter() for histograms

3. What will be the output of this code snippet?

import matplotlib.pyplot as plt
import numpy as np

data = np.array([1, 2, 2, 3, 3, 3, 4, 4, 4, 4])
plt.hist(data, bins=4)
plt.show()

medium

A. A histogram with 4 bars showing counts: 1, 2, 3, 4

B. A histogram with 4 bars showing counts: 1, 2, 3, 4 but bars are unevenly spaced

C. A histogram with 4 bars showing counts: 1, 2, 3, 4 but bars represent ranges, not exact values

D. An error because bins must be equal to the number of unique values

Solution

1. Step 1: Understand bins in histogram

   Bins divide the data range into intervals. Here, bins=4 divides data from 1 to 4 into 4 intervals.

2. Step 2: Analyze counts per bin

   Counts per bin correspond to how many data points fall into each interval, not just counts of exact values.

3. Final Answer:

   A histogram with 4 bars showing counts: 1, 2, 3, 4 but bars represent ranges, not exact values -> Option C

4. Quick Check:

   Bins = ranges, counts per range [OK]

Hint: Bins group ranges, not just unique values [OK]

Common Mistakes:

• Assuming bins equal unique values
• Thinking bars show exact counts per value
• Expecting error due to bins count

4. Identify the error in this code that tries to plot a histogram:

import matplotlib.pyplot as plt

values = [5, 7, 8, 5, 6]
plt.hist(values, bins='five')
plt.show()

medium

A. bins parameter should be an integer, not a string

B. plt.hist() does not accept lists as data

C. plt.show() is missing

D. values list must be converted to numpy array first

Solution

1. Step 1: Check bins parameter type

   bins must be an integer or sequence, not a string like 'five'.

2. Step 2: Verify other parts

   plt.hist accepts lists, plt.show() is present, numpy array conversion is optional.

3. Final Answer:

   bins parameter should be an integer, not a string -> Option A

4. Quick Check:

   bins must be int or sequence [OK]

Hint: bins must be int or list, not string [OK]

Common Mistakes:

• Passing bins as string causes error
• Thinking plt.hist needs numpy array
• Forgetting plt.show()

5. You have a dataset with ages: [22, 25, 29, 35, 40, 42, 45, 50, 55, 60]. You want to create a histogram with bins representing decades (20-29, 30-39, 40-49, 50-59, 60-69). Which bins parameter should you use in plt.hist() to get this grouping?

hard

A. [20, 30, 40, 50, 60, 70]

B. [20, 29, 39, 49, 59, 69]

C. [20, 25, 30, 35, 40, 45, 50, 55, 60, 65]

D. [21, 31, 41, 51, 61, 71]

Solution

1. Step 1: Define bin edges for decades

   Bins edges must cover ranges: 20-29, 30-39, etc. Using edges [20, 30, 40, 50, 60, 70] creates intervals [20-30), [30-40), etc.

2. Step 2: Confirm bins cover all ages

   These edges include all ages from 22 to 60 correctly in decade groups.

3. Final Answer:

   [20, 30, 40, 50, 60, 70] -> Option A

4. Quick Check:

   Bins edges = decade boundaries [OK]

Hint: Bins edges define intervals; use decade boundaries [OK]

Common Mistakes:

• Using bin edges that exclude upper bounds
• Using single values instead of edges
• Misaligning bins with decade ranges