Histogram plots in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to plot a histogram of the 'age' column from the DataFrame df.

Pandas

df['age'].[1](bins=10)

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

Ahist

Bbar

Cscatter

Dplot

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'plot' instead of 'hist' which creates a line plot by default.

Using 'scatter' which is for scatter plots, not histograms.

The hist method creates a histogram plot of the data.

2fill in blank

medium

Complete the code to plot a histogram with 20 bins for the 'salary' column in DataFrame df.

Pandas

df['salary'].hist([1]=20)

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

Arange

Bwidth

Cbins

Dheight

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'range' which defines the interval but not the number of bins.

Using 'width' or 'height' which are not parameters for histograms.

The bins parameter controls the number of bins in the histogram.

3fill in blank

hard

Fix the error in the code to plot a histogram of 'height' with 15 bins.

Pandas

df['height'].hist(bins=[1])

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

A15

B'15'

Crange(15)

DNone

Attempts:

3 left

💡 Hint

Common Mistakes

Passing '15' as a string instead of integer 15.

Passing a range object which is not accepted.

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

4fill in blank

hard

Fill both blanks to create a histogram of 'weight' with 12 bins and a blue color.

Pandas

df['weight'].hist(bins=[1], color=[2])

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

A12

B'red'

C'blue'

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Using color without quotes.

Using a string for bins instead of a number.

Use bins=12 for 12 bins and color='blue' to set the bar color.

5fill in blank

hard

Fill all three blanks to create a histogram of 'score' with 8 bins, green color, and transparency set to 0.5.

Pandas

df['score'].hist(bins=[1], color=[2], alpha=[3])

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

A10

B'green'

C0.5

D8

Attempts:

3 left

💡 Hint

Common Mistakes

Using alpha as a string instead of a number.

Using wrong number of bins.

Set bins=8, color='green', and alpha=0.5 for transparency.

Practice

1. What does a histogram plot show when created from a pandas DataFrame column?

easy

A. The exact values of each data point

B. The frequency distribution of values grouped into bins

C. The relationship between two variables

D. The sum of all values in the column

Solution

1. Step 1: Understand histogram purpose

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

2. Step 2: Identify what histogram shows

   It shows frequency distribution, not individual values or sums.

3. Final Answer:

   The frequency distribution of values grouped into bins -> Option B

4. Quick Check:

   Histogram = frequency distribution [OK]

Hint: Histograms show counts per group, not individual points [OK]

Common Mistakes:

• Thinking histogram shows exact data points
• Confusing histogram with scatter plot
• Assuming histogram shows sums instead of counts

2. Which of the following is the correct way to plot a histogram of the 'age' column in a pandas DataFrame named df?

easy

A. df['age'].hist()

B. df.plot.hist('age')

C. df['age'].histogram()

D. df.histogram('age')

Solution

1. Step 1: Recall pandas histogram syntax

   To plot a histogram of a single column, use df['column'].hist().

2. Step 2: Check each option

   df['age'].histogram() is incorrect syntax; df.plot.hist('age') is invalid method; df.histogram('age') does not exist; df['age'].hist() is correct.

3. Final Answer:

   df['age'].hist() -> Option A

4. Quick Check:

   Single column histogram = df['col'].hist() [OK]

Hint: Use df['col'].hist() for single column histogram [OK]

Common Mistakes:

• Using df['age'].histogram() which is invalid
• Trying df.plot.hist('col') which is incorrect
• Calling non-existent df.histogram() method

3. Given the code:

import pandas as pd
import matplotlib.pyplot as plt
data = {'scores': [55, 60, 65, 70, 75, 80, 85, 90, 95, 100]}
df = pd.DataFrame(data)
df['scores'].hist(bins=5)
plt.show()

How many bars will the histogram display?

medium

A. Cannot determine without data

B. 10

C. 5

D. 1

Solution

1. Step 1: Understand bins parameter

   The bins=5 argument divides the data range into 5 equal groups (bars).

2. Step 2: Count bars from bins

   Histogram will show 5 bars representing frequency counts in each bin.

3. Final Answer:

   5 -> Option C

4. Quick Check:

   bins=5 means 5 bars [OK]

Hint: Number of bars equals bins parameter [OK]

Common Mistakes:

• Confusing bins with number of data points
• Assuming one bar per data point
• Ignoring bins argument effect

4. What is wrong with this code snippet to plot a histogram of the 'height' column?

import pandas as pd
df = pd.DataFrame({'height': [150, 160, 170, 180, 190]})
df.hist('height', bins=3, xlabel='Height')

medium

A. The parameter 'xlabel' is not valid in df.hist()

B. The 'bins' parameter must be a list, not an integer

C. The column name must be passed as a list ['height']

D. The DataFrame is missing a required index

Solution

1. Step 1: Check df.hist() parameters

   df.hist() does not accept 'xlabel' parameter directly.

2. Step 2: Identify correct way to label axes

   Labels should be set using matplotlib functions after plotting, not as df.hist() arguments.

3. Final Answer:

   The parameter 'xlabel' is not valid in df.hist() -> Option A

4. Quick Check:

   Use plt.xlabel() to label axes, not df.hist() args [OK]

Hint: Use plt.xlabel() for labels, not df.hist() params [OK]

Common Mistakes:

• Passing axis labels as df.hist() arguments
• Thinking bins must be a list
• Assuming column name must be a list

5. You have a DataFrame df with a 'salary' column containing values from 2000 to 10000. You want to create a histogram with 4 bins and label the x-axis as 'Salary Range'. Which code correctly achieves this?

hard

A. ax = df['salary'].hist(bins=4)
ax.xlabel('Salary Range')

B. df.hist('salary', bins=4, xlabel='Salary Range')

C. df['salary'].plot.hist(bins=4, xlabel='Salary Range')

D. df['salary'].hist(bins=4)
plt.xlabel('Salary Range')

Solution

1. Step 1: Plot histogram with bins=4

   Use df['salary'].hist(bins=4) to create histogram with 4 bins.

2. Step 2: Label x-axis correctly

   Use matplotlib's plt.xlabel('Salary Range') after plotting to set label.

3. Final Answer:

   df['salary'].hist(bins=4) plt.xlabel('Salary Range') -> Option D

4. Quick Check:

   Use plt.xlabel() after hist() for axis label [OK]

Hint: Set labels with plt.xlabel() after plotting histogram [OK]

Common Mistakes:

• Passing xlabel directly to hist()
• Using plot.hist() with xlabel param
• Not labeling axes at all