Ranking charts in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of Ranking Chart Code

What will be the output of this code snippet that creates a ranking chart using matplotlib?

Matplotlib

import matplotlib.pyplot as plt
import pandas as pd

scores = {'Alice': 88, 'Bob': 95, 'Charlie': 70, 'David': 85}
ranked = pd.Series(scores).rank(ascending=False, method='min')

plt.bar(ranked.index, ranked.values)
plt.gca().invert_yaxis()
plt.title('Ranking Chart')
plt.ylabel('Rank')
plt.show()

A A bar chart with names on x-axis and ranks on y-axis, ranks inverted so 1 is at top

B A line chart showing scores over names

C A bar chart with scores on x-axis and names on y-axis

D A scatter plot with scores vs ranks

💡 Hint

Look at how rank is calculated and how y-axis is inverted.

The code ranks scores descending, then plots ranks as bars with names on x-axis. Inverting y-axis puts rank 1 at top.

❓ data_output

intermediate

Number of Items in Ranked Data

Given this code that ranks data, how many items are in the resulting ranked Series?

Matplotlib

import pandas as pd

scores = {'Anna': 78, 'Ben': 82, 'Cara': 78, 'Derek': 90}
ranked = pd.Series(scores).rank(ascending=False, method='min')

A 3

B 1

C 4

D 2

💡 Hint

Count the keys in the original dictionary.

The ranked Series has one rank per original item, so it has 4 items.

❓ visualization

advanced

Identify the Correct Ranking Chart Visualization

Which option shows the correct matplotlib code to create a horizontal ranking bar chart with names on y-axis and ranks on x-axis, with rank 1 at left?

A

plt.barh(ranked.index, ranked.values)
plt.xlabel('Rank')
plt.title('Horizontal Ranking Chart')
plt.show()

B

plt.bar(ranked.index, ranked.values)
plt.gca().invert_yaxis()
plt.ylabel('Rank')
plt.title('Ranking Chart')
plt.show()

C

plt.barh(ranked.values, ranked.index)
plt.gca().invert_xaxis()
plt.xlabel('Rank')
plt.title('Horizontal Ranking Chart')
plt.show()

D

plt.barh(ranked.index, ranked.values)
plt.gca().invert_xaxis()
plt.xlabel('Rank')
plt.title('Horizontal Ranking Chart')
plt.show()

💡 Hint

Horizontal bar charts use barh; invert x-axis to put rank 1 at left.

Option D correctly uses barh with names on y-axis and ranks on x-axis, then inverts x-axis to have rank 1 on left.

🔧 Debug

advanced

Error in Ranking Chart Code

What error will this code produce when run?

Matplotlib

import matplotlib.pyplot as plt
import pandas as pd

scores = {'Eve': 92, 'Frank': 85}
ranked = pd.Series(scores).rank(ascending=False)

plt.bar(ranked.values, ranked.index)
plt.show()

A TypeError: unhashable type: 'numpy.float64'

B ValueError: x and height must be the same size

C TypeError: 'float' object cannot be interpreted as an integer

D No error, chart displays correctly

💡 Hint

Check the order of arguments in plt.bar(x, height).

plt.bar expects x as categories and height as numeric values. Here, x and height are reversed causing size mismatch error.

🚀 Application

expert

Create a Ranking Chart with Ties Correctly Displayed

You have scores with ties: {'Gina': 88, 'Hank': 88, 'Ivy': 75}. Which code correctly creates a ranking chart that assigns the same rank to ties and plots them with rank 1 at top?

A

import matplotlib.pyplot as plt
import pandas as pd
scores = {'Gina': 88, 'Hank': 88, 'Ivy': 75}
ranked = pd.Series(scores).rank(ascending=False, method='min')
plt.bar(ranked.index, ranked.values)
plt.gca().invert_yaxis()
plt.title('Ranking with Ties')
plt.ylabel('Rank')
plt.show()

B

import matplotlib.pyplot as plt
import pandas as pd
scores = {'Gina': 88, 'Hank': 88, 'Ivy': 75}
ranked = pd.Series(scores).rank(ascending=False, method='average')
plt.bar(ranked.index, ranked.values)
plt.gca().invert_yaxis()
plt.title('Ranking with Ties')
plt.ylabel('Rank')
plt.show()

C

import matplotlib.pyplot as plt
import pandas as pd
scores = {'Gina': 88, 'Hank': 88, 'Ivy': 75}
ranked = pd.Series(scores).rank(ascending=True, method='min')
plt.bar(ranked.index, ranked.values)
plt.gca().invert_yaxis()
plt.title('Ranking with Ties')
plt.ylabel('Rank')
plt.show()

D

import matplotlib.pyplot as plt
import pandas as pd
scores = {'Gina': 88, 'Hank': 88, 'Ivy': 75}
ranked = pd.Series(scores).rank(ascending=False, method='max')
plt.bar(ranked.index, ranked.values)
plt.gca().invert_yaxis()
plt.title('Ranking with Ties')
plt.ylabel('Rank')
plt.show()

💡 Hint

Use method='min' to assign the same lowest rank to ties and invert y-axis for rank 1 at top.

Method 'min' assigns the lowest rank to tied scores. Ascending=False ranks highest score as 1. Inverting y-axis puts rank 1 at top.