Downsampling strategies in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the matplotlib pyplot module with the common alias.

Matplotlib

import matplotlib.[1] as plt

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Agraph

Bplot

Cmpl

Dpyplot

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'plot' instead of 'pyplot' causes import errors.

Using 'mpl' or 'graph' are not valid module names.

The matplotlib plotting interface is in the pyplot module, commonly imported as plt.

2fill in blank

medium

Complete the code to plot a line graph of y versus x using matplotlib.

Matplotlib

plt.[1](x, y)
plt.show()

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Ascatter

Bbar

Cplot

Dhist

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'scatter' plots points without connecting lines.

Using 'bar' or 'hist' creates different chart types.

The plot function draws a line graph connecting points.

3fill in blank

hard

Fix the error in the code to downsample data by selecting every nth point.

Matplotlib

downsampled = data[[1]::n]

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A1

B0

C-1

Dn

Attempts:

3 left

💡 Hint

Common Mistakes

Using 1 skips the first element.

Using -1 reverses the data.

Using n as start index skips too many elements.

To select every nth element starting from the first, use data[0::n].

4fill in blank

hard

Fill both blanks to create a dictionary of downsampled points where keys are indices and values are data points greater than threshold.

Matplotlib

downsampled_dict = {i: data[i] for i in range(0, len(data), [1]) if data[i] [2] threshold}

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A5

B>

C<

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' filters points less than threshold.

Using 10 as step size changes downsampling rate.

Mixing operators causes wrong filtering.

We downsample by steps of 5 and keep points greater than the threshold.

5fill in blank

hard

Fill all three blanks to create a list of downsampled points squared, only if the point is less than max_val.

Matplotlib

result = [data[[1]]**2 for [2] in range(0, len(data), [3]) if data[i] < max_val]

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Ai

C5

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names causes errors.

Using wrong step size changes downsampling.

Forgetting to square the data point.

Use 'i' as the index variable and downsample by steps of 5, squaring each selected point less than max_val.