Time series with fill_between in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to plot a time series line using matplotlib.

Matplotlib

import matplotlib.pyplot as plt
import pandas as pd

dates = pd.date_range('2024-01-01', periods=5)
values = [10, 12, 9, 14, 13]

plt.plot(dates, [1])
plt.show()

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A[10, 12, 9, 14]

Bdates

Crange(5)

Dvalues

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'dates' as the y-axis data instead of 'values'.

Using a range or incomplete list instead of the full values list.

The y-axis data for the plot should be the 'values' list, which contains the time series data points.

2fill in blank

medium

Complete the code to fill the area under the time series line.

Matplotlib

plt.plot(dates, values)
plt.[1](dates, values, alpha=0.3)
plt.show()

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Afill

Bfill_between

Cbar

Dscatter

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'fill' which is not a matplotlib function for this purpose.

Using 'bar' or 'scatter' which create different plot types.

The 'fill_between' function fills the area between the x-axis and the line defined by the y-values.

3fill in blank

hard

Fix the error in the code to fill between two time series lines.

Matplotlib

values2 = [8, 11, 10, 13, 12]
plt.plot(dates, values)
plt.plot(dates, values2)
plt.fill_between(dates, values, [1], color='gray', alpha=0.2)
plt.show()

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Arange(5)

Bvalues

Cvalues2

Ddates

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'dates' or 'range(5)' which are x-axis values, not y-values.

Using the same 'values' list twice, which fills under the same line.

To fill between two lines, the third argument to fill_between should be the second y-values list, here 'values2'.

4fill in blank

hard

Fill the blanks to create a dictionary comprehension that maps dates to values only if the value is greater than 10.

Matplotlib

filtered = { [1]: [2] for [3], [4] in zip(dates, values) if [2] > 10 }

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Adate

Bvalue

Attempts:

3 left

💡 Hint

Common Mistakes

Using the same variable name for both key and value.

Not matching variable names in the for loop and the key:value pair.

The dictionary comprehension maps each date to its value if the value is greater than 10. The variables in the loop are 'date' and 'value'.

5fill in blank

hard

Fill the blanks to create a dictionary comprehension that maps uppercase dates (as strings) to values only if the value is less than 13.

Matplotlib

result = { [1]: [2] for [3], [4] in zip(dates, values) if [2] < 13 }

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Adate.strftime('%Y-%m-%d').upper()

Bvalue

Cdate

Attempts:

3 left

💡 Hint

Common Mistakes

Not converting the date to string before calling upper().

Using inconsistent variable names.

The comprehension converts dates to uppercase strings as keys and maps them to values less than 13.