Why time series need special handling in Matplotlib - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

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

Matplotlib

import matplotlib.pyplot as plt
import pandas as pd

dates = pd.date_range('20230101', periods=5)
values = [10, 12, 15, 14, 13]

plt.plot(dates, values)
plt.xlabel('Date')
plt.ylabel('Value')
plt.title('Time Series Plot')
plt.[1]()

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

Asavefig

Bclose

Cshow

Dlegend

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.savefig() instead of plt.show() when you want to display the plot.

Forgetting to call plt.show() so the plot does not appear.

The plt.show() function displays the plot window with the time series chart.

2fill in blank

medium

Complete the code to convert a string column to datetime format in pandas.

Matplotlib

import pandas as pd

data = {'date': ['2023-01-01', '2023-01-02', '2023-01-03'], 'value': [5, 6, 7]}
df = pd.DataFrame(data)
df['date'] = pd.to_datetime(df['[1]'])

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

Avalue

Bdate

Cindex

Dtime

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to convert a non-date column like 'value'.

Not converting the date column before plotting or analysis.

The 'date' column contains the date strings that need to be converted to datetime objects.

3fill in blank

hard

Fix the error in the code that resamples time series data to monthly frequency.

Matplotlib

import pandas as pd

dates = pd.date_range('2023-01-01', periods=90)
values = range(90)
df = pd.DataFrame({'value': values}, index=dates)
monthly = df.resample('[1]').mean()

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

AM

BD

CY

DH

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'D' which means daily, not monthly.

Using 'Y' which means yearly, not monthly.

The 'M' frequency string resamples data by calendar month, which is correct for monthly aggregation.

4fill in blank

hard

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

Matplotlib

data = {'2023-01-01': 8, '2023-01-02': 12, '2023-01-03': 15}
filtered = {date: value for date, value in data.items() if value [1] 10}

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A==

B<

C!=

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' which filters values less than 10.

Using '==' which filters values equal to 10.

We want values greater than 10, so the condition is value > 10.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps dates to values only if the date is after '2023-01-01' and the value is less than 20.

Matplotlib

data = {'2023-01-01': 8, '2023-01-02': 12, '2023-01-03': 25}
filtered = { [1]: [2] for [3] in data.items() if [1] > '2023-01-01' and [2] < 20 }

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

Adate

Bvalue

Cdate, value

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using a single variable instead of unpacking the tuple.

Mixing up key and value in the comprehension.

We unpack items into date and value, then map date to value with conditions on both.