Why time series need special handling in Matplotlib - See It in Action

Why Time Series Need Special Handling

📖 Scenario: Imagine you are a weather analyst. You have daily temperature data for a city. You want to understand how temperature changes over time.

🎯 Goal: You will create a simple time series plot using matplotlib to see why time series data needs special handling compared to regular data.

📋 What You'll Learn

Create a dictionary with dates as keys and temperatures as values

Create a list of dates from the dictionary keys

Create a list of temperatures from the dictionary values

Plot the temperature over time using matplotlib

Label the x-axis as 'Date' and y-axis as 'Temperature (°C)'

Show the plot

💡 Why This Matters

🌍 Real World

Time series data is everywhere: weather, stock prices, sales over months, and more. Understanding how to handle and plot it is important.

💼 Career

Data scientists and analysts often work with time series data to find patterns and make forecasts.

1

Create the temperature data dictionary

Create a dictionary called temperature_data with these exact entries: '2024-01-01': 5, '2024-01-02': 7, '2024-01-03': 6, '2024-01-04': 8, '2024-01-05': 7

Matplotlib

# Create the temperature_data dictionary with dates and temperatures
# Your code here

Need a hint?

Use curly braces to create a dictionary. Dates are keys as strings, temperatures are integer values.

2

Extract dates and temperatures into lists

Create a list called dates from the keys of temperature_data and a list called temperatures from the values of temperature_data

Matplotlib

temperature_data = {
    '2024-01-01': 5,
    '2024-01-02': 7,
    '2024-01-03': 6,
    '2024-01-04': 8,
    '2024-01-05': 7
}
# Create dates list from temperature_data keys
# Create temperatures list from temperature_data values
# Your code here

Need a hint?

Use the keys() and values() methods of the dictionary and convert them to lists.

3

Plot the temperature over time

Import matplotlib.pyplot as plt. Use plt.plot(dates, temperatures) to plot the data. Then label the x-axis as 'Date' and y-axis as 'Temperature (°C)'

Matplotlib

temperature_data = {
    '2024-01-01': 5,
    '2024-01-02': 7,
    '2024-01-03': 6,
    '2024-01-04': 8,
    '2024-01-05': 7
}
dates = list(temperature_data.keys())
temperatures = list(temperature_data.values())
# Import matplotlib.pyplot as plt
# Plot dates vs temperatures
# Label x-axis and y-axis
# Your code here

Need a hint?

Use plt.plot() to create the line plot. Use plt.xlabel() and plt.ylabel() to add labels.

4

Show the plot

Use plt.show() to display the plot

Matplotlib

import matplotlib.pyplot as plt

temperature_data = {
    '2024-01-01': 5,
    '2024-01-02': 7,
    '2024-01-03': 6,
    '2024-01-04': 8,
    '2024-01-05': 7
}
dates = list(temperature_data.keys())
temperatures = list(temperature_data.values())

plt.plot(dates, temperatures)
plt.xlabel('Date')
plt.ylabel('Temperature (°C)')
# Show the plot
# Your code here

Need a hint?

Use plt.show() to display the plot window.