Rolling standard deviation in Pandas - Mini Project: Build & Apply

Rolling Standard Deviation with pandas

📖 Scenario: You work in a weather station. You have daily temperature data for a week. You want to understand how much the temperature changes over a short period.

🎯 Goal: Calculate the rolling standard deviation of daily temperatures over a 3-day window using pandas.

📋 What You'll Learn

Create a pandas DataFrame with daily temperatures for 7 days.

Set a window size variable for rolling calculation.

Calculate the rolling standard deviation using the window size.

Print the resulting rolling standard deviation values.

💡 Why This Matters

🌍 Real World

Rolling standard deviation helps weather analysts understand short-term temperature fluctuations, which is useful for forecasting and detecting unusual weather patterns.

💼 Career

Data scientists and analysts use rolling statistics to analyze trends and variability in time series data across many fields like finance, weather, and manufacturing.

1

Create the temperature DataFrame

Create a pandas DataFrame called df with a column 'Temperature' containing these exact values: [22, 21, 23, 24, 22, 20, 19].

Pandas

# Create the DataFrame df with the Temperature column
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary where the key is 'Temperature' and the value is the list of temperatures.

2

Set the rolling window size

Create a variable called window_size and set it to 3.

Pandas

import pandas as pd

df = pd.DataFrame({'Temperature': [22, 21, 23, 24, 22, 20, 19]})

# Set the rolling window size to 3
# Your code here

Need a hint?

Just create a variable named window_size and assign the number 3 to it.

3

Calculate rolling standard deviation

Create a new column in df called 'RollingStd' that contains the rolling standard deviation of the 'Temperature' column using the window size stored in window_size. Use pandas rolling() and std() methods.

Pandas

import pandas as pd

df = pd.DataFrame({'Temperature': [22, 21, 23, 24, 22, 20, 19]})

window_size = 3

# Calculate rolling standard deviation and store in 'RollingStd' column
# Your code here

Need a hint?

Use df['Temperature'].rolling(window=window_size).std() to calculate the rolling standard deviation.

4

Print the rolling standard deviation

Print the df DataFrame to display the 'Temperature' and 'RollingStd' columns.

Pandas

import pandas as pd

df = pd.DataFrame({'Temperature': [22, 21, 23, 24, 22, 20, 19]})

window_size = 3

df['RollingStd'] = df['Temperature'].rolling(window=window_size).std()

# Print the DataFrame df
# Your code here

Need a hint?

Use print(df) to show the DataFrame with the new rolling standard deviation column.