Why SciPy connects to broader tools - See It in Action

Why SciPy Connects to Broader Tools

📖 Scenario: You are working on a data science project where you need to analyze and visualize scientific data. You want to understand how SciPy helps connect different tools to make your work easier and more powerful.

🎯 Goal: Build a simple Python program that shows how SciPy can work with NumPy arrays and Matplotlib plots to analyze and visualize data.

📋 What You'll Learn

Create a NumPy array with sample data

Create a threshold variable to filter data

Use SciPy to find peaks in the data

Plot the original data and highlight the peaks using Matplotlib

💡 Why This Matters

🌍 Real World

Scientists and engineers often use SciPy together with NumPy and Matplotlib to analyze experimental data and create clear visual reports.

💼 Career

Knowing how SciPy connects with other tools is important for data scientists and analysts to build efficient workflows and communicate results effectively.

1

Create sample data using NumPy

Create a NumPy array called data with these exact values: [0, 2, 1, 3, 7, 1, 2, 6, 0, 1]

SciPy

# Create a NumPy array called data with the given values
# Your code here

Need a hint?

Use np.array() to create the array with the exact values.

2

Set a threshold to filter peaks

Create a variable called threshold and set it to 5

SciPy

import numpy as np

data = np.array([0, 2, 1, 3, 7, 1, 2, 6, 0, 1])

# Create a variable called threshold and set it to 5
# Your code here

Need a hint?

Just assign the number 5 to the variable threshold.

3

Find peaks in data using SciPy

Import find_peaks from scipy.signal and use it to find peaks in data with height greater than threshold. Store the result in a variable called peaks

SciPy

import numpy as np

data = np.array([0, 2, 1, 3, 7, 1, 2, 6, 0, 1])

threshold = 5

# Import find_peaks and find peaks in data above threshold
# Your code here

Need a hint?

Use find_peaks(data, height=threshold) and unpack the first result into peaks.

4

Plot data and highlight peaks using Matplotlib

Import matplotlib.pyplot as plt. Plot data as a line plot. Then plot the peaks as red dots on the same graph. Finally, use plt.show() to display the plot.

SciPy

import numpy as np
from scipy.signal import find_peaks

data = np.array([0, 2, 1, 3, 7, 1, 2, 6, 0, 1])

threshold = 5

peaks, _ = find_peaks(data, height=threshold)

# Import matplotlib.pyplot as plt
# Plot data and highlight peaks
# Show the plot
# Your code here

Need a hint?

Use plt.plot() twice: once for data line, once for peaks as red dots. Then call plt.show().