Apply code for scatter plot on animal statistics using matplotlib.

10 b] Apply code for scatter plot on animal statistics using matplotlib.

Let’s visualize the correlation between various animals with the help of a scatter plot

1. Open the Exercise3.03.ipynb Jupyter Notebook from the Chapter03 folder to implement this exercise. Navigate to the path of this file and type in the following at the command-line
   terminal: jupyter-lab.
2. Import the necessary modules and enable plotting within the Jupyter Notebook:

# Import statements
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

3. Use pandas to read the data located in the Datasets folder

# Load dataset
data = pd.read_csv('../../Datasets/anage_data.csv')

4. The given dataset is not complete. Filter the data so that you end up with samples containing a body mass and a maximum longevity. Sort the data according to the animal class; here, the isfinite() function (to check whether the number is finite or not) checks for the finiteness of the given element:

# Preprocessing
longevity = 'Maximum longevity (yrs)'
mass = 'Body mass (g)'
data = data[np.isfinite(data[longevity]) & np.isfinite(data[mass])]
# Sort according to class
amphibia = data[data['Class'] == 'Amphibia']
aves = data[data['Class'] == 'Aves']
mammalia = data[data['Class'] == 'Mammalia']
reptilia = data[data['Class'] == 'Reptilia']

5. Create a scatter plot visualizing the correlation between the body mass and the maximum longevity. Use different colors to group data samples according to their class. Add a legend, labels, and a title. Use a log scale for both the x-axis and y-axis:

# Create figure
plt.figure(figsize=(10, 6), dpi=300)
# Create scatter plot
plt.scatter(amphibia[mass], amphibia[longevity], label='Amphibia')
plt.scatter(aves[mass], aves[longevity], label='Aves')
plt.scatter(mammalia[mass], mammalia[longevity], label='Mammalia')
plt.scatter(reptilia[mass], reptilia[longevity], label='Reptilia')
# Add legend
plt.legend()
# Log scale
ax = plt.gca()
ax.set_xscale('log')
ax.set_yscale('log')
# Add labels
plt.xlabel('Body mass in grams')
plt.ylabel('Maximum longevity in years')
# Show plot
plt.show()