35 lines
1,011 B
Python
35 lines
1,011 B
Python
|
import pandas as pd
|
||
|
|
import matplotlib.pyplot as plt
|
||
|
|
import numpy as np
|
||
|
|
from scipy.stats import linregress
|
||
|
|
|
||
|
|
def draw_plot():
|
||
|
|
# Read data from file
|
||
|
|
df = pd.read_csv('epa-sea-level.csv')
|
||
|
|
|
||
|
|
# Create scatter plot
|
||
|
|
plt.figure(figsize=(16, 6))
|
||
|
|
|
||
|
|
|
||
|
|
plt.scatter(df['Year'], df['CSIRO Adjusted Sea Level'])
|
||
|
|
|
||
|
|
# Create first line of best fit
|
||
|
|
res = linregress(df['Year'], df['CSIRO Adjusted Sea Level'])
|
||
|
|
plt.plot(np.arange(1880, 2051), res.intercept + res.slope * np.arange(1880, 2051), 'g')
|
||
|
|
|
||
|
|
# Create second line of best fit
|
||
|
|
df = df.loc[df['Year'] >= 2000]
|
||
|
|
|
||
|
|
res = linregress(df['Year'], df['CSIRO Adjusted Sea Level'])
|
||
|
|
|
||
|
|
plt.plot(np.arange(2000, 2051), res.intercept + res.slope * np.arange(2000, 2051), 'r')
|
||
|
|
|
||
|
|
# Add labels and title
|
||
|
|
plt.xlabel('Year')
|
||
|
|
plt.ylabel('Sea Level (inches)')
|
||
|
|
plt.title('Rise in Sea Level')
|
||
|
|
plt.xlim(1850, 2075)
|
||
|
|
|
||
|
|
# Save plot and return data for testing (DO NOT MODIFY)
|
||
|
|
plt.savefig('sea_level_plot.png')
|
||
|
|
return plt.gca()
|