35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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from scipy.stats import linregress
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def draw_plot():
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# Read data from file
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df = pd.read_csv("epa-sea-level.csv")
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result = linregress(x=df["Year"], y=df["CSIRO Adjusted Sea Level"])
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result2 = linregress(x=df["Year"][df["Year"] >= 2000], y=df["CSIRO Adjusted Sea Level"][df["Year"] >= 2000])
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span = np.arange(1880, 2051, dtype='float64')
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span2 = np.arange(2000, 2051, dtype='float64')
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# Create scatter plot
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fig, ax = plt.subplots(ncols=1, figsize=(10, 10))
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x1 = df.plot.scatter(x="Year", y="CSIRO Adjusted Sea Level", color="b", ax=ax).set(ylabel="Sea Level (inches)", title="Rise in Sea Level")
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# Create first line of best fit
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ax2 = ax.plot(span, result.intercept+result.slope*span, "r")
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# ax3 = df.plot.scatter(x="Year", y="NOAA Adjusted Sea Level", color="r", ax=ax).set(ylabel="Sea Level (inches)")
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# Create second line of best fit
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ax4 = ax.plot(span2, result2.intercept+result2.slope*span2, "y")
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# Add labels and title
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# Save plot and return data for testing (DO NOT MODIFY)
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plt.savefig('sea_level_plot.png')
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return plt.gca() |