import numpy as np
import matplotlib.pyplot as plt


data = np.genfromtxt("weather-raw.csv", delimiter=",", usecols=(1, 4))
# Remove any rows with either missing T or missing p.
data = data[~np.any(np.isnan(data), axis=1)]

# Temperatures are reported after multiplication by a factor of 10 so remove
# this factor.
data[:, 0] /= 10
# Remove temperature outliers (degC).
data = data[(data[:, 0] > -20) & (data[:, 0] < 40)]
# Remove pressure outliers (mbar).
data = data[(data[:, 1] > 920) & (data[:, 1] < 1100)]

# Get the correlation coefficient
corr = np.corrcoef(data, rowvar=0)[0, 1]
print(f"p-T correlation coefficient: {corr:.4f}")

# Plot the data on a scatter plot: T on x-axis, p on y-axis.
plt.scatter(*data.T, marker=".", s=2)
plt.xlabel(r"$T$ /$\mathrm{^\circ C}$")
plt.ylabel(r"$p$ /mbar")
plt.show()