<jupyter_start><jupyter_text>Data ScreeningLoad and review the data, check that dates are loaded properly and filter data down to the events in La Palma only. The dataset itself contains all recent IGN earthquake data for Spanish territory.<jupyter_code>import pandas as pd
from igndata import load
import matplotlib.pyplot as plt
df = load('../data.csv')
df.head()
df.describe()
plt.figure(figsize=(12,12))
ax = df.plot.scatter(x="Longitude", y="Latitude", figsize=(12,12), grid="on")<jupyter_output><empty_output><jupyter_text>Filter down to La Palma events onlyAlso some rows seem to be missing depth measurements, (see differences in the **count** for columns above) - take only rows with valid depths<jupyter_code>df = df[(df['Latitude'] < 29) & (df['Latitude'] > 28.3) & (df['Longitude'] < -17.5) & (df['Longitude'] > -18)]
df = df[df['Depth(km)'].notna()]
df.describe()
plt.figure(figsize=(20,6))
plt.subplot(1,3,1)
df["Latitude"].plot.hist(bins=20, density=True)
df["Latitude"].plot.kde()
plt.subplot(1,3,2)
df["Longitude"].plot.hist(bins=20, density=True)
df["Longitude"].plot.kde()
plt.subplot(1,3,3)
df["Depth(km)"].plot.hist(bins=50, density=True)
_=df["Depth(km)"].plot.kde()
from matplotlib import cm
cmap = cm.get_cmap('viridis_r')
ax = df.plot.scatter(x="Longitude", y="Latitude", s=40-df["Depth(km)"], c=df["Magnitude"], figsize=(12,10), grid="on", cmap=cmap)
# ax.set_ylim((28.4, 28.9))
# ax.set_xlim((-18, -17.75))
df.to_csv("./lapalma.csv", index=False)<jupyter_output><empty_output>
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