Data Screening - La Palma Seismicity 2021

Data Screening

Load 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.

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv('../data/catalogoComunSV_1663233588717.csv', sep=';')
df.columns = ['Event', 'Date', 'Time', 'Latitude', 'Longitude', 'Depth(km)', 'Intensity','Magnitude', 'Type Mag', 'Location']
df['Time'] = df['Time'].str.strip()
df['Date'] = df['Date'].str.strip()
df['DateTime'] = (df['Date'] + ' ' + df['Time']).apply(pd.to_datetime, format='%d/%m/%Y %H:%M:%S')
df['Timestamp'] = pd.to_numeric(pd.to_datetime(df['DateTime']))
df['Date'] = pd.to_datetime(df['Date'], format="%d/%m/%Y")
df = df.sort_values(by=['DateTime'], ascending=True)
df.head()

df.describe()

df.plot.scatter(x="Longitude", y="Latitude", figsize=(12,12), grid="on");

Filter down to La Palma events only¶

Also some rows seem to be missing depth measurements, (see differences in the count for columns above) - take only rows with valid depths

df = df[(df['Latitude'] < 28.7) & (df['Latitude'] > 28.3) & (df['Longitude'] < -17.7) & (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()

Spatial Plot¶

Scatter plot the spatial locations of events

from matplotlib import colormaps
cmap = colormaps['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)

/opt/anaconda3/envs/py3/lib/python3.9/site-packages/matplotlib/collections.py:967: RuntimeWarning: invalid value encountered in sqrt
  scale = np.sqrt(self._sizes) * dpi / 72.0 * self._factor

Timeline Plot¶

Scatter plot the event time series and look for any quantization issues. Have times & dates been loaded correctly?

ax = df.plot.scatter(x='DateTime', y='Depth(km)', figsize=(20,8))
ax.set_ylim(50,0);

df['Swarm'] = 0
df.loc[(df['Date'] >= '2017-10-01') & (df['Date'] <= '2017-10-31'), 'Swarm'] = 1
df.loc[(df['Date'] >= '2019-02-01') & (df['Date'] <= '2019-02-28'), 'Swarm'] = 2
df.loc[(df['Date'] >= '2020-07-21') & (df['Date'] <= '2020-08-05'), 'Swarm'] = 3
df.loc[(df['Date'] >= '2020-10-04') & (df['Date'] <= '2020-10-10'), 'Swarm'] = 4
df.loc[(df['Date'] >= '2020-10-11') & (df['Date'] <= '2020-10-22'), 'Swarm'] = 5
df.loc[(df['Date'] >= '2020-11-15') & (df['Date'] <= '2020-11-29'), 'Swarm'] = 6
df.loc[(df['Date'] >= '2020-12-10') & (df['Date'] <= '2020-12-29'), 'Swarm'] = 7
df.loc[(df['Date'] >= '2020-12-10') & (df['Date'] <= '2020-12-31'), 'Swarm'] = 8
df.loc[(df['Date'] >= '2021-01-15') & (df['Date'] <= '2021-02-07'), 'Swarm'] = 9
df.loc[(df['Date'] >= '2021-06-01') & (df['Date'] <= '2021-06-30'), 'Swarm'] = 10
df.loc[(df['Date'] >= '2021-07-01'), 'Swarm'] = None


df['Phase'] = 0;
df.loc[(df['Date'] >= '2021-09-11') & (df['Date'] <= '2021-09-30'), 'Phase'] = 1
df.loc[(df['Date'] >= '2021-10-01') & (df['Date'] <= '2021-11-30'), 'Phase'] = 2
df.loc[(df['Date'] >= '2021-12-01') & (df['Date'] <= '2021-12-31'), 'Phase'] = 3
df.loc[(df['Date'] >= '2021-12-31'), 'Phase'] = 4

df.to_csv("../data/lapalma_ign.csv", index=False)