In [1]:

    

import wget
    import os
    import zipfile
    
    import urllib3
    import certifi
    import sys
    import glob
    
    import numpy as np
    import pandas as pd
    
    import matplotlib.pyplot as plt
    
    %matplotlib inline


    import plotly.offline as py
    import plotly.graph_objs as go
    import plotly.tools as tls
    import seaborn as sns
    
    import plotly
    plotly.offline.init_notebook_mode()


    

In [2]:

    

df = pd.read_csv("italy_earthquakes_from_2016-08-24_to_2016-11-30.csv").set_index('Time')
df.index = pd.to_datetime(df.index)
df.head()


    

    
Out[2]:






  

    

      

      
Latitude
      
Longitude
      
Depth/Km
      
Magnitude
    
    

      
Time
      

      

      

      

    
  
  

    

      
2016-08-24 03:36:32.000
      
42.6983
      
13.2335
      
8.1
      
6.0
    
    

      
2016-08-24 03:37:26.580
      
42.7123
      
13.2533
      
9.0
      
4.5
    
    

      
2016-08-24 03:40:46.590
      
42.7647
      
13.1723
      
9.7
      
3.8
    
    

      
2016-08-24 03:41:38.900
      
42.7803
      
13.1683
      
9.7
      
3.9
    
    

      
2016-08-24 03:42:07.170
      
42.7798
      
13.1575
      
9.7
      
3.6
    
  

In [3]:

    

trace = go.Scatter(x=df.index,
                   y=df.Magnitude)

data = [trace]
layout = dict(
    title='Time series for Magnitude',
    xaxis=dict(
        rangeselector=dict(
            buttons=list([
                dict(count=1,
                     label='1m',
                     step='month',
                     stepmode='backward'),
                dict(step='all')
            ])
        ),
        rangeslider=dict(),
        type='date'
    )
)

fig = dict(data=data, layout=layout)
py.iplot(fig)


    

In [4]:

    

trace = go.Scattergl(
    x = df.index,
    y = df.Magnitude,
    mode = 'markers',
    marker = dict(
        color = 'FFBAD2',
        line = dict(width = 1)
    )
)
data = [trace]
layout = go.Layout(
    title='Magnitude <br>(Hover to see the magnitude of the eartquake and the time it occured)',
    xaxis=dict(
        title='Time',
        titlefont=dict(
            family='Courier New, monospace',
            size=18,
            color='#7f7f7f'
        )
    ),
    yaxis=dict(
        title='Magnitude',
        titlefont=dict(
            family='Courier New, monospace',
            size=18,
            color='#7f7f7f'
        )
    )
)
fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='compare_webgl')


    

In [5]:

    

import vincent
vincent.initialize_notebook()
line = vincent.Line(df[['Magnitude', 'Depth/Km']])
line.axis_titles(x='Date', y='Value')
line.legend(title='Magnitude vs Depth/Km')


    

    






           






    
Out[5]:







        

In [31]:

    

import bokeh
from bokeh.io import output_notebook


    

In [36]:

    

from bokeh.models import BoxAnnotation
from bokeh.plotting import figure, show, output_file


TOOLS = "pan,wheel_zoom,box_zoom,reset,save"

# reduce data size

p = figure(x_axis_type="datetime", tools=TOOLS, title="Earthquake's Magnitude")
p.xgrid.grid_line_color=None
p.ygrid.grid_line_alpha=0.5
p.xaxis.axis_label = 'Time (2016)'
p.yaxis.axis_label = 'Magnitude'

p.line(df.index, df.Magnitude, line_color="gray")

p.add_layout(BoxAnnotation(top=80, fill_alpha=0.1, fill_color='red'))
p.add_layout(BoxAnnotation(bottom=80, top=180, fill_alpha=0.1, line_color='olive', fill_color='olive'))
p.add_layout(BoxAnnotation(bottom=180, fill_alpha=0.1, fill_color='red'))

#output_file("box_annotation.html", title="box_annotation.py example")

output_notebook()
show(p)


    

    






    

        
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