In [5]:
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
import sqlite3
con = sqlite3.connect('test.db')
df = pd.read_sql_query('select * from telemetry where boat_id =5', con, parse_dates=['received'], index_col=['received'])
#df = pd.read_sql_query('select * from telemetry where boat_id =33', con, parse_dates=['received'], index_col=['received'])
#df = pd.read_sql_query('select * from telemetry where boat_id =107', con, parse_dates=['received'], index_col=['received'])
#df = pd.read_sql_query('select * from telemetry where boat_id =156', con, parse_dates=['received'], index_col=['received'])
#df = pd.read_sql_query('select * from telemetry where boat_id in (5, 33, 107, 156)', con, parse_dates=['received'], index_col=['received'])
df.index = df.index.tz_localize('Canada/Pacific')
In [3]:
#df.timestamp.resample('30T').count().plot()
#df[['nav_status','boat_id']].hist().plot()
print(set(df.nav_status))
#df.groupby(['boat_id']).nav_status.hist(bins=15).plot()
df.groupby(['boat_id']).nav_status.plot()
#df.columns
Out[3]:
In [6]:
import folium
from folium import plugins
datmap = folium.Map(location=(49.284768, -123.109248), zoom_start=12)
datmap.add_children(plugins.HeatMap(df[['lat', 'lon']].values))
Out[6]:
In [7]: