In [1]:

    

%load_ext autoreload
%autoreload 2
%matplotlib inline


    

In [2]:

    

import sqlite3
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import matplotlib as mpl

from flight_safety.queries import get_events_accidents


    

In [3]:

    

mpl.rcParams['figure.figsize'] = 10, 6

mpl.rcParams['font.size'] = 20

con = sqlite3.connect('data/avall.db')

events = get_events_accidents(con)


    

In [4]:

    

gby_year = events.groupby(events.ev_date.dt.year)

injured_per_year = gby_year[['inj_tot_f', 'inj_tot_s', 'inj_tot_m']].sum()


    

In [5]:

    

injured_per_year.plot.area(alpha=0.8)
plt.xlabel('Year')
plt.ylabel('Number of victims');


    

In [6]:

    

passengers = pd.read_csv('./data/annual_passengers_carried_data.csv', nrows=1, usecols=range(4,60))
passengers = passengers.transpose()
# renaming column
passengers.columns = ['passengers']
gby_year = events.groupby(events.ev_date.dt.year)

injured_per_year = gby_year[['inj_tot_f', 'inj_tot_s', 'inj_tot_m']].sum()

injured_per_year.tail()
# parsing date in index 
passengers.index = pd.to_datetime(passengers.index.str[:4])
# converting flight number to number
passengers['passengers'] = pd.to_numeric(passengers['passengers'], errors='coerce') / 1e6
passengers.index = passengers.index.year


    

In [7]:

    

flights = pd.read_csv('data/API_IS.AIR.DPRT_DS2_en_csv_v2/API_IS.AIR.DPRT_DS2_en_csv_v2.csv', skiprows=4)
flights = flights[flights['Country Name'] == 'United States']

flights = flights.iloc[:, 5:-1].T
flights.index = pd.to_numeric(flights.index)
flights = flights / 1e6

flights.columns = ['flights']


    

In [8]:

    

fig, ax = plt.subplots(1, 1)
# ax[0].set_title('Millions of passengers transported')
# passengers['passengers'].plot.area(ax=ax[0], alpha=0.6, color="#0072B2")
# ax[0].set_xlim(1975, 2014)

ax.set_title('Millions of flights')
flights.plot.area(ax=ax, alpha=0.6, legend=False)
ax.set_xlim(1975, 2014)

plt.tight_layout()


    

In [9]:

    

accidents_gby_year = events.groupby(events.ev_date.dt.year).ntsb_no.count()
ax = accidents_gby_year.plot.area(alpha=0.8,)
ax.set_xlim(1982, 2015)

ax.set_ylabel('Number of accidents');


    

In [10]:

    

accident_rate = accidents_gby_year / flights.flights
accident_rate.tail()


    

    
Out[10]:





2013    2.052230
2014    2.720711
2015    2.737860
2016    1.661170
2017         NaN
dtype: float64

In [11]:

    

ax = accident_rate.plot.area(alpha=0.8, figsize=(11,5))
ax.set_xlim(1982, 2015)
ax.set_ylabel('accident rate');


    

In [12]:

    

ax = accident_rate.plot.area(alpha=0.8, figsize=(11,5))
ax.set_xlim(1998, 2016)
ax.set_ylabel('accident rate');