Project: Visualizing Geographic Data with Basemap toolkit (Flight Routes)

Questions to address:

  • Which areas of the world have more airports?
  • What are the destinations served by the Dallas airport?
  • What are the european destinations from the Lisbon airport?

Tools:

  • Basemap Toolkit


load defaults

In [1]:
import pandas as pd
import re
import numpy as np

from IPython.display import display
%matplotlib inline
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
from matplotlib import rcParams

from functions import *

plt.rcParams.update({'axes.titlepad': 20, 'font.size': 12, 'axes.titlesize':20})

colors = [(0/255,107/255,164/255), (255/255, 128/255, 14/255), 'red', 'green']


Dataset: Flight Data from Airlines, Airports and Routes

In [2]:
airlines = pd.read_csv('./data/airlines.csv')
airports = pd.read_csv('./data/airports.csv')
routes = pd.read_csv('./data/routes.csv')
geo_routes = pd.read_csv('./data/geo_routes.csv')

Variables available:

In [3]:
print("Airlines: ", end='')
for element in airlines.columns:
    print("%s | " % element, end='')
    
print("\nAirports: ", end='')
for element in airports.columns:
    print("%s | " % element, end='')
    
print("\nRoutes: ", end='')
for element in routes.columns:
    print("%s | " % element, end='')
    
print("\nGeo Routes: ", end='')
for element in geo_routes.columns:
    print("%s | " % element, end='')

Airlines: id | name | alias | iata | icao | callsign | country | active | 
Airports: id | name | city | country | code | icao | latitude | longitude | altitude | offset | dst | timezone | 
Routes: airline | airline_id | source | source_id | dest | dest_id | codeshare | stops | equipment | 
Geo Routes: airline | source | dest | equipment | start_lon | end_lon | start_lat | end_lat |

DF snipet:

In [4]:
print("Airlines:")
display(airlines.iloc[:3])

print("Airports:")
display(airports.iloc[:3])

print("Routes:")
display(routes.iloc[:3])

print("Geo Routes:")
display(geo_routes.iloc[:3])

Airlines:
id name alias iata icao callsign country active
0 1 Private flight \N - NaN NaN NaN Y
1 2 135 Airways \N NaN GNL GENERAL United States N
2 3 1Time Airline \N 1T RNX NEXTIME South Africa Y 
Airports:
id name city country code icao latitude longitude altitude offset dst timezone
0 1 Goroka Goroka Papua New Guinea GKA AYGA -6.081689 145.391881 5282 10.0 U Pacific/Port_Moresby
1 2 Madang Madang Papua New Guinea MAG AYMD -5.207083 145.788700 20 10.0 U Pacific/Port_Moresby
2 3 Mount Hagen Mount Hagen Papua New Guinea HGU AYMH -5.826789 144.295861 5388 10.0 U Pacific/Port_Moresby 
Routes:
airline airline_id source source_id dest dest_id codeshare stops equipment
0 2B 410 AER 2965 KZN 2990 NaN 0 CR2
1 2B 410 ASF 2966 KZN 2990 NaN 0 CR2
2 2B 410 ASF 2966 MRV 2962 NaN 0 CR2 
Geo Routes:
airline source dest equipment start_lon end_lon start_lat end_lat
0 2B AER KZN CR2 39.956589 49.278728 43.449928 55.606186
1 2B ASF KZN CR2 48.006278 49.278728 46.283333 55.606186
2 2B ASF MRV CR2 48.006278 43.081889 46.283333 44.225072


Analysis:

Q1: Which areas of the world have more airports?

In [5]:
from mpl_toolkits.basemap import Basemap

fig, ax = plt.subplots(figsize=(15,20))

m = Basemap(projection='merc', llcrnrlat=-80, urcrnrlat=80, llcrnrlon=-180, urcrnrlon=180)
x,y = m(airports['longitude'].tolist(), airports['latitude'].tolist())

m.scatter(x, y, s=1)
m.drawcoastlines()
ax.set_title('Scaled Up Earth With Coastlines')
plt.show()
  • Central Europe and the East coast of the US


Q2: Which airports have direct flights from Dallas?

In [6]:
fig, ax = plt.subplots(figsize=(15,20))
m = Basemap(projection='merc', llcrnrlat=-80, urcrnrlat=80, llcrnrlon=-180, urcrnrlon=180)
m.drawcoastlines()

def create_great_circles(input_df):
    for idx, row in input_df.iterrows():
        #print(row['start_lon'], row['end_lon'], row['start_lat'], row['end_lat'])
        if((abs(row['end_lat']-row['start_lat']) < 180) & 
           (abs(row['end_lon']-row['start_lon']) < 180)):
            m.drawgreatcircle(row['start_lon'], row['start_lat'], row['end_lon'], row['end_lat'])
        
dfw = geo_routes[geo_routes['source']=='DFW']
create_great_circles(dfw)
plt.show()


Q3: Which airports in Europe have direct flights from Lisbon?

In [54]:
fig, ax = plt.subplots(figsize=(10,10))
m = Basemap(projection='merc', llcrnrlat=20, urcrnrlat=70, llcrnrlon=-30, urcrnrlon=50, resolution='l')
m.drawcoastlines()
m.fillcontinents(color='#F0E0BB', lake_color='#BBDDF0')
m.drawmapboundary(fill_color='#BBDDF0')
m.drawcountries(linewidth=0.5)

def create_great_circles(input_df):
    for idx, row in input_df.iterrows():
        #print(row['start_lon'], row['end_lon'], row['start_lat'], row['end_lat'])
        if((abs(row['end_lat']-row['start_lat']) < 180) & 
           (abs(row['end_lon']-row['start_lon']) < 180)):
            m.drawgreatcircle(row['start_lon'], row['start_lat'], row['end_lon'], row['end_lat'])
        
df = geo_routes[geo_routes['source']=='LIS']
european_routes = df[(df['end_lon']>-50) & (df['end_lon']<50) & (df['end_lat']>20) & (df['end_lat']<70)]
create_great_circles(european_routes)
plt.show()
In [ ]: