Using Heatmaps¶

[1]:

import transportation_tutorials as tt
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
pd.options.display.max_columns = 100

Questions¶

Prepare a heatmap that visualizes the joint distribution of the number of trips taken by each household and the number of automobiles owned by the household.

For households with 2 automobiles, what is the most frequent number of trips made by those households in the data?
For households making 2 trips in the data, how many automobiles do most households own?

Data¶

To answer the questions, use the following data files:

[2]:

trip = pd.read_csv(tt.data('SERPM8-BASE2015-TRIPS'))
trip.head()

[2]:

	hh_id	person_id	person_num	tour_id	stop_id	inbound	tour_purpose	orig_purpose	dest_purpose	orig_mgra	dest_mgra	parking_mgra	stop_period	trip_mode	trip_board_tap	trip_alight_tap	tour_mode	smplRate_geo	autotech	tncmemb
0	1690841	4502948	1	0	-1	0	Work	Home	Work	7736	9290	-1	8	6	0	0	6	1.0	0	0
1	1690841	4502948	1	0	-1	1	Work	Work	Home	9290	7736	0	29	3	0	0	6	1.0	0	0
2	1690841	4502948	1	1	-1	0	Work-Based	Work	Work-Based	9290	7980	-1	13	1	0	0	1	1.0	0	0
3	1690841	4502948	1	1	-1	1	Work-Based	Work-Based	Work	7980	9290	-1	14	1	0	0	1	1.0	0	0
4	1690841	4502948	1	2	-1	0	Work-Based	Work	Work-Based	9290	10608	-1	19	3	0	0	3	1.0	0	0

[3]:

hh = pd.read_csv(tt.data('SERPM8-BASE2015-HOUSEHOLDS'))
hh.head()

[3]:

	Unnamed: 0	hh_id	home_mgra	income	autos	transponder	cdap_pattern	jtf_choice	autotech	tncmemb
0	426629	1690841	7736	512000	2	1	MMMM0	0	0	0
1	426630	1690961	7736	27500	1	0	MNMM0	0	0	0
2	426631	1690866	7736	150000	2	0	HMM0	0	0	0
3	426632	1690895	7736	104000	2	1	MMMM0	0	0	0
4	426633	1690933	7736	95000	2	1	MNM0	0	0	0