In [12]:

#CrossCompute
vehicle_table_path = 'monthly_FHV_count.csv'
target_folder = '/tmp'

In [13]:

import pandas as pd
vehicle_table = pd.read_csv(vehicle_table_path)

In [14]:

vehicle_table[:2]

Out[14]:

	Month Number	For Hire Vehicle Count
0	1	200
1	2	300

In [15]:

len(vehicle_table)

Out[15]:

In [16]:

vehicle_table['Predicted Bus Ride Count'] = [23,34,34,23,20,45,34,56,55,67,88,12]
vehicle_table['Actual Bus Ride Count'] = [25,54,74,83,28,49,34,56,57,69,68,72]

In [17]:

# Save table
target_path = target_folder + '/a.csv'
vehicle_table.to_csv(target_path, index=False)
print('a_table_path = %s' % target_path)

a_table_path = /tmp/a.csv

In [18]:

# Save plot
%matplotlib inline
target_path = target_folder + '/b.png'
plot_table = vehicle_table.copy()
plot_table = plot_table.set_index('Month Number')
axes = plot_table.plot(kind='line')
figure = axes.get_figure()
figure.savefig(target_path)
print(f'b_image_path = {target_path}')

b_image_path = /tmp/b.png

In [23]:

# Save number
error_table = vehicle_table.copy()
error_table['Absolute Error'] = (error_table[
'Predicted Bus Ride Count'
] - error_table[
'Actual Bus Ride Count'
]).abs()

In [24]:

error_table

Out[24]:

	Month Number	For Hire Vehicle Count	Predicted Bus Ride Count	Actual Bus Ride Count	Absolute Error
0	1	200	23	25	2
1	2	300	34	54	20
2	3	230	34	74	40
3	4	330	23	83	60
4	5	540	20	28	8
5	6	400	45	49	4
6	7	230	34	34	0
7	8	543	56	56	0
8	9	340	55	57	2
9	10	230	67	69	2
10	11	450	88	68	20
11	12	200	12	72	60

In [25]:

print('mean_absolute_error = %s' % error_table['Absolute Error'].mean())

mean_absolute_error = 18.166666666666668

In [ ]:

Pay Notebook Creator: Ning Wei	0
Set Container: Numerical CPU with TINY Memory for 10 Minutes	0
Total	0

	Month Number	For Hire Vehicle Count	Predicted Bus Ride Count	Actual Bus Ride Count	Absolute Error
0	1	200	23	25	2
1	2	300	34	54	20
2	3	230	34	74	40
3	4	330	23	83	60
4	5	540	20	28	8
5	6	400	45	49	4
6	7	230	34	34	0
7	8	543	56	56	0
8	9	340	55	57	2
9	10	230	67	69	2
10	11	450	88	68	20
11	12	200	12	72	60

	Month Number	For Hire Vehicle Count	Predicted Bus Ride Count	Actual Bus Ride Count	Absolute Error
0	1	200	23	25	2
1	2	300	34	54	20
2	3	230	34	74	40
3	4	330	23	83	60
4	5	540	20	28	8
5	6	400	45	49	4
6	7	230	34	34	0
7	8	543	56	56	0
8	9	340	55	57	2
9	10	230	67	69	2
10	11	450	88	68	20
11	12	200	12	72	60

income and FHV trips per region 20190213-2048

	Month Number	For Hire Vehicle Count	Predicted Bus Ride Count	Actual Bus Ride Count	Absolute Error
0	1	200	23	25	2
1	2	300	34	54	20
2	3	230	34	74	40
3	4	330	23	83	60
4	5	540	20	28	8
5	6	400	45	49	4
6	7	230	34	34	0
7	8	543	56	56	0
8	9	340	55	57	2
9	10	230	67	69	2
10	11	450	88	68	20
11	12	200	12	72	60