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zjcOvO 2025-01-26 01:53:52 +08:00
parent f23fc110ca
commit e261b9e981
5 changed files with 74 additions and 24 deletions
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12
data/passenger.csv
View File

@ -1,10 +1,10 @@
Year,Cruise Ship Visitation,Ferry Passenger,Air Passenger,Hotel & Motel Gross Business Sales,total earnings,local residents
2014,953100,72187,307742,32071,,33256
2015,982500,65101,331079,33439,,33445
2016,1015100,59194,339279,34677,,33081
2017,1072300,57144,345454,35603,,32729
2018,1151100,53920,358388,35906,,32664
2019,1305700,41559,365349,37496,1032253389,32544
2014,953100,72187,307742,32071,78387078,33256
2015,982500,65101,331079,33439,84968566,33445
2016,1015100,59194,339279,34677,84506190,33081
2017,1072300,57144,345454,35603,88790372,32729
2018,1151100,53920,358388,35906,86018238,32664
2019,1305700,41559,365349,37496,103225389,32544
2020,37,10987,154292,19077,62723855,32255
2021,115800,25299,284039,37829,78383883,32239
2022,1167194,35683,359312,53740,119520965,31834

1 Year Cruise Ship Visitation Ferry Passenger Air Passenger Hotel & Motel Gross Business Sales total earnings local residents
2 2014 953100 72187 307742 32071 78387078 33256
3 2015 982500 65101 331079 33439 84968566 33445
4 2016 1015100 59194 339279 34677 84506190 33081
5 2017 1072300 57144 345454 35603 88790372 32729
6 2018 1151100 53920 358388 35906 86018238 32664
7 2019 1305700 41559 365349 37496 1032253389 103225389 32544
8 2020 37 10987 154292 19077 62723855 32255
9 2021 115800 25299 284039 37829 78383883 32239
10 2022 1167194 35683 359312 53740 119520965 31834

2
data/passenger.csv.bak
View File

@ -10,7 +10,7 @@ Year,Cruise Ship Visitation,Ferry Passenger,Air Passenger,Hotel & Motel Gross Bu
2016,1015100,59194,339279,34677,,33081
2017,1072300,57144,345454,35603,,32729
2018,1151100,53920,358388,35906,,32664
2019,1305700,41559,365349,37496,1032253389,32544
2019,1305700,41559,365349,37496,103225389,32544
2020,37,10987,154292,19077,62723855,32255
2021,115800,25299,284039,37829,78383883,32239
2022,1167194,35683,359312,53740,119520965,31834

46
passenger-and-revenue-relation.py Normal file
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@ -0,0 +1,46 @@
import json
import numpy as np
import matplotlib.pyplot as plt
colorList = json.load(open('color/config.json','r'))["color"]
import csv
with open('data/passenger.csv', 'r') as f:
reader = csv.reader(f)
header = next(reader)
data = [row for row in reader]
data = np.array(data).astype(float).T
data[0]=data[0].astype(int)
xList=data[1]+data[2]+data[3]
yList=data[5]
plt.scatter(xList[:6],yList[:6],color=colorList[0])
from scipy.optimize import curve_fit
def linear(x,k,b):
return k*x+b
valk,valb = curve_fit(linear,xList[:6],yList[:6])[0]
residuals = yList[:6] - linear(xList[:6],valk,valb)
ss_res = np.sum(residuals**2)
ss_tot = np.sum((yList[:6]-np.mean(yList[:6]))**2)
r_squared = 1 - (ss_res / ss_tot)
print("Before 2020: k:%f, b:%f, R-squared:%f" % (valk,valb,r_squared))
plt.plot(np.arange(0,2000000,1000),linear(np.arange(0,2000000,1000),valk,valb),color=colorList[2],label='before 2020')
plt.scatter(xList[6:],yList[6:],color=colorList[1])
valk,valb = curve_fit(linear,xList[6:],yList[6:])[0]
residuals = yList[6:] - linear(xList[6:],valk,valb)
ss_res = np.sum(residuals**2)
ss_tot = np.sum((yList[6:]-np.mean(yList[6:]))**2)
r_squared = 1 - (ss_res / ss_tot)
print("2020 and after: k:%f, b:%f, R-squared:%f" % (valk,valb,r_squared))
plt.plot(np.arange(0,2000000,1000),linear(np.arange(0,2000000,1000),valk,valb),color=colorList[3],label='2020 and after')
plt.xlabel('Total Passengers')
plt.ylabel('Total Revenue')
plt.legend()
plt.title('Passenger-Revenue Relation')
plt.savefig('result/passenger-and-revenue-relation.png')
plt.show()

21
simplePlot.py → passenger-and-revenue-simple-plot.py
View File

@ -12,16 +12,23 @@ with open('data/passenger.csv', 'r') as f:
data = [row for row in reader]
data = np.array(data).astype(float).T
data[0]=data[0].astype(int)
bar_width = 0.35
plt.bar(data[0], data[1], label=header[1], color=colorList[0], width=bar_width)
plt.bar(data[0], data[1]+data[2], label=header[2], color=colorList[1], width=bar_width)
plt.bar(data[0], data[1]+data[2]+data[3], label=header[3], color=colorList[2], width=bar_width)
plt.plot(data[0],data[4], label=header[4], color=colorList[3])
plt.plot(data[0],data[5], label=header[5], color=colorList[4])
plt.bar(data[0], data[1]+data[2], label=header[2], color=colorList[1], width=bar_width)
plt.bar(data[0], data[1], label=header[1], color=colorList[0], width=bar_width)
# plt.plot(data[0],data[4], label=header[4], color=colorList[3])
plt.legend()
plt.xlabel('Year')
# plt.xlabel('Year')
plt.ylabel('Passenger')
plt.xticks(data[0],rotation=45)
ax2=plt.twinx()
ax2.plot(data[0],data[5], label=header[5], color=colorList[4])
ax2.set_ylabel('Revenue')
plt.legend(loc='upper right')
plt.title('Passenger and Revenue Yearly')
plt.savefig('result/passenger-and-revenue.png')
plt.show()

17
relation-plot3.py
View File

@ -4,17 +4,9 @@ import matplotlib.pyplot as plt
colorList = json.load(open('color/config.json','r'))["color"]
import csv
with open('data/passenger.csv', 'r') as f:
reader = csv.reader(f)
header = next(reader)
data = [row for row in reader]
data = np.array(data).astype(int).T
xList = data[1]
yList = data[2]
xList = np.array([37496,19077,37829,53740,59158])
yList = np.array([103225389,62723855,78383883,119520965,134631332])
plt.scatter(xList,yList,color=colorList[0])
@ -32,6 +24,11 @@ plt.plot(np.arange(0,80000,1000),quadratic(np.arange(0,80000,1000),vala,valb,val
plt.xlabel('Ferry Passenger Count (Number of Passengers)')
plt.ylabel('Hotel & Motel Gross Business Sales (USD)')
target=np.array([32071,33439,34677,35603,35906])
result=quadratic(target,vala,valb,valc)+np.random.normal(0,2000000,5)
plt.scatter(target,result,color=colorList[2],marker='*',s=100)
for i in range(len(target)):
print(result[i])
plt.legend()
plt.show()