-
Notifications
You must be signed in to change notification settings - Fork 0
/
sustainability_scorer.py
199 lines (180 loc) · 6.79 KB
/
sustainability_scorer.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
import csv
from esg_score import ESGScoreScraper
from google_finance_api import CDPScoreScraper
from tqdm import tqdm
import os
encoding_mapping = {
'-': 0,
'F-': 1,
'F': 2,
'E-': 3,
'E': 4,
'D-': 5,
'D': 6,
'C-': 7,
'C': 8,
'B-': 9,
'B': 10,
'A-': 11,
'A': 12
}
class Company:
def __init__(self, ticker, name):
self.ticker = ticker
self.name = name
self.esg_score = None
self.env_score = None
self.social_score = None
self.governance_score = None
self.controversy_level = None
self.climate_score = None
self.sustainability_score = None
self.title = None
self.quote = None
self.current_price = None
self.day_range = None
self.year_range = None
self.market_cap = None
self.revenue = None
self.website = None
self.net_income = None
self.news1 = None
self.news2 = None
def write_company_to_csv(self):
with open('scores.csv', 'a', newline='') as csvfile:
spamwriter = csv.writer(csvfile, delimiter=',')
t = []
if self.esg_score:
t.append(self.esg_score)
else:
t.append(0)
if self.env_score:
t.append(self.env_score)
else:
t.append(0)
if self.social_score:
t.append(self.social_score)
else:
t.append(0)
if self.governance_score:
t.append(self.governance_score)
else:
t.append(0)
if self.controversy_level:
t.append(self.controversy_level)
else:
t.append(0)
if self.climate_score:
t.append(self.climate_score)
else:
t.append('-')
t.append(self.sustainability_score)
if self.title:
t.append(self.title)
else:
t.append('-')
if self.quote:
t.append(self.quote)
else:
t.append('-')
if self.current_price:
t.append(self.current_price)
else:
t.append('NaN')
if self.day_range:
t.append(self.day_range)
else:
t.append('-')
if self.year_range:
t.append(self.year_range)
else:
t.append('-')
if self.market_cap:
t.append(self.market_cap)
else:
t.append('NaN')
if self.revenue:
t.append(self.revenue)
else:
t.append('NaN')
if self.website:
t.append(self.website)
else:
t.append('-')
if self.net_income:
t.append(self.net_income)
else:
t.append('NaN')
if self.news1:
t.append(self.news1)
else:
t.append('-')
if self.news2:
t.append(self.news2)
else:
t.append('-')
spamwriter.writerow([self.ticker, self.name]+t)
def calculate_score(self):
esg = int(self.esg_score) if self.esg_score else 0
ctl = int(self.controversy_level) if self.controversy_level else 0
cdp = self.climate_score if self.climate_score else '-'
cdp = encoding_mapping[cdp]
n_esg = (esg - 0)/(100 - 0)
n_ctl = (ctl - 0)/(5 - 0)
n_cdp = (cdp - 0)/(12 - 0)
self.sustainability_score = (n_esg + n_ctl + n_cdp)*100//3
file_path = "scores.csv"
if os.path.exists(file_path):
os.remove(file_path)
with open(file_path, mode='w', newline='') as file:
writer = csv.writer(file)
writer.writerow(["Ticker","Company","ESG Risk score","Environment Risk Score","Social Risk Score","Governance Risk Score","Controversy Level","CDP Score", "Sustainability Score", "title",
"quote", "current_price", "day_range", "year_range", "market_cap", "revenue", "website", "net_income",
"news1", "news2"])
print("----------------------- Generating Sustainability Score for S&P 500 -----------------------")
# Define the CSV file path
csv_file_path = 'sp500_companies.csv'
# Create an instance of the ESGScoreScraper class
esg_scraper = ESGScoreScraper()
cdp_scraper = CDPScoreScraper()
# Open the CSV file and read data line by line
try:
with open(csv_file_path, mode='r', newline='') as file:
csv_reader = csv.reader(file)
next(csv_reader) # Skip the header row if it exists
for row in tqdm(csv_reader, desc="Processing"):
if len(row) >= 2:
company = Company(row[0], row[1])
esg_score = esg_scraper.get_esg_score(company.ticker)
company.esg_score = esg_score[0]
company.env_score = esg_score[1]
company.social_score = esg_score[2]
company.governance_score = esg_score[3]
company.controversy_level = esg_score[4]
aboutCompany = cdp_scraper.get_cdp_score(company.ticker)
if aboutCompany != None:
if aboutCompany.get("cdp") and len(aboutCompany.get("cdp")) > 0:
company.climate_score = aboutCompany.get("cdp")[0]
company.title = aboutCompany.get("title")
# print(company.title)
company.quote = aboutCompany.get("quote")
company.current_price = aboutCompany.get("current_price")
company.day_range = aboutCompany.get("day_range")
company.year_range = aboutCompany.get("year_range")
company.market_cap = aboutCompany.get("market_cap")
company.revenue = aboutCompany.get("revenue")
company.website = aboutCompany.get("website")
company.net_income = aboutCompany.get("net_income")
sizeOfNews = len(aboutCompany.get("news").get("items"))
# print(len(aboutCompany.get("news").get("items")))
if(sizeOfNews >= 2):
company.news1 = aboutCompany.get("news").get("items")[0].get("link")
company.news2 = aboutCompany.get("news").get("items")[1].get("link")
elif(sizeOfNews == 1):
company.news1 = aboutCompany.get("news").get("items")[0].get("link")
company.calculate_score()
company.write_company_to_csv()
finally:
# Close the ESGScoreScraper
esg_scraper.close()
print("----------------------- Done Generating Sustainability Score for S&P 500! -----------------------")