-
-
Notifications
You must be signed in to change notification settings - Fork 394
391 lines (325 loc) · 17.5 KB
/
database_update.yml
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
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
name: Database Update
on:
push:
schedule:
- cron: '0 12 * * SUN'
jobs:
Add-New-Ticker:
runs-on: ubuntu-latest
steps:
- name: checkout repo content
uses: actions/checkout@v3
- name: pull changes
run: git pull https://${{secrets.PAT}}@github.com/JerBouma/FinanceDatabase.git main
- name: setup python
uses: actions/setup-python@v4
with:
python-version: '3.10'
- run: pip install -r requirements.txt
- run: pip install financedatabase openpyxl
- name: Add New Tickers and Update Old Ones
uses: jannekem/run-python-script-action@v1
with:
script: |
import numpy as np
import pandas as pd
# Collect NASDAQ data
nasdaq = pd.read_json("https://raw.githubusercontent.com/rreichel3/US-Stock-Symbols/main/nasdaq/nasdaq_full_tickers.json")
nasdaq = nasdaq.set_index('symbol')
nasdaq['exchange'] = 'NMS'
nasdaq['market'] = 'NASDAQ Global Select'
# Collect NYSE data
nyse = pd.read_json("https://raw.githubusercontent.com/rreichel3/US-Stock-Symbols/main/nyse/nyse_full_tickers.json")
nyse = nyse.set_index('symbol')
nyse['exchange'] = 'ASE'
nyse['market'] = 'NYSE MKT'
# Collect AMEX data, since it got acquired this is now the same exchange/market as NYSE
amex = pd.read_json("https://raw.githubusercontent.com/rreichel3/US-Stock-Symbols/main/amex/amex_full_tickers.json")
amex = amex.set_index('symbol')
amex['exchange'] = 'ASE'
amex['market'] = 'NYSE MKT'
# Combine the datasets
exchange_data = pd.concat([nasdaq, nyse, amex])
# Obtain the categories from the FinanceDatabase for conversion
fd_categories_path = 'compression/categories/github_exchange_categories.xlsx'
fd_sectors = pd.read_excel(fd_categories_path, sheet_name='sector', index_col=1)
fd_industry_groups = pd.read_excel(fd_categories_path, sheet_name='industry_group', index_col=1)
fd_industries = pd.read_excel(fd_categories_path, sheet_name='industry', index_col=1)
# Read the equities database
equities = pd.read_csv('database/equities.csv', index_col=0)
ticker_dict = {}
# Loop over the exchange dataset and create a new object that will be added to the database
for index, row in exchange_data.iterrows():
if row['marketCap']:
market_cap_value = float(row['marketCap'])
if market_cap_value >= 200_000_000_000:
market_cap = 'Mega Cap'
elif market_cap_value >= 10_000_000_000 and market_cap_value < 200_000_000_000:
market_cap= 'Large Cap'
elif market_cap_value >= 2_000_000_000 and market_cap_value < 10_000_000_000:
market_cap = 'Mid Cap'
elif market_cap_value >= 300_000_000 and market_cap_value < 2_000_000_000:
market_cap = 'Small Cap'
elif market_cap_value >= 50_000_000 and market_cap_value < 300_000_000:
market_cap = 'Micro Cap'
else:
market_cap = 'Nano Cap'
else:
market_cap = np.nan
try:
# Checks if ticker exists, if yes, continue
fd_data = equities.loc[index]
if fd_data['market_cap'] != market_cap and market_cap == market_cap:
ticker_dict[index] = {'symbol': index}
for column, value in fd_data.items():
if column == 'market_cap':
ticker_dict[index][column] = market_cap
else:
ticker_dict[index][column] = value
continue
except KeyError:
if row['name'] == 'Nano Labs Ltd American Depositary Shares':
# Specific case where the ticker is NA which is recognized
# as a NaN instead meaning it will continuously be added
index = "NA"
ticker_dict[index] = {}
ticker_dict[index]['name'] = row['name']
ticker_dict[index]['summary'] = np.nan
ticker_dict[index]['currency'] = "USD"
try:
industry = fd_industries.loc[row['industry']].iloc[0]
if isinstance(industry, pd.Series):
industry = industry[0]
ticker_dict[index]['industry'] = industry
except KeyError:
ticker_dict[index]['industry'] = np.nan
try:
industry_divison = equities[equities['industry'] == ticker_dict[index]['industry']]
industry_group = industry_divison['industry_group'].mode()[0]
ticker_dict[index]['industry_group'] = industry_group
except KeyError:
ticker_dict[index]['industry_group'] = np.nan
try:
sector_division = equities[(equities['industry_group'] == ticker_dict[index]['industry_group']) & (equities['industry'] == ticker_dict[index]['industry'])]
sector = sector_division['sector'].mode()[0]
ticker_dict[index]['sector'] = sector
except Exception:
ticker_dict[index]['sector'] = np.nan
ticker_dict[index]['exchange'] = row['exchange']
ticker_dict[index]['market'] = row['market']
ticker_dict[index]['country'] = row['country']
ticker_dict[index]['state'] = np.nan
ticker_dict[index]['city'] = np.nan
ticker_dict[index]['zipcode'] = np.nan
ticker_dict[index]['website'] = np.nan
ticker_dict[index]['market_cap'] = market_cap
ticker_dict[index]['isin'] = np.nan
ticker_dict[index]['cusip'] = np.nan
ticker_dict[index]['figi'] = np.nan
ticker_dict[index]['composite_figi'] = np.nan
ticker_dict[index]['shareclass_figi'] = np.nan
# Create a DataFrame out of the created dictionary
updated_companies = pd.DataFrame.from_dict(ticker_dict, orient='index')
updated_companies.index.name = 'symbol'
print(f"There are {len(updated_companies)} new updates!")
if not updated_companies.empty:
# Loop over all acquired values and update data
for index, values in updated_companies.iterrows():
try:
equities.loc[index] = updated_companies.loc[index]
except KeyError:
equities = pd.concat([equities, values])
# Sort the index
equities = equities.sort_index()
# Send to CSV
equities.to_csv('database/equities.csv')
- name: Commit files and log
run: |
git config --global user.name 'GitHub Action'
git config --global user.email '[email protected]'
git add -A
git checkout main
git diff-index --quiet HEAD || git commit -am "Update database with new tickers"
git push
- name: Check run status
if: steps.run.outputs.status != '0'
run: exit "${{ steps.run.outputs.status }}"
Update-Compression-Files:
needs: Add-New-Ticker
runs-on: ubuntu-latest
steps:
- name: checkout repo content
uses: actions/checkout@v3
- name: pull changes
run: git pull https://${{secrets.PAT}}@github.com/JerBouma/FinanceDatabase.git main
- name: setup python
uses: actions/setup-python@v4
with:
python-version: '3.10'
- run: pip install -r requirements.txt
- run: pip install financedatabase
- run : pip install openpyxl
- name: Update Compressions
uses: jannekem/run-python-script-action@v1
with:
script: |
import financedatabase as fd
import pandas as pd
cryptos = pd.read_csv('database/cryptos.csv')
cryptos.to_csv('compression/cryptos.bz2', index=False, compression='bz2')
currencies = pd.read_csv('database/currencies.csv')
currencies.to_csv('compression/currencies.bz2', index=False, compression='bz2')
equities = pd.read_csv('database/equities.csv')
equities.to_csv('compression/equities.bz2', index=False, compression='bz2')
etfs = pd.read_csv('database/etfs.csv')
etfs.to_csv('compression/etfs.bz2', index=False, compression='bz2')
funds = pd.read_csv('database/funds.csv')
funds.to_csv('compression/funds.bz2', index=False, compression='bz2')
indices = pd.read_csv('database/indices.csv')
indices.to_csv('compression/indices.bz2', index=False, compression='bz2')
moneymarkets = pd.read_csv('database/moneymarkets.csv')
moneymarkets.to_csv('compression/moneymarkets.bz2', index=False, compression='bz2')
- name: Commit files and log
run: |
git config --global user.name 'GitHub Action'
git config --global user.email '[email protected]'
git add -A
git checkout main
git diff-index --quiet HEAD || git commit -am "Update Compression Files"
git push
- name: Check run status
if: steps.run.outputs.status != '0'
run: exit "${{ steps.run.outputs.status }}"
Update-Categorization-Files:
needs: [Add-New-Ticker, Update-Compression-Files]
runs-on: ubuntu-latest
steps:
- name: checkout repo content
uses: actions/checkout@v3
- name: pull changes
run: git pull https://${{secrets.PAT}}@github.com/JerBouma/FinanceDatabase.git main
- name: setup python
uses: actions/setup-python@v4
with:
python-version: '3.10'
- run: pip install -r requirements.txt
- run: pip install financedatabase
- name: Update categories
uses: jannekem/run-python-script-action@v1
with:
script: |
import financedatabase as fd
import pandas as pd
cryptos = pd.read_csv("database/cryptos.csv", index_col=0)
cryptos_categories = {}
for column in cryptos:
if column in ['name', 'summary']:
continue
cryptos_categories[column] = cryptos[column].dropna().unique()
cryptos_categories[column].sort()
df_temp = pd.DataFrame.from_dict(cryptos_categories, orient='index').reset_index()
df_temp.to_csv('compression/categories/cryptos_categories.gzip', index=False, compression='gzip')
currencies = pd.read_csv("database/currencies.csv", index_col=0)
currencies_categories = {}
for column in currencies:
if column in ['name']:
continue
currencies_categories[column] = currencies[column].dropna().unique()
currencies_categories[column].sort()
df_temp = pd.DataFrame.from_dict(currencies_categories, orient='index').reset_index()
df_temp.to_csv('compression/categories/currencies_categories.gzip', index=False, compression='gzip')
equities = pd.read_csv("database/equities.csv", index_col=0)
equities_categories = {}
for column in equities:
if column in ['name', 'summary', 'website']:
continue
equities_categories[column] = equities[column].dropna().unique()
equities_categories[column].sort()
df_temp = pd.DataFrame.from_dict(equities_categories, orient='index').reset_index()
df_temp.to_csv('compression/categories/equities_categories.gzip', index=False, compression='gzip')
etfs = pd.read_csv("database/etfs.csv", index_col=0)
etfs_categories = {}
for column in etfs:
if column in ['name', 'summary']:
continue
etfs_categories[column] = etfs[column].dropna().unique()
etfs_categories[column].sort()
df_temp = pd.DataFrame.from_dict(etfs_categories, orient='index').reset_index()
df_temp.to_csv('compression/categories/etfs_categories.gzip', index=False, compression='gzip')
funds = pd.read_csv("database/funds.csv", index_col=0)
funds_categories = {}
for column in funds:
if column in ['name', 'summary', 'manager_name', 'manager_bio']:
continue
funds_categories[column] = funds[column].dropna().unique()
funds_categories[column].sort()
df_temp = pd.DataFrame.from_dict(funds_categories, orient='index').reset_index()
df_temp.to_csv('compression/categories/funds_categories.gzip', index=False, compression='gzip')
indices = pd.read_csv("database/indices.csv", index_col=0)
indices_categories = {}
for column in indices:
if column in ['name']:
continue
indices_categories[column] = indices[column].dropna().unique()
indices_categories[column].sort()
df_temp = pd.DataFrame.from_dict(indices_categories, orient='index').reset_index()
df_temp.to_csv('compression/categories/indices_categories.gzip', index=False, compression='gzip')
moneymarkets = pd.read_csv("database/moneymarkets.csv", index_col=0)
moneymarkets_categories = {}
for column in moneymarkets:
if column in ['name']:
continue
moneymarkets_categories[column] = moneymarkets[column].dropna().unique()
moneymarkets_categories[column].sort()
df_temp = pd.DataFrame.from_dict(moneymarkets_categories, orient='index').reset_index()
df_temp.to_csv('compression/categories/moneymarkets_categories.gzip', index=False, compression='gzip')
- name: Commit files and log
run: |
git config --global user.name 'GitHub Action'
git config --global user.email '[email protected]'
git add -A
git checkout main
git diff-index --quiet HEAD || git commit -am "Update Categorization Files"
git push
- name: Check run status
if: steps.run.outputs.status != '0'
run: exit "${{ steps.run.outputs.status }}"
Check-GICS-Categorisation:
needs: [Add-New-Ticker, Update-Compression-Files, Update-Categorization-Files]
runs-on: ubuntu-latest
steps:
- name: checkout repo content
uses: actions/checkout@v3
- name: setup python
uses: actions/setup-python@v4
with:
python-version: '3.10'
- run: pip install -r requirements.txt
- run: pip install financedatabase
- name: Check GICS Categorisation
uses: jannekem/run-python-script-action@v1
with:
script: |
import pandas as pd
import json
invalid_rows = pd.DataFrame()
errors = []
gics = json.load(open("compression/categories/gics_categories.json", "r"))
equities = pd.read_csv("database/equities.csv", index_col=0)
filtered_data = equities[equities['sector'].notna() & equities['industry_group'].notna() & equities['industry'].notna()]
for index, row in filtered_data.iterrows():
sector, industry_group, industry = row['sector'], row['industry_group'], row['industry']
try:
# Search whether it can find the combination
gics[sector][industry_group][industry]
except KeyError as error:
# If it can't, add to invalid_rows DataFrame
row['error'] = error
invalid_rows = pd.concat([invalid_rows, row], axis=1)
if not invalid_rows.empty:
invalid_rows = invalid_rows.T
print("Invalid Rows for:")
for index, row in invalid_rows.iterrows():
print(f"{index}: {row['error']}")
raise ValueError("There are invalid sector, industry groups and/or industries found. "
"Please check if it adheres to https://www.msci.com/our-solutions/indexes/gics")