v0.1.2
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@ -61,12 +61,12 @@ def forex(instrument = "eurusd", startdate = "2019-01-01", enddate = "2021-01-01
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df = df.reset_index(drop = True)
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return df
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def index(instrument = "eurusd", startdate = "2019-01-01", enddate = "2021-01-01"):
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def index(instrument = "vix", startdate = "2019-01-01", enddate = "2021-01-01"):
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startdate = datetime.strptime(startdate, "%Y-%m-%d").strftime("%m/%d/%y")
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enddate = datetime.strptime(enddate, "%Y-%m-%d").strftime("%m/%d/%y")
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df = pd.DataFrame()
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def _FX(instrument = "eurusd", startdate = "01/01/2020", enddate = "01/01/2021"):
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def _index(instrument = "vix", startdate = "01/01/2020", enddate = "01/01/2021"):
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"""
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https://www.marketwatch.com/investing/
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"""
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@ -101,7 +101,7 @@ def index(instrument = "eurusd", startdate = "2019-01-01", enddate = "2021-01-01
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else:
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tmp_enddate = "01/01/" + str(i+1) + " 00:00:00"
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tmp_df = _FX(instrument=instrument, startdate = tmp_startdate, enddate = tmp_enddate)
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tmp_df = _index(instrument=instrument, startdate = tmp_startdate, enddate = tmp_enddate)
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if i == int(startdate[6:10]):
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df = tmp_df
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else:
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@ -110,8 +110,109 @@ def index(instrument = "eurusd", startdate = "2019-01-01", enddate = "2021-01-01
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df = df.reset_index(drop = True)
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return df
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def crypto(instrument = "btcusd", startdate = "2019-01-01", enddate = "2021-01-01"):
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startdate = datetime.strptime(startdate, "%Y-%m-%d").strftime("%m/%d/%y")
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enddate = datetime.strptime(enddate, "%Y-%m-%d").strftime("%m/%d/%y")
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df = pd.DataFrame()
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def _crypto(instrument = "btcusd", startdate = "01/01/2020", enddate = "01/01/2021"):
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"""
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https://www.marketwatch.com/investing/
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"""
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tmp_url = url["moneywatch"] + "cryptocurrency/{}/downloaddatapartial".format(instrument)
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ua = UserAgent(verify_ssl=False)
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request_header = {"User-Agent": ua.random}
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request_params = urlencode({
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"startdate": r"{}".format(startdate),
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"enddate": r"{}".format(enddate),
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"daterange": "d30",
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"frequency": "p1d",
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"csvdownload": "true",
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"downloadpartial": "false",
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"newdates": "false"}, quote_via= quote)
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r = requests.get(tmp_url, params=request_params.replace("%2F", "/").replace("%20", " ").replace("%3A", ":"), headers=request_header)
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data_text = r.content
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df = pd.read_csv(io.StringIO(data_text.decode('utf-8')))
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Date = []
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for i in range(0, len(df)):
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Date.append(datetime.strptime(df["Date"][i], "%m/%d/%Y"))
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df["Date"] = Date
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return df
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for i in range(int(startdate[6:10]), int(enddate[6:10])):
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if i == int(startdate[6:10]):
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tmp_startdate = startdate
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else:
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tmp_startdate = "01/01/" + str(i) + " 00:00:00"
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if (i+1) == int(enddate[6:10]):
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tmp_enddate = enddate
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else:
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tmp_enddate = "01/01/" + str(i+1) + " 00:00:00"
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tmp_df = _crypto(instrument=instrument, startdate = tmp_startdate, enddate = tmp_enddate)
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if i == int(startdate[6:10]):
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df = tmp_df
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else:
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df = pd.concat([tmp_df, df], axis=0)
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df = df.reset_index(drop = True)
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return df
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def stock(countrycode = "cn", instrument = "601988", startdate = "2019-01-01", enddate = "2021-01-01"):
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startdate = datetime.strptime(startdate, "%Y-%m-%d").strftime("%m/%d/%y")
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enddate = datetime.strptime(enddate, "%Y-%m-%d").strftime("%m/%d/%y")
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df = pd.DataFrame()
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def _stock(countrycode = "cn", instrument = "601988", startdate = "01/01/2020", enddate = "01/01/2021"):
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"""
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https://www.marketwatch.com/investing/
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"""
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tmp_url = url["moneywatch"] + "stock/{}/downloaddatapartial".format(instrument)
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ua = UserAgent(verify_ssl=False)
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request_header = {"User-Agent": ua.random}
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request_params = urlencode({
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"startdate": r"{}".format(startdate),
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"enddate": r"{}".format(enddate),
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"daterange": "d30",
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"frequency": "p1d",
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"csvdownload": "true",
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"downloadpartial": "false",
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"newdates": "false",
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"countrycode": "{}".format(countrycode)}, quote_via= quote)
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r = requests.get(tmp_url, params=request_params.replace("%2F", "/").replace("%20", " ").replace("%3A", ":"), headers=request_header)
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data_text = r.content
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df = pd.read_csv(io.StringIO(data_text.decode('utf-8')))
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Date = []
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for i in range(0, len(df)):
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Date.append(datetime.strptime(df["Date"][i], "%m/%d/%Y"))
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df["Date"] = Date
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return df
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for i in range(int(startdate[6:10]), int(enddate[6:10])):
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if i == int(startdate[6:10]):
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tmp_startdate = startdate
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else:
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tmp_startdate = "01/01/" + str(i) + " 00:00:00"
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if (i+1) == int(enddate[6:10]):
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tmp_enddate = enddate
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else:
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tmp_enddate = "01/01/" + str(i+1) + " 00:00:00"
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if countrycode == "us":
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countrycode = ""
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tmp_df = _stock(countrycode = countrycode, instrument=instrument, startdate = tmp_startdate, enddate = tmp_enddate)
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if i == int(startdate[6:10]):
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df = tmp_df
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else:
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df = pd.concat([tmp_df, df], axis=0)
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df = df.reset_index(drop = True)
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return df
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#https://www.marketwatch.com/investing/stock/googl/downloaddatapartial?startdate=05/05/2021 00:00:00&enddate=06/04/2021 23:59:59&daterange=d30&frequency=p1d&csvdownload=true&downloadpartial=false&newdates=false
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if __name__ == "__main__":
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data = FX()
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data = FX()
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@ -1,12 +1,16 @@
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__version__ = "0.1.1"
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__author__ = "TerenceLau"
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import sys
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import os
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__version__ = "0.1.2"
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__author__ = "Terence Lau"
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__data_source__ = open(os.path.join(
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os.path.dirname(__file__),
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'source.md')).read()
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if sys.version_info < (3, 6):
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print(f"CEDA {__version__} requires Python 3.6+")
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sys.exit(1)
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del sys
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from CEDA import *
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@ -0,0 +1,7 @@
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(https://www.eastmoney.com)
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(https://fred.stlouisfed.org/)
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(https://www.chicagofed.org/)
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(https://www.philadelphiafed.org/)
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(https://ec.europa.eu/eurostat/cache/infographs/economy/desktop/index.html)
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(https://www.ecb.europa.eu)
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(https://www.marketwatch.com/)
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@ -32,7 +32,7 @@ python -m pip install CEDApy
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* Thanks [Philadelphia Federal Reserve Bank](https://www.philadelphiafed.org/)
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* Thanks [eurostat Economic Indicators](https://ec.europa.eu/eurostat/cache/infographs/economy/desktop/index.html)
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* Thanks [Europen Central Bank](https://www.ecb.europa.eu)
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* Thanks [MarketWatch](https://www.marketwatch.com/)
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## If you want to cite...
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