add XHData
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@ -1,6 +1,14 @@
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import ast
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import json
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import requests
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import pandas as pd
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from tqdm import tqdm
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from pygtrans import Translate
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def translate(text:str=None):
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client = Translate()
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text = client.translate(text, target="en")
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return text.translatedText
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url = {
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"CNFIN": "https://api.cnfin.com/roll/charts/"
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@ -10,203 +18,10 @@ class XHData(object):
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def __init__(self):
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pass
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def download(self, id:int=None):
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tmp_url = url["CNFIN"] + "getContent?ids={}".format(id)
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r = requests.get(tmp_url)
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if r.ok:
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raw_data = r.json()
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data = pd.DataFrame(ast.literal_eval(raw_data["data"]["list"][0]["content"]))
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return data
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else:
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return ValueError("Something went wrong, try again later")
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def GDP(self):
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"""
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quarterly
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"""
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data = self.download(id=12006)
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data.columns = ["date", "data"]
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return data
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def Household_Consumption_SPLY(self):
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"""
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quarterly
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"""
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data = self.download(id=12073)
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data.columns = ["date", "data"]
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return data
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def Household_Consumption(self):
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"""
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quarterly
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"""
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data = self.download(id=12074)
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data.columns = ["date", "data"]
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return data
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def Per_capita_Disposable_Income(self):
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"""
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quarterly
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"""
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data = self.download(id=12071)
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data.columns = ["date", "data"]
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return data
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def Urban_Average_Salary_Annual(self):
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"""
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quarterly
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"""
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data = self.download(id=12070)
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data.columns = ["date", "data"]
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return data
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def Urban_Uneployment_Rate(self):
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"""
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quarterly
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"""
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data = self.download(id=12069)
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data.columns = ["date", "data"]
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return data
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def Government_Bound_Return_Rate_10_Year(self):
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"""
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quarterly
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"""
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data = self.download(id=12068)
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data.columns = ["date", "data"]
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return data
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def Government_Bound_Return_Rate_3_Year(self):
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"""
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quarterly
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"""
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data = self.download(id=12067)
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data.columns = ["date", "data"]
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return data
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def Government_Bound_Return_Rate_1_Year(self):
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"""
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quarterly
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"""
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data = self.download(id=12066)
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data.columns = ["date", "data"]
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return data
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def LPR_1_Year(self):
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"""
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Monthly
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"""
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data = self.download(id=12065)
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data.columns = ["date", "data"]
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return data
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def SHIBOR_3_Month(self):
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"""
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Daily
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"""
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data = self.download(id=12064)
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data.columns = ["date", "data"]
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return data
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def SHIBOR_2_Week(self):
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"""
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Daily
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"""
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data = self.download(id=12063)
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data.columns = ["date", "data"]
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return data
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def SHIBOR_1_Day(self):
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"""
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Daily
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"""
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data = self.download(id=12063)
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data.columns = ["date", "data"]
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return data
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def Foreign_Exchange_Options(self):
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data = self.download(id=12060)
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data.columns = ["date", "data"]
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return data
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def Foreign_Exchange_Swaps(self):
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data = self.download(id=12059)
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data.columns = ["date", "data"]
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return data
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def Foreign_Exchange_Forward(self):
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data = self.download(id=12058)
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data.columns = ["date", "data"]
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return data
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def Foreign_Exchange_Spot(self):
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data = self.download(id=12057)
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data.columns = ["date", "data"]
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return data
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def Loan_to_Deposit(self):
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data = self.download(id=12056)
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data.columns = ["date", "data"]
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return data
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def RMB_Deposits(self):
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data = self.download(id=12055)
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data.columns = ["date", "data"]
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return data
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def RMB_Loan(self):
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data = self.download(id=12054)
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data.columns = ["date", "data"]
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return data
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def M0_SPLY(self):
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data = self.download(id=12053)
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data.columns = ["date", "data"]
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return data
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def M1_SPLY(self):
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data = self.download(id=12052)
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data.columns = ["date", "data"]
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return data
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def M2_SPLY(self):
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data = self.download(id=12051)
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data.columns = ["date", "data"]
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return data
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def M0(self):
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data = self.download(id=12050)
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data.columns = ["date", "data"]
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return data
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def M1(self):
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data = self.download(id=12049)
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data.columns = ["date", "data"]
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return data
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def M2(self):
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data = self.download(id=12048)
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data.columns = ["date", "data"]
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return data
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def Total_Retail_Sales_of_Consumer_Goods_LP(self):
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data = self.download(id=12047)
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data.columns = ["date", "data"]
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return data
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def Total_Retail_Sales_of_Consumer_Goods_SPLY(self):
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data = self.download(id=12046)
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data.columns = ["date", "data"]
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return data
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"""
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import json
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import requests
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from tqdm import tqdm
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urls, titles = [], []
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for i in tqdm(range(5000, 20000)):
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def toc(self):
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urls, tid, titles, titles_en = [], [], [], []
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for i in tqdm(range(12005, 12100)):
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url = "https://api.cnfin.com/roll/charts/getContent?ids={}".format(i)
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r = requests.get(url)
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if r.ok:
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@ -215,9 +30,25 @@ for i in tqdm(range(5000, 20000)):
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pass
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else:
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urls.append(url)
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titles.append(json.loads(data["data"]["list"][0]["modelCode"])["title"]["text"])
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"""
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tid.append(i)
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title = json.loads(data["data"]["list"][0]["modelCode"])["title"]["text"]
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titles.append(title)
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titles_en.append(translate(text=title))
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return pd.DataFrame({"urls":urls, "id":tid, "title_zh":titles, "title_en":titles_en})
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def download_data(self, iid:int=None):
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tmp_url = url["CNFIN"] + "getContent?ids={}".format(iid)
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r = requests.get(tmp_url)
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if r.ok:
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raw_data = r.json()
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data = pd.DataFrame(ast.literal_eval(raw_data["data"]["list"][0]["content"]))
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data.columns = ["date", "data"]
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return data
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else:
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return ValueError("Something went wrong, try again later")
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if __name__ == "__main__":
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xhdata = XHData()
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toc = xhdata.toc()
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data = xhdata.download_data(iid=12006) # GDP
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@ -24,7 +24,7 @@ We have included multiple API for banks or statistics deparment of countries/reg
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* Asia:
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- [ ] `NBSCData` for [National Bureau of Statistics of China](http://www.stats.gov.cn/english/)
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- [ ] `XHData` for [Xinhua](https://www.cnfin.com/data/macro-data/index.html)
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- [x] `XHData` for [Xinhua](https://www.cnfin.com/data/macro-data/index.html)
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- [x] `BOJData` for [Bank of Japan](https://www.boj.or.jp/en/index.htm/)
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### Market Data
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