224 lines
5.3 KiB
Python
224 lines
5.3 KiB
Python
import ast
|
|
import requests
|
|
import pandas as pd
|
|
|
|
url = {
|
|
"CNFIN": "https://api.cnfin.com/roll/charts/"
|
|
}
|
|
|
|
class XHData(object):
|
|
def __init__(self):
|
|
pass
|
|
|
|
def download(self, id:int=None):
|
|
tmp_url = url["CNFIN"] + "getContent?ids={}".format(id)
|
|
r = requests.get(tmp_url)
|
|
if r.ok:
|
|
raw_data = r.json()
|
|
data = pd.DataFrame(ast.literal_eval(raw_data["data"]["list"][0]["content"]))
|
|
return data
|
|
else:
|
|
return ValueError("Something went wrong, try again later")
|
|
|
|
|
|
def GDP(self):
|
|
"""
|
|
quarterly
|
|
"""
|
|
data = self.download(id=12006)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Household_Consumption_SPLY(self):
|
|
"""
|
|
quarterly
|
|
"""
|
|
data = self.download(id=12073)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Household_Consumption(self):
|
|
"""
|
|
quarterly
|
|
"""
|
|
data = self.download(id=12074)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Per_capita_Disposable_Income(self):
|
|
"""
|
|
quarterly
|
|
"""
|
|
data = self.download(id=12071)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Urban_Average_Salary_Annual(self):
|
|
"""
|
|
quarterly
|
|
"""
|
|
data = self.download(id=12070)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Urban_Uneployment_Rate(self):
|
|
"""
|
|
quarterly
|
|
"""
|
|
data = self.download(id=12069)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Government_Bound_Return_Rate_10_Year(self):
|
|
"""
|
|
quarterly
|
|
"""
|
|
data = self.download(id=12068)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Government_Bound_Return_Rate_3_Year(self):
|
|
"""
|
|
quarterly
|
|
"""
|
|
data = self.download(id=12067)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Government_Bound_Return_Rate_1_Year(self):
|
|
"""
|
|
quarterly
|
|
"""
|
|
data = self.download(id=12066)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def LPR_1_Year(self):
|
|
"""
|
|
Monthly
|
|
"""
|
|
data = self.download(id=12065)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def SHIBOR_3_Month(self):
|
|
"""
|
|
Daily
|
|
"""
|
|
data = self.download(id=12064)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def SHIBOR_2_Week(self):
|
|
"""
|
|
Daily
|
|
"""
|
|
data = self.download(id=12063)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def SHIBOR_1_Day(self):
|
|
"""
|
|
Daily
|
|
"""
|
|
data = self.download(id=12063)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Foreign_Exchange_Options(self):
|
|
data = self.download(id=12060)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Foreign_Exchange_Swaps(self):
|
|
data = self.download(id=12059)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Foreign_Exchange_Forward(self):
|
|
data = self.download(id=12058)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Foreign_Exchange_Spot(self):
|
|
data = self.download(id=12057)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Loan_to_Deposit(self):
|
|
data = self.download(id=12056)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def RMB_Deposits(self):
|
|
data = self.download(id=12055)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def RMB_Loan(self):
|
|
data = self.download(id=12054)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def M0_SPLY(self):
|
|
data = self.download(id=12053)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def M1_SPLY(self):
|
|
data = self.download(id=12052)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def M2_SPLY(self):
|
|
data = self.download(id=12051)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def M0(self):
|
|
data = self.download(id=12050)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def M1(self):
|
|
data = self.download(id=12049)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def M2(self):
|
|
data = self.download(id=12048)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Total_Retail_Sales_of_Consumer_Goods_LP(self):
|
|
data = self.download(id=12047)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
def Total_Retail_Sales_of_Consumer_Goods_SPLY(self):
|
|
data = self.download(id=12046)
|
|
data.columns = ["date", "data"]
|
|
return data
|
|
|
|
"""
|
|
import json
|
|
import requests
|
|
from tqdm import tqdm
|
|
|
|
urls, titles = [], []
|
|
for i in tqdm(range(5000, 20000)):
|
|
url = "https://api.cnfin.com/roll/charts/getContent?ids={}".format(i)
|
|
r = requests.get(url)
|
|
if r.ok:
|
|
data = r.json()
|
|
if data["data"] == "图表数据不存在":
|
|
pass
|
|
else:
|
|
urls.append(url)
|
|
titles.append(json.loads(data["data"]["list"][0]["modelCode"])["title"]["text"])
|
|
"""
|
|
|
|
|
|
|
|
|