#!/usr/bin/env python
# coding: utf-8

# **[mark down math functions](https://twinstarinfo.blogspot.com/2019/11/bloggerblogspot-markdown-mathjax.html)** \\  **[Finance-data](https://github.com/FinanceData/FinanceDataReader)**
# 
# - ! pip install finance-datareader
# - ! pip install beautifulsoup4
# 

# In[1]:


get_ipython().run_line_magic('matplotlib', 'inline')
get_ipython().run_line_magic('config', "InlineBackend.figure_format = 'retina'")
# Loading ... Visualization Modules
import matplotlib.pyplot as plt
import warnings
plt.style.use('seaborn')
warnings.simplefilter(action='ignore', category=FutureWarning)

from matplotlib.font_manager import fontManager as fm # 한글폰트 확인 및 추가
font_list_check  = ['D2Coding', 'NanumGothicCoding', 'NanumGothic']
for _ in font_list_check:
    font_counts = [f  for f in font_list_check if _ in [_.name for _ in fm.ttflist]]
    if len(font_counts) > 1: print(f"found : {_}"); plt.rc('font', family=_); break 


# In[2]:


# S&P 500 지수와 VIX 지수를 다운로드 합니다
import yfinance as yf
df = yf.download(['^GSPC', '^VIX'], 
                 start='1999-01-01', 
                 end='2022-12-31',
                 progress=False)
df = df[['Adj Close']].copy()
df.columns = df.columns.droplevel(0)
df = df.rename(columns={'^GSPC': 'sp500', '^VIX': 'vix'})


# In[3]:


# yahoo finance 를 활용한 주가수집
# loading ... the Financial DataSet
import os
import pandas as pd

def fd_csv(file_name, code='', date_start='', date_end=''):
    if os.path.isfile(file_name):     # Checking the File exist
        data = pd.read_csv(file_name)
        data['Date'] = pd.to_datetime(data['Date']) # datetime 포맷
        data = data.set_index('Date') # 변경된 컬럼을 Index 로 설정
    else:                             # if not, download the data
        from FinanceDataReader import DataReader as fdr
        data = fdr(code, date_start, date_end).reset_index()
        data.to_csv(file_name, index=None)
        data = data.set_index('Date')
    return data

# Finance DataSet 생성하기
file_name = './data/stock-msft.csv'
data_csv = fd_csv(file_name, 'MSFT', date_start='2020-1-1', date_end='2021-3-31')
data_csv.tail(3)


# In[4]:


# yahoo finance 를 활용한 주가수집
# loading ... the Financial DataSet
import os
import pandas as pd

def yf_csv(file_name, code='', date_start='', date_end=''):
    if os.path.isfile(file_name):  # Checking the File exist
        data = pd.read_csv(file_name)
        data['Date'] = pd.to_datetime(data['Date']) # datetime 포맷 변경
        data = data.set_index('Date')               # 변경된 컬럼을 Index 로 설정
    else:  # if not, download the data
        import yfinance as yf
        data = yf.download(code, start=date_start, end=date_end,
            progress=False, auto_adjust=True).reset_index()
        data.to_csv(file_name, index=None)
        data = data.set_index('Date')
    return data

# Finance DataSet 생성하기
file_name = './data/stock-samsung.csv'
data_csv = yf_csv(file_name, '005930', date_start='2020-1-1', date_end='2021-3-31')
data_csv.tail(3)


# In[12]:


data_csv['2021-MAR-1':'2021-MAY-1'].tail()


# In[ ]:


data_csv


# In[6]:


import os
import pandas as pd

class StockCSV:
    
    #def __init__(self):
    #    self.code = '005930'
        
    def finance(self, code='', date_start='', date_end='', file_name=None):
        r'''Finance Data Reacer : CSV file save & loader
        https://github.com/FinanceData/FinanceDataReader/blob/master/README.md'''
        # case 1 : 파일을 지정한 경우
        if file_name:
            ## 01 Loading from CSV
            if os.path.isfile(file_name):     # Checking the File exist
                data = pd.read_csv(file_name)
                data['Date'] = pd.to_datetime(data['Date']) # datetime 포맷
                data = data.set_index('Date') # 변경된 컬럼을 Index 로 설정
            ## 02 Loading from Py Module API
            else:                             # if not, download the data
                from FinanceDataReader import DataReader as fdr
                data = fdr(code, date_start, date_end).reset_index()
                data.to_csv(file_name, index=None)
                data = data.set_index('Date')
        # case 2 : 파일을 지정하지 않은경우
        else:
            from FinanceDataReader import DataReader as fdr
            data = fdr(code, date_start, date_end)            
        return data
    
    
    def yahoo(self, code='', date_start='', date_end='', file_name=None):
        r'''Yahoo Finance : CSV file save & loader'''
        # case 1 : 파일을 지정한 경우
        if file_name:
            ## 01 Loading from CSV
            if os.path.isfile(file_name):  # Checking the File exist
                data = pd.read_csv(file_name)
                data['Date'] = pd.to_datetime(data['Date']) # datetime 포맷 변경
                data = data.set_index('Date')               # 변경된 컬럼을 Index 로 설정
            ## 02 Loading from Py Module API
            else:  # if not, download the data
                import yfinance as yf
                data = yf.download(code, start=date_start, end=date_end,
                    progress=False, auto_adjust=True).reset_index()
                data.to_csv(file_name, index=None)
                data = data.set_index('Date')
        # case 2 : 파일을 지정하지 않은경우
        else:
            import yfinance as yf
            data = yf.download(code, start=date_start, end=date_end,
                progress=False, auto_adjust=True) #.reset_index()
        return data  


# In[7]:


reader = StockCSV()
# reader.finance('005930', '2020-01-01','2021-01-01', './data/test.csv')
reader.finance('005930', '2020-01-01','2021-01-01').tail()


# ### **2) BOK EOS 한국은행 통계정보 API**
# - **[한국은행 API Key 확인하기](https://ecos.bok.or.kr/jsp/openapi/OpenApiController.jsp?t=myAuthKey#)**
# - **[한국은행 통계코드 검색](https://ecos.bok.or.kr/jsp/openapi/OpenApiController.jsp?t=guideStatCd&menuGroup=MENU000004&menuCode=MENU000024)**
# - **[Python Tutorial](https://ecos.bok.or.kr/jsp/openapi/OpenApiController.jsp?t=guideDevGuide&menuGroup=MENU000004&menuCode=MENU000017)**
# - **[Python Example](https://hayjo.tistory.com/57)** // **[파이썬 자료수집 예시](https://bjecondata.blogspot.com/2019/08/open-api-ecos-ii.html)**

# In[8]:


# https://bjecondata.blogspot.com/2019/08/open-api-ecos-ii.html
import pandas as pd
code_table = pd.read_csv('./data/BOK_ECOS_EXAMPLE.csv')
code_table.head(3)


# In[9]:


# 필요한 자료코드 추출하기
search_text = '인플레'
code_index = [no   for no, _ in enumerate(code_table['통계명'].to_list())
              if _.find(search_text) != -1]
code_example = code_table.iloc[code_index, :].reset_index(drop=True)
code_example.head(3)
# code_example['URL'][:3].to_list()


# In[10]:


from data.finance import bok_eos_api
eos_table = bok_eos_api('040Y003', date_end='20210101', code2='FMB')  # 7년 단위로만 추출가능
eos_table['DATA_VALUE'] = list(map(lambda x : float(x),  eos_table['DATA_VALUE']))
eos_table = eos_table.rename(columns={'DATA_VALUE':'cpi', 'TIME':'Date'})

eos_table['Date'] = pd.to_datetime(eos_table['Date'], format='%Y%m')
eos_table = eos_table.set_index('Date')  # eos_table.head(3)
eos_table = eos_table[['cpi']]
# ploting the DataSet
eos_table.head(3)