Python으로 금융 데이터 가져오기와 관리
Stefan Jansen
Instructor




from pandas_datareader.data import DataReader from datetime import dateseries_code = 'DGS10' # 10년물 국채 금리data_source = 'fred' # 연준 경제 데이터 서비스start = date(1962, 1, 1)data = DataReader(series_code, data_source, start)data.info()
DatetimeIndex: 15754 entries, 1962-01-02 to 2022-05-20
Data columns (total 1 columns):
# Column Non-Null Count Dtype
-- ------ -------------- -----
0 DGS10 15083 non-null float64
dtypes: float64(1)
.rename(columns={old_name: new_name})series_name = '10년물 국채' data = data.rename(columns={series_code: series_name})data.plot(title=series_name); plt.show()

start = date(2000, 1, 1) series = 'DCOILWTICO' # 서부텍사스중질유(WTI) 가격oil = DataReader(series, 'fred', start)ticker = 'XOM' # 엑슨모빌 stock = DataReader(ticker, 'yanoo', start)data = pd.concat([stock[['Close']], oil], axis=1)data.info()
DatetimeIndex: 5841 entries, 2000-01-03 to 2022-05-23
Data columns (total 2 columns):
# Column Non-Null Count Dtype
-- ------ -------------- -----
0 Close 5634 non-null float64
1 DCOILWTICO 5615 non-null float64
data.columns = ['엑슨모빌', '유가']
data.plot()
plt.show()

Python으로 금융 데이터 가져오기와 관리