我正在尝试创建一个包含大量股票的数据框，最终将其发送到 MySQL 数据库。我需要获取所有单独的数据帧并将它们连接在一起，保持它们的名称和日期唯一我当前遇到的问题是代码的连接部分抛出错误，我尝试了合并，但这样做会丢失每个数据帧的名称值，因此不适合我的需求。我也研究过使用面板，但我读到 .to_sql 函数仅适用于数据帧。任何帮助将不胜感激。
exchList =['A','AA','AAL','AAP','AAPL','ABBV','ABC','ABT','ACN','ADBE','ADI','ADM','ADP','ADS','ADSK','AEE','AEP']
main_df = pd.DataFrame()
start = datetime.datetime(2000,1,1)
end = datetime.date.today()
for ticker in exchList:
df = web.DataReader(ticker, "yahoo",start, end)
df.reset_index(level=df.index.names, inplace=True)
if main_df.empty:
main_df = df
else:
main_df = main_df.join(df)
错误如下。
ValueError: columns overlap but no suffix specified: Index(['Date', 'Open', 'High', 'Low', 'Close', 'Volume', 'Adj Close'], dtype='object')
最佳答案
有一种更优雅的方法可以做到这一点 - 将所有代码的数据一步读取到 Pandas.Panel，然后将 Panel 的 flatten 读取到 数据框:
In [126]: p = web.DataReader(exchList, "yahoo",start, end)
In [129]: p.to_frame()
Out[129]:
Open High Low Close Volume Adj Close
Date minor
2000-01-03 A 78.749999 78.937500 67.374999 72.000003 4674300.0 46.106304
AAPL 104.874997 112.499998 101.687501 111.937502 133949200.0 3.625643
ABC 15.500000 15.750000 15.250000 15.562500 2784800.0 3.297376
ABT 35.249948 35.999945 34.749947 34.999948 10635000.0 9.517434
ADBE 67.250000 67.500000 64.250000 65.562500 7384400.0 16.274673
ADI 93.500000 93.875000 88.000000 90.187500 3655600.0 32.584012
ADM 11.999999 12.062499 11.875000 11.999999 984600.0 7.798824
ADP 53.499906 53.937406 51.937409 51.999911 2698800.0 28.858381
ADSK 34.000000 34.625000 32.125000 33.375000 2845600.0 8.052905
AEE 32.562500 32.625000 31.562500 32.312500 700800.0 13.102718
... ... ... ... ... ... ...
2017-02-23 ABT 45.029999 45.509998 44.849998 45.400002 9389100.0 45.400002
ACN 122.589996 122.709999 121.730003 122.480003 1428000.0 122.480003
ADBE 120.099998 120.150002 118.029999 118.830002 2381700.0 118.830002
ADI 82.150002 82.160004 81.029999 81.610001 2277500.0 81.610001
ADM 44.799999 45.270000 44.490002 45.090000 3256200.0 45.090000
ADP 100.790001 101.779999 100.489998 101.639999 1459300.0 101.639999
ADS 240.589996 243.520004 239.279999 242.419998 650800.0 242.419998
ADSK 86.690002 87.370003 85.919998 87.099998 1368000.0 87.099998
AEE 54.230000 54.270000 53.689999 54.070000 1438100.0 54.070000
AEP 65.550003 66.089996 65.309998 66.010002 2272900.0 66.010002
[63153 rows x 6 columns]
您可能还想重置多重索引:
In [130]: p.to_frame().reset_index()
Out[130]:
Date minor Open High Low Close Volume Adj Close
0 2000-01-03 A 78.749999 78.937500 67.374999 72.000003 4674300.0 46.106304
1 2000-01-03 AAPL 104.874997 112.499998 101.687501 111.937502 133949200.0 3.625643
2 2000-01-03 ABC 15.500000 15.750000 15.250000 15.562500 2784800.0 3.297376
3 2000-01-03 ABT 35.249948 35.999945 34.749947 34.999948 10635000.0 9.517434
4 2000-01-03 ADBE 67.250000 67.500000 64.250000 65.562500 7384400.0 16.274673
5 2000-01-03 ADI 93.500000 93.875000 88.000000 90.187500 3655600.0 32.584012
6 2000-01-03 ADM 11.999999 12.062499 11.875000 11.999999 984600.0 7.798824
7 2000-01-03 ADP 53.499906 53.937406 51.937409 51.999911 2698800.0 28.858381
8 2000-01-03 ADSK 34.000000 34.625000 32.125000 33.375000 2845600.0 8.052905
9 2000-01-03 AEE 32.562500 32.625000 31.562500 32.312500 700800.0 13.102718
... ... ... ... ... ... ... ... ...
63143 2017-02-23 ABT 45.029999 45.509998 44.849998 45.400002 9389100.0 45.400002
63144 2017-02-23 ACN 122.589996 122.709999 121.730003 122.480003 1428000.0 122.480003
63145 2017-02-23 ADBE 120.099998 120.150002 118.029999 118.830002 2381700.0 118.830002
63146 2017-02-23 ADI 82.150002 82.160004 81.029999 81.610001 2277500.0 81.610001
63147 2017-02-23 ADM 44.799999 45.270000 44.490002 45.090000 3256200.0 45.090000
63148 2017-02-23 ADP 100.790001 101.779999 100.489998 101.639999 1459300.0 101.639999
63149 2017-02-23 ADS 240.589996 243.520004 239.279999 242.419998 650800.0 242.419998
63150 2017-02-23 ADSK 86.690002 87.370003 85.919998 87.099998 1368000.0 87.099998
63151 2017-02-23 AEE 54.230000 54.270000 53.689999 54.070000 1438100.0 54.070000
63152 2017-02-23 AEP 65.550003 66.089996 65.309998 66.010002 2272900.0 66.010002
[63153 rows x 8 columns]
关于python - 连接 pandas 数据框时出错，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/42446659/