python - 用 Python 中特定列的先前值填充 NaN

Question

我有一个 Pandas 数据框，如下所示:

df =

                      open       high        low      close
Timestamp                                                      
2014-01-07 13:18:00  874.67040  892.06753  874.67040  892.06753
2014-01-07 13:19:00        NaN        NaN        NaN        NaN
2014-01-07 13:20:00        NaN        NaN        NaN        NaN
2014-01-07 13:21:00  883.23085  883.23085  874.48165  874.48165
2014-01-07 13:22:00        NaN        NaN        NaN        NaN

对于每个 NaN，它们都应采用前一时期的收盘价。

编辑:我试过使用 df.fillna(method='ffill') 但它使每个 NaN 直接在其上方取值。我希望每个 NaN 只取它前面的 Close 值。

使用填充产量:

                      open       high        low      close
Timestamp                                                      
2014-01-07 13:18:00  874.67040  892.06753  874.67040  892.06753
2014-01-07 13:19:00  874.67040  892.06753  874.67040  892.06753

但我正在寻找:

                      open       high        low      close
Timestamp                                                      
2014-01-07 13:18:00  874.67040  892.06753  874.67040  892.06753
2014-01-07 13:19:00  892.06753  892.06753  892.06753  892.06753

Answer 1

几种方式:

In [3166]: df.apply(lambda x: x.fillna(df.close.shift())).ffill()
Out[3166]:
                          open       high        low      close
Timestamp
2014-01-07 13:18:00  874.67040  892.06753  874.67040  892.06753
2014-01-07 13:19:00  892.06753  892.06753  892.06753  892.06753
2014-01-07 13:20:00  892.06753  892.06753  892.06753  892.06753
2014-01-07 13:21:00  883.23085  883.23085  874.48165  874.48165
2014-01-07 13:22:00  874.48165  874.48165  874.48165  874.48165

---

In [3167]: df.fillna({c: df.close.shift() for c in df}).ffill()
Out[3167]:
                          open       high        low      close
Timestamp
2014-01-07 13:18:00  874.67040  892.06753  874.67040  892.06753
2014-01-07 13:19:00  892.06753  892.06753  892.06753  892.06753
2014-01-07 13:20:00  892.06753  892.06753  892.06753  892.06753
2014-01-07 13:21:00  883.23085  883.23085  874.48165  874.48165
2014-01-07 13:22:00  874.48165  874.48165  874.48165  874.48165