Question

我有一组数据，其中某些数据集包含需要更正的行'null'。

有规则要更正pandas数据框中的数据。

当音量为null时，请更改为0。
Open，High，Low，Close按照前一天的结束。具有2016-6-29的平均null将跟随2016-6-28的结束0.6

如果第一行为空，则会volume = 0和Open，high，Low Close，按照第二天的开放值

>>df_a   
Date,Stock,Open,High,Low,Close,Adj Close,Volume
2016-06-22,AWG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-23,AWG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-24,AWG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-27,AWG,0.600000,0.600000,0.600000,0.600000,0.600000,800
2016-06-28,AWG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-29,AWG,null,null,null,null,null,null
2016-06-30,AWG,null,null,null,null,null,null
2016-07-01,AWG,0.620000,0.650000,0.620000,0.650000,0.650000,40000
2016-07-04,AWG,null,null,null,null,null,null
2016-07-05,AWG,null,null,null,null,null,null
2016-07-07,AWG,0.625000,0.650000,0.565000,0.650000,0.650000,3000
2016-07-08,AWG,0.650000,0.650000,0.650000,0.650000,0.650000,0
2016-07-11,AWG,0.650000,0.650000,0.605000,0.605000,0.605000,6000
2016-07-12,AWG,0.640000,0.640000,0.640000,0.640000,0.640000,3300

>>df_b
Date,Stock,Open,High,Low,Close,Adj Close,Volume
2016-06-10,WG,null,null,null,null,null,null
2016-06-13,WG,null,null,null,null,null,null
2016-06-14,WG,0.600000,0.600000,0.600000,0.600000,0.600000,1000
2016-06-15,WG,0.600000,0.600000,0.600000,0.600000,0.600000,2000
2016-06-16,WG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-17,WG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-20,WG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-21,WG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-22,WG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-23,WG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-24,WG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-27,WG,0.600000,0.600000,0.600000,0.600000,0.600000,800
2016-06-28,WG,0.600000,0.600000,0.600000,0.600000,0.600000,0
2016-06-29,WG,null,null,null,null,null,null
2016-06-30,WG,null,null,null,null,null,null
2016-07-01,WG,0.620000,0.650000,0.620000,0.650000,0.650000,40000
2016-07-04,WG,null,null,null,null,null,null
2016-07-05,WG,null,null,null,null,null,null

我的部分代码：

volume = df_a['Volume'] == 'null'
df_a.loc[volume,'Volume'] = 0

但是，我无法继续Open，High，Low和Close。

Answer 1

第1部分（已经由你回答）

对于矢量化实现，最好将null转换为第一个nan（可能存在更好的解决方案）

第3部（替换第一行）

  df.replace('null',np.NaN,inplace=True)
  df.iloc[0].fillna(df.iloc[1].Open,inplace=True)

第2部分（用以前的关闭值替换所有空值）：

df['Close'].bfill(inplace=True)
df['Low'].fillna(df['Close'].shift(1),inplace=True)
df['Open'].fillna(df['Close'].shift(1),inplace=True)
df['High'].fillna(df['Close'].shift(1),inplace=True)
print(df)

Python：如何在pandas中修改null数据

1 个答案: