Pandas 根据多个条件删除和移动列中的单元格

Question

我有一种情况，我想根据某些条件删除和移动 pandas 数据框中的单元格。我的数据框如下所示：

Value_1      ID_1      Value_2      ID_2         Value_3      ID_3
   A           1            D         1               G          1
   B           1            E         2               H          1
   C           1            F         2               I          3
   C           1            F         2               H          1

现在我要比较以下条件：

ID_2 and ID_3 should always be less than or equal to ID_1. If anyone of them is greater than ID_1 then that cell should be deleted and shifted with the next column cell

输出应如下所示：

    Value_1      ID_1      Value_2      ID_2         Value_3      ID_3
       A           1            D         1               G          1
       B           1            H         1           blank        nan
       C           1       blank        nan           blank        nan
       C           1            H         1           blank        nan

Answer 1

您可以按条件创建掩码，此处用于更大的值，例如 ID_1 by DataFrame.gt::

cols1 = ['Value_2','Value_3']
cols2 = ['ID_2','ID_3']

m = df[cols2].gt(df['ID_1'], axis=0)
print (m)
    ID_2   ID_3
0  False  False
1   True  False
2   True   True
3   True  False

如果通过 DataFrame.mask:

匹配掩码，则替换缺失值

df[cols2] = df[cols2].mask(m) 
df[cols1] = df[cols1].mask(m.to_numpy())

最后一次使用 DataFrame.shift with set new columns by Series.mask:

df1 = df[cols2].shift(-1, axis=1)
df['ID_2'] =  df['ID_2'].mask(m['ID_2'], df1['ID_2'])
df['ID_3'] =  df['ID_3'].mask(m['ID_2'])

df2 = df[cols1].shift(-1, axis=1)
df['Value_2'] =  df['Value_2'].mask(m['ID_2'], df2['Value_2'])
df['Value_3'] =  df['Value_3'].mask(m['ID_2'])

print (df)
  Value_1  ID_1 Value_2  ID_2 Value_3  ID_3
0       A     1       D   1.0       G   1.0
1       B     1       H   1.0     NaN   NaN
2       C     1     NaN   NaN     NaN   NaN
3       C     1       H   1.0     NaN   NaN

如有必要，最后用空字符串替换：

df[cols1] = df[cols1].fillna('')
print (df)
  Value_1  ID_1 Value_2  ID_2 Value_3  ID_3
0       A     1       D   1.0       G   1.0
1       B     1       H   1.0           NaN
2       C     1           NaN           NaN
3       C     1       H   1.0           NaN

Pandas 根据多个条件删除和移动列中的单元格

Pandas delete and shift cells in a column basis multiple conditions

python-3.x

pandas

merge

shift

del