用条件填充列

Question

我有一个包含2列的数据框：

          Col1          Col2
1          NaN         Someval1
2           Y          Someval2
3           N          Someval3
4          NaN           NaN
5          NaN         Someval4

我希望您能使用以下条件填充NaN值：

If Col1 has NaN and Col2 has a Someval1 that is in list 1 then fillna with Y
If Col1 has NaN and Col2 has a Someval4 that is in list 2 then fillna with N
If Col1 has NaN and Col2 has a NaN that is in list 2 then fillna with N

任何建议？（不知道是否可能）

非常感谢！

- datascana

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列表1中的NaN是什么意思？ :) - tworec

列表2，感谢验证，我会进行编辑。 - datascana

Answer 1

我认为你需要使用mask函数，针对isnull和isin条件：

L1 = ['Someval1','Someval8']
L2 = ['Someval4','Someval9', np.nan]
m1 = df['Col1'].isnull()
m2 = df['Col2'].isin(L1)
m3 = df['Col2'].isin(L2)

df['Col1'] = df['Col1'].mask(m1 & m2, 'Y')
df['Col1'] = df['Col1'].mask(m1 & m3, 'N')

print (df)
  Col1      Col2
1    Y  Someval1
2    Y  Someval2
3    N  Someval3
4    N       NaN
5    N  Someval4

使用numpy.where的另一种解决方案:

df['Col1'] = np.where(m1 & m2, 'Y',
             np.where(m1 & m3, 'N', df['Col1']))

print (df)
  Col1      Col2
1    Y  Someval1
2    Y  Someval2
3    N  Someval3
4    N       NaN
5    N  Someval4

另一种使用一个条件以及 fillna 的解决方案:

L1 = ['Someval1','Someval8']
L2 = ['Someval4','Someval9', np.nan]

df['Col1'] = df['Col1'].mask(df['Col2'].isin(L1), df['Col1'].fillna('Y'))
df['Col1'] = df['Col1'].mask(df['Col2'].isin(L2), df['Col1'].fillna('N'))
print (df)
  Col1      Col2
1    Y  Someval1
2    Y  Someval2
3    N  Someval3
4    N       NaN
5    N  Someval4

- jezrael

Answer 2

这里是.loc的解决方案

df.loc[df.Col1.isnull() & df.Col2.isin(['Someval1']), 'Col1'] = 'Y'
df.loc[df.Col1.isnull() & df.Col2.isin(['Someval4']), 'Col1'] = 'N'
df.loc[df.Col1.isnull() & df.Col2.isin([np.nan]), :] = 'N'

完整脚本：

df = pd.read_csv(StringIO("""Col1          Col2
1          NaN         Someval1
2           Y          Someval2
3           N          Someval3
4          NaN           NaN
5          NaN         Someval4
"""), sep="\s+")

df.loc[df.Col1.isnull() & df.Col2.isin(['Someval1']), 'Col1'] = 'Y'
df.loc[df.Col1.isnull() & df.Col2.isin(['Someval4']), 'Col1'] = 'N'
df.loc[df.Col1.isnull() & df.Col2.isin([np.nan]), :] = 'N'

df

  Col1      Col2
1    Y  Someval1
2    Y  Someval2
3    N  Someval3
4    N         N
5    N  Someval4

- tworec

Answer 3

您可以使用

df.Col1[(df['Col1'].isnull())&(df['Col2']=='Someval1')] = 'Y'
df.Col1[(df['Col1'].isnull())&(df['Col2']=='Someval4')] = 'N'
df.Col1[(df['Col1'].isnull())&(df['Col2'].isnull())] = 'N'

- danche

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第二行覆盖了第五行的“Someval4”；第二行和第三行不支持在第四行和第五行中使用fillna函数来填充Col1。 - tworec

@tworec 我认为 list 2 指的是 第二列, 我会修改它。 - danche