根据另一个特定列显示特定列的缺失值

时间:2016-09-01 05:45:43

标签: python pandas dataframe multiple-columns nan

这是我的问题

我们说数据框上有2列,如下所示:

 Type   | Killed
_______ |________
 Dog        1
 Dog       nan
 Dog       nan
 Cat        4
 Cat       nan
 Cow        1
 Cow       nan

我想根据类型显示所有缺失的值并计算它们

我的愿望结果看起来像这样:

Type | Sum(isnull)
Dog       2
Cat       1
Cow       1

无论如何都要显示这个?

2 个答案:

答案 0 :(得分:3)

您可以boolean indexing使用value_counts

print (df.ix[df.Killed.isnull(), 'Type'].value_counts().reset_index(name='Sum(isnull)'))

  index  Sum(isnull)
0   Dog            2
1   Cow            1
2   Cat            1

或汇总size,似乎更快:

print (df[df.Killed.isnull()]
            .groupby('Type')['Killed']
            .size()
            .reset_index(name='Sum(isnull)'))

  Type  Sum(isnull)
0  Cat           1
1  Cow           1
2  Dog           2

<强>计时

df = pd.concat([df]*1000).reset_index(drop=True)

In [30]: %timeit (df.ix[df.Killed.isnull(), 'Type'].value_counts().reset_index(name='Sum(isnull)'))
100 loops, best of 3: 5.36 ms per loop

In [31]: %timeit (df[df.Killed.isnull()].groupby('Type')['Killed'].size().reset_index(name='Sum(isnull)'))
100 loops, best of 3: 2.02 ms per loop

答案 1 :(得分:1)

I can get you both isnull and notnull

isnull = np.where(df.Killed.isnull(), 'isnull', 'notnull')
df.groupby([df.Type, isnull]).size().unstack()

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