根据值插入列特定的NaN并删除行

时间:2016-06-14 20:20:24

标签: python pandas dataframe insert nan

我对昆虫进行了几次假设性测试。我想删除 result_1值低于10' 的行,我认为这些行不重要,但希望将NaN保留为单行的值显示执行了哪种测试以及哪种昆虫。

from pandas import Series, DataFrame
import numpy as np

A = Series(['A','A','B','B','B','C'])
B = Series(['ant','flea','flea','spider','spider','flea'])
C = Series([88,77,1,3,2,67])
D = Series(np.random.randn(6))

df = DataFrame({'test':A.values,'insect':B.values,
            'result_1':C.values,'result_2':D.values},
           columns=['test','insect','result_1','result_2'])
df

所以原始的Dataframe看起来像这样:

enter image description here

因为索引2,3和4的 results_1 值<10,所以我想删除所有这些行,但要注意一行是左边的(NaN在中都是< / strong>结果列)显示测试B是在跳蚤(index2)上进行的,应留下一行来表明测试B确实是在蜘蛛上进行的(索引3和4,需要丢弃一个另一个需要在结果列中插入NaN)。

因此,生成的Dataframe应如下所示:

enter image description here

1 个答案:

答案 0 :(得分:2)

我认为你可以使用:

#add NaN by condition
df.loc[df.result_1 < 10, ['result_1','result_2']] = np.nan 
#drop duplicated by column insect
df[df.result_1.isnull()] = df[df.result_1.isnull()].drop_duplicates(subset='insect')
df = df.dropna(how='all')
print (df)
  test  insect  result_1  result_2
0    A     ant      88.0 -0.037844
1    A    flea      77.0 -1.088879
2    B    flea       NaN       NaN
3    B  spider       NaN       NaN
5    C    flea      67.0  1.455632

找到相关索引的另一个解决方案然后dropindex

mask = df.result_1 < 10

df.loc[mask, ['result_1','result_2']] = np.nan 
a = df[mask].duplicated(subset='insect')
print (a)
2    False
3    False
4     True
dtype: bool

a = a[a].index
df = df.drop(a)
print (df)
  test  insect  result_1  result_2
0    A     ant      88.0 -0.176274
1    A    flea      77.0 -0.123691
2    B    flea       NaN       NaN
3    B  spider       NaN       NaN
5    C    flea      67.0 -0.310655