用 pandas 计算每一行中的非空值 [英] Count non-null values in each row with pandas
本文介绍了用 pandas 计算每一行中的非空值的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有数据框
site1 time1 site2 time2 site3 time3 site4 time4 site5 time5 ... time6 site7 time7 site8 time8 site9 time9 site10 time10 target
session_id
21669 56 2013-01-12 08:05:57 55.0 2013-01-12 08:05:57 NaN NaT NaN NaT NaN NaT ... NaT NaN NaT NaN NaT NaN NaT NaN NaT 0
54843 56 2013-01-12 08:37:23 55.0 2013-01-12 08:37:23 56.0 2013-01-12 09:07:07 55.0 2013-01-12 09:07:09 NaN NaT ... NaT NaN NaT NaN NaT NaN NaT NaN NaT 0
77292 946 2013-01-12 08:50:13 946.0 2013-01-12 08:50:14 951.0 2013-01-12 08:50:15 946.0 2013-01-12 08:50:15 946.0 2013-01-12 08:50:16 ... 2013-01-12 08:50:16 948.0 2013-01-12 08:50:16 784.0 2013-01-12 08:50:16 949.0 2013-01-12 08:50:17 946.0 2013-01-12 08:50:17 0
114021 945 2013-01-12 08:50:17 948.0 2013-01-12 08:50:17 949.0 2013-01-12 08:50:18 948.0 2013-01-12 08:50:18 945.0 2013-01-12 08:50:18 ... 2013-01-12 08:50:18 947.0 2013-01-12 08:50:19 945.0 2013-01-12 08:50:19 946.0 2013-01-12 08:50:19 946.0 2013-01-12 08:50:20 0
我需要计算 N 列,其中 site != NaN.我尝试使用
I need to count N of columns, where site != NaN. I try to use
df[['site%s' % i for i in range(1, 11)]].count(axis=1)
但它给我每个 id 返回 10
but it returns me 10 to every id
我也试过
train_df[sites].notnull().count(axis=1)
它也没有帮助.
期望输出
21669 2
54843 4
77292 10
114021 10
推荐答案
我会用 count
做到这一点:
I'd do this with just count
:
train_df[sites].count(axis=1)
count
专门计算非空值.您当前实现的问题是 notnull
产生布尔值,而 bool
肯定不是 null,这意味着它们总是被计算在内.
count
specifically counts non-null values. The issue with your current implementation is that notnull
yields boolean values, and bool
s are certainly not-null, meaning they are always counted.
df
one two three four five
a -0.166778 0.501113 -0.355322 bar False
b NaN NaN NaN NaN NaN
c -0.337890 0.580967 0.983801 bar False
d NaN NaN NaN NaN NaN
e 0.057802 0.761948 -0.712964 bar True
f -0.443160 -0.974602 1.047704 bar False
g NaN NaN NaN NaN NaN
h -0.717852 -1.053898 -0.019369 bar False
df.count(axis=1)
a 5
b 0
c 5
d 0
e 5
f 5
g 0
h 5
dtype: int64
还有……
df.notnull().count(axis=1)
a 5
b 5
c 5
d 5
e 5
f 5
g 5
h 5
dtype: int64
这篇关于用 pandas 计算每一行中的非空值的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!
查看全文