[英]Count rows with 1 or more NaNs in a Dataframe
I have the following: 我有以下内容:
print(df.isna().sum())
Which gives me: 这给了我:
city 2
country 0
testid 0
house 1807
house_number 248
po_box 1845
zipcode 260
road 132
state 1
state_district 1817
suburb 1800
unit 1806
I want the total number of rows that have 1 or more NaN
values from columns city, state, zip, and house
我想从列
city, state, zip, and house
中获得具有1个或多个NaN
值的总行数
Thanks for any suggestions. 谢谢你的任何建议。
This is how I would use isna
and sum
: 这是我如何使用
isna
和sum
:
cols = ['city', 'state', 'zip', 'house']
df[df[cols].isna().sum(axis=1) > 0]
Another option is calling dropna
and checking the length. 另一种选择是调用
dropna
并检查长度。
u = df.dropna(subset=['city', 'state', 'zip', 'house'])
len(df) - len(u)
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