Python，Pandas：只返回那些有缺失值的行

Question

While working in Pandas in Python...

I'm working with a dataset that contains some missing values, and I'd like to return a dataframe which contains only those rows which have missing data. Is there a nice way to do this?

(My current method to do this is an inefficient "look to see what index isn't in the dataframe without the missing values, then make a df out of those indices.")

Answer 1

您可以使用any axis=1来检查每行是否至少有一个True ，然后使用布尔索引进行过滤：

null_data = df[df.isnull().any(axis=1)]

Answer 2

df.isnull().any(axis = 1).sum()

这为您提供了至少一个缺失数据的总行数

Answer 3

如果您只想查看包含 NaN 值的行，您可以执行以下操作：

data_frame[data_frame.iloc[:, insert column number here]=='NaN']

Answer 4

您可以通过这种方式使用代码

sum(df.isnull().any(axis=1))

Answer 5

Similar to metersk's answer,

null_data = df[np.logical_or.reduce(df.isnull().values, axis=1)]

Test

n = 2
df = pd.DataFrame({'a':np.tile([0,1,2,3,4,np.nan],n),
                   'b':np.tile([0,1,2,3,np.nan,5],n)})

x = df[np.logical_or.reduce(df.isnull().values,axis=1)]
y = df[df.isnull().any(axis=1)]
x.equals(y)

Answer 6

我刚遇到这个问题我假设您想查看由我使用的缺失值的行组成的数据框部分

````df.loc[df.isnull().any(axis=1)]```

Answer 7

If you are looking for a quicker way to find the total number of missing rows in the dataframe, you can use this:

sum(df.isnull().values.any(axis=1))