当我缩放数据时,输入包含NaN、infinity或一个对dtype('float64')太大的值

你也可以查一下 NaN s和 inf

df = pd.DataFrame({'B':[4,5,4,5,5,np.inf],
                   'C':[7,8,9,4,2,3],
                   'D':[np.nan,3,5,7,1,0],
                   'E':[5,3,6,9,2,4]})

print (df)
          B  C    D  E
0  4.000000  7  NaN  5
1  5.000000  8  3.0  3
2  4.000000  9  5.0  6
3  5.000000  4  7.0  9
4  5.000000  2  1.0  2
5       inf  3  0.0  4

nan = df[df.isnull().any(axis=1)]
print (nan)
     B  C   D  E
0  4.0  7 NaN  5

inf = df[df.eq(np.inf).any(axis=1)]
print (inf)
     B  C    D  E
5  inf  3  0.0  4

如果要查找至少有一个的所有索引 行中的s:

print (df.index[np.isnan(df).any(axis=1)])
Int64Index([0], dtype='int64')

和列:

print (df.columns[np.isnan(df).any()])
Index(['D'], dtype='object')