python - 根据严格的不平等和缺失数据过滤 Pandas 数据框

Question

我是 Pandas 新手。如何根据严格不等式或缺失数据进行过滤？在下面的代码中，我希望 one 高于阈值或缺失。我该如何实现这一目标？谢谢。

import pandas as pd
import numpy as np

d = {
    'one' : [1.1, np.nan, 3.1],
    'two' : [3.2, 2.2, 1.2],
    }

df = pd.DataFrame(d)

for one in np.arange(0, 6, 1.):
    df1 = df[(df['one']>one) | (df['one']==np.nan)]
    if len(df1) == 0:
        continue
    for two in np.arange(0, 6, 1.):
        df2 = df1[(df1['two']>two)]
        if len(df2) == 0:
            continue
        print(one, two, len(df2))

Answer 1

使用isnull()函数来识别缺失值。

df.loc[(df['one'] > 2) | (df['one'].isnull())]

#    one  two
# 1  NaN  2.2
# 2  3.1  1.2