我有一个pandas数据框，sample其中有一个调用列PR，其中应用了lambda函数，如下所示：
sample['PR'] = sample['PR'].apply(lambda x: NaN if x < 90)
然后，我得到以下语法错误消息：
sample['PR'] = sample['PR'].apply(lambda x: NaN if x < 90)
^
SyntaxError: invalid syntax
我究竟做错了什么？
您需要mask：
sample['PR'] = sample['PR'].mask(sample['PR'] < 90, np.nan)
用另一种解决方案loc和boolean indexing：
sample.loc[sample['PR'] < 90, 'PR'] = np.nan
样本：
import pandas as pd
import numpy as np
sample = pd.DataFrame({'PR':[10,100,40] })
print (sample)
PR
0 10
1 100
2 40
sample['PR'] = sample['PR'].mask(sample['PR'] < 90, np.nan)
print (sample)
PR
0 NaN
1 100.0
2 NaN
sample.loc[sample['PR'] < 90, 'PR'] = np.nan
print (sample)
PR
0 NaN
1 100.0
2 NaN
编辑：
解决方案apply：
sample['PR'] = sample['PR'].apply(lambda x: np.nan if x < 90 else x)
时间 len(df)=300k：
sample = pd.concat([sample]*100000).reset_index(drop=True)
In [853]: %timeit sample['PR'].apply(lambda x: np.nan if x < 90 else x)
10 loops, best of 3: 102 ms per loop
In [854]: %timeit sample['PR'].mask(sample['PR'] < 90, np.nan)
The slowest run took 4.28 times longer than the fastest. This could mean that an intermediate result is being cached.
100 loops, best of 3: 3.71 ms per loop
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