为了检查值是否为 NaN,可以使用isnull()或notnull()函数。 In [1]: import numpy as np In [2]: import pandas as pd In [3]: ser = pd.Series([1, 2, np.nan, 4]) In [4]: pd.isnull(ser) Out[4]: 0 False 1 False 2 True 3 False dtype: bool ...
In any way, checking for empty values after importing is always a good step, using - in your third example - df_a.isnull() or df_a.isnull().sum. Member phofl commented Jun 1, 2021 This is a duplicate, please search the issue tracker, 👎 1 Author buhtz commented Jun 2, 202...
You can load this in Python as a Pandas DataFrame or something (see here for an example of using pd.read_csv() on this), and then you can create a new column, raw_ratio, as follows: import math # You may need to filter out samples with a NaN or null log-ratio first sample_...
By now, you can set a timeout by using the set_trace_timeout method, but bear in mind that:If a timeout is specified, it is not possible to guarantee that the alignments found are optimal (please check our research article.) If a timeout is specified, exceptions due to null values ...