Lets say I have following pandas DataFrame:
import pandas as pd
df = pd.DataFrame({“A”:[1,pd.np.nan,2], “B”:[5,6,0]})
Which would look like:
df
A B
0 1.0 5
1 NaN 6
2 2.0 0
First option
I know one way to check if a particular value is NaN, which is as follows:
df.isnull().ix[1,0]
True
Second option (not working)
I thought below option, using ix, would work as well, but it’s not:
df.ix[1,0]==pd.np.nan
False
I also tried iloc with same results:
df.iloc[1,0]==pd.np.nan
False
However if I check for those values using ix or iloc I get:
df.ix[1,0]
nan
df.iloc[1,0]
nan
So, why is the second option not working? Is it possible to check for NaN values using ix or iloc?
解决方案
Try this:
In [107]: pd.isnull(df.iloc[1,0])
Out[107]: True
UPDATE: in a newer Pandas versions use pd.isna():
In [7]: pd.isna(df.iloc[1,0])
Out[7]: True
Original: https://blog.csdn.net/weixin_42523529/article/details/112963299
Author: 胖芋圆的耳饰
Title: pandas 判断是否等于nan_使用ix或iloc检查pandas DataFrame中的特定值（单元格中）是否为NaN不能正常工作…
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