If we want to find missing values positions in a vector, we can use which and is.na functions in R.
a=c(1,2,3,NA,5,6,NA)
positions=which(is.na(a))
How can we find missing values positions in python?
a=[1,2,3,np.nan,5,6,np.nan]
positions=pd.isnull(a)
Here I can get true or false. But I want to find missing values positions.
Thanks in advance.
You can use np.nonzero:
In [307]:
a=[1,2,3,np.nan,5,6,np.nan]
np.nonzero(pd.isnull(a))
Out[307]:
(array([3, 6], dtype=int64),)
You can use enumerate and test each element of your list whith the numpy method : isnan()
indexes = [index for index,element in enumerate(a) if np.isnan(element)]
when using
pd.isnull(a)
you get true as output when the value at that cell is missing, you get false as output if the cell you are referring to has a certain value, and no missing value, here in this url you can find different ways to detect missing values https://medium.com/@kanchanardj/jargon-in-python-used-in-data-science-to-laymans-language-part-two-98787cce0928
If you have a pandas.Dataframe you can use this approach
df.loc[df['Feature'].isnull()]
It will return the lines of the specific column on thedataframe where Nan values are present.
