Converting data to missing in pandas
numpy, pandas, python
Solution
Just do `from numpy import nan`. (You will have to convert your DataTable to float type, because you can't use `NaN` in integer arrays.)
Problem
I have a `DataFrame` with a mix of 0's and other numbers. I would like to convert the 0's to missing. For example, I am looking for the command that would convert ``` In [618]: a=DataFrame(data=[[1,2],[0,1],[1,2],[0,0]]) In [619]: a Out[619]: 0 1 0 1 2 1 0 1 2 1 2 3 0 0 ``` to ``` In [619]: a Out[619]: 0 1 0 1 2 1 NaN 1 2 1 2 3 NaN NaN ``` I tried pandas.replace(0, NaN), but I get an error that NaN is not defined. And I don't see anywhere to import NaN from.