Python pandas: selecting rows whose column value is null / None / nan
pandas, python
Solution
you can use .isna() method:
In [48]: df[df[2].isna()]
Out[48]:
0 1 2
1 3 4 NaN
Problem
How do I select those rows of a DataFrame whose value in a column is none? I've coded these to `np.nan` and can't match against this type. ``` In [1]: import numpy as np In [2]: import pandas as pd In [3]: df = pd.DataFrame([[1, 2, 3], [3, 4, None]]) In [4]: df Out[4]: 0 1 2 0 1 2 3.0 1 3 4 NaN In [5]: df = df.fillna(np.nan) In [6]: df Out[6]: 0 1 2 0 1 2 3.0 1 3 4 NaN In [7]: df.iloc[1][2] Out[7]: nan In [8]: df.iloc[1][2] == np.nan Out[8]: False In [9]: df[df[2] == None] Out[9]: Empty DataFrame Columns: [0, 1, 2] Index: [] ```