Jase Villam - 7 months ago 49

Python Question

I have a df like this:

`a b c`

1 NaT w

2 2014-02-01 g

3 NaT x

df=df[df.b=='2014-02-01']

will give me

`a b c`

2 2014-02-01 g

I want a database of all rows with NaT in column b?

`df=df[df.b==None] #Doesn't work`

I want this:

`a b c`

1 NaT w

3 NaT x

Answer

`isnull`

and `notnull`

work with `NaT`

so you can handle them much the same way you handle `NaNs`

:

```
>>> df
a b c
0 1 NaT w
1 2 2014-02-01 g
2 3 NaT x
>>> df.dtypes
a int64
b datetime64[ns]
c object
```

just use `isnull`

to select:

```
df[df.b.isnull()]
a b c
0 1 NaT w
2 3 NaT x
```

Source (Stackoverflow)