I am working with Python 2.7 and pandas and I have the following dataframe:

```
    col1    col2    col3    date_col
0   123     0       foo     9999-12-31
1   456     1       bar     2017-09-15
2   789     1       psi     9999-12-31  

```

When I try to work with this dataframe I get the following error: 

> 
> pandas.\_libs.tslibs.OutOfBoundsDattime: Out of bounds nanosecond timestamp: 9999-12-31 00:00:00
> 
> 
> 

I am aware that this is because pandas has a limited window of timestamps it can represent.

**My question is:** How can I replace all the values in the column date\_col which are exceeding the bound of the date window with a default value (for example 2000-01-01)? 
Also in my real dataframe I only know the indices of the columns that contain dates, so I *cannot* use the column names.

Any help is appreciated!