Python Pandas Divide multiple columns by a value for the rows that match a condition in another column

I have a data like below in a pandas dataframe but there are over 500 columns and for columns 2-500+ I need to divide only the rows where in column 0 the value is ‘dog’ by 100.

0       1       2       3
cat    2019   19.80   96.28
cat    2022   19.50   66.80
dog    2022   21.10   57.70
dog    2021   21.50   42.85

The expected output is below:

0       1       2       3
cat    2019   19.80    96.28
cat    2022   19.50    66.80
dog    2022   0.211    0.577
dog    2021   0.215    0.4285

I have the following code which works to divide it by 100 for those specific rows and columns but it removes columns 0 and 1 and any rows that aren’t ‘dog’.

df=df[df[0].str.contains("dog")].loc[:,2:len(r2.columns)-1].div(100)

How do I keep the full dataframe and apply this division on those specific rows and columns?

>Solution :

Hate it when people post the correct answer in the comments, Imma just post the same thing as I thought as a real answer. Small credit for @mozway cuz’ otherwise I would’ve needed to rummage in my brain how to do so.

df.loc[df[0].str.contains("dog"), 2:] /= 100

Have a good day.