# pandas bins dummy

>>> dout age ageD_[5, 30] ageD_(30, 70] (-inf, 5] (-inf, 30] (-inf, 70] (5, +inf) (30, +inf) (70, +inf) 0 5 1 0 1 1 1 0 0 0 1 23 1 0 0 1 1 1 0 0 2 43 0 1 0 0 1 1 1 0 3 70 0 1 0 0 1 1 1 0 4 30 1 0 0 1 1 1 0 0

**Here is what the above code is Doing:**

1. We create a new column for each bin.

2. We then populate the new columns with a 1 if the value in the original column is in the bin, and 0 otherwise.

3. We then drop the original column.