I have multiple data frames to compare. My problem is the product IDs. one is set up like:

* 000-000-000-000
* Vs
* 000-000-000

(gross)

I have looked on here, reddit, YouTube, and even went deep down the rabbit hole trying .join, .append, some other method I've never seen before, or even understand yet. Is there a way(or even better some documentation I can read on to learn this) to pull the Product ID from the Main excel sheet, compare it to the one(s) that should match. Then i will more than like make the in place ID across all sheets. That way I can use those IDs as the index and do a side by side compare of the ID to row data? Each ID has about 113 values to compare. That's 113 columns, but for each row if that make sense

Example: (colorful columns is main sheet that the non colored column will be compared to)
[![enter image description here](https://i.stack.imgur.com/C1Ex2.jpg)](https://i.stack.imgur.com/C1Ex2.jpg)

additional notes:
The highlighted yellow IDs are "unique", and I wont be changing those but instead write them to a list or something and use an if statement to ignore them when found.

Edit:
so I wrote this code which is almost perfect what I need to do with this.
It takes out the "-" which I apply to all my IDs. Just need to make a list of ID that are unique to skip over on taking away the zeros

```
dfSS["Product ID"] = dfSS["Product ID"].str.replace("-", "")

```

Then this will only list the digits up to 9 digits, except the unique IDs

```
dfSS["Product ID"] = dfSS["Product ID"]str[:9]

```

Will add the full code below here once i get it to work 100%

I am now trying to figure out how to say somethin like

```
lst =[1,2,3,4,5]
if dfSS["Product ID"] not in lst:
   dfSS["Product ID"] = dfSS["Product ID"].str.replace("-", "").str[:9]

```

This code does not work but everyday I get closer and closer to being able to compare these similar yet different data frames. the lst is just an example of a 000-000-000 Product IDs in a list that I do not want to filter at all. but keep in the data frame