I need to manipulate a huge csv a few more than 16 go, I can't even read it, with chunk parameters.

So I tried with 1 go and 300 Mo samples I can, but it's so long for a loop.

I tried this on the 300 MO : I made a new column by doing df["ID"] = ""

```
j = 0
for i in range(len(df["T"]) :
    if (df["N"][i+1] ==  df_base["N"][i]) and  (df["C"][i+1] ==  df["C"][i]) and  (df["S"][i+1] ==  df["S"][i]) and  (df["SL"][i+1] ==  df_base["SL"][i]) :
        df["ID"][i] = j
    else :
        df["ID"][i] = j
        j += 1

```

I did this to get 1 column with identify a unique thing and not 4 to identify it.

But it's so long and I got the warning :

> 
> "A value is trying to be set on a copy of a slice from a DataFrame
> 
> 
> See the caveats in the documentation:
> <https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy>
> df\_["ID"][i] = j"
> 
> 
> 

I don't mind about the error but the algorithm in 2 hours never finished, so i gave up, because i'm in work, i will not stay 2 hours doing nothing...

-So how to know the execution time of a function before/Without executing it ?
-What computer i need to do this...

It's a laptop with 8 go of RAM (7.88 go can be usable, but it's less because of the others applications that are obligatory for the society), speed 2667 MHz, processor intel core i5-8365U CPU @ 1.60 GHz there is also Intel UHD Graphics 620 but I don't know if this is useful information for you.
I use Jupyter Notebook, I tried pycharm but i couldn't because security restriction.

My main question is about what is the more important to speed up those process, the ram, the processor ?? And what can be done ? Thanks

Thanks.