How to select multiple rows based on header values? - python-3.x

Question

I wish to iterate over rows of a Pandas dataframe while only checking for similarity within a few columns among the rows. Then, I want to check for a similarity condition, followed by a date comparison (which one is earlier/later) and apply corresponding changes to one element of the row selected.
For selecting particular rows, I kind of want something like this:
p=z["product_name", "Category 1", "Category 2", "Features"].iloc[i-1:i]
I know it's not correct, but it's just to give an idea. Select a row with only a few particular headers out of many.
i=1
while (i<=len(z)):
j=i+1
p=z["product_name", "Category 1", "Category 2", "Features"].iloc[i-1:i]
p=p.to_string(index=False)
while(j<=len(z)):
q=z["product_name", "Category 1", "Category 2", "Features"].iloc[j-1:j]
q=q.to_string(index=False)
if (p==q):
if(z["Update Date"].iloc[i-1:i]>z["Update Date"].iloc[j-1:j]):
z.drop(j, axis=0)
j=j+1
i=i+1
I know that most of this code is actually wrong but this is the approach I'm trying. Please suggest a better approach/function that solves this problem.

Answer 1

I don't know your question exactly, But there are Basic Issue in your code when you start i-1:i, it gives only one value why you use this line instead of directly one variable
p=z["product_name", "Category 1", "Category 2", "Features"].iloc[i-1:i]
try This:
p=z[["product_name", "Category 1", "Category 2", "Features"]].iloc[i-1:i]