python: Compare compound primary keys values

Asked Apr 15 '20 at 08:30

Active Apr 15 '20 at 08:35

Viewed 18 times

I have a table with composed primary keys(3 columns) I'm new to python, I want to get rows where the compound primary key is 123, 'M', 17.

row_1 = df[
        (df[pr_keys[0]] == (123, 'M', 17))].iloc[0]

I tried also

 (123, 'M', 17) but got always syntax error.

Thank you in advance.

edited Apr 15 '20 at 08:35

pcampana

asked Apr 15 '20 at 08:30

charles

@jezrael it does not anwser my question. thank you – charles Apr 15 '20 at 08:37
Do you need sql solution? – jezrael Apr 15 '20 at 08:39
Problem is in data missing some sample data, what is `pr_keys` and expected output. So I guess need dupe solution, but maybe I am wrong. Can you explian more what need? – jezrael Apr 15 '20 at 08:41
@jezrael of course. Thank you for your response. My pr_keys countains the names of columns that are primary keys . For my case (x1, x2, x3) primary key. – charles Apr 15 '20 at 08:46
It is tuples, strings? list of strings? – jezrael Apr 15 '20 at 08:46
x1 is int, x2 is string and x3 int – charles Apr 15 '20 at 08:50
OK, so why not compare each column separately like dupe? Not understand. – jezrael Apr 15 '20 at 08:51
row_1 = df[ (df[pr_keys[0]] == 123 and df [pr_keys[1]]== 'M' and df[pr_keys[2]]== 17) ].iloc[0] – charles Apr 15 '20 at 09:03
is it what you mean? @jezrael – charles Apr 15 '20 at 09:03
super, you are close. Give me a sec. – jezrael Apr 15 '20 at 09:03
Use `row_1 = df[ (df[pr_keys[0]] == 123) & (df [pr_keys[1]] == 'M') & (df[pr_keys[2]]== 17) ].iloc[0]` it return first row if match all 3 conditions – jezrael Apr 15 '20 at 09:04

0 Answers0