Chi-square test - how can I say if attributes are correlated?

I am experimenting a course's teorical contents on this dataset. After data cleaning, I am trying to use chi-square test. I wrote the following code:

chisq.test(chocolate$CompanyMaker, chocolate$Rating, simulate.p.value = TRUE)
chisq.test(chocolate$SpecificBeanOriginOrBarName, chocolate$Rating, simulate.p.value = TRUE)
chisq.test(chocolate$CompanyLocation, chocolate$Rating, simulate.p.value = TRUE)
chisq.test(chocolate$BeanType, chocolate$Rating, simulate.p.value = TRUE)
chisq.test(chocolate$BroadBeanOrigin, chocolate$Rating, simulate.p.value = TRUE)

chisq.test(chocolate$CompanyMaker, chocolate$CocoaPerc, simulate.p.value = TRUE)
chisq.test(chocolate$SpecificBeanOriginOrBarName, chocolate$CocoaPerc, simulate.p.value = TRUE)
chisq.test(chocolate$CompanyLocation, chocolate$CocoaPerc, simulate.p.value = TRUE)
chisq.test(chocolate$BeanType, chocolate$CocoaPerc, simulate.p.value = TRUE)
chisq.test(chocolate$BroadBeanOrigin, chocolate$CocoaPerc, simulate.p.value = TRUE)

And these are my results:

RATING

• CompanyMarker = 0.29

• Specific... = 0.6267

• CompanyLocation = 0.1819

• BeanType = 0.5372

• BroadBeanOrigin = 0.1534

COCOA PERC

• CompanyMarker = 0.0004998
• Specific... = 0.902
• CompanyLocation = 0.04748
• BeanType = 0.8136
• BroadBeanOrigin = 0.8356

Online, I read about significance level, but i didn't quite understand it. In particular, is it at 0.5 or 0.05? Which values are "ok"?

From what I understood, I should say that CompanyMarker, CompanyLocation and BroadBeanOrigin are related to Rating, while CompanyMarker and CompanyLocation are related to cocoaPercent.

Is this right? If not, can you write or link me an example or a guide to do it right? Thanks.