How to create a correlation matrix without using the data source to call each variable?

Publishing Your Results
1

This is what I've been doing it it creates really long column and row labels. I'm been trying to the cor(x, method =c(.....)) but I can't seem to make it work. I've put quotes around all my variables, I've put in data.frame(....) with everything below in it. Nothing's working.

As you can clearly see, Final_Project_Data is the csv document title but I don't want it in matrix labels. Is there a way to create a correlation matrix without "Final Project Data "Variable Label" or it's just my variable label?

What I've put below is as simple and as clean as I can make my script too.

cor(data.frame(Final_Project_Data$Giv_Money, Final_Project_Data$Econ_Fr, Final_Project_Data$GDP_Cap, Final_Project_Data$NGOs, Final_Project_Data$Lab_For, Final_Project_Data$Fem_Lab_For, Final_Project_Data$Fem_Pop, Final_Project_Data$Fin_HH_Con, Final_Project_Data$Age_0_14, Final_Project_Data$Fin_Gov_Con, Final_Project_Data$Gen_Dev, Final_Project_Data$Gen_Ineq, Final_Project_Data$Age_15_24,Final_Project_Data$Age_55_64, Final_Project_Data$Age_55_64, Final_Project_Data$Age_65_P, Final_Project_Data$Imp, Final_Project_Data$Exp, Final_Project_Data$Int_Acc, Final_Project_Data$Mrkt_Pro, Final_Project_Data$Inc_Tax, Final_Project_Data$Tax_Burd,Final_Project_Data$Age_Dep))

Thanks

2

Did you mean CSV?

If so, you can call the cor function on a data.frame directly. See documentation.

---
title: "Example"
output: html_document
---

```{r, include = FALSE}
# generating a csv, you don't need this
x1 = runif(10)
x2 = rnorm(10)
x3 = rexp(10)
d = data.frame(x1, x2, x3)
write.csv(d, "example.csv")
```

```{r}
dataset = read.csv("example.csv") # creates an index column automatically
cor(dataset[-1])
```

This generates

Example
Example1440×860 43.7 KB
.

1 Like
3

My typo has been corrected

4

This situation has been resolved.

cor(Final_Project_Data_2[, c("Giv_Money", "Econ_Fr", "GDP_Cap", "NGOs", "Lab_For", "Fem_Lab_For", "Fem_Pop", "Fin_HH_Con", "Age_0_14", "Fin_Gov_Con", "Gen_Dev", "Gen_Ineq", "Age_15_24","Age_55_64", "Age_55_64", "Age_65_P", "Imp", "Exp", "Int_Acc", "Mrkt_Pro", "Inc_Tax", "Tax_Burd","Age_Dep")])

5

Maybe you’ve already sorted this out, but it’s good to understand the difference between:

  • dataframe$variable1, dataframe$variable2
    supplies separate vectors that happen to have been pulled from dataframe, but may as well have come from anywhere

and

  • dataframe[, c("variable1", "variable2")]
    supplies a data frame, filtered to include only the variable1 and variable2 columns
3 Likes
6

Thanks--that's really helpful for the future. I honestly have no idea half of what I'm doing in R.

7

Lots of us start out just mashing the buttons and hoping for the best! (I certainly did :upside_down_face:) A good reference for learning the basics can really help. This thread has a ton of good resources:

(Despite the original topic, many of the suggestions are suitable for people with all sorts of previous experience levels)

1 Like