The issue is not necessarily be memory‐ it could also be due to a 32-bit installation of R, which only supports up to 3GB address space. If your OS supports it, install the 64-bit version of R.

I called `activity`

*toy data* only because it seemed designed solely to illuminate the issue of manipulating data frames. Because it has four categorical variables and one numeric variable, it's not obvious how a logistic model is being constructed, since each of the categorical variables have unique values. The Big Book of R has many examples and explanations, but finding the appropriate ones requires careful framing of the question.

The goal is to model a dependent variable Y as a function of X_1 \dots X_n where Y is continuous and \forall X_i is categorical.

For example, with `Supply_hrs`

in the role of Y and the remaining variables X_1 \dots X_4, it becomes clear immediately that a logistic model is inappropriate:

```
> fit <- glm(Supply_hrs ~ ., data = activity, family = "binomial")
Error in eval(family$initialize) : y values must be 0 <= y <= 1`
```

By contrast, an OLS model will run, although the data characteristics limit its usefulness (all values are unique)

```
suppressPackageStartupMessages({
library(dplyr)
})
activity <- data.frame(
Customer_Name = c("Jane", "Bill", "Fred", "Tina", "Joe"),
Account_No = c("332", "432", "556", "884", "119"),
supply_line = c("York", "shark", "Aba", "kwara", "Bethel"),
Cons = c("0-2300", "2300-4003", "4003-1121", "1121-3022", "3022-1713"),
Supply_hrs = c(9, 5, 8, 10, 1)
)
fit <- lm(Supply_hrs ~ ., data = activity)
summary(fit)
#>
#> Call:
#> lm(formula = Supply_hrs ~ ., data = activity)
#>
#> Residuals:
#> ALL 5 residuals are 0: no residual degrees of freedom!
#>
#> Coefficients: (12 not defined because of singularities)
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 5 NA NA NA
#> Customer_NameFred 3 NA NA NA
#> Customer_NameJane 4 NA NA NA
#> Customer_NameJoe -4 NA NA NA
#> Customer_NameTina 5 NA NA NA
#> Account_No332 NA NA NA NA
#> Account_No432 NA NA NA NA
#> Account_No556 NA NA NA NA
#> Account_No884 NA NA NA NA
#> supply_lineBethel NA NA NA NA
#> supply_linekwara NA NA NA NA
#> supply_lineshark NA NA NA NA
#> supply_lineYork NA NA NA NA
#> Cons1121-3022 NA NA NA NA
#> Cons2300-4003 NA NA NA NA
#> Cons3022-1713 NA NA NA NA
#> Cons4003-1121 NA NA NA NA
#>
#> Residual standard error: NaN on 0 degrees of freedom
#> Multiple R-squared: 1, Adjusted R-squared: NaN
#> F-statistic: NaN on 4 and 0 DF, p-value: NA
```

^{Created on 2020-11-14 by the reprex package (v0.3.0.9001)}