Can't find the missing values in dataframe

General
,
1

I have a dataset containing 188k rows, having 4 columns. I was cleaning the dataset and i used skim for knowing how many missing values are there :

skim(Main_data)

It showed it has more than 50k missing values in each columns. So i treid to eliminate the rows containg empty cell, But I didn't geting the rows conating empty cell.
I tried many methods like this :

num_empty_val <- sum(Main_data1  == " ")
num_empty_val <- sum(is.na(Main_data1 ))
num_empty_val1 <- sum(complete.cases(Main_data1 ))

After trying all this it just giving m output that there is no empty cell, why?
I had just started to code in R, So please help me with this by suggesting some other ways i can do this.

2

If you want to eliminate all rows that have one or more columns with NA

reduced_data <- Main_data[complete.cases,]
3

by doing this it is showing a error

Error in xj[i] : invalid subscript type 'closure'
4

Without a reprex, I can't understand what's happening clearly. See the FAQ: How to do a minimal reproducible example reprex for beginners.

This error is something that can happen when using a function out of place. For example

xj <- LETTERS
xj[5]
#> [1] "E"

i <- function() pi
# this is the call of a function
i()
#> [1] 3.141593
# here is a "closure"
i
#> function() pi
xj[i]
#> Error in xj[i]: invalid subscript type 'closure'

# within the `for` function, i
# is no longer a closure, because
# it is being invoked in the .Local
# environment
for(i in 1:3) print(xj[i])
#> [1] "A"
#> [1] "B"
#> [1] "C"

Created on 2023-07-19 with reprex v2.0.2

Here's what I mean by using complete.cases

# the data frame has 32 rows
dim(mtcars)
#> [1] 32 11
# introduce a missing value in the first row
mtcars[1,1] <- NA
# subset by the rows with no missing values
# dimension now shows one fewer row
mtcars[complete.cases(mtcars),] |> dim()
#> [1] 31 11
5

It worked, Thanks for your time sir