Is there an R function for including column into row data - r

Question

I would like to perform chi-square test in R by transform data frame from csv file using R from the following structure
Observed Values East West North South
Males 50 142 131 70
Females 435 1523 1356 750
to
following example
Row Observed value Region
1 1 East
2 1 East
3 1 East
...
435 0 East
Given that 1 = male. 0 = female
I been trying to use stack and data frame function to create the new table using R. I need the following table to perform chi-square test in R. The code I am trying is as below:
Stacked_data <- stack(data)
library(dummies)
df1 <- data.frame(id = 1:0, Observed.Values )
df2 <- cbind(Stacked_data, dummy(df1$id, sep = "_"))
Expected result will contain 2 column (observed value and region). Observed value will contain the categorical value for male = 1, and female = 0.Region will contain the region for respective observed value.
So that when i perform
table(Region,Observed Values)
It will produce
Observed Values
Region 1 0
East 50 435
West 142 1523
North 131 1356
South 70 750

Answer 1

Update: based on your expected output, you don't need much at all. Using obs from below, all you need to get your output (on which you can run chisq.test) is:
obs2 <- t(obs[,-1])
dimnames(obs2) <- list(Region = rownames(obs2), Observed = c('0', '1'))
obs2
# Observed
# Region 0 1
# East 50 435
# West 142 1523
# North 131 1356
# South 70 750
But, then again, if all you need is to run a chisq.test on them, it doesn't matter which orientation you use:
### original frame you provided
chisq.test(obs[,-1])
# Pearson's Chi-squared test
# data: as.matrix(obs[, -1])
# X-squared = 1.5959, df = 3, p-value = 0.6603
### transposed/re-labeled frame
chisq.test(obs2)
# Pearson's Chi-squared test
# data: obs2
# X-squared = 1.5959, df = 3, p-value = 0.6603
No difference. Perhaps all you needed was the [,-1] part?
Here's an attempt, though I don't know that it's exactly what you expect. (Input data is at the bottom of this answer.)
library(dplyr)
library(tidyr)
out1 <- obs %>%
gather(Region, v, -Observed) %>%
rowwise() %>%
do( tibble(Region = .$Region, Observed = rep(1L * (.$Observed == "Males"), .$v)) ) %>%
ungroup() %>%
mutate(Row = row_number())
out1
# # A tibble: 4,457 x 3
# Region Observed Row
# <chr> <int> <int>
# 1 East 1 1
# 2 East 1 2
# 3 East 1 3
# 4 East 1 4
# 5 East 1 5
# 6 East 1 6
# 7 East 1 7
# 8 East 1 8
# 9 East 1 9
# 10 East 1 10
# # ... with 4,447 more rows
We can verify that it is reversible with
xtabs(~ Observed + Region, data = out1)
# Region
# Observed East North South West
# 0 435 1356 750 1523
# 1 50 131 70 142
(even if the columns and rows are in a different order as the input, the numbers match).
Data:
obs <- read.table(header=TRUE, stringsAsFactors=FALSE, text="
Observed East West North South
Males 50 142 131 70
Females 435 1523 1356 750 ")