Matrix from count of rows and columns of different excel file

I have 8 excel files. Each file has some number of rows and columns. I want to read 8 excel files in R studio and then create a matrix with number of rows and columns of each file. So the matrix should look like this

Name_of_Excel_file    CountOfRows    CountOfColumns
Excel1                100000          25
Excel2                50000           100
Excel3                10000           300
Excel4                3000            10
Excel5                80000           50
Excel6                50000           250
Excel7                40000           10
Excel8                20000           10

Could someone please help?

Solution 1:

I'll show you a probably long-winded way of getting your answer. I included commands for if you were actually loading the excel docs below:

# Load libraries:
library(readxl)
library(tidyverse)

# Read excel docs:
df1 <- data.frame(read_xlsx("df1.xlsx"))
df2 <- data.frame(read_xlsx("df2.xlsx"))

Then to simulate what you would do, I just created my own data frames that represent the excel docs to make it easy to reproduce:

# First "excel" doc:
x1 <- c(1,2,3,4)
y1 <- c(2,3,4,1)
df1 <- data.frame(x1,y1)

# Second excel doc:
x2 <- c(1,2,3,8)
y2 <- c(2,3,4,3)
df2 <- data.frame(x2,y2)

# Create variables for rows and cols each:
df1row <- nrow(df1)
df1col <- ncol(df1)
df2row <- nrow(df2)
df2col <- ncol(df2)

# Make data frames for each:
dfdims <- data.frame(df1row,
                     df1col)
df2dims <- data.frame(df2row,
                      df2col)

# Combine them:
all_dims <- data.frame(df1col, df1row, df2col, df2row)
all_dims

# Pivot so rows categorize docs:
pivot_dims <- all_dims %>% 
  pivot_longer(cols = 1:4,
               names_to = "Excel Doc",
               values_to = "Dims")

Should look like this when you print the pivot_dims function: