I know this question may be repeated but i tried all the solutions in :
How to convert entire dataframe to numeric while preserving decimals?
https://statisticsglobe.com/convert-data-frame-column-to-numeric-in-r
But didn't work
i imported excel data : from my computer manually :
File > import data > excel and i set the type of data as numeric
i checked my data using
View(Old_data)
and it s true of type numeric
head(Old_data)
QC_G.F9_01_4768 QC_G.F9_01_4765
M95T834 70027.02 69578.19
M97T834 95774.14 81479.30
M105T541 75686.39 68455.65
M109T834 72093.07 70942.65
M111T834_2 77502.98 77527.54
M114T834 68132.06 70296.73
M121T834 52233.05 56074.64
M125T834 44559.99 35831.79
M128T834 59257.48 59574.73
M135T834 105136.55 105274.98
but after data i Converted rows into columns and columns into rows using R :
New_data <- as.data.frame(t(Old_data))
When i checked my new data using :
View(New_data)
I found that my columns are of type character and not numeric
i tried to convert New_data to numeric
New_data_B -> as.numeric(New_data)
i checked my data using
dim(New_data_B)
17 1091
Here's example of my data
New_data_B
#> Name MT95T843 MT95T756
#> 1 QC_G.F9_01_4768 70027.02132 95774.13597
#> 2 QC_G.F9_01_4765 69578.18634 81479.29575
#> 3 QC_G.F9_01_4762 69578.18634 87021.95427
#> 4 QC_G.F9_01_4759 68231.14338 95558.76738
#> 5 QC_G.F9_01_4756 64874.12936 96780.77245
#> 6 QC_G.F9_01_4753 63866.65780 91854.35304
#> 7 CtrF01R5_G.D1_01_4757 66954.38799 128861.36163
#> 8 CtrF01R4_G.D5_01_4763 97352.55229 101353.25927
#> 9 CtrF01R3_G.C8_01_4754 61311.78576 7603.60896
#> 10 CtrF01R2_G.D3_01_4760 85768.36117 109461.75445
#> 11 CtrF01R1_G.C9_01_4755 85302.81947 104253.84537
#> 12 BtiF01R5_G.D7_01_4766 61252.42545 115683.73755
#> 13 BtiF01R4_G.D6_01_4764 81873.96379 112164.14229
#> 14 BtiF01R3_G.D2_01_4758 84981.21914 0.00000
#> 15 BtiF01R2_G.D4_01_4761 36629.02462 124806.49101
#> 16 BtiF01R1_G.D8_01_4767 0.00000 109927.26425
#> 17 rt 13.90181 13.90586
also i converted my data to csv file and i imported it :
Old_data <- as.data.frame(read.csv("data.csv" , sep="," , header=TRUE,stringsAsFactors=FALSE))
And also using :
#install.packages("readxl")
library("readxl")
Old_data <- read_excel("data.xlsx")
I tried the solution suggested by Mr sveer
New_data <- cbind(Name=Old_data[1,],as.data.frame(t(Old_data[-1,])))
it gives this result
head(New_data)
When i tried
View(New_data)
Name.QC_G.F9_01_4768 Name.QC_G.F9_01_4765
70027.02 69578.19
95774.14 81479.30
75686.39 68455.65
72093.07 70942.65
77502.98 77527.54
68132.06 70296.73
52233.05 56074.64
4559.99 35831.79
59257.48 59574.73
105136.55 105274.98
it delets the rownames !
Im just confused of this problem, i think the problem is because i converted rows into columns and columns into rows
Please tell me for any clarification and also if i can send the data to someone so he can try Thank you very much