I have merged two tables together and I want to write them to a .txt file. I have managed to do this, however when I open the .txt file in excel the symbols   have been added to some values. How do I stop this from happening? I have used the following code:
ICU_PPS <- merge(ICU, PPS, by=c("Study","Lane","Isolate_ID","Sample_Number","MALDI_ID", "WGS","Source"),all=TRUE)
write.table(ICU_PPS,"ICUPPS2.txt", sep="\t", row.names = FALSE)
An example of some values in a column that I get:
100_1#175
100_1#176
100_1#177
100_1#179
100_1#18 
100_1#19 
100_1#20 
What I want to achieve:
100_1#175
100_1#176
100_1#177
100_1#179
100_1#18
100_1#19
100_1#20
Related
I have an Excel file test.xlsx on my desktop and have a dataframe in R. How can I overwrite numbers in Excel file sheet "Capitals"? Say table in excel starts at B6 and has the same size as table in R.
I tried to run following command, however, it creates a new excel file, however I need to make changes in the existing one.
write.xlsx(df, file = "//Desktop//test.xlsx",
sheetName = "Capitals", append = TRUE)
I'm working with a huge file to do some data analysis in R. This file is a .csv. I can import it just fine. However, after transposing all the rows and columns using data.frame(t(data)), I export it and cannot re-import this data.
This is the code I am using:
write.csv(transposed_data, file = "transposed_data.csv", row.names = FALSE, quote = FALSE)
When I transpose the rows and columns, does something happen to the data that is causing these issues? When using read.csv, the transposed data simply will not open.
I am writing a dataframe using a csv file. I am making a data frame. However, when I go to run it, it's not recognizing the objects in the file. It will recognize some of them, but not all.
smallsample <- data.frame(read.csv("SmallSample.csv",header = TRUE),smallsample$age,smallsample$income,smallsample$gender,smallsample$marital,smallsample$numkids,smallsample$risk)
smallsample
It wont recognize marital or numkids, despite the fact that those are the column names in the table in the .csv file.
When you use read.csv the output is already in a dataframe.
You can simple use smallsample <- read.csv("SmallSample.csv")
Result using a dummy csv file
<table><tbody><tr><th> </th><th>age</th><th>income</th><th>gender</th><th>marital</th><th>numkids</th><th>risk</th></tr><tr><td>1</td><td>32</td><td>34932</td><td>Female</td><td>Single</td><td>1</td><td>0.9611315</td></tr><tr><td>2</td><td>22</td><td>50535</td><td>Male</td><td>Single</td><td>0</td><td>0.7257541</td></tr><tr><td>3</td><td>40</td><td>42358</td><td>Male</td><td>Single</td><td>1</td><td>0.6879534</td></tr><tr><td>4</td><td>40</td><td>54648</td><td>Male</td><td>Single</td><td>3</td><td>0.568068</td></tr></tbody></table>
The program I am exporting my data from (PowerBI) saves the data as a .csv file, but the first line of the file is sep=, and then the second line of the file has the header (column names).
Sample fake .csv file:
sep=,
Initiative,Actual to Estimate (revised),Hours Logged,Revised Estimate,InitiativeType,Client
FakeInitiative1 ,35 %,320.08,911,Platform,FakeClient1
FakeInitiative2,40 %,161.50,400,Platform,FakeClient2
I'm using this command to read the file:
initData <- read.csv("initData.csv",
row.names=NULL,
header=T,
stringsAsFactors = F)
but I keep getting an error that there are the wrong number of columns (because it thinks the first line tells it the number of columns).
If I do header=F instead then it loads, but then when I do names(initData) <- initData[2,] then the names have spaces and illegal characters and it breaks the rest of my program. Obnoxious.
Does anyone know how to tell R to ignore that first line? I can go into the .csv file in a text editor and just delete the first line manually before I load it each time (if I do that, everything works fine) but I have to export a bunch of files and this is a bit stupid and tedious.
Any help would be much appreciated.
There are many ways to do that. Here's one:
all_content = readLines("initData.csv")
skip_first_line = all_content[-1]
initData <- read.csv(textConnection(skip_first_line),
row.names=NULL,
header=T,
stringsAsFactors = F)
Your file could be in a UTF-16 encoding. See hrbrmstr's answer in how to read a UTF-16 file:
I have the following code to read a file and save it as a csv file, I remove the first 7 lines in the text file and then the 3rd column as well, since I just require the first two columns.
current_file <- paste("Experiment 1 ",i,".cor",sep="")
curfile <- list.files(pattern = current_file)
curfile_data <- read.table(curfile, header=F,skip=7,sep=",")
curfile_data <- curfile_data[-grep('V3',colnames(curfile_data))]
write.csv(curfile_data,curfile)
new_file <- paste("Dev_C",i,".csv",sep="")
new_file
file.copy(curfile, new_file)
The curfile thus hold two column variables V1 and V2 along with the observation number column in the beginning.
Now when I use file.copy to copy the contents of the curfile into a .csv file and then open the new .csv file in Excel, all the data seems to be concatenated and appear in a single column, is there a way to show each of the individual columns separately? Thanks in advance for your suggestions.
The data in the .txt file looks like this,
"","V1","V2","V3"
"1",-0.02868862,5.442283e-11,76.3
"2",-0.03359281,7.669754e-12,76.35
"3",-0.03801883,-1.497323e-10,76.4
"4",-0.04320051,-6.557672e-11,76.45
"5",-0.04801207,-2.557059e-10,76.5
"6",-0.05325544,-9.986231e-11,76.55
You need to use Text to columns feature in Excel, selecting comma as a delimiter. The position of this point in menu depends on version of Excel you are using.