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When and how to use as.name() vs.get() in data.table (ex. in looping over columns)?

By : Abhi Kashyap
Date : October 17 2020, 06:10 AM
fixed the issue. Will look into that further To answer the overall question - "When and how to use as.name() vs.get() in data.table?".
In my experience, it is rarely needed when you can use existing R programming methods:
code :
  newcol := Reduce(`+`, Map(`*`, c(100,75,50,25,0), .SD)) / Reduce(`+`, .SD),

#1:      21      37      16      14      11   200784       61 60.85859
#2:      20      37      16      15      11   177165       60 60.10101

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Looping through table columns

By : logslogs
Date : March 29 2020, 07:55 AM
it should still fix some issue I have a query that is supposed to loop through all the tables in the database. It does that fine, I test it by outputting the table names. , Something like :
code :
$host = "";
$username = "username";
$password = "password";
$database = "database";

$link = new mysqli($host, $username, $password, $database);

    die("Connection died: ".$link->connect_error);

$showtables = $link->query("DESCRIBE name_of_table;");

foreach($showtables->fetch_all() as $table)
    printf($table[0] . "\n");
select * from information_schema.columns
where table_schema = 'your_db'
order by table_name,ordinal_position

R data.table looping over columns to conditionally replace row values

By : Frug
Date : March 29 2020, 07:55 AM
I hope this helps . Looking for what should be an incredibly simple solution. I'd like to conditionally replace a value in a row if it meets a given condition (less than zero), and I would like to do this for hundreds (twenty in the example) of columns each with 150 million rows. I'm on hour seven of trying every solution that I found on the stack, so please don't mark this as duplicate. :-) , Option 1 using :=:
code :
dt[, (paste0("y", 50:70)) := lapply(.SD, function(x) {x[x<0] <- 0; x}), .SDcols=paste0("y", 50:70)]
for (j in paste0("y", 50:70)) {
    set(dt, dt[,which(get(j) < 0)], j, 0)
dt <- data.table(id=c(1:1000), x=rnorm(1:1000,60,20))
for(i in 50:70) {
    dt[, paste0("y", i) := i-x]

Cleaning data dynamically after looping through table and columns

By : user2300511
Date : March 29 2020, 07:55 AM
fixed the issue. Will look into that further Before I insert the results into the staging table, it needs to be cleaned of all white spaces and carriage returns. I can sadly not provide sample data because it is private company data. All tables have different columns of type NVARCHAR* , You should probably replace
code :
INSERT INTO [LIST].[STG].[' + @NAME + '] (' + @CNAME + ', [Inserted_Date])
INSERT INTO [LIST].[STG].[' + @NAME + '] (' + @CNAME + ', [Inserted_Date])

Looping over columns in data.table R

By : user3595854
Date : March 29 2020, 07:55 AM
it should still fix some issue I am trying to loop over columns in data.table package in R. I have been having trouble trying to get the for loop to accurately input the column when I subset the datatable. , You can use colSums, which is much simpler and faster than looping.
code :
dt <- data.table(va=c(1,0,1), vb=c(1,0,0), vc=c(1,1,1))
col.names <- c("va", "vc")
dt[, colSums(.SD==1), .SDcols = col.names]
# va vc 
# 2  3 
for (col in col.names) {
  dt[get(col) == 1, print(.N)]

How do I move the same columns data within the same table without looping

By : user3812123
Date : March 29 2020, 07:55 AM
I hope this helps you . I would suggest creating fake data instead of obfuscating real data. With fake data there's no possibility that you might expose sensitive information. Red Gate has a nifty tool to create test data, SQL Data Generator, that makes it trivial to generate realistic, fake data using various types of rules given your table schema.
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