I am a total beginner but I want to post that a lot.

auto autoCorrelation(R)(R range)
        if (isRandomAccessRange!R)
{

	import std.numeric : fft, inverseFft;
	import std.range : chain, repeat, zip, dropBack;
	import std.algorithm : map;
	import std.complex;
	
	auto residual = residualPowerOf2(range.length);
	auto fftResult = range.chain(repeat(0, residual)).fft();
	auto autoCorrResult = fftResult.zip(fftResult.map!(a => a.conj())).
							map!( a=> a[0] * a[1] ).
							inverseFft().
							dropBack(residual).
							map!( a => a.re );
				
	return autoCorrResult;
}	

I implemented auto correlation in C++ before which is I believe 2~3 time bigger(also I needed to compile fftw, lapack etc.. ) :
https://forum.kde.org/viewtopic.php?f=74&t=118619 .

That was the moment I feel in love with D.

Another solution using dlangs builtin csv support for reading.

import std.csv;
import std.file;
import std.algorithm : map;
import std.range;

string csvWrite(Header, Rows)(Header header, Rows rows)
{
    return header.join(",") ~ "\n" ~ rows.map!(r => header.map!(h =>
r[h]).join(",")).join("\n");
}

int main(string[] args)
{
    auto inputFile = args[1];
    auto columnName = args[2];
    auto replacement = args[3];
    auto outputFile = args[4];

    auto records = readText(inputFile).csvReader!(string[string])(null);
    write(outputFile, csvWrite(records.header, records.map!((r) {
                r[columnName] = replacement;
                return r;
            })));
    return 0;
}

Unfortunately this is still far from the powershell solution :/

cK