Which of the following tools would be best to use to calculate the interquartile range, median, mean, and standard deviation of a column in a table that has 5.000.000 rows?
This is a job for the R-pocalypse! Seriously, Excel would probably just throw in the towel and go on vacation if you asked it to handle 5 million rows. And Snowflake, bless its heart, is more of a data storage solution than a statistical workhorse. R, on the other hand, is like a data analysis superhero. Bring it on, 5 million rows!
R is the way to go here, no doubt. I mean, who wants to wait forever for Excel to crunch through 5 million rows? And Snowflake is great for warehousing, but not so much for hardcore number-crunching. Time to break out the R magic!
I'm going with option B. R is specifically designed for this kind of heavy-duty data analysis. Excel might work, but it would be painfully slow. And Snowflake and SQL are more for data storage and querying, not advanced statistical computations.
B for sure. R is a power tool for statistical analysis, and it can handle huge datasets like no other. Excel would probably start smoking if you tried to run those calculations on 5 million rows!
Hmm, I'd say R would be the way to go for crunching those big numbers. Excel might choke on a dataset that size, and Snowflake is more for warehousing than analysis, right? SQL could work, but R has those built-in stats functions that would make this a breeze.
Hoa
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