copy and paste this google map to your website or blog!
Press copy button and paste into your blog or website.
(Please switch to 'HTML' mode when posting into your blog. Examples: WordPress Example, Blogger Example)
Input Form:Deal with this potential dealer,buyer,seller,supplier,manufacturer,exporter,importer
(Any information to deal,buy, sell, quote for products or service)
Why use as. factor () instead of just factor () - Stack Overflow ‘factor(x, exclude = NULL)’ applied to a factor without ‘NA’s is a no-operation unless there are unused levels: in that case, a factor with the reduced level set is returned ‘as factor’ coerces its argument to a factor It is an abbreviated (sometimes faster) form of ‘factor’ Performance: as factor > factor when input is a factor The word "no-operation" is a bit ambiguous
r - How to convert a factor to integer\numeric without loss of . . . See the Warning section of ?factor: In particular, as numeric applied to a factor is meaningless, and may happen by implicit coercion To transform a factor f to approximately its original numeric values, as numeric(levels(f))[f] is recommended and slightly more efficient than as numeric(as character(f)) The FAQ on R has similar advice
When to use as. numeric and as. factor in R - Stack Overflow Factors (with as factor) are variables that have discrete values, which may or may not be ordered In other areas of science outside R they're often called categorical values For example North South East and West could be factors Numerics (with as numeric) are numbers, with infinite other numbers between them So for example 5 is a number, as is 6, but so are 5 01, 5 001, 5 0001 etc To
What is the significance of load factor in HashMap? A load factor=1 hashmap with number of entries=capacity will statistically have significant amount of collisions (=when multiple keys are producing the same hash) When collision occurs the lookup time increases, as in one bucket there will be >1 matching entries, for which the key must be individually checked for equality
r - list all factor levels of a data. frame - Stack Overflow with dplyr::glimpse(data) I get more values, but no infos about number values of factor-levels Is there an automatic way to get all level informations of all factor vars in a data frame?
when to use factor () when plotting with ggplot in R? Is the general rule to use factor when the variable being used to determine the shape size colour is discrete, and not continuous? Or is there another use of factor in this context? It seems like the first command can be made like the second with the right legend, even without factor thanks edit: I get this when I use the colour=gear:
Convert existing dataframe variable to factor in Tidyverse When you have an existing character variable in a dataframe, is there an easy method for converting that variable to a factor using the tidyverse format? For example, the 2nd line of code below won't reorder the factor levels, but the last line will
Convert all data frame character columns to factors Given a (pre-existing) data frame that has columns of various types, what is the simplest way to convert all its character columns to factors, without affecting any columns of other types? Here's an
r - Changing factor levels with dplyr mutate - Stack Overflow 19 From my understanding, the currently accepted answer only changes the order of the factor levels, not the actual labels (i e , how the levels of the factor are called) To illustrate the difference between levels and labels, consider the following example: