Description Usage Arguments Value Author(s) Examples

Helper function that rescales a continuous variable to have specified minimum and maximum values.

The function rescale a continuous variable as follows:

*Rv_i = (Nmax -
Nmin)/(Omax - Omin) * (O_i - Omax) + Nmax*

Where *Rv_i* is the rescaled
value of the ith position of the variable/ vector; *Nmax* and *Nmin*
are the new maximum and minimum values; *Omax and Omin* are the maximum
and minimum values of the original data, and *O_i* is the ith value of
the original data.

There are basically two options to use `resca`

to rescale a variable.
The first is passing a data frame to `.data`

argument and selecting one
or more variables to be scaled using `...`

. The function will return the
original variables in `.data`

plus the rescaled variable(s) with the
prefix `_res`

. By using the function `group_by`

from **dplyr**
package it is possible to rescale the variable(s) within each level of the
grouping factor. The second option is pass a numeric vector in the argument
`values`

. The output, of course, will be a numeric vector of rescaled
values.

1 2 3 4 5 6 7 8 9 |

`.data` |
The dataset. Grouped data is allowed. |

`...` |
Comma-separated list of unquoted variable names that will be rescaled. |

`values` |
Optional vector of values to rescale |

`new_min` |
The minimum value of the new scale. Default is 0. |

`new_max` |
The maximum value of the new scale. Default is 100 |

`na.rm` |
Remove |

`keep` |
Should all variables be kept after rescaling? If false, only rescaled variables will be kept. |

A numeric vector if `values`

is used as input data or a tibble
if a data frame is used as input in `.data`

.

Tiago Olivoto tiagoolivoto@gmail.com

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
library(metan)
library(dplyr)
# Rescale a numeric vector
resca(values = c(1:5))
# Using a data frame
head(
resca(data_ge, GY, HM, new_min = 0, new_max = 1)
)
# Rescale within factors;
# Select variables that stats with 'N' and ends with 'L';
# Compute the mean of these variables by ENV and GEN;
# Rescale the variables that ends with 'L' whithin ENV;
data_ge2 %>%
select(ENV, GEN, starts_with("N"), ends_with("L")) %>%
means_by(ENV, GEN) %>%
group_by(ENV) %>%
resca(ends_with("L")) %>%
head(n = 13)
``` |

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