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Find valid numeric variables in a dataframe

Source: R/identify_numeric_variables.R
identify_numeric_variables.Rd

Identifies valid numeric variables and ignores those with constant values.

Usage

identify_numeric_variables(
  df = NULL,
  responses = NULL,
  predictors = NULL,
  decimals = 4,
  quiet = FALSE,
  ...
)

Arguments

df

(required; dataframe, tibble, or sf) A dataframe with responses (optional) and predictors. Must have at least 10 rows for pairwise correlation analysis, and 10 * (length(predictors) - 1) for VIF. Default: NULL.

responses

(optional; character, character vector, or NULL) Name of one or several response variables in df. Default: NULL.

predictors

(required, character vector) Names of the predictors to identify. Default: NULL

decimals

(required, integer) Number of decimal places for the zero variance test. Smaller numbers will increase the number of variables detected as near-zero variance. Recommended values will depend on the range of the numeric variables in 'df'. Default: 4

quiet

(optional; logical) If FALSE, messages are printed. Default: FALSE.

...

(optional) Internal args (e.g. function_name for validate_arg_function_name, a precomputed correlation matrix m, or cross-validation args for preference_order).

Value

list:

  • valid: character vector with valid numeric predictor names.

  • invalid: character vector with invalid numeric predictor names due to near-zero variance.

See also

Other data_types: identify_categorical_variables(), identify_logical_variables(), identify_response_type(), identify_valid_variables(), identify_zero_variance_variables()

Author

Blas M. Benito, PhD

Examples


data(vi_smol, vi_predictors)

x <- identify_numeric_variables(
  df = vi_smol,
  responses = "vi_numeric",
  predictors = vi_predictors
)

#valid numeric predictors
x$valid
#>  [1] "vi_numeric"                 "topo_slope"                
#>  [3] "topo_diversity"             "topo_elevation"            
#>  [5] "swi_mean"                   "swi_max"                   
#>  [7] "swi_min"                    "swi_range"                 
#>  [9] "soil_temperature_mean"      "soil_temperature_max"      
#> [11] "soil_temperature_min"       "soil_temperature_range"    
#> [13] "soil_sand"                  "soil_clay"                 
#> [15] "soil_silt"                  "soil_ph"                   
#> [17] "soil_soc"                   "soil_nitrogen"             
#> [19] "solar_rad_mean"             "solar_rad_max"             
#> [21] "solar_rad_min"              "solar_rad_range"           
#> [23] "growing_season_length"      "growing_season_temperature"
#> [25] "growing_season_rainfall"    "growing_degree_days"       
#> [27] "temperature_mean"           "temperature_max"           
#> [29] "temperature_min"            "temperature_range"         
#> [31] "temperature_seasonality"    "rainfall_mean"             
#> [33] "rainfall_min"               "rainfall_max"              
#> [35] "rainfall_range"             "evapotranspiration_mean"   
#> [37] "evapotranspiration_max"     "evapotranspiration_min"    
#> [39] "evapotranspiration_range"   "cloud_cover_mean"          
#> [41] "cloud_cover_max"            "cloud_cover_min"           
#> [43] "cloud_cover_range"          "aridity_index"             
#> [45] "humidity_mean"              "humidity_max"              
#> [47] "humidity_min"               "humidity_range"            

#invalid due to zero variance (none here)
x$invalid
#> NULL