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Binning by value is the only original binning method implemented in this package. It is inspired by the case in marketing when accounts need to be binned by their sales. For example, creating 10 bins, where each bin represent 10% of all market sales. The first bin contains the highest sales accounts, thus has the small total number of accounts, whereas the last bin contains the smallest sales accounts, thus requiring the most number of accounts per bin to reach 10% of the market sales.
tibble::tibble(SALES = as.integer(rnorm(1000L, mean = 10000L, sd = 3000))) -> sales_data
sales_data %>%
bin_cols(SALES, bin_type = "value") -> sales_data1
#> Warning: SALES contains negative values. Negative values are treated as 0.
sales_data1
#> # A tibble: 1,000 × 2
#> SALES SALES_va10
#> <int> <int>
#> 1 10609 5
#> 2 8370 2
#> 3 10786 6
#> 4 12320 8
#> 5 11110 6
#> 6 10797 6
#> 7 10213 5
#> 8 7287 2
#> 9 9904 4
#> 10 6460 1
#> # ℹ 990 more rowsNotice that the sum is equal across bins.
sales_data1 %>%
bin_summary() %>%
print(width = Inf)
#> # A tibble: 11 × 14
#> column method n_bins .rank .min .mean .max .count .uniques
#> <chr> <chr> <int> <int> <int> <dbl> <int> <int> <int>
#> 1 SALES equal value 10 10 14348 15719. 19905 63 61
#> 2 SALES equal value 10 9 13038 13574. 14339 73 69
#> 3 SALES equal value 10 8 12160 12527. 13006 79 75
#> 4 SALES equal value 10 7 11254 11722. 12153 84 81
#> 5 SALES equal value 10 6 10719 10969. 11251 90 83
#> 6 SALES equal value 10 5 10142 10433. 10714 95 84
#> 7 SALES equal value 10 4 9350 9698. 10137 102 94
#> 8 SALES equal value 10 3 8420 8905. 9345 111 108
#> 9 SALES equal value 10 2 7194 7832. 8419 126 117
#> 10 SALES equal value 10 1 760 5603. 7176 176 170
#> 11 SALES equal value 10 0 -180 -180 -180 1 1
#> relative_value .sum .med .sd width
#> <dbl> <int> <dbl> <dbl> <int>
#> 1 100 990276 15492 1147. 5557
#> 2 86.4 990874 13552 360. 1301
#> 3 79.7 989631 12503 265. 846
#> 4 74.6 984631 11662. 274. 899
#> 5 69.8 987232 10938. 148. 532
#> 6 66.4 991174 10423 181. 572
#> 7 61.7 989162 9668. 231. 787
#> 8 56.7 988447 8902 273. 925
#> 9 49.8 986795 7798. 367. 1225
#> 10 35.6 986058 6161 1506. 6416
#> 11 -1.15 -180 -180 NA 0These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.