Hello,
I have the following error.
library(tidyverse)
library(scales)
#>
#> Attaching package: 'scales'
#> The following object is masked from 'package:purrr':
#>
#> discard
#> The following object is masked from 'package:readr':
#>
#> col_factor
library(forcats)
library(dplyr)
library(ggplot2)
library(data.table)
#>
#> Attaching package: 'data.table'
#> The following objects are masked from 'package:dplyr':
#>
#> between, first, last
#> The following object is masked from 'package:purrr':
#>
#> transpose
library(reprex)
library(cowplot)
#>
#> Attaching package: 'cowplot'
#> The following object is masked from 'package:ggplot2':
#>
#> ggsave
library(lubridate)
#>
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:data.table':
#>
#> hour, isoweek, mday, minute, month, quarter, second, wday,
#> week, yday, year
#> The following object is masked from 'package:base':
#>
#> date
library(RColorBrewer)
dput(datt_merge[1:20,])
#> Error in dput(datt_merge[1:20, ]): object 'datt_merge' not found
data = structure(list(CUSTOMER_NUMBER = c(0L, 209020998L, 209100011L,
209100058L, 209100072L, 209100080L, 209100404L, 209100520L, 209100821L,
209101604L, 209103004L, 209104201L, 209104202L, 209106542L, 209107926L,
209108266L, 209108384L, 209108744L, 209109816L, 209109929L),
Cluster = structure(c(6L, 2L, 5L, 2L, 1L, 2L, 2L, 6L, 2L,
1L, 6L, 4L, 1L, 2L, 2L, 3L, 4L, 6L, 1L, 4L), .Label = c("1",
"2", "3", "4", "5", "6"), class = "factor"), PROGRAM_LEVEL_DESCR = structure(c(11L,
11L, 11L, 7L, 14L, 11L, 11L, 11L, 12L, 11L, 11L, 14L, 11L,
14L, 11L, 11L, 12L, 11L, 11L, 9L), .Label = c("Branch Refusal",
"Club", "Corporate Refusal", "Credit Hold", "Customer Refusal",
"Diamond", "Enrollment", "Failed 2X in Calendar Year", "Gold",
"Institutional", "No Program", "Platinum", "RSVP", "Silver"
), class = "factor"), Handpieces.x = c(1, 0, 0, 0, 0, 0,
0, 0, 10, 0, 0, 2, 0, 3, 10, 0, 2, 2, 0, 4), `PRIVATE LABEL.x` = c(2,
85, 0, 0, 553, 0, 3, 0, 1288, 2, 0, 454, 1, 702, 184, 0,
347, 24, 54, 897), `SUND DISC.x` = c(0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), SUNDRY.x = c(133,
167, 66, 127, 490, 1, 20, 12, 1974, 2, 12, 560, 2, 656, 337,
67, 1440, 8, 65, 817), Total_Orders = c(136, 252, 66, 127,
1043, 1, 23, 12, 3272, 4, 12, 1016, 3, 1361, 531, 67, 1789,
34, 119, 1718), PL_Order_Percentage = c(1.47, 33.73, 0, 0,
53.02, 0, 13.04, 0, 39.36, 50, 0, 44.69, 33.33, 51.58, 34.65,
0, 19.4, 70.59, 45.38, 52.21), Handpieces.y = c(23, 0, 0,
0, 0, 0, 0, 0, 12073.4, 0, 0, 289.25, 0, 1485.95, 6633.44,
0, 1752.05, 396.4, 0, 3390.7), `PRIVATE LABEL.y` = c(96.74,
2448.25, 0, 0, 6593.85, 0, 80.45, 0, 19704.78, 25, 0, 8249.15,
25.15, 10954.25, 1819.83, 0, 12489.05, 502.25, 553.93, 17949.9
), `SUND DISC.y` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0), SUNDRY.y = c(6177.78, 11495.25,
11715.85, 4193.6, 28834.85, 36.75, 1355.4, 1006.2, 106976.7,
70.9, 2416.8, 52468.77, 66.25, 27370.09, 13765.64, 718.1,
77445.12, 1304.6, 1778.05, 45650.3), Total_Sales = c(6297.52,
13943.5, 11715.85, 4193.6, 35428.7, 36.75, 1435.85, 1006.2,
138754.88, 95.9, 2416.8, 61007.17, 91.4, 39810.29, 22218.91,
718.1, 91686.22, 2203.25, 2331.98, 66990.9)), row.names = c(NA,
20L), class = "data.frame")
new_datt_merge =
data %>%
mutate(category =
cut(PL_Order_Percentage,breaks = c(0,1,11,21,31,41,51,61,71,81,91,100,Inf),
labels = c('0% - < 1%','1%-10%','11%-20%',
'21%-30%','31%-40%','41%-50%',
'51%-60%','61%-70%','71%-80%',
'81%-90%','91% - < 100%','100%'),include.lowest = T,right = F)) %>%
select(CUSTOMER_NUMBER, Cluster,PL_Order_Percentage,
"PRIVATE LABEL.y","SUNDRY.y","Handpieces.y", Total_Sales, category) %>%
gather(bucket,value,-category) %>%
filter(bucket %in% c("PRIVATE LABEL.y","SUNDRY.y","Handpieces.y")) %>%
group_by(category, bucket) %>%
summarise(count = n(),
total_Sales = sum(value)) %>%
spread(bucket, total_Sales, fill = 0) %>%
na.omit() %>%
mutate(NonPL_Sales = `SUNDRY.y` + `Handpieces.y`,
PL_Sales = `PRIVATE LABEL.y`,
percent = count/sum(count)*100)
#> Warning: attributes are not identical across measure variables;
#> they will be dropped
#> Error in summarise_impl(.data, dots): Evaluation error: invalid 'type' (character) of argument.
Created on 2018-07-21 by the reprex
package (v0.2.0).