This is a typical example of how a Data science report can be made.

The data used here belongs to Biodelta Pharmacueticals

This work can certainly be improved upon

library(readr)
CustSalesMAY2019 <- read_csv("CustSalesMAY2019.csv")
## Warning: Missing column names filled in: 'X13' [13]
## Parsed with column specification:
## cols(
##   SUPNO = col_double(),
##   SUPNAME = col_character(),
##   BRANCH = col_character(),
##   CUSTNO = col_double(),
##   CUSTNAME = col_character(),
##   CUSTTOWN = col_character(),
##   CUSTPCODE = col_character(),
##   ITEMCODE = col_double(),
##   ITEMDESCR1 = col_character(),
##   ITEMDESCR2 = col_character(),
##   QTYSHIPPED = col_double(),
##   EXTPRC = col_double(),
##   X13 = col_character()
## )
## Warning: 589 parsing failures.
## row col   expected     actual                   file
##   1  -- 13 columns 12 columns 'CustSalesMAY2019.csv'
##   2  -- 13 columns 12 columns 'CustSalesMAY2019.csv'
##   3  -- 13 columns 12 columns 'CustSalesMAY2019.csv'
##   4  -- 13 columns 12 columns 'CustSalesMAY2019.csv'
##   5  -- 13 columns 12 columns 'CustSalesMAY2019.csv'
## ... ... .......... .......... ......................
## See problems(...) for more details.
View(CustSalesMAY2019)
head(CustSalesMAY2019)
## # A tibble: 6 x 13
##   SUPNO SUPNAME BRANCH CUSTNO CUSTNAME CUSTTOWN CUSTPCODE ITEMCODE
##   <dbl> <chr>   <chr>   <dbl> <chr>    <chr>    <chr>        <dbl>
## 1 11843 BIO DE… BFN    504869 ASSEMBL… KIMBERL… <NA>       1846964
## 2 11843 BIO DE… BFN    514503 BAHLABA… THABA N… 9780       1847035
## 3 11843 BIO DE… BFN    514503 BAHLABA… THABA N… 9780       1846913
## 4 11843 BIO DE… BFN    514503 BAHLABA… THABA N… 9780       1846956
## 5 11843 BIO DE… BFN    514503 BAHLABA… THABA N… 9780       1706427
## 6 11843 BIO DE… BFN    514503 BAHLABA… THABA N… 9780       1847019
## # ... with 5 more variables: ITEMDESCR1 <chr>, ITEMDESCR2 <chr>,
## #   QTYSHIPPED <dbl>, EXTPRC <dbl>, X13 <chr>

what the first 6 six rows of our data looks like

dim(CustSalesMAY2019)
## [1] 589  13

there are 589 observations and 13 variables

length(unique(CustSalesMAY2019$CUSTNAME))
## [1] 136

You had about 136 unique customers visit your shop

length(unique(CustSalesMAY2019$ITEMDESCR1))
## [1] 32

A total of 32 products were on the shelf

length(unique(CustSalesMAY2019$QTYSHIPPED))
## [1] 38

38 unique purchases were made

sum(CustSalesMAY2019$EXTPRC)
## [1] 126856.3

total of $126,866 was made in May

sum(CustSalesMAY2019$QTYSHIPPED)
## [1] 5365

5,365 cartons of items was sold on May

mean(CustSalesMAY2019$QTYSHIPPED)
## [1] 9.108659

Everyday about 9.2 cartons were sold

sort(table(CustSalesMAY2019$CUSTNAME),decreasing=TRUE)[1:3]
## 
##        MEDHOF APTEEK   MARBLE HALL APTEEK MASUPATSELA PHARMACY 
##                   21                   20                   17

3 Most valuable customers

 sort(table(CustSalesMAY2019$ITEMDESCR1),decreasing=TRUE)[1:3]
## 
## ALPHA VIT C 500MG 100 TABS         ALPHA CALM CAPS 20 
##                         74                         51 
##         ALPHA THROATIES 10 
##                         45

3 most shipped most products are ALPHA VIT C 500MG, 100 TABS, ALPHA CALM CAPS 20, and, ALPHA THROATIES 10

H <- c(74, 51 , 45 )
M <- c("VITC", "CALMCAPS", "THROATIE")
barplot(H,xlab="April 2019",ylab="most sold drug ",col=("blue"),names.arg=M, main="actual cartons shipped",border="red", horiz=TRUE)

ALPHA VIT C 500MG is the most sold item in the category being sold more than 70 times