Chris Abraham

https://www.linkedin.com/in/cabraham1/
abrahajc89@gmail.com
216-554-2405

Data Analyst with extensive experience in storytelling with data, and creating streamlined workflows through stored processes. Searching for opportunities in a truly collaborative environment. Enjoy developing technical skills and learning how to best package findings via easy-to-follow and insightful deliverables. I created this resume entirely from my own coding in RMarkdown.

See How I Created This Resume in RMarkdown!

I have received many resumes where candidates exaggerated or misrepresented their coding or technical skills. I would like to separate myself by actually using my coding skills to create my resume, and have chosen my preferred medium (R) to do so. I have actually only recently started using RMarkdown to create documents and HTMLs that display both coding and outputs.

I enjoy Markdown because it allows be to format text using HTML Coding. For instance, I can format text that I want to see in bold below, or text on the same line where part of the string is left-justified (Company Name) and the other is right-justified (Years of Employment). You can also establish the color of font and the background color. Formatting bulleted- lists is pretty easy, too!

Work Experience

TravelCenters of America2019-Present

American Greetings2016-2018

St. Edward High School2013-2016

Relevant Skills Create a Bar Plot of Skills

library(data.table)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:data.table':
## 
##     between, first, last
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(ggplot2)
library(scales)

skilldf<-data.frame(skill=c('Microsoft Office (Excel, PowerPoint, Word, Outlook)','VBA', 'JavaScript',
                       'SPSS','SAS','SQL','R','Tableau','IBM Cognos','SAP', 'Python'),
                    experience=c('Frequent and Extensive Use Over a Long Period of Time',
                                 'Know a Few Commands and Have Used in a Professional Setting',
                                 'Have Taken Online Courses Like DataCamp or Codecademy',
                                 'Know a Few Commands and Have Used in a Professional Setting',
                                 'Moderate Experience But Not Currently Using Extensively',
                                 'Frequent and Extensive Use Over a Long Period of Time',
                                 'Frequent and Extensive Use Over a Long Period of Time',
                                 'Moderate Experience But Not Currently Using Extensively',
                                 'Moderate Experience But Not Currently Using Extensively',
                                 'Know a Few Commands and Have Used in a Professional Setting',
                                 'Have Taken Online Courses Like DataCamp or Codecademy')) %>%
  mutate(level=if_else(grepl("Frequent", experience), 4, if_else(grepl("Moderate", experience), 3,
                                                                 if_else(grepl('Few', experience),2, 1)))) %>%
  mutate(factorexp = factor(experience, levels = c('Have Taken Online Courses Like DataCamp or Codecademy',
                                                   'Know a Few Commands and Have Used in a Professional Setting',
                                                   'Moderate Experience But Not Currently Using Extensively',
                                                   'Frequent and Extensive Use Over a Long Period of Time')))

Relevant Skills 

ggplot(skilldf, aes(x=reorder(skill, -level), y=factorexp, fill=factorexp))+
  geom_bar(stat="identity" , colour="black")+
  scale_y_discrete(labels = wrap_format(10))+
  scale_x_discrete(labels = wrap_format(10))+
  ggtitle("Relevant Skills and Level of Experience")+
  theme(axis.title.y = element_blank(), axis.title.x=element_blank(), axis.text.y=element_text(size=7, face="bold"), axis.text.x=element_text(size=8))+
  theme(legend.position = "none", plot.title = element_text(hjust = 0.5))

Most Frequently Used R Packages Import the text from a sample of RScripts. Search For the Occurrences of ‘library(…)’. Create a Word Cloud with the most commonly-used library names.

setwd('C:\\Users\\abrah\\Desktop\\R codes\\')

scripts=list.files(pattern = "\\.R$")
head(scripts)
## [1] "1 Infiling SAP METERS AND SOLD tables.R"   
## [2] "2 SAP SOLD TABLE.R"                        
## [3] "2018 Holiday GC Code.R"                    
## [4] "2018 National Cheeseburger Research.R"     
## [5] "2019 Mothers Day High Level Summary Code.R"
## [6] "2019 Mothers Day Pmix code.R"
allscriptext<-lapply(scripts, readLines)

I copied hundreds of R Scripts that I have written and placed them in a folder on my Desktop, this is a few of their names.

allscriptext2<-paste(unlist(allscriptext), collapse=" ")

libraries<-data.frame(package=gsub("library|[\\(\\)]", "", regmatches(allscriptext2, gregexpr("library\\(.*?\\)", allscriptext2))[[1]]),
                      
                      count=1) %>%
  
  group_by(package) %>% summarise(count=sum(count)) %>% mutate(package=gsub("\\.", "", package)) %>%
  
  filter(!grepl("\"", package))

head(libraries)
## # A tibble: 6 x 2
##   package      count
##   <chr>        <dbl>
## 1 clValid          1
## 2 datatable      325
## 3 dplyr          303
## 4 factoextra      10
## 5 fitdistrplus     1
## 6 flextable        1

Above is a portion of the ‘libraries’ dataset, where I searched the text from all of the R Codes in the Desktop folder for everything that occurs between the parentheses where the string pattern ‘library(…)’ occurs.

library(wordcloud)
## Warning: package 'wordcloud' was built under R version 3.6.3
## Loading required package: RColorBrewer
library(RColorBrewer)

library(wordcloud2)
## Warning: package 'wordcloud2' was built under R version 3.6.3

Most Frequently Used R Packages

wordcloud2(data=libraries %>% mutate(count=sqrt(count)) %>% filter(!grepl('xxx', package)), size=0.5, color='random-dark')

AWESOME!

Education