GitHub User : Max Goodridge

Max Goodridge is a Software engineer. These repositories are based on his tutorials posted in youtube

Github Repo : Max Goodridge has 38 repositories and 1.2k+ followers

Github link : https://github.com/maxg203

R setup

# Install if first time
#install.packages("gh")
library(gh)
library(httr)
library(tidyverse)
library(kableExtra)
library(ggthemes)

# Token from Github
my_token = "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"
Sys.setenv(GITHUB_TOKEN = my_token)

TASK 1

A table showing the user’s login, name, public_repos, followers

gh_max_profile <- gh("GET /users/maxg203", 
                     username = "maxg203",.limit=Inf)

library(tidyverse)
gh_max_profile <- tibble(
  login = gh_max_profile$login,
  name = gh_max_profile$name,
  public_repos = gh_max_profile$public_repos,
  followers = gh_max_profile$followers
)
head(gh_max_profile, n = 50) %>% 
  kable() %>% 
  kable_styling(bootstrap_options = c("bordered","striped","hover","condensed","responsive"))
login name public_repos followers
maxg203 Max Goodridge 38 1219

TASK 2

A table summarizing the followers’ login, name, public_repos, followers

# fetch follower list
gh_max_followers <- gh("/users/maxg203/followers", .limit = Inf)

# Create a dataframe 
df_followers <- data.frame(User=character(),
                           login=character(), 
                           public_repos=integer(), 
                           followers=integer()) 

# create functions to handle null values
null_list <- function(x){
  map_chr(x, ~{ifelse(is.null(.x), NA, .x)})
}

is.not.null <- function(x) !is.null(x)
n <- length(gh_max_followers)

# Fro loop for going to url of each follower and take further info

for (i in 1:n)
{
  # Take login of one follower to fetch further data 
  login = gh_max_followers[[i]]$login
  
  # fetch that follower's profile
  f_profile <- gh("GET /users/:login", login = login, .limit = Inf)
  
  # Take rest of data
  name = f_profile$name
  public_repos =f_profile$public_repos
  followers = f_profile$followers
  
  # Check for null and if not then populate data frame
if (is.not.null(name) & is.not.null(login) & is.not.null(public_repos) 
      & is.not.null(followers))
  {
        df_followers <- rbind(df_followers, data.frame(User=null_list(name),
        login = (login),
    public_repos=null_list(public_repos),
        followers = null_list(followers)))
  }
}
head(df_followers, n = 10) %>% 
  kable() %>% 
  kable_styling(bootstrap_options = c("bordered","striped","hover","condensed","responsive"))
User login public_repos followers
Donald Johnson copyleftdev 172 53
Sui Libin bygreencn 1355 142
unclefonso thefonso 212 118
Martin Tomanec wnetoa 9 6
X Code singerdmx 15 391
Juliano Fischer Naves julianofischer 108 37
Leonardo J. Caballero G. macagua 153 293
Jaime Jiménez jejimenez 17 5
Roman Ch farschmessivo 42 7
ángel abr4xas 77 201

TASK 3

A table summarizing the repositories’ name, size, forks_count, open_issues_count, closed_issue_count

Note : For the purpose of visualization, I have added “created_year” column as well

# get repo info 
gh_max_repos <- gh("GET /users/maxg203/repos", username = "maxg203",.limit = Inf)
length(gh_max_repos)
## [1] 38
library(tidyverse)

# create data frame
df_max_repo_info <- data.frame(Repo_Name=character(),
                           size=integer(), 
                           forks=integer(), 
                           open_issues_count=integer(),
                           closed_issues_count=integer()) 

# Fetch data for each repo

for (i in 1:length(gh_max_repos))
{ 
  
# Find all required columns 
name = gh_max_repos[[i]]$name
size = gh_max_repos[[i]]$size
created_year = as.integer(substring(gh_max_repos[[i]]$created_at,1,4))
forks = gh_max_repos[[i]]$forks_count
open_issues_count = gh_max_repos[[i]]$open_issues_count
    
closed_issues_url <-
  paste0(gh_max_repos[[i]]$url,"/issues?state=closed")
    
closed_issues = gh(closed_issues_url,username = "maxg203",.limit = Inf)
closed_issues_count = length(closed_issues)
    
# Populate data to data frame
if (is.not.null(name) & is.not.null(size) & is.not.null(forks)
    & is.not.null(created_year)
        & is.not.null(open_issues_count) & is.not.null(closed_issues_count))
{
df_max_repo_info<-rbind(df_max_repo_info, data.frame(Repo_Name = null_list(name),
size = null_list(size),
forks = null_list(forks),
created_year = null_list(created_year),
open_issues_count = null_list(open_issues_count),
closed_issues_count = null_list(closed_issues_count)))
}
    
}
head(df_max_repo_info, n = 15) %>% kable() %>%
  kable_styling(bootstrap_options = c("bordered","striped","hover","condensed","responsive")) %>% scroll_box(width="100%",height="300px")
Repo_Name size forks created_year open_issues_count closed_issues_count
accessible-bath 726 0 2017 0 0
airflow-workflows 23 1 2019 1 0
angular-seed 3382 1 2017 0 0
angular-todo 9 1 2017 3 2
aws_kinesis_ingestion_pipeline 24 0 2019 0 0
Content-Feed 540 2 2017 0 0
Content-Feed-FE 112 2 2017 0 0
django 196825 3 2016 0 0
django-dbbackup 404 4 2017 0 0
django-rest-framework 37679 6 2018 0 0
django-starter 163 2 2017 0 0
Django-Tutorials 139 169 2017 14 3
django-tweets 13 1 2016 0 0
docker.github.io 510622 1 2017 0 0
docs 31773 4 2017 0 3

Visualizations - Plot 1

User’s top repositories based on number of forks

# Create summary table ( By year )
DF_top_repos <- df_max_repo_info %>% 
  arrange(desc(forks))

df <- head(DF_top_repos)

# create the plot using ggplot 
ggplot(df, 
    aes(x = Repo_Name, y = forks)) +
    geom_bar(stat = "identity", position = "dodge") + 
    theme_economist() +
    scale_color_gdocs() +
    theme(axis.text.x=element_text(angle = 30, vjust = 0.5)) +
    theme(plot.title = element_text(hjust = 0.5), legend.position = "bottom") +
    ggtitle("Popular Repos ") +
    xlab("Repo Name") +
    ylab ("Number of Forks")

Visualizations - Plot 2

Repo Counts per year ( See how active user is through out)

df_repo_summary <- df_max_repo_info %>% group_by(created_year) %>% 
  summarise(Repo_Count = n())



# create the plot using ggplot 
ggplot(df_repo_summary, 
    aes(x = created_year, y = Repo_Count)) +
    geom_bar(stat = "identity", position = "dodge") + 
    theme_economist() +
    scale_color_gdocs() +
    theme(axis.text.x=element_text(angle = 30, vjust = 0.5)) +
    theme(plot.title = element_text(hjust = 0.5), legend.position = "bottom") +
    ggtitle("Repo count by year") +
    xlab("Year") +
    ylab ("Number of Repos")

```