Living Former US Presidents

In this project I used the table found in the following link: https://en.wikipedia.org/wiki/List_of_Presidents_of_the_United_States#Living_former_presidents. The table shows the information about living former US presidents.

• Part 1: Create a .CSV file that includes all of the information above:
  • Install all the packages that will be used in this project.
    
  • Used rvest to pull the needed table from online and tidy it.
    
  • Created a .CSV file and uploaded it to GitHub repository.
    
• Part 2: Read the information from your .CSV file into R, and use tidyr and dplyr as needed to tidy and transform your “data”:
  • Read the .CSV file form GitHub.
    
  • Used dplyr and tidyr packages to transform and tidy the data.
    
  • More tiding and transforming data.
    
• Part 3: Perform analysis on the “data”:
  • Used knitr to create table.
    
  • Table that shows the summary of former president by age.
    
  • Overall summary of the living former president.

Part 1:

• Installing all the necessary packages needed for this data analysis.

library(rvest)

## Warning: package 'rvest' was built under R version 3.2.2

## Loading required package: xml2

## Warning: package 'xml2' was built under R version 3.2.2

library(stringr)
library(curl)
library(tidyr)

## Warning: package 'tidyr' was built under R version 3.2.2

library(dplyr)

## Warning: package 'dplyr' was built under R version 3.2.2

## 
## Attaching package: 'dplyr'
## 
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## 
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(knitr) 

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• I used rvest package to scrape, the table from “Wikipedia,” of living former president. This step for me was very hard for me, since I am new to web scraping. After finally getting r to load the table I noticed that I had to format the data, since it did not look like the table online. Therefore I used stringr to format the data and created the table “LF_President”. The new table looked exactly like the table found online.

url <- read_html("https://en.wikipedia.org/wiki/List_of_Presidents_of_the_United_States", Encoding = "UTF-8")
table1 <- url %>% html_nodes("table") %>% .[[2]]  %>% html_table()
table1

##           President Term of office                          Date of birth
## 1 George H. W. Bush    1989â<U+0080><U+0093>1993   (1924-06-12) June 12, 1924 (age 91)
## 2      Jimmy Carter    1977â<U+0080><U+0093>1981 (1924-10-01) October 1, 1924 (age 91)
## 3    George W. Bush    2001â<U+0080><U+0093>2009    (1946-07-06) July 6, 1946 (age 69)
## 4      Bill Clinton    1993â<U+0080><U+0093>2001 (1946-08-19) August 19, 1946 (age 69)

LF_President <- table1
LF_President$"Term of office" <- str_replace_all(LF_President$"Term of office", pattern = "(\\d{4}).*?(\\d{4})", replacement = "\\1\\-\\2 ") 
LF_President$"Date of birth" <- LF_President$"Date of birth" %>% str_replace_all(pattern = "\\(\\d{4}\\-\\d{2}\\-\\d{2}\\)", replacement = "") %>% str_replace_all(pattern = "age.\\s", replacement = "age ") 
LF_President

##           President Term of office             Date of birth
## 1 George H. W. Bush     1989-1993     June 12, 1924 (age 91)
## 2      Jimmy Carter     1977-1981   October 1, 1924 (age 91)
## 3    George W. Bush     2001-2009      July 6, 1946 (age 69)
## 4      Bill Clinton     1993-2001   August 19, 1946 (age 69)

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• I created a .CSV file with the living former president table in my local GitHub repository.

write.csv(LF_President, file = "C:/Users/Nabila/Documents/GitHub/Class-IS607/Project 2/Living Former Presidents/Living_Former_Presidents.csv")

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Part 2:

• Using the library curl I uploaded the living former president table from my online GitHub repository.

Living_President <- read.csv(file="https://raw.githubusercontent.com/nabilahossain/Class-IS607/master/Project%202/Living%20Former%20Presidents/Living_Former_Presidents.csv", header=TRUE, sep=",")
Living_President

##   X         President Term.of.office             Date.of.birth
## 1 1 George H. W. Bush     1989-1993     June 12, 1924 (age 91)
## 2 2      Jimmy Carter     1977-1981   October 1, 1924 (age 91)
## 3 3    George W. Bush     2001-2009      July 6, 1946 (age 69)
## 4 4      Bill Clinton     1993-2001   August 19, 1946 (age 69)

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• Using libraries dplyrand tidyr I transformed and tidied the data. Since the original table had a lot of data mashed together, I created a new table “Living Former President 1” (LFP1) by transforming the original table. I separated the 3rd and 4th columns into six columns. I originally wanted to separate the president’s name in first, last and middle name, however since we have two “George Bush” I thought it would be confusing to study the data with only last or first name.

LFP1 <- Living_President %>%  separate(Term.of.office, c("Term_Start_Year", "Term_End_Year"), sep = "-") %>% separate(Date.of.birth, c("Y", "Birth_Month", "Birth_Day", "Birth_Year", "Z", "Age"), extra = "drop") %>% select(-X, -Y, -Z)
LFP1

##           President Term_Start_Year Term_End_Year Birth_Month Birth_Day
## 1 George H. W. Bush            1989         1993         June        12
## 2      Jimmy Carter            1977         1981      October         1
## 3    George W. Bush            2001         2009         July         6
## 4      Bill Clinton            1993         2001       August        19
##   Birth_Year Age
## 1       1924  91
## 2       1924  91
## 3       1946  69
## 4       1946  69

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• I further transform and tidy the data. I created a table “Living_Former_President,” which has the president’s birth month in numeric, how many years they served, and their age when they were in term.

LFP1$Term_End_Year <- as.numeric(LFP1$Term_End_Year)
LFP1$Term_Start_Year <- as.numeric(LFP1$Term_Start_Year)
LFP1$Birth_Year <- as.numeric(LFP1$Birth_Year) 
LFP1$Birth_Day <- as.numeric(LFP1$Birth_Day) 
LFP1$Birth_Day <- sprintf("%02d", LFP1$Birth_Day)
LFP1$Age <- as.numeric(LFP1$Age)

Living_Former_President <- LFP1 %>% mutate(Years_In_Term = Term_End_Year - Term_Start_Year) %>% mutate(Age_Start_Term = Term_Start_Year - Birth_Year) %>% mutate(Age_End_Term = Term_End_Year - Birth_Year) %>% mutate(Term_Served = Years_In_Term / 4 )

Living_Former_President$Birth_Month <- Living_Former_President$Birth_Month %>% as.character.Date() %>% str_replace(pattern = "June\\s{1,}", replacement = "6") %>% str_replace(pattern = "October", replacement = "10") %>% str_replace(pattern = "July\\s{1,}", replacement = "7") %>% str_replace(pattern = "August\\s", replacement = "8") %>% as.numeric() 


Living_Former_President

##           President Term_Start_Year Term_End_Year Birth_Month Birth_Day
## 1 George H. W. Bush            1989          1993           6        12
## 2      Jimmy Carter            1977          1981          10        01
## 3    George W. Bush            2001          2009           7        06
## 4      Bill Clinton            1993          2001           8        19
##   Birth_Year Age Years_In_Term Age_Start_Term Age_End_Term Term_Served
## 1       1924  91             4             65           69           1
## 2       1924  91             4             53           57           1
## 3       1946  69             8             55           63           2
## 4       1946  69             8             47           55           2

Part 3:

• The table below shows the original data that was presented on the website.

kable(select(Living_President, -X), caption = "Table 1: Original table living former president (online).", align = "c")

Table 1: Original table living former president (online).

President	Term.of.office	Date.of.birth
George H. W. Bush	1989-1993	June 12, 1924 (age 91)
Jimmy Carter	1977-1981	October 1, 1924 (age 91)
George W. Bush	2001-2009	July 6, 1946 (age 69)
Bill Clinton	1993-2001	August 19, 1946 (age 69)

• The table below lists the presidents’ by their birth date, from oldest to youngest. We see that George H. W. Bush is older then Jimmy Carter even though they both were born in the same year, 1924. We can also see that they both served one term. On the other hand George W. Bush is older then Bill Clinton (they were also born in the same year, 1946) and they both served two terms.

Living_Former_President$Birth_Month <- sprintf("%02d", Living_Former_President$Birth_Month)
LFP2 <- Living_Former_President %>% select(President, Birth_Month, Birth_Day, Birth_Year, Term_Start_Year, Term_End_Year, Term_Served) %>% arrange( Birth_Year, Birth_Month) %>% unite("Date_of_Birth", Birth_Month, Birth_Day, Birth_Year, sep = "-")

kable(LFP2, caption = "Table 2: Living Former President, Oldest to Youngest, by date.", align = "c")

Table 2: Living Former President, Oldest to Youngest, by date.

President	Date_of_Birth	Term_Start_Year	Term_End_Year	Term_Served
George H. W. Bush	06-12-1924	1989	1993	1
Jimmy Carter	10-01-1924	1977	1981	1
George W. Bush	07-06-1946	2001	2009	2
Bill Clinton	08-19-1946	1993	2001	2

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• The table below shows the summary of the living former president by age. From this table we learn that the oldest out of the four to take office is George H. W. Bush at the age of 65, while Bill Clinton is the youngest, who became president at the age of 47.

LFP3 <- Living_Former_President %>% select(President, Age, Age_Start_Term, Age_End_Term, Years_In_Term) 

kable(LFP3, caption = "Table 3: Summary of living former president, by age.", align = "c")

Table 3: Summary of living former president, by age.

President	Age	Age_Start_Term	Age_End_Term	Years_In_Term
George H. W. Bush	91	65	69	4
Jimmy Carter	91	53	57	4
George W. Bush	69	55	63	8
Bill Clinton	69	47	55	8

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• The table below show the average age and term in years. The average year of a president to start term is 55 and the average age of all the living former president is 80. The average term in years a president held office is 6.

LFP4 <- Living_Former_President %>% summarise(Age_Started_Term=mean(Age_Start_Term), Age_Ended_Term=mean(Age_End_Term), Age=mean(Age), Years_In_Term=mean(Years_In_Term)) %>% data.frame() %>% gather("Average", "Years", 1:4)
LFP4

##            Average Years
## 1 Age_Started_Term    55
## 2   Age_Ended_Term    61
## 3              Age    80
## 4    Years_In_Term     6

kable(LFP4, caption = "Table 4: The four living former presidents' summary (average).", align = "c")

Table 4: The four living former presidents’ summary (average).

Average	Years
Age_Started_Term	55
Age_Ended_Term	61
Age	80
Years_In_Term	6

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