library(ggplot2)

# Preprocessing for density chart
raw1 <- read.csv("JMoSp_noLink_ready_for_processing.csv")
str(raw1)
## 'data.frame':    1529 obs. of  12 variables:
##  $ Column                     : int  0 1 2 3 4 5 6 7 8 9 ...
##  $ article                    : Factor w/ 1529 levels "S0022285203002546.xml",..: 1 2 3 4 5 6 7 8 9 10 ...
##  $ Non_self_referencial_link  : Factor w/ 1 level "False": 1 1 1 1 1 1 1 1 1 1 ...
##  $ volume                     : int  223 223 223 223 223 223 223 223 223 223 ...
##  $ pre_link_text              : Factor w/ 1529 levels " (FTIR)Journal of Molecular Spectroscopy 257 (2009) 187-199. doi:10.1016j.jms.2009.08.004journalJournal of Molecular Spectrosco"| __truncated__,..: 398 679 989 70 986 622 79 748 1212 374 ...
##  $ link_text                  : Factor w/ 1529 levels "http://dx.doi.org/10.1016/j.jms.2003.08.008doi:10.1016/j.jms.2003.08.008JournalsS300.1",..: 3 1 2 5 4 9 8 7 12 6 ...
##  $ clean_link_text_not_article: logi  NA NA NA NA NA NA ...
##  $ DOI_for_article            : Factor w/ 1529 levels "10.1016/j.jms.2003.08.008",..: 3 1 2 5 4 9 8 7 12 6 ...
##  $ linkDOI                    : Factor w/ 1529 levels "https://dx.doi.org/10.1016/j.jms.2003.08.008",..: 3 1 2 5 4 9 8 7 12 6 ...
##  $ citationCount              : int  2 9 6 2 6 21 27 10 12 0 ...
##  $ Date                       : Factor w/ 122 levels "2004-01-00","2004-02-00",..: 1 2 1 2 1 1 1 1 1 1 ...
##  $ dateYear                   : int  2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 ...
colnames(raw1)
##  [1] "Column"                      "article"                    
##  [3] "Non_self_referencial_link"   "volume"                     
##  [5] "pre_link_text"               "link_text"                  
##  [7] "clean_link_text_not_article" "DOI_for_article"            
##  [9] "linkDOI"                     "citationCount"              
## [11] "Date"                        "dateYear"
keeps1 <- c("Non_self_referencial_link","citationCount", "dateYear")
link_data1 <- raw1[keeps1]

raw2 <- read.csv("JMoSp_records_ready_for_processing.csv")
keeps2 <- c("Non_self_referencial_link","citationCount", "dateYear")
link_data2 <- raw2[keeps2]

link_data <- rbind(link_data1,link_data2)

colnames(link_data) <- c("Links", "Citations", "Year") 

# Preprocessing for histogram
keeps3 <- c("Column","StatusOverview", "dateYear")
chart2 <- raw2[keeps3]

colnames(chart2) <- c("number", "Status", "Year") 
chart2$number <- factor(chart2$number)
chart2$Year <- factor(chart2$Year)
str(chart2)
## 'data.frame':    1634 obs. of  3 variables:
##  $ number: Factor w/ 1634 levels "0","1","2","3",..: 1 2 3 4 5 6 7 8 9 10 ...
##  $ Status: Factor w/ 2 levels "ACTIVE","BROKEN": 1 1 1 1 2 2 1 1 1 2 ...
##  $ Year  : Factor w/ 11 levels "2004","2005",..: 1 1 1 1 1 1 1 1 1 1 ...

Plotting

# Desity plots
link_data$Links <- factor(link_data$Links)

l <- ggplot(link_data, aes(x = Citations, fill = Links)) + 
  geom_density(alpha = .3) +
  facet_grid(Year ~.) +
  scale_fill_manual( values = c("green","blue"))
l

# Bar plot
ggplot(chart2,aes(x=Year,fill=Status)) + geom_bar(position="dodge")