/
Class.FIx.R
367 lines (318 loc) · 22.8 KB
/
Class.FIx.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
Class.Fix <- function(A) {
str(ClassData)
summary(ClassData)
ClassData$JOURNAL<-as.factor(ClassData$JOURNAL)
#write.csv(ClassData, file="/Users/emiliobruna/Dropbox/EMB - ACTIVE/MANUSCRIPTS/Editorial Board Geography/ClassData.csv", row.names = T) #export it as a csv file
# THIS REMOVEAS A FEW WITH BLANKS IN THE NAMES
ClassData <-filter(ClassData, ClassData$FIRST_NAME!="" & ClassData$LAST_NAME!="")
# Error Correction
####FIX THIS
# ClassData[which(ClassData$JOURNAL==""),] #are there any with no journal?
# ClassData[which(ClassData$FIRST_NAME==""),] #are there any with no 1st name?
# ClassData[which(ClassData$LAST_NAME==""),] #are there any with no 1st name?
ClassData$FIRST_NAME<-as.character(ClassData$FIRST_NAME)
#####
str(ClassData)
# Make the data types consistent with ChoData
ClassData$VOLUME<-as.integer(ClassData$VOLUME)
ClassData$ISSUE<-as.integer(ClassData$ISSUE)
#Remove (trim) the leading and trailing white spaces (note can do with one command as per: http://stackoverflow.com/questions/2261079/how-to-trim-leading-and-trailing-whitespace-in-r)
trim.trailing <- function (x) sub("\\s+$", "", x)
ClassData$FIRST_NAME<-trim.trailing(ClassData$FIRST_NAME)
ClassData$MIDDLE_NAME<-trim.trailing(ClassData$MIDDLE_NAME)
ClassData$LAST_NAME<-trim.trailing(ClassData$LAST_NAME)
ClassData$TITLE<-trim.trailing(ClassData$TITLE)
ClassData$INSTITUTION<-trim.trailing(ClassData$INSTITUTION)
trim.leading <- function (x) sub("^\\s+", "", x)
ClassData$FIRST_NAME<-trim.leading(ClassData$FIRST_NAME)
ClassData$MIDDLE_NAME<-trim.leading(ClassData$MIDDLE_NAME)
ClassData$LAST_NAME<-trim.leading(ClassData$LAST_NAME)
ClassData$TITLE<-trim.leading(ClassData$TITLE)
ClassData$INSTITUTION<-trim.leading(ClassData$INSTITUTION)
# remove any double spaces
ClassData$FIRST_NAME<-gsub(" ", " ", ClassData$FIRST_NAME)
ClassData$LAST_NAME<-gsub(" ", " ", ClassData$LAST_NAME, fixed=TRUE)
ClassData$MIDDLE_NAME<-gsub(" ", " ", ClassData$MIDDLE_NAME, fixed=TRUE)
# Remove the periods from peoples names to make consistent accross all files
ClassData$FIRST_NAME<-gsub("[.]","", ClassData$FIRST_NAME) # . is a wildcard, so [.] removes only the period.
ClassData$MIDDLE_NAME<-gsub(".", "", ClassData$MIDDLE_NAME, fixed=TRUE)
ClassData$LAST_NAME<-gsub(".", "", ClassData$LAST_NAME, fixed=TRUE)
# which(ClassData$FIRST_NAME=="Marc-Andr_")
# which(ClassData$MIDDLE_NAME=="JT")
# which(ClassData$LAST_NAME=="Selosse")
# Add the missing years and volumes
ClassData$VOLUME[ClassData$JOURNAL == "AMNAT" & ClassData$YEAR == "2006"] <- "167"
ClassData$VOLUME[ClassData$JOURNAL == "AMNAT" & ClassData$YEAR == "2007"] <- "169"
ClassData$VOLUME[ClassData$JOURNAL == "AMNAT" & ClassData$YEAR == "2008"] <- "171"
ClassData$VOLUME[ClassData$JOURNAL == "AMNAT" & ClassData$YEAR == "2009"] <- "173"
ClassData$VOLUME[ClassData$JOURNAL == "AMNAT" & ClassData$YEAR == "2010"] <- "175"
ClassData$VOLUME[ClassData$JOURNAL == "AMNAT" & ClassData$YEAR == "2011"] <- "177"
ClassData$VOLUME[ClassData$JOURNAL == "AMNAT" & ClassData$YEAR == "2012"] <- "179"
ClassData$VOLUME[ClassData$JOURNAL == "AMNAT" & ClassData$YEAR == "2013"] <- "181"
ClassData$VOLUME[ClassData$JOURNAL == "AMNAT" & ClassData$YEAR == "2014"] <- "183"
ClassData$ISSUE[ClassData$JOURNAL == "AMNAT" & is.na(ClassData$ISSUE)] <- 1
ClassData$VOLUME[ClassData$JOURNAL == "PLANTECOL" & ClassData$YEAR == "1993"] <- "104/105"
ClassData$YEAR[ClassData$JOURNAL == "LECO" & ClassData$YEAR == "1996" & ClassData$VOLUME == "10"] <- "1995"
ClassData$VOLUME[ClassData$JOURNAL == "LECO" & ClassData$YEAR == "2001"] <- "16"
ClassData$VOLUME[ClassData$JOURNAL == "LECO" & ClassData$YEAR == "2002"] <- "17"
ClassData$VOLUME[ClassData$JOURNAL == "LECO" & ClassData$YEAR == "2003"] <- "18"
ClassData$VOLUME[ClassData$JOURNAL == "LECO" & ClassData$YEAR == "2012"] <- "27"
ClassData$VOLUME[ClassData$JOURNAL == "LECO" & ClassData$YEAR == "2014"] <- "28"
ClassData$VOLUME[ClassData$JOURNAL == "LECO" & ClassData$YEAR == "2014"] <- "29"
ClassData$VOLUME[ClassData$JOURNAL == "JZOOL" & ClassData$YEAR == "2006"] <- "268"
ClassData$VOLUME[ClassData$JOURNAL == "JZOOL" & ClassData$YEAR == "2007"] <- "271"
ClassData$VOLUME[ClassData$JOURNAL == "JZOOL" & ClassData$YEAR == "2008"] <- "274"
ClassData$VOLUME[ClassData$JOURNAL == "JZOOL" & ClassData$YEAR == "2009"] <- "277"
ClassData$VOLUME[ClassData$JOURNAL == "JZOOL" & ClassData$YEAR == "2010"] <- "280"
ClassData$VOLUME[ClassData$JOURNAL == "JZOOL" & ClassData$YEAR == "2011"] <- "283"
ClassData$VOLUME[ClassData$JOURNAL == "ECOGRAPHY" & ClassData$YEAR == "2013"] <- "36"
ClassData$VOLUME[ClassData$JOURNAL == "ECOGRAPHY" & ClassData$YEAR == "2014"] <- "37"
ClassData$VOLUME[ClassData$JOURNAL == "OIKOS" & ClassData$YEAR == "2010"] <- "119"
ClassData$VOLUME[ClassData$JOURNAL == "OIKOS" & ClassData$YEAR == "2011"] <- "120"
ClassData$VOLUME[ClassData$JOURNAL == "OIKOS" & ClassData$YEAR == "2012"] <- "121"
ClassData$VOLUME[ClassData$JOURNAL == "OIKOS" & ClassData$YEAR == "2013"] <- "122"
ClassData$VOLUME[ClassData$JOURNAL == "OIKOS" & ClassData$YEAR == "2014"] <- "123"
# FIRST NAMES TO BE CORRECTED
ClassData$FIRST_NAME[ClassData$LAST_NAME == "Briones"] <- "Maria"
ClassData$FIRST_NAME[ClassData$LAST_NAME == "Kudla"] <- "Jorg"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Aliastair"] <- "Alastair"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Marc-Andr_"] <- "Marc-Andre"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "J_rgen"] <- "Jurgen"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Pihilip"] <- "Philip"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Ricardo"] <- "Riccardo"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Daphnew"] <- "Daphne"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Emflia"] <- "Emilia"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Clharles"] <- "Charles"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Daniei"] <- "Daniel"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Dianne"] <- "Diane"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Harol"] <- "Harold"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Jefery"] <- "Jeffry"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Natalie"] <- "Nathalie"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Candance"] <- "Candace"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Pfter"] <- "Peter"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Rolbert"] <- "Robert"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Andr_"] <- "Andre"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Vejo"] <- "Veijo"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Ikka"] <- "Ilkka"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Mxrrhew"] <- "Matthew"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Drie"] <- "Dries"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Jean-Michelle"] <- "Jean-Michel"
ClassData$FIRST_NAME[ClassData$FIRST_NAME == "Neal"] <- "Neil" #JBIOG has his name wrong in the journal - corrct is Neil j enright, not neal l enright
ClassData$MIDDLE_NAME[ClassData$FIRST_NAME == "Neil"] <- "J" #JBIOG has his name wrong in the journal - corrct is Neil j enright, not neal l enright
ClassData$FIRST_NAME[ClassData$FIRST == "Charles" & ClassData$LAST_NAME == "Godfray"] <- "H" #WORKING?
# MIDDLE NAMES TO BE CORRECTED
ClassData$MIDDLE_NAME[ClassData$MIDDLE_NAME == "J A"] <- "JA"
ClassData$MIDDLE_NAME[ClassData$MIDDLE_NAME == "Richiard"] <- "Richard"
ClassData$MIDDLE_NAME[ClassData$MIDDLE_NAME == "AlbertC"] <- "Albert C"
ClassData$MIDDLE_NAME[ClassData$MIDDLE_NAME == "GA"] <- "G A"
ClassData$MIDDLE_NAME[ClassData$FIRST_NAME == "H" & ClassData$LAST_NAME == "Godfray"] <- "CharlesJ" #WORKING?
ClassData$MIDDLE_NAME[ClassData$MIDDLE_NAME == "Paolo"] <- ""
ClassData$MIDDLE_NAME[ClassData$MIDDLE_NAME == "G"] <- "Green"
# LAST NAMES TO BE CORRECTED
ClassData$LAST_NAME[ClassData$LAST_NAME == "Saltzburger"] <- "Salzburger"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Ballar_"] <- "Ballare"
ClassData$LAST_NAME[ClassData$LAST_NAME == "JD"] <- "JT"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Mueller" & ClassData$FIRST_NAME == "Caroline"] <- "Muller" #WORKING?
ClassData$LAST_NAME[ClassData$LAST_NAME == "Fairburn"] <- "Fairbairn"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Buerger"] <- "Burger"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Colwel"] <- "Colwell"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Abrecht"] <- "Albrecht"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Meaghe"] <- "Meagher"
ClassData$LAST_NAME[ClassData$LAST_NAME == "McCailum"] <- "McCallum"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Mit[On"] <- "Mitton"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Gerber"] <- "Geber"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Harevey"] <- "Harvey"
ClassData$LAST_NAME[ClassData$LAST_NAME == "O'Donnell"] <- "ODonnell"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Odonnell"] <- "ODonnell"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Beashop"] <- "Bearhop"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Plnero"] <- "Pinero"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Coyn"] <- "Coyne"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Fryxwell"] <- "Fryxell"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Lillim"] <- "Lill"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Lillm"] <- "Lill"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Ericksson"] <- "Eriksson"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Bennet"] <- "Bennett"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Pim"] <- "Pimm"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Rot"] <- "Roth"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Sieman"] <- "Siemann"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Yl_nen"] <- "Ylonen"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Lillm"] <- "Lill"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Niemala"] <- "Niemela"
#ClassData$LAST_NAME[ClassData$LAST_NAME == "Schmid"] <- "Schmitz"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Fielder"] <- "Fiedler"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Karieva"] <- "Kareiva"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Diaz-Filho"] <- "Diniz-Filho"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Diniz-Filho"] <- "Diniz-Filho"
ClassData$FIRST_NAME[ClassData$LAST_NAME == "Diniz-Filho"] <- "Jose" #WORKING?
ClassData$MIDDLE_NAME[ClassData$LAST_NAME == "Diniz-Filho"] <- "Alexandre" #WORKING?
ClassData$LAST_NAME[ClassData$LAST_NAME == "Rea"] <- "Real"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Paolo"] <- "Paolo-Patti"
ClassData$LAST_NAME[ClassData$LAST_NAME == "Patti"] <- "Paolo-Patti"
ClassData$LAST_NAME[ClassData$LAST_NAME == "H" & ClassData$FIRST_NAME=="George"] <- "Heimpel"
ClassData$LAST_NAME[ClassData$LAST_NAME == "vanderhaijden"] <- "vanderheijden"
# Cleaning up the titles
# FIrst standardize them
# #remove extra spaces, converts to chr
# ClassData$TITLE<-gsub(" ", "", ClassData$TITLE, fixed=TRUE)
ClassData$TITLE<-gsub("\\ ", ".", ClassData$TITLE) #Replace spaces with period
ClassData$TITLE<-gsub(":", "", ClassData$TITLE) #Replace : with period
ClassData$TITLE[ClassData$JOURNAL == "AMNAT" & ClassData$TITLE == "AE"] <- "Editorial.Board"
ClassData$TITLE[ClassData$TITLE == "Editor-in-Chief"] <- "EIC"
ClassData$TITLE[ClassData$TITLE == "Editor-In-Chief"] <- "EIC"
ClassData$TITLE[ClassData$TITLE == "Natural.HistoryEditor"] <- "Natural.History.Editor"
ClassData$TITLE[ClassData$TITLE == "Deputy.Editor-In-Chief"] <- "Deputy.EIC"
ClassData$TITLE[ClassData$TITLE == "Deputy.Editor.in.Chief"] <- "Deputy.EIC"
ClassData$TITLE[ClassData$TITLE == "Editor-in-Chief"] <- "EIC"
ClassData$TITLE[ClassData$TITLE == "SPECIAL.EDITORS"] <- "Special.Editor"
ClassData$TITLE[ClassData$TITLE == "editor"] <- "Editor"
ClassData$TITLE[ClassData$TITLE == "guest.editor"] <- "Guest.Editor"
ClassData$TITLE[ClassData$TITLE == "Associate.Editors"] <- "Associate.Editor"
ClassData$TITLE[ClassData$TITLE == "EIC "] <- "EIC"
ClassData$TITLE[ClassData$TITLE == "Acting.director.in.chief"] <- "Acting.Director.In.Chief"
ClassData$TITLE[ClassData$TITLE == "Co-Editor"] <- "CoEditor"
ClassData$TITLE[ClassData$TITLE == "Deputy.director.in.chief"] <- "Deputy.EIC"
ClassData$TITLE[ClassData$TITLE == "editor"] <- "Editor"
ClassData$TITLE[ClassData$TITLE == "Editor.-.Executive.Editor"] <- "Editor-Executive.Editor"
ClassData$TITLE[ClassData$TITLE == "Editorial.board"] <- "Editorial.Board"
ClassData$TITLE[ClassData$TITLE == "Editors"] <- "Editor"
ClassData$TITLE[ClassData$TITLE == "Executive.Sevretary"] <- "Executive.Secretary"
ClassData$TITLE[ClassData$TITLE == "Production.editor"] <- "Production.Editor"
ClassData$TITLE[ClassData$TITLE == "ReviewsEditor"] <- "Reviews.Editor"
ClassData$TITLE[ClassData$TITLE == "editorial.review.board"] <- "Editorial.Review.Board"
ClassData$TITLE[ClassData$TITLE == "EditorialBoard"] <- "Editorial.Board"
ClassData$TITLE[ClassData$TITLE == "HandlingEditor"] <- "Handling.Editor"
ClassData$TITLE[ClassData$TITLE == "Section.Editors..Environment"] <- "Section.Editors.Environment"
ClassData$TITLE[ClassData$TITLE == "Section.Editors..Physiology.&.Development"] <- "Section.Editors.Physiology.&.Development"
ClassData$TITLE[ClassData$TITLE == "Tansley.review.Editor"] <- "Tansley.Review.Editor"
ClassData$TITLE[ClassData$TITLE == "associate.editor"] <- "Associate.Editor"
ClassData$TITLE[ClassData$TITLE == "Deputy.editor.in.chief"] <- "Deputy.EIC"
ClassData$TITLE[ClassData$TITLE == "Editor.In.Chief"] <- "EIC"
ClassData$TITLE[ClassData$TITLE == "Editorial.board"] <- "Editorial.Board"
ClassData$TITLE[ClassData$TITLE == "Production.editor"] <- "Production.Editor"
ClassData$TITLE[ClassData$TITLE == "ReviewsEditor"] <- "Reviews.Editor"
ClassData$TITLE[ClassData$TITLE == "Review.Editor"] <- "Reviews.Editor"
ClassData$TITLE[ClassData$TITLE == "Section.Editor.Physiology.&.Development"] <- "Section.Editor.Physiology.Development"
ClassData$TITLE[ClassData$TITLE == "Section.Editors..Function"] <- "Section.Editors.Function"
ClassData$TITLE[ClassData$TITLE == "Sections.Editor"] <- "Section.Editor"
ClassData$TITLE[ClassData$TITLE == "Subject.Editors"] <- "Subject.Editor"
ClassData$TITLE[ClassData$TITLE == "Editor.in.chief"] <- "EIC"
ClassData$TITLE[ClassData$TITLE == "TE"] <- "Technical.Editor"
ClassData$TITLE[ClassData$TITLE == "WA"] <- "Website.Administrator"
ClassData$TITLE[ClassData$TITLE == "JPS"] <- "Journal.Production.Supervisor"
ClassData$TITLE[ClassData$TITLE == "JES"] <- "Journal.Editorial.Supervisor"
ClassData$TITLE[ClassData$TITLE == "JS"] <- "Journal.Supervisor"
ClassData$TITLE[ClassData$TITLE == "PE"] <- "Production.Editor"
ClassData$TITLE[ClassData$TITLE == "ME"] <- "Managing.Editor"
ClassData$TITLE[ClassData$TITLE == "PD"] <- "Publications.Director"
ClassData$TITLE[ClassData$TITLE == "BRE"] <- "Book.Review.Editor"
#Now correct the Categories that were incorrectly assigned
ClassData$CATEGORY<-as.character(ClassData$CATEGORY)
ClassData$CATEGORY[ClassData$JOURNAL == "AMNAT" & ClassData$TITLE == "Natural.History.Editor"] <- "SPECIAL"
ClassData$CATEGORY[ClassData$JOURNAL == "AMNAT" & ClassData$TITLE == "EIC"] <- "EIC"
ClassData$CATEGORY[ClassData$JOURNAL == "AMNAT" & ClassData$TITLE == "Editor" & (ClassData$YEAR >= 2005 & ClassData$YEAR < 2016) ] <- "AE"
ClassData$CATEGORY[ClassData$JOURNAL == "AMNAT" & ClassData$TITLE == "AE" & (ClassData$YEAR >= 2005 & ClassData$YEAR < 2016) ] <- "AE"
ClassData$TITLE[ClassData$JOURNAL == "AMNAT" & ClassData$LAST_NAME == "Whitlock" & ClassData$YEAR == 2005] <- "Editor"
ClassData$CATEGORY[ClassData$JOURNAL == "AMNAT" & ClassData$LAST_NAME == "Whitlock" & ClassData$YEAR == 2005] <- "AE"
ClassData$TITLE[ClassData$JOURNAL == "AMNAT" & ClassData$LAST_NAME == "Winn" & ClassData$YEAR == 2015] <- "Editorial.Board"
ClassData$CATEGORY[ClassData$JOURNAL == "AMNAT" & ClassData$LAST_NAME == "Winn" & ClassData$YEAR == 2015] <- "SE"
ClassData$TITLE[ClassData$JOURNAL == "AMNAT" & ClassData$LAST_NAME == "McPeek" & ClassData$YEAR == 2015] <- "Natural.History.Editor"
ClassData$CATEGORY[ClassData$JOURNAL == "AMNAT" & ClassData$LAST_NAME == "McPeek" & ClassData$YEAR == 2015] <- "SPECIAL"
ClassData$TITLE[ClassData$JOURNAL == "AMNAT" & ClassData$FIRST_NAME == "Yannis" & ClassData$YEAR == 2015] <- "Editorial.Board"
ClassData$CATEGORY[ClassData$JOURNAL == "AMNAT" & ClassData$LAST_NAME == "Yannis" & ClassData$YEAR == 2015] <- "SE"
ClassData$CATEGORY[ClassData$JOURNAL == "OIKOS" & ClassData$TITLE == "Deputy.EIC"] <- "EIC"
ClassData$CATEGORY[ClassData$JOURNAL == "OIKOS" & ClassData$TITLE == "Editor"] <- "AE"
ClassData$CATEGORY[ClassData$JOURNAL == "EVOL" & ClassData$YEAR == 2015 & ClassData$TITLE == "Editor"] <- "AE"
ClassData$TITLE[ClassData$JOURNAL == "AGRONOMY" & ClassData$TITLE == "E"] <- "EIC"
ClassData$CATEGORY[ClassData$JOURNAL == "AGRONOMY" & ClassData$LAST_NAME == "Raun" & ClassData$YEAR == 2014 ] <- "EIC"
ClassData$CATEGORY[ClassData$TITLE == "Editor" & ClassData$JOURNAL=="JBIOG"] <- "AE" # NEED to 2x
ClassData$CATEGORY[ClassData$TITLE == "Senior.Editor" & ClassData$JOURNAL=="JBIOG"] <- "EIC" # I think this because "Deputy EIC later"
ClassData$CATEGORY[ClassData$TITLE == "Associate.Editor" & ClassData$JOURNAL=="JBIOG"] <- "SE" # NEED to 2x
ClassData$CATEGORY[ClassData$TITLE == "Deputy.Editor" & ClassData$JOURNAL=="JBIOG"] <- "EIC" # NEED to 2x
ClassData$CATEGORY[ClassData$TITLE == "Deputy.EIC" & ClassData$JOURNAL=="JBIOG"] <- "EIC" # NEED to 2x
ClassData$CATEGORY[ClassData$TITLE == "Technical.Editor" & ClassData$JOURNAL == "JBIOG"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Journal.Editorial.Supervisor"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Production.Editor"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Publications.Director"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Book.Review.Editor"] <- "SPECIAL"
ClassData$CATEGORY[ClassData$TITLE == "Reviews.Editor"] <- "SPECIAL"
ClassData$CATEGORY[ClassData$TITLE == "Production.Staff"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Editorial.Assistant"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Editorial.Assistants"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Secretary"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Editorial.Office.Manager"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Production.Editor"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Technical.Editor" & ClassData$JOURNAL == "AGRONOMY"] <- "AE"
ClassData$CATEGORY[ClassData$TITLE == "Editorial.Board" & ClassData$JOURNAL == "AMNAT" ] <- "SE"
ClassData$CATEGORY[ClassData$TITLE == "Special.Editor" & ClassData$JOURNAL=="EVOL"] <- "SPECIAL" # NEED to 2x
ClassData$CATEGORY[ClassData$TITLE == "Academic.Associate" & ClassData$JOURNAL=="EVOL"] <- "2xCheck" # NEED to 2x
ClassData$CATEGORY[ClassData$TITLE == "Advisory.Panel" & ClassData$JOURNAL=="OIKOS"] <- "SE"
ClassData$CATEGORY[ClassData$TITLE == "Publication.Board" & ClassData$JOURNAL=="OIKOS"] <- "Society.Publication.Committee"
ClassData$CATEGORY[ClassData$CATEGORY == "" & ClassData$JOURNAL=="EVOL"] <- "2xCheck" # NEED to 2x
ClassData$CATEGORY[ClassData$TITLE == "Guest.Editor"] <- "SPECIAL"
ClassData$CATEGORY[ClassData$TITLE == "Managing.Editor"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Executive.Secretary"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Editorial.Staff"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Copy.Editor"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Assistant.Managing.Editor"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Assistant.Editor"] <- "Production"
ClassData$CATEGORY[ClassData$TITLE == "Academic.Associate"] <- "Production"
#Clean Up Categories
ClassData$CATEGORY<-as.character(ClassData$CATEGORY)
ClassData$CATEGORY[ClassData$CATEGORY == "Ae"] <- "AE"
ClassData$CATEGORY[ClassData$CATEGORY == "OTHER"] <- "other"
ClassData$CATEGORY[ClassData$CATEGORY == "Other"] <- "other"
ClassData$CATEGORY[ClassData$CATEGORY == "Other "] <- "other"
ClassData$CATEGORY[ClassData$CATEGORY == "EDITOR-IN-CHIEF"] <- "EIC"
ClassData$CATEGORY[ClassData$CATEGORY == "SE "] <- "SE"
ClassData$CATEGORY[ClassData$CATEGORY == "EIC "] <- "EIC"
ClassData$CATEGORY[ClassData$CATEGORY == "None"] <- "none"
# ClassData$CATEGORY[ClassData$CATEGORY == "SPECIAL"] <- "special"
ClassData$CATEGORY[ClassData$CATEGORY == "Special"] <- "SPECIAL"
ClassData$CATEGORY[ClassData$CATEGORY == "Production editor"] <- "Production"
ClassData$CATEGORY[ClassData$CATEGORY == "Production Staff"] <- "Production"
ClassData$CATEGORY[ClassData$CATEGORY == "Journal Supervisor"] <- "Production"
ClassData$CATEGORY[ClassData$CATEGORY == "JPS"] <- "Production"
ClassData$CATEGORY[ClassData$CATEGORY == "JS"] <- "Production"
ClassData$CATEGORY[ClassData$CATEGORY == "PE"] <- "Production"
ClassData$CATEGORY[ClassData$CATEGORY == "Productioneditor"] <- "Production"
ClassData$CATEGORY[ClassData$CATEGORY == "other"] <- "OTHER"
#make special->SPECIAL to match with CHO
ClassData$CATEGORY[ClassData$CATEGORY == "special"] <- "SPECIAL"
# Convert to factor and drop levels
ClassData$TITLE<-as.factor(ClassData$TITLE)
ClassData$TITLE<-droplevels(ClassData$TITLE)
ClassData$CATEGORY<-as.factor(ClassData$CATEGORY)
ClassData$CATEGORY<-droplevels(ClassData$CATEGORY)
# levels(ClassData$CATEGORY)
# levels(ClassData$TITLE)
# Make Gender Consistent
ClassData$GENDER[ClassData$GENDER == "female"] <- "F"
ClassData$GENDER[ClassData$GENDER == "male"] <- "M"
ClassData$GENDER[ClassData$GENDER == "U"] <- NA
ClassData$GENDER[ClassData$GENDER == "Unkown"] <- NA
ClassData$GENDER[ClassData$GENDER == "Unknown"] <- NA
ClassData$GENDER[ClassData$GENDER == ""] <- NA
ClassData$GENDER<-droplevels(ClassData$GENDER)
# Correct some of the countries
ClassData$COUNTRY[ClassData$COUNTRY == "Austrailia"] <- "Australia" #removing old names
ClassData$COUNTRY[ClassData$COUNTRY == "US"] <- "USA" #removing old names
# Adding combinations of names to the database
# First Name, Last Name
ClassData$FirstLast<-paste(ClassData$FIRST_NAME,ClassData$LAST_NAME, sep=" ")
# First Name, Middle Name, Last Name
ClassData$FirstMiddleLast<-paste(ClassData$FIRST_NAME,ClassData$MIDDLE_NAME,ClassData$LAST_NAME, sep=" ")
# First initial 1st name + last name":
ClassData$FIRST_INIT<-as.character(ClassData$FIRST_NAME)
ClassData$FIRST_INIT<-substring(ClassData$FIRST_INIT,1,1)
ClassData$FirstInitialLast<-paste(ClassData$FIRST_INIT,ClassData$LAST_NAME, sep=" ")
ClassData$FIRST_INIT<-NULL #delete it out now that we don't need it
#Delete column with suffix
ClassData$SUFFIX<-NULL #delete it out now that we don't need it
# Remove the periods from peoples names to make consistent accross all files
ClassData$FirstLast<-gsub(" ", " ", ClassData$FirstLast)
ClassData$FirstMiddleLast<-gsub(" ", " ", ClassData$FirstMiddleLast)
ClassData$FirstInitialLast<-gsub(" ", " ", ClassData$FirstInitialLast)
#
ClassData_clean<-ClassData
return(ClassData_clean)
}