Display Arabic text as separate characters (instead of cursive script) using CSS - css

To display license plates in Arabic, I wish to have each letter displayed without joining adjacent characters.
Is it possible to display Arabic text as separate characters, without the cursive script?


There are unique isolated Arabic UTF-8 characters just for this type of purpose.
It's all explained in this Wikipedia page.
(sorry, it pasted in as a bit of a mess)
A demonstration for the basic alphabet used in Modern Standard Arabic:
General
Unicode Contextual forms Name
Isolated End Middle Beginning
0623
أ‎ FE83
أ‎ FE84
ـأ‎ ʾalif
0628
ب‎ FE8F
ﺏ‎ FE90
ـب‎ FE92
ـبـ‎ FE91
بـ‎ bāʾ
062A
ت‎ FE95
ﺕ‎ FE96
ـت‎ FE98
ـتـ‎ FE97
تـ‎ tāʾ
062B
ث‎ FE99
ﺙ‎ FE9A
ـث‎ FE9C
ـثـ‎ FE9B
ثـ‎ ṯāʾ
062C
ج‎ FE9D
ﺝ‎ FE9E
ـج‎ FEA0
ـجـ‎ FE9F
جـ‎ ǧīm
062D
ح‎ FEA1
ﺡ‎ FEA2
ـح‎ FEA4
ـحـ‎ FEA3
حـ‎ ḥāʾ
062E
خ‎ FEA5
ﺥ‎ FEA6
ـخ‎ FEA8
ـخـ‎ FEA7
خـ‎ ḫāʾ
062F
د‎ FEA9
ﺩ‎ FEAA
ـد‎ dāl
0630
ذ‎ FEAB
ﺫ‎ FEAC
ـذ‎ ḏāl
0631
ر‎ FEAD
ﺭ‎ FEAE
ـر‎ rāʾ
0632
ز‎ FEAF
ﺯ‎ FEB0
ـز‎ zayn/zāy
0633
س‎ FEB1
ﺱ‎ FEB2
ـس‎ FEB4
ـسـ‎ FEB3
سـ‎ sīn
0634
ش‎ FEB5
ﺵ‎ FEB6
ـش‎ FEB8
ـشـ‎ FEB7
شـ‎ šīn
0635
ص‎ FEB9
ﺹ‎ FEBA
ـص‎ FEBC
ـصـ‎ FEBB
صـ‎ ṣād
0636
ض‎ FEBD
ﺽ‎ FEBE
ـض‎ FEC0
ـضـ‎ FEBF
ضـ‎ ḍād
0637
ط‎ FEC1
ﻁ‎ FEC2
ـط‎ FEC4
ـطـ‎ FEC3
طـ‎ ṭāʾ
0638
ظ‎ FEC5
ﻅ‎ FEC6
ـظ‎ FEC8
ـظـ‎ FEC7
ظـ‎ ẓāʾ
0639
ع‎ FEC9
ﻉ‎ FECA
ـع‎ FECC
ـعـ‎ FECB
عـ‎ ʿayn
063A
غ‎ FECD
ﻍ‎ FECE
ـغ‎ FED0
ـغـ‎ FECF
غـ‎ ġayn
0641
ف‎ FED1
ف‎ FED2
ـف‎ FED4
ـفـ‎ FED3
فـ‎ fāʾ
0642
ق‎ FED5
ﻕ‎ FED6
ـق‎ FED8
ـقـ‎ FED7
قـ‎ qāf
0643
ك‎ FED9
ﻙ‎ FEDA
ـك‎ FEDC
ـكـ‎ FEDB
كـ‎ kāf
0644
ل‎ FEDD
ﻝ‎ FEDE
ـل‎ FEE0
ـلـ‎ FEDF
لـ‎ lām
0645
م‎ FEE1
ﻡ‎ FEE2
ـم‎ FEE4
ـمـ‎ FEE3
مـ‎ mīm
0646
ن‎ FEE5
ن‎ FEE6
ـن‎ FEE8
ـنـ‎ FEE7
نـ‎ nūn
0647
ﻫ‎ FEE9
ﻩ‎ FEEA
ـه‎ FEEC
ـهـ‎ FEEB
هـ‎ hāʾ
0648
و‎ FEED
ﻭ‎ FEEE
ـو‎ wāw
064A
ي‎ FEF1
ﻱ‎ FEF2
ـي‎ FEF4
ـيـ‎ FEF3
يـ‎ yāʾ
0622
آ‎ FE81
ﺁ‎ FE82
ـآ‎ ʾalif maddah
0629
ة‎ FE93
ﺓ‎ FE94
ـة‎ — — Tāʾ marbūṭah
0649
ى‎ FEEF
ﻯ‎ FEF0
ـى‎ — — ʾalif maqṣūrah
[edit]

Related

Incomplete Expression in R

I'm currently running a time series script in R-Markdown where I pass the values of Percent Use and another vector of the time values. I am processing the two separate vectors with the regular c() function within r. The percentage vector is able to be passed through when compilining like normal, however I am running into trouble with the date/time vector. The length of both vectors are 749, the percentage vector just has values 0-100 passed within them. THe date/time vector has strings passed into them as such:
dt=c('2022-06-19 14:05:00.0','2022-06-19 14:06:00.0', ....
If I only pass a few arguments into the dt vector, it will compile regularly, however, once I increase the size to around half of what it needs to be I start getting the following error:
Error: Incomplete expression: dt=c('2022-06-19 12:40:00.0','2022-06-19 12:41:00.0','2022-06-19 12:42:00.0','2022-06-19 12:43:00.0','2022-06-19 12:44:00.0','2022-06-19 12:45:00.0','2022-06-19 12:46:00.0','2022-06-19 12:47:00.0','2022-06-19 12:48:00.0','2022-06-19 12:49:00.0','2022-06-19 12:50:00.0','2022-06-19 12:51:00.0','2022-06-19 12:52:00.0','2022-06-19 12:53:00.0','2022-06-19 12:54:00.0','2022-06-19 12:55:00.0','2022-06-19 12:56:00.0','2022-06-19 12:57:00.0','2022-06-19 12:58:00.0','2022-06-19 12:59:00.0','2022-06-19 13:00:00.0','2022-06-19 13:01:00.0','2022-06-19 13:02:00.0','2022-06-19 13:03:00.0','2022-06-19 13:04:00.0','2022-06-19 13:05:00.0','2022-06-19 13:06:00.0','2022-06-19 13:07:00.0','2022-06-19 13:08:00.0','2022-06-19 13:09:00.0','2022-06-19 13:10:00.0','2022-06-19 13:11:00.0','2022-06-19 13:12:00.0','2022-06-19 13:13:00.0','2022-06-19 13:14:00.0','2022-06-19 13:15:00.0','2022-06-19 13:16:00.0','2022-06-19 13:17:00.0','2022-06-19 13:18:00.0','2022-06-19 13:19:00.0','2022
At first I believed it could be a parenthesis in the wrong place, however, there is no mistakes with that. I've looked at other articles with somewhat similar issues and have seen a concept of a maximum size vector allowed, however the percentage vector was able to pass all 700. Is there a way to bypass this error, I feel that it is a memory/storage issue with R.
The full code is a lot but it is:
dt=c('2022-06-19 12:40:00.0','2022-06-19 12:41:00.0','2022-06-19 12:42:00.0','2022-06-19 12:43:00.0','2022-06-19 12:44:00.0','2022-06-19 12:45:00.0','2022-06-19 12:46:00.0','2022-06-19 12:47:00.0','2022-06-19 12:48:00.0','2022-06-19 12:49:00.0','2022-06-19 12:50:00.0','2022-06-19 12:51:00.0','2022-06-19 12:52:00.0','2022-06-19 12:53:00.0','2022-06-19 12:54:00.0','2022-06-19 12:55:00.0','2022-06-19 12:56:00.0','2022-06-19 12:57:00.0','2022-06-19 12:58:00.0','2022-06-19 12:59:00.0','2022-06-19 13:00:00.0','2022-06-19 13:01:00.0','2022-06-19 13:02:00.0','2022-06-19 13:03:00.0','2022-06-19 13:04:00.0','2022-06-19 13:05:00.0','2022-06-19 13:06:00.0','2022-06-19 13:07:00.0','2022-06-19 13:08:00.0','2022-06-19 13:09:00.0','2022-06-19 13:10:00.0','2022-06-19 13:11:00.0','2022-06-19 13:12:00.0','2022-06-19 13:13:00.0','2022-06-19 13:14:00.0','2022-06-19 13:15:00.0','2022-06-19 13:16:00.0','2022-06-19 13:17:00.0','2022-06-19 13:18:00.0','2022-06-19 13:19:00.0','2022-06-19 13:20:00.0','2022-06-19 13:21:00.0','2022-06-19 13:22:00.0','2022-06-19 13:23:00.0','2022-06-19 13:24:00.0','2022-06-19 13:25:00.0','2022-06-19 13:26:00.0','2022-06-19 13:27:00.0','2022-06-19 13:28:00.0','2022-06-19 13:29:00.0','2022-06-19 13:30:00.0','2022-06-19 13:31:00.0','2022-06-19 13:32:00.0','2022-06-19 13:33:00.0','2022-06-19 13:34:00.0','2022-06-19 13:35:00.0','2022-06-19 13:36:00.0','2022-06-19 13:37:00.0','2022-06-19 13:38:00.0','2022-06-19 13:39:00.0','2022-06-19 13:40:00.0','2022-06-19 13:41:00.0','2022-06-19 13:42:00.0','2022-06-19 13:43:00.0','2022-06-19 13:44:00.0','2022-06-19 13:45:00.0','2022-06-19 13:46:00.0','2022-06-19 13:47:00.0','2022-06-19 13:48:00.0','2022-06-19 13:49:00.0','2022-06-19 13:50:00.0','2022-06-19 13:51:00.0','2022-06-19 13:52:00.0','2022-06-19 13:53:00.0','2022-06-19 13:54:00.0','2022-06-19 13:55:00.0','2022-06-19 13:56:00.0','2022-06-19 13:57:00.0','2022-06-19 13:58:00.0','2022-06-19 13:59:00.0','2022-06-19 14:00:00.0','2022-06-19 14:01:00.0','2022-06-19 14:02:00.0','2022-06-19 14:03:00.0','2022-06-19 14:04:00.0','2022-06-19 14:05:00.0','2022-06-19 14:06:00.0','2022-06-19 14:07:00.0','2022-06-19 14:08:00.0','2022-06-19 14:09:00.0','2022-06-19 14:10:00.0','2022-06-19 14:11:00.0','2022-06-19 14:12:00.0','2022-06-19 14:13:00.0','2022-06-19 14:14:00.0','2022-06-19 14:15:00.0','2022-06-19 14:16:00.0','2022-06-19 14:17:00.0','2022-06-19 14:18:00.0','2022-06-19 14:19:00.0','2022-06-19 14:20:00.0','2022-06-19 14:21:00.0','2022-06-19 14:22:00.0','2022-06-19 14:23:00.0','2022-06-19 14:24:00.0','2022-06-19 14:25:00.0','2022-06-19 14:26:00.0','2022-06-19 14:27:00.0','2022-06-19 14:28:00.0','2022-06-19 14:29:00.0','2022-06-19 14:30:00.0','2022-06-19 14:31:00.0','2022-06-19 14:32:00.0','2022-06-19 14:33:00.0','2022-06-19 14:34:00.0','2022-06-19 14:35:00.0','2022-06-19 14:36:00.0','2022-06-19 14:37:00.0','2022-06-19 14:38:00.0','2022-06-19 14:39:00.0','2022-06-19 14:40:00.0','2022-06-19 14:41:00.0','2022-06-19 14:42:00.0','2022-06-19 14:43:00.0','2022-06-19 14:44:00.0','2022-06-19 14:45:00.0','2022-06-19 14:46:00.0','2022-06-19 14:47:00.0','2022-06-19 14:48:00.0','2022-06-19 14:49:00.0','2022-06-19 14:50:00.0','2022-06-19 14:51:00.0','2022-06-19 14:52:00.0','2022-06-19 14:53:00.0','2022-06-19 14:54:00.0','2022-06-19 14:55:00.0','2022-06-19 14:56:00.0','2022-06-19 14:57:00.0','2022-06-19 14:58:00.0','2022-06-19 14:59:00.0','2022-06-19 15:00:00.0','2022-06-19 15:01:00.0','2022-06-19 15:02:00.0','2022-06-19 15:03:00.0','2022-06-19 15:04:00.0','2022-06-19 15:05:00.0','2022-06-19 15:06:00.0','2022-06-19 15:07:00.0','2022-06-19 15:08:00.0','2022-06-19 15:09:00.0','2022-06-19 15:10:00.0','2022-06-19 15:11:00.0','2022-06-19 15:12:00.0','2022-06-19 15:13:00.0','2022-06-19 15:14:00.0','2022-06-19 15:15:00.0','2022-06-19 15:16:00.0','2022-06-19 15:17:00.0','2022-06-19 15:18:00.0','2022-06-19 15:19:00.0','2022-06-19 15:20:00.0','2022-06-19 15:21:00.0','2022-06-19 15:22:00.0','2022-06-19 15:23:00.0','2022-06-19 15:24:00.0','2022-06-19 15:25:00.0','2022-06-19 15:26:00.0','2022-06-19 15:27:00.0','2022-06-19 15:28:00.0','2022-06-19 15:29:00.0','2022-06-19 15:30:00.0','2022-06-19 15:31:00.0','2022-06-19 15:32:00.0','2022-06-19 15:33:00.0','2022-06-19 15:34:00.0','2022-06-19 15:35:00.0','2022-06-19 15:36:00.0','2022-06-19 15:37:00.0','2022-06-19 15:38:00.0','2022-06-19 15:39:00.0','2022-06-19 15:40:00.0','2022-06-19 15:41:00.0','2022-06-19 15:42:00.0','2022-06-19 15:43:00.0','2022-06-19 15:44:00.0','2022-06-19 15:45:00.0','2022-06-19 15:46:00.0','2022-06-19 15:47:00.0','2022-06-19 15:48:00.0','2022-06-19 15:49:00.0','2022-06-19 15:50:00.0','2022-06-19 15:51:00.0','2022-06-19 15:52:00.0','2022-06-19 15:53:00.0','2022-06-19 15:54:00.0','2022-06-19 15:55:00.0','2022-06-19 15:56:00.0','2022-06-19 15:57:00.0','2022-06-19 15:58:00.0','2022-06-19 15:59:00.0','2022-06-19 16:00:00.0','2022-06-19 16:01:00.0','2022-06-19 16:02:00.0','2022-06-19 16:03:00.0','2022-06-19 16:04:00.0','2022-06-19 16:05:00.0','2022-06-19 16:06:00.0','2022-06-19 16:07:00.0','2022-06-19 16:08:00.0','2022-06-19 16:09:00.0','2022-06-19 16:10:00.0','2022-06-19 16:11:00.0','2022-06-19 16:12:00.0','2022-06-19 16:13:00.0','2022-06-19 16:14:00.0','2022-06-19 16:15:00.0','2022-06-19 16:16:00.0','2022-06-19 16:17:00.0','2022-06-19 16:18:00.0','2022-06-19 16:19:00.0','2022-06-19 16:20:00.0','2022-06-19 16:21:00.0','2022-06-19 16:22:00.0','2022-06-19 16:23:00.0','2022-06-19 16:24:00.0','2022-06-19 16:25:00.0','2022-06-19 16:26:00.0','2022-06-19 16:27:00.0','2022-06-19 16:28:00.0','2022-06-19 16:29:00.0','2022-06-19 16:30:00.0','2022-06-19 16:31:00.0','2022-06-19 16:32:00.0','2022-06-19 16:33:00.0','2022-06-19 16:34:00.0','2022-06-19 16:35:00.0','2022-06-19 16:36:00.0','2022-06-19 16:37:00.0','2022-06-19 16:38:00.0','2022-06-19 16:39:00.0','2022-06-19 16:40:00.0','2022-06-19 16:41:00.0','2022-06-19 16:42:00.0','2022-06-19 16:43:00.0','2022-06-19 16:44:00.0','2022-06-19 16:45:00.0','2022-06-19 16:46:00.0','2022-06-19 16:47:00.0','2022-06-19 16:48:00.0','2022-06-19 16:49:00.0','2022-06-19 16:50:00.0','2022-06-19 16:51:00.0','2022-06-19 16:52:00.0','2022-06-19 16:53:00.0','2022-06-19 16:54:00.0','2022-06-19 16:55:00.0','2022-06-19 16:56:00.0','2022-06-19 16:57:00.0','2022-06-19 16:58:00.0','2022-06-19 16:59:00.0','2022-06-19 17:00:00.0','2022-06-19 17:01:00.0','2022-06-19 17:02:00.0','2022-06-19 17:03:00.0','2022-06-19 17:04:00.0','2022-06-19 17:05:00.0','2022-06-19 17:06:00.0','2022-06-19 17:07:00.0','2022-06-19 17:08:00.0','2022-06-19 17:09:00.0','2022-06-19 17:10:00.0','2022-06-19 17:11:00.0','2022-06-19 17:12:00.0','2022-06-19 17:13:00.0','2022-06-19 17:14:00.0','2022-06-19 17:15:00.0','2022-06-19 17:16:00.0','2022-06-19 17:17:00.0','2022-06-19 17:18:00.0','2022-06-19 17:19:00.0','2022-06-19 17:20:00.0','2022-06-19 17:21:00.0','2022-06-19 17:22:00.0','2022-06-19 17:23:00.0','2022-06-19 17:24:00.0','2022-06-19 17:25:00.0','2022-06-19 17:26:00.0','2022-06-19 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18:08:00.0','2022-06-19 18:09:00.0','2022-06-19 18:10:00.0','2022-06-19 18:11:00.0','2022-06-19 18:12:00.0','2022-06-19 18:13:00.0','2022-06-19 18:14:00.0','2022-06-19 18:15:00.0','2022-06-19 18:16:00.0','2022-06-19 18:17:00.0','2022-06-19 18:18:00.0','2022-06-19 18:19:00.0','2022-06-19 18:20:00.0','2022-06-19 18:21:00.0','2022-06-19 18:22:00.0','2022-06-19 18:23:00.0','2022-06-19 18:24:00.0','2022-06-19 18:25:00.0','2022-06-19 18:26:00.0','2022-06-19 18:27:00.0','2022-06-19 18:28:00.0','2022-06-19 18:29:00.0','2022-06-19 18:30:00.0','2022-06-19 18:31:00.0','2022-06-19 18:32:00.0','2022-06-19 18:33:00.0','2022-06-19 18:34:00.0','2022-06-19 18:35:00.0','2022-06-19 18:36:00.0','2022-06-19 18:37:00.0','2022-06-19 18:38:00.0','2022-06-19 18:39:00.0','2022-06-19 18:40:00.0','2022-06-19 18:41:00.0','2022-06-19 18:42:00.0','2022-06-19 18:43:00.0','2022-06-19 18:44:00.0','2022-06-19 18:45:00.0','2022-06-19 18:46:00.0','2022-06-19 18:47:00.0','2022-06-19 18:48:00.0','2022-06-19 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22:14:00.0','2022-06-19 22:15:00.0','2022-06-19 22:16:00.0','2022-06-19 22:17:00.0','2022-06-19 22:18:00.0','2022-06-19 22:19:00.0','2022-06-19 22:20:00.0','2022-06-19 22:21:00.0','2022-06-19 22:22:00.0','2022-06-19 22:23:00.0','2022-06-19 22:24:00.0','2022-06-19 22:25:00.0','2022-06-19 22:26:00.0','2022-06-19 22:27:00.0','2022-06-19 22:28:00.0','2022-06-19 22:29:00.0','2022-06-19 22:30:00.0','2022-06-19 22:31:00.0','2022-06-19 22:32:00.0','2022-06-19 22:33:00.0','2022-06-19 22:34:00.0','2022-06-19 22:35:00.0','2022-06-19 22:36:00.0','2022-06-19 22:37:00.0','2022-06-19 22:38:00.0','2022-06-19 22:39:00.0','2022-06-19 22:40:00.0','2022-06-19 22:41:00.0','2022-06-19 22:42:00.0','2022-06-19 22:43:00.0','2022-06-19 22:44:00.0','2022-06-19 22:45:00.0','2022-06-19 22:46:00.0','2022-06-19 22:47:00.0','2022-06-19 22:48:00.0','2022-06-19 22:49:00.0','2022-06-19 22:50:00.0','2022-06-19 22:51:00.0','2022-06-19 22:52:00.0','2022-06-19 22:53:00.0','2022-06-19 22:54:00.0','2022-06-19 22:55:00.0','2022-06-19 22:56:00.0','2022-06-19 22:57:00.0','2022-06-19 22:58:00.0','2022-06-19 22:59:00.0','2022-06-19 23:00:00.0','2022-06-19 23:01:00.0','2022-06-19 23:02:00.0','2022-06-19 23:03:00.0','2022-06-19 23:04:00.0','2022-06-19 23:05:00.0','2022-06-19 23:06:00.0','2022-06-19 23:07:00.0','2022-06-19 23:08:00.0','2022-06-19 23:09:00.0','2022-06-19 23:10:00.0','2022-06-19 23:11:00.0','2022-06-19 23:12:00.0','2022-06-19 23:13:00.0','2022-06-19 23:14:00.0','2022-06-19 23:15:00.0','2022-06-19 23:16:00.0','2022-06-19 23:17:00.0','2022-06-19 23:18:00.0','2022-06-19 23:19:00.0','2022-06-19 23:20:00.0','2022-06-19 23:21:00.0','2022-06-19 23:22:00.0','2022-06-19 23:23:00.')
I can understand saying there is a issue with the quotations, but I cant find it anywhere. It seems as there is a maximum allowed in a vector, if I compile only the first quarter of the entries it works, else wise on R studio it gives an error, and in the terminal it just expects more code so it gives you a + to add more instead of >.

Best way to import words from a text file into a data frame in R

I have a text file filled with words separated by spaces as seen below:
ACNES ACOCK ACOLD ACORN ACRED ACRES ACRID ACTED ACTIN ACTON ACTOR ACUTE ACYLS ADAGE ADAPT ADAWS ADAYS ADDAX ADDED ADDER ADDIO ADDLE ADEEM ADEPT ADHAN ADIEU ADIOS ADITS ADMAN ADMEN ADMIN ADMIT ADMIX ADOBE ADOBO ADOPT ADORE ADORN ADOWN ADOZE ADRAD ADRED ADSUM ADUKI ADULT ADUNC ADUST ADVEW ADYTA ADZED ADZES AECIA AEDES AEGIS AEONS AERIE AEROS AESIR AFALD AFARA AFARS AFEAR AFFIX AFIRE AFLAJ AFOOT AFORE AFOUL AFRIT AFROS AFTER AGAIN AGAMA AGAMI AGAPE AGARS AGAST AGATE AGAVE AGAZE AGENE AGENT AGERS AGGER AGGIE AGGRI AGGRO AGGRY AGHAS AGILA AGILE AGING AGIOS AGISM AGIST AGITA AGLEE AGLET AGLEY AGLOO AGLOW AGLUS AGMAS AGOGE AGONE AGONS AGONY AGOOD AGORA AGREE AGRIA AGRIN
What's the best way to import all these words into a 1 column data frame?

RStudio truncates long strings when pasting into IDE - workaround?

I'm using R 3.6.1 and RStudio 1.3.1056.
When pasting a long character string into RStudio using either paste() or paste0() or even c() or just simply assigning the string to an object, I get some strange results, and it looks to be unique to RStudio (if you place this code directly into R it works just fine; the correct value is given for nchar()):
thing <- paste0("(blah blah
'100869017', '100895297', '100937037', '100952542', '100953872', '100958290', '100977291', '100978521', '100982570', '100983764', '100986439', '100987969', '100988635', '100988637', '100989748', '100992594', '100998300', '100998306', '101000068', '101000556', '101002036', '101002550', '101002813', '101002871', '101002872', '101003492', '101003787', '101003789', '101003830', '101004348', '101004349', '101004400', '101004401', '101005323', '101005738', '101006388', '101006411', '101006413', '101006414', '101006416', '101006417', '101006419', '101006440', '101006441', '101006442', '101006443', '101006444', '101006445', '101006446', '101006447', '101006448', '101006449', '101006450', '101006451', '101006452', '101006453', '101006454', '101006455', '101006456', '101006457', '101006458', '101006554', '101006588', '101006608', '101008736', '101009658', '101011518', '101011680', '101011681', '101012457', '101012495', '101014157', '101014197', '101014240', '101014244', '101014248', '101014301', '101014302', '101014303', '101014304', '101014358', '101014480', '101014481', '101015219', '101017560', '101019383', '101019396', '101019454', '101019480', '101019481', '101019567', '101020977', '101022585', '101024007', '101024436', '101028376', '101028377', '101028405', '101029814', '101030739', '101030940', '101031364', '101031368', '101032356', '101032399', '101032440', '101032441', '101032442', '101032443', '101032444', '101032462', '101032468', '101032482', '101032483', '101032484', '101032485', '101032486', '101032487', '101032488', '101032489', '101032590', '101032591', '101032735', '101032987', '101033456', '101036227', '101037275', '101038196', '101038279', '101038930', '101038932', '101038938', '101039576', '101041116', '101041233', '101041288', '101042815', '101043166', '101043280', '101043281', '101043282', '101043285', '101043288', '101043307', '101043302', '101043329', '101043405', '101043837', '101045392', '101045635', '101046419', '101046440', '101046441', '101047082', '101047224', '101047227', '101047275', '101047281', '101047286', '101047287', '101047288', '101047290', '101047293', '101047295', '101047297', '101047304', '101048355', '101048439', '101048480', '101048905', '101048921', '101050905', '101052305', '101052442', '101052448', '101052449', '101052480', '101052481', '101052485', '101052487', '101052489', '101052522', '101052550', '101052551', '101053187', '101055017', '101055036', '101055039', '101055220', '101055258', '101055313', '101055316', '101055317', '101059567', '101060256', '101060554', '101060810', '101060817', '101061738', '101061739', '101061762', '101062369', '101062469', '101063528', '101063909', '101065440', '101065471', '101065473', '101065536', '101065760', '101065784', '101065805', '101065813', '101068343', '101068346', '101069329', '101069472', '101069478', '101069771', '101069871', '101069902', '101070895', '101071301', '101071303', '101072911', '101072914', '101072915', '101072944', '101072946', '101072949', '101072972', '101072981', '101072984', '101072985', '101073389', '101073806', '101074467', '101074469', '101074650', '101074709', '101074721', '101074869', '101075639', '101075881', '101075887', '101075888', '101076841', '101076843', '101076884', '101076885', '101076889', '101076930', '101077036', '101077872', '101077877', '101078006', '101078141', '101078834', '101079626', '101079624', '101079658', '101080128', '101080146', '101080341', '101080389', '101080732', '101080738', '101080931', '101081744', '101081745', '101082123', '101082443', '101082445', '101082447', '101085919', '101086763', '101086774', '101086801', '101086915', '101086964', '101086965', '101087006', '101088057', '101088465', '101089884', '101089915', '101089945', '101090159', '101090197', '101090225', '101090226', '101090227', '101090229', '101090293', '101091218', '101091232', '101091238', '101091239', '101091635', '101091655', '101092773', '101092997', '101093029', '101093064', '101093067', '101093255', '101093344', '101097283', '101097668', '101098444', '101098514', '101099068', '101099073', '101099076', '101099141', '101099170', '101099172', '101099173', '101099175', '101099177', '101099178', '101099194', '101099204', '101099206', '101099581', '101099666', '101100002', '101100179', '101100492', '101100617', '101101080', '101101088', '101101091', '101101092', '101101115', '101101117', '101101150', '101101158', '101102050', '101102086', '101102101', '101102108', '101102169', '101102650', '101102712', '101103376', '101106299', '101106618', '101107257', '101107277', '101108114', '101108119', '101108670', '101108702', '101108707', '101109772', '101109774', '101109779', '101111022', '101111029', '101113873', '101114376', '101114390', '101115163', '101115246', '101115247', '101115357', '101115358', '101116813', '101116819', '101116870', '101116877', '101118108', '101118175', '101118178', '101118277', '101118441', '101118449', '101118471', '101118505', '101118631', '101119051', '101119448', '101119914', '101120073', '101120076', '101120127', '101120292', '101120334', '101120387', '101120389', '101122367', '101122822', '101122881', '101122886', '101124670', '101124838', '101125490', '101125610', '101126329', '101127340', '101127341', '101127342', '101127343', '101127346', '101127347', '101127360', '101127853', '101127855', '101127856', '101127857', '101128128', '101128126', '101128132', '101128135', '101130135', '101131523', '101132622', '101132648', '101132850', '101132870', '101132931', '101132938', '101132990', '101132994', '101133104', '101133206', '101133248', '101134597', '101134599', '101134611', '101134649', '101134661', '101134704', '101134771', '101135221', '101135276', '101135278', '101135409', '101135444', '101135518', '101135630', '101135633', '101135632', '101137571', '101137750', '101137812', '101137875', '101138237', '101139907', '101139931', '101139968', '101140076', '101140148', '101140181', '101140250', '101140253', '101140460', '101140462', '101140466', '101140469', '101140518', '101150986', '101150987', '101150990', '101150994', '101150995', '101151373', '101151376', '101151416', '101151418', '101151419', '101151434', '101151437', '101151891', '101151974', '101151978', '101151979', '101151996', '101152030', '101152031', '101152032', '101152037', '101152062', '101152063', '101152066', '101152068', '101152069', '101152070', '101152072', '101152073', '101152074', '101152077', '101152078', '101152080', '101152081', '101152083', '101152085', '101152087', '101152088', '101152089', '101152100', '101152103', '101152105', '101153684', '101153944', '101153966', '101153996', '101153999', '101155013', '101155141', '101155149', '101155311', '101155560', '101155880', '101155882', '101155883', '101155884', '101155905', '101156458', '101156459', '101156511', '101156524', '101156546', '101156547', '101156596', '101156611', '101156641', '101156664', '101156752', '101156786', '101156801', '101156842', '101156885', '101156888', '101156892', '101157753', '101157844', '101157881', '101157905', '101157927', '101158001', '101158011', '101158025', '101158028', '101158034', '101158061', '101158081', '101158084', '101158103', '101158107', '101159736', '101160183', '101160203', '101160234', '101160373', '101160377', '101160381', '101160378', '101160451', '101160551', '101162202', '101162245', '101162247', '101162249', '101162492', '101162538', '101162585', '101162595', '101162627', '101162630', '101162634', '101162792', '101162848', '101162876', '101162904', '101164138', '101164337', '101165132', '101165133', '101165134'
blah blah)")
nchar(thing)
The output of nchar() is 4130. In reality, nchar() should be showing 7603.
Why would I do something like this in a script? In this case, it was a SQL query written into a script and being run via RStudio.
Even stranger is removing the "blah blah" at the top and bottom of the string:
thing <- paste0("'100869017', '100895297', '100937037', '100952542', '100953872', '100958290', '100977291', '100978521', '100982570', '100983764', '100986439', '100987969', '100988635', '100988637', '100989748', '100992594', '100998300', '100998306', '101000068', '101000556', '101002036', '101002550', '101002813', '101002871', '101002872', '101003492', '101003787', '101003789', '101003830', '101004348', '101004349', '101004400', '101004401', '101005323', '101005738', '101006388', '101006411', '101006413', '101006414', '101006416', '101006417', '101006419', '101006440', '101006441', '101006442', '101006443', '101006444', '101006445', '101006446', '101006447', '101006448', '101006449', '101006450', '101006451', '101006452', '101006453', '101006454', '101006455', '101006456', '101006457', '101006458', '101006554', '101006588', '101006608', '101008736', '101009658', '101011518', '101011680', '101011681', '101012457', '101012495', '101014157', '101014197', '101014240', '101014244', '101014248', '101014301', '101014302', '101014303', '101014304', '101014358', '101014480', '101014481', '101015219', '101017560', '101019383', '101019396', '101019454', '101019480', '101019481', '101019567', '101020977', '101022585', '101024007', '101024436', '101028376', '101028377', '101028405', '101029814', '101030739', '101030940', '101031364', '101031368', '101032356', '101032399', '101032440', '101032441', '101032442', '101032443', '101032444', '101032462', '101032468', '101032482', '101032483', '101032484', '101032485', '101032486', '101032487', '101032488', '101032489', '101032590', '101032591', '101032735', '101032987', '101033456', '101036227', '101037275', '101038196', '101038279', '101038930', '101038932', '101038938', '101039576', '101041116', '101041233', '101041288', '101042815', '101043166', '101043280', '101043281', '101043282', '101043285', '101043288', '101043307', '101043302', '101043329', '101043405', '101043837', '101045392', '101045635', '101046419', '101046440', '101046441', '101047082', '101047224', '101047227', '101047275', '101047281', '101047286', '101047287', '101047288', '101047290', '101047293', '101047295', '101047297', '101047304', '101048355', '101048439', '101048480', '101048905', '101048921', '101050905', '101052305', '101052442', '101052448', '101052449', '101052480', '101052481', '101052485', '101052487', '101052489', '101052522', '101052550', '101052551', '101053187', '101055017', '101055036', '101055039', '101055220', '101055258', '101055313', '101055316', '101055317', '101059567', '101060256', '101060554', '101060810', '101060817', '101061738', '101061739', '101061762', '101062369', '101062469', '101063528', '101063909', '101065440', '101065471', '101065473', '101065536', '101065760', '101065784', '101065805', '101065813', '101068343', '101068346', '101069329', '101069472', '101069478', '101069771', '101069871', '101069902', '101070895', '101071301', '101071303', '101072911', '101072914', '101072915', '101072944', '101072946', '101072949', '101072972', '101072981', '101072984', '101072985', '101073389', '101073806', '101074467', '101074469', '101074650', '101074709', '101074721', '101074869', '101075639', '101075881', '101075887', '101075888', '101076841', '101076843', '101076884', '101076885', '101076889', '101076930', '101077036', '101077872', '101077877', '101078006', '101078141', '101078834', '101079626', '101079624', '101079658', '101080128', '101080146', '101080341', '101080389', '101080732', '101080738', '101080931', '101081744', '101081745', '101082123', '101082443', '101082445', '101082447', '101085919', '101086763', '101086774', '101086801', '101086915', '101086964', '101086965', '101087006', '101088057', '101088465', '101089884', '101089915', '101089945', '101090159', '101090197', '101090225', '101090226', '101090227', '101090229', '101090293', '101091218', '101091232', '101091238', '101091239', '101091635', '101091655', '101092773', '101092997', '101093029', '101093064', '101093067', '101093255', '101093344', '101097283', '101097668', '101098444', '101098514', '101099068', '101099073', '101099076', '101099141', '101099170', '101099172', '101099173', '101099175', '101099177', '101099178', '101099194', '101099204', '101099206', '101099581', '101099666', '101100002', '101100179', '101100492', '101100617', '101101080', '101101088', '101101091', '101101092', '101101115', '101101117', '101101150', '101101158', '101102050', '101102086', '101102101', '101102108', '101102169', '101102650', '101102712', '101103376', '101106299', '101106618', '101107257', '101107277', '101108114', '101108119', '101108670', '101108702', '101108707', '101109772', '101109774', '101109779', '101111022', '101111029', '101113873', '101114376', '101114390', '101115163', '101115246', '101115247', '101115357', '101115358', '101116813', '101116819', '101116870', '101116877', '101118108', '101118175', '101118178', '101118277', '101118441', '101118449', '101118471', '101118505', '101118631', '101119051', '101119448', '101119914', '101120073', '101120076', '101120127', '101120292', '101120334', '101120387', '101120389', '101122367', '101122822', '101122881', '101122886', '101124670', '101124838', '101125490', '101125610', '101126329', '101127340', '101127341', '101127342', '101127343', '101127346', '101127347', '101127360', '101127853', '101127855', '101127856', '101127857', '101128128', '101128126', '101128132', '101128135', '101130135', '101131523', '101132622', '101132648', '101132850', '101132870', '101132931', '101132938', '101132990', '101132994', '101133104', '101133206', '101133248', '101134597', '101134599', '101134611', '101134649', '101134661', '101134704', '101134771', '101135221', '101135276', '101135278', '101135409', '101135444', '101135518', '101135630', '101135633', '101135632', '101137571', '101137750', '101137812', '101137875', '101138237', '101139907', '101139931', '101139968', '101140076', '101140148', '101140181', '101140250', '101140253', '101140460', '101140462', '101140466', '101140469', '101140518', '101150986', '101150987', '101150990', '101150994', '101150995', '101151373', '101151376', '101151416', '101151418', '101151419', '101151434', '101151437', '101151891', '101151974', '101151978', '101151979', '101151996', '101152030', '101152031', '101152032', '101152037', '101152062', '101152063', '101152066', '101152068', '101152069', '101152070', '101152072', '101152073', '101152074', '101152077', '101152078', '101152080', '101152081', '101152083', '101152085', '101152087', '101152088', '101152089', '101152100', '101152103', '101152105', '101153684', '101153944', '101153966', '101153996', '101153999', '101155013', '101155141', '101155149', '101155311', '101155560', '101155880', '101155882', '101155883', '101155884', '101155905', '101156458', '101156459', '101156511', '101156524', '101156546', '101156547', '101156596', '101156611', '101156641', '101156664', '101156752', '101156786', '101156801', '101156842', '101156885', '101156888', '101156892', '101157753', '101157844', '101157881', '101157905', '101157927', '101158001', '101158011', '101158025', '101158028', '101158034', '101158061', '101158081', '101158084', '101158103', '101158107', '101159736', '101160183', '101160203', '101160234', '101160373', '101160377', '101160381', '101160378', '101160451', '101160551', '101162202', '101162245', '101162247', '101162249', '101162492', '101162538', '101162585', '101162595', '101162627', '101162630', '101162634', '101162792', '101162848', '101162876', '101162904', '101164138', '101164337', '101165132', '101165133', '101165134'")
In this case the console hangs with the + as if awaiting further input.
Again, take those examples and put them directly into R and nchar() provides the correct count.
The worst part of this is that in the first example, the object is created but is truncated, and the final part of the string is retained, i.e. the ending "blah blah". This has resulted in SQL queries excluding some criteria - over 3400 characters worth of criteria!
If anyone was to say that this is an ugly way to write SQL queries, I'd agree. And I certainly wouldn't want a single string so long anywhere in my code, but there's a solid chance they could show up in a team environment where a user is less familiar with R and RStudio.
RStudio gives absolutely no indicator or warning that this is done as far as I can tell.
Is there any way to avoid this behavior besides splitting strings or sourcing SQL scripts or text files?

Unicode map from Font Awesome 4 to Font Awesome 5

I have several css files that contain hard-coded FA 4 Unicode values. Does there exist a map from FA 4 Unicode to FA 5 Unicode?

To create the map, I had to use three different tables:
https://fontawesome.com/v4.7.0/cheatsheet/
https://fontawesome.com/cheatsheet
https://fontawesome.com/how-to-use/on-the-web/setup/upgrading-from-version-4
With the help of some MySQL queries, I created the following map that relates the font awesome 4 name and Unicode value to its respective font awesome 5 name and Unicode value only if the Unicode values differ:
"fa4name","fa5name","fa4code","fa5code"
"fa-address-book-o","address-book","f2ba","f2b9"
"fa-address-card-o","address-card","f2bc ","f2bb"
"fa-arrow-circle-o-down","arrow-alt-circle-down","f01a","f358"
"fa-arrow-circle-o-left","arrow-alt-circle-left","f190","f359"
"fa-arrow-circle-o-right","arrow-alt-circle-right","f18e ","f35a"
"fa-arrow-circle-o-up","arrow-alt-circle-up","f01b ","f35b"
"fa-arrows","arrows-alt","f047 ","f0b2"
"fa-arrows-alt","expand-arrows-alt","f0b2 ","f31e"
"fa-arrows-h","arrows-alt-h","f07e ","f337"
"fa-arrows-v","arrows-alt-v","f07d","f338"
"fa-bell-o","bell","f0a2","f0f3"
"fa-bell-slash-o","bell-slash","f1f7","f1f6"
"fa-bookmark-o","bookmark","f097","f02e"
"fa-building-o","building","f0f7 ","f1ad"
"fa-check-circle-o","check-circle","f05d ","f058"
"fa-check-square-o","check-square","f046 ","f14a"
"fa-circle-o","circle","f10c","f111"
"fa-circle-thin","circle","f1db ","f111"
"fa-clipboard","clipboard","f0ea ","f328"
"fa-cloud-download","cloud-download-alt","f0ed ","f381"
"fa-cloud-upload","cloud-upload-alt","f0ee ","f382"
"fa-comment-o","comment","f0e5","f075"
"fa-commenting","comment-dots","f27a","f4ad"
"fa-commenting-o","comment-dots","f27b ","f4ad"
"fa-comments-o","comments","f0e6 ","f086"
"fa-credit-card-alt","credit-card","f283 ","f09d"
"fa-cutlery","utensils","f0f5 ","f2e7"
"fa-diamond","gem","f219","f3a5"
"fa-envelope-o","envelope","f003","f0e0"
"fa-envelope-open-o","envelope-open","f2b7","f2b6"
"fa-exchange","exchange-alt","f0ec ","f362"
"fa-external-link","external-link-alt","f08e ","f35d"
"fa-external-link-square","external-link-square-alt","f14c ","f360"
"fa-folder-o","folder","f114 ","f07b"
"fa-folder-open-o","folder-open","f115 ","f07c"
"fa-heart-o","heart","f08a","f004"
"fa-hourglass-o","hourglass","f250","f254"
"fa-id-card-o","id-card","f2c3","f2c2"
"fa-level-down","level-down-alt","f149 ","f3be"
"fa-level-up","level-up-alt","f148","f3bf"
"fa-long-arrow-down","long-arrow-alt-down","f175 ","f309"
"fa-long-arrow-left","long-arrow-alt-left","f177 ","f30a"
"fa-long-arrow-right","long-arrow-alt-right","f178 ","f30b"
"fa-long-arrow-up","long-arrow-alt-up","f176","f30c"
"fa-map-marker","map-marker-alt","f041","f3c5"
"fa-map-o","map","f278","f279"
"fa-minus-square-o","minus-square","f147","f146"
"fa-mobile","mobile-alt","f10b ","f3cd"
"fa-money","money-bill-alt","f0d6 ","f3d1"
"fa-paper-plane-o","paper-plane","f1d9 ","f1d8"
"fa-pause-circle-o","pause-circle","f28c","f28b"
"fa-pencil","pencil-alt","f040 ","f303"
"fa-play-circle-o","play-circle","f01d","f144"
"fa-plus-square-o","plus-square","f196","f0fe"
"fa-question-circle-o","question-circle","f29c","f059"
"fa-share-square-o","share-square","f045","f14d"
"fa-shield","shield-alt","f132","f3ed"
"fa-sign-in","sign-in-alt","f090","f2f6"
"fa-sign-out","sign-out-alt","f08b ","f2f5"
"fa-spoon","utensil-spoon","f1b1","f2e5"
"fa-square-o","square","f096","f0c8"
"fa-star-half-o","star-half","f123 ","f089"
"fa-star-o","star","f006","f005"
"fa-sticky-note-o","sticky-note","f24a ","f249"
"fa-stop-circle-o","stop-circle","f28e","f28d"
"fa-tablet","tablet-alt","f10a ","f3fa"
"fa-tachometer","tachometer-alt","f0e4 ","f3fd"
"fa-thumbs-o-down","thumbs-down","f088 ","f165"
"fa-thumbs-o-up","thumbs-up","f087 ","f164"
"fa-ticket","ticket-alt","f145 ","f3ff"
"fa-times-circle-o","times-circle","f05c","f057"
"fa-trash","trash-alt","f1f8 ","f2ed"
"fa-trash-o","trash-alt","f014","f2ed"
"fa-user-circle-o","user-circle","f2be ","f2bd"
"fa-user-o","user","f2c0","f007"
"fa-window-close-o","window-close","f2d4","f410"
"fa-calendar","calendar","f073","f133"
"fa-reply","reply","f112 ","f3e5"
"fa-window-close","window-close","f2d3","f410"
The first row has the column description.
Note that the table, upgrading-from-version-4, only lists changes in the name; it was necessary to also join on the two different cheat-sheets listed above where the names are the same, but the Unicode values differ.

How to separate unique characters from several words in a "indic" text file?

I've a plain text file.
> Input: इंजेक्शन इंटरनॅशनल इंटिग्रेटेड इंटिरिअर इंडस्ट्री
All words are separated by one or more spaces. I want to collect all unique chars from the text file. I'm looking for a unix command; the order of the result chars is not important.
> Expected result: इं जे क्श न ट र नॅ श ल इ्रे टे ड टि रिअ र ड स्ट्री
With the command Klaus has provided
cat <file>|sed -e 's/\(.\)/\1\n/g'|sort -u|tr -d '\n'
Result comes as:
ं अ इ क ग ज ट ड न र ल श सिीॅे्
I don't want to separate horizontal or vertical conjuncts or dependent vowels from its base character.
I just want to separate complete characters in a word from each other.
Can we achieve this with UNIX commands?
"base character" + "dependent vowel" = "complete character"
- क ा का
- क ि कि
Klaus's command works for English text only. But, It doesn't work with indic languages such as Hindi.
Input: hi1 hello-2 how!3 "are4 ?you5
result: h i e l o w a r y u 1 2 3 4 5 - ! "
Note:- You have to install Indic support in your OS.
Also, download Mangal font from http://hindi-fonts.com/fonts/Mangal

Try this:
cat <file>|sed -e 's/\(.\)/\1\n/g'|sort -u|tr -d '\n'
or simplified ( stolen from fedorqui comment, thanks! Never seen & before in the replacement part. Good to learn something new! )
sed 's/./&\n/g' <file> | sort -u | tr -d '\n'

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