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library(ggplot2)

Registered S3 method overwritten by 'dplyr':
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  print.rowwise_df     

library(dplyr)

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(tidyverse)

Registered S3 methods overwritten by 'dbplyr':
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  print.tbl_sql      
── Attaching packages ─────────────────────────────────────────────────────────────────────── tidyverse 1.3.0 ──
✓ tibble  3.0.0     ✓ stringr 1.4.0
✓ tidyr   1.0.2     ✓ forcats 0.5.0
✓ purrr   0.3.4     
── Conflicts ────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()

library(lubridate)

Attaching package: ‘lubridate’

The following objects are masked from ‘package:dplyr’:

    intersect, setdiff, union

The following objects are masked from ‘package:base’:

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library(ggplot2)
library(data.table)

Registered S3 method overwritten by 'data.table':
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data.table 1.12.8 using 2 threads (see ?getDTthreads).  Latest news: r-datatable.com

Attaching package: ‘data.table’

The following objects are masked from ‘package:lubridate’:

    hour, isoweek, mday, minute, month, quarter, second, wday, week, yday, year

The following object is masked from ‘package:purrr’:

    transpose

The following objects are masked from ‘package:dplyr’:

    between, first, last

library(ggrepel)
library(ggmap)

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Please cite ggmap if you use it! See citation("ggmap") for details.

library(wordcloud)

Loading required package: RColorBrewer

library(wordcloud2)

Registered S3 methods overwritten by 'htmltools':
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  print.html           tools:rstudio
  print.shiny.tag      tools:rstudio
  print.shiny.tag.list tools:rstudio
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  print.htmlwidget tools:rstudio

library(readr)

food_master_clean <- Food_Service_Establishment_Last_Inspection %>%
   summarize (COUNTY = n_distinct(COUNTY, na.rm = TRUE))
food_master_clean

food_master_clean <- Food_Service_Establishment_Last_Inspection %>%

    select(COUNTY, `TOTAL # CRITICAL VIOLATIONS`) %>%
    rename("VIOLATIONS" = `TOTAL # CRITICAL VIOLATIONS`) %>%
    group_by(COUNTY) %>%
    summarise(VIOLATIONS = sum(VIOLATIONS, na.rm=TRUE)) %>%
    arrange(desc(VIOLATIONS))

print.data.frame(food_master_clean)

        COUNTY VIOLATIONS
1     SARATOGA        369
2       NASSAU        351
3       WARREN        266
4  SCHENECTADY        239
5     ONONDAGA        235
6       OTSEGO        216
7      ONTARIO        211
8  ST LAWRENCE        197
9  WESTCHESTER        196
10       ESSEX        193
11      MONROE        191
12   JEFFERSON        175
13  RENSSELAER        170
14    DELAWARE        164
15    SULLIVAN        153
16  CHAUTAUQUA        136
17      GREENE        132
18     STEUBEN        121
19 CATTARAUGUS        118
20      ONEIDA         92
21    ROCKLAND         92
22       WAYNE         90
23     CLINTON         85
24    CORTLAND         76
25      ORANGE         75
26  WASHINGTON         65
27     GENESEE         61
28    FRANKLIN         58
29      OSWEGO         58
30      ALBANY         55
31    DUTCHESS         55
32      BROOME         54
33    ALLEGANY         52
34    CHENANGO         46
35   SCHOHARIE         44
36     CHEMUNG         38
37    TOMPKINS         38
38     WYOMING         38
39      FULTON         35
40  MONTGOMERY         34
41     NIAGARA         33
42       YATES         33
43    COLUMBIA         29
44     ORLEANS         29
45      SENECA         29
46    HAMILTON         27
47     MADISON         26
48       LEWIS         23
49    HERKIMER         22
50       TIOGA         22
51    SCHUYLER         19
52  LIVINGSTON         12
53      ULSTER         10
54      PUTNAM          5
55      CAYUGA          3

g <- ggplot(food_master_clean, aes(reorder(COUNTY, VIOLATIONS, sum), VIOLATIONS))
g + geom_bar(stat="identity", width = 0.2, fill="tomato2") + 
      labs(title="New York State Critical Violations", 
           subtitle="Food Service Establishment Violations Per County", 
           caption="Source: Open New York - Food Service Establishment: Last Inspection",
           x="COUNTY")+
          
      theme(axis.text.x = element_text(angle=89, vjust=0.5))

#ggplot(assets, aes(reorder(Currency, -Value, sum), Value)) +
  #geom_col()

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