This is an trial to extract data from Taipei gov API and take use of wordcloud to visualize data.
library(jsonlite)
library(tidyverse)
library(wordcloud2)
rm(list = ls())
options(Encoding="UTF-8")
data <- fromJSON("http://data.taipei/opendata/datalist/apiAccess?scope=resourceAquire&rid=a8fd6811-ab29-40dd-9b92-383e8ebd2a4e")
str(data)
## List of 1
## $ result:List of 5
## ..$ offset : int 0
## ..$ limit : int 10000
## ..$ count : int 77
## ..$ sort : chr ""
## ..$ results:'data.frame': 77 obs. of 12 variables:
## .. ..$ _id : chr [1:77] "1" "2" "3" "4" ...
## .. ..$ CITYZONE : chr [1:77] "士林區" "大同區" "大安區" "大安區" ...
## .. ..$ NAME : chr [1:77] "西歐" "中油" "中油" "勝利基金會" ...
## .. ..$ S_NAME : chr [1:77] "基河站" "民權西路站" "龍安站" "勝利站" ...
## .. ..$ SUPPLIER : chr [1:77] "台塑" "中油直營站" "中油直營站" "中油加盟站" ...
## .. ..$ ADDRESS : chr [1:77] "承德路四段200號" "民權西路194號" "和平東路二段2號" "建國南路二段75之1號" ...
## .. ..$ PHONE : chr [1:77] "02-28815335" "02-25575809" "02-23631735" "02-27555499" ...
## .. ..$ DUTY_TIME: chr [1:77] "24小時" "24小時" "24小時" "24小時" ...
## .. ..$ HAVEOIL : chr [1:77] "Y" "Y" "Y" "Y" ...
## .. ..$ HAVESELF : chr [1:77] "Y" "Y" "Y" NA ...
## .. ..$ ADDR_X : chr [1:77] "302652.865071764" "301878.706792256" "304016.333023747" "304275.87835925" ...
## .. ..$ ADDR_Y : chr [1:77] "2775582.73828788" "2772826.41098118" "2768731.6261877" "2769314.53330986" ...
df <- data$result$results
str(df)
## 'data.frame': 77 obs. of 12 variables:
## $ _id : chr "1" "2" "3" "4" ...
## $ CITYZONE : chr "士林區" "大同區" "大安區" "大安區" ...
## $ NAME : chr "西歐" "中油" "中油" "勝利基金會" ...
## $ S_NAME : chr "基河站" "民權西路站" "龍安站" "勝利站" ...
## $ SUPPLIER : chr "台塑" "中油直營站" "中油直營站" "中油加盟站" ...
## $ ADDRESS : chr "承德路四段200號" "民權西路194號" "和平東路二段2號" "建國南路二段75之1號" ...
## $ PHONE : chr "02-28815335" "02-25575809" "02-23631735" "02-27555499" ...
## $ DUTY_TIME: chr "24小時" "24小時" "24小時" "24小時" ...
## $ HAVEOIL : chr "Y" "Y" "Y" "Y" ...
## $ HAVESELF : chr "Y" "Y" "Y" NA ...
## $ ADDR_X : chr "302652.865071764" "301878.706792256" "304016.333023747" "304275.87835925" ...
## $ ADDR_Y : chr "2775582.73828788" "2772826.41098118" "2768731.6261877" "2769314.53330986" ...
ci <- df$CITYZONE %>% na.omit() %>%
str_replace_all("區", "")
tci <- table(ci)
wordcloud2(tci)