# restart R
# .rs.restartR()
# pacotes
library(tidyverse) # varios
library(readxl) # read_xlsx
library(lubridate) # wday
library(qcc) # pareto.chart
library(voice)
library(jurimetrics)
library(devtools)
# functions
# source('~/Dropbox/Jurimetria/codigos/git/jurimetrics/fits.R')
# set strings as factors to false
options(stringsAsFactors = FALSE)
# diretorio
# setwd('~/Desktop/wbs/arquivosLiteExcel/') # Mac
# setwd('~/Documentos/tjrs/arquivosLiteExcel/') # Linux
setwd('~/Documentos/tjrs/csvFromXlsx/') # Linux
# lendo bancos de dados 2000:2017
ini <- Sys.time()
data <- tibble()
for(i in 2015:2020){
df <- read_csv(paste0('tjrs_',i,'.csv'))
temp <- df %>%
select(data_julgamento, tipo_processo, assunto_cnj) %>%
arrange(data_julgamento)
data <- bind_rows(data,temp)
gc()
print(i)
}
memory()
Sys.time() - ini # Time difference of 4.599254 mins
# criando colunas de semana e mês
ini <- Sys.time()
data <- data %>%
mutate(weekDay = lubridate::wday(data_julgamento, label = T))
data <- data %>%
mutate(yearMonth = as.Date(paste0(substr(data_julgamento,1,7),'-01'),
format = '%Y-%m-%d'))
# new wd
setwd('~/Dropbox/Jurimetria/codigos/git/jurimetrics/data/')
# agrupando e contando o número de processos por dia
count_day2 <- data %>%
group_by(data_julgamento) %>%
summarize(count = n())
use_data(count_day2, overwrite = T)
write_csv(count_day2, '~/Dropbox/Jurimetria/codigos/git/jurimetrics/data_extra/count_day2.csv')
# agrupando e contando o número de processos por dia por tipo de processo
count_day_type2 <- data %>%
group_by(data_julgamento, tipo_processo) %>%
summarize(count = n())
use_data(count_day_type2, overwrite = T)
write_csv(count_day_type2, '~/Dropbox/Jurimetria/codigos/git/jurimetrics/data_extra/count_day_type2.csv')
# agrupando e contando o número de processos por dia por assunto
count_day_subject2 <- data %>%
group_by(tipo_processo, assunto_cnj) %>%
summarize(count = n())
use_data(count_day_subject2, overwrite = T)
write_csv(count_day_subject2, '~/Dropbox/Jurimetria/codigos/git/jurimetrics/data_extra/count_day_subject2.csv')
# agrupando e contando o número de processos por dia da semana
count_week_day2 <- data %>%
group_by(weekDay) %>%
summarize(count = n())
use_data(count_week_day2, overwrite = T)
write_csv(count_week_day2, '~/Dropbox/Jurimetria/codigos/git/jurimetrics/data_extra/count_week_day2.csv')
# pareto.chart(table(data$weekDay))
# agrupando e contando o número de processos por dia da semana por tipo de processo
count_week_day_type2 <- data %>%
group_by(weekDay, tipo_processo) %>%
summarize(count = n())
use_data(count_week_day_type2, overwrite = T)
write_csv(count_week_day_type2, '~/Dropbox/Jurimetria/codigos/git/jurimetrics/data_extra/count_week_day_type2.csv')
# agrupando e contando o número de processos por dia da semana por assunto
count_week_day_subject2 <- data %>%
group_by(weekDay, assunto_cnj) %>%
summarize(count = n())
use_data(count_week_day_subject2, overwrite = T)
write_csv(count_week_day_subject2, '~/Dropbox/Jurimetria/codigos/git/jurimetrics/data_extra/count_day_subject2.csv')
# agrupando e contando o número de processos por mês
count_year_month2 <- data %>%
group_by(yearMonth) %>%
summarize(count = n())
use_data(count_year_month2, overwrite = T)
write_csv(count_year_month2, '~/Dropbox/Jurimetria/codigos/git/jurimetrics/data_extra/count_year_month2.csv')
# ggplot(count_year_month, aes(yearMonth, count)) +
# geom_line()
# agrupando e contando o número de processos por dia da semana por tipo de processo
count_year_month_type2 <- data %>%
group_by(yearMonth, tipo_processo) %>%
summarize(count = n())
use_data(count_year_month_type2, overwrite = T)
write_csv(count_year_month_type2, '~/Dropbox/Jurimetria/codigos/git/jurimetrics/data_extra/count_year_month_type2.csv')
# agrupando e contando o número de processos por dia da semana por assunto
count_year_month_subject2 <- data %>%
group_by(yearMonth, assunto_cnj) %>%
summarize(count = n())
use_data(count_year_month_subject2, overwrite = T)
write_csv(count_year_month_subject2, '~/Dropbox/Jurimetria/codigos/git/jurimetrics/data_extra/count_year_month_subject2.csv')
# data("count_day")
# count_day
# # projetando
# ini <- Sys.time()
# y <- ts(count_year_month$count, start = c(2000,1), frequency = 12)
# fits(y, steps = 48, lim = F, graf = T, PI = F)
# Sys.time()-ini # Time difference of 6.028008 mins, PI = T
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