Empenho vs. Pago por Função, 2014-2018

df_all_clean <- df_all %>%
  # era: rename(), select() deixa df menor
  select(ano,
         func_cod=`Função`,
         func=`Nome Função`,
         empenhado=`Valor Empenhado`,
         liquidado=`Valor Liquidado`,
         pago=`Valor Pago`)

df_all_clean %>%
  head(5) %>%
  knitr::kable(digits=0) %>%
  kableExtra::kable_styling("striped")

df_all_clean_summary <- df_all_clean %>%
  rename_all(~str_replace_all(.,fixed("_"),"-")) %>% # to avoid "_" conflict
  summarize_if(is.numeric,list(o0.n=~length(.),
                               o1.min=~min(.), # labels "a." preserve order
                               o2.q1=~quantile(.,.25),
                               o3.median=~median(.),
                               o4.mean=~mean(.),
                               o5.q3=~quantile(.,.75),
                               o6.max=~max(.))) %>%
  gather() %>%
  separate(key,c("col","stat"),sep="_") %>%
  spread(stat,value) %>%
  rename_all(~str_remove(.,"(..\\.)"))
#> Warning: attributes are not identical across measure variables;
#> they will be dropped
df_all_clean_summary %>%
  knitr::kable(digits=0) %>%
  kableExtra::kable_styling("striped")

df_all_clean_summary_card <- df_all_clean %>%
  rename_all(~str_replace_all(.,fixed("_"),"-")) %>% # to avoid "_" conflict
  summarize_if(~!is.numeric(.),list(o0.n=~length(.),
                                    o1.card=~n_distinct(.))) %>%
  gather() %>%
  separate(key,c("col","stat"),sep="_") %>%
  spread(stat,value) %>%
  rename_all(~str_remove(.,"(..\\.)"))

df_all_clean_summary_card %>%
  knitr::kable(digits=0) %>%
  kableExtra::kable_styling("striped")

df_all_clean %>%
  mutate(func=func%>%fct_reorder(-empenhado,sum)) %>%
  filter(as.integer(func)<6) %>%
  mutate(func=func%>%fct_drop%>%fct_rev) %>% # for coord_flip
  group_by(func) %>%
  # milhoes
  summarize_at(vars(empenhado,liquidado,pago),
               list(~(sum(.)/10^9))) %>%
  gather("tipo","valor",-func) %>%
  mutate(tipo=factor(tipo,levels=c("pago","liquidado","empenhado"))) %>%
  ggplot(aes(func,valor,group=tipo,fill=tipo)) +
  geom_col(position="dodge") +
  coord_flip() +
  labs(title="Totais por Função",
       subtitle="Top 5 por empenho total 2014-8",
       y="R$ bilhões") +
  theme(legend.position = "top",
        legend.title = element_blank(),
        axis.title.y=element_blank())

df_all_clean %>%
  mutate(func=func%>%fct_reorder(-empenhado,sum)) %>%
  filter(as.integer(func)<6) %>%
  mutate(func=func%>%fct_drop%>%fct_rev) %>% # for coord_flip
  group_by(ano,func) %>%
  # milhoes
  summarize_at(vars(empenhado,liquidado,pago),
               list(~(sum(.)/10^9))) %>%
  gather("tipo","valor",-func,-ano) %>%
  mutate(tipo=factor(tipo,levels=c("pago","liquidado","empenhado"))) %>%
  ggplot(aes(func,valor,group=tipo,fill=tipo)) +
  geom_col(position="dodge") +
  coord_flip() +
  labs(title="Totais por Função",
       subtitle="Top 5 por empenho total 2014-8",
       y="R$ bilhões") +
  theme(legend.position = "top",
        legend.title = element_blank(),
        axis.title.y=element_blank()) +
  facet_wrap(~ano)

top_levs <- df_top_funcs_empenhado$func%>%levels
df_all_clean_gathered <- df_all_clean %>%
  { suppressWarnings(inner_join(.,df_top_funcs_empenhado%>%
                                  select(rank,func_cod),
                               by="func_cod")) } %>%
  arrange(rank) %>%
  mutate(func=func%>%fct_drop%>%fct_inorder) %>%
  group_by(ano,func) %>%
  summarise(empenhado=sum(empenhado),
            pago=sum(pago)) %>%
  ungroup() %>%
  gather("tipo","valor",empenhado,pago)

abbrev_func <- function(s_vec) s_vec %>% str_split(" ") %>% map_chr(~.x%>%str_sub(end=3)%>%str_c(collapse="."))
anos <- df_all_clean_gathered$ano%>%as.character%>%unique
p <- df_all_clean_gathered %>%
  mutate(tipo=tipo%>%fct_recode(emp="empenhado",pag="pago"),
         func=func%>%abbrev_func%>%fct_inorder,
         valor=(valor/10^9)%>%round(1),
         func_tipo=func%>%str_c("_",tipo)%>%fct_inorder) %>%
  ggplot(aes(ano,valor,
             group=func_tipo,
             color=func,linetype=tipo)) +
  scale_linetype_manual(values=c("dotted","solid"))+
  geom_line(size=I(1.2)) +
  labs(title="Total Anual por Função",
       subtitle=sprintf("Anos %s-%s, Top 5",
                        min(anos),max(anos)),
       y = "R$ bilhões") +
  theme_minimal() +
    theme(legend.position = "bottom",
          legend.title=element_blank(),
          axis.title.x=element_blank())
ggplotly(p,tooltip=c("func","valor","tipo")) %>%
  # hide_legend() %>%
  config(displayModeBar = F)%>%
  layout(legend = list(orientation="v",font = list(size = 8)))