Plotting data evolution in time on R

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Good afternoon,

I’m having trouble plotting this data series over time. I would like to see the frequency of clients without CPF and without note per month, and how these indicators are evolving.

I can see that by looking at all the data, like this. However, I had another difficulty in adding the NR_NR field which is the note number.

freq_cpf_nota <- orcamento_filtrado %>%
  group_by(TEM_CPF, TEM_NF) %>%
  summarise(n = n()) %>% 
  mutate(FREQUENCIA = (n / 48952 * 100)) %>% 
  ungroup()

structure(list(NR_ORCAMENTO = c("10182", "10182", "10182", "10225", 
"10225", "10225", "10225", "10226", "10226", "10227", "10228", 
"10229", "10229", "10229", "10229", "10230", "10231", "10231", 
"10232", "10233"), DT_EMISSAO = structure(c(NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_), class = c("POSIXct", 
"POSIXt"), tzone = "UTC"), CICCGC = c("1457", "1457", "1457", 
NA, NA, NA, NA, "1315", "1315", "3588", "2048", "5408", "5408", 
"5408", "5408", "1363", "1374", "1374", "226", NA), NM_CLIENTE = c("CRISTIANO SANTOS DO CARMO", 
"CRISTIANO SANTOS DO CARMO", "CRISTIANO SANTOS DO CARMO", "PAULO", 
"PAULO", "PAULO", "PAULO", "SIDNEY DE ABREU JUNIOR", "SIDNEY DE ABREU JUNIOR", 
"ARI PEREIRA DE REZENDE", "FABIANO ALVES DA SILVA", "MAESTRO LOCADORA DE VEIC LTDA", 
"MAESTRO LOCADORA DE VEIC LTDA", "MAESTRO LOCADORA DE VEIC LTDA", 
"MAESTRO LOCADORA DE VEIC LTDA", "ROSALINA CRISTINA S PEREIRA", 
"DANIEL ROSSONY FILHO", "DANIEL ROSSONY FILHO", "MARIA DO CARMO G DA S FARIA", 
"JORGE"), FONE_NUMERO = c("31025016", "31025016", "31025016", 
"1", "1", "1", "1", "27928169", "27928169", "37788926", "1", 
"47850200", "47850200", "47850200", "47850200", "33711518", "1", 
"1", "31698881", "31844750"), PLACA = c("2767", "2767", "2767", 
NA, NA, NA, NA, NA, NA, NA, "2589", "437", "437", "437", "437", 
"3321", "1103", "1103", "3815", NA), NR_NOTA = c("25336", "25336", 
"25336", NA, NA, NA, NA, NA, NA, "28979", NA, "28986", "28986", 
"28986", "28986", "25337", "28980", "28980", "399", NA), TEM_CPF = c("Com CPF", 
"Com CPF", "Com CPF", "Sem CPF", "Sem CPF", "Sem CPF", "Sem CPF", 
"Com CPF", "Com CPF", "Com CPF", "Com CPF", "Com CPF", "Com CPF", 
"Com CPF", "Com CPF", "Com CPF", "Com CPF", "Com CPF", "Com CPF", 
"Sem CPF"), TEM_NF = c("Com Nota", "Com Nota", "Com Nota", "Sem Nota", 
"Sem Nota", "Sem Nota", "Sem Nota", "Sem Nota", "Sem Nota", "Com Nota", 
"Sem Nota", "Com Nota", "Com Nota", "Com Nota", "Com Nota", "Com Nota", 
"Com Nota", "Com Nota", "Com Nota", "Sem Nota"), TEM_PLACA = c("Com Placa", 
"Com Placa", "Com Placa", "Sem Placa", "Sem Placa", "Sem Placa", 
"Sem Placa", "Sem Placa", "Sem Placa", "Sem Placa", "Com Placa", 
"Com Placa", "Com Placa", "Com Placa", "Com Placa", "Com Placa", 
"Com Placa", "Com Placa", "Com Placa", "Sem Placa"), TEM_FONE = c("Com Telefone", 
"Com Telefone", "Com Telefone", "Com Telefone", "Com Telefone", 
"Com Telefone", "Com Telefone", "Com Telefone", "Com Telefone", 
"Com Telefone", "Com Telefone", "Com Telefone", "Com Telefone", 
"Com Telefone", "Com Telefone", "Com Telefone", "Com Telefone", 
"Com Telefone", "Com Telefone", "Com Telefone"), TEM_NOME = c("Com Nome", 
"Com Nome", "Com Nome", "Com Nome", "Com Nome", "Com Nome", "Com Nome", 
"Com Nome", "Com Nome", "Com Nome", "Com Nome", "Com Nome", "Com Nome", 
"Com Nome", "Com Nome", "Com Nome", "Com Nome", "Com Nome", "Com Nome", 
"Com Nome"), DATA_MES = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1)), .Names = c("NR_ORCAMENTO", "DT_EMISSAO", 
"CICCGC", "NM_CLIENTE", "FONE_NUMERO", "PLACA", "NR_NOTA", "TEM_CPF", 
"TEM_NF", "TEM_PLACA", "TEM_FONE", "TEM_NOME", "DATA_MES"), row.names = c(NA, 
20L), class = "data.frame")
r lubridate
  • 1

    Can you please edit the question with the output of dput(orcamento_filtrado) or if the base is too large, dput(head(orcamento_filtrado, 20))? The problem with data like this is that it will be difficult to read columns with spaces in their values.

  • I tried to do this, but for some reason one of the fields he’s not giving head, and he’s taking the whole base, even parameterizing the number of records. you know why this might be happening?

  • No, we can’t know without seeing. Try sapply(orcamento_filtrado, class) to see if any column is a class object list or more weird. You can also try dput(orcamento_filtrado[1:20, ]).

  • didn’t work tbm.. gave the same thing.. the strange eh that classes are all factor, dttm, Chr, and Dbl. And the dataset is in date.frame... format I tried to convert to Tibble but did not solve tbm.. I cannot send a csv?

  • It all happened factor then it is explained, the result of the dput is too big because it is giving all levels of each factor. Re-read the file but this time with the argument stringsAsFactors = FALSE and should solve the problem of dput.

  • ready! the problem was with the same factor. I converted to character and it worked!

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1 answer

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Would that be:

#aumentar os dados para mais meses:
orcamento_filtrado<-rbind(orcamento_filtrado,orcamento_filtrado)
orcamento_filtrado<-rbind(orcamento_filtrado,orcamento_filtrado)
orcamento_filtrado[20:40,13]=2
orcamento_filtrado[40:60,13]=3
orcamento_filtrado[60:80,13]=4

#filtro por características e mês:

freq_cpf_nota <- orcamento_filtrado %>%
  group_by(TEM_CPF, TEM_NF,DATA_MES) %>%
  summarise(n = n()) %>% 
  mutate(FREQUENCIA = (n / 48952 * 100)) %>% 
  ungroup()
freq_cpf_nota$TEMCPF_e_NF<-factor(paste(freq_cpf_nota$TEM_CPF,freq_cpf_nota$TEM_NF,sep=" e "))

plot(freq_cpf_nota$n~freq_cpf_nota$DATA_MES,col=freq_cpf_nota$TEMCPF_e_NF,pch=2)
legend("center",legend = levels(freq_cpf_nota$TEMCPF_e_NF),col=1:length(levels(freq_cpf_nota$TEMCPF_e_NF)),pch = 2)

inserir a descrição da imagem aqui

With ggplot

ggplot(aes(DATA_MES, n, group = TEMCPF_e_NF), data = freq_cpf_nota) +  
  geom_point(shape=23,size=3) +
  geom_line(aes(colour=TEMCPF_e_NF), linetype=2)

inserir a descrição da imagem aqui

  • Here gave the following error: Error in Plot.window(...) : finite values are required for 'xlim' In addition: Warning messages: 1: In min(x) : no non-missing Arguments to min; returning Inf 2: In max(x) : no non-missing Arguments to max; -Inf 3: In min(x) : no non-missing Arguments to min; returning Inf 4: In max(x) : no non-missing Arguments to max; returning -Inf . I have about a year and a half of data, and I’d like to see the month-to-month evolution of how many budgets have CPF, and how many have NF

  • Test if it works in the data you posted enlarged

  • I was able to do it here.. but the chart was really bad, the caption is on the chart.. how could I make a better chart? maybe with lines instead of dots

  • with ggplot maybe? did not understand very well the logic that Voce used to get to the ggplot

  • worked out, thanks!

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