Projeto Análise de Dados
Alessandra e Leandro
2025-12-01
#Análise Estatística de Dados e Visualização
library(readr)
library(readxl)
library(writexl)
library(openxlsx)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, unionlibrary(ggplot2)library(knitr)library(forecast)## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zooIntrodução
Este relatório apresenta uma análise exploratória e estatística das
vendas da empresa, utilizando os dados fornecidos no arquivo
Vendas2024.xlsx. A análise utiliza dplyr e
ggplot2, como solicitado no projeto, e apresenta
estatísticas descritivas, tabelas e visualizações.
Leitura dos dados
# Lendo o mesmo arquivo no computador - neste caso, utilizei o endereço da internet para baixar o arquivo
Vendas2024 <- read_excel("Vendas2024.xlsx")vendas <- read_excel("Vendas2024.xlsx", sheet = 1)vendas <- vendas |>
mutate(
vendedor = as.factor(vendedor),
dias = as.Date(dias),
venda_diaria = as.numeric(venda_diaria),
mes = as.numeric(mes),
ano = as.numeric(ano)
)# Ajuste o caminho se necessário
vendas <- read_excel("Vendas2024.xlsx", sheet = 1)
# Ajuste de tipos
vendas <- vendas |>
mutate(
vendedor = as.factor(vendedor),
dias = as.Date(dias),
venda_diaria = as.numeric(venda_diaria),
mes = as.numeric(mes),
ano = as.numeric(ano)
)
# Remover NAs em venda_diaria
vendas <- vendas |> filter(!is.na(venda_diaria))
# Estrutura
str(vendas)## tibble [113,202 × 5] (S3: tbl_df/tbl/data.frame)
## $ vendedor : Factor w/ 12 levels "101101","101102",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ dias : Date[1:113202], format: "2018-01-01" "2018-01-01" ...
## $ venda_diaria: num [1:113202] 372 139 354 241 123 ...
## $ ano : num [1:113202] 2018 2018 2018 2018 2018 ...
## $ mes : num [1:113202] 1 1 1 1 1 1 1 1 1 1 ...# 5 primeiras linhas
head(vendas)## # A tibble: 6 × 5
## vendedor dias venda_diaria ano mes
## <fct> <date> <dbl> <dbl> <dbl>
## 1 101101 2018-01-01 372. 2018 1
## 2 101101 2018-01-01 139. 2018 1
## 3 101101 2018-01-01 354. 2018 1
## 4 101101 2018-01-01 241. 2018 1
## 5 101101 2018-01-01 123. 2018 1
## 6 101101 2018-01-01 165. 2018 1# Resumo
summary(vendas)## vendedor dias venda_diaria ano
## 101102 :14604 Min. :2018-01-01 Min. : 9.79 Min. :2018
## 101101 :13742 1st Qu.:2020-09-19 1st Qu.:133.27 1st Qu.:2020
## 101103 :12779 Median :2022-02-03 Median :254.06 Median :2022
## 101104 :10493 Mean :2021-11-21 Mean :260.38 Mean :2021
## 101105 :10419 3rd Qu.:2023-03-15 3rd Qu.:373.85 3rd Qu.:2023
## 101106 : 9997 Max. :2024-03-30 Max. :838.42 Max. :2024
## (Other):41168
## mes
## Min. : 1.000
## 1st Qu.: 3.000
## Median : 7.000
## Mean : 6.548
## 3rd Qu.:10.000
## Max. :12.000
## Análise Estatística com dplyr
##Estatísticas por vendedor
estat_vendedor <- vendas |>
group_by(vendedor) |>
summarise(
total_vendas = sum(venda_diaria),
media_diaria = mean(venda_diaria),
mediana_diaria = median(venda_diaria),
desvio_padrao = sd(venda_diaria),
registros = n()
) |>
arrange(desc(total_vendas))
kable(estat_vendedor, caption = "Estatísticas por Vendedor")| vendedor | total_vendas | media_diaria | mediana_diaria | desvio_padrao | registros |
|---|---|---|---|---|---|
| 101102 | 4031176 | 276.0323 | 268.370 | 160.7581 | 14604 |
| 101101 | 3489519 | 253.9309 | 249.280 | 146.2669 | 13742 |
| 101103 | 3433923 | 268.7161 | 264.700 | 155.3434 | 12779 |
| 101105 | 2694622 | 258.6258 | 250.790 | 150.1411 | 10419 |
| 101104 | 2491491 | 237.4432 | 232.130 | 137.8471 | 10493 |
| 101108 | 2473665 | 271.4734 | 265.235 | 157.0374 | 9112 |
| 101106 | 2458056 | 245.8794 | 240.990 | 143.1502 | 9997 |
| 102111 | 2441308 | 244.6691 | 240.990 | 140.9007 | 9978 |
| 101107 | 2201441 | 250.2775 | 243.280 | 146.5876 | 8796 |
| 102112 | 1338667 | 289.5042 | 282.730 | 166.8494 | 4624 |
| 101109 | 1296194 | 304.0569 | 297.620 | 173.8729 | 4263 |
| 101110 | 1125154 | 256.0078 | 252.310 | 145.7166 | 4395 |
##Venda mensal total (geral)
venda_mensal_geral <- vendas |>
group_by(ano, mes) |>
summarise(total_mensal = sum(venda_diaria))## `summarise()` has grouped output by 'ano'. You can override using the `.groups`
## argument.kable(venda_mensal_geral, caption = "Venda Mensal Total da Empresa")| ano | mes | total_mensal |
|---|---|---|
| 2018 | 1 | 101567.93 |
| 2018 | 2 | 84566.85 |
| 2018 | 3 | 85530.13 |
| 2018 | 4 | 98811.06 |
| 2018 | 5 | 120225.68 |
| 2018 | 6 | 97619.83 |
| 2018 | 7 | 83419.18 |
| 2018 | 8 | 124339.31 |
| 2018 | 9 | 120982.09 |
| 2018 | 10 | 127807.90 |
| 2018 | 11 | 155285.26 |
| 2018 | 12 | 187369.81 |
| 2019 | 1 | 136127.00 |
| 2019 | 2 | 98931.27 |
| 2019 | 3 | 114280.20 |
| 2019 | 4 | 126960.42 |
| 2019 | 5 | 171233.06 |
| 2019 | 6 | 149914.75 |
| 2019 | 7 | 107252.77 |
| 2019 | 8 | 141441.62 |
| 2019 | 9 | 129484.14 |
| 2019 | 10 | 288625.81 |
| 2019 | 11 | 355359.75 |
| 2019 | 12 | 468261.28 |
| 2020 | 1 | 271472.65 |
| 2020 | 2 | 222533.09 |
| 2020 | 3 | 382382.08 |
| 2020 | 4 | 421068.32 |
| 2020 | 5 | 517596.70 |
| 2020 | 6 | 416373.11 |
| 2020 | 7 | 351208.06 |
| 2020 | 8 | 331284.75 |
| 2020 | 9 | 400772.74 |
| 2020 | 10 | 387258.35 |
| 2020 | 11 | 505659.62 |
| 2020 | 12 | 595835.98 |
| 2021 | 1 | 360726.31 |
| 2021 | 2 | 301422.03 |
| 2021 | 3 | 385502.04 |
| 2021 | 4 | 430170.60 |
| 2021 | 5 | 483334.28 |
| 2021 | 6 | 476022.42 |
| 2021 | 7 | 400116.30 |
| 2021 | 8 | 392945.07 |
| 2021 | 9 | 375571.56 |
| 2021 | 10 | 441425.94 |
| 2021 | 11 | 503923.84 |
| 2021 | 12 | 608599.31 |
| 2022 | 1 | 398929.02 |
| 2022 | 2 | 344108.08 |
| 2022 | 3 | 366832.24 |
| 2022 | 4 | 479610.28 |
| 2022 | 5 | 669782.26 |
| 2022 | 6 | 616457.44 |
| 2022 | 7 | 540985.75 |
| 2022 | 8 | 530524.87 |
| 2022 | 9 | 510590.58 |
| 2022 | 10 | 614907.36 |
| 2022 | 11 | 736200.89 |
| 2022 | 12 | 817665.03 |
| 2023 | 1 | 568067.46 |
| 2023 | 2 | 477297.07 |
| 2023 | 3 | 577768.37 |
| 2023 | 4 | 608208.92 |
| 2023 | 5 | 699119.04 |
| 2023 | 6 | 682889.59 |
| 2023 | 7 | 574676.55 |
| 2023 | 8 | 571171.72 |
| 2023 | 9 | 572114.63 |
| 2023 | 10 | 651203.73 |
| 2023 | 11 | 757312.16 |
| 2023 | 12 | 898480.62 |
| 2024 | 1 | 549534.22 |
| 2024 | 2 | 468779.94 |
| 2024 | 3 | 553397.54 |
##Venda mensal por vendedor
venda_mensal_vendedor <- vendas |>
group_by(vendedor, ano, mes) |>
summarise(total_mensal = sum(venda_diaria))## `summarise()` has grouped output by 'vendedor', 'ano'. You can override using
## the `.groups` argument.kable(venda_mensal_vendedor, caption = "Venda Mensal por Vendedor")| vendedor | ano | mes | total_mensal |
|---|---|---|---|
| 101101 | 2018 | 1 | 40681.80 |
| 101101 | 2018 | 2 | 41947.67 |
| 101101 | 2018 | 3 | 39753.13 |
| 101101 | 2018 | 4 | 40270.40 |
| 101101 | 2018 | 5 | 60735.17 |
| 101101 | 2018 | 6 | 37626.92 |
| 101101 | 2018 | 7 | 52441.26 |
| 101101 | 2018 | 8 | 34252.90 |
| 101101 | 2018 | 9 | 30023.94 |
| 101101 | 2018 | 10 | 41341.30 |
| 101101 | 2018 | 11 | 51040.47 |
| 101101 | 2018 | 12 | 39680.91 |
| 101101 | 2019 | 1 | 41224.85 |
| 101101 | 2019 | 2 | 29976.22 |
| 101101 | 2019 | 3 | 39335.37 |
| 101101 | 2019 | 4 | 45675.40 |
| 101101 | 2019 | 5 | 62870.07 |
| 101101 | 2019 | 6 | 42763.94 |
| 101101 | 2019 | 7 | 22912.14 |
| 101101 | 2019 | 8 | 33704.01 |
| 101101 | 2019 | 9 | 43377.77 |
| 101101 | 2019 | 10 | 38542.64 |
| 101101 | 2019 | 11 | 45892.56 |
| 101101 | 2019 | 12 | 59826.48 |
| 101101 | 2020 | 1 | 41723.03 |
| 101101 | 2020 | 2 | 40801.88 |
| 101101 | 2020 | 3 | 36346.38 |
| 101101 | 2020 | 4 | 57174.21 |
| 101101 | 2020 | 5 | 46558.86 |
| 101101 | 2020 | 6 | 55376.25 |
| 101101 | 2020 | 7 | 31939.62 |
| 101101 | 2020 | 8 | 34637.89 |
| 101101 | 2020 | 9 | 46056.07 |
| 101101 | 2020 | 10 | 41511.59 |
| 101101 | 2020 | 11 | 55041.55 |
| 101101 | 2020 | 12 | 57423.68 |
| 101101 | 2021 | 1 | 47447.76 |
| 101101 | 2021 | 2 | 38324.18 |
| 101101 | 2021 | 3 | 44383.22 |
| 101101 | 2021 | 4 | 53238.65 |
| 101101 | 2021 | 5 | 53321.54 |
| 101101 | 2021 | 6 | 56447.64 |
| 101101 | 2021 | 7 | 55493.95 |
| 101101 | 2021 | 8 | 51480.23 |
| 101101 | 2021 | 9 | 31795.73 |
| 101101 | 2021 | 10 | 45357.13 |
| 101101 | 2021 | 11 | 65867.85 |
| 101101 | 2021 | 12 | 62318.68 |
| 101101 | 2022 | 1 | 44862.95 |
| 101101 | 2022 | 2 | 37567.03 |
| 101101 | 2022 | 3 | 38841.08 |
| 101101 | 2022 | 4 | 71495.72 |
| 101101 | 2022 | 5 | 53722.20 |
| 101101 | 2022 | 6 | 39531.22 |
| 101101 | 2022 | 7 | 48382.74 |
| 101101 | 2022 | 8 | 43965.06 |
| 101101 | 2022 | 9 | 33527.00 |
| 101101 | 2022 | 10 | 56199.89 |
| 101101 | 2022 | 11 | 72540.26 |
| 101101 | 2022 | 12 | 71716.98 |
| 101101 | 2023 | 1 | 45169.53 |
| 101101 | 2023 | 2 | 47677.66 |
| 101101 | 2023 | 3 | 35270.33 |
| 101101 | 2023 | 4 | 44725.80 |
| 101101 | 2023 | 5 | 55171.66 |
| 101101 | 2023 | 6 | 41878.86 |
| 101101 | 2023 | 7 | 33125.65 |
| 101101 | 2023 | 8 | 43020.87 |
| 101101 | 2023 | 9 | 50643.02 |
| 101101 | 2023 | 10 | 49500.21 |
| 101101 | 2023 | 11 | 63300.72 |
| 101101 | 2023 | 12 | 76105.38 |
| 101101 | 2024 | 1 | 43886.63 |
| 101101 | 2024 | 2 | 44546.65 |
| 101101 | 2024 | 3 | 37178.72 |
| 101102 | 2018 | 1 | 60886.13 |
| 101102 | 2018 | 2 | 42619.18 |
| 101102 | 2018 | 3 | 45777.00 |
| 101102 | 2018 | 4 | 58540.66 |
| 101102 | 2018 | 5 | 59490.51 |
| 101102 | 2018 | 6 | 59992.91 |
| 101102 | 2018 | 7 | 30977.92 |
| 101102 | 2018 | 8 | 49979.25 |
| 101102 | 2018 | 9 | 55287.71 |
| 101102 | 2018 | 10 | 42099.44 |
| 101102 | 2018 | 11 | 52017.64 |
| 101102 | 2018 | 12 | 67636.95 |
| 101102 | 2019 | 1 | 48626.39 |
| 101102 | 2019 | 2 | 40099.17 |
| 101102 | 2019 | 3 | 43901.94 |
| 101102 | 2019 | 4 | 40445.01 |
| 101102 | 2019 | 5 | 47833.10 |
| 101102 | 2019 | 6 | 61289.65 |
| 101102 | 2019 | 7 | 47540.56 |
| 101102 | 2019 | 8 | 62335.37 |
| 101102 | 2019 | 9 | 53614.69 |
| 101102 | 2019 | 10 | 61192.03 |
| 101102 | 2019 | 11 | 54301.42 |
| 101102 | 2019 | 12 | 94872.18 |
| 101102 | 2020 | 1 | 38565.85 |
| 101102 | 2020 | 2 | 33627.55 |
| 101102 | 2020 | 3 | 48784.70 |
| 101102 | 2020 | 4 | 53038.01 |
| 101102 | 2020 | 5 | 66041.61 |
| 101102 | 2020 | 6 | 49906.18 |
| 101102 | 2020 | 7 | 50975.88 |
| 101102 | 2020 | 8 | 33748.93 |
| 101102 | 2020 | 9 | 47629.52 |
| 101102 | 2020 | 10 | 42814.18 |
| 101102 | 2020 | 11 | 61986.54 |
| 101102 | 2020 | 12 | 90890.89 |
| 101102 | 2021 | 1 | 60906.04 |
| 101102 | 2021 | 2 | 23835.06 |
| 101102 | 2021 | 3 | 65606.24 |
| 101102 | 2021 | 4 | 45976.78 |
| 101102 | 2021 | 5 | 38404.23 |
| 101102 | 2021 | 6 | 49060.50 |
| 101102 | 2021 | 7 | 38758.11 |
| 101102 | 2021 | 8 | 49200.11 |
| 101102 | 2021 | 9 | 63058.72 |
| 101102 | 2021 | 10 | 56906.38 |
| 101102 | 2021 | 11 | 63786.96 |
| 101102 | 2021 | 12 | 78153.60 |
| 101102 | 2022 | 1 | 55255.92 |
| 101102 | 2022 | 2 | 34207.18 |
| 101102 | 2022 | 3 | 47499.21 |
| 101102 | 2022 | 4 | 62037.36 |
| 101102 | 2022 | 5 | 46808.94 |
| 101102 | 2022 | 6 | 55693.53 |
| 101102 | 2022 | 7 | 67518.71 |
| 101102 | 2022 | 8 | 44106.31 |
| 101102 | 2022 | 9 | 38518.99 |
| 101102 | 2022 | 10 | 49778.25 |
| 101102 | 2022 | 11 | 67588.72 |
| 101102 | 2022 | 12 | 85524.24 |
| 101102 | 2023 | 1 | 46544.32 |
| 101102 | 2023 | 2 | 50858.30 |
| 101102 | 2023 | 3 | 52274.98 |
| 101102 | 2023 | 4 | 56676.20 |
| 101102 | 2023 | 5 | 44685.25 |
| 101102 | 2023 | 6 | 75753.23 |
| 101102 | 2023 | 7 | 54960.13 |
| 101102 | 2023 | 8 | 54417.98 |
| 101102 | 2023 | 9 | 54924.12 |
| 101102 | 2023 | 10 | 75660.18 |
| 101102 | 2023 | 11 | 54897.82 |
| 101102 | 2023 | 12 | 95026.18 |
| 101102 | 2024 | 1 | 47541.22 |
| 101102 | 2024 | 2 | 33181.72 |
| 101102 | 2024 | 3 | 46217.34 |
| 101103 | 2018 | 8 | 40107.16 |
| 101103 | 2018 | 9 | 35670.44 |
| 101103 | 2018 | 10 | 44367.16 |
| 101103 | 2018 | 11 | 52227.15 |
| 101103 | 2018 | 12 | 80051.95 |
| 101103 | 2019 | 1 | 46275.76 |
| 101103 | 2019 | 2 | 28855.88 |
| 101103 | 2019 | 3 | 31042.89 |
| 101103 | 2019 | 4 | 40840.01 |
| 101103 | 2019 | 5 | 60529.89 |
| 101103 | 2019 | 6 | 45861.16 |
| 101103 | 2019 | 7 | 36800.07 |
| 101103 | 2019 | 8 | 45402.24 |
| 101103 | 2019 | 9 | 32491.68 |
| 101103 | 2019 | 10 | 29469.33 |
| 101103 | 2019 | 11 | 57024.57 |
| 101103 | 2019 | 12 | 69231.29 |
| 101103 | 2020 | 1 | 34040.09 |
| 101103 | 2020 | 2 | 34720.06 |
| 101103 | 2020 | 3 | 53394.72 |
| 101103 | 2020 | 4 | 56202.20 |
| 101103 | 2020 | 5 | 61665.25 |
| 101103 | 2020 | 6 | 42014.44 |
| 101103 | 2020 | 7 | 42022.52 |
| 101103 | 2020 | 8 | 45156.58 |
| 101103 | 2020 | 9 | 55491.47 |
| 101103 | 2020 | 10 | 50256.26 |
| 101103 | 2020 | 11 | 56058.54 |
| 101103 | 2020 | 12 | 67130.83 |
| 101103 | 2021 | 1 | 36376.50 |
| 101103 | 2021 | 2 | 33595.41 |
| 101103 | 2021 | 3 | 33227.95 |
| 101103 | 2021 | 4 | 59818.55 |
| 101103 | 2021 | 5 | 58715.66 |
| 101103 | 2021 | 6 | 62600.09 |
| 101103 | 2021 | 7 | 51214.27 |
| 101103 | 2021 | 8 | 53747.81 |
| 101103 | 2021 | 9 | 45131.78 |
| 101103 | 2021 | 10 | 59707.33 |
| 101103 | 2021 | 11 | 56102.67 |
| 101103 | 2021 | 12 | 63409.49 |
| 101103 | 2022 | 1 | 51045.78 |
| 101103 | 2022 | 2 | 34164.39 |
| 101103 | 2022 | 3 | 45948.09 |
| 101103 | 2022 | 4 | 45476.96 |
| 101103 | 2022 | 5 | 53996.74 |
| 101103 | 2022 | 6 | 46459.24 |
| 101103 | 2022 | 7 | 29727.23 |
| 101103 | 2022 | 8 | 45158.18 |
| 101103 | 2022 | 9 | 54360.77 |
| 101103 | 2022 | 10 | 67618.27 |
| 101103 | 2022 | 11 | 63546.87 |
| 101103 | 2022 | 12 | 49755.54 |
| 101103 | 2023 | 1 | 47465.35 |
| 101103 | 2023 | 2 | 49485.80 |
| 101103 | 2023 | 3 | 53620.82 |
| 101103 | 2023 | 4 | 62219.08 |
| 101103 | 2023 | 5 | 55499.90 |
| 101103 | 2023 | 6 | 56547.28 |
| 101103 | 2023 | 7 | 59279.52 |
| 101103 | 2023 | 8 | 60395.88 |
| 101103 | 2023 | 9 | 58152.23 |
| 101103 | 2023 | 10 | 44951.77 |
| 101103 | 2023 | 11 | 92007.39 |
| 101103 | 2023 | 12 | 86666.28 |
| 101103 | 2024 | 1 | 41747.12 |
| 101103 | 2024 | 2 | 46263.66 |
| 101103 | 2024 | 3 | 44313.81 |
| 101104 | 2019 | 10 | 33794.18 |
| 101104 | 2019 | 11 | 49385.73 |
| 101104 | 2019 | 12 | 65688.42 |
| 101104 | 2020 | 1 | 46715.12 |
| 101104 | 2020 | 2 | 29915.38 |
| 101104 | 2020 | 3 | 42158.82 |
| 101104 | 2020 | 4 | 34877.36 |
| 101104 | 2020 | 5 | 57734.07 |
| 101104 | 2020 | 6 | 39480.47 |
| 101104 | 2020 | 7 | 38777.38 |
| 101104 | 2020 | 8 | 30401.98 |
| 101104 | 2020 | 9 | 36096.87 |
| 101104 | 2020 | 10 | 40318.73 |
| 101104 | 2020 | 11 | 56019.02 |
| 101104 | 2020 | 12 | 62334.30 |
| 101104 | 2021 | 1 | 36774.92 |
| 101104 | 2021 | 2 | 25862.77 |
| 101104 | 2021 | 3 | 38957.57 |
| 101104 | 2021 | 4 | 43709.66 |
| 101104 | 2021 | 5 | 46277.30 |
| 101104 | 2021 | 6 | 52985.08 |
| 101104 | 2021 | 7 | 31522.06 |
| 101104 | 2021 | 8 | 37061.10 |
| 101104 | 2021 | 9 | 35948.57 |
| 101104 | 2021 | 10 | 58349.95 |
| 101104 | 2021 | 11 | 63357.07 |
| 101104 | 2021 | 12 | 72010.63 |
| 101104 | 2022 | 1 | 49932.40 |
| 101104 | 2022 | 2 | 27377.62 |
| 101104 | 2022 | 3 | 33783.94 |
| 101104 | 2022 | 4 | 34471.94 |
| 101104 | 2022 | 5 | 68517.78 |
| 101104 | 2022 | 6 | 52691.69 |
| 101104 | 2022 | 7 | 46350.99 |
| 101104 | 2022 | 8 | 37598.99 |
| 101104 | 2022 | 9 | 43736.90 |
| 101104 | 2022 | 10 | 47450.31 |
| 101104 | 2022 | 11 | 54349.11 |
| 101104 | 2022 | 12 | 68822.24 |
| 101104 | 2023 | 1 | 48155.44 |
| 101104 | 2023 | 2 | 31349.82 |
| 101104 | 2023 | 3 | 53884.72 |
| 101104 | 2023 | 4 | 41858.56 |
| 101104 | 2023 | 5 | 57249.61 |
| 101104 | 2023 | 6 | 65325.10 |
| 101104 | 2023 | 7 | 36866.69 |
| 101104 | 2023 | 8 | 39211.38 |
| 101104 | 2023 | 9 | 38574.54 |
| 101104 | 2023 | 10 | 50925.85 |
| 101104 | 2023 | 11 | 68969.34 |
| 101104 | 2023 | 12 | 57583.34 |
| 101104 | 2024 | 1 | 41084.28 |
| 101104 | 2024 | 2 | 40511.71 |
| 101104 | 2024 | 3 | 48342.67 |
| 101105 | 2019 | 10 | 42449.43 |
| 101105 | 2019 | 11 | 65144.64 |
| 101105 | 2019 | 12 | 57601.64 |
| 101105 | 2020 | 1 | 30683.57 |
| 101105 | 2020 | 2 | 28573.11 |
| 101105 | 2020 | 3 | 38557.74 |
| 101105 | 2020 | 4 | 46891.04 |
| 101105 | 2020 | 5 | 54064.64 |
| 101105 | 2020 | 6 | 55954.07 |
| 101105 | 2020 | 7 | 43596.58 |
| 101105 | 2020 | 8 | 39722.83 |
| 101105 | 2020 | 9 | 46191.38 |
| 101105 | 2020 | 10 | 42497.82 |
| 101105 | 2020 | 11 | 55015.43 |
| 101105 | 2020 | 12 | 62930.58 |
| 101105 | 2021 | 1 | 48910.62 |
| 101105 | 2021 | 2 | 32011.15 |
| 101105 | 2021 | 3 | 49272.21 |
| 101105 | 2021 | 4 | 43871.95 |
| 101105 | 2021 | 5 | 59294.86 |
| 101105 | 2021 | 6 | 50159.39 |
| 101105 | 2021 | 7 | 53520.67 |
| 101105 | 2021 | 8 | 52949.18 |
| 101105 | 2021 | 9 | 44501.40 |
| 101105 | 2021 | 10 | 41925.48 |
| 101105 | 2021 | 11 | 46053.34 |
| 101105 | 2021 | 12 | 76323.37 |
| 101105 | 2022 | 1 | 53802.84 |
| 101105 | 2022 | 2 | 41266.12 |
| 101105 | 2022 | 3 | 37527.97 |
| 101105 | 2022 | 4 | 67326.98 |
| 101105 | 2022 | 5 | 38395.01 |
| 101105 | 2022 | 6 | 51755.83 |
| 101105 | 2022 | 7 | 47463.86 |
| 101105 | 2022 | 8 | 29691.43 |
| 101105 | 2022 | 9 | 50389.50 |
| 101105 | 2022 | 10 | 42623.25 |
| 101105 | 2022 | 11 | 60050.65 |
| 101105 | 2022 | 12 | 65712.66 |
| 101105 | 2023 | 1 | 54674.38 |
| 101105 | 2023 | 2 | 40549.65 |
| 101105 | 2023 | 3 | 50381.04 |
| 101105 | 2023 | 4 | 59397.07 |
| 101105 | 2023 | 5 | 58379.51 |
| 101105 | 2023 | 6 | 53443.95 |
| 101105 | 2023 | 7 | 53699.36 |
| 101105 | 2023 | 8 | 56296.74 |
| 101105 | 2023 | 9 | 41755.10 |
| 101105 | 2023 | 10 | 49514.58 |
| 101105 | 2023 | 11 | 55557.79 |
| 101105 | 2023 | 12 | 76852.62 |
| 101105 | 2024 | 1 | 55530.18 |
| 101105 | 2024 | 2 | 38729.36 |
| 101105 | 2024 | 3 | 55186.72 |
| 101106 | 2019 | 10 | 37548.02 |
| 101106 | 2019 | 11 | 49206.99 |
| 101106 | 2019 | 12 | 70671.43 |
| 101106 | 2020 | 1 | 42163.70 |
| 101106 | 2020 | 2 | 28291.89 |
| 101106 | 2020 | 3 | 44241.16 |
| 101106 | 2020 | 4 | 38296.63 |
| 101106 | 2020 | 5 | 52844.38 |
| 101106 | 2020 | 6 | 38589.21 |
| 101106 | 2020 | 7 | 29265.36 |
| 101106 | 2020 | 8 | 38487.96 |
| 101106 | 2020 | 9 | 42207.37 |
| 101106 | 2020 | 10 | 37963.25 |
| 101106 | 2020 | 11 | 59080.63 |
| 101106 | 2020 | 12 | 75311.16 |
| 101106 | 2021 | 1 | 30655.78 |
| 101106 | 2021 | 2 | 38480.01 |
| 101106 | 2021 | 3 | 39078.94 |
| 101106 | 2021 | 4 | 39281.75 |
| 101106 | 2021 | 5 | 54357.39 |
| 101106 | 2021 | 6 | 41095.05 |
| 101106 | 2021 | 7 | 33558.33 |
| 101106 | 2021 | 8 | 36138.42 |
| 101106 | 2021 | 9 | 35000.16 |
| 101106 | 2021 | 10 | 38592.88 |
| 101106 | 2021 | 11 | 49079.87 |
| 101106 | 2021 | 12 | 46704.00 |
| 101106 | 2022 | 1 | 38842.32 |
| 101106 | 2022 | 2 | 49873.47 |
| 101106 | 2022 | 3 | 32980.65 |
| 101106 | 2022 | 4 | 55487.60 |
| 101106 | 2022 | 5 | 60911.80 |
| 101106 | 2022 | 6 | 43988.99 |
| 101106 | 2022 | 7 | 33318.68 |
| 101106 | 2022 | 8 | 44194.64 |
| 101106 | 2022 | 9 | 52064.92 |
| 101106 | 2022 | 10 | 53858.19 |
| 101106 | 2022 | 11 | 64545.39 |
| 101106 | 2022 | 12 | 53160.32 |
| 101106 | 2023 | 1 | 40549.52 |
| 101106 | 2023 | 2 | 25910.63 |
| 101106 | 2023 | 3 | 52192.52 |
| 101106 | 2023 | 4 | 54543.35 |
| 101106 | 2023 | 5 | 80185.63 |
| 101106 | 2023 | 6 | 54460.64 |
| 101106 | 2023 | 7 | 42205.96 |
| 101106 | 2023 | 8 | 45039.40 |
| 101106 | 2023 | 9 | 48898.60 |
| 101106 | 2023 | 10 | 35861.74 |
| 101106 | 2023 | 11 | 48334.42 |
| 101106 | 2023 | 12 | 54848.14 |
| 101106 | 2024 | 1 | 38536.49 |
| 101106 | 2024 | 2 | 43693.53 |
| 101106 | 2024 | 3 | 43376.99 |
| 101107 | 2020 | 3 | 37411.23 |
| 101107 | 2020 | 4 | 56681.90 |
| 101107 | 2020 | 5 | 57528.10 |
| 101107 | 2020 | 6 | 47267.98 |
| 101107 | 2020 | 7 | 39980.54 |
| 101107 | 2020 | 8 | 42331.26 |
| 101107 | 2020 | 9 | 33294.96 |
| 101107 | 2020 | 10 | 50274.04 |
| 101107 | 2020 | 11 | 48352.69 |
| 101107 | 2020 | 12 | 51632.93 |
| 101107 | 2021 | 1 | 31529.34 |
| 101107 | 2021 | 2 | 38842.04 |
| 101107 | 2021 | 3 | 30994.21 |
| 101107 | 2021 | 4 | 46837.09 |
| 101107 | 2021 | 5 | 59902.15 |
| 101107 | 2021 | 6 | 56710.53 |
| 101107 | 2021 | 7 | 45639.08 |
| 101107 | 2021 | 8 | 37714.43 |
| 101107 | 2021 | 9 | 18645.64 |
| 101107 | 2021 | 10 | 52331.33 |
| 101107 | 2021 | 11 | 39344.72 |
| 101107 | 2021 | 12 | 71135.85 |
| 101107 | 2022 | 1 | 30047.33 |
| 101107 | 2022 | 2 | 48633.94 |
| 101107 | 2022 | 3 | 40480.66 |
| 101107 | 2022 | 4 | 36265.17 |
| 101107 | 2022 | 5 | 47390.38 |
| 101107 | 2022 | 6 | 39575.81 |
| 101107 | 2022 | 7 | 38074.92 |
| 101107 | 2022 | 8 | 53896.20 |
| 101107 | 2022 | 9 | 47856.28 |
| 101107 | 2022 | 10 | 38500.05 |
| 101107 | 2022 | 11 | 36167.03 |
| 101107 | 2022 | 12 | 64409.32 |
| 101107 | 2023 | 1 | 33212.71 |
| 101107 | 2023 | 2 | 33408.24 |
| 101107 | 2023 | 3 | 46666.91 |
| 101107 | 2023 | 4 | 47119.40 |
| 101107 | 2023 | 5 | 51355.69 |
| 101107 | 2023 | 6 | 49539.90 |
| 101107 | 2023 | 7 | 36181.39 |
| 101107 | 2023 | 8 | 40788.21 |
| 101107 | 2023 | 9 | 54367.96 |
| 101107 | 2023 | 10 | 48918.53 |
| 101107 | 2023 | 11 | 66891.38 |
| 101107 | 2023 | 12 | 62666.69 |
| 101107 | 2024 | 1 | 37202.57 |
| 101107 | 2024 | 2 | 27816.98 |
| 101107 | 2024 | 3 | 49625.06 |
| 101108 | 2020 | 3 | 40287.20 |
| 101108 | 2020 | 4 | 39834.30 |
| 101108 | 2020 | 5 | 59674.79 |
| 101108 | 2020 | 6 | 55556.24 |
| 101108 | 2020 | 7 | 42364.64 |
| 101108 | 2020 | 8 | 44083.46 |
| 101108 | 2020 | 9 | 52584.44 |
| 101108 | 2020 | 10 | 43293.87 |
| 101108 | 2020 | 11 | 61969.09 |
| 101108 | 2020 | 12 | 68630.77 |
| 101108 | 2021 | 1 | 34525.65 |
| 101108 | 2021 | 2 | 37742.07 |
| 101108 | 2021 | 3 | 48854.68 |
| 101108 | 2021 | 4 | 53487.21 |
| 101108 | 2021 | 5 | 50197.82 |
| 101108 | 2021 | 6 | 56985.85 |
| 101108 | 2021 | 7 | 45505.89 |
| 101108 | 2021 | 8 | 38917.57 |
| 101108 | 2021 | 9 | 56213.38 |
| 101108 | 2021 | 10 | 47959.59 |
| 101108 | 2021 | 11 | 63126.13 |
| 101108 | 2021 | 12 | 82214.15 |
| 101108 | 2022 | 1 | 34230.79 |
| 101108 | 2022 | 2 | 41191.62 |
| 101108 | 2022 | 3 | 58873.65 |
| 101108 | 2022 | 4 | 67481.57 |
| 101108 | 2022 | 5 | 76864.17 |
| 101108 | 2022 | 6 | 37195.79 |
| 101108 | 2022 | 7 | 51102.40 |
| 101108 | 2022 | 8 | 50987.90 |
| 101108 | 2022 | 9 | 39343.09 |
| 101108 | 2022 | 10 | 42726.22 |
| 101108 | 2022 | 11 | 59484.86 |
| 101108 | 2022 | 12 | 60823.14 |
| 101108 | 2023 | 1 | 39263.91 |
| 101108 | 2023 | 2 | 31232.69 |
| 101108 | 2023 | 3 | 39938.08 |
| 101108 | 2023 | 4 | 42656.60 |
| 101108 | 2023 | 5 | 70100.10 |
| 101108 | 2023 | 6 | 62499.65 |
| 101108 | 2023 | 7 | 52787.92 |
| 101108 | 2023 | 8 | 35130.81 |
| 101108 | 2023 | 9 | 46627.42 |
| 101108 | 2023 | 10 | 59917.05 |
| 101108 | 2023 | 11 | 56113.58 |
| 101108 | 2023 | 12 | 82224.56 |
| 101108 | 2024 | 1 | 36358.63 |
| 101108 | 2024 | 2 | 37009.96 |
| 101108 | 2024 | 3 | 37490.39 |
| 101109 | 2022 | 5 | 39008.32 |
| 101109 | 2022 | 6 | 58234.50 |
| 101109 | 2022 | 7 | 36848.68 |
| 101109 | 2022 | 8 | 51849.04 |
| 101109 | 2022 | 9 | 29144.07 |
| 101109 | 2022 | 10 | 52264.97 |
| 101109 | 2022 | 11 | 74003.36 |
| 101109 | 2022 | 12 | 67959.96 |
| 101109 | 2023 | 1 | 69639.75 |
| 101109 | 2023 | 2 | 55192.42 |
| 101109 | 2023 | 3 | 52421.49 |
| 101109 | 2023 | 4 | 56328.50 |
| 101109 | 2023 | 5 | 57419.20 |
| 101109 | 2023 | 6 | 75135.38 |
| 101109 | 2023 | 7 | 57240.51 |
| 101109 | 2023 | 8 | 49776.84 |
| 101109 | 2023 | 9 | 50912.83 |
| 101109 | 2023 | 10 | 79406.41 |
| 101109 | 2023 | 11 | 71912.10 |
| 101109 | 2023 | 12 | 83162.48 |
| 101109 | 2024 | 1 | 60652.90 |
| 101109 | 2024 | 2 | 33987.64 |
| 101109 | 2024 | 3 | 33693.06 |
| 101110 | 2022 | 5 | 45843.15 |
| 101110 | 2022 | 6 | 61213.07 |
| 101110 | 2022 | 7 | 47587.43 |
| 101110 | 2022 | 8 | 49755.38 |
| 101110 | 2022 | 9 | 38668.54 |
| 101110 | 2022 | 10 | 51085.62 |
| 101110 | 2022 | 11 | 50252.76 |
| 101110 | 2022 | 12 | 54660.01 |
| 101110 | 2023 | 1 | 42327.50 |
| 101110 | 2023 | 2 | 33983.23 |
| 101110 | 2023 | 3 | 36725.08 |
| 101110 | 2023 | 4 | 49210.58 |
| 101110 | 2023 | 5 | 57250.94 |
| 101110 | 2023 | 6 | 50591.92 |
| 101110 | 2023 | 7 | 50021.23 |
| 101110 | 2023 | 8 | 45758.96 |
| 101110 | 2023 | 9 | 43033.40 |
| 101110 | 2023 | 10 | 52427.85 |
| 101110 | 2023 | 11 | 70183.22 |
| 101110 | 2023 | 12 | 55249.31 |
| 101110 | 2024 | 1 | 59893.54 |
| 101110 | 2024 | 2 | 37693.37 |
| 101110 | 2024 | 3 | 41738.19 |
| 102111 | 2019 | 10 | 45630.18 |
| 102111 | 2019 | 11 | 34403.84 |
| 102111 | 2019 | 12 | 50369.84 |
| 102111 | 2020 | 1 | 37581.29 |
| 102111 | 2020 | 2 | 26603.22 |
| 102111 | 2020 | 3 | 41200.13 |
| 102111 | 2020 | 4 | 38072.67 |
| 102111 | 2020 | 5 | 61485.00 |
| 102111 | 2020 | 6 | 32228.27 |
| 102111 | 2020 | 7 | 32285.54 |
| 102111 | 2020 | 8 | 22713.86 |
| 102111 | 2020 | 9 | 41220.66 |
| 102111 | 2020 | 10 | 38328.61 |
| 102111 | 2020 | 11 | 52136.13 |
| 102111 | 2020 | 12 | 59550.84 |
| 102111 | 2021 | 1 | 33599.70 |
| 102111 | 2021 | 2 | 32729.34 |
| 102111 | 2021 | 3 | 35127.02 |
| 102111 | 2021 | 4 | 43948.96 |
| 102111 | 2021 | 5 | 62863.33 |
| 102111 | 2021 | 6 | 49978.29 |
| 102111 | 2021 | 7 | 44903.94 |
| 102111 | 2021 | 8 | 35736.22 |
| 102111 | 2021 | 9 | 45276.18 |
| 102111 | 2021 | 10 | 40295.87 |
| 102111 | 2021 | 11 | 57205.23 |
| 102111 | 2021 | 12 | 56329.54 |
| 102111 | 2022 | 1 | 40908.69 |
| 102111 | 2022 | 2 | 29826.71 |
| 102111 | 2022 | 3 | 30896.99 |
| 102111 | 2022 | 4 | 39566.98 |
| 102111 | 2022 | 5 | 63356.50 |
| 102111 | 2022 | 6 | 62146.51 |
| 102111 | 2022 | 7 | 43699.03 |
| 102111 | 2022 | 8 | 27354.80 |
| 102111 | 2022 | 9 | 37341.67 |
| 102111 | 2022 | 10 | 51251.84 |
| 102111 | 2022 | 11 | 54907.09 |
| 102111 | 2022 | 12 | 77431.22 |
| 102111 | 2023 | 1 | 50018.82 |
| 102111 | 2023 | 2 | 34667.70 |
| 102111 | 2023 | 3 | 47380.27 |
| 102111 | 2023 | 4 | 33408.09 |
| 102111 | 2023 | 5 | 49778.63 |
| 102111 | 2023 | 6 | 51324.63 |
| 102111 | 2023 | 7 | 45631.93 |
| 102111 | 2023 | 8 | 42452.77 |
| 102111 | 2023 | 9 | 39394.53 |
| 102111 | 2023 | 10 | 48633.20 |
| 102111 | 2023 | 11 | 63571.54 |
| 102111 | 2023 | 12 | 84882.05 |
| 102111 | 2024 | 1 | 52158.11 |
| 102111 | 2024 | 2 | 36653.85 |
| 102111 | 2024 | 3 | 50860.12 |
| 102112 | 2022 | 5 | 74967.27 |
| 102112 | 2022 | 6 | 67971.26 |
| 102112 | 2022 | 7 | 50911.08 |
| 102112 | 2022 | 8 | 51966.94 |
| 102112 | 2022 | 9 | 45638.85 |
| 102112 | 2022 | 10 | 61550.50 |
| 102112 | 2022 | 11 | 78764.79 |
| 102112 | 2022 | 12 | 97689.40 |
| 102112 | 2023 | 1 | 51046.23 |
| 102112 | 2023 | 2 | 42980.93 |
| 102112 | 2023 | 3 | 57012.13 |
| 102112 | 2023 | 4 | 60065.69 |
| 102112 | 2023 | 5 | 62042.92 |
| 102112 | 2023 | 6 | 46389.05 |
| 102112 | 2023 | 7 | 52676.26 |
| 102112 | 2023 | 8 | 58881.88 |
| 102112 | 2023 | 9 | 44830.88 |
| 102112 | 2023 | 10 | 55486.36 |
| 102112 | 2023 | 11 | 45572.86 |
| 102112 | 2023 | 12 | 83213.59 |
| 102112 | 2024 | 1 | 34942.55 |
| 102112 | 2024 | 2 | 48691.51 |
| 102112 | 2024 | 3 | 65374.47 |
#Visualização de Dados com ggplot2 ##Gráfico de barras: venda total por vendedor
ggplot(estat_vendedor, aes(x = vendedor, y = total_vendas)) +
geom_col() +
labs(title = "Total de Vendas por Vendedor", x = "Vendedor", y = "Total de Vendas")
##Gráfico de linhas: vendas mensais totais da empresa
ggplot(venda_mensal_geral, aes(x = mes, y = total_mensal, group = ano, color = as.factor(ano))) +
geom_line(size = 1) +
labs(title = "Tendência Mensal das Vendas", x = "Mês", y = "Total Mensal")## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
##Gráfico facetado: venda mensal por vendedor
ggplot(venda_mensal_vendedor, aes(x = mes, y = total_mensal, group = vendedor)) +
geom_line() +
facet_wrap(~ vendedor, scales = "free_y") +
labs(title = "Vendas Mensais por Vendedor", x = "Mês", y = "Total Mensal")
##Histograma da venda diária
ggplot(vendas, aes(x = venda_diaria)) +
geom_histogram(bins = 20) +
labs(title = "Distribuição das Vendas Diárias", x = "Venda Diária")
##Boxplot das vendas por mês
ggplot(vendas, aes(x = as.factor(mes), y = venda_diaria)) +
geom_boxplot() +
labs(title = "Vendas Diárias por Mês", x = "Mês", y = "Venda Diária")
##Boxplot das vendas por vendedor
ggplot(vendas, aes(x = vendedor, y = venda_diaria)) +
geom_boxplot() +
labs(title = "Distribuição das Vendas por Vendedor", x = "Vendedor", y = "Venda Diária")
#DESAFIO — Previsão de Vendas
# Série temporal mensal geral
ts_vendas <- ts(venda_mensal_geral$total_mensal, frequency = 12)
modelo <- auto.arima(ts_vendas)
previsao <- forecast(modelo, h = 6)
autoplot(previsao) +
labs(title = "Previsão de Vendas para os Próximos 6 Meses")
#Conclusão
A análise permitiu identificar padrões de vendas, desempenho dos vendedores, tendências mensais e distribuição dos valores diários. Os gráficos facilitam a visualização das variações ao longo do tempo, e o modelo ARIMA fornece uma estimativa da tendência futura da empresa.