104 lines
5.2 KiB
R
104 lines
5.2 KiB
R
library(ggplot2)
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library(dplyr)
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library(ggpubr)
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library(ggthemes)
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install.packages("gridExtra")
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library("gridExtra")
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install.packages("cowplot")
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library("cowplot")
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lech <- read.csv(file = "C:\\Users\\Lenovo\\Desktop\\MGR\\analiza_danych_sportowych\\ADS\\preprocessed_data\\club-lech-preprocessed.csv", fileEncoding = "utf-8", head = TRUE, sep=",")
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legia <- read.csv(file = "C:\\Users\\Lenovo\\Desktop\\MGR\\analiza_danych_sportowych\\ADS\\preprocessed_data\\club-legia-preprocessed.csv", fileEncoding = "utf-8", head = TRUE, sep=",")
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piast <- read.csv(file = "C:\\Users\\Lenovo\\Desktop\\MGR\\analiza_danych_sportowych\\ADS\\preprocessed_data\\club-piast-preprocessed.csv", fileEncoding = "utf-8", head = TRUE, sep=",")
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pogon <- read.csv(file = "C:\\Users\\Lenovo\\Desktop\\MGR\\analiza_danych_sportowych\\ADS\\preprocessed_data\\club-pogon-preprocessed.csv", fileEncoding = "utf-8", head = TRUE, sep=",")
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View(lech)
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lech <- transform(lech, Frekwencja = as.numeric(Frekwencja))
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legia <- transform(legia, Frekwencja = as.numeric(Frekwencja))
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piast <- transform(piast, Frekwencja = as.numeric(Frekwencja))
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pogon <- transform(pogon, Frekwencja = as.numeric(Frekwencja))
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lech$Data = as.Date(lech$Data, format="%d.%m.%Y")
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legia$Data = as.Date(legia$Data, format="%d.%m.%Y")
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piast$Data = as.Date(piast$Data, format="%d.%m.%Y")
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pogon$Data = as.Date(pogon$Data, format="%d.%m.%Y")
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sezon_lech <- filter(lech, Graj¹.u.siebie == "1", Sezon == "1")
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sezon_legia <- filter(legia, Graj¹.u.siebie == "1", Sezon == "1")
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sezon_piast <- filter(piast, Graj¹.u.siebie == "1", Sezon == "1")
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sezon_pogon <- filter(pogon, Graj¹.u.siebie == "1", Sezon == "1")
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lech_u_siebie <- filter(lech, Graj¹.u.siebie == "1")
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View(lech_u_siebie)
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result_colors <- c('#d9261e','#69d100', '#69d1cd')
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# Wykres liniowy przedstawiaj¹cy frekwencjê Lecha na swoim stadionie z oznaczeniem rezulatów spotkañ
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plot1 <- ggplot(data = lech_u_siebie, aes(x = Data, y = Frekwencja, group = 1, color = as.factor(Wygrana))) +
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geom_point(size = 2) +
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scale_color_manual(values=result_colors, labels = c("Przegrana", "Zwyciêstwo", "Remis")) +
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geom_line() +
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theme(axis.text.x = element_text(angle = 15, vjust = 0.5, hjust=1), axis.title.x = element_blank()) +
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labs(color = "Rezultat spotkania") +
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ggtitle("Frekwencja Lecha Poznañ na swoim stadionie w latach 2016-2019") +
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scale_x_date(date_breaks = "1 month", date_labels = "%b %Y")
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show(plot1)
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# Wykres liniowy przedstawiaj¹cy frekwencjê Lecha, Legii, Piasta i Pogoni w meczach rozgrywanych na swoim stadionie w sezonie YYYY
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lech_plot <- ggplot(data = sezon_lech, aes(x = Data, y = Frekwencja, group = 1, color = as.factor(Wygrana), alpha=0.5)) +
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geom_point(size = 3) +
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theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
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scale_color_manual(values=result_colors) +
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geom_line(size = 1) + theme(legend.position="none") +
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scale_x_date(date_breaks = "1 month", date_labels = "%m.%Y")
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legia_plot <- ggplot(data = sezon_legia, aes(x = Data, y = Frekwencja, group = 1, color = as.factor(Wygrana), alpha=0.5)) +
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geom_point(size = 3, alpha=0.5) +
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theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
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scale_color_manual(values=result_colors) +
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geom_line(size = 1) + theme(legend.position="none") +
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scale_x_date(date_breaks = "1 month", date_labels = "%m.%Y")
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piast_plot <- ggplot(data = sezon_piast, aes(x = Data, y = Frekwencja, group = 1, color = as.factor(Wygrana), alpha=0.5)) +
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geom_point(size = 3, alpha=0.5) +
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theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
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scale_color_manual(values=result_colors) +
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geom_line(size = 1) + theme(legend.position="none") +
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scale_x_date(date_breaks = "1 month", date_labels = "%m.%Y")
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pogon_plot <- ggplot(data = sezon_pogon, aes(x = Data, y = Frekwencja, group = 1, color = as.factor(Wygrana), alpha=0.5)) +
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geom_point(size = 3, alpha=0.5) +
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theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
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scale_color_manual(values=result_colors) +
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geom_line(size = 1) + theme(legend.position="none") +
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scale_x_date(date_breaks = "1 month", date_labels = "%m.%Y")
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plot_grid(lech_plot, legia_plot, piast_plot, pogon_plot,
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labels=c("Lech Poznañ", "Legia Warszawa", "Piast Gliwice", "Pogoñ Szczecin"),
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ncol = 2, nrow = 2)
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# Mecze Lecha Poznañ rozegrane na swoim stadionie w sezonach 2016/2019 z uwzglêdnieniem godziny i dnia tygodnia
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plot2 <- ggplot(lech_u_siebie, aes(x=Data, y=Dzieñ.tygodnia, color=Godzina, size=Frekwencja)) +
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geom_point(alpha=0.5) +
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scale_size(range = c(3, 30)) +
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theme(axis.text.x = element_text(angle = 20, vjust = 0.5, hjust=1), axis.title.x = element_blank()) +
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scale_x_date(date_breaks = "1 month", date_labels = "%m.%Y")
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show(plot2)
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# Mecze Lecha Poznañ rozegrane na swoim stadionie w sezonach 2016-2019 z uwzglêdnieniem Temperatury
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plot3 <- ggplot(lech_u_siebie, aes(x=Data, y=Temperatura, color=Godzina, size=Frekwencja)) +
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geom_point(alpha=0.5) +
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scale_size(range = c(0, 15)) +
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theme(axis.text.x = element_text(angle = 30, vjust = 0.5, hjust=1), axis.title.x = element_blank()) +
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scale_x_date(date_breaks = "1 month", date_labels = "%m.%Y")
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show(plot3)
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