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library(ggplot2)
library(plotly)
library(dplyr)
library(readr)
library(lubridate)
library(stringr)
library(ggthemes)
library(extrafont)
library(gapminder)

official_table <- read.csv(file='AAPL_Pre_Official_DB_7_31.csv',check.names=F,stringsAsFactors = F)#Reading the official file
month_summary<- subset(official_table) %>% group_by(Month) %>% summarize(Mean_volume=mean(Volume), .groups = 'keep') #create summary table for months by volume 
month_plt <- ggplot(month_summary,aes(x=Month,y=Mean_volume)) #import dataset into ggplot2
month_plt + geom_line() + 
  
  theme_minimal() +
  scale_fill_gradient(low = "black", high = "#8de1f0") +
  labs(title = "Total Volume By months") +

  theme(panel.grid.major=element_blank(),
        panel.grid.minor=element_blank(),
        text = element_text(family="DM Sans"),
        plot.title = element_text(hjust = 0.5),
        legend.position = "none")

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year_summary_season <- subset(official_table) %>% group_by(Year, Season)  %>% summarize(Mean_volume=mean(Volume), .groups = 'keep') #create summary table


plt_year_summary_season <- ggplot(year_summary_season,aes(x=Year,y=Mean_volume,color=Season)) #import dataset into ggplot2

plt_year_summary_season + geom_point() + labs(x="Year", y="Mean_volume", color="Season", title ="Summary of Volume per Season & Year" )#add scatter plot with labels

year_lastTenSeason <- subset(official_table, Year > 2015 & Year <= 2020) %>% group_by(Year, Season)  %>% summarize(Mean_volume=mean(Volume), .groups = 'keep') #create summary table
plt_year_lastTenSeason <- ggplot(year_lastTenSeason,aes(x=Year,y=Mean_volume,color=Season)) #import dataset into ggplot2

plt_year_lastTenSeason + geom_point() + labs(x="Year", y="Mean_volume", color="Season", title="Summary of Volume in Last 5 Years for Seasons")#add scatter plot with labels

year_summary_quarter <- subset(official_table) %>% group_by(Year, Quarter)  %>% summarize(Mean_volume=mean(Volume), .groups = 'keep') #create summary table

plt_year_summary_quarter <- ggplot(year_summary_quarter,aes(x=Year,y=Mean_volume,color=Quarter)) #import dataset into ggplot2

plt_year_summary_quarter + geom_point() + labs(x="Year", y="Mean_volume", color="Quarter", title ="Summary of Volume per Quarters & Year")#add scatter plot with labels

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year_lastTenQuarter <- subset(official_table, Year > 2015 & Year <= 2020) %>% group_by(Year, Quarter)  %>% summarize(Mean_volume=mean(Volume), .groups = 'keep') #create summary table
plt_year_lastTenQuarter <- ggplot(year_lastTenQuarter,aes(x=Year,y=Mean_volume,color=Quarter)) #import dataset into ggplot2

plt_year_lastTenQuarter + geom_point() + labs(x="Year", y="Mean_volume", color="Quarters", title="Summary of Volume in Last 5 Years for Quarters")#add scatter plot with labels

month_summary_Gain_Loss_Open_season <- subset(official_table) %>% group_by(Gain_Loss_Open, Month , Season)  %>% summarize(Mean_volume=mean(Volume), .groups = 'keep') #create summary table for Gain_Loss_Open in each seasons for the months

plt_month_summary_Gain_Loss_Open_season <- ggplot(month_summary_Gain_Loss_Open_season,aes(x=Month,y=Mean_volume,color=Season,shape = Gain_Loss_Open)) #import dataset into ggplot2

plt_month_summary_Gain_Loss_Open_season + geom_point() + labs(x="Month", y="Mean_volume", color="Season", shape ="Gain_Loss_Open")#add scatter plot with labels

month_summary_Gain_Loss_Open_quarter <- subset(official_table) %>% group_by(Gain_Loss_Open, Month , Quarter)  %>% summarize(Mean_volume=mean(Volume), .groups = 'keep') #create summary table for Gain_Loss_Open in each quarters for the months

plt_month_summary_Gain_Loss_Open <- ggplot(month_summary_Gain_Loss_Open_quarter,aes(x=Month,y=Mean_volume,color=Quarter,shape = Gain_Loss_Open)) #import dataset into ggplot2


plt_month_summary_Gain_Loss_Open + geom_point() + labs(x="Month", y="Mean_volume", color="Quarter", shape ="Gain_Loss_Open")#add scatter plot with labels

#create summary table for quarter by volume 
quarter_summary_<- subset(official_table) %>% group_by(Quarter) %>% 
  summarize(Mean_volume=mean(Volume), .groups = 'keep') 


##create summary table for Gain_Loss_Open in each quarter 
quarter_summary_Gain_Loss_Open <- subset(official_table) %>% 
  group_by(Gain_Loss_Open, Quarter)  %>% 
  summarize(Mean_volume=mean(Volume), .groups = 'keep') #

#import dataset into ggplot2
plt_quarter_summary_Gain_Loss_Open <- 
  ggplot(quarter_summary_Gain_Loss_Open,
         aes(x=Quarter,y=Mean_volume,color=Quarter,shape = Gain_Loss_Open)) 

#add scatter plot with labels
plt_quarter_summary_Gain_Loss_Open + geom_point() + 
  labs(x="Quarter", y="Mean_volume", title ="Quarter_G/L_Open",
       color="Quarter", shape ="Gain_Loss_Open")

##create summary table for Gain_Loss_Closein each quarter 
quarter_summary_Gain_Loss_Close <- subset(official_table) %>% 
  group_by(Gain_Loss_Close, Quarter)  %>% 
  summarize(Mean_volume=mean(Volume), .groups = 'keep') #

#import dataset into ggplot2
plt_quarter_summary_Gain_Loss_Close <- 
  ggplot(quarter_summary_Gain_Loss_Close,
         aes(x=Quarter,y=Mean_volume,color=Quarter,shape = Gain_Loss_Close)) 

#add scatter plot with labels
plt_quarter_summary_Gain_Loss_Close + geom_point() + 
  labs(x="Quarter", y="Mean_volume", title ="Quarter_G/L_Close",
       color="Quarter", shape ="Gain_Loss_Close")

##create summary table for Gain_Loss_High in each quarter 
quarter_summary_Gain_Loss_High <- subset(official_table) %>% 
  group_by(Gain_Loss_High, Quarter)  %>% 
  summarize(Mean_volume=mean(Volume), .groups = 'keep') #

#import dataset into ggplot2
plt_quarter_summary_Gain_Loss_High <- 
  ggplot(quarter_summary_Gain_Loss_High,
         aes(x=Quarter,y=Mean_volume,color=Quarter,shape = Gain_Loss_High)) 

#add scatter plot with labels
plt_quarter_summary_Gain_Loss_High + geom_point() + 
  labs(x="Quarter", y="Mean_volume", title ="Quarter_G/L_High",
       color="Quarter", shape ="Gain_Loss_High")

##create summary table for Gain_Loss_Low in each quarter 
quarter_summary_Gain_Loss_Low <- subset(official_table) %>% 
  group_by(Gain_Loss_Low, Quarter)  %>% 
  summarize(Mean_volume=mean(Volume), .groups = 'keep') #

#import dataset into ggplot2
plt_quarter_summary_Gain_Loss_Low <- 
  ggplot(quarter_summary_Gain_Loss_Low,
         aes(x=Quarter,y=Mean_volume,color=Quarter,shape = Gain_Loss_Low)) 

#add scatter plot with labels
plt_quarter_summary_Gain_Loss_Low + geom_point() + 
  labs(x="Quarter", y="Mean_volume", title ="Quarter_G/L_Low",
       color="Quarter", shape ="Gain_Loss_Low")

#create summary table for season by volume 
season_summary_<- subset(official_table) %>% group_by(Season) %>% 
  summarize(Mean_volume=mean(Volume), .groups = 'keep')

##create summary table for Gain_Loss_Open in each season
season_summary_Gain_Loss_Open <- subset(official_table) %>% 
  group_by(Gain_Loss_Open, Season)  %>% 
  summarize(Mean_volume=mean(Volume), .groups = 'keep') #

#import dataset into ggplot2
plt_season_summary_Gain_Loss_Open <- 
  ggplot(season_summary_Gain_Loss_Open,
         aes(x=Season,y=Mean_volume,color=Season,shape = Gain_Loss_Open)) 

#add scatter plot with labels
plt_season_summary_Gain_Loss_Open + geom_point() + 
  labs(x="Season", y="Mean_volume", title ="Season_G/L_Open",
       color="Season", shape ="Gain_Loss_Open")

##create summary table for Gain_Loss_Close in each season
season_summary_Gain_Loss_Close <- subset(official_table) %>% 
  group_by(Gain_Loss_Close, Season)  %>% 
  summarize(Mean_volume=mean(Volume), .groups = 'keep') #

#import dataset into ggplot2
plt_season_summary_Gain_Loss_Close <- 
  ggplot(season_summary_Gain_Loss_Close,
         aes(x=Season,y=Mean_volume,color=Season,shape = Gain_Loss_Close)) 

#add scatter plot with labels
plt_season_summary_Gain_Loss_Close + geom_point() + 
  labs(x="Season", y="Mean_volume", title ="Season_G/L_Close",
       color="Season", shape ="Gain_Loss_Close")

##create summary table for Gain_Loss_High in each season
season_summary_Gain_Loss_High <- subset(official_table) %>% 
  group_by(Gain_Loss_High, Season)  %>% 
  summarize(Mean_volume=mean(Volume), .groups = 'keep') #

#import dataset into ggplot2
plt_season_summary_Gain_Loss_High <- 
  ggplot(season_summary_Gain_Loss_High,
         aes(x=Season,y=Mean_volume,color=Season,shape = Gain_Loss_High)) 

#add scatter plot with labels
plt_season_summary_Gain_Loss_High + geom_point() + 
  labs(x="Season", y="Mean_volume", title ="Season_G/L_High",
       color="Season", shape ="Gain_Loss_High")

##create summary table for Gain_Loss_Low in each season
season_summary_Gain_Loss_Low <- subset(official_table) %>% 
  group_by(Gain_Loss_Low, Season)  %>% 
  summarize(Mean_volume=mean(Volume), .groups = 'keep') #

#import dataset into ggplot2
plt_season_summary_Gain_Loss_Low <- 
  ggplot(season_summary_Gain_Loss_Low,
         aes(x=Season,y=Mean_volume,color=Season,shape = Gain_Loss_Low)) 

#add scatter plot with labels
plt_season_summary_Gain_Loss_Low + geom_point() + 
  labs(x="Season", y="Mean_volume", title ="Season_G/L_Low",
       color="Season", shape ="Gain_Loss_Low")

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