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library(dplyr) | |
day<-read.csv("day.csv") | |
hour<-read.csv("hour.csv") | |
#1 Dias de la semana# | |
par(mfrow=c(1,2), oma=c(3,1,4,0) | |
data<-tbl_df(day) | |
day %>%filter(yr==0) %>% select(cnt) %>%summary() | |
day %>% filter(yr==0) %>% select(weekday, cnt) %>%plot(col="orange", main="Bicicletas por dias de la semana, year 1", ylab="Numero de bicicletas alquiladas", xlab="Dias de la semana") | |
day %>% filter(yr==1) %>% select(weekday, cnt) %>%plot(col="orange", main="Bicicletas por dias de la semana, year 2", ylab="Numero de bicicletas alquiladas", xlab="Dias de la semana") | |
mtext("Demanda por dia en cada anio", side=3, outer=TRUE, line=-1,cex=1.5) | |
#demanda por temporada en el a??o 1# | |
par(mfrow=c(2,4)) | |
day %>% filter(season==1,yr==0) %>% select(weekday, cnt) %>%plot(type="h", col="orange",main="Demanda en Primavera, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Dias de la semana") | |
day %>% filter(season==2,yr==0) %>% select(weekday, cnt) %>%plot(type="h", col="orange",main="Demanda en Verano, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Dias de la semana") | |
day %>% filter(season==3,yr==0) %>% select(weekday, cnt) %>%plot(type="h", col="orange",main="Demanda en Otono, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Dias de la semana") | |
day %>% filter(season==4,yr==0) %>% select(weekday, cnt) %>%plot(type="h", col="orange",main="Demanda en Invierno,Year 1", ylab="Numero de bicicletas alquiladas", xlab="Dias de la semana") | |
mtext("Demanda por dia en cada temporada del 2011", side=3, outer=TRUE, line=-1,cex=1.5) | |
#Demanda por temporada en el a??o 2# | |
day %>% filter(season==1,yr==1) %>% select(weekday, cnt) %>%plot(type="h", col="orange",main="Demanda en Primavera, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Dias de la semana") | |
day %>% filter(season==2,yr==1) %>% select(weekday, cnt) %>%plot(type="h", col="orange",main="Demanda en Verano, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Dias de la semana") | |
day %>% filter(season==3,yr==1) %>% select(weekday, cnt) %>%plot(type="h", col="orange",main="Demanda en Otono, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Dias de la semana") | |
day %>% filter(season==4,yr==1) %>% select(weekday, cnt) %>%plot(type="h", col="orange",main="Demanda en Invierno,Year 2", ylab="Numero de bicicletas alquiladas", xlab="Dias de la semana") | |
mtext("Demanda por dia en cada temporada del 2012", side=3, outer=TRUE, line=-1,cex=1.5) | |
###Conclusiones: sabado y domingo son los dias de la semana con mas demanda### | |
#2 dias festivos# | |
day %>% filter(season==1,yr==0) %>% select(holiday, cnt) %>%plot(col="blue",main="Primavera, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Dias festivos") | |
day %>% filter(season==2,yr==0) %>% select(holiday, cnt) %>%plot(col="blue",main="Verano, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Dias festivos") | |
day %>% filter(season==3,yr==0) %>% select(holiday, cnt) %>%plot(col="blue",main="Otono, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Dias festivos") | |
day %>% filter(season==4,yr==0) %>% select(holiday, cnt) %>%plot(col="blue",main="Invierno, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Dias festivos") | |
day %>% filter(season==1,yr==1) %>% select(holiday, cnt) %>%plot(col="blue",main="Primavera, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Dias festivos") | |
day %>% filter(season==2,yr==1) %>% select(holiday, cnt) %>%plot(col="blue",main="Verano, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Dias festivos") | |
day %>% filter(season==3,yr==1) %>% select(holiday, cnt) %>%plot(col="blue",main="Otono, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Dias festivos") | |
day %>% filter(season==4,yr==1) %>% select(holiday, cnt) %>%plot(col="blue",main="Invierno, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Dias festivos") | |
##Conclusion: La demanda de bicicletas tiende a bajar en los holidays## | |
#3 humedad# | |
day %>% filter(season==1,yr==0) %>% select(hum, cnt) %>%plot(type="h", col="purple",main="Primavera, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Humedad") | |
day %>% filter(season==2,yr==0) %>% select(hum, cnt) %>%plot(type="h", col="purple",main="Verano, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Humedad") | |
day %>% filter(season==3,yr==0) %>% select(hum, cnt) %>%plot(type="h", col="purple",main="Otono, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Humedad") | |
day %>% filter(season==4,yr==0) %>% select(hum, cnt) %>%plot(type="h", col="purple",main="Invierno, Year 1", ylab="Numero de bicicletas alquiladas", xlab="Humedad") | |
mtext("Demanda segun la humedad en cada temporada del 2011", side=3, outer=TRUE, line=-1,cex=1.5) | |
day %>% filter(season==1,yr==1) %>% select(hum, cnt) %>%plot(type="h", col="purple",main="Primavera, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Humedad") | |
day %>% filter(season==2,yr==1) %>% select(hum, cnt) %>%plot(type="h", col="purple",main="Verano, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Humedad") | |
day %>% filter(season==3,yr==1) %>% select(hum, cnt) %>%plot(type="h", col="purple",main="Otono, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Humedad") | |
day %>% filter(season==4,yr==1) %>% select(hum, cnt) %>%plot(type="h", col="purple",main="Invierno, Year 2", ylab="Numero de bicicletas alquiladas", xlab="Humedad") | |
mtext("Demanda segun la humedad en cada temporada del 2012", side=3, outer=TRUE, line=-1,cex=1.5) | |
#Conclusion: cuando la humedad esta a 60%, existe mas demanda# | |
#4 velocidad del viento# | |
day %>% filter(season==1,yr==0) %>% select(windspeed, cnt) %>%plot(col="red",main="Primavera, Year 1", ylab="Numero de bicicletas alquiladas", xlab="velocidad del viento") | |
day %>% filter(season==2,yr==0) %>% select(windspeed, cnt) %>%plot(col="red",main="Verano, Year 1", ylab="Numero de bicicletas alquiladas", xlab="velocidad del viento") | |
day %>% filter(season==3,yr==0) %>% select(windspeed, cnt) %>%plot(col="red",main="Otono, Year 1", ylab="Numero de bicicletas alquiladas", xlab="velocidad del viento") | |
day %>% filter(season==4,yr==0) %>% select(windspeed, cnt) %>%plot(col="red",main="Invierno, Year 1", ylab="Numero de bicicletas alquiladas", xlab="velocidad del viento") | |
mtext("Demanda segun velocidad del viento en cada temporada del 2011", side=3, outer=TRUE, line=-1,cex=1.5) | |
day %>% filter(season==1,yr==1) %>% select(windspeed, cnt) %>%plot(col="red",main="Primavera, Year 2", ylab="Numero de bicicletas alquiladas", xlab="velocidad del viento") | |
day %>% filter(season==2,yr==1) %>% select(windspeed, cnt) %>%plot(col="red",main="Verano, Year 2", ylab="Numero de bicicletas alquiladas", xlab="velocidad del viento") | |
day %>% filter(season==3,yr==1) %>% select(windspeed, cnt) %>%plot(col="red",main="Otono, Year 2", ylab="Numero de bicicletas alquiladas", xlab="velocidad del viento") | |
day %>% filter(season==4,yr==1) %>% select(windspeed, cnt) %>%plot(col="red",main="Invierno, Year 2", ylab="Numero de bicicletas alquiladas", xlab="velocidad del viento") | |
mtext("Demanda segun velocidad del viento en cada temporada del 2012", side=3, outer=TRUE, line=-1,cex=1.5) | |
# La velocidad del viento ideal en verano y en primavera es aprox. de 16.75k/h. Y | |
#en otono e invierno, es de aprox. de 6.7km/h# | |
##5 temperatura# | |
day %>% filter(season==1,yr==0) %>% select(atemp, cnt) %>%plot(col="20", main="Primavera", ylab="Numero de bicicletas alquiladas", xlab="Feels like") | |
day %>% filter(season==2,yr==0) %>% select(atemp, cnt) %>%plot(col="20", main="Verano", ylab="Numero de bicicletas alquiladas", xlab="Feels like") | |
day %>% filter(season==3,yr==0) %>% select(atemp, cnt) %>%plot(col="20", main="Otono", ylab="Numero de bicicletas alquiladas", xlab="Feels like") | |
day %>% filter(season==4,yr==0) %>% select(atemp, cnt) %>%plot(col="20", main="Invierno", ylab="Numero de bicicletas alquiladas", xlab="Feels like") | |
mtext("Demanda segun temperatura en cada temporada del 2011", side=3, outer=TRUE, line=-1,cex=1.5) | |
day %>% filter(season==1,yr==1) %>% select(atemp, cnt) %>%plot(col="20", main="Primavera", ylab="Demanda de bicicletas") | |
day %>% filter(season==2,yr==1) %>% select(atemp, cnt) %>%plot(col="20", main="Verano", ylab="Demanda de bicicletas") | |
day %>% filter(season==3,yr==1) %>% select(atemp, cnt) %>%plot(col="20", main="Otono", ylab="Demanda de bicicletas") | |
day %>% filter(season==4,yr==1) %>% select(atemp, cnt) %>%plot(col="20", main="Invierno", ylab="Demanda de bicicletas") | |
mtext("Demanda segun temperatura en cada temporada del 2012", side=3, outer=TRUE, line=-1,cex=1.5) | |
#La temperatura ideal en primavera es de 25 grados, en verano e invierno es de 27.5 grados y en otono es de 30 grados. | |
day %>% filter(season,yr==0) %>% select(mnth, cnt) %>%plot(col="20", main="2011", ylab="Demanda de bicicletas", xlab="meses del anio") | |
day %>% filter(season,yr==1) %>% select(mnth, cnt) %>%plot(col="20", main="2012", ylab="Demanda de bicicletas", xlab="meses del anio") | |
mtext("Demanda por mes en cada anio", side=3, outer=TRUE, line=-1,cex=1.5) | |
#En el quinto, sexto, septimo y octavo mes hay mas demanda. En el 2012 es de 8714, y en el 2011 es de 6043# |
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