.Rhistory

c(1:10)
my_vector+10
my_vector<-c(1:10)
my_vector+10
my_vector+c(1,2)
c(100,my_vector,200)
seq(1,10)
seq(1,10,bye=2)
seq(1,10,by=2)
seq(20,120,length=10)
seq(20,120,length=10,length.out = 10)
rep(0,times=100)
my_vector >5
my_vector+na
my_vector + NA
c(1,NA,5)+5
dim((my_vector)
dim(my_vector)
dim(my_vector)
dim(my_vector)<-c(10,10)
matrix(100,nrow=10,ncol=10)
my_matrix2<- matrix(1:20,nrow=4ncol=5)
my_matrix2<- matrix(1:20,nrow=4,ncol=5)
cbind(my_matrix2,1)
dim(my_matrix2)
my_data <-sdvbhc
my_data1 <- chakri
my_data1<- data.frame(2,my_matrix2)
my_mean <- function(veet)
{ sum(vect)/length(vector)}
my_mean(c(1:5))
mean(c(1:5))
1:10
1:10
c(1,10)
sum(1,5,4,5)
clearPushBack()
clearPushBack(5)
clearPushBack()
clearPushBack(connection=5)
mean(1,5,4,4,5,6)
str(cars1)
sum(1,2,3,5,6)
mean(1,2,5,4)
library(rpart)
ifx<0{print("x is a negative number")}
if(x<0){print("x is a negative number")}
x<-4
if(x<0){print("x is a negative number")}
if(x<0){print("x is a negative number")}
if(x<0){print("x is a negative number")}
x<-5
if(x<0) {print("x is a negative no")}
x<--2
x<--5
if(x<0) {print("x is a negative no")}
if(x<0){print("x is a negative no")}else{print("x is a positive no or zero")}
x<5
x<-6
if(x<0){print("x is a negative no")}else{print("x is a positive no or zero")}
if(x<0){print("xis a negative no")}elseif(x==0){print("x is zero")}else{print("x is a positiveno")}
if(x<0){print("xis a negative no")}else if(x==0){print("x is zero")}else{print("x is a positiveno")}
install.packages("twitteR")
install.packages("ROAuth")
library("twitteR")
library("ROAuth")
download.file(url="http://curl.haxx.se/ca/cacert.pem",destfile="cacert.pem")
authURL='https://api.twitter.com/oauth/authorize')
consumerSecret='	h58VQnikdy5tuzzGTJv6DMPf97wHW9zG1o6PH9fK9HVmJ9dYjn',
consumerSecret='	h58VQnikdy5tuzzGTJv6DMPf97wHW9zG1o6PH9fK9HVmJ9dYjn',
consumerSecret='h58VQnikdy5tuzzGTJv6DMPf97wHW9zG1o6PH9fK9HVmJ9dYjn',
library(lpsolve)
library(lpSolve)
library(lpSolve)
install.packages("lpSolve")
library(lpSolve)
obj.fun->c(20,40)
obj.fun<-c(20,40)
constr <- matrix (c(30 , 20 , 5 , 10 , 1 , 1) , ncol = 2 , byrow =
TRUE )
constr . dir <- c(" <=", " <=", " >=")
rhs <- c(2700 , 850 , 95)
constr.dir <- c(" <=", " <=", " >=")
?dply
??dplyr
`New.Microsoft.Excel.Worksheet.(2)` <- read.csv("C:/Users/chakradhar/Desktop/Data and Formats/New Microsoft Excel Worksheet (2).csv", header=FALSE)
View(`New.Microsoft.Excel.Worksheet.(2)`)
check_my<-function(x){
z<-data.frame()
y<-as.character(x)
a<-1
b<-1
n<-1
for(i in 1:12){
if(a<=4){
if(substring(y,i,i)==":"|substring(y,i,i)=="*"|substring(y,i,i)==""&&substring(y,i-1,i-1)!=""){
z[1,a]<-as.numeric(substring(y,b,i-1))
b<-i+1
a<-a+1
}
if(substring(y,i,i)==""&&substring(y,i-1,i-1)==""){
z[1,a]<-0
a<-a+1
}
}
}
return(z)
}
find_seq<-function(x){
z<-check_my(x[1])
for(i in 2:length(x)){
z<-rbind(z,check_my(x[i]))
}
return(z)
}
data<-read.csv(file.choose(),header=T)
x<-data[,7]
find_seq(x)
y<-find_seq(x)
View(y)
View(data)
data<-read.csv(file.choose(),header = T)
data<-read.csv(file.choose(),header = T)
data<-read.csv(file.choose(),header = T)
View(data)
y<-find_seq(data[,2])
head(y)
View(y)
write.csv(y,file="res.csv")
getwd()
temp<-y[,1]==0
y[temp,1]=1
y[temp]
y[temp,1]
View(y)
write.csv(y,file="res1.csv")
View(data)
getwd
getwd()
data<-read.csv(file.choose(),header = T)
data<-read.csv(file.choose(),header = T)
data<-read.csv(file.choose(),header = T)
data<-read.csv(file.choose(),header = T)
data<-read.csv(file.choose(),header = T)
View(data)
x<-data[,"Crp1_rat_K"]
head(x)
y<-find_seq(x)
head(y)
z<-y[,1]!=0 & data[,'Crp1_var_K']==0 & data[,'Crp1_totare_K']!=0
data[z,1]
z<-y[,1]!=0 & data[,"Crp1_mx1_K
"]==0 & data[,"Crp1_totare_K
"]
z<-y[,1]!=0 & data[,'Crp1_mx1_K']==0 & data[,'Crp1_totare_K']!=0
data[z,1]
crop1<-c(data[z,1])
z<-y[,2]!=0 & data[,'Crp1_mx1_K']==0 & data[,'Crp1_totare_K']!=0
crop1<-c(data[z,1])
crop1
z<-y[,3]!=0 & data[,'Crp1_mx2_K']==0 & data[,'Crp1_totare_K']!=0
data[z,1]
z<-y[,4]!=0 & data[,'Crp1_mx3_K']==0 & data[,'Crp1_totare_K']!=0
data[z,1]
z<-y[,1]!=0 & data[,'Crp2_var_K']==0 & data[,'Crp2_totare_K']!=0
data[z,1]
x<-data[,"Crp2_rat_K"]
y<-find_seq(x)
head(y)
z<-y[,1]!=0 & data[,'Crp2_var_K']==0 & data[,'Crp2_totare_K']!=0
data[z,1]
z<-y[,2]!=0 & data[,'Crp2_mx1_K']==0 & data[,'Crp2_totare_K']!=0
data[z,1]
crp2<-data[z,1]\
crp2<-data[z,1]
crop1<-c(crop1,10140,10708)
crop1
z<-y[,3]!=0 & data[,'Crp2_mx2_K']==0 & data[,'Crp2_totare_K']!=0
data[z,1]
z<-y[,4]!=0 & data[,'Crp2_mx3_K']==0 & data[,'Crp2_totare_K']!=0
data[z,1]
x<-data[,"Crp3_rat_K"]
y<-find_seq(x)
head(y)
z<-y[,1]!=0 & data[,'Crp3_var_K']==0 & data[,'Crp3_totare_K']!=0
data[z,1]
z<-y[,2]!=0 & data[,'Crp3_mx1_K']==0 & data[,'Crp3_totare_K']!=0
data[z,1]
crop3<-data[z,1]
z<-y[,3]!=0 & data[,'Crp3_mx2_K']==0 & data[,'Crp3_totare_K']!=0
data[z,1]
x<-data[,"Crp4_rat_K"]
y<-find_seq(x)
head(y)
z<-y[,1]!=0 & data[,'Crp4_var_K']==0 & data[,'Crp4_totare_K']!=0
data[z,1]
z<-y[,2]!=0 & data[,'Crp4_mx1_K']==0 & data[,'Crp4_totare_K']!=0
data[z,1]
crop4<-data[z,1]
z<-y[,3]!=0 & data[,'Crp4_mx2_K']==0 & data[,'Crp4_totare_K']!=0
data[z,1]
x<-data[,"Crp5_rat_K"]
y<-find_seq(x)
z<-y[,1]!=0 & data[,'Crp5_var_K']==0 & data[,'Crp5_totare_K']!=0
data[z,1]
z<-y[,2]!=0 & data[,'Crp5_mx_K']==0 & data[,'Crp5_totare_K']!=0
data[z,1]
crop5<-data[z,1]
x<-data[,"Crp6_rat_K"]
y<-find_seq(x)
head(y)
z<-y[,1]!=0 & data[,'Crp6_var_K']==0 & data[,'Crp6_totare_K']!=0
data[z,1]
z<-y[,2]!=0 & data[,'Crp6_mx_K']==0 & data[,'Crp6_totare_K']!=0
data[z,1]
View(crop1)
crop1
crp2
crop3
crop4
crop5
crop6
setwd("C:/Users/chakradhar/Desktop/Databyte")
library(readxl)
databyte_project1 <- read_excel("C:/Users/chakradhar/Desktop/Databyte/databyte project1.xlsx")
View(databyte_project1)
summary(databyte_project1)
plot(databyte_project1, ylab="Retail", xlab="year")
tsdisplay(diff(databyte_project1,4))
fit <- Arima(databyte_project1, order=c(0,1,1), seasonal=c(0,1,1))
auto.arima(databyte_project1)