The complexity of an algorithm is a function that defines the efficiency of the algorithm in terms of the amount of data and time taken by the algorithm to process.
The complexity of an algorithm is a function that defines the efficiency of the algorithm in terms of the amount of data and time taken by the algorithm to process.
# Create the data for the chart marks <- c(70,82,96,80,90) subject <- c("DBMS","IOT","C++","JAVA","PYTHON") png(file = "subject_marks.png") # Plot the bar chart barplot(marks,names.arg=subject,xlab="subjects",ylab="marks",col="red", main="Subject-Marks chart",border="black") # Save the file deRead more
# Create the data for the chart
marks <- c(70,82,96,80,90)
subject <- c("DBMS","IOT","C++","JAVA","PYTHON")
png(file = "subject_marks.png")
# Plot the bar chart
barplot(marks,names.arg=subject,xlab="subjects",ylab="marks",col="red",
main="Subject-Marks chart",border="black")
# Save the file
dev.off()
#output
what is complexity in data structure?
The complexity of an algorithm is a function that defines the efficiency of the algorithm in terms of the amount of data and time taken by the algorithm to process.
The complexity of an algorithm is a function that defines the efficiency of the algorithm in terms of the amount of data and time taken by the algorithm to process.
See lessAlpha 125.5 0 Beta 235.6 1 Beta 212.03 0 Beta 211.30 0 Alpha 265.46 1 File Name – Dataframe.csv Which …
ANSWER: D) csv2(‘Dataframe.csv’,header=FALSE,sep=’,’)
ANSWER: D) csv2(‘Dataframe.csv’,header=FALSE,sep=’,’)
See lessWrite an R program for following operations:- a) First make two separate files (word, excel) and then perform import and …
DOWNLOAD BELOW ATTACHMENT FOR ANSWER ALSO, SUPPORT US BY VOTING UP ANSWERS.
DOWNLOAD BELOW ATTACHMENT FOR ANSWER
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See lessWrite an R programme to add a new column in a given data frame.
data1 =data.frame( subject = c("C++", "PYTHON", "IOT", "DBMS", "DS"), mark= c(78,67,89,98,88) ) print(data1) #add new column to existing one data1<-data.frame(grade=c("B+","B", "A","A+","A"),data1) data1
data1 =data.frame( subject = c("C++", "PYTHON", "IOT", "DBMS", "DS"), mark= c(78,67,89,98,88) ) print(data1) #add new column to existing one data1<-data.frame(grade=c("B+","B", "A","A+","A"),data1) data1See lessWrite an R program to change a column name of a given data frame.
data1 =data.frame( subject = c("C++", "PYTHON", "IOT", "DBMS", "DS"), mark= c(78,67,89,98,88) ) print(data1) #change column name "mark to NEW_MARKS" names(data1)[2] <- 'NEW_MARKS' data1
data1 =data.frame( subject = c("C++", "PYTHON", "IOT", "DBMS", "DS"), mark= c(78,67,89,98,88) ) print(data1) #change column name "mark to NEW_MARKS" names(data1)[2] <- 'NEW_MARKS' data1See lessWrite an R program to create a simple bar plot of five subject’s marks.
# Create the data for the chart marks <- c(70,82,96,80,90) subject <- c("DBMS","IOT","C++","JAVA","PYTHON") png(file = "subject_marks.png") # Plot the bar chart barplot(marks,names.arg=subject,xlab="subjects",ylab="marks",col="red", main="Subject-Marks chart",border="black") # Save the file deRead more
# Create the data for the chart marks <- c(70,82,96,80,90) subject <- c("DBMS","IOT","C++","JAVA","PYTHON") png(file = "subject_marks.png") # Plot the bar chart barplot(marks,names.arg=subject,xlab="subjects",ylab="marks",col="red", main="Subject-Marks chart",border="black") # Save the file dev.off() #output
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