Data Frames in R.Rmd

---
title: "Data Frames in R"
date: "12/08/2021"
output: html_document
---
#### Name : Sara Kulkarni
#### Reg. no : 19BCE1567

Creating a data frame

1. Create a data frame by considering 5 students and 4 courses (C1,C2, C3, C4). Each score has a maximum score of 30. If a student is absent for CAT1 of a course, the mark entry is 0 for that course. (Have 0 entry also in the data)
```{r}
Names = c("Stud1","Stud2","Stud3","Stud4","Stud5")
c1 = c(21,18,22,27,18)
c2 = c(26,15,23,13,12)
c3 = c(18,22,0,0,21)
c4 = c(20,13,12,0,17)

my_df <- data.frame(Names,c1,c2,c3,c4)
```

2. View the contents of the data frame.
```{r}
View(my_df)
my_df

```

3. Find the total marks of each student.
4. Append a column to include the total marks of the students and view the data frame.
```{r}
my_df$total <- rowSums(my_df[c(2,3,4,5)])
View(my_df)
my_df
```

5. Find the maximum total marks and display the name of the participant who scored it

```{r}
which.max(my_df$total)
```

```{r}
my_df$Names[which.max(my_df$total)]
```

6. Compute the average mark in each course and append it as a new row in the data frame.

```{r}
my_df <- rbind(my_df,data.frame(Names = "Average",c1=mean(my_df$c1),c2=mean(my_df$c2),c3=mean(my_df$c3),c4=mean(my_df$c4),total=mean(my_df$total)))
my_df
```

7. Store the details in a comma separated values (csv) file. Also suppress the row numbers.

```{r}
write.csv(my_df,"marks.csv",row.names = FALSE)
```

Indexing and Slicing data frames

8. Read the content of recently stored csv file in a data frame and view it.

```{r}
studentmarks <- read.csv("marks.csv")
studentmarks
```



9. Access the marks of students in C2 using the column name.
```{r}
studentmarks$c2
```

10. Use index number to retrieve the same data.
```{r}
studentmarks[3]
```

11. Extract the marks of third student in C3.
```{r}
studentmarks[3,4]
```

12. Display the names and total marks of all students.
```{r}
studentmarks[c(1,2,3,4,5),c(1,6)]
```

13. Display the names of the students who were absent for the course C3 during CAT1.
```{r}
absent <- studentmarks["c3"]==0
row.names(studentmarks)[absent]
```

14. Obtain the names whose total marks is below its average.
```{r}
lessthan <- studentmarks["total"]<studentmarks["Average",6]
row.names(studentmarks)[lessthan]
```


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