Session1b_R-dataframes.Rmd

---
title: "R-Dataframes"
output:
  html_notebook: default
  pdf_document: default
---


# Dataframes
In any form of data analysis, its most important to understand the datasets. 
Data frames are form of data structures in tabular format. They are most widely used for data analysis in R. 
Data frames,:

- rows : Observations
- columns are vectors of particular data types (such as character, integer,logical).
- different columns can be diff datatype.
- Elements of same column should be same type


Creating a data frame
```{r}
firstName <- c("Vilas","Pallavi", "Archana","Matti", "Dylan","Tain","Fahad", "Ivy","Jason") ## firstName is a Vector
lastName <- c("Menon", "Gaur", "Yadav", "Lam", "Lee","Luquez","Paryani", "Kosater", "Mares")
Gender <- c("male", "female", "female", "male", "male","male","male","female","male")
id_no <- c(20,29,32,15,26,19,30,25,27)
Fav_icecream <- c("Vanilla","Rose","Saffron","Chocolate","Vanilla","Chocolate","Vanilla","Cookies&Cream","Saffron")


Menon_lab <-  data.frame(firstName, lastName, FullName=paste(firstName, lastName), Gender, id_no, Fav_icecream) # data.frame is a function, Menon_lab is dataframe
Menon_lab
```



```{r}
getwd()
```

```{r}
Menon_lab
```


```{r}
#summary(Menon_lab)
str(Menon_lab)
```
```{r}
class(Fav_icecream)
```
```{r}
Menon_lab
```

```{r}
#Menon_lab$firstName
table(Menon_lab$Gender)

table(Menon_lab$Gender, Menon_lab$Fav_icecream)
```


```{r}
#save this table
write.csv(Menon_lab,"menon_lab.csv")
```

```{r}
# open and read a csv file
m_lab <- read.csv("menon_lab.csv", row.names = 1)
m_lab
```
```{r}
getwd()
```

```{r}
list.files()
```

```{r}
##Exploring data frame

#Size
dim(Menon_lab) #returns number of rows and the number of columns

nrow(Menon_lab) # number of rows

ncol(Menon_lab) # number of columns



```

```{r}
#Content
head(Menon_lab)
tail(Menon_lab)
colnames(Menon_lab)
rownames(Menon_lab)
#rownames(Menon_lab) <- Menon_lab$firstName
#rownames(Menon_lab)

```
```{r}

str(Menon_lab)

```

```{r}
summary(Menon_lab)
```


####Indexing and subsetting
use [] bracketcs, [row position,column position] 
```{r}
Menon_lab
```

```{r}

#Menon_lab[2,]#extract entire row, which is a dataframe with single observation
Menon_lab[2,3] # extract a particular element at row2 column3
```


```{r}
#Extract entire column, which is a vector
#Menon_lab$firstName
#Menon_lab[["firstName"]]
Menon_lab[,"firstName"]
Menon_lab[,"Gender"]
```

```{r}
Menon_lab
```


```{r}
#Extract particular cell
Menon_lab[4,6]
```
```{r}
#extract cell using column name
Menon_lab[4,"firstName"]
```


```{r}
# subsetting
#extract n number of rows
Menon_lab[c(1,2,4,6),]
```

```{r}
##extract some rows and columns
new_set<- Menon_lab[1:5,c("firstName","id_no", "Gender")]
new_set
```

```{r}
Menon_lab
```

```{r}
#extract rows based on some comparison
Menon_lab[Menon_lab$Gender=="female",]
```


```{r}
##make a new table with only female members
Menon_lab[Menon_lab$Gender=="female",]
female_members <- Menon_lab[Menon_lab$Gender=="female",]
female_members

```


```{r}
#show everything except particular column
Menon_lab[,-1]
```

```{r}
#show everything except particular rows
Menon_lab[-c(1,3),]
```

```{r}
Menon_lab
```

###using Grep

```{r}
###using Grep
## grep index values i.e.tell me the name of row numbers where the last name starts with 'L'
grep("^L", Menon_lab$lastName) # ^ is a regular expression also called regex in coding language

```



```{r}
####subsetting with grep
#Menon_lab[]
lastnameL <- Menon_lab[grep("^L",Menon_lab$lastName),]


```

### change the values in data frame
```{r}
# gsub function
Menon_lab$Fav_icecream<- gsub("Vanilla","Mochi",Menon_lab$Fav_icecream )
Menon_lab
```




```{r}
Menon_lab[4,5] <- "50"
```
```{r}
Menon_lab
```