R Tutorials by : Er Karan Arora : Founder & CEO - ITRONIX SOLUTIONS

Data Frames

• Data Frames are data displayed in a format as a table.
• Data Frames can have different types of data inside it. While the first column can be character, the second and third can be numeric or logical. However, each column should have the same type of data.
• Use the data.frame() function to create a data frame:

Create a data frame

df <- data.frame (
  Name = c("Karan", "Keisha", "Atharv"),
  Age = c(30, 23, 27),
  Marks = c(89, 97, 70)
)

Print the data frame

df

A data.frame: 3 × 3

Name	Age	Marks
<fct>	<dbl>	<dbl>
Karan	30	89
Keisha	23	97
Atharv	27	70

Summarize the Data

• Use the summary() function to summarize the data from a Data Frame:

summary(df)

     Name        Age            Marks      
 Atharv:1   Min.   :23.00   Min.   :70.00  
 Karan :1   1st Qu.:25.00   1st Qu.:79.50  
 Keisha:1   Median :27.00   Median :89.00  
            Mean   :26.67   Mean   :85.33  
            3rd Qu.:28.50   3rd Qu.:93.00  
            Max.   :30.00   Max.   :97.00  

Access Items

• We can use single brackets [ ], double brackets [[ ]] or $ to access columns from a data frame:

df[1]

A data.frame: 3 × 1

Name
<fct>
Karan
Keisha
Atharv

df[["Name"]]

1. Karan
2. Keisha
3. Atharv

Levels:

1. 'Atharv'
2. 'Karan'
3. 'Keisha'

df$Name

1. Karan
2. Keisha
3. Atharv

Levels:

1. 'Atharv'
2. 'Karan'
3. 'Keisha'

Add Rows

• Use the rbind() function to add new rows in a Data Frame:

df$Name <- as.character(df$Name)

new_row <- c("Priya", 88, 99)
df1 <- rbind(df, new_row)
df1

A data.frame: 4 × 3

Name	Age	Marks
<chr>	<chr>	<chr>
Karan	30	89
Keisha	23	97
Atharv	27	70
Priya	88	99

Add Columns

• Use the cbind() function to add new columns in a Data Frame:

Add a new column

df2 <- cbind(df, Roll_No = c(10, 11, 12))
df2

A data.frame: 3 × 4

Name	Age	Marks	Roll_No
<chr>	<dbl>	<dbl>	<dbl>
Karan	30	89	10
Keisha	23	97	11
Atharv	27	70	12

Remove Rows and Columns

• Use the c() function to remove rows and columns in a Data Frame:

Remove the first row and column

df3 <- df[-c(1), -c(1)]
df3

A data.frame: 2 × 2

	Age	Marks
	<dbl>	<dbl>
2	23	97
3	27	70

Amount of Rows and Columns

• Use the dim() function to find the amount of rows and columns in a Data Frame:

dim(df)

1. 3
2. 3

ncol(df)

3

nrow(df)

3

Data Frame Length

• Use the length() function to find the number of columns in a Data Frame (similar to ncol()):

length(df)

3

Combining Data Frames

• Use the rbind() function to combine two or more data frames in R vertically:

df1 <- data.frame (
  Name = c("Karan", "Keisha", "Atharv"),
  Age = c(30, 23, 27),
  Marks = c(89, 97, 70)
)
df2 <- data.frame (
  Name = c("Akshay", "Robin", "Manish"),
  Age = c(31, 24, 28),
  Marks = c(69, 91, 77)
)

df <- rbind(df1, df2)
df

A data.frame: 6 × 3

Name	Age	Marks
<fct>	<dbl>	<dbl>
Karan	30	89
Keisha	23	97
Atharv	27	70
Akshay	31	69
Robin	24	91
Manish	28	77

And use the cbind() function to combine two or more data frames in R horizontally:

df <- cbind(df1, df2)
df

A data.frame: 3 × 6

Name	Age	Marks	Name	Age	Marks
<fct>	<dbl>	<dbl>	<fct>	<dbl>	<dbl>
Karan	30	89	Akshay	31	69
Keisha	23	97	Robin	24	91
Atharv	27	70	Manish	28	77