Data Frame Manipulation -- Base R data.frame¶

Basic data frame manipulation using base R data frames.

In [1]:

library(magrittr)

library(magrittr)

Load csv¶

In [2]:

df <- read.csv(here::here(".data", "titanic.csv"))
head(df, 3)

df <- read.csv(here::here(".data", "titanic.csv")) head(df, 3)

A data.frame: 3 × 14

	pclass	survived	name	sex	age	sibsp	parch	ticket	fare	cabin	embarked	boat	body	home.dest
	<int>	<int>	<chr>	<chr>	<dbl>	<int>	<int>	<chr>	<dbl>	<chr>	<chr>	<chr>	<int>	<chr>
1	1	1	Allen, Miss. Elisabeth Walton	female	29.0000	0	0	24160	211.3375	B5	S	2	NA	St Louis, MO
2	1	1	Allison, Master. Hudson Trevor	male	0.9167	1	2	113781	151.5500	C22 C26	S	11	NA	Montreal, PQ / Chesterville, ON
3	1	0	Allison, Miss. Helen Loraine	female	2.0000	1	2	113781	151.5500	C22 C26	S		NA	Montreal, PQ / Chesterville, ON

Summary¶

In [3]:

# Rows
nrow(df)

# Rows nrow(df)

1309

In [4]:

# Columns
length(df)

# Columns length(df)

14

In [5]:

# Inspect types
str(df)

# Inspect types str(df)

'data.frame':	1309 obs. of  14 variables:
 $ pclass   : int  1 1 1 1 1 1 1 1 1 1 ...
 $ survived : int  1 1 0 0 0 1 1 0 1 0 ...
 $ name     : chr  "Allen, Miss. Elisabeth Walton" "Allison, Master. Hudson Trevor" "Allison, Miss. Helen Loraine" "Allison, Mr. Hudson Joshua Creighton" ...
 $ sex      : chr  "female" "male" "female" "male" ...
 $ age      : num  29 0.917 2 30 25 ...
 $ sibsp    : int  0 1 1 1 1 0 1 0 2 0 ...
 $ parch    : int  0 2 2 2 2 0 0 0 0 0 ...
 $ ticket   : chr  "24160" "113781" "113781" "113781" ...
 $ fare     : num  211 152 152 152 152 ...
 $ cabin    : chr  "B5" "C22 C26" "C22 C26" "C22 C26" ...
 $ embarked : chr  "S" "S" "S" "S" ...
 $ boat     : chr  "2" "11" "" "" ...
 $ body     : int  NA NA NA 135 NA NA NA NA NA 22 ...
 $ home.dest: chr  "St Louis, MO" "Montreal, PQ / Chesterville, ON" "Montreal, PQ / Chesterville, ON" "Montreal, PQ / Chesterville, ON" ...

In [6]:

# Descriptive statistics
summary(df)

# Descriptive statistics summary(df)

     pclass         survived         name               sex           
 Min.   :1.000   Min.   :0.000   Length:1309        Length:1309       
 1st Qu.:2.000   1st Qu.:0.000   Class :character   Class :character  
 Median :3.000   Median :0.000   Mode  :character   Mode  :character  
 Mean   :2.295   Mean   :0.382                                        
 3rd Qu.:3.000   3rd Qu.:1.000                                        
 Max.   :3.000   Max.   :1.000                                        
                                                                      
      age              sibsp            parch          ticket         
 Min.   : 0.1667   Min.   :0.0000   Min.   :0.000   Length:1309       
 1st Qu.:21.0000   1st Qu.:0.0000   1st Qu.:0.000   Class :character  
 Median :28.0000   Median :0.0000   Median :0.000   Mode  :character  
 Mean   :29.8811   Mean   :0.4989   Mean   :0.385                     
 3rd Qu.:39.0000   3rd Qu.:1.0000   3rd Qu.:0.000                     
 Max.   :80.0000   Max.   :8.0000   Max.   :9.000                     
 NA's   :263                                                          
      fare            cabin             embarked             boat          
 Min.   :  0.000   Length:1309        Length:1309        Length:1309       
 1st Qu.:  7.896   Class :character   Class :character   Class :character  
 Median : 14.454   Mode  :character   Mode  :character   Mode  :character  
 Mean   : 33.295                                                           
 3rd Qu.: 31.275                                                           
 Max.   :512.329                                                           
 NA's   :1                                                                 
      body        home.dest        
 Min.   :  1.0   Length:1309       
 1st Qu.: 72.0   Class :character  
 Median :155.0   Mode  :character  
 Mean   :160.8                     
 3rd Qu.:256.0                     
 Max.   :328.0                     
 NA's   :1188                      

Slice data¶

In [7]:

# Select rows by number
df[2:4,]

# Select rows by number df[2:4,]

A data.frame: 3 × 14

	pclass	survived	name	sex	age	sibsp	parch	ticket	fare	cabin	embarked	boat	body	home.dest
	<int>	<int>	<chr>	<chr>	<dbl>	<int>	<int>	<chr>	<dbl>	<chr>	<chr>	<chr>	<int>	<chr>
2	1	1	Allison, Master. Hudson Trevor	male	0.9167	1	2	113781	151.55	C22 C26	S	11	NA	Montreal, PQ / Chesterville, ON
3	1	0	Allison, Miss. Helen Loraine	female	2.0000	1	2	113781	151.55	C22 C26	S		NA	Montreal, PQ / Chesterville, ON
4	1	0	Allison, Mr. Hudson Joshua Creighton	male	30.0000	1	2	113781	151.55	C22 C26	S		135	Montreal, PQ / Chesterville, ON

In [8]:

# Select rows by condition
df[df[, "survived"] == 1,] %>% head(3)

# Select rows by condition df[df[, "survived"] == 1,] %>% head(3)

A data.frame: 3 × 14

	pclass	survived	name	sex	age	sibsp	parch	ticket	fare	cabin	embarked	boat	body	home.dest
	<int>	<int>	<chr>	<chr>	<dbl>	<int>	<int>	<chr>	<dbl>	<chr>	<chr>	<chr>	<int>	<chr>
1	1	1	Allen, Miss. Elisabeth Walton	female	29.0000	0	0	24160	211.3375	B5	S	2	NA	St Louis, MO
2	1	1	Allison, Master. Hudson Trevor	male	0.9167	1	2	113781	151.5500	C22 C26	S	11	NA	Montreal, PQ / Chesterville, ON
6	1	1	Anderson, Mr. Harry	male	48.0000	0	0	19952	26.5500	E12	S	3	NA	New York, NY

In [9]:

# Select rows by multiple conditions
df[df[, "survived"] == 1 & df[, "sex"] == "female",] %>% head(3)

# Select rows by multiple conditions df[df[, "survived"] == 1 & df[, "sex"] == "female",] %>% head(3)

A data.frame: 3 × 14

	pclass	survived	name	sex	age	sibsp	parch	ticket	fare	cabin	embarked	boat	body	home.dest
	<int>	<int>	<chr>	<chr>	<dbl>	<int>	<int>	<chr>	<dbl>	<chr>	<chr>	<chr>	<int>	<chr>
1	1	1	Allen, Miss. Elisabeth Walton	female	29	0	0	24160	211.3375	B5	S	2	NA	St Louis, MO
7	1	1	Andrews, Miss. Kornelia Theodosia	female	63	1	0	13502	77.9583	D7	S	10	NA	Hudson, NY
9	1	1	Appleton, Mrs. Edward Dale (Charlotte Lamson)	female	53	2	0	11769	51.4792	C101	S	D	NA	Bayside, Queens, NY

In [10]:

# Select columns by name
df[, c("survived", "pclass")] %>% head(3)

# Select columns by name df[, c("survived", "pclass")] %>% head(3)

A data.frame: 3 × 2

	survived	pclass
	<int>	<int>
1	1	1
2	1	1
3	0	1

Assign values¶

In [11]:

# Assign a (new) column
df$sparkles <- 8
head(df, 3)

# Assign a (new) column df$sparkles <- 8 head(df, 3)

A data.frame: 3 × 15

	pclass	survived	name	sex	age	sibsp	parch	ticket	fare	cabin	embarked	boat	body	home.dest	sparkles
	<int>	<int>	<chr>	<chr>	<dbl>	<int>	<int>	<chr>	<dbl>	<chr>	<chr>	<chr>	<int>	<chr>	<dbl>
1	1	1	Allen, Miss. Elisabeth Walton	female	29.0000	0	0	24160	211.3375	B5	S	2	NA	St Louis, MO	8
2	1	1	Allison, Master. Hudson Trevor	male	0.9167	1	2	113781	151.5500	C22 C26	S	11	NA	Montreal, PQ / Chesterville, ON	8
3	1	0	Allison, Miss. Helen Loraine	female	2.0000	1	2	113781	151.5500	C22 C26	S		NA	Montreal, PQ / Chesterville, ON	8

In [12]:

# Assign value to some rows
df[df[, "survived"] == 1, "sparkles"] <- 3
head(df, 3)

# Assign value to some rows df[df[, "survived"] == 1, "sparkles"] <- 3 head(df, 3)

A data.frame: 3 × 15

	pclass	survived	name	sex	age	sibsp	parch	ticket	fare	cabin	embarked	boat	body	home.dest	sparkles
	<int>	<int>	<chr>	<chr>	<dbl>	<int>	<int>	<chr>	<dbl>	<chr>	<chr>	<chr>	<int>	<chr>	<dbl>
1	1	1	Allen, Miss. Elisabeth Walton	female	29.0000	0	0	24160	211.3375	B5	S	2	NA	St Louis, MO	3
2	1	1	Allison, Master. Hudson Trevor	male	0.9167	1	2	113781	151.5500	C22 C26	S	11	NA	Montreal, PQ / Chesterville, ON	3
3	1	0	Allison, Miss. Helen Loraine	female	2.0000	1	2	113781	151.5500	C22 C26	S		NA	Montreal, PQ / Chesterville, ON	8

Group by¶

In [ ]:

Reshape¶

In [13]:

# Gather / melt

# Gather / melt

In [14]:

# Spread / cast / pivot

# Spread / cast / pivot

Join¶

In [ ]:

Creation¶

In [15]:

df2 <- data.frame(
    x = c(1,2,3)
    , y = c('a', 'b', 'c')
    , z = c(TRUE, FALSE, TRUE)
)
df2

df2 <- data.frame( x = c(1,2,3) , y = c('a', 'b', 'c') , z = c(TRUE, FALSE, TRUE) ) df2

A data.frame: 3 × 3

x	y	z
<dbl>	<chr>	<lgl>
1	a	TRUE
2	b	FALSE
3	c	TRUE