Useful R tricks

Question 1

To convert coded categorical data

Answer 1

filecall$columnname=

replace( fc$cn, fc$cn==categorycode, ‘varname’)

Question 2

view all column data of a specific type

Answer 2

ColumnName$ColumnData

Question 3

Create table of column data of specific variable type

Answer 3

table(ColumnName$ColumnData)

Question 4

View the proportion of each data type in a column from table t

Answer 4

prop=prop.table(table name)

Question 5

View the percent of each data type in a column of table t

Answer 5

percent=prop.table(table name)*100

Question 6

Creating category names for pie charts

Answer 6

for pie(tablename, _____)

paste(c(“category1”,”cat2”,”cat3”), function for percent, “%”, sep=” “)

Combines data

Question 8

Display graphic output in new window

Answer 8

add x11()

in the console or before the code

Question 9

build a histogram

Answer 9

hist(columndata, parameters….)

Question 10

histogram breaks function

Answer 10

hist(actor_age$Age,
breaks=10,

main=”“,….)

Changes the interval reported for data

Question 11

The following command will show you the five-number summary and the mean value of the data

Answer 11

summary(actor_age$Age)

Question 12

For the Mean:

Answer 12

mean(actor_age$Age)

Question 13

For the Standard Deviation:

Answer 13

sd(actor_age$Age)

Question 14

For the Variance:

Answer 14

var(actor_age$Age)

Question 15

For the Median:

Answer 15

median(actor_age$Age)

Question 16

For the Inter-quartile range:

Answer 16

IQR(actor_age$Age)

Question 17

For the Minimum:

Answer 17

min(actor_age$Age)

Question 18

For the Maximum:

Answer 18

max(actor_age$Age)

Question 19

For the Sample Size (n):

Answer 19

length(actor_age$Age)

Question 20

For the First Quartile (25th percentile, Q1):

Answer 20

quantile(actor_age$Age, 0.25)

Question 21

For the Third Quartile (75th percentile, Q3):

Answer 21

quantile(actor_age$Age, 0.75)