05-data-structures-part2.md

05 Exploring Data Frames

csiu

OBJECTIVES
- Be able to add and remove rows and columns.
- Be able to remove rows with NA values.
- Be able to append two data frames
- Be able to articulate what a factor is and how to convert between factor and character.
- Be able to find basic properties of a data frames including size, class or type of the columns, names, and first few rows.

Editing a data frame

• cbind() to add a new column to a data frame.
• rbind() to add a new row to a data frame.
• key to remember when adding data to a data frame is that columns are vectors or factors, and rows are lists
• na.omit() to remove rows from a data frame with NA values.
• remove rows by minusing offending row

cats[-4,]  # format is dataframe[row,column]
           # "-" to remove

Converting between a factor & character

• when R creates a factor (as column in data frame), it only allows whatever is originally there when our data was first loaded else becomes NA
• levels() to explore that categories in a factor
• as.character() to convert column "coat" from factor to character:

cats$coat <- as.character(cats$coat)

Inspecting data frames

gapminder <-
  read.csv("https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/gh-pages/_episodes_rmd/data/gapminder-FiveYearData.csv")


str(gapminder)
str(gapminder$country)

typeof(gapminder)
typeof(gapminder$year)
typeof(gapminder$country)

length(gapminder)

nrow(gapminder)
ncol(gapminder)
dim(gapminder)

head(gapminder)

colnames(gapminder)
rownames(gapminder)