prop1 <- sum(GE_survey$`Q17_What department are you in` == "HSS") / nrow(GE_survey)
-
nrow() and ncol(): Suppose you have a dataset
my_data
that contains information about customers, with each row representing a different customer and each column representing a different attribute (e.g., ID, name, age, etc.). You can usenrow(my_data)
to find out how many customers are in the dataset andncol(my_data)
to find out how many attributes each customer record has. -
length(): If you have a vector
my_vector
containing the sales figures for each month of the year, you can uselength(my_vector)
to find out how many months of sales data you have. -
dim(): Suppose you have a matrix
my_matrix
that represents the results of a survey, with each row representing a different question and each column representing a different respondent. You can usedim(my_matrix)
to find out how many questions were asked in the survey and how many respondents answered the survey. -
dimnames(): If
my_matrix
has row and column names indicating the questions and respondent IDs, respectively, you can usedimnames(my_matrix)
to access and manipulate these names. -
attributes(): If you have a data frame
my_df
that contains information about products, including their names, prices, and quantities, you can useattributes(my_df)
to view or modify the attributes of the data frame, such as its column names or class.
These functions are commonly used in data analysis and manipulation tasks to understand and work with the structure of your data.