/edX-R

edX Course on R (2019)

edX-R

edX Course on R (2019)

R - edX 2019 (Quick Ref Guide)

? - help for that function

Eg: ? sqrt

Assignment: = and <-

Vectors:

vect = c(1, 2, 3)
vect1 = c('A', 'E', 'I')
sequ = seq(0, 100, 2) or c(seq(0, 100, 2))
		   |   |   |
		   |  end  diff
		  start

FUNCTIONS

  1. sqrt(number or sequence) - gives square root for each element of the vector.

    Eg: sqrt(100) or sqrt(sequence)

  2. abs(number or sequence) - gives the absolute value.

  3. mean(vector) - Find the mean of a vector.

    Eg: mean(vect1) 
    mean(df$col)

  4. sd(vector) - Find the standard deviation. Same as mean

  5. seq(start, end, incr) - creates a vector from start to end with each element differing by incr (similar to np.arange)

  6. min(vector) - returns the minimum value

  7. max(vector) - returns the max of a vector

  8. str(df) - Display the structure of an R object

  9. summary(df) - Display the summary of an R object

  10. ls() - list of variables

  11. read.csv(filename) - Read filename

  12. write.csv(filename) - Write to filename

  13. rm(var_name) or remove(var_name) - remove a variable or a list of variables (comma separated)

  14. which.min(vector) - return the index of the minimum value.

  15. which.max(vector) - return the index of the max value.

  16. rbind(df1, df2) and cbind(df1, df2) - combine to vectors or dataframes row-wise/column-wise.

  17. View(df, title(optional)) - Invoke a spreadsheet-style data viewer on a matrix-like R object.

  18. plot(x, y, xlab, ylab) - Plots a graph for x and y (which are R objects) and sets the x-label as xlab and y-label as ylab.

  19. nrow(x) - no. of rows in x

  20. ncol(x) - no. of columns in x

  21. hist(df$col) - plot a histogram

  22. table(df$col_1, (optional)df$col_2...) - table uses the cross-classifying factors to build a contingency table of the counts at each combination of factor levels. Length should be same.

  23. names(df) - to get or set the name of an object.

    Eg: names(x)
	names(x) <- value

  24. tapply(df$col_1, df$col_2, op, (optional)na.rm = T): To remove na values, pass na.rm = T or TRUE a. Split the data by col_2 b. Perform operation on col_1

  25. subset(DataFrame, condition) - truncates the dataframe to the given condition

    Eg: df_europe = subset(df, Region == "Europe")

  26. match(x, table) - return a vector of indices where x is first found in table

    Eg: match('Africa', df$Region)
	      |	    	|
	      |	      vector
	    vector/value

DATAFRAMES

df$new_col = c(1, 2, 3) - Appends this vector to an already existing dataframe df.

Eg: vect = df$col > mean(df$col, na.rm = T)

vect contains True of False based on the condition.

vect = as.numeric(df$col > mean(df$col, na.rm = T))

now vect contains binary values.