Statistics Programming

Left join

left_join(table_1,
		  table_2,
		  by = "column")

Add columns of table_2 to table_1 that match by the column specified. NAs are added to rows of table_2 not matching rows of table_1.

dplyr::bind_rows function

Binds data frames, by row, into a tibble

dplyr::setequal function

Returns whether the data frames are equal, regardless of row order

Right join

right_join(table_1,
		   table_2,
		   by = "column")

Add columns of table_1 to table_2 that match by the column specified. NAs are added to rows of table_1 not matching rows of table_2.

Semi join

semi_join(table_1,
		  table_2,
		  by = "column")

Only keep rows of table_1 that match by the column specified to table_2. No extra columns added.

dplyr::bind_cols function

Binds data frames, by column, into a tibble

Sensitivity

$$\frac{TP}{TP + FN}$$

AKA true positive rate (TPR) or recall

Probability: \(P(\hat{Y} = 1|Y = 1)\)

dplyr::union function

Unique rows between tables with the same column names

\(F_1\) score

\[\frac{1}{\frac{1}{2}\cdot\left(\frac{1}{\text{recall}} + \frac{1}{\text{precision}}\right)}\]

Harmonic average of recall and precision

AKA balanced accuracy

Precision

$$\frac{TP}{TP + FP}$$

AKA positive predictive value (PPV)

Probability: \(P(Y = 1|\hat{Y} = 1)\)

Full join

full_join(table_1,
		  table_2,
		  by = "column")

All columns of table_1 and table_2 that match by the column specified. NAs are added to unmatched rows.

Inner join

inner_join(table_1,
		   table_2,
		   by = "column")

Keep only rows matching by the column specified

dplyr::intersect function

Common rows between tables with the same column names

dplyr::setdiff function

Rows in the first table argument not present in the second table argument

Anti join

anti_join(table_1,
		  table_2,
		  by = "column")

Only keep rows of table_1 that don't match by the column specified to table_2. No extra columns added.

Specificity

$$\frac{TN}{TN + FP}$$

AKA true negative rate (TNR)

Probability: \(P(\hat{Y} = 0|Y = 0)\)