# corr

Returns `DataFrame`

with the pairwise correlation between two sets of columns.

It computes the Pearson correlation coefficient.

To compute pairwise correlation between all columns in the `DataFrame`

use `corr`

without arguments:

The function is available for numeric- and `Boolean`

columns. `Boolean`

values are converted into `1`

for `true`

and `0`

for `false`

. All other columns are ignored.

If a `ColumnGroup`

instance is passed as target column for correlation, it will be unpacked into suitable nested columns.

The resulting `DataFrame`

will have `n1`

rows and `n2+1`

columns, where `n1`

and `n2`

are the number of columns in `columns1`

and `columns2`

correspondingly.

The first column will have the name "column" and will contain names of columns in `column1`

. Other columns will have the same names as in `columns2`

and will contain the computed correlation coefficients.

If exactly one `ColumnGroup`

is passed in `columns1`

, the first column in the output will have its name.