Determines whether or not notches are drawn. Notches displays a confidence interval around the median. We compute the confidence interval as median +/- 1.57 * IQR / sqrt(N), where IQR is the interquartile range and N is the sample size. If two boxes' notches do not overlap there is 95% confidence their medians differ. See https://sites.google.com/site/davidsstatistics/home/notched-box-plots for more info. Defaults to *false* unless `notchwidth` or `notchspan` is set.

Sets the notch span from the boxes' `median` values. There should be as many items as the number of boxes desired. This attribute has effect only under the q1/median/q3 signature. If `notchspan` is not provided but a sample (in `y` or `x`) is set, we compute it as 1.57 * IQR / sqrt(N), where N is the sample size.

Sets the source reference on Chart Studio Cloud for `notchspan`.

Sets the width of the notches relative to the box' width. For example, with 0, the notches are as wide as the box(es).

Sets the orientation of the box(es). If *v* (*h*), the distribution is visualized along the vertical (horizontal).

Sets the position of the sample points in relation to the box(es). If *0*, the sample points are places over the center of the box(es). Positive (negative) values correspond to positions to the right (left) for vertical boxes and above (below) for horizontal boxes

Sets the Quartile 1 values. There should be as many items as the number of boxes desired.

Sets the source reference on Chart Studio Cloud for `q1`.

Sets the Quartile 3 values. There should be as many items as the number of boxes desired.

Sets the source reference on Chart Studio Cloud for `q3`.

Sets the method used to compute the sample's Q1 and Q3 quartiles. The *linear* method uses the 25th percentile for Q1 and 75th percentile for Q3 as computed using method #10 (listed on http://www.amstat.org/publications/jse/v14n3/langford.html). The *exclusive* method uses the median to divide the ordered dataset into two halves if the sample is odd, it does not include the median in either half - Q1 is then the median of the lower half and Q3 the median of the upper half. The *inclusive* method also uses the median to divide the ordered dataset into two halves but if the sample is odd, it includes the median in both halves - Q1 is then the median of the lower half and Q3 the median of the upper half.