Choose a histogram's bin count from the data

The Freedman–Diaconis rule picks a bin width from the data: width = 2 × IQR ÷ n^(1/3), where n is the number of values and IQR uses pandas' default quantiles. Write fd_bins(values): return the number of bins, the range (max − min) divided by that width, rounded up, and at least 1. If the IQR is 0 (or there are fewer than 2 values), return 1. Ignore missing values (None).