datascience.tables.Table.pivot_bin

Table.pivot_bin(pivot_columns, value_column, bins=None, **vargs)[source]

Form a table with columns formed by the unique tuples in pivot_columns containing counts per bin of the values associated with each tuple in the value_column.

By default, bins are chosen to contain all values in the value_column. The following named arguments from numpy.histogram can be applied to specialize bin widths:

Args:
bins (int or sequence of scalars): If bins is an int,

it defines the number of equal-width bins in the given range (10, by default). If bins is a sequence, it defines the bin edges, including the rightmost edge, allowing for non-uniform bin widths.

range ((float, float)): The lower and upper range of

the bins. If not provided, range contains all values in the table. Values outside the range are ignored.

normed (bool): If False, the result will contain the number of

samples in each bin. If True, the result is normalized such that the integral over the range is 1.