- DataFrame.plot.hexbin(*args, **kwargs)#
Generate a hexagonal binning plot.
Generate a hexagonal binning plot of x versus y. If C is None (the default), this is a histogram of the number of occurrences of the observations at
If C is specified, specifies values at given coordinates
(x[i], y[i]). These values are accumulated for each hexagonal bin and then reduced according to reduce_C_function, having as default the NumPy’s mean function (
numpy.mean()). (If C is specified, it must also be a 1-D sequence of the same length as x and y, or a column label.)
reduce_C_function (callable, default np.mean) – Function of one argument that reduces all the values in a bin to a single number (e.g. np.mean, np.max, np.sum, np.std).
gridsize (int or tuple of (int, int), default 100) – The number of hexagons in the x-direction. The corresponding number of hexagons in the y-direction is chosen in a way that the hexagons are approximately regular. Alternatively, gridsize can be a tuple with two elements specifying the number of hexagons in the x-direction and the y-direction.
**kwargs – Additional keyword arguments are documented in
Axeson which the hexbin is plotted.
- Return type
The following examples are generated with random data from a normal distribution.
The next example uses C and np.sum as reduce_C_function. Note that ‘observations’ values ranges from 1 to 5 but the result plot shows values up to more than 25. This is because of the reduce_C_function.