[docs]class DataFrameAccessorViz(object):
[docs] def __init__(self, df):
self.df = df
# this will add methods to the above class
from . import mpl
[docs]class ExpressionAccessorViz:
[docs] def __init__(self, expression):
self.expression = expression
self.df = self.expression.df
[docs] def histogram(self, what="count(*)", grid=None, shape=64, facet=None, limits=None, figsize=None, f="identity", n=None, normalize_axis=None,
xlabel=None, ylabel=None, label=None,
selection=None, show=False, tight_layout=True, hardcopy=None,
progress=None,
**kwargs):
""" Plot a histogram of the expression. This is a convenience method for `df.histogram(...)`
Example:
>>> df.x.histogram()
>>> df.x.histogram(limits=[0, 100], shape=100)
>>> df.x.histogram(what='mean(y)', limits=[0, 100], shape=100)
If you want to do a computation yourself, pass the grid argument, but you are responsible for passing the
same limits arguments:
>>> counts = df.mean(df.y, binby=df.x, limits=[0, 100], shape=100)/100.
>>> df.plot1d(df.x, limits=[0, 100], shape=100, grid=means, label='mean(y)/100')
:param x: Expression to bin in the x direction
:param what: What to plot, count(*) will show a N-d histogram, mean('x'), the mean of the x column, sum('x') the sum
:param grid: If the binning is done before by yourself, you can pass it
:param facet: Expression to produce facetted plots ( facet='x:0,1,12' will produce 12 plots with x in a range between 0 and 1)
:param limits: list of [xmin, xmax], or a description such as 'minmax', '99%'
:param figsize: (x, y) tuple passed to plt.figure for setting the figure size
:param f: transform values by: 'identity' does nothing 'log' or 'log10' will show the log of the value
:param n: normalization function, currently only 'normalize' is supported, or None for no normalization
:param normalize_axis: which axes to normalize on, None means normalize by the global maximum.
:param normalize_axis:
:param xlabel: String for label on x axis (may contain latex)
:param ylabel: Same for y axis
:param: tight_layout: call plt.tight_layout or not
:param kwargs: extra argument passed to plt.plot
:return:
"""
return self.df.viz.histogram(self.expression, what=what, grid=grid, shape=shape, facet=facet, limits=limits, figsize=figsize, f=f, n=n, normalize_axis=normalize_axis,
xlabel=xlabel, ylabel=ylabel, label=label, selection=selection, show=show, tight_layout=tight_layout, hardcopy=hardcopy,
progress=progress, **kwargs)
