我正在尝试将自己的绘图方法添加到pandas.DataFrame.plot
在下面的示例中,我复制并粘贴了pandas的^{VscatterPlot
。然后我将这个类连同它的corresponding helper function到pandas.DataFrame.plot
一起添加到它们各自的位置(见下文)。你知道吗
VscatterPlot
import pandas
import numpy as np
class VscatterPlot(pandas.plotting._core.PlanePlot):
_kind = 'vscatter'
def __init__(self, data, x, y, s=None, c=None, **kwargs):
if s is None:
# hide the matplotlib default for size, in case we want to change
# the handling of this argument later
s = 20
super(VscatterPlot, self).__init__(data, x, y, s=s, **kwargs)
if is_integer(c) and not self.data.columns.holds_integer():
c = self.data.columns[c]
self.c = c
def _make_plot(self):
x, y, c, data = self.x, self.y, self.c, self.data
ax = self.axes[0]
c_is_column = is_hashable(c) and c in self.data.columns
# plot a colorbar only if a colormap is provided or necessary
cb = self.kwds.pop('colorbar', self.colormap or c_is_column)
# pandas uses colormap, matplotlib uses cmap.
cmap = self.colormap or 'Greys'
cmap = self.plt.cm.get_cmap(cmap)
color = self.kwds.pop("color", None)
if c is not None and color is not None:
raise TypeError('Specify exactly one of `c` and `color`')
elif c is None and color is None:
c_values = self.plt.rcParams['patch.facecolor']
elif color is not None:
c_values = color
elif c_is_column:
c_values = self.data[c].values
else:
c_values = c
if self.legend and hasattr(self, 'label'):
label = self.label
else:
label = None
scatter = ax.scatter(data[x].values, data[y].values, c=c_values,
label=label, cmap=cmap, **self.kwds)
if cb:
img = ax.collections[0]
kws = dict(ax=ax)
if self.mpl_ge_1_3_1():
kws['label'] = c if c_is_column else ''
self.fig.colorbar(img, **kws)
if label is not None:
self._add_legend_handle(scatter, label)
else:
self.legend = False
errors_x = self._get_errorbars(label=x, index=0, yerr=False)
errors_y = self._get_errorbars(label=y, index=0, xerr=False)
if len(errors_x) > 0 or len(errors_y) > 0:
err_kwds = dict(errors_x, **errors_y)
err_kwds['ecolor'] = scatter.get_facecolor()[0]
ax.errorbar(data[x].values, data[y].values,
linestyle='none', **err_kwds)
# Set VscatterPlot as an attribute of pandas.plotting._core
setattr(pandas.plotting._core, "VscatterPlot", VscatterPlot)
# Create the vscatter helper function
def vscatter(self, x, y, s=None, c=None, **kwds):
return self(kind='vscatter', x=x, y=y, c=c, s=s, **kwds)
# Set the helper function
setattr(pandas.plotting._core.FramePlotMethods, "vscatter", vscatter)
# Append the class to pandas.plotting._core._klasses
pandas.plotting._core._klasses.append(pandas.plotting._core.VscatterPlot)
# Add the class to the pandas.plotting._core._plot_klass dict
pandas.plotting._core._plot_klass[VscatterPlot._kind] = pandas.plotting._core.VscatterPlot
example = pandas.DataFrame(np.random.random((5,2)), columns=["x", "y"])
example.plot.vscatter(x="x", y="y")
ValueError: 'vscatter' is not a valid plot kind
我错过了什么?vscatter
在pandas.plotting._core._plot_klass
中,那么它为什么抛出这个ValueError呢?你知道吗
在
pandas.plotting._core
中有两个列表决定了类的实例化方式。你需要把"vscatter"
放在那些列表中。你知道吗除此之外,还少了一些进口货。以下代码
生成此输出
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