ValueError: Invalid RGBA argument: masked

[Lekhan02]

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn import *
import seaborn as sns
import matplotlib.pyplot as plt

def regression_model(model, df1,df2, name):
x=df1=[["month","year","laptop","mobile"]]
y=df1=[["revenue"]]
model.fit(x,y)
x_test=df2=[["month","year","laptop","mobile"]]
y_test=df2=[["revenue"]]
prediction=model.predict(x_test)
accuracy=model.score(x_test,y_test)
print ('Accuracy : %s' % '{0:.3%}'.format(accuracy), name)
newarray=x_test[["month"]].values
newarray2=newarray.ravel()
newarray3=x_test[["year"]].values
newarray4=newarray3.ravel()
newarray5=predictions.ravel()
newdf = pd.DataFrame({'revenue':newarray5, 'month':newarray2, 'year':newarray4})
sns.factorplot(x="month", y="revenue", hue="year", data=newdf)
plt.show()

data=pd.read_csv("D:/mlsalesdata/testing.csv")
df=pd.DataFrame(data)
df = pd.DataFrame(data)
x = df[['month','year','laptop','mobile']]
y = df[['revenue']]
sns.factorplot(x="month",y="revenue",hue="year",data=df)

---

ValueError Traceback (most recent call last)
in
----> 1 sns.factorplot(x="month",y="revenue",hue="year",data=df)

C:\ProgramData\Anaconda3\lib\site-packages\seaborn\categorical.py in factorplot(*args, **kwargs)
3674 kwargs.setdefault("kind", "point")
3675
-> 3676 return catplot(*args, **kwargs)
3677
3678

C:\ProgramData\Anaconda3\lib\site-packages\seaborn\categorical.py in catplot(x, y, hue, data, row, col, col_wrap, estimator, ci, n_boot, units, order, hue_order, row_order, col_order, kind, height, aspect, orient, color, palette, legend, legend_out, sharex, sharey, margin_titles, facet_kws, **kwargs)
3753
3754 # Draw the plot onto the facets
-> 3755 g.map_dataframe(plot_func, x, y, hue, **plot_kws)
3756
3757 # Special case axis labels for a count type plot

C:\ProgramData\Anaconda3\lib\site-packages\seaborn\axisgrid.py in map_dataframe(self, func, *args, **kwargs)
818
819 # Draw the plot
--> 820 self._facet_plot(func, ax, args, kwargs)
821
822 # Finalize the annotations and layout

C:\ProgramData\Anaconda3\lib\site-packages\seaborn\axisgrid.py in _facet_plot(self, func, ax, plot_args, plot_kwargs)
836
837 # Draw the plot
--> 838 func(*plot_args, **plot_kwargs)
839
840 # Sort out the supporting information

C:\ProgramData\Anaconda3\lib\site-packages\seaborn\categorical.py in pointplot(x, y, hue, data, order, hue_order, estimator, ci, n_boot, units, markers, linestyles, dodge, join, scale, orient, color, palette, errwidth, capsize, ax, **kwargs)
3338 ax = plt.gca()
3339
-> 3340 plotter.plot(ax)
3341 return ax
3342

C:\ProgramData\Anaconda3\lib\site-packages\seaborn\categorical.py in plot(self, ax)
1809 def plot(self, ax):
1810 """Make the plot."""
-> 1811 self.draw_points(ax)
1812 self.annotate_axes(ax)
1813 if self.orient == "h":

C:\ProgramData\Anaconda3\lib\site-packages\seaborn\categorical.py in draw_points(self, ax)
1805 c=point_colors, edgecolor=point_colors,
1806 linewidth=mew, marker=marker, s=markersize,
-> 1807 zorder=z)
1808
1809 def plot(self, ax):

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib_init_.py in inner(ax, data, *args, **kwargs)
1587 def inner(ax, *args, data=None, **kwargs):
1588 if data is None:
-> 1589 return func(ax, *map(sanitize_sequence, args), **kwargs)
1590
1591 bound = new_sig.bind(ax, *args, **kwargs)

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes_axes.py in scatter(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, plotnonfinite, **kwargs)
4488 offsets=offsets,
4489 transOffset=kwargs.pop('transform', self.transData),
-> 4490 alpha=alpha
4491 )
4492 collection.set_transform(mtransforms.IdentityTransform())

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\collections.py in init(self, paths, sizes, **kwargs)
881 """
882
--> 883 Collection.init(self, **kwargs)
884 self.set_paths(paths)
885 self.set_sizes(sizes)

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\collections.py in init(self, edgecolors, facecolors, linewidths, linestyles, capstyle, joinstyle, antialiaseds, offsets, transOffset, norm, cmap, pickradius, hatch, urls, offset_position, zorder, **kwargs)
126 self._hatch_color = mcolors.to_rgba(mpl.rcParams['hatch.color'])
127 self.set_facecolor(facecolors)
--> 128 self.set_edgecolor(edgecolors)
129 self.set_linewidth(linewidths)
130 self.set_linestyle(linestyles)

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\collections.py in set_edgecolor(self, c)
726 """
727 self._original_edgecolor = c
--> 728 self._set_edgecolor(c)
729
730 def set_alpha(self, alpha):

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\collections.py in _set_edgecolor(self, c)
710 except AttributeError:
711 pass
--> 712 self._edgecolors = mcolors.to_rgba_array(c, self._alpha)
713 if set_hatch_color and len(self._edgecolors):
714 self._hatch_color = tuple(self._edgecolors[0])

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\colors.py in to_rgba_array(c, alpha)
284 result = np.empty((len(c), 4), float)
285 for i, cc in enumerate(c):
--> 286 result[i] = to_rgba(cc, alpha)
287 return result
288

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\colors.py in to_rgba(c, alpha)
175 rgba = None
176 if rgba is None: # Suppress exception chaining of cache lookup failure.
--> 177 rgba = _to_rgba_no_colorcycle(c, alpha)
178 try:
179 _colors_full_map.cache[c, alpha] = rgba

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\colors.py in _to_rgba_no_colorcycle(c, alpha)
236 # float)andnp.array(...).astype(float)` all convert "0.5" to 0.5.
237 # Test dimensionality to reject single floats.
--> 238 raise ValueError("Invalid RGBA argument: {!r}".format(orig_c))
239 # Return a tuple to prevent the cached value from being modified.
240 c = tuple(c.astype(float))

ValueError: Invalid RGBA argument: masked