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Description
It looks like when two or more geoms are plotted and the input data is a Pandas IntegerArray, specifically a pandas.Int64Dtype. It's throwing the TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe'' error.
Found this out because for some reason my database driver's "to pandas" feature returns 64 bit int columns as this type instead of as a numpy.int64.
from plotnine import *
import numpy as np
import pandas as pd
x = pd.array(np.arange(0, 10), dtype=pd.Int64Dtype())
y = x**2
(
ggplot(mapping=aes(x=x, y=y)) +
geom_point() +
geom_line()
)---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/IPython/core/formatters.py:706](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/IPython/core/formatters.py:706), in PlainTextFormatter.__call__(self, obj)
699 stream = StringIO()
700 printer = pretty.RepresentationPrinter(stream, self.verbose,
701 self.max_width, self.newline,
702 max_seq_length=self.max_seq_length,
703 singleton_pprinters=self.singleton_printers,
704 type_pprinters=self.type_printers,
705 deferred_pprinters=self.deferred_printers)
--> 706 printer.pretty(obj)
707 printer.flush()
708 return stream.getvalue()
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/IPython/lib/pretty.py:410](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/IPython/lib/pretty.py:410), in RepresentationPrinter.pretty(self, obj)
407 return meth(obj, self, cycle)
408 if cls is not object \
409 and callable(cls.__dict__.get('__repr__')):
--> 410 return _repr_pprint(obj, self, cycle)
412 return _default_pprint(obj, self, cycle)
413 finally:
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/IPython/lib/pretty.py:778](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/IPython/lib/pretty.py:778), in _repr_pprint(obj, p, cycle)
776 """A pprint that just redirects to the normal repr function."""
777 # Find newlines and replace them with p.break_()
--> 778 output = repr(obj)
779 lines = output.splitlines()
780 with p.group():
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/ggplot.py:95](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/ggplot.py:95), in ggplot.__repr__(self)
91 def __repr__(self):
92 """
93 Print/show the plot
94 """
---> 95 self.__str__()
96 return '<ggplot: (%d)>' % self.__hash__()
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/ggplot.py:86](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/ggplot.py:86), in ggplot.__str__(self)
82 def __str__(self):
83 """
84 Print/show the plot
85 """
---> 86 self.draw(show=True)
88 # Return and empty string so that print(p) is "pretty"
89 return ''
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/ggplot.py:203](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/ggplot.py:203), in ggplot.draw(self, return_ggplot, show)
201 self = deepcopy(self)
202 with plot_context(self, show=show):
--> 203 self._build()
205 # setup
206 figure, axs = self._create_figure()
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/ggplot.py:299](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/ggplot.py:299), in ggplot._build(self)
295 scales.add_missing(('x', 'y'))
297 # Map and train positions so that statistics have access
298 # to ranges and all positions are numeric
--> 299 layout.train_position(layers, scales)
300 layout.map_position(layers)
302 # Apply and map statistics
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/facets/layout.py:88](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/facets/layout.py:88), in Layout.train_position(self, layers, scales)
85 result = self.facet.init_scales(layout, None, scales.y)
86 self.panel_scales_y = result.y
---> 88 self.facet.train_position_scales(self, layers)
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/facets/facet.py:238](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/facets/facet.py:238), in facet.train_position_scales(self, layout, layers)
236 # the scale index for each data point
237 SCALE_X = _layout['SCALE_X'].iloc[match_id].tolist()
--> 238 panel_scales_x.train(data, x_vars, SCALE_X)
240 if panel_scales_y:
241 y_vars = list(set(panel_scales_y[0].aesthetics) &
242 set(data.columns))
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/scales/scales.py:128](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/scales/scales.py:128), in Scales.train(self, data, vars, idx)
126 for i, sc in enumerate(self, start=1):
127 bool_idx = (i == idx)
--> 128 sc.train(data.loc[bool_idx, col])
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/scales/scale.py:703](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/scales/scale.py:703), in scale_continuous.train(self, x)
700 if not len(x):
701 return
--> 703 self.range.train(x)
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/scales/range.py:33](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/plotnine/scales/range.py:33), in RangeContinuous.train(self, x)
29 def train(self, x):
30 """
31 Train continuous range
32 """
---> 33 self.range = scale_continuous.train(x, self.range)
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/mizani/scale.py:108](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/mizani/scale.py:108), in scale_continuous.train(cls, new_data, old)
105 if old is not None:
106 new_data = np.hstack([new_data, old])
--> 108 return min_max(new_data, na_rm=True, finite=True)
File [~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/mizani/utils.py:85](https://vscode-remote+wsl-002bubuntu-002d20-002e04.vscode-resource.vscode-cdn.net/home/alex/Python-Team-Queries/UsageAnalysis/mdu/~/.pyenv/versions/3.10.8/lib/python3.10/site-packages/mizani/utils.py:85), in min_max(x, na_rm, finite)
82 x = np.asarray(x)
84 if na_rm and finite:
---> 85 x = x[np.isfinite(x)]
86 elif not na_rm and np.any(np.isnan(x)):
87 return np.nan, np.nan
TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''