8000 MNT: add a warning if a categroical string array is all convertible t… · matplotlib/matplotlib@24db221 · GitHub
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MNT: add a warning if a categroical string array is all convertible to numbers or dates
1 parent 56243e9 commit 24db221

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2 files changed

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+30
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‎lib/matplotlib/category.py

Lines changed: 26 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -12,10 +12,13 @@
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"""
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from collections import OrderedDict
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import dateutil.parser
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import itertools
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import numpy as np
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import warnings
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import matplotlib.cbook as cbook
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import matplotlib.units as units
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import matplotlib.ticker as ticker
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@@ -168,6 +171,20 @@ def __init__(self, data=None):
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if data is not None:
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self.update(data)
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@staticmethod
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def _str_is_convertable(val):
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"""
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Helper method to see if string can be cast to float or parsed as date.
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"""
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try:
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float(val)
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except ValueError:
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try:
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dateutil.parser.parse(val)
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except ValueError:
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return False
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return True
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def update(self, data):
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"""Maps new values to integer identifiers.
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@@ -183,11 +200,20 @@ def update(self, data):
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"""
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data = np.atleast_1d(np.array(data, dtype=object))
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convertable = True
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for val in OrderedDict.fromkeys(data):
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# OrderedDict just iterates over unique values in data.
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if not isinstance(val, (str, bytes)):
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raise TypeError("{val!r} is not a string".format(val=val))
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# check if we can convert string to number or date...
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convertable = (convertable and self._str_is_convertable(val))
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if val not in self._mapping:
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self._mapping[val] = next(self._counter)
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if convertable:
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cbook._warn_external('using category units to plot a list of '
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'strings that is a;; floats or parsable as dates. '
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'If you do not mean these to be categories, cast '
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'to the approriate data type before plotting.')
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# Connects the convertor to matplotlib

‎lib/matplotlib/tests/test_category.py

Lines changed: 4 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -203,7 +203,8 @@ class TestPlotNumlike(object):
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@pytest.mark.parametrize("ndata", numlike_data, ids=numlike_ids)
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def test_plot_numlike(self, ax, plotter, ndata):
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counts = np.array([4, 6, 5])
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plotter(ax, ndata, counts)
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with pytest.warns(UserWarning, match='using category units to plot'):
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plotter(ax, ndata, counts)
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axis_test(ax.xaxis, ndata)
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@@ -261,12 +262,14 @@ def test_update_plot(self, ax, plotter):
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PLOT_BROKEN_IDS = ["scatter", "plot", "bar"]
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265+
@pytest.mark.filterwarnings('ignore::UserWarning')
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@pytest.mark.parametrize("plotter", PLOT_BROKEN_LIST, ids=PLOT_BROKEN_IDS)
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@pytest.mark.parametrize("xdata", fvalues, ids=fids)
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def test_mixed_type_exception(self, ax, plotter, xdata):
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with pytest.raises(TypeError):
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plotter(ax, xdata, [1, 2])
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@pytest.mark.filterwarnings('ignore::UserWarning')
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@pytest.mark.parametrize("plotter", PLOT_BROKEN_LIST, ids=PLOT_BROKEN_IDS)
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@pytest.mark.parametrize("xdata", fvalues, ids=fids)
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def test_mixed_type_update_exception(self, ax, plotter, xdata):

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