本文整理匯總了Python中pandas.plotting.parallel_coordinates方法的典型用法代碼示例。如果您正苦於以下問題:Python plotting.parallel_coordinates方法的具體用法?Python plotting.parallel_coordinates怎麽用?Python plotting.parallel_coordinates使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類pandas.plotting
的用法示例。
在下文中一共展示了plotting.parallel_coordinates方法的9個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_parallel_coordinates_with_sorted_labels
# 需要導入模塊: from pandas import plotting [as 別名]
# 或者: from pandas.plotting import parallel_coordinates [as 別名]
def test_parallel_coordinates_with_sorted_labels(self):
""" For #15908 """
from pandas.plotting import parallel_coordinates
df = DataFrame({"feat": [i for i in range(30)],
"class": [2 for _ in range(10)] +
[3 for _ in range(10)] +
[1 for _ in range(10)]})
ax = parallel_coordinates(df, 'class', sort_labels=True)
polylines, labels = ax.get_legend_handles_labels()
color_label_tuples = \
zip([polyline.get_color() for polyline in polylines], labels)
ordered_color_label_tuples = sorted(color_label_tuples,
key=lambda x: x[1])
prev_next_tupels = zip([i for i in ordered_color_label_tuples[0:-1]],
[i for i in ordered_color_label_tuples[1:]])
for prev, nxt in prev_next_tupels:
# labels and colors are ordered strictly increasing
assert prev[1] < nxt[1] and prev[0] < nxt[0]
示例2: test_get_standard_colors_random_seed
# 需要導入模塊: from pandas import plotting [as 別名]
# 或者: from pandas.plotting import parallel_coordinates [as 別名]
def test_get_standard_colors_random_seed(self):
# GH17525
df = DataFrame(np.zeros((10, 10)))
# Make sure that the random seed isn't reset by _get_standard_colors
plotting.parallel_coordinates(df, 0)
rand1 = random.random()
plotting.parallel_coordinates(df, 0)
rand2 = random.random()
assert rand1 != rand2
# Make sure it produces the same colors every time it's called
from pandas.plotting._style import _get_standard_colors
color1 = _get_standard_colors(1, color_type='random')
color2 = _get_standard_colors(1, color_type='random')
assert color1 == color2
示例3: test_parallel_coordinates_with_sorted_labels
# 需要導入模塊: from pandas import plotting [as 別名]
# 或者: from pandas.plotting import parallel_coordinates [as 別名]
def test_parallel_coordinates_with_sorted_labels(self):
""" For #15908 """
from pandas.plotting import parallel_coordinates
df = DataFrame({"feat": [i for i in range(30)],
"class": [2 for _ in range(10)] +
[3 for _ in range(10)] +
[1 for _ in range(10)]})
ax = parallel_coordinates(df, 'class', sort_labels=True)
polylines, labels = ax.get_legend_handles_labels()
color_label_tuples = \
zip([polyline.get_color() for polyline in polylines], labels)
ordered_color_label_tuples = sorted(color_label_tuples,
key=lambda x: x[1])
prev_next_tupels = zip([i for i in ordered_color_label_tuples[0:-1]],
[i for i in ordered_color_label_tuples[1:]])
for prev, nxt in prev_next_tupels:
# labels and colors are ordered strictly increasing
assert prev[1] < nxt[1] and prev[0] < nxt[0]
示例4: parallel_plot
# 需要導入模塊: from pandas import plotting [as 別名]
# 或者: from pandas.plotting import parallel_coordinates [as 別名]
def parallel_plot(data, num=None):
plt.figure(num=num, figsize=(50,25))
ax = parallel_coordinates(
data, 'target', colormap=cmap, axvlines=False)
plt.legend().set_visible(False)
plt.grid(False)
ax.xaxis.set_ticks_position('none')
for label in ax.get_xticklabels():
label.set_fontname('Arial')
label.set_fontsize(0)
for label in ax.get_yticklabels():
label.set_fontname('Arial')
label.set_fontsize(30)
axis_font = {'fontname':'Arial', 'size':'35'}
plt.ylabel("Numeric Representation", **axis_font)
plt.xlabel("Fingerprint", **axis_font)
# We can then plot the original unscaled data.
# In[10]:
示例5: parallel_plot
# 需要導入模塊: from pandas import plotting [as 別名]
# 或者: from pandas.plotting import parallel_coordinates [as 別名]
def parallel_plot(data, num=None):
plt.figure(num=num, figsize=(50,25))
ax = parallel_coordinates(
data, 'target', colormap=cmap, axvlines=False)
plt.legend().set_visible(False)
plt.grid(False)
ax.xaxis.set_ticks_position('none')
for label in ax.get_xticklabels():
label.set_fontname('Arial')
label.set_fontsize(0)
for label in ax.get_yticklabels():
label.set_fontname('Arial')
label.set_fontsize(30)
axis_font = {'fontname':'Arial', 'size':'35'}
plt.ylabel("Numeric Representation", **axis_font)
plt.xlabel("Fingerprint", **axis_font)
# In[11]:
示例6: test_parallel_coordinates_with_sorted_labels
# 需要導入模塊: from pandas import plotting [as 別名]
# 或者: from pandas.plotting import parallel_coordinates [as 別名]
def test_parallel_coordinates_with_sorted_labels(self):
""" For #15908 """
from pandas.plotting import parallel_coordinates
df = DataFrame({"feat": [i for i in range(30)],
"class": [2 for _ in range(10)] +
[3 for _ in range(10)] +
[1 for _ in range(10)]})
ax = parallel_coordinates(df, 'class', sort_labels=True)
polylines, labels = ax.get_legend_handles_labels()
color_label_tuples = \
zip([polyline.get_color() for polyline in polylines], labels)
ordered_color_label_tuples = sorted(color_label_tuples,
key=lambda x: x[1])
prev_next_tupels = zip([i for i in ordered_color_label_tuples[0:-1]],
[i for i in ordered_color_label_tuples[1:]])
for prev, nxt in prev_next_tupels:
# lables and colors are ordered strictly increasing
assert prev[1] < nxt[1] and prev[0] < nxt[0]
示例7: test_parallel_coordinates
# 需要導入模塊: from pandas import plotting [as 別名]
# 或者: from pandas.plotting import parallel_coordinates [as 別名]
def test_parallel_coordinates(self, iris):
from pandas.plotting import parallel_coordinates
from matplotlib import cm
df = iris
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name')
nlines = len(ax.get_lines())
nxticks = len(ax.xaxis.get_ticklabels())
rgba = ('#556270', '#4ECDC4', '#C7F464')
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', color=rgba)
self._check_colors(
ax.get_lines()[:10], linecolors=rgba, mapping=df['Name'][:10])
cnames = ['dodgerblue', 'aquamarine', 'seagreen']
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', color=cnames)
self._check_colors(
ax.get_lines()[:10], linecolors=cnames, mapping=df['Name'][:10])
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', colormap=cm.jet)
cmaps = lmap(cm.jet, np.linspace(0, 1, df['Name'].nunique()))
self._check_colors(
ax.get_lines()[:10], linecolors=cmaps, mapping=df['Name'][:10])
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', axvlines=False)
assert len(ax.get_lines()) == (nlines - nxticks)
colors = ['b', 'g', 'r']
df = DataFrame({"A": [1, 2, 3],
"B": [1, 2, 3],
"C": [1, 2, 3],
"Name": colors})
ax = parallel_coordinates(df, 'Name', color=colors)
handles, labels = ax.get_legend_handles_labels()
self._check_colors(handles, linecolors=colors)
with tm.assert_produces_warning(FutureWarning):
parallel_coordinates(data=df, class_column='Name')
with tm.assert_produces_warning(FutureWarning):
parallel_coordinates(df, 'Name', colors=colors)
# not sure if this is indicative of a problem
示例8: test_parallel_coordinates
# 需要導入模塊: from pandas import plotting [as 別名]
# 或者: from pandas.plotting import parallel_coordinates [as 別名]
def test_parallel_coordinates(self, iris):
from pandas.plotting import parallel_coordinates
from matplotlib import cm
df = iris
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name')
nlines = len(ax.get_lines())
nxticks = len(ax.xaxis.get_ticklabels())
rgba = ('#556270', '#4ECDC4', '#C7F464')
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', color=rgba)
self._check_colors(
ax.get_lines()[:10], linecolors=rgba, mapping=df['Name'][:10])
cnames = ['dodgerblue', 'aquamarine', 'seagreen']
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', color=cnames)
self._check_colors(
ax.get_lines()[:10], linecolors=cnames, mapping=df['Name'][:10])
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', colormap=cm.jet)
cmaps = lmap(cm.jet, np.linspace(0, 1, df['Name'].nunique()))
self._check_colors(
ax.get_lines()[:10], linecolors=cmaps, mapping=df['Name'][:10])
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', axvlines=False)
assert len(ax.get_lines()) == (nlines - nxticks)
colors = ['b', 'g', 'r']
df = DataFrame({"A": [1, 2, 3],
"B": [1, 2, 3],
"C": [1, 2, 3],
"Name": colors})
ax = parallel_coordinates(df, 'Name', color=colors)
handles, labels = ax.get_legend_handles_labels()
self._check_colors(handles, linecolors=colors)
with tm.assert_produces_warning(FutureWarning):
parallel_coordinates(data=df, class_column='Name')
with tm.assert_produces_warning(FutureWarning):
parallel_coordinates(df, 'Name', colors=colors)
示例9: test_parallel_coordinates
# 需要導入模塊: from pandas import plotting [as 別名]
# 或者: from pandas.plotting import parallel_coordinates [as 別名]
def test_parallel_coordinates(self):
from pandas.plotting import parallel_coordinates
from matplotlib import cm
df = self.iris
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name')
nlines = len(ax.get_lines())
nxticks = len(ax.xaxis.get_ticklabels())
rgba = ('#556270', '#4ECDC4', '#C7F464')
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', color=rgba)
self._check_colors(
ax.get_lines()[:10], linecolors=rgba, mapping=df['Name'][:10])
cnames = ['dodgerblue', 'aquamarine', 'seagreen']
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', color=cnames)
self._check_colors(
ax.get_lines()[:10], linecolors=cnames, mapping=df['Name'][:10])
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', colormap=cm.jet)
cmaps = lmap(cm.jet, np.linspace(0, 1, df['Name'].nunique()))
self._check_colors(
ax.get_lines()[:10], linecolors=cmaps, mapping=df['Name'][:10])
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', axvlines=False)
assert len(ax.get_lines()) == (nlines - nxticks)
colors = ['b', 'g', 'r']
df = DataFrame({"A": [1, 2, 3],
"B": [1, 2, 3],
"C": [1, 2, 3],
"Name": colors})
ax = parallel_coordinates(df, 'Name', color=colors)
handles, labels = ax.get_legend_handles_labels()
self._check_colors(handles, linecolors=colors)
with tm.assert_produces_warning(FutureWarning):
parallel_coordinates(data=df, class_column='Name')
with tm.assert_produces_warning(FutureWarning):
parallel_coordinates(df, 'Name', colors=colors)