def plot_histogram(data: Union["ps.DataFrame", "ps.Series"], **kwargs):
import plotly.graph_objs as go
bins = kwargs.get("bins", 10)
kdf, bins = HistogramPlotBase.prepare_hist_data(data, bins)
assert len(bins) > 2, "the number of buckets must be higher than 2."
output_series = HistogramPlotBase.compute_hist(kdf, bins)
prev = float("%.9f" % bins[0]) # to make it prettier, truncate.
text_bins = []
for b in bins[1:]:
norm_b = float("%.9f" % b)
text_bins.append("[%s, %s)" % (prev, norm_b))
prev = norm_b
text_bins[
-1] = text_bins[-1][:-1] + "]" # replace ) to ] for the last bucket.
bins = 0.5 * (bins[:-1] + bins[1:])
output_series = list(output_series)
bars = []
for series in output_series:
bars.append(
go.Bar(
x=bins,
y=series,
name=name_like_string(series.name),
text=text_bins,
hovertemplate=("variable=" + name_like_string(series.name) +
"<br>value=%{text}<br>count=%{y}"),
))
fig = go.Figure(data=bars, layout=go.Layout(barmode="stack"))
fig["layout"]["xaxis"]["title"] = "value"
fig["layout"]["yaxis"]["title"] = "count"
return fig
def test_compute_hist_multi_columns(self):
expected_bins = np.linspace(1, 50, 11)
kdf = ps.DataFrame(
{
"a": [1, 2, 3, 4, 5, 6, 7, 8, 9, 15, 50],
"b": [50, 50, 30, 30, 30, 24, 10, 5, 4, 3, 1],
}
)
bins = HistogramPlotBase.get_bins(kdf.to_spark(), 10)
self.assert_eq(pd.Series(expected_bins), pd.Series(bins))
expected_histograms = [
np.array([5, 4, 1, 0, 0, 0, 0, 0, 0, 1]),
np.array([4, 1, 0, 0, 1, 3, 0, 0, 0, 2]),
]
histograms = HistogramPlotBase.compute_hist(kdf, bins)
expected_names = ["a", "b"]
for histogram, expected_histogram, expected_name in zip(
histograms, expected_histograms, expected_names
):
self.assert_eq(
pd.Series(expected_histogram, name=expected_name), histogram, almost=True
)
def _make_plot(self):
# TODO: this logic is similar with KdePlot. Might have to deduplicate it.
# 'num_colors' requires to calculate `shape` which has to count all.
# Use 1 for now to save the computation.
colors = self._get_colors(num_colors=1)
stacking_id = self._get_stacking_id()
output_series = HistogramPlotBase.compute_hist(self.data, self.bins)
for (i, label), y in zip(enumerate(self.data._internal.column_labels),
output_series):
ax = self._get_ax(i)
kwds = self.kwds.copy()
label = pprint_thing(label if len(label) > 1 else label[0])
kwds["label"] = label
style, kwds = self._apply_style_colors(colors, kwds, i, label)
if style is not None:
kwds["style"] = style
kwds = self._make_plot_keywords(kwds, y)
artists = self._plot(ax,
y,
column_num=i,
stacking_id=stacking_id,
**kwds)
self._add_legend_handle(artists[0], label, index=i)
def test_compute_hist_single_column(self):
kdf = ps.DataFrame(
{"a": [1, 2, 3, 4, 5, 6, 7, 8, 9, 15, 50]}, index=[0, 1, 3, 5, 6, 8, 9, 9, 9, 10, 10]
)
expected_bins = np.linspace(1, 50, 11)
bins = HistogramPlotBase.get_bins(kdf[["a"]].to_spark(), 10)
expected_histogram = np.array([5, 4, 1, 0, 0, 0, 0, 0, 0, 1])
histogram = HistogramPlotBase.compute_hist(kdf[["a"]], bins)[0]
self.assert_eq(pd.Series(expected_bins), pd.Series(bins))
self.assert_eq(pd.Series(expected_histogram, name="a"), histogram, almost=True)
def plot_histogram(data: Union["ps.DataFrame", "ps.Series"], **kwargs):
import plotly.graph_objs as go
import pyspark.pandas as ps
bins = kwargs.get("bins", 10)
y = kwargs.get("y")
if y and isinstance(data, ps.DataFrame):
# Note that the results here are matched with matplotlib. x and y
# handling is different from pandas' plotly output.
data = data[y]
psdf, bins = HistogramPlotBase.prepare_hist_data(data, bins)
assert len(bins) > 2, "the number of buckets must be higher than 2."
output_series = HistogramPlotBase.compute_hist(psdf, bins)
prev = float("%.9f" % bins[0]) # to make it prettier, truncate.
text_bins = []
for b in bins[1:]:
norm_b = float("%.9f" % b)
text_bins.append("[%s, %s)" % (prev, norm_b))
prev = norm_b
text_bins[
-1] = text_bins[-1][:-1] + "]" # replace ) to ] for the last bucket.
bins = 0.5 * (bins[:-1] + bins[1:])
output_series = list(output_series)
bars = []
for series in output_series:
bars.append(
go.Bar(
x=bins,
y=series,
name=name_like_string(series.name),
text=text_bins,
hovertemplate=("variable=" + name_like_string(series.name) +
"<br>value=%{text}<br>count=%{y}"),
))
layout_keys = inspect.signature(go.Layout).parameters.keys()
layout_kwargs = {k: v for k, v in kwargs.items() if k in layout_keys}
fig = go.Figure(data=bars, layout=go.Layout(**layout_kwargs))
fig["layout"]["barmode"] = "stack"
fig["layout"]["xaxis"]["title"] = "value"
fig["layout"]["yaxis"]["title"] = "count"
return fig