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Class hvPlotTabular

hvplot/plotting/core.py:154–1480  ·  view source on GitHub ↗

The plotting method: `df.hvplot(...)` creates a plot similarly to the familiar Pandas `df.plot` method. For more detailed options use a specific plotting method, e.g. `df.hvplot.line`. Reference: https://hvplot.holoviz.org/ref/api/index.html Plotting options: https://hvplot.h

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152
153
154class hvPlotTabular(hvPlotBase):
155 """
156 The plotting method: `df.hvplot(...)` creates a plot similarly to the familiar Pandas
157 `df.plot` method.
158
159 For more detailed options use a specific plotting method, e.g. `df.hvplot.line`.
160
161 Reference: https://hvplot.holoviz.org/ref/api/index.html
162
163 Plotting options: https://hvplot.holoviz.org/ref/plotting_options/index.html
164
165 Parameters
166 ----------
167 x : string, optional
168 Field name(s) to draw x-positions from. If not specified, the index is
169 used.
170 y : string or list, optional
171 Field name(s) to draw y-positions from. If not specified, all numerical
172 fields are used.
173 kind : string, optional
174 The kind of plot to generate, e.g. 'area', 'bar', 'line', 'scatter' etc. To see the
175 available plots run `print(df.hvplot.__all__)`.
176 **kwds : optional
177 Additional keywords arguments are documented in :ref:`plot-options`.
178
179
180 Returns
181 -------
182 A Holoviews object. You can `print` the object to study its composition and run
183
184 .. code-block::
185
186 import holoviews as hv
187 hv.help(the_holoviews_object)
188
189 to learn more about its parameters and options.
190
191 Examples
192 --------
193
194 .. code-block::
195
196 import pandas as pd
197 import hvplot.pandas
198
199 df = pd.DataFrame(
200 {
201 "actual": [100, 150, 125, 140, 145, 135, 123],
202 "forecast": [90, 160, 125, 150, 141, 141, 120],
203 "numerical": [1.1, 1.9, 3.2, 3.8, 4.3, 5.0, 5.5],
204 "date": pd.date_range("2022-01-03", "2022-01-09"),
205 "string": ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"],
206 },
207 )
208 line = df.hvplot.line(
209 x="numerical",
210 y=["actual", "forecast"],
211 ylabel="value",

Callers 12

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lag_plotFunction · 0.85
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