Implement OHLC plot (#623)

examples/reference/pandas/ohlc.ipynb

@@ -0,0 +1,123 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import hvplot.pandas  # noqa"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`ohlc` is a useful chart type to visualize stock movements"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from bokeh.sampledata import stocks\n",
+    "\n",
+    "df = pd.DataFrame(stocks.AAPL)\n",
+    "df['date'] = pd.to_datetime(df.date)\n",
+    "\n",
+    "df.iloc[-50:].hvplot.ohlc(grid=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can control the `neg_color`, `pos_color`, `line_color` and `bar_width`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.iloc[-50:].hvplot.ohlc(neg_color='indianred', pos_color='chartreuse', line_color='gray', bar_width=0.9, grid=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "By default `ohlc` will assume the `index` OR the first datetime column should be mapped to the x-axis and the first four non-datetime columns correspond to the O (open), H (high), L (low) and C (close) components. The default call is therefore equivalent to:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.iloc[-50:].hvplot.ohlc('date', ['open', 'low', 'high', 'close'], grid=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Using the HoloViews `RangeToolLink` we can make it easy to scroll through the data while still seeing an overview of the overall timeseries:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from holoviews.plotting.links import RangeToolLink\n",
+    "\n",
+    "df_2012 = df[df.date > pd.to_datetime('2012')]\n",
+    "\n",
+    "ohlc = df_2012.hvplot.ohlc(ylabel='Price ($)', grid=True, xaxis=None)\n",
+    "overview = df_2012.hvplot.ohlc(yaxis=None, height=150, fields={'date': 'Date'})\n",
+    "volume = df_2012.hvplot.step('date', 'volume', height=100, xaxis=None)\n",
+    "\n",
+    "RangeToolLink(overview.get(0), ohlc.get(0))\n",
+    "\n",
+    "layout = (volume + ohlc + overview).cols(1)\n",
+    "\n",
+    "layout.opts(merge_tools=False)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.8"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {},
+    "version_major": 2,
+    "version_minor": 0
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

hvplot/converter.py

@@ -20,7 +20,7 @@
     Curve, Scatter, Area, Bars, BoxWhisker, Dataset, Distribution,
     Table, HeatMap, Image, HexTiles, QuadMesh, Bivariate, Histogram,
     Violin, Contours, Polygons, Points, Path, Labels, RGB, ErrorBars,
-    VectorField
+    VectorField, Rectangles, Segments
 )
 from holoviews.plotting.bokeh import OverlayPlot, colormap_generator
 from holoviews.plotting.util import process_cmap
@@ -224,7 +224,9 @@ class HoloViewsConverter(object):
         the default is 'Wikipedia'.
     """
 
-    _gridded_types = ['image', 'contour', 'contourf', 'quadmesh', 'rgb', 'points', 'dataset']
+    _gridded_types = [
+        'image', 'contour', 'contourf', 'quadmesh', 'rgb', 'points', 'dataset'
+    ]
 
     _geom_types = ['paths', 'polygons']
 
@@ -258,6 +260,7 @@ class HoloViewsConverter(object):
         'step'     : ['where'],
         'area'     : ['y2'],
         'errorbars': ['yerr1', 'yerr2'],
+        'ohlc'     : ['bar_width', 'pos_color', 'neg_color', 'line_color'],
         'hist'     : ['bins', 'bin_range', 'normed', 'cumulative'],
         'heatmap'  : ['C', 'reduce_function', 'logz'],
         'hexbin'   : ['C', 'reduce_function', 'gridsize', 'logz', 'min_count'],
@@ -284,7 +287,7 @@ class HoloViewsConverter(object):
         'bar': Bars, 'barh': Bars, 'contour': Contours, 'contourf': Polygons,
         'points': Points, 'polygons': Polygons, 'paths': Path, 'step': Curve,
         'labels': Labels, 'rgb': RGB, 'errorbars': ErrorBars,
-        'vectorfield': VectorField,
+        'vectorfield': VectorField, 'ohlc': Rectangles
     }
 
     _colorbar_types = ['image', 'hexbin', 'heatmap', 'quadmesh', 'bivariate',
@@ -1743,6 +1746,51 @@ def bivariate(self, x=None, y=None, data=None):
         opts = self._get_opts('Bivariate', **self.kwds)
         return Bivariate(data, [x, y]).redim(**self._redim).opts(**opts)
 
+    def ohlc(self, x=None, y=None, data=None):
+        data = self.data if data is None else data
+        if x is None:
+            variables = [var for var in self.variables if var not in self.indexes]
+            if data[variables[0]].dtype.kind == 'M':
+                x = variables[0]
+            else:
+                x = self.indexes[0]
+        width = self.kwds.get('bar_width', 0.5)
+        if y is None:
+            o, h, l, c = [col for col in data.columns if col != x][:4]
+        else:
+            o, h, l, c = y
+        neg, pos = self.kwds.get('neg_color', 'red'), self.kwds.get('pos_color', 'green')
+        color_exp = (dim(o)>dim(c)).categorize({True: neg, False: pos})
+        ds = Dataset(data, [x], [o, h, l, c])
+        if ds.data[x].dtype.kind in 'SUO':
+            rects = Rectangles(ds, [x, o, x, c])
+        else:
+            if len(ds):
+                sampling = np.min(np.diff(ds[x])) * width/2.
+                ds = ds.transform(lbound=dim(x)-sampling, ubound=dim(x)+sampling)
+            else:
+                ds = ds.transform(lbound=dim(x), ubound=dim(x))
+            rects = Rectangles(ds, ['lbound', o, 'ubound', c])
+        segments = Segments(ds, [x, l, x, h])
+        rect_opts = self._get_opts('Rectangles')
+        rect_opts.pop('tools')
+        rect_opts['color'] = color_exp
+        seg_opts = self._get_opts('Segments')
+        tools = seg_opts.pop('tools', [])
+        if 'hover' in tools:
+            tools[tools.index('hover')] = HoverTool(tooltips=[
+                (x, '@{%s}' % x), ('Open', '@{%s}' % o), ('High', '@{%s}' % h),
+                ('Low', '@{%s}' % l), ('Close', '@{%s}' % c)
+            ])
+        seg_opts['tools'] = tools
+        seg_opts ['color'] = self.kwds.get('line_color', 'black')
+        if 'xlabel' not in seg_opts:
+            seg_opts['xlabel'] = '' if x == 'index' else x
+        if 'ylabel' not in seg_opts:
+            seg_opts['ylabel'] = ''
+        return (segments.redim(**self._redim).opts(**seg_opts) *
+                rects.redim(**self._redim).opts(**rect_opts))
+
     def table(self, x=None, y=None, data=None):
         data = self.data if data is None else data
         if isinstance(data.index, (DatetimeIndex, MultiIndex)):

hvplot/plotting/core.py

@@ -118,6 +118,7 @@ class hvPlotTabular(hvPlotBase):
         'scatter',
         'area',
         'errorbars',
+        'ohlc',
         'heatmap',
         'hexbin',
         'bivariate',
@@ -242,6 +243,26 @@ def errorbars(self, x=None, y=None, yerr1=None, yerr2=None, **kwds):
         return self(x, y, kind='errorbars',
                     yerr1=yerr1, yerr2=yerr2, **kwds)
 
+    def ohlc(self, x=None, y=None, **kwds):
+        """
+        OHLC
+
+        Parameters
+        ----------
+        x: string, optional
+            Field name to draw x coordinates from.
+        y: list or tuple, optional
+            Field names of the OHLC columns
+        **kwds : optional
+            Keyword arguments to pass on to
+            :py:meth:`hvplot.converter.HoloViewsConverter`.
+        Returns
+        -------
+        obj : HoloViews object
+            The HoloViews representation of the plot.
+        """
+        return self(kind='ohlc', x=x, y=y, **kwds)
+
     def heatmap(self, x=None, y=None, C=None, colorbar=True, **kwds):
         """
         HeatMap plot