Merge pull request #25 from wwymak/colorbar-formatting

Colorbar tick formatting

CONTRIBUTORS.md

@@ -4,4 +4,8 @@
 
 [munehiro-k](https://github.com/munehiro-k)
 
- * Pull Request: *escape column names in default hovertool_string of stacked bar plots*
+ * Pull Request: *escape column names in default hovertool_string of stacked bar plots*
+
+[wwymak](https://github.com/wwymak)
+
+ * Pull Request: *add option to customize colorbar tick formatting*

README.md

@@ -836,6 +836,55 @@ In a similar way, also GeoDataFrames with (multi)line shapes can be drawn using
 
 <br>
 
+---
+
+### Colorbar formatting:
+
+If you want to display the numerical labels on your colorbar with an alternative to the scientific format, you
+can pass in a one of the [bokeh number string formats](https://bokeh.pydata.org/en/latest/_modules/bokeh/models/formatters.html#NumeralTickFormatter)
+or an instance of one of the [bokeh.models.formatters](https://bokeh.pydata.org/en/latest/docs/reference/models/formatters.html) to the `colorbar_tick_format` argument
+in the geoplot
+
+An example of using the string format argument:
+
+```python
+df_states = gpd.read_file(r"https://raw.githubusercontent.com/PatrikHlobil/Pandas-Bokeh/master/Documentation/Testdata/states/states.geojson")
+
+df_states["STATE_NAME_SMALL"] = df_states["STATE_NAME"].str.lower()
+
+# pass in a string format to colorbar_tick_format to display the ticks as 10m rather than 1e7
+df_states.plot_bokeh(
+    figsize=(900, 600),
+    category="POPESTIMATE2017",
+    simplify_shapes=5000,    
+    colormap="Inferno",
+    colormap_uselog=True,
+    colorbar_tick_format="0.0a")
+```
+![colorbar_tick_format with string argument](Documentation/Images/geoplot_string_tickformatter.png)
+
+An example of using the bokeh `PrintfTickFormatter`:
+
+```python
+df_states = gpd.read_file(r"https://raw.githubusercontent.com/PatrikHlobil/Pandas-Bokeh/master/Documentation/Testdata/states/states.geojson")
+
+df_states["STATE_NAME_SMALL"] = df_states["STATE_NAME"].str.lower()
+
+for i in range(8):
+    df_states["Delta_Population_201%d"%i] = ((df_states["POPESTIMATE201%d"%i] / df_states["POPESTIMATE2010"]) -1 ) * 100
+
+# pass in a PrintfTickFormatter instance colorbar_tick_format to display the ticks with 2 decimal places  
+df_states.plot_bokeh(
+    figsize=(900, 600),
+    category="Delta_Population_2017",
+    simplify_shapes=5000,    
+    colormap="Inferno",
+    colorbar_tick_format=PrintfTickFormatter(format="%4.2f"))
+```
+![colorbar_tick_format with bokeh.models.formatter_instance](Documentation/Images/geoplot_PrintfTickFormatter.png)
+
+<br>
+
 <p id="Layouts"></p>
 
 ## Outputs, Formatting & Layouts

pandas_bokeh/geoplot.py

@@ -14,6 +14,10 @@
 
 from bokeh.colors import RGB
 import bokeh
+from bokeh.models import (
+        TickFormatter,
+        NumeralTickFormatter
+    )
 
 blue_colormap = [RGB(255 - i, 255 - i, 255) for i in range(256)]
 
@@ -143,6 +147,17 @@ def convert_geoDataFrame_to_patches(gdf, geometry_column_name="geometry"):
     return gdf_new
 
 
+def get_tick_formatter(formatter_arg):
+
+    if issubclass(formatter_arg.__class__, TickFormatter):
+        return formatter_arg
+    elif isinstance(formatter_arg, str):
+        return NumeralTickFormatter(format=formatter_arg)
+    else:
+        raise ValueError(
+            "<colorbar_tick_format> parameter only accepts a string or a objects of bokeh.models.formatters.")
+
+
 def geoplot(
     gdf_in,
     figure=None,
@@ -162,6 +177,7 @@ def geoplot(
     slider_range=None,
     slider_name="",
     show_colorbar=True,
+    colorbar_tick_format=None,
     xrange=None,
     yrange=None,
     hovertool=True,
@@ -676,6 +692,9 @@ def geoplot(
         if colormap_uselog:
             colorbar_options["ticker"] = LogTicker()
 
+        if colorbar_tick_format:
+            colorbar_options["formatter"] = get_tick_formatter(colorbar_tick_format)
+
         colorbar = ColorBar(**colorbar_options)
 
         p.add_layout(colorbar, "right")