Merge pull request #124 from PatrikHlobil/use-poetry-as-package-manager

use poetry as package manager

.github/workflows/python-package.yml

@@ -10,7 +10,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.6', '3.7', '3.8', '3.9']
+        python-version: ['3.7', '3.8', '3.9']
     steps:
     - uses: actions/checkout@v2
     - name: Set up Python ${{ matrix.python-version }}
@@ -22,9 +22,10 @@ jobs:
         sudo apt-get update
         sudo apt-get install openjdk-8-jre
         python -m pip install --upgrade pip
-        python -m pip install black pypandoc
-        pip install -r Tests/requirements_test.txt
+        python -m pip install poetry
+        # Only Test Pyspark API for supported Python versions:
+        if [ "${{ matrix.python-version }}" != "3.10" ]; then echo "Install Pyspark" && poetry add pyspark; fi
+        poetry install
     - name: Test with pytest
       run: |
-        pip install .
-        pytest --color=yes -s -x -vv --cov-report term-missing --cov=pandas_bokeh Tests/
+        poetry run pytest --color=yes -s -x -vv --cov-report term-missing --cov=pandas_bokeh Tests/

.gitignore

@@ -20,3 +20,5 @@ github-pages-tmp/
 !index.html
 !template.html
 docs/sphinx/source/index.md
+venv
+.DS_Store

CONTRIBUTING.md

@@ -69,3 +69,7 @@ Now, before every commit you make to your repository, it will automatically appl
 [verdimrc](https://github.com/verdimrc)
 
  * Pull request[#96](https://github.com/PatrikHlobil/Pandas-Bokeh/pull/96) *fix problem when passing string-values to `bins`*
+
+[vroger11](https://github.com/vroger11)
+
+ * Pull request[#115](https://github.com/PatrikHlobil/Pandas-Bokeh/pull/115)  *Fix longitude and latitude values checking*

README.md

@@ -379,7 +379,7 @@ p_scatter = df.plot_bokeh.scatter(
 )
 
 # Combine Table and Scatterplot via grid layout:
-pandas_bokeh.plot_grid([[data_table, p_scatter]], plot_width=400, plot_height=350)
+pandas_bokeh.plot_grid([[data_table, p_scatter]], width=400, height=350)
 ```
 <p id="scatterplot_picture"> </p>
 
@@ -468,7 +468,7 @@ p_stacked_hbar = df.plot_bokeh.barh(
 #Plot all barplot examples in a grid:
 pandas_bokeh.plot_grid([[p_bar, p_stacked_bar],
                         [p_hbar, p_stacked_hbar]], 
-                       plot_width=450)
+                       width=450)
 ```
 
 ![Barplot3](docs/Images/Barplot3.png)
@@ -556,7 +556,7 @@ p_hist_cum = df_hist.plot_bokeh.hist(
     title="Normal distributions (normed & cumulative)",
     show_figure=False)
 
-pandas_bokeh.plot_grid([[p_hist, p_hist_cum]], plot_width=450, plot_height=300)
+pandas_bokeh.plot_grid([[p_hist, p_hist_cum]], width=450, height=300)
 ```
 
 ![Histogram2](docs/Images/Histogram2.png)
@@ -1124,7 +1124,7 @@ df = pd.DataFrame({"Animal": ["Mouse", "Rabbit", "Dog", "Tiger", "Elefant", "Wal
                    "Weight [g]": [19, 3000, 40000, 200000, 6000000, 50000000]})
 p_scientific = df.plot_bokeh(x="Animal", y="Weight [g]", show_figure=False)
 p_non_scientific = df.plot_bokeh(x="Animal", y="Weight [g]", disable_scientific_axes="y", show_figure=False,)
-pandas_bokeh.plot_grid([[p_scientific, p_non_scientific]], plot_width = 450)
+pandas_bokeh.plot_grid([[p_scientific, p_non_scientific]], width = 450)
 ```
 
 ![Number format](docs/Images/Scientific_axes.png)
@@ -1209,16 +1209,16 @@ p_hist = df_hist.plot_bokeh(
 
 #Make Dashboard with Grid Layout:
 pandas_bokeh.plot_grid([[p_line, p_bar], 
-                        [p_scatter, p_hist]], plot_width=450)
+                        [p_scatter, p_hist]], width=450)
 ```
 
 ![Dashboard Layout](docs/Images/Startimage.gif)
 
 Using a combination of *row* and *column* elements (see also [Bokeh Layouts](https://bokeh.pydata.org/en/latest/docs/user_guide/layout.html)) allow for a very easy general arrangement of elements. An alternative layout to the one above is:
 
 ```python
-p_line.plot_width = 900
-p_hist.plot_width = 900
+p_line.width = 900
+p_hist.width = 900
 
 layout = pandas_bokeh.column(p_line,
                 pandas_bokeh.row(p_scatter, p_bar),

Release_Notes.md

@@ -141,3 +141,9 @@ Plots like scatterplot or histogram also have many more additional customization
 ## 0.5.5
 
 * Display adaptive xticks per default
+
+# 0.6.0
+
+* Drop support for Python 3.6
+* Rename **plot_height -> height, plot_width -> width** in `pandas_bokeh.plot_grid` interface
+* Bugfixes (i.e. fix of lattitude/longitude checking -> thanks @vroger11)

Tests/test_PandasBokeh.py

@@ -1,4 +1,3 @@
-import json
 import os
 
 import numpy as np
@@ -18,6 +17,7 @@
 ##############################################################################
 #################################FIXTURES#####################################
 ##############################################################################
+pytestmark = pytest.mark.filterwarnings("error")
 
 
 @pytest.fixture(scope="function")
@@ -547,7 +547,7 @@ def test_barplot_layout(df_fruits):
                 p_stacked_hbar_pandas_backend,
             ],
         ],
-        plot_width=450,
+        width=450,
         show_plot=False,
         return_html=True,
     )
@@ -681,8 +681,8 @@ def test_histogram_average_diplay(df_hist):
 
     p_average = pandas_bokeh.plot_grid(
         [[p_hist, p_hist_cum, p_hist_cum_pandas_backend]],
-        plot_width=450,
-        plot_height=300,
+        width=450,
+        height=300,
         show_plot=False,
     )
 
@@ -746,8 +746,8 @@ def test_area_plots(df_energy):
             [p_area, p_area_normed],
             [p_area_pandas_backend, p_area_normed_pandas_backend],
         ],
-        plot_width=450,
-        plot_height=300,
+        width=450,
+        height=300,
         show_plot=False,
     )
 
@@ -797,8 +797,8 @@ def test_pieplot(df_election):
             [p_pie, p_pie_multiple],
             [p_pie_pandas_backend, p_pie_multiple_pandas_backend],
         ],
-        plot_width=450,
-        plot_height=300,
+        width=450,
+        height=300,
         show_plot=False,
     )
 
@@ -833,8 +833,8 @@ def test_mapplot(df_mapplot):
             [p_map, p_map_accessor],
             [p_map_pandas_backend, p_map_accessor_pandas_backend],
         ],
-        plot_width=450,
-        plot_height=300,
+        width=450,
+        height=300,
         show_plot=False,
     )
 

Tests/test_PySpark.py

@@ -1,4 +1,3 @@
-import json
 import os
 import sys
 
@@ -23,7 +22,7 @@ def spark():
 
 
 @pytest.mark.skipif(
-    sys.version_info >= (3, 8), reason="Pyspark 2.4.2 requires Python <= 3.7"
+    sys.version_info >= (3, 10), reason="Pyspark 3.2.1 requires Python <= 3.9"
 )
 def test_basic_lineplot_pyspark(spark):
     """Test for basic lineplot with Pyspark"""

pandas_bokeh/__init__.py

@@ -82,12 +82,11 @@ def stepplot(self, **kwargs):
     pass
 
 
-# Define Bokeh-plot method for PySpark DataFrames:
-if sys.version_info[1] < 8:  # TODO: pyspark currently does not support Python 3.8!
-    try:
-        import pyspark
-
-        plot_bokeh = CachedAccessor("plot_bokeh", FramePlotMethods)
-        pyspark.sql.dataframe.DataFrame.plot_bokeh = plot_bokeh
-    except ImportError:
-        pass
+# Define Bokeh-plot method for PySpark DataFrames:¥
+try:
+    import pyspark
+
+    plot_bokeh = CachedAccessor("plot_bokeh", FramePlotMethods)
+    pyspark.sql.dataframe.DataFrame.plot_bokeh = plot_bokeh
+except ImportError:
+    pass

pandas_bokeh/base.py

@@ -70,9 +70,9 @@ def plot_grid(children, show_plot=True, return_html=False, **kwargs):
     -ncols (int, optional) – Specify the number of columns you would like in your grid.
         You must only pass an un-nested list of plots (as opposed to a list of lists of
         plots) when using ncols.
-    - plot_width (int, optional) – The width you would like all your
+    - width (int, optional) – The width you would like all your
         plots to be
-    - plot_height (int, optional) – The height you would like all your
+    - height (int, optional) – The height you would like all your
         plots to be.
     - toolbar_options (dict, optional) – A dictionary of options that
         will be used to construct the grid’s toolbar (an instance of ToolbarBox). If

pandas_bokeh/geoplot.py

@@ -115,7 +115,7 @@ def add_x_and_y_columns(row, geometry):
             df_new.append(add_x_and_y_columns(row, geometry))
 
         if geometry.type == "MultiPolygon":
-            for polygon in geometry:
+            for polygon in geometry.geoms:
                 df_new.append(add_x_and_y_columns(row, polygon))
 
     df_new = pd.DataFrame(df_new)
@@ -125,7 +125,6 @@ def add_x_and_y_columns(row, geometry):
 
 
 def get_tick_formatter(formatter_arg):
-
     if issubclass(formatter_arg.__class__, TickFormatter):
         return formatter_arg
     elif isinstance(formatter_arg, str):
@@ -225,8 +224,8 @@ def geoplot(  # noqa C901
         "title": title,
         "x_axis_label": xlabel,
         "y_axis_label": ylabel,
-        "plot_width": 600,
-        "plot_height": 400,
+        "width": 600,
+        "height": 400,
         "toolbar_location": toolbar_location,
         "active_scroll": "wheel_zoom",
         "x_axis_type": "mercator",
@@ -235,8 +234,8 @@ def geoplot(  # noqa C901
     }
     if figsize is not None:
         width, height = figsize
-        figure_options["plot_width"] = width
-        figure_options["plot_height"] = height
+        figure_options["width"] = width
+        figure_options["height"] = height
     if webgl:
         figure_options["output_backend"] = "webgl"
 

pandas_bokeh/plot.py

@@ -250,8 +250,8 @@ def plot(  # noqa C901
         "title": title,
         "toolbar_location": toolbar_location,
         "active_scroll": "wheel_zoom",
-        "plot_width": 600,
-        "plot_height": 400,
+        "width": 600,
+        "height": 400,
         "output_backend": "webgl",
         "sizing_mode": sizing_mode,
         "x_axis_location": x_axis_location,
@@ -261,8 +261,8 @@ def plot(  # noqa C901
 
     if figsize is not None:
         width, height = figsize
-        figure_options["plot_width"] = width
-        figure_options["plot_height"] = height
+        figure_options["width"] = width
+        figure_options["height"] = height
     if logx:
         figure_options["x_axis_type"] = "log"
     if logy:
@@ -1608,15 +1608,13 @@ def pieplot(
     max_col_stringlength = max([len(col) for col in data_cols])
 
     # Create Figure for Pieplot:
-    plot_width = figure_options["plot_width"]
-    plot_height = figure_options["plot_height"]
     title = figure_options["title"]
     toolbar_location = None
     x_range = (-1.4 - 0.05 * max_col_stringlength, 2)
     y_range = (-1.2, 1.2)
     p = figure(
-        plot_width=plot_width,
-        plot_height=plot_height,
+        width=figure_options["width"],
+        height=figure_options["height"],
         title=title,
         toolbar_location=toolbar_location,
         x_range=x_range,
@@ -2425,8 +2423,8 @@ def _initialize_rangetool(p, x_axis_type, source):
     # Initialize range tool plot
     p_rangetool = figure(
         title="Drag the box to change the range above.",
-        plot_height=130,
-        plot_width=p.plot_width,
+        height=130,
+        width=p.width,
         y_range=p.y_range,
         x_axis_type=x_axis_type,
         y_axis_type=None,
@@ -2436,7 +2434,14 @@ def _initialize_rangetool(p, x_axis_type, source):
 
     # Need to explicitly set the initial range of the plot for the range tool.
     start_index = int(0.75 * len(source["__x__values"]))
-    p.x_range = Range1d(source["__x__values"][start_index], source["__x__values"][-1])
+    start = source["__x__values"][start_index]
+    end = source["__x__values"][-1]
+    # Explicitly cast to python datetime object due to a bug in numpy
+    # (see https://github.com/bokeh/bokeh/blob/branch-3.0/bokeh/core/property/bases.py#L251):
+    if source["__x__values"].dtype.name == "datetime64[ns]":
+        start = datetime.datetime.fromtimestamp(int(start) / 1_000_000_000)
+        end = datetime.datetime.fromtimestamp(int(end) / 1_000_000_000)
+    p.x_range = Range1d(start, end)
 
     range_tool = RangeTool(x_range=p.x_range)
     range_tool.overlay.fill_color = "navy"