Merge pull request #132 from PatrikHlobil/#128--fix-broken-import

update poetry config

.github/workflows/python-package.yml

@@ -10,7 +10,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.7', '3.8', '3.9']
+        python-version: ['3.8', '3.9', '3.10', '3.11']
     steps:
     - uses: actions/checkout@v2
     - name: Set up Python ${{ matrix.python-version }}
@@ -19,13 +19,15 @@ jobs:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
       run: |
-        sudo apt-get update
-        sudo apt-get install openjdk-8-jre
+        sudo apt update
+        sudo apt install proj-bin
+        sudo apt install openjdk-8-jre
         python -m pip install --upgrade pip
         python -m pip install poetry
-        # Only Test Pyspark API for supported Python versions:
-        if [ "${{ matrix.python-version }}" != "3.10" ]; then echo "Install Pyspark" && poetry add pyspark; fi
         poetry install
+        # Only Test GeoPandas and Pyspark API for supported Python versions:
+        if [ "${{ matrix.python-version }}" != "3.11" ]; then echo "Install Pyspark" && poetry add pyspark; fi
+        if [ "${{ matrix.python-version }}" == "3.8" ]; then echo "Install GeoPandas" && poetry add geopandas; fi
     - name: Test with pytest
       run: |
         poetry run pytest --color=yes -s -x -vv --cov-report term-missing --cov=pandas_bokeh Tests/

.pre-commit-config.yaml

@@ -4,15 +4,15 @@ repos:
     hooks:
     - id: isort
   - repo: https://github.com/ambv/black
-    rev: 20.8b1
+    rev: 23.1.0
     hooks:
     - id: black
-  - repo: https://gitlab.com/pycqa/flake8
-    rev: 3.9.0 
+  - repo: https://github.com/pycqa/flake8
+    rev: 6.0.0
     hooks:
     - id: flake8
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v3.4.0
+    rev: v4.4.0
     hooks:
       - id: check-json
       - id: check-merge-conflict

Release_Notes.md

@@ -146,4 +146,6 @@ Plots like scatterplot or histogram also have many more additional customization
 
 * 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)
+* Bugfixes (thanks @vroger11, @Sigmun, @ToniSkulj)
+* Drop support for Python3.8
+* Add support for Python3.10 and Python3.11

Tests/test_GeoPandasBokeh.py

@@ -1,10 +1,6 @@
-import json
 import os
 import sys
 
-import geopandas as gpd
-import numpy as np
-import pandas as pd
 import pytest
 
 import pandas_bokeh
@@ -13,16 +9,20 @@
 test_sets_directory = os.path.join(os.path.dirname(directory), "docs", "Testdata")
 os.makedirs(os.path.join(directory, "Plots"), exist_ok=True)
 
+# Pyspark requires Python < 3.9:
+if sys.version_info < (3, 9):
+    import geopandas as gpd
+else:
+    pytestmark = pytest.mark.skip
+
 
 @pytest.fixture
 def df_states():
-
     return gpd.read_file(os.path.join(test_sets_directory, "states", "states.geojson"))
 
 
 @pytest.fixture
 def df_cities():
-
     return gpd.read_file(
         os.path.join(
             test_sets_directory,

Tests/test_PandasBokeh.py

@@ -22,7 +22,6 @@
 
 @pytest.fixture(scope="function")
 def df_stock():
-
     np.random.seed(42)
     df_stock = pd.DataFrame(
         {"Google": np.random.randn(1000) + 0.2, "Apple": np.random.randn(1000) + 0.17},
@@ -37,7 +36,6 @@ def df_stock():
 
 @pytest.fixture(scope="function")
 def df_iris():
-
     # Load Iris Dataset:
     df_iris = pd.read_csv(os.path.join(TEST_SETS_DIRECTORY, "iris", "iris.csv"))
 
@@ -46,7 +44,6 @@ def df_iris():
 
 @pytest.fixture(scope="function")
 def df_fruits():
-
     data = {
         "fruits": ["Apples", "Pears", "Nectarines", "Plums", "Grapes", "Strawberries"],
         "2015": [2, 1, 4, 3, 2, 4],
@@ -61,7 +58,6 @@ def df_fruits():
 
 @pytest.fixture(scope="function")
 def df_hist():
-
     np.random.seed(42)
 
     df_hist = pd.DataFrame(
@@ -78,7 +74,6 @@ def df_hist():
 
 @pytest.fixture(scope="function")
 def df_energy():
-
     df_energy = pd.read_csv(
         os.path.join(TEST_SETS_DIRECTORY, "energy", "energy.csv"), parse_dates=["Year"]
     )
@@ -88,7 +83,6 @@ def df_energy():
 
 @pytest.fixture(scope="function")
 def df_election():
-
     df_election = pd.read_csv(
         os.path.join(TEST_SETS_DIRECTORY, "Bundestagswahl", "Bundestagswahl.csv")
     )
@@ -98,7 +92,6 @@ def df_election():
 
 @pytest.fixture(scope="function")
 def df_mapplot():
-
     df_mapplot = pd.read_csv(
         os.path.join(TEST_SETS_DIRECTORY, "populated places", "populated_places.csv")
     )
@@ -279,8 +272,8 @@ def test_pointplot():
     "Test for pointplot"
 
     x = np.arange(-3, 3, 0.1)
-    y2 = x ** 2
-    y3 = x ** 3
+    y2 = x**2
+    y3 = x**3
     df = pd.DataFrame({"x": x, "Parabula": y2, "Cube": y3})
 
     arguments = dict(

Tests/test_PySpark.py

@@ -10,20 +10,20 @@
 BASE_DIR = os.path.dirname(__file__)
 os.makedirs(os.path.join(BASE_DIR, "Plots"), exist_ok=True)
 
+# Pyspark requires Python < 3.11:
+if sys.version_info < (3, 11):
+    from pyspark.sql import SparkSession
+else:
+    pytestmark = pytest.mark.skip
+
 
 @pytest.fixture
 def spark():
-    # Start PySpark
-    from pyspark.sql import SparkSession
-
     spark = SparkSession.builder.getOrCreate()
     yield spark
     spark.stop()
 
 
-@pytest.mark.skipif(
-    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"""
 

description.md

@@ -0,0 +1,60 @@
+# Pandas Bokeh
+
+**Pandas Bokeh** provides a [Bokeh](https://bokeh.pydata.org/en/latest/) plotting backend for [Pandas](https://pandas.pydata.org/) and [GeoPandas](http://geopandas.org/), similar to the already existing [Visualization](https://pandas.pydata.org/pandas-docs/stable/visualization.html) feature of Pandas. Importing the library adds a complementary plotting method ***plot_bokeh()*** on **DataFrames** and **Series**. It also has native plotting backend support for Pandas >= 0.25.
+
+For more information and examples have a look at the [Github Repository](https://github.com/PatrikHlobil/Pandas-Bokeh).
+
+---
+
+## Installation
+
+
+You can install **Pandas Bokeh** from *PyPI* via **pip**:
+
+    pip install pandas-bokeh
+
+or *conda*:
+
+    conda install -c patrikhlobil pandas-bokeh
+
+**Pandas Bokeh** is officially supported on Python 3.5 and above.
+
+---
+
+## Description
+
+With **Pandas Bokeh**, creating stunning, interactive, HTML-based visualization is as easy as calling:
+```python
+df.plot_bokeh()
+```
+
+The following plot types are supported:
+
+* line
+* step
+* point
+* scatter
+* bar
+* histogram
+* area
+* pie
+* mapplot
+
+<br>
+
+Furthermore, also **GeoPandas** and **Pyspark** have a new plotting backend as can be seen in the provided [examples](https://github.com/PatrikHlobil/Pandas-Bokeh#geoplots).
+
+<br>
+
+**Pandas Bokeh** is a high-level API for **Bokeh** on top of **Pandas** and **GeoPandas** that tries to figure out best, what the user wants to plot. Nevertheless, there are many options for customizing the plots, for example:
+
+* **figsize**: Choose width & height of the plot
+* **title**: Sets title of the plot
+* **xlim**/**ylim**: Set visible range of plot for x- and y-axis (also works for *datetime x-axis*)
+* **xlabel**/**ylabel**: Set x- and y-labels
+* **logx**/**logy**: Set log-scale on x-/y-axis
+* **xticks**/**yticks**: Explicitly set the ticks on the axes
+* **colormap**: Defines the colors to plot. Can be either a list of colors or the name of a [Bokeh color palette](https://bokeh.pydata.org/en/latest/docs/reference/palettes.html)
+* **hovertool_string**: For customization of hovertool content
+
+Each plot type like scatterplot or histogram further has many more additional customization options that is described [here](https://github.com/PatrikHlobil/Pandas-Bokeh).

docs/sphinx/source/utils/make_plots.py

@@ -37,8 +37,8 @@ def df_stocks() -> pd.DataFrame:
 
 def df_parabula_cube() -> pd.DataFrame:
     x = np.arange(-3, 3, 0.1)
-    y2 = x ** 2
-    y3 = x ** 3
+    y2 = x**2
+    y3 = x**3
     df = pd.DataFrame({"x": x, "Parabula": y2, "Cube": y3})
 
     return df
@@ -395,6 +395,5 @@ def _return_plot_functions() -> Callable:
 
 
 if __name__ == "__main__":
-
     plots = make_and_return_plots()
     print(list(plots.keys()))

pandas_bokeh/__init__.py

@@ -10,7 +10,7 @@
 from .geoplot import geoplot
 from .plot import FramePlotMethods, plot
 
-__version__ = "0.5.5"
+__version__ = "0.6.0"
 
 
 # Register plot_bokeh accessor for Pandas DataFrames and Series:

pandas_bokeh/base.py

@@ -171,7 +171,6 @@ def output_file(filename, title="Bokeh Plot", mode="cdn", root_dir=None):
 def show(
     obj, browser=None, new="tab", notebook_handle=False, notebook_url="localhost:8888"
 ):
-
     global SUPPRESS_OUTPUT
     if SUPPRESS_OUTPUT:
         return obj

pandas_bokeh/geoplot.py

@@ -646,7 +646,6 @@ def geoplot(  # noqa C901
         )
 
     if "Polygon" in layertypes:
-
         if "line_color" not in kwargs:
             kwargs["line_color"] = "black"
 
@@ -723,7 +722,6 @@ def geoplot(  # noqa C901
 
     # Add Slider Widget:
     if slider is not None:
-
         if slider_range is None:
             slider_start = 0
             slider_end = len(slider) - 1