Merge pull request #18 from Casyfill/black

Black

Author: jakevdp

.gitignore

@@ -102,3 +102,10 @@ venv.bak/
 
 # mypy
 .mypy_cache/
+
+
+# vscode
+.vscode/
+
+#examples
+examples/*.ipynb

.pre-commit-config.yaml

@@ -0,0 +1,6 @@
+repos:
+-   repo: https://github.com/psf/black
+    rev: stable
+    hooks:
+    - id: black
+      language_version: python3.6

README.md

@@ -1,6 +1,7 @@
 # altair_pandas
 
 [![build status](http://img.shields.io/travis/altair-viz/altair_pandas/master.svg?style=flat)](https://travis-ci.org/altair-viz/altair_pandas)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
 
 Altair backend for pandas plotting functions.
 

altair_pandas/__init__.py

@@ -1,5 +1,5 @@
 """Altair plotting extension for pandas."""
 __version__ = "0.1.0dev0"
-__all__ = ['plot']
+__all__ = ["plot"]
 
 from ._core import plot

altair_pandas/_core.py

@@ -8,6 +8,7 @@ def _valid_column(column_name):
 
 class _PandasPlotter:
     """Base class for pandas plotting."""
+
     @classmethod
     def create(cls, data):
         if isinstance(data, pd.Series):
@@ -20,6 +21,7 @@ def create(cls, data):
 
 class _SeriesPlotter(_PandasPlotter):
     """Functionality for plotting of pandas Series."""
+
     def __init__(self, data):
         if not isinstance(data, pd.Series):
             raise ValueError(f"data: expected pd.Series; got {type(data)}")
@@ -32,7 +34,8 @@ def _preprocess_data(self, with_index=True):
             if isinstance(data.index, pd.MultiIndex):
                 data = data.copy()
                 data.index = pd.Index(
-                    [str(i) for i in data.index], name=data.index.name)
+                    [str(i) for i in data.index], name=data.index.name
+                )
             data = data.reset_index()
         else:
             data = data.to_frame()
@@ -41,25 +44,29 @@ def _preprocess_data(self, with_index=True):
 
     def _xy(self, mark, **kwargs):
         data = self._preprocess_data(with_index=True)
-        return alt.Chart(data, mark=mark).encode(
-            x=alt.X(data.columns[0], title=None),
-            y=alt.Y(data.columns[1], title=None),
-            tooltip=list(data.columns)
-        ).interactive()
+        return (
+            alt.Chart(data, mark=mark)
+            .encode(
+                x=alt.X(data.columns[0], title=None),
+                y=alt.Y(data.columns[1], title=None),
+                tooltip=list(data.columns),
+            )
+            .interactive()
+        )
 
     def line(self, **kwargs):
-        return self._xy('line', **kwargs)
+        return self._xy("line", **kwargs)
 
     def bar(self, **kwargs):
-        return self._xy({'type': 'bar', 'orient': 'vertical'}, **kwargs)
+        return self._xy({"type": "bar", "orient": "vertical"}, **kwargs)
 
     def barh(self, **kwargs):
-        chart = self._xy({'type': 'bar', 'orient': 'horizontal'}, **kwargs)
+        chart = self._xy({"type": "bar", "orient": "horizontal"}, **kwargs)
         chart.encoding.x, chart.encoding.y = chart.encoding.y, chart.encoding.x
         return chart
 
     def area(self, **kwargs):
-        return self._xy(mark='area', **kwargs)
+        return self._xy(mark="area", **kwargs)
 
     def scatter(self, **kwargs):
         raise ValueError("kind='scatter' can only be used for DataFrames.")
@@ -71,23 +78,28 @@ def hist(self, bins=None, **kwargs):
             bins = alt.Bin(maxbins=bins)
         elif bins is None:
             bins = True
-        return alt.Chart(data).mark_bar().encode(
-            x=alt.X(column, title=None, bin=bins),
-            y=alt.Y('count()', title='Frequency'),
+        return (
+            alt.Chart(data)
+            .mark_bar()
+            .encode(
+                x=alt.X(column, title=None, bin=bins),
+                y=alt.Y("count()", title="Frequency"),
+            )
         )
 
     def box(self, **kwargs):
         data = self._preprocess_data(with_index=False)
-        return alt.Chart(data).transform_fold(
-            list(data.columns), as_=['column', 'value']
-        ).mark_boxplot().encode(
-            x=alt.X('column:N', title=None),
-            y='value:Q',
+        return (
+            alt.Chart(data)
+            .transform_fold(list(data.columns), as_=["column", "value"])
+            .mark_boxplot()
+            .encode(x=alt.X("column:N", title=None), y="value:Q")
         )
 
 
 class _DataFramePlotter(_PandasPlotter):
     """Functionality for plotting of pandas DataFrames."""
+
     def __init__(self, data):
         if not isinstance(data, pd.DataFrame):
             raise ValueError(f"data: expected pd.DataFrame; got {type(data)}")
@@ -100,7 +112,8 @@ def _preprocess_data(self, with_index=True, usecols=None):
         if with_index:
             if isinstance(data.index, pd.MultiIndex):
                 data.index = pd.Index(
-                    [str(i) for i in data.index], name=data.index.name)
+                    [str(i) for i in data.index], name=data.index.name
+                )
             return data.reset_index()
         return data
 
@@ -120,82 +133,80 @@ def _xy(self, mark, x=None, y=None, **kwargs):
             assert y in data.columns
             y_values = [y]
 
-        return alt.Chart(
-            data,
-            mark=mark
-        ).transform_fold(
-            y_values, as_=['column', 'value']
-        ).encode(
-            x=x,
-            y=alt.Y('value:Q', title=None),
-            color=alt.Color('column:N', title=None),
-            tooltip=[x] + y_values,
-        ).interactive()
+        return (
+            alt.Chart(data, mark=mark)
+            .transform_fold(y_values, as_=["column", "value"])
+            .encode(
+                x=x,
+                y=alt.Y("value:Q", title=None),
+                color=alt.Color("column:N", title=None),
+                tooltip=[x] + y_values,
+            )
+            .interactive()
+        )
 
     def line(self, x=None, y=None, **kwargs):
-        return self._xy('line', x, y, **kwargs)
+        return self._xy("line", x, y, **kwargs)
 
     def area(self, x=None, y=None, **kwargs):
-        return self._xy('area', x, y, **kwargs)
+        return self._xy("area", x, y, **kwargs)
 
     # TODO: bars should be grouped, not stacked.
     def bar(self, x=None, y=None, **kwargs):
-        return self._xy(
-            {'type': 'bar', 'orient': 'vertical'}, x, y, **kwargs)
+        return self._xy({"type": "bar", "orient": "vertical"}, x, y, **kwargs)
 
     def barh(self, x=None, y=None, **kwargs):
-        chart = self._xy(
-            {'type': 'bar', 'orient': 'horizontal'}, x, y, **kwargs)
+        chart = self._xy({"type": "bar", "orient": "horizontal"}, x, y, **kwargs)
         chart.encoding.x, chart.encoding.y = chart.encoding.y, chart.encoding.x
         return chart
 
     def scatter(self, x, y, c=None, s=None, **kwargs):
         if x is None or y is None:
             raise ValueError("kind='scatter' requires 'x' and 'y' arguments.")
-        encodings = {'x': _valid_column(x), 'y': _valid_column(y)}
+        encodings = {"x": _valid_column(x), "y": _valid_column(y)}
         if c is not None:
-            encodings['color'] = _valid_column(c)
+            encodings["color"] = _valid_column(c)
         if s is not None:
-            encodings['size'] = _valid_column(s)
+            encodings["size"] = _valid_column(s)
         columns = list(set(encodings.values()))
         data = self._preprocess_data(with_index=False, usecols=columns)
-        encodings['tooltip'] = columns
-        return alt.Chart(data).mark_point().encode(
-            **encodings
-        ).interactive()
+        encodings["tooltip"] = columns
+        return alt.Chart(data).mark_point().encode(**encodings).interactive()
 
     def hist(self, bins=None, stacked=None, **kwargs):
         data = self._preprocess_data(with_index=False)
         if isinstance(bins, int):
             bins = alt.Bin(maxbins=bins)
         elif bins is None:
             bins = True
-        return alt.Chart(data).transform_fold(
-            list(data.columns), as_=['column', 'value']
-        ).mark_bar().encode(
-            x=alt.X('value:Q', title=None, bin=bins),
-            y=alt.Y('count()', title='Frequency', stack=stacked),
-            color=alt.Color('column:N')
+        return (
+            alt.Chart(data)
+            .transform_fold(list(data.columns), as_=["column", "value"])
+            .mark_bar()
+            .encode(
+                x=alt.X("value:Q", title=None, bin=bins),
+                y=alt.Y("count()", title="Frequency", stack=stacked),
+                color=alt.Color("column:N"),
+            )
         )
 
     def box(self, **kwargs):
         data = self._preprocess_data(with_index=False)
-        return alt.Chart(data).transform_fold(
-            list(data.columns), as_=['column', 'value']
-        ).mark_boxplot().encode(
-            x=alt.X('column:N', title=None),
-            y='value:Q',
+        return (
+            alt.Chart(data)
+            .transform_fold(list(data.columns), as_=["column", "value"])
+            .mark_boxplot()
+            .encode(x=alt.X("column:N", title=None), y="value:Q")
         )
 
 
-def plot(data, kind='line', **kwargs):
+def plot(data, kind="line", **kwargs):
     """Pandas plotting interface for Altair."""
     plotter = _PandasPlotter.create(data)
 
     if hasattr(plotter, kind):
         plotfunc = getattr(plotter, kind)
     else:
-        raise NotImplementedError(
-            f"kind='{kind}' for data of type {type(data)}")
+        raise NotImplementedError(f"kind='{kind}' for data of type {type(data)}")
 
     return plotfunc(**kwargs)

altair_pandas/conftest.py

@@ -7,16 +7,16 @@ def pytest_addoption(parser):
         "--backend_name",
         action="store",
         default="altair_pandas",
-        help="Plotting backend to use."
+        help="Plotting backend to use.",
     )
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def with_plotting_backend(request):
-    default = pd.get_option('plotting.backend')
-    pd.set_option('plotting.backend', request.config.getoption("backend_name"))
+    default = pd.get_option("plotting.backend")
+    pd.set_option("plotting.backend", request.config.getoption("backend_name"))
     yield
     try:
-        pd.set_option('plotting.backend', default)
+        pd.set_option("plotting.backend", default)
     except ImportError:
         pass  # matplotlib is not installed.