Updated isort and pre-commit.

.gitignore

@@ -3,6 +3,9 @@ __pycache__
 .vscode
 .coverage
 .python-version
+.pytest_cache
+cb_model.onnx
+encoding.json
 htmlcov
 dist
 coolpandas.egg-info

.pre-commit-config.yaml

@@ -13,14 +13,14 @@ repos:
             "--rcfile=pyproject.toml",
           ]
   - repo: https://github.com/psf/black
-    rev: 22.10.0
+    rev: 23.3.0
     hooks:
       - id: black
         language_version: python3.11
         args: [--config=pyproject.toml]
         entry: black --check .
   - repo: https://github.com/pycqa/isort
-    rev: 5.10.1
+    rev: 5.12.0
     hooks:
       - id: isort
         language_version: python3.11

coolpandas/eda/duplicates.py

@@ -1,49 +1,49 @@
-"""DataFrames cleaning module."""
-import pandas as pd
-
-
-def duplicated_rows(
-    data_frame: pd.DataFrame, display_summary: bool = True, drop: bool = False
-) -> pd.DataFrame:
-    """Get duplicated rows in a DataFrame and drop them if specified.
-    Args:
-        data_frame (pd.DataFrame): DataFrame to get duplicated rows.
-        display_summary (bool, optional): Whether to display summary. Defaults to True.
-        drop (bool, optional): Whether to drop duplicated rows. Defaults to True.
-    Returns:
-        pd.DataFrame: Duplicated rows.
-    """
-    duplicated_data_frame: pd.DataFrame = data_frame[data_frame.duplicated(keep=False)]
-    if display_summary:
-        print(f"Number of duplicated rows: {duplicated_data_frame.shape[0]}")
-    if drop:
-        data_frame.drop_duplicates(inplace=True)
-    if display_summary and drop:
-        print("DataFrame shape after dropping duplicated rows:")
-        print(data_frame.shape)
-    return duplicated_data_frame
-
-
-def duplicated_columns(
-    data_frame: pd.DataFrame, display_summary: bool = True, drop: bool = False
-) -> pd.DataFrame:
-    """Get duplicated columns in a DataFrame and drop them if specified.
-    Args:
-        data_frame (pd.DataFrame): DataFrame to get duplicated columns.
-        display_summary (bool, optional): Whether to display summary. Defaults to True.
-        drop (bool, optional): Whether to drop duplicated columns. Defaults to True.
-    Returns:
-        pd.DataFrame: Duplicated columns.
-    """
-    # uniques, indexes = np.unique(data_frame, return_index=True, axis=1)
-    # return pd.DataFrame(uniq, index=data_frame.index, columns=data_frame.columns[~indexes])
-    duplicates: pd.Series = data_frame.apply(lambda x: x.duplicated(), axis=1).all()
-    duplicated_data_frame: pd.DataFrame = data_frame[duplicates[duplicates].index]
-    if display_summary:
-        print(f"Number of duplicated columns: {duplicated_data_frame.shape[1]}")
-    if drop:
-        data_frame.drop(columns=duplicated_data_frame.columns, inplace=True)
-    if display_summary and drop:
-        print("DataFrame shape after dropping duplicated columns:")
-        print(data_frame.shape)
-    return duplicated_data_frame
+"""DataFrames cleaning module."""
+import pandas as pd
+
+
+def duplicated_rows(
+    data_frame: pd.DataFrame, display_summary: bool = True, drop: bool = False
+) -> pd.DataFrame:
+    """Get duplicated rows in a DataFrame and drop them if specified.
+    Args:
+        data_frame (pd.DataFrame): DataFrame to get duplicated rows.
+        display_summary (bool, optional): Whether to display summary. Defaults to True.
+        drop (bool, optional): Whether to drop duplicated rows. Defaults to True.
+    Returns:
+        pd.DataFrame: Duplicated rows.
+    """
+    duplicated_data_frame: pd.DataFrame = data_frame[data_frame.duplicated(keep=False)]
+    if display_summary:
+        print(f"Number of duplicated rows: {duplicated_data_frame.shape[0]}")
+    if drop:
+        data_frame.drop_duplicates(inplace=True)
+    if display_summary and drop:
+        print("DataFrame shape after dropping duplicated rows:")
+        print(data_frame.shape)
+    return duplicated_data_frame
+
+
+def duplicated_columns(
+    data_frame: pd.DataFrame, display_summary: bool = True, drop: bool = False
+) -> pd.DataFrame:
+    """Get duplicated columns in a DataFrame and drop them if specified.
+    Args:
+        data_frame (pd.DataFrame): DataFrame to get duplicated columns.
+        display_summary (bool, optional): Whether to display summary. Defaults to True.
+        drop (bool, optional): Whether to drop duplicated columns. Defaults to True.
+    Returns:
+        pd.DataFrame: Duplicated columns.
+    """
+    # uniques, indexes = np.unique(data_frame, return_index=True, axis=1)
+    # return pd.DataFrame(uniq, index=data_frame.index, columns=data_frame.columns[~indexes])
+    duplicates: pd.Series = data_frame.apply(lambda x: x.duplicated(), axis=1).all()
+    duplicated_data_frame: pd.DataFrame = data_frame[duplicates[duplicates].index]
+    if display_summary:
+        print(f"Number of duplicated columns: {duplicated_data_frame.shape[1]}")
+    if drop:
+        data_frame.drop(columns=duplicated_data_frame.columns, inplace=True)
+    if display_summary and drop:
+        print("DataFrame shape after dropping duplicated columns:")
+        print(data_frame.shape)
+    return duplicated_data_frame

coolpandas/plot/__init__.py

@@ -2,4 +2,5 @@
 from .barplot import barplot
 from .distplot import distplot
 from .geoplot import geoplot
+from .lineplot import lineplot
 from .mapplot import mapplot

coolpandas/plot/lineplot.py

@@ -0,0 +1,40 @@
+"""Lineplot module."""
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+
+from .style import custom_template, format_title
+
+
+def lineplot(
+    data_frame: pd.DataFrame,
+    x_axis: str,
+    y_axis: str,
+    title: str,
+    subtitle: str = None,
+    **kwargs,
+) -> go.Figure:
+    """Create a bar plot.
+
+    Args:
+        data_frame (pd.DataFrame): DataFrame to plot.
+        x_axis (str): Column to use as x axis.
+        y_axis (str): Column to use as y axis.
+        title (str): Title of the plot.
+        subtitle (str, optional): Subtitle of the plot. Defaults to None.
+        **kwargs: Keyword arguments to pass to plotly.express.bar.
+
+    Returns:
+        go.Figure: Bar plot figure.
+    """
+    fig = px.line(
+        data_frame,
+        x=x_axis,
+        y=y_axis,
+        title=format_title(title, subtitle=subtitle),
+        template=custom_template,
+        width=800,
+        height=400,
+        **kwargs,
+    )
+    return fig

requirements.txt

@@ -1,12 +1,12 @@
-pandas==1.5.1
-scipy==1.9.3
-scikit-learn==1.1.3
-plotly==5.11.0
-nbformat==5.7.0
-ipython==8.6.0
-openrouteservice==2.3.3
-pytest-cov==4.0.0
-black==22.10.0
-pylint==2.15.5
-isort==5.10.1
-pre-commit==2.20.0
+pandas>=1.5.1
+scipy>=1.9.3
+scikit-learn>=1.1.3
+plotly>=5.11.0
+nbformat>=5.7.0
+ipython>=8.6.0
+openrouteservice>=2.3.3
+pytest-cov>=4.0.0
+black>=22.10.0
+pylint>=2.15.5
+isort>=5.12.0
+pre-commit>=2.20.0

tests/eda/test_duplicates.py

@@ -1,56 +1,56 @@
-"""Test duplicates.py functions."""
-from unittest.mock import MagicMock, patch
-
-import pandas as pd
-from numpy.testing import assert_equal
-
-from coolpandas import eda
-
-
-@patch("builtins.print")
-def test_duplicated_rows(mock_print: MagicMock, test_dataframe: pd.DataFrame) -> None:
-    """Test duplicated_rows function."""
-    duplicated_rows: pd.DataFrame = eda.duplicated_rows(
-        test_dataframe, display_summary=False, drop=False
-    )
-    assert duplicated_rows.empty
-
-    test_dataframe_duplicated: pd.DataFrame = pd.concat(
-        [test_dataframe, test_dataframe.head()]
-    )
-    duplicated_rows: pd.DataFrame = eda.duplicated_rows(
-        test_dataframe_duplicated, display_summary=False, drop=False
-    )
-    assert len(duplicated_rows) == 8
-
-    eda.duplicated_rows(test_dataframe_duplicated, display_summary=True, drop=False)
-    eda.duplicated_rows(test_dataframe_duplicated, display_summary=True, drop=True)
-    assert_equal(
-        test_dataframe_duplicated.fillna(0).values, test_dataframe.fillna(0).values
-    )
-    assert mock_print.call_count == 4
-
-
-@patch("builtins.print")
-def test_duplicated_columns(
-    mock_print: MagicMock, test_dataframe: pd.DataFrame
-) -> None:
-    """Test duplicated_columns function."""
-    duplicated_columns: list[str] = eda.duplicated_columns(
-        test_dataframe, display_summary=False, drop=False
-    )
-    assert duplicated_columns.empty
-
-    test_dataframe_duplicated: pd.DataFrame = test_dataframe.copy()
-    test_dataframe_duplicated["test"] = test_dataframe_duplicated["Animal"]
-    duplicated_columns: list[str] = eda.duplicated_columns(
-        test_dataframe_duplicated, display_summary=False, drop=False
-    )
-    assert_equal(duplicated_columns.columns.values, ["test"])
-
-    eda.duplicated_columns(test_dataframe_duplicated, display_summary=True, drop=False)
-    eda.duplicated_columns(test_dataframe_duplicated, display_summary=True, drop=True)
-    assert_equal(
-        test_dataframe_duplicated.columns.values, test_dataframe.columns.values
-    )
-    assert mock_print.call_count == 4
+"""Test duplicates.py functions."""
+from unittest.mock import MagicMock, patch
+
+import pandas as pd
+from numpy.testing import assert_equal
+
+from coolpandas import eda
+
+
+@patch("builtins.print")
+def test_duplicated_rows(mock_print: MagicMock, test_dataframe: pd.DataFrame) -> None:
+    """Test duplicated_rows function."""
+    duplicated_rows: pd.DataFrame = eda.duplicated_rows(
+        test_dataframe, display_summary=False, drop=False
+    )
+    assert duplicated_rows.empty
+
+    test_dataframe_duplicated: pd.DataFrame = pd.concat(
+        [test_dataframe, test_dataframe.head()]
+    )
+    duplicated_rows: pd.DataFrame = eda.duplicated_rows(
+        test_dataframe_duplicated, display_summary=False, drop=False
+    )
+    assert len(duplicated_rows) == 8
+
+    eda.duplicated_rows(test_dataframe_duplicated, display_summary=True, drop=False)
+    eda.duplicated_rows(test_dataframe_duplicated, display_summary=True, drop=True)
+    assert_equal(
+        test_dataframe_duplicated.fillna(0).values, test_dataframe.fillna(0).values
+    )
+    assert mock_print.call_count == 4
+
+
+@patch("builtins.print")
+def test_duplicated_columns(
+    mock_print: MagicMock, test_dataframe: pd.DataFrame
+) -> None:
+    """Test duplicated_columns function."""
+    duplicated_columns: list[str] = eda.duplicated_columns(
+        test_dataframe, display_summary=False, drop=False
+    )
+    assert duplicated_columns.empty
+
+    test_dataframe_duplicated: pd.DataFrame = test_dataframe.copy()
+    test_dataframe_duplicated["test"] = test_dataframe_duplicated["Animal"]
+    duplicated_columns: list[str] = eda.duplicated_columns(
+        test_dataframe_duplicated, display_summary=False, drop=False
+    )
+    assert_equal(duplicated_columns.columns.values, ["test"])
+
+    eda.duplicated_columns(test_dataframe_duplicated, display_summary=True, drop=False)
+    eda.duplicated_columns(test_dataframe_duplicated, display_summary=True, drop=True)
+    assert_equal(
+        test_dataframe_duplicated.columns.values, test_dataframe.columns.values
+    )
+    assert mock_print.call_count == 4