refactor(eda): ran just ci

Author: Devin Lu

dataprep/clean/clean_country.py

@@ -271,7 +271,7 @@ def _format_country(
     return result, 2 if val != result else 3
 
 
-@lru_cache(maxsize=2**20)
+@lru_cache(maxsize=2 ** 20)
 def _check_country(country: str, input_formats: Tuple[str, ...], strict: bool, clean: bool) -> Any:
     """
     Finds the index of the given country in the DATA dataframe.
@@ -322,7 +322,7 @@ def _check_country(country: str, input_formats: Tuple[str, ...], strict: bool, c
     return (None, "unknown") if clean else False
 
 
-@lru_cache(maxsize=2**20)
+@lru_cache(maxsize=2 ** 20)
 def _check_fuzzy_dist(country: str, fuzzy_dist: int) -> Any:
     """
     A match is found if a country has an edit distance <= fuzzy_dist

dataprep/eda/create_diff_report/diff_formatter.py

@@ -68,7 +68,7 @@ def format_diff_report(
     cfg: Config,
     mode: Optional[str],
     progress: bool = True,
-    target: Optional[str] = None
+    target: Optional[str] = None,
 ) -> Dict[str, Any]:
     """
     Format the data and figures needed by create_diff_report
@@ -118,6 +118,7 @@ def format_diff_report(
             raise ValueError(f"Unknown mode: {mode}")
     return report
 
+
 def validate_target(target: str, df_list: List[pd.DataFrame]):
     """
     Helper function, verify that target column exists
@@ -128,7 +129,8 @@ def validate_target(target: str, df_list: List[pd.DataFrame]):
             exists = True
         break
     if not exists:
-        raise ValueError(f'Sorry, {target} is not a valid column')
+        raise ValueError(f"Sorry, {target} is not a valid column")
+
 
 def format_basic(df_list: List[pd.DataFrame], target: Optional[str], cfg: Config) -> Dict[str, Any]:
     """
@@ -295,7 +297,9 @@ def compute_plot_data(
         elif is_dtype(dtp, DateTime_v1()):
             plot_data.append((col, dtp, dask.compute(*datum), orig))  # workaround
 
-    return Intermediate(data=plot_data, stats=stats, visual_type="comparison_grid", target=target, df_list=pd_list)
+    return Intermediate(
+        data=plot_data, stats=stats, visual_type="comparison_grid", target=target, df_list=pd_list
+    )
 
 
 def _compute_variables(df: EDAFrame, cfg: Config) -> Dict[str, Any]:

dataprep/eda/diff/render.py

@@ -84,7 +84,7 @@ def bar_viz(
     df_labels: List[str],
     baseline: int,
     target: Optional[str] = None,
-    df_list: Optional[List[pd.DataFrame]] = None
+    df_list: Optional[List[pd.DataFrame]] = None,
 ) -> Figure:
     """
     Render a bar chart
@@ -119,7 +119,7 @@ def bar_viz(
         tools="hover",
         x_range=list(df[baseline].index),
         y_axis_type=yscale,
-        y_range=(min(col1_min, col2_min) * (1 - y_inc), max(col1_max, col2_max) * (1 + y_inc))
+        y_range=(min(col1_min, col2_min) * (1 - y_inc), max(col1_max, col2_max) * (1 + y_inc)),
     )
     row_names = None
     offset = np.linspace(-0.08 * len(df), 0.08 * len(df), len(df)) if len(df) > 1 else [0]
@@ -157,7 +157,7 @@ def bar_viz(
 
     if show_yticks and yscale == "linear":
         _format_axis(fig, 0, df[baseline].max(), "y")
-    
+
     df1, df2 = df_list[0], df_list[1]
     if target != col and target and col in df1.columns and col in df2.columns:
         col1, col2 = df_list[0][col], df_list[1][col]
@@ -166,12 +166,23 @@ def bar_viz(
         for names in row_names:
             row_avgs_1.append(df_list[0][target][col1 == names].mean())
             row_avgs_2.append(df_list[1][target][col2 == names].mean())
-        
+
         row_avgs_1 = [0 if math.isnan(x) else x for x in row_avgs_1]
         row_avgs_2 = [0 if math.isnan(x) else x for x in row_avgs_2]
-        fig.extra_y_ranges = {"Averages": Range1d(start=min(row_avgs_1 + row_avgs_2) * (1 - y_inc), end=max(row_avgs_1 + row_avgs_2) * (1 + y_inc))}
-        fig.multi_line([row_names, row_names], [row_avgs_1, row_avgs_2], color=['navy', 'firebrick'], y_range_name="Averages", line_width=4)
-        fig.add_layout(LinearAxis(y_range_name="Averages"), 'right')
+        fig.extra_y_ranges = {
+            "Averages": Range1d(
+                start=min(row_avgs_1 + row_avgs_2) * (1 - y_inc),
+                end=max(row_avgs_1 + row_avgs_2) * (1 + y_inc),
+            )
+        }
+        fig.multi_line(
+            [row_names, row_names],
+            [row_avgs_1, row_avgs_2],
+            color=["navy", "firebrick"],
+            y_range_name="Averages",
+            line_width=4,
+        )
+        fig.add_layout(LinearAxis(y_range_name="Averages"), "right")
     return fig
 
 
@@ -186,7 +197,7 @@ def hist_viz(
     df_labels: List[str],
     orig: Optional[List[str]] = None,
     target: Optional[str] = None,
-    df_list: Optional[List[pd.DataFrame]] = None
+    df_list: Optional[List[pd.DataFrame]] = None,
 ) -> Figure:
     """
     Render a histogram
@@ -222,14 +233,13 @@ def hist_viz(
         counts_max_2 = max(counts_list[1])
 
         y_start, y_end = min(counts_min_1, counts_min_2), max(counts_max_1, counts_max_2)
-    
 
     fig = Figure(
         plot_height=plot_height,
         plot_width=plot_width,
         title=col,
         toolbar_location=None,
-        y_axis_type=yscale
+        y_axis_type=yscale,
     )
     bins_list = []
     for i, hst in enumerate(hist):
@@ -252,7 +262,9 @@ def hist_viz(
         bottom = 0 if yscale == "linear" or df.empty else counts.min() / 2
         if y_start is not None and y_end is not None:
             # fig.y_range = (y_start * (1 - y_inc), y_end * (1 + y_inc))
-            fig.extra_y_ranges = {"Counts": Range1d(start=y_start * (1 - y_inc), end=y_end * (1 + y_inc))}
+            fig.extra_y_ranges = {
+                "Counts": Range1d(start=y_start * (1 - y_inc), end=y_end * (1 + y_inc))
+            }
             fig.quad(
                 source=df,
                 left="left",
@@ -262,7 +274,7 @@ def hist_viz(
                 top="freq",
                 fill_color=CATEGORY10[i],
                 line_color=CATEGORY10[i],
-                y_range_name="Counts"
+                y_range_name="Counts",
             )
         else:
             fig.quad(
@@ -273,11 +285,11 @@ def hist_viz(
                 alpha=0.5,
                 top="freq",
                 fill_color=CATEGORY10[i],
-                line_color=CATEGORY10[i]
+                line_color=CATEGORY10[i],
             )
         # if col == 'LotFrontage':
-            # breakpoint()
-    
+        # breakpoint()
+
     hover = HoverTool(tooltips=tooltips, attachment="vertical", mode="vline")
     fig.add_tools(hover)
 
@@ -325,9 +337,17 @@ def hist_viz(
         max_range = max(df1_bin_averages + df2_bin_averages)
         min_range = min(df1_bin_averages + df2_bin_averages)
 
-        fig.extra_y_ranges['Averages'] = Range1d(start=min_range * (1 - y_inc), end=max_range * (1 + y_inc))
-        fig.multi_line([bins_1, bins_2], [df1_bin_averages, df2_bin_averages], color=['navy', 'firebrick'], y_range_name="Averages", line_width=4)
-        fig.add_layout(LinearAxis(y_range_name="Averages", axis_label='Bin Averages'), 'right')
+        fig.extra_y_ranges["Averages"] = Range1d(
+            start=min_range * (1 - y_inc), end=max_range * (1 + y_inc)
+        )
+        fig.multi_line(
+            [bins_1, bins_2],
+            [df1_bin_averages, df2_bin_averages],
+            color=["navy", "firebrick"],
+            y_range_name="Averages",
+            line_width=4,
+        )
+        fig.add_layout(LinearAxis(y_range_name="Averages", axis_label="Bin Averages"), "right")
     return fig
 
 
@@ -678,7 +698,7 @@ def format_num_stats(data: Dict[str, List[Any]]) -> Dict[str, Dict[str, List[Any
     descriptive = {
         "Mean": data["mean"],
         "Standard Deviation": data["std"],
-        "Variance": [std**2 for std in data["std"]],
+        "Variance": [std ** 2 for std in data["std"]],
         "Sum": [mean * npres for mean, npres in zip(data["mean"], data["npres"])],
         "Skewness": [float(skew) for skew in data["skew"]],
         "Kurtosis": [float(kurt) for kurt in data["kurt"]],
@@ -734,7 +754,7 @@ def render_comparison_grid(itmdt: Intermediate, cfg: Config) -> Dict[str, Any]:
                 df_labels,
                 baseline if len(df) > 1 else 0,
                 target,
-                df_list
+                df_list,
             )
         elif is_dtype(dtp, Continuous()):
             if cfg.diff.density:
@@ -753,7 +773,7 @@ def render_comparison_grid(itmdt: Intermediate, cfg: Config) -> Dict[str, Any]:
                     df_labels,
                     orig,
                     target,
-                    df_list
+                    df_list,
                 )
         elif is_dtype(dtp, DateTime()):
             df, timeunit = data

dataprep/eda/intermediate.py

@@ -30,11 +30,11 @@ def __init__(self, *args: Any, **kwargs: Any) -> None:
             visual_type = kwargs.pop("visual_type")
             super().__init__(**kwargs)
             self.visual_type = visual_type
-            if 'target' in kwargs:
-                self.target = kwargs.pop('target')
-            
-            if 'df_list' in kwargs:
-                self.df_list = kwargs.pop('df_list')
+            if "target" in kwargs:
+                self.target = kwargs.pop("target")
+
+            if "df_list" in kwargs:
+                self.df_list = kwargs.pop("df_list")
         else:
             raise ValueError("Unsupported initialization")