Added Formatting and PyCodeStyle

src/Plotter.py

@@ -4,41 +4,46 @@ import pandas as pd
 import seaborn as sns
 from .Dataset import Dataset
 
+
 class Plotter:
     def __init__(self, dataset: Dataset):
         self.ds = dataset
         self.df = dataset.get_dataframe()
 
-    
     def customize_plot(self, fig, ax, styling_params):
-        if styling_params.get('title'):
+        if styling_params.get("title"):
             ax.set_title(styling_params["title"])
-    
+
     def distribution_plot(self, target):
-        grouped_data = self.df.groupby(target).size() 
+        grouped_data = self.df.groupby(target).size()
         plt.barh(grouped_data.index, grouped_data.values)
-        print(str(grouped_data), str(grouped_data.index), str(grouped_data.values))
+        print(
+            str(grouped_data),
+            str(grouped_data.index),
+            str(grouped_data.values),
+        )
         plt.xlabel("Size")
         plt.ylabel(target)
         plt.title(f"Distribution of {target}")
-        
-        
-    def plot_categorical_bar_chart(self, category1, category2, styling_params = {}):
+
+    def plot_categorical_bar_chart(
+        self, category1, category2, styling_params={}
+    ):
         ct = pd.crosstab(self.df[category1], self.df[category2])
         # Calculate percentages by row
-        ct_percent = ct.apply(lambda r: r/r.sum() * 100, axis=0)                
+        ct_percent = ct.apply(lambda r: r / r.sum() * 100, axis=0)
         fig, ax = plt.subplots()
         self.customize_plot(fig, ax, styling_params)
-        ct_percent.plot(kind='bar', ax=ax)
+        ct_percent.plot(kind="bar", ax=ax)
 
-
-    def plot_categorical_boxplot(self, target, category, styling_params = {}):
+    def plot_categorical_boxplot(self, target, category, styling_params={}):
         fig, ax = plt.subplots()
         self.customize_plot(fig, ax, styling_params)
-        sns.boxplot(x=category,y=target,data=self.df, palette='rainbow')
-
+        sns.boxplot(x=category, y=target, data=self.df, palette="rainbow")
 
-    def plot_categorical_histplot(self, target, category, styling_params = {}, bins= 30):
+    def plot_categorical_histplot(
+        self, target, category, styling_params={}, bins=30
+    ):
         uniques = self.ds.get_unique_column_values(category)
         fig, ax = plt.subplots()
         self.customize_plot(fig, ax, styling_params)
@@ -48,11 +53,11 @@ class Plotter:
             ax.hist(
                 anx_score,
                 weights=anx_score_weights,
-                bins = bins,
+                bins=bins,
                 alpha=0.5,
             )
 
-    def plot_scatterplot(self, target1, target2, styling_params = {}):
+    def plot_scatterplot(self, target1, target2, styling_params={}):
         fig, ax = plt.subplots()
         self.customize_plot(fig, ax, styling_params)
-        ax.scatter(self.df[target1], self.df[target2])
+        ax.scatter(self.df[target1], self.df[target2])
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