app

app.py

@@ -22,8 +22,13 @@ def outbreak(plot_type):
     if plot_type == "Find Data Correlation":
         fig = plt.figure()
         data_correlation = data_encoded.corr()
-        plt.rcParams["figure.figsize"] = [6,6]
-        sns.heatmap(data_correlation,xticklabels=data_correlation.columns,yticklabels=data_correlation.columns)
+        sns.heatmap(data_correlation, xticklabels = data_correlation.columns, yticklabels = data_correlation.columns)
+        return fig
+    if plot_type == "Filter Correlation Data":
+        fig = plt.figure()
+        filtered_df = df[['EmployeeExperience', 'EmployeeFeedbackSentiments', 'Age', 'SalarySatisfaction', 'BusinessTravel', 'HealthBenefitsSatisfaction']]
+        correlation_filter_data = filtered_df.corr()
+        sns.heatmap(correlation_filter_data, xticklabels = filtered_df.columns, yticklabels = filtered_df.columns)
         return fig
     if plot_type == "Age Attrition":
         fig = plt.figure()
@@ -43,7 +48,7 @@ def outbreak(plot_type):
         return fig
 
 inputs = [
-        gr.Dropdown(["Find Data Correlation", "Age Attrition", "Distance Attrition"], label="Data Correlation and Visualization")
+        gr.Dropdown(["Find Data Correlation", "Filter Correlation Data", "Age Attrition", "Distance Attrition"], label="Data Correlation and Visualization")
     ]
 
 outputs = gr.Plot()