Update app.py

app.py

@@ -5,6 +5,10 @@ from datasets import load_dataset
 from sklearn.model_selection import train_test_split
 import subprocess
 
+# Function to show value counts of 'Hair Loss'
+def show_hair_loss_counts():
+    return df['Hair Loss'].value_counts().to_json()  # Convert to JSON for display
+
 # Function to run commands
 def run_command(command):
     try:
@@ -74,6 +78,7 @@ def predict(*inputs):
 def explore_data(row_number):
     return df.iloc[row_number].to_dict()
     
+
 # Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("# Hair Health Dataset Exploration")
@@ -93,6 +98,12 @@ with gr.Blocks() as demo:
     # Unpack the dictionary values into a list of input components
     submit_button.click(predict, inputs=list(input_components.values()), outputs=[output])
 
+    gr.Markdown("## Hair Loss Value Counts")
+
+    value_counts_output = gr.JSON(label="Hair Loss Value Counts")
+    value_counts_button = gr.Button("Show Hair Loss Counts")
+    value_counts_button.click(show_hair_loss_counts, outputs=[value_counts_output])
+
     gr.Markdown("## Command Runner")
 
     command_input = gr.Textbox(label="Enter Command")
@@ -101,6 +112,5 @@ with gr.Blocks() as demo:
     run_button = gr.Button("Run Command")
     run_button.click(run_command, inputs=command_input, outputs=command_output)
 
-
 demo.launch()