Create app.py

app.py

@@ -0,0 +1,97 @@
+import gradio as gr
+import supabase
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+client = supabase.create_client(
+   "https://tmjhrfjckqnlvqnsspnr.supabase.co",
+    "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6InRtamhyZmpja3FubHZxbnNzcG5yIiwicm9sZSI6ImFub24iLCJpYXQiOjE3MjExMjE1NTgsImV4cCI6MjAzNjY5NzU1OH0.E34R6qPWavp2uRWKinZQICgdEqRjov46VnE38F24Al8"
+
+                   )
+
+def read_data():
+    response = client.table('Customer_purchase_dataset').select("*").execute()
+    df = pd.DataFrame(response.data)
+    return df
+
+df= read_data()
+#print(df.head)
+#print(df.dtypes)
+
+# Convert Gender to categorical
+df['Gender'] = df['Gender'].map({0: 'Female', 1: 'Male'})
+
+# Convert LoyaltyProgram to categorical
+df['LoyaltyProgram'] = df['LoyaltyProgram'].map({0: 'No', 1: 'Yes'})
+
+# Convert PurchaseStatus to categorical
+df['PurchaseStatus'] = df['PurchaseStatus'].map({0: 'Not Purchased', 1: 'Purchased'})
+
+# Function to create histogram
+def create_histogram(column):
+    plt.figure(figsize=(10, 6))
+    sns.histplot(data=df, x=column, kde=True)
+    plt.title(f'Histogram of {column}')
+    plt.xlabel(column)
+    plt.ylabel('Count')
+    return plt
+
+# Function to create scatter plot
+def create_scatter(x_column, y_column, hue_column):
+    plt.figure(figsize=(10, 6))
+    sns.scatterplot(data=df, x=x_column, y=y_column, hue=hue_column)
+    plt.title(f'{x_column} vs {y_column} (colored by {hue_column})')
+    plt.xlabel(x_column)
+    plt.ylabel(y_column)
+    return plt
+
+# Function to create box plot
+def create_boxplot(x_column, y_column):
+    plt.figure(figsize=(10, 6))
+    sns.boxplot(data=df, x=x_column, y=y_column)
+    plt.title(f'Box Plot of {y_column} by {x_column}')
+    plt.xlabel(x_column)
+    plt.ylabel(y_column)
+    return plt
+
+# Function to create bar plot
+def create_barplot(x_column, y_column):
+    plt.figure(figsize=(10, 6))
+    sns.barplot(data=df, x=x_column, y=y_column)
+    plt.title(f'Bar Plot of {y_column} by {x_column}')
+    plt.xlabel(x_column)
+    plt.ylabel(y_column)
+    plt.xticks(rotation=45)
+    return plt
+
+# Gradio interface
+def visualize(plot_type, x_column, y_column, hue_column):
+    if plot_type == "Histogram":
+        return create_histogram(x_column)
+    elif plot_type == "Scatter Plot":
+        return create_scatter(x_column, y_column, hue_column)
+    elif plot_type == "Box Plot":
+        return create_boxplot(x_column, y_column)
+    elif plot_type == "Bar Plot":
+        return create_barplot(x_column, y_column)
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=visualize,
+    inputs=[
+        gr.Dropdown(["Histogram", "Scatter Plot", "Box Plot", "Bar Plot"], label="Plot Type"),
+        gr.Dropdown(df.columns.tolist(), label="X-axis"),
+        gr.Dropdown(df.columns.tolist(), label="Y-axis"),
+        gr.Dropdown(df.columns.tolist(), label="Hue (for Scatter Plot)")
+
+    ],
+    outputs="plot",
+    title="Customer Purchase Data Visualization Dashboard",
+    description="Explore the customer purchase dataset through various visualizations."
+)
+
+# Launch the interface
+iface.launch()
+