here is my NIFTY PSU BANK - HistoricalPE_PBDIV_Data EDA app

Financial APIs/NIFTY PSU BANK - HistoricalPE_PBDIV_Data EDA app/EDA app.py

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+import pandas as pd
+import matplotlib.pyplot as plt
+import gradio as gr
+import os
+import numpy as np
+
+# Define the path to the CSV file
+csv_file_path = 'NIFTY PSU BANK - HistoricalPE_PBDIV_Data.csv'
+
+def visualize_eda(start_date, end_date):
+    # Create a directory to save plots
+    if not os.path.exists('eda_plots'):
+        os.makedirs('eda_plots')
+
+    # Initialize output paths
+    line_plot_path = 'eda_plots/line_plot.png'
+    bar_plot_path = 'eda_plots/bar_plot.png'
+    hist_plot_path = 'eda_plots/hist_plot.png'
+    scatter_plot_path = 'eda_plots/scatter_plot.png'
+
+    # Load the data from the CSV file
+    try:
+        df = pd.read_csv(csv_file_path, parse_dates=True, index_col=0)
+    except Exception as e:
+        return [None, None, None, None, f"Error loading CSV file: {e}"]
+
+    # Filter the data by the given date range
+    try:
+        df = df.loc[start_date:end_date]
+    except Exception as e:
+        return [None, None, None, None, f"Error filtering data: {e}"]
+
+    # Check for and handle non-numeric columns
+    df_numeric = df.select_dtypes(include=['float64', 'int64'])
+    if df_numeric.empty:
+        return [None, None, None, None, "Error: No numeric data found in CSV file."]
+
+    # Plot 1: Line plot of all numerical features
+    try:
+        plt.figure(figsize=(12, 6))
+        for column in df_numeric.columns:
+            plt.plot(df_numeric.index, df_numeric[column], label=column)
+        plt.title('Line Plot of Numerical Features')
+        plt.xlabel('Date')
+        plt.ylabel('Value')
+        plt.legend()
+        plt.savefig(line_plot_path)
+        plt.close()
+    except Exception as e:
+        return [None, None, None, None, f"Error generating line plot: {e}"]
+
+    # Plot 2: Bar plot of average values per month
+    try:
+        plt.figure(figsize=(12, 6))
+        monthly_avg = df_numeric.resample('M').mean()
+        monthly_avg.plot(kind='bar', figsize=(15, 7))
+        plt.title('Monthly Average of Numerical Features')
+        plt.xlabel('Month')
+        plt.ylabel('Average Value')
+        plt.savefig(bar_plot_path)
+        plt.close()
+    except Exception as e:
+        return [None, None, None, None, f"Error generating bar plot: {e}"]
+
+    # Plot 3: Histogram of numerical features
+    try:
+        plt.figure(figsize=(12, 6))
+        df_numeric.hist(bins=30, figsize=(15, 7))
+        plt.suptitle('Histogram of Numerical Features')
+        plt.savefig(hist_plot_path)
+        plt.close()
+    except Exception as e:
+        return [None, None, None, None, f"Error generating histogram: {e}"]
+
+    # Plot 4: Scatter plot matrix of numerical features
+    try:
+        from pandas.plotting import scatter_matrix
+        plt.figure(figsize=(12, 12))
+        scatter_matrix(df_numeric, alpha=0.2, figsize=(15, 15), diagonal='kde')
+        plt.suptitle('Scatter Plot Matrix of Numerical Features')
+        plt.savefig(scatter_plot_path)
+        plt.close()
+    except Exception as e:
+        return [None, None, None, None, f"Error generating scatter plot matrix: {e}"]
+
+    # Return paths to generated plots
+    return [line_plot_path, bar_plot_path, hist_plot_path, scatter_plot_path, None]
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=visualize_eda,
+    inputs=[
+        gr.Textbox(label="Start Date (YYYY-MM-DD)", value="2002-01-02"),
+        gr.Textbox(label="End Date (YYYY-MM-DD)", value="2022-10-10")
+    ],
+    outputs=[
+        gr.Image(type="filepath", label="Line Plot"),
+        gr.Image(type="filepath", label="Bar Plot"),
+        gr.Image(type="filepath", label="Histogram"),
+        gr.Image(type="filepath", label="Scatter Plot Matrix"),
+        gr.Textbox(label="Error Message", type="text")  # Add a textbox for error messages
+    ],
+    live=False  # This will add an explicit "Submit" button
+)
+
+# Launch the Gradio app
+iface.launch(share=True, inbrowser=True)