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00:00:00+05:30,245.1999969482422,249.9499969482422,240.10000610351562,243.14999389648438,8227006,0.0,0.0 +2022-12-22 00:00:00+05:30,247.9499969482422,248.8000030517578,223.5,231.75,17713841,0.0,0.0 +2022-12-23 00:00:00+05:30,228.60000610351562,233.1999969482422,225.5500030517578,226.5,10671892,0.0,0.0 +2022-12-26 00:00:00+05:30,227.0,235.9499969482422,225.4499969482422,233.75,6753199,0.0,0.0 +2022-12-27 00:00:00+05:30,235.75,237.9499969482422,232.75,236.9499969482422,6266060,0.0,0.0 +2022-12-28 00:00:00+05:30,236.8000030517578,237.14999389648438,232.35000610351562,233.0,5414094,0.0,0.0 +2022-12-29 00:00:00+05:30,232.25,236.85000610351562,227.75,236.0,10042367,0.0,0.0 +2022-12-30 00:00:00+05:30,237.39999389648438,238.5,232.6999969482422,234.1999969482422,8281916,0.0,0.0 diff --git a/Financial APIs/BANDHAN BANK EDA APP/EDA app.py b/Financial APIs/BANDHAN BANK EDA APP/EDA app.py new file mode 100644 index 00000000..15c29747 --- /dev/null +++ b/Financial APIs/BANDHAN BANK EDA APP/EDA app.py @@ -0,0 +1,107 @@ +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 = 'walmart.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) diff --git "a/Financial APIs/BANDHAN BANK EDA APP/Screenshot 2024-08-03 at 1.18.03\342\200\257AM.png" "b/Financial APIs/BANDHAN BANK EDA APP/Screenshot 2024-08-03 at 1.18.03\342\200\257AM.png" new file mode 100644 index 00000000..101a8279 Binary files /dev/null and "b/Financial APIs/BANDHAN BANK EDA APP/Screenshot 2024-08-03 at 1.18.03\342\200\257AM.png" differ diff --git a/Financial APIs/BANDHAN BANK EDA APP/readme.md b/Financial APIs/BANDHAN BANK EDA APP/readme.md new file mode 100644 index 00000000..dcdb49c5 --- /dev/null +++ b/Financial APIs/BANDHAN BANK EDA APP/readme.md @@ -0,0 +1,54 @@ + + +# stocks Visualization App + +Screenshot 2024-08-07 at 1 35 18 PM + + + +This application provides interactive visualizations of numerical data from a CSV file using Gradio. The application allows users to view line plots and bar charts for the specified date range. + +## Features +- **Line Plot**: Displays trends for all numerical features over time. +- **Bar Plot**: Shows the average values of numerical features per month. + +## Requirements +- Python 3.x +- `pandas` +- `matplotlib` +- `gradio` + +You can install the required packages using: +```bash +pip install pandas matplotlib gradio +``` + +## Usage +1. **Prepare Your Data**: Ensure your CSV file is in the same directory as this script. The CSV should have a date column as the index and numerical columns for plotting. + +2. **Run the App**: Execute the script to launch the Gradio interface: + ```bash + python your_script_name.py + ``` + Replace `your_script_name.py` with the name of your Python script. + +3. **Interact with the App**: + - Enter the **Start Date** and **End Date** in the format `YYYY-MM-DD`. + - Click **Submit** to generate the plots. + - View the generated **Line Plot** and **Bar Plot**. + +## Example +For a CSV file with the following columns: `Date`, `Feature1`, `Feature2`, the app will generate: +- **Line Plot**: Trends of `Feature1` and `Feature2` over the selected date range. +- **Bar Plot**: Monthly averages of `Feature1` and `Feature2`. + +## Troubleshooting +- **No Numeric Data Error**: Ensure your CSV contains numeric data and the index column is of date type. +- **Plot Generation Error**: Check if the date range covers the data present in the CSV file. + +## License +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. + +--- + +Feel free to adjust the content as needed!