here is my Gross_Fiscal_Deficits EDA app

Financial APIs/Gross_Fiscal_Deficits 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 = 'Gross_Fiscal_Deficits.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)

Financial APIs/Gross_Fiscal_Deficits EDA app/Gross_Fiscal_Deficits.csv

@@ -0,0 +1,32 @@
+Year,1980-81,1981-82,1982-83,1983-84,1984-85,1985-86,1986-87,1987-88,1988-89,1989-90,1990-91,1991-92,1992-93,1993-94,1994-95,1995-96,1996-97,1997-98,1998-99,1999-00,2000-01,2001-02,2002-03,2003-04,2004-05,2005-06,2006-07,2007-08,2008-09,2009-10,2010-11,2011-12,2012-13,2013-14,2014-15 (RE),2015-16 (BE)
+Andhra Pradesh ,222.1,243.7,172.4,493,591.4,435,804,568,673,972,967.1,1125.3,1569.3,1833.2,2348.5,2416.8,2811.5,2427.8,5705.6,4976.4,7305.9,6723.1,7630,7450,8190,8300,5640,8790,12410,14010,11800,15400,17510,18040,20320,17580
+Arunachal Pradesh,�,�,�,�,�,�,23,38,1,75,25.8,-20.3,-9.3,16.1,73.2,39.8,70.1,121,55.4,59.3,210.1,274.7,210,250,390,260,-110,-20,330,500,-10,990,230,1610,3560,510
+Assam,-27.4,171.7,200.1,327.2,366.6,154,243,421,303,528,567.5,254.7,208.1,-17.9,710.6,652.2,73.8,142.1,338.2,1605.8,1540,1448.1,930,1390,2060,-360,-710,-790,-1410,4040,1990,1650,1520,3780,16260,4680
+Bihar,335.8,409.1,434.7,328,395.9,326,461,825,535,994,1594.6,1617,1330.9,1339.3,1342.1,1570.6,890.6,981.4,2378.9,6107.7,4884.3,4010.3,4910,4110,1240,3700,3020,1710,2510,5270,3970,5910,6550,8350,32820,13580
+Chhattisgarh,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,-47.5,1060.7,970,2200,1230,430,-30,130,1030,1760,-410,800,2660,5060,5770,6840
+Goa,�,�,�,�,�,�,61,72,64,95,96.1,125.3,90.3,59.6,44.5,97.3,104,124.6,269.1,341,412.9,412.8,380,450,550,600,490,540,810,1240,570,880,1150,1350,1740,2710
+Gujarat,246.5,253.9,376.6,397.6,520.2,514,900,976,735,952,1798.2,1875.7,1173.6,526.4,1292.4,1745.6,2358.3,3174.5,5619,6792,7987.6,6510.8,6080,9160,8700,6270,5650,4770,10440,15150,15070,11030,16490,18420,18380,22050
+Haryana,112,101.6,188.6,133.7,234.8,230,170,216,289,393,385.7,374.7,444.1,479.9,534.6,986,1099.4,1127.6,2240.4,2132.5,2265.2,2739.6,1470,2930,1210,290,-1180,1260,6560,10090,7260,7150,10360,8310,15630,16420
+Himachal Pradesh,-34.9,56.6,74.1,57.9,79.5,35,89,129,254,226,278.6,223.8,311.5,152.1,620.4,521.4,572,1202.2,1661.5,189.6,1844.8,1511.3,2340,2380,1810,720,920,550,2280,2780,1830,1630,2980,4010,3830,3280
+Jammu & Kashmir,144.5,135.9,142,198.3,248.2,247,244,417,410,524,661.2,448.7,203.5,87.7,-23.4,96.6,166.2,443.6,1054.4,1338.6,2166.4,748.1,1250,-20,1010,1590,1460,2610,2330,2230,2370,3690,4220,4550,6630,6630
+Jharkhand,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,1642.7,2190,1660,3650,4920,5260,6220,3750,1780,4840,1930,3400,2220,4910,5160
+Karnataka,225.9,118,279.9,287.7,563.3,550,514,518,497,625,558.5,917.8,1386,1254,1512.9,1456.8,1944,1609.8,3112.1,4276.5,4219.2,5869.9,5280,4500,3600,3690,4690,5330,8730,10870,10690,12300,14510,17090,19030,20220
+Kerala,179.8,61.7,122.9,299.3,232.3,323,440,448,412,604,798.5,803.4,732,935.2,1108.7,1302.7,1542.5,2413.9,3012.2,4536.6,3877.8,3269.4,4990,5540,4450,4180,3820,6100,6350,7870,7730,12810,15000,16940,16000,17700
+Madhya Pradesh,337.2,237.5,290.5,366.4,494.2,516,561,725,871,723,1019.3,984,876.3,982.5,1416.9,1633.4,1926.3,1820.6,4126.7,3911.4,2712.1,3649.4,4060,7320,6490,4570,2750,2780,4430,6200,5270,5760,9420,9880,13570,16750
+Maharashtra,463.3,488.5,551.5,739.7,1050.5,1234,1065,1014,1277,1844,1610.9,1656.9,2585.6,2265.3,2861.4,4150.8,4953.7,6442.2,7462.4,11706.2,8975.8,10897.7,14290,17930,18620,17630,11550,-2820,14000,26160,18860,19970,13740,26020,37250,30730
+Manipur,-6.7,27.1,17.4,26.2,14.5,-9,32,17,33,71,39.6,69.1,18.2,-20.4,62.1,104.7,167.5,187.5,106.2,655.8,234.4,340.3,250,290,450,270,480,-100,220,730,570,1050,0,-270,930,580
+Meghalaya,-7.7,16.5,15.1,10,2,-8,5,1.5,10,31,41.2,72.2,93.1,87.6,35.3,51.9,23.1,126.5,147.3,209.1,249.6,220.9,160,200,310,180,80,210,440,230,340,1070,400,380,530,820
+Mizoram,�,�,�,�,�,41,-22,102,11,-3,-94.4,4.8,59.5,7.6,38.4,70.7,125.3,124.2,132.3,179.1,375.3,422.4,320,310,230,400,190,390,90,310,650,210,580,750,2000,110
+Nagaland,-26.3,20.1,29.5,41,-4.6,-12,30,60,48,141,101.9,95.7,138.2,174.2,238.8,231,184.2,203.9,243.2,249,358.8,366.1,440,-160,220,310,160,400,340,520,310,540,650,460,850,1160
+Odisha,134.1,141.8,212.2,191.6,328.4,326,372,506,550,574,616.2,913.2,740.1,901.5,1158.9,1395.9,1602,1802.5,2915.5,3746.1,3325.3,3964.2,2820,3570,1370,280,-820,-1320,330,2270,660,-620,0,4630,9140,10400
+Punjab,159.8,178.3,182.8,262.1,479.2,566,343,968,833,909,1242.2,1150.5,1252,1493.4,1785.2,1364.6,1464.7,2477.6,3779.3,3194.7,3903.8,4958,4400,4880,4040,2660,4380,4600,6690,6170,7140,8490,9350,8790,10400,11900
+Rajasthan,206.7,326.5,274.9,297.5,362.7,343,467,903,736,581,544.8,792.4,1158.7,1470,1762.7,2574.3,2506.5,2552,5150.9,5361.2,4313.2,5748.4,6110,7370,6150,5150,3970,3410,6970,10300,4130,3630,8530,15190,23160,20610
+Sikkim,5.6,4.8,-1.8,6.9,-2.8,12,1,9,11,30,20.2,41.1,34.1,30.7,45.7,40.1,55.9,66.9,146.9,92.6,50.5,66.8,10,50,190,150,100,60,230,170,320,180,70,50,450,520
+Tamil Nadu,210.4,212.5,326.1,363.6,397.7,365,454,660,654,919,1126.3,1299.9,1749.1,1357.6,1496.4,1255.9,2445,2121.7,4777.1,5382.3,5076,4739.4,6740,5590,5570,2250,3960,3690,8550,11810,16650,17270,16520,20580,27350,31830
+Telangana,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0,17400,16970
+Tripura,-9.1,24.8,17.1,34.9,12.4,15,15,62,84,89,85.6,93.9,23,111,110,33.9,121.7,195.8,118.4,290.3,445.2,538.2,540,340,240,110,-130,20,270,-70,250,-260,-340,-50,1320,1940
+Uttar Pradesh,551.4,452,581.7,1082.3,1493.6,1058,1410,1014,1802,2482,3067.6,2836.6,3710.9,3165.8,4766.5,4380.6,5956.2,7576,11632.5,11098.7,10179.5,9898.1,9500,16650,13000,10080,9620,13790,20510,18690,17250,15430,19240,23680,28380,31560
+Uttarakhand,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,�,136.4,424.2,890,1410,2170,1880,890,1740,1840,2780,1840,1760,1600,2650,3970,4100
+West Bengal,289.2,380.1,497.8,413.9,339.7,259,587,551,579,1055,1633.7,1143.7,1012.5,1671.9,1965.3,2696.3,3396.9,4007.7,7109.1,11666.4,10920.2,11804.1,10570,12870,10650,9600,11430,11400,13560,24950,19530,17700,19150,25350,23880,15980
+Delhi,�,�,�,�,�,�,�,�,�,�,�,�,�,231.7,388.9,555.9,690,726.4,959.2,1381.6,1609.7,1733,2400,2440,1480,-250,410,2040,2820,3550,-730,2550,2280,3940,350,420
+Puducherry,,,,,,,,,,,,,,,,,,,,,,,,,,280,400,330,370,580,710,820,220,540,550,610

Financial APIs/Gross_Fiscal_Deficits EDA app/readme.md

@@ -0,0 +1,54 @@
+
+
+#  stocks Visualization App
+
+<img width="1599" alt="Screenshot 2024-08-03 at 1 29 46 AM" src="https://github.com/user-attachments/assets/b395de2a-4fab-4fae-b390-b8ec8b82cc2a">
+
+
+
+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!