Create app.py

app.py

@@ -0,0 +1,31 @@
+import gradio as gr
+import pandas as pd
+
+data1 = pd.read_csv('dataset/archive (2)/ball.csv')
+data2 = pd.read_csv('dataset/archive (2)/bat.csv')
+
+datasets = {'Bowling Data': pd.DataFrame(data1), 'Batting Data': pd.DataFrame(data2)}
+
+
+# Function to filter the DataFrame based on user inputs
+def filter_data(dataset_name='', name_x='', name_y='', start_date=''):
+    selected_dataset = datasets.get(dataset_name, pd.DataFrame())
+    filtered_df = selected_dataset[
+        selected_dataset['name_x'].str.contains(name_x, case=False) &
+        selected_dataset['name_y'].str.contains(name_y, case=False) &
+        selected_dataset['start_date'].str.contains(start_date, case=False)
+        ]
+    return filtered_df
+
+
+# Define the input components for the Gradio interface
+dataset_selector = gr.Dropdown(choices=list(datasets.keys()), label='Select Dataset')
+name_x_filter = gr.Textbox(label='Player Name', placeholder='eg. Virat Kohli')
+name_y_filter = gr.Textbox(label='Match Detail', placeholder='eg. India v Australia')
+start_date_filter = gr.Textbox(label='Match Date', placeholder='eg. 2015-10-13')
+
+# Create the Gradio interface
+iface = gr.Interface(fn=filter_data, inputs=[dataset_selector, name_x_filter, name_y_filter, start_date_filter], outputs='dataframe')
+
+# Launch the interface
+iface.launch()