import gradio as gr
import pandas as pd

data1 = pd.read_csv('ball.csv')
data2 = pd.read_csv('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


title = "Players Performance"
description = "Get the performance of each player in the match."

# 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', title=title, description=description,)

# Launch the interface
iface.launch()