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import os | |
import pandas as pd | |
import streamlit as st | |
def download_dataset(): | |
# Ensure the data directory exists | |
if not os.path.exists('./data'): | |
os.makedirs('./data') | |
# Download the dataset using Kaggle API | |
os.system("kaggle datasets download -d mohaideenabuthahir/analyzeyt -p ./data --unzip") | |
def load_data(): | |
# Ensure dataset is downloaded | |
download_dataset() | |
# List available files in the data directory | |
available_files = [f for f in os.listdir('./data') if f.endswith('.csv')] | |
# Ask user to select which file to load | |
selected_file = st.selectbox('Select a file to load', available_files) | |
# Load the selected dataset | |
data = pd.read_csv(f'./data/{selected_file}') | |
return data | |
def main(): | |
st.title("Kaggle Dataset Loader") | |
data = load_data() | |
st.write(data.head()) | |
if __name__ == "__main__": | |
main() | |