import streamlit as st
import pandas as pd
# from __future__ import division

import numpy as np

import xgboost as xgb

x = st.slider("Select a value")
st.write(x, "squared is", x * x)


data = pd.read_csv("hf://datasets/Ammok/hair_health/predict_hair_fall.csv")


# Calculate split point (70%)
split_point = int(len(data) * 0.7)

# Split into train and test
train = data.iloc[:split_point]
test = data.iloc[split_point:]

# If you need numpy arrays instead of dataframes
train_np = train.to_numpy()
test_np = test.to_numpy()

st.dataframe(data)