streamlit_lab002.py

import streamlit as st
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px
import plotly.graph_objs as go

st.set_page_config(
    page_title="VAMStack Course",
    layout="wide",
    # page_icon=None
)


col01, col02, col03 = st.columns([1,10,1])
with col01:
  st.write("")
with col02:
  st.title("Welcome to Employee Management Record")
with col03:
  st.write("")

col04, col05, col06 = st.columns([1,10,1])
with col04:
	st.write("")
with col05:
	st.subheader("Data Visualisation")
with col06:
  st.write("")


# Adding a function for selecting the model
col07, col08, col09 = st.columns([1, 10, 1])
with col07:
    st.write("")
with col08:
    st.subheader("Select Animal")
    animal_option = st.selectbox(
        "Choose an animal",
        ("cat", "dog", "cow","goat")
    )
    st.write(f"Selected Animal: {animal_option}")
with col09:
    st.write("")


# Adding a function for selecting the model

col10, col11, col12 = st.columns([1, 10, 1])
with col10:
    st.write("")
with col11:
    st.subheader("Select Model")
    model_option = st.selectbox(
        "Choose a model for analysis",
        ("Random Forest", "Decision Tree")
    )
    if model_option == "Random Forest":
        model = "Random Forest Model"
    elif model_option == "Decision Tree":
        model = "Decision Tree Model"
    st.write(f"Selected Model: {model_option}")
with col12:
    st.write("")