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import streamlit as st | |
import pandas as pd | |
import plotly.express as px | |
st.set_page_config(page_title="AutoML Streamlit App", page_icon=":robot:", layout="wide") | |
st.title("AutoML Streamlit App") | |
# Upload a CSV dataset | |
uploaded_file = st.file_uploader("Upload your dataset", type=["csv"]) | |
if uploaded_file is not None: | |
# Load the dataset and display the first 5 rows | |
df = pd.read_csv(uploaded_file) | |
st.dataframe(df.head()) | |
# Generate a treemap or sunburst plot based on data types | |
numerical_cols = df.select_dtypes(include=["float", "int"]).columns | |
categorical_cols = df.select_dtypes(include=["object"]).columns | |
if len(numerical_cols) >= 2: | |
fig = px.scatter_matrix(df, dimensions=numerical_cols) | |
st.plotly_chart(fig) | |
elif len(categorical_cols) >= 2: | |
fig = px.treemap(df, path=categorical_cols) | |
st.plotly_chart(fig) | |
else: | |
fig = px.sunburst(df, path=categorical_cols + numerical_cols) | |
st.plotly_chart(fig) |