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Delete appbackup.py
Browse files- appbackup.py +0 -28
appbackup.py
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import streamlit as st
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import pandas as pd
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import plotly.express as px
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st.set_page_config(page_title="AutoML Streamlit App", page_icon=":robot:", layout="wide")
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st.title("AutoML Streamlit App")
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# Upload a CSV dataset
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uploaded_file = st.file_uploader("Upload your dataset", type=["csv"])
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if uploaded_file is not None:
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# Load the dataset and display the first 5 rows
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df = pd.read_csv(uploaded_file)
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st.dataframe(df.head())
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# Generate a treemap or sunburst plot based on data types
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numerical_cols = df.select_dtypes(include=["float", "int"]).columns
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categorical_cols = df.select_dtypes(include=["object"]).columns
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if len(numerical_cols) >= 2:
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fig = px.scatter_matrix(df, dimensions=numerical_cols)
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st.plotly_chart(fig)
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elif len(categorical_cols) >= 2:
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fig = px.treemap(df, path=categorical_cols)
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st.plotly_chart(fig)
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else:
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fig = px.sunburst(df, path=categorical_cols + numerical_cols)
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st.plotly_chart(fig)
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