|
|
import streamlit as st |
|
|
import pandas as pd |
|
|
import plotly.express as px |
|
|
import pandas_profiling |
|
|
|
|
|
@st.cache |
|
|
def load_data(file): |
|
|
return pd.read_csv(file) |
|
|
|
|
|
def main(): |
|
|
st.set_page_config(page_title="AutoML", page_icon=":robot:", layout="wide") |
|
|
st.title("AutoML Streamlit Application") |
|
|
file = st.file_uploader("Upload your CSV file", type=["csv"]) |
|
|
if file is not None: |
|
|
df = load_data(file) |
|
|
st.dataframe(df.head(10)) |
|
|
st.write("Statistics:") |
|
|
st.write(df.describe()) |
|
|
st.write("Data Distribution:") |
|
|
st.write(df.hist()) |
|
|
st.write("Pandas Profiling:") |
|
|
profile = df.profile_report(title="Pandas Profiling Report") |
|
|
st.write(profile) |
|
|
st.write("Pandas Profiling (Sunburst Chart):") |
|
|
sunburst = profile.get_final_html() |
|
|
st.write(sunburst, unsafe_allow_html=True) |
|
|
st.write("Filter by Column:") |
|
|
column = st.selectbox("Select Column", df.columns) |
|
|
filtered = df.sort_values(by=column) |
|
|
st.write(filtered) |
|
|
|
|
|
if __name__ == '__main__': |
|
|
main() |
