app.py

import numpy as np
import pandas as pd
import streamlit as st
# from pandas_profiling import ProfileReport
from ydata_profiling import ProfileReport
from streamlit_pandas_profiling import st_profile_report
st.markdown('''
# **The EDA App**

Unleash the Power of Data Exploration with our EDA App: Dive Deep, Discover Insights, and Empower Your Analysis!

**Credit:** App built  by [Sanjana Singamsetty](https://github.com/sanjana-singamsetty) 

---
''')

# Upload CSV data
with st.sidebar.header('1. Upload your CSV data'):
    uploaded_file = st.sidebar.file_uploader("Upload your input CSV file", type=["csv"])
    st.sidebar.markdown("""
[Example CSV input file](https://raw.githubusercontent.com/sanjana-singamsetty/sample/master/delaney_solubility_with_descriptors.csv)
""")
if uploaded_file is not None:
    @st.cache_data
    def load_csv():
        csv = pd.read_csv(uploaded_file)
        return csv
    df = load_csv()
    pr = ProfileReport(df, explorative=True)
    st.header('**Input DataFrame**')
    st.dataframe(df)
    st.header('**Pandas Profiling Report**')
    st_profile_report(pr)
else:
    st.info('Please Upload CSV file to Begin.')
    if st.button('If you have nodataset Press me!>-<'):
        # Example data
        @st.cache_data
        def load_data():
            a = pd.DataFrame(
                np.random.rand(100, 5),
                columns=['a', 'b', 'c', 'd', 'e']
            )
            return a
        df = load_data()
        pr = ProfileReport(df, explorative=True)
        st.header('**Input DataFrame**')
        st.write(df)
        st.write('---')
        st.header('**Pandas Profiling Report**')
        st_profile_report(pr)