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app.py

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+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)

requirements.txt

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+streamlit
+pandas
+numpy
+ydata-profiling
+streamlit-pandas-profiling
+Jinja2