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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!
''')
# Upload CSV data
with st.sidebar.header('Upload your CSV data'):
uploaded_file = st.sidebar.file_uploader("Upload your input CSV file", type=["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)
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