Update app.py

app.py

@@ -1,4 +1,3 @@
-#pass="Leswhdc2023$!"
 
 import streamlit as st
 import pandas as pd
@@ -9,38 +8,6 @@ from pandas_profiling import ProfileReport
 
 st.title("File Upload and Profiling")
 
-# uploaded_file = st.file_uploader("Upload a CSV file", type="csv")
-
-# RunProfiler=False
-# if uploaded_file is not None:
-#     if RunProfiler:
-
-#         # Load the data using pandas
-#         df = pd.read_csv(uploaded_file)
-
-#         # Generate the pandas profiling report
-#         profile = ProfileReport(df, explorative=True)
-
-#         # Display the pandas profiling report using streamlit
-#         st.header("Data Profiling Report")
-#         st.write(profile.to_html(), unsafe_allow_html=True)
-
-#         # Display word statistics for each categorical string column
-#         cat_cols = df.select_dtypes(include='object').columns
-#         st.header("Word Statistics for Categorical Columns")
-#         for col in cat_cols:
-#             st.subheader(col)
-#             word_count = df[col].str.split().apply(len).value_counts().sort_index()
-#             st.bar_chart(word_count)
-
-#     # Grouped count by each feature
-#     num_cols = df.select_dtypes(include=['float', 'int']).columns
-#     st.header("Grouped Count by Each Feature")
-#     for col in num_cols:
-#         st.subheader(col)
-#         count_by_feature = df.groupby(col).size().reset_index(name='count')
-#         st.bar_chart(count_by_feature)
-
 # Upload a CSV dataset
 uploaded_file = st.file_uploader("Upload your dataset", type=["csv"])
 if uploaded_file is not None: