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Update pages/2_Data Cleaning and Processing .py
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pages/2_Data Cleaning and Processing .py
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@@ -188,20 +188,20 @@ if df is not None:
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""")
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# Store the cleaned data in session state
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st.session_state.cleaned_data =
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st.write("""
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### 11. **Store Cleaned Data in Session State**
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The cleaned DataFrame is stored in Streamlit’s session state, allowing it to persist across pages or interactions.
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""")
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# Display cleaned data
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st.subheader("Cleaned Data Preview:")
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st.dataframe(
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st.write("""
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### 12. **Dataset Information**
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Displays basic information about the DataFrame such as column data types, non-null counts, and memory usage.
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""")
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buffer = StringIO()
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# Display the content in Streamlit as Markdown
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st.subheader("Info of the Dataset:")
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@@ -215,7 +215,7 @@ if df is not None:
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st.subheader("Download the Cleaned Data")
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st.download_button(
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label="Download CSV",
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data=
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file_name="Cleaned_Hotel_Data.csv",
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mime="text/csv"
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)
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""")
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# Store the cleaned data in session state
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st.session_state.cleaned_data = data
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st.write("""
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### 11. **Store Cleaned Data in Session State**
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The cleaned DataFrame is stored in Streamlit’s session state, allowing it to persist across pages or interactions.
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""")
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# Display cleaned data
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st.subheader("Cleaned Data Preview:")
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st.dataframe(data)
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st.write("""
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### 12. **Dataset Information**
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Displays basic information about the DataFrame such as column data types, non-null counts, and memory usage.
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""")
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buffer = StringIO()
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data.info(buf=buffer)
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# Display the content in Streamlit as Markdown
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st.subheader("Info of the Dataset:")
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st.subheader("Download the Cleaned Data")
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st.download_button(
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label="Download CSV",
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data=data.to_csv(index=False),
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file_name="Cleaned_Hotel_Data.csv",
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mime="text/csv"
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)
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