fix the missing part

pages/15_📈_Table_Data_Cleaning.py

@@ -7,77 +7,77 @@ import base64
 # st.set_page_config(layout="wide")
 
 # Function for the CSV Visualization App
-def app():
-
-    hide_streamlit_style = """
-            <style>
-            #MainMenu {visibility: hidden;}
-            footer {visibility: hidden;}
-            </style>
-            """
-    st.markdown(hide_streamlit_style, unsafe_allow_html=True)
-
-    st.title("CSV Data Cleaning Tool")
-
-    st.markdown("Upload one or multiple CSV files to preprocess and clean your files quickly and stress free.")
-
-    uploaded_files = st.file_uploader("Choose CSV files", type="csv", accept_multiple_files=True)
-
-    dataframes = []
-
-    if uploaded_files:
-        for file in uploaded_files:
-            file.seek(0)
-            df = pd.read_csv(file)
-            dataframes.append(df)
-
-        if len(dataframes) > 1:
-            merge = st.checkbox("Merge uploaded CSV files")
-
-            if merge:
-                # Merge options
-                keep_first_header_only = st.selectbox("Keep only the header (first row) of the first file", ["Yes", "No"])
-                remove_duplicate_rows = st.selectbox("Remove duplicate rows", ["No", "Yes"])
-                remove_empty_rows = st.selectbox("Remove empty rows", ["Yes", "No"])
-                end_line = st.selectbox("End line", ["\\n", "\\r\\n"])
-
-                try:
-                    if keep_first_header_only == "Yes":
-                        for i, df in enumerate(dataframes[1:]):
-                            df.columns = dataframes[0].columns.intersection(df.columns)
-                            dataframes[i+1] = df
-
-                    merged_df = pd.concat(dataframes, ignore_index=True, join='outer')
-
-                    if remove_duplicate_rows == "Yes":
-                        merged_df.drop_duplicates(inplace=True)
-
-                    if remove_empty_rows == "Yes":
-                        merged_df.dropna(how="all", inplace=True)
-
-                    dataframes = [merged_df]
-
-                except ValueError as e:
-                    st.error("Please make sure columns match in all files. If you don't want them to match, select 'No' in the first option.")
-                    st.stop()
-
-        # Show or hide DataFrames
-        show_dataframes = st.checkbox("Show DataFrames", value=True)
-
-        if show_dataframes:
-            for i, df in enumerate(dataframes):
-                st.write(f"DataFrame {i + 1}")
-                st.dataframe(df)
-
-        if st.button("Download cleaned data"):
-            for i, df in enumerate(dataframes):
-                csv = df.to_csv(index=False)
-                b64 = base64.b64encode(csv.encode()).decode()
-                href = f'<a href="data:file/csv;base64,{b64}" download="cleaned_data_{i + 1}.csv">Download cleaned_data_{i + 1}.csv</a>'
-                st.markdown(href, unsafe_allow_html=True)
-    else:
-        st.warning("Please upload CSV file(s).")
-        st.stop()
-app()
+# def app():
+
+hide_streamlit_style = """
+        <style>
+        #MainMenu {visibility: hidden;}
+        footer {visibility: hidden;}
+        </style>
+        """
+st.markdown(hide_streamlit_style, unsafe_allow_html=True)
+
+st.title("CSV Data Cleaning Tool")
+
+st.markdown("Upload one or multiple CSV files to preprocess and clean your files quickly and stress free.")
+
+uploaded_files = st.file_uploader("Choose CSV files", type="csv", accept_multiple_files=True)
+
+dataframes = []
+
+if uploaded_files:
+    for file in uploaded_files:
+        file.seek(0)
+        df = pd.read_csv(file)
+        dataframes.append(df)
+
+    if len(dataframes) > 1:
+        merge = st.checkbox("Merge uploaded CSV files")
+
+        if merge:
+            # Merge options
+            keep_first_header_only = st.selectbox("Keep only the header (first row) of the first file", ["Yes", "No"])
+            remove_duplicate_rows = st.selectbox("Remove duplicate rows", ["No", "Yes"])
+            remove_empty_rows = st.selectbox("Remove empty rows", ["Yes", "No"])
+            end_line = st.selectbox("End line", ["\\n", "\\r\\n"])
+
+            try:
+                if keep_first_header_only == "Yes":
+                    for i, df in enumerate(dataframes[1:]):
+                        df.columns = dataframes[0].columns.intersection(df.columns)
+                        dataframes[i+1] = df
+
+                merged_df = pd.concat(dataframes, ignore_index=True, join='outer')
+
+                if remove_duplicate_rows == "Yes":
+                    merged_df.drop_duplicates(inplace=True)
+
+                if remove_empty_rows == "Yes":
+                    merged_df.dropna(how="all", inplace=True)
+
+                dataframes = [merged_df]
+
+            except ValueError as e:
+                st.error("Please make sure columns match in all files. If you don't want them to match, select 'No' in the first option.")
+                st.stop()
+
+    # Show or hide DataFrames
+    show_dataframes = st.checkbox("Show DataFrames", value=True)
+
+    if show_dataframes:
+        for i, df in enumerate(dataframes):
+            st.write(f"DataFrame {i + 1}")
+            st.dataframe(df)
+
+    if st.button("Download cleaned data"):
+        for i, df in enumerate(dataframes):
+            csv = df.to_csv(index=False)
+            b64 = base64.b64encode(csv.encode()).decode()
+            href = f'<a href="data:file/csv;base64,{b64}" download="cleaned_data_{i + 1}.csv">Download cleaned_data_{i + 1}.csv</a>'
+            st.markdown(href, unsafe_allow_html=True)
+else:
+    st.warning("Please upload CSV file(s).")
+    st.stop()
+# app()