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| import streamlit as st | |
| import pandas as pd | |
| import io | |
| 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() | |