|
import streamlit as st |
|
import pandas as pd |
|
import io |
|
import base64 |
|
|
|
st.set_page_config(page_title="Data Cleaning Tool") |
|
|
|
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: |
|
|
|
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_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() |
|
|
|
st.markdown("") |
|
st.markdown("---") |
|
st.markdown("") |
|
st.markdown("<p style='text-align: center'><a href='https://github.com/Kaludii'>Github</a> | <a href='https://huggingface.co/Kaludi'>HuggingFace</a></p>", unsafe_allow_html=True) |
|
|
