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| import streamlit as st | |
| import pandas as pd | |
| st.set_page_config( | |
| page_title="File Checker", | |
| page_icon="🥥", | |
| layout="wide" | |
| ) | |
| hide_streamlit_style = """ | |
| <style> | |
| #MainMenu {visibility: hidden;} | |
| footer {visibility: hidden;} | |
| </style> | |
| """ | |
| st.markdown(hide_streamlit_style, unsafe_allow_html=True) | |
| st.title('🥥 File Checker', anchor=False) | |
| def reset_data(): | |
| st.cache_data.clear() | |
| #===check filetype=== | |
| def get_ext(extype): | |
| extype = uploaded_file.name | |
| return extype | |
| #===upload=== | |
| def upload(extype): | |
| keywords = pd.read_csv(uploaded_file) | |
| return keywords | |
| def conv_txt(extype): | |
| col_dict = {'TI': 'Title', | |
| 'SO': 'Source title', | |
| 'DE': 'Author Keywords', | |
| 'DT': 'Document Type', | |
| 'AB': 'Abstract', | |
| 'TC': 'Cited by', | |
| 'PY': 'Year', | |
| 'ID': 'Keywords Plus'} | |
| keywords = pd.read_csv(uploaded_file, sep='\t', lineterminator='\r') | |
| keywords.rename(columns=col_dict, inplace=True) | |
| return keywords | |
| st.subheader('Put your file here...', anchor=False) | |
| #===read data=== | |
| uploaded_file = st.file_uploader("Choose your a file", type=['csv','txt'], on_change=reset_data) | |
| if uploaded_file is not None: | |
| extype = get_ext(uploaded_file) | |
| if extype.endswith('.csv'): | |
| data = upload(extype) | |
| elif extype.endswith('.txt'): | |
| data = conv_txt(extype) | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| #===check keywords=== | |
| keycheck = list(data.columns) | |
| keycheck = [k for k in keycheck if 'Keyword' in k] | |
| container1 = st.container(border=True) | |
| if not keycheck: | |
| container1.subheader('❌ Keyword Stem', divider='red') | |
| container1.write("Unfortunately, you don't have a column containing keywords in your data. Please check again. If you want to use it in another column, please rename it to 'Keywords'.") | |
| else: | |
| container1.subheader('✔️ Keyword Stem', divider='blue') | |
| container1.write('Congratulations! You can use Keywords Stem') | |
| #===check any obj=== | |
| coldf = sorted(data.select_dtypes(include=['object']).columns.tolist()) | |
| container2 = st.container(border=True) | |
| if not coldf: | |
| container2.subheader('❌ Topic Modeling', divider='red') | |
| container2.write("Unfortunately, you don't have a column containing object in your data. Please check again.") | |
| else: | |
| container2.subheader('✔️ Topic Modeling', divider='blue') | |
| container2.write('Congratulations! You can use Topic Modeling') | |
| with col2: | |
| #===bidirected=== | |
| container3 = st.container(border=True) | |
| if not keycheck: | |
| container3.subheader('❌ Bidirected Network', divider='red') | |
| container3.write("Unfortunately, you don't have a column containing keywords in your data. Please check again. If you want to use it in another column, please rename it to 'Keywords'.") | |
| else: | |
| container3.subheader('✔️ Bidirected Network', divider='blue') | |
| container3.write('Congratulations! You can use Bidirected Network') | |
| #===Visualization=== | |
| if 'Publication Year' in data.columns: | |
| data.rename(columns={'Publication Year': 'Year', 'Citing Works Count': 'Cited by', | |
| 'Publication Type': 'Document Type', 'Source Title': 'Source title'}, inplace=True) | |
| col2check = ['Document Type','Source title','Cited by','Year'] | |
| miss_col = [column for column in col2check if column not in data.columns] | |
| container4 = st.container(border=True) | |
| if not miss_col: | |
| container4.subheader('✔️ Sunburst', divider='blue') | |
| container4.write('Congratulations! You can use Sunburst') | |
| else: | |
| container4.subheader('❌ Sunburst', divider='red') | |
| miss_col_str = ', '.join(miss_col) | |
| container4.write(f"Unfortunately, you don't have: {miss_col_str}. Please check again.") |