| import streamlit as st | |
| import pandas as pd | |
| import datetime | |
| import io | |
| def save_text_as_file(text, file_type): | |
| current_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S") | |
| file_name = f"text_file_{current_time}.{file_type}" | |
| with open(file_name, "w") as file: | |
| file.write(text) | |
| st.success(f"Text saved as {file_name}") | |
| def save_csv_as_excel(text): | |
| try: | |
| df = pd.read_csv(io.StringIO(text), header=None) | |
| if df.iloc[0].dtype == object: | |
| header = 0 | |
| file_name = f"csv_with_header_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.xlsx" | |
| else: | |
| header = None | |
| file_name = f"csv_without_header_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.xlsx" | |
| df.to_excel(file_name, index=False, header=header) | |
| st.success(f"CSV data saved as {file_name}") | |
| except pd.errors.EmptyDataError: | |
| st.error("The pasted text does not contain valid CSV data.") | |
| def create_demo_excel_file(): | |
| data = { | |
| "Name": ["John", "Alice", "Bob"], | |
| "Age": [25, 30, 35], | |
| "City": ["New York", "London", "Paris"] | |
| } | |
| df = pd.DataFrame(data) | |
| file_name = "demo_excel_file.xlsx" | |
| df.to_excel(file_name, index=False) | |
| st.success(f"Demo Excel file created: {file_name}") | |
| def main(): | |
| st.title("AI UI for Text Processing") | |
| st.markdown(""" | |
| ## Pandas Cheat Sheet | |
| | Lesson | Code Example | | |
| |--------|-------------| | |
| | 1. Import xlsx | `df = pd.read_excel('data.xlsx')` | | |
| | 2. Export xlsx | `df.to_excel('output.xlsx', index=False)` | | |
| | 3. Create DataFrame | `df = pd.DataFrame(data)` | | |
| | 4. Apply function to DataFrame | `df['Column'] = df['Column'].apply(lambda x: x.capitalize())` | | |
| | 5. Reduce columns | `df = df[['Column1', 'Column2']]` | | |
| | 6. Aggregate data | `df_agg = df.groupby('Column').mean()` | | |
| | 7. Create Plotly graph | `fig = px.bar(df, x='Column1', y='Column2')` | | |
| | 8. Map values | `df['Column'] = df['Column'].map({'Old': 'New'})` | | |
| | 9. Capitalize column | `df['Column'] = df['Column'].str.capitalize()` | | |
| | 10. Filter DataFrame | `df_filtered = df[df['Column'] > 10]` | | |
| | 11. Sort DataFrame | `df_sorted = df.sort_values('Column')` | | |
| | 12. Merge DataFrames | `df_merged = pd.merge(df1, df2, on='Column')` | | |
| """) | |
| text_input = st.text_area("Paste your text here") | |
| if st.button("Process Text"): | |
| if text_input.strip() == "": | |
| st.warning("Please paste some text.") | |
| else: | |
| if "," in text_input or "\t" in text_input: | |
| save_csv_as_excel(text_input) | |
| elif text_input.startswith("#") or text_input.startswith("- "): | |
| save_text_as_file(text_input, "md") | |
| elif "def" in text_input or "import" in text_input: | |
| save_text_as_file(text_input, "py") | |
| else: | |
| save_text_as_file(text_input, "txt") | |
| if st.button("Create Demo Excel File"): | |
| create_demo_excel_file() | |
| if __name__ == "__main__": | |
| main() |