Refactor and document code; add new files

Refactored `script.py` by adding detailed docstrings and organizing functions. Created `.idea` configuration files and `gotodashboard.js` for `sisa_crawl` project. Added `readme.md` files with usage instructions and context for multiple scripts, and set up `package.json` for `sisa_crawl` dependencies.

examen grote lokalen/main.py

@@ -1,18 +1,48 @@
 import pandas as pd
 
-file_path = 'file.xlsx'
-sheet_name = 'ps (32)'
+# Constants
+FILE_PATH = 'file.xlsx'
+SHEET_NAME = 'ps (32)'
+OUTPUT_FILE_PATH = 'filtered_grote_lokalen.xlsx'
+EXAM_FORM_COLUMN = 'Examenvorm'
+REGISTRATION_COLUMN = 'Aant. inschr.'
+BEGIN_TIME_COLUMN = 'Beginuur S+'
+END_TIME_COLUMN = 'Einduur S+'
+TEACHERS_COLUMN = 'Docenten'
+LOCATION_COLUMNS = ['Datum S+', BEGIN_TIME_COLUMN, END_TIME_COLUMN, 'Studiegidsnr.', 'Omschrijving', TEACHERS_COLUMN, REGISTRATION_COLUMN]
 
-df = pd.read_excel(file_path, sheet_name=sheet_name)
-filtered_df = df[df['Examenvorm'] == 'Schriftelijk' ]
-filtered_df = filtered_df[filtered_df['Aant. inschr.'] > 65]
-filtered_df = filtered_df[['Datum S+','Beginuur S+','Einduur S+', 'Studiegidsnr.', 'Omschrijving', 'Docenten', 'Aant. inschr.']]
+# Read the Excel file
+def read_excel(file_path, sheet_name):
+    return pd.read_excel(file_path, sheet_name=sheet_name)
 
+# Filter DataFrame
+def filter_dataframe(df):
+    df = df[df[EXAM_FORM_COLUMN] == 'Schriftelijk']
+    df = df[df[REGISTRATION_COLUMN] > 65]
+    return df[LOCATION_COLUMNS]
 
-#formatting the timestrings
-filtered_df['Beginuur S+'] = filtered_df['Beginuur S+'].apply(lambda x: x.strftime('%H:%M'))
-filtered_df['Einduur S+'] = filtered_df['Einduur S+'].apply(lambda x: x.strftime('%H:%M'))
-filtered_df['Docenten'] = filtered_df['Docenten'].str.replace(r'\b(Titularis|Co-Titularis|Medewerker)\b', '',
-                                                              regex=True).str.strip()
+# Format time strings
+def format_time_strings(df):
+    df[BEGIN_TIME_COLUMN] = df[BEGIN_TIME_COLUMN].apply(lambda x: x.strftime('%H:%M') if pd.notnull(x) else '')
+    df[END_TIME_COLUMN] = df[END_TIME_COLUMN].apply(lambda x: x.strftime('%H:%M') if pd.notnull(x) else '')
+    return df
 
-filtered_df.to_excel('filtered_grote_lokalen.xlsx', index=False)
+# Clean up teacher titles
+def clean_teacher_titles(df):
+    df[TEACHERS_COLUMN] = df[TEACHERS_COLUMN].str.replace(r'\b(Titularis|Co-Titularis|Medewerker)\b', '', regex=True).str.strip()
+    return df
+
+# Save DataFrame to Excel
+def save_to_excel(df, file_path):
+    df.to_excel(file_path, index=False)
+
+# Main process
+def main():
+    df = read_excel(FILE_PATH, SHEET_NAME)
+    filtered_df = filter_dataframe(df)
+    filtered_df = format_time_strings(filtered_df)
+    filtered_df = clean_teacher_titles(filtered_df)
+    save_to_excel(filtered_df, OUTPUT_FILE_PATH)
+
+if __name__ == "__main__":
+    main()

examen grote lokalen/readme.md

@@ -0,0 +1,79 @@
+# Excel Filtering and Formatting Script
+
+The file in this repository filters has the intent to filter all written exams that require a 'large room' 
+(>65 inschrijvingen) and thus need to be brought to the meeting which assigns large rooms to written exams on campus. The output has
+the layout in mind of the master file provided by E-campus but may need changes if the master file changes.
+
+## Prerequisites
+
+Make sure you have the following software installed:
+- Python 3.x
+- Pip (Python package installer)
+
+## Required Packages
+
+The script depends on the following Python packages:
+- `pandas`
+
+You can install the required package using pip:
+```bash
+pip install pandas
+```
+
+## Description
+
+The script performs the following operations:
+
+1. Reads data from the specified Excel file and sheet.
+2. Filters rows based on the value of the 'Examenvorm' column and the count of 'Aant. inschr.' column.
+3. Selects specific columns from the filtered DataFrame.
+4. Formats time strings in the columns 'Beginuur S+' and 'Einduur S+'.
+5. Cleans the 'Docenten' column by removing specific keywords and trimming whitespace.
+6. Writes the processed DataFrame to a new Excel file.
+
+## Usage
+
+1. Place your Excel file in the same directory as the script.
+2. Update the `file_path` and `sheet_name` variables in the script with your specific file path and sheet name.
+3. Run the script:
+
+```bash
+python script.py
+```
+
+## Code
+
+```python
+import pandas as pd
+
+file_path = 'file.xlsx'
+sheet_name = 'ps (32)'
+
+# Read the data from the Excel file
+df = pd.read_excel(file_path, sheet_name=sheet_name)
+
+# Filter the data based on certain criteria
+filtered_df = df[df['Examenvorm'] == 'Schriftelijk']
+filtered_df = filtered_df[filtered_df['Aant. inschr.'] > 65]
+filtered_df = filtered_df[['Datum S+', 'Beginuur S+', 'Einduur S+', 'Studiegidsnr.', 'Omschrijving', 'Docenten', 'Aant. inschr.']]
+
+# Format the time strings
+filtered_df['Beginuur S+'] = filtered_df['Beginuur S+'].apply(lambda x: x.strftime('%H:%M'))
+filtered_df['Einduur S+'] = filtered_df['Einduur S+'].apply(lambda x: x.strftime('%H:%M'))
+filtered_df['Docenten'] = filtered_df['Docenten'].str.replace(r'\b(Titularis|Co-Titularis|Medewerker)\b', '', regex=True).str.strip()
+
+# Save the filtered and formatted data to a new Excel file
+filtered_df.to_excel('filtered_grote_lokalen.xlsx', index=False)
+```
+
+## Additional Notes
+
+- This script assumes that the input Excel file has specific columns like 'Examenvorm', 'Aant. inschr.', 'Datum S+', 'Beginuur S+', 'Einduur S+', 'Studiegidsnr.', 'Omschrijving', and 'Docenten'.
+- Make sure that the time columns ('Beginuur S+' and 'Einduur S+') are in datetime format in the original Excel file for the `.strftime('%H:%M')` method to work correctly.
+- The `Docenten` column will be cleaned by removing occurrences of the keywords 'Titularis', 'Co-Titularis', and 'Medewerker'.
+
+Feel free to adjust the script according to your specific needs.
+
+## License
+
+This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.