{ "cells": [ { "cell_type": "markdown", "id": "02b9e8f5-82ed-460b-af25-9034e538b7b3", "metadata": {}, "source": [ "# Workshop Schedule and Signup" ] }, { "cell_type": "code", "execution_count": 1, "id": "d3aa7606-0f50-4f05-b104-ad4521c80406", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [ "remove-input" ] }, "outputs": [ { "data": { "text/markdown": [ "- Python for Data Analysis: 29th November/6th December 10am-1pm (In-person only) - [MS Form Signup](https://forms.office.com/e/ChUMbgntbr)\n", "- Regression Analysis with R: 25th October 10am-1pm (online only) - [MS Form Signup](https://forms.office.com/Pages/ResponsePage.aspx?id=d10qkZj77k6vMhM02PBKU-3R4SvRoClNrKjEX5qG1X1UMU1KRUpEOFRJQjFEOVVUVzFDMTRQMFZLRi4u)\n", "- Working with Data in R: 18th/25th November 1-4pm (online only) - [MS Form Signup](https://forms.office.com/e/zi5g1uP5sB)" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "from IPython.display import Markdown, display\n", "from datetime import datetime\n", "\n", "# Load the CSV file (adjust the file path as needed)\n", "file_path = '../data/workshop_info.csv'\n", "courses_df = pd.read_csv(file_path)\n", "\n", "# Strip any extra spaces in the column names\n", "courses_df.columns = courses_df.columns.str.strip()\n", "\n", "# Convert the 'End Date' column to datetime (assuming the date format is day-first)\n", "courses_df['End Date'] = pd.to_datetime(courses_df['End Date'], dayfirst=True, errors='coerce')\n", "\n", "# Get today's date\n", "today = datetime.now()\n", "\n", "# Filter for rows that contain valid MS Form Signup links, Course Date information, and check if the 'End Date' is still valid\n", "filtered_courses_df = courses_df.dropna(subset=['Course Date', 'MS Form Signup'])\n", "filtered_courses_df = filtered_courses_df[filtered_courses_df['End Date'] > today]\n", "\n", "# Function to generate markdown text based on course details\n", "def generate_markdown(row):\n", " return f\"- {row['Course Name']}: {row['Course Date']} - [MS Form Signup]({row['MS Form Signup']})\"\n", "\n", "# Apply the function and create the markdown output\n", "markdown_output = filtered_courses_df.apply(generate_markdown, axis=1).tolist()\n", "\n", "# Join the markdown lines into a single block\n", "markdown_text = \"\\n\".join(markdown_output)\n", "\n", "# Display the markdown text in rendered form\n", "display(Markdown(markdown_text))" ] }, { "cell_type": "markdown", "id": "7101f2f7-2903-4cdc-b736-3f5000c467f7", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "# Previous Workshops" ] }, { "cell_type": "code", "execution_count": 3, "id": "0a814add-f545-4663-8b06-39c40b636509", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [ "remove-input" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
Course NameCourse DateCourse LeaderCourse Helpers
Regression Analysis with RJun-24Eilis HannonCuihong Xie, Emma Walker
Introduction to MATLABJun-24Jake HollinsJonathan Witton, Han Wu, Fred Wobus
Parallel Computing Jun-24Ed HoneFred Wobus, Han Wu, Stephen Cook
Introduction to RJun-24Ricky OlivierMichelle Ledbetter, Theresa Wacker, Jingzhan Lu
Intermediate Version ControlMay-24Stephen CookTom Wilson, Liam Berrisford
Python for Data AnalysisMay-24Michael SaunbyJohn Luff, Simon Kirby
Introduction to HPC and ISCAMay-24Ricky OlivierFred Wobus, Matt West
Introduction to Version ControlMay-24Linus Tata John Luff, David Studholme, Simon Kirby
Advanced Regression Analysis with RApr-24Eilis HannonBecky Ward, Cuihong Xie, Ishaan Sinha
Software Development Best PracticeApr-24Fliss GuestJoseph Paulo
Computational ThinkingApr-24Michael SaunbyEilis Hannon, Fotis Tsiroukis, Liam Berrisford
Introduction to PythonApr-24Matt JohnsTom Hawes, Liam Berrisford, Jack Morton, Finley Gibson
Working With Data in R Mar-24Tom HawesAli Hudson, Emma Walker
Introduction to UNIX Mar-24Eilis HannonLinus Tata, Han Wu
Regression Analysis with RJan-24Eilis HannonAlice Franklin, Cuihong Xie
Introduction to RJan-24Jamie HarrisonAlexandra Gardner, Cuihong Xie, Becky Ward Alice Franklin
Introduction to Version ControlDec-23Linus Tata Matt Johns, Han Wu
Introduction to HPC and ISCANov-23Ricky OlivierMatt Johns, Matt West, Han Wu
Introduction to juliaNovember/December 2023George DatserisEd Hone, Nick Owens
Introduction to PythonNov-23Michael SaunbyJohn Luff, Hao Meng, Mustafa Albalushi
Introduction to UNIX Oct-23Simon KirbyStephen Cook, Ali Hudson, Kartik Chundru 
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "from IPython.display import display, HTML\n", "\n", "# Load the CSV file (adjust the file path as needed)\n", "file_path_previous = '../data/previous_workshops.csv'\n", "previous_courses_df = pd.read_csv(file_path_previous)\n", "previous_courses_df = previous_courses_df.iloc[::-1].reset_index(drop=True)\n", "\n", "# Strip any extra spaces in the column names\n", "previous_courses_df.columns = previous_courses_df.columns.str.strip()\n", "\n", "# Function to generate an HTML table row for each course\n", "def generate_html_row(row):\n", " #return f\"{row['Course Name']}{row['Course Info']}{row['Course Leader']}{row['Course Helpers']}{row['Course Developers']}\"\n", " return f\"{row['Course Name']}{row['Course Info']}{row['Course Leader']}{row['Course Helpers']}\"\n", "\n", "#Generate HTML table header\n", "# html_table_header = \"\"\"\n", "# \n", "# \n", "# \n", "# \n", "# \n", "# \n", "# \n", "# \n", "# \"\"\"\n", "html_table_header = \"\"\"\n", "
Course NameCourse InfoCourse LeaderCourse HelpersCourse Developers
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\"\"\"\n", "\n", "# Apply the function and create the HTML table rows\n", "table_rows = previous_courses_df.apply(generate_html_row, axis=1).tolist()\n", "\n", "# Join the table rows into a single block\n", "html_table = html_table_header + \"\\n\".join(table_rows) + \"
Course NameCourse DateCourse LeaderCourse Helpers
\"\n", "\n", "# Display the HTML table\n", "display(HTML(html_table))\n" ] }, { "cell_type": "code", "execution_count": null, "id": "2b3dc21f-a316-4357-8e4a-9c83c3703fd0", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.19" } }, "nbformat": 4, "nbformat_minor": 5 }