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Merge pull request #135 from coding-for-reproducible-research/auto-update-accept-apps
Add python code to generate markdown code for courses
2 parents 75e89af + c070fec commit d29a4a7

23 files changed

+1003
-37
lines changed

‎data/accepting_applications.csv

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Course Name,Start Date,End Date
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Introduction to Python,18/09/2024,16/10/2024
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Python for Data Analysis,,
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Introduction to R,18/09/2024,01/10/2024
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Regression Analysis with R,18/09/2024,18/10/2024
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Advanced Regression Analysis with R,,
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Working with Data in R,,
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Introduction to HPC,,
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Introduction to Version Control,,
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Intermediate Version Control,,
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Introduction to Unix,,
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Computational Thinking,,
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Software Development Best Practice,,
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Introduction to Julia,,

‎programme_information/R.ipynb

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{
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"cell_type": "markdown",
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"id": "9f765ae0-0f63-44eb-9d61-76d5664bea89",
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"metadata": {},
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
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"# R\n",
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"\n",

‎programme_information/advanced_regression_analysis_with_r.ipynb

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"cells": [
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{
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"cell_type": "markdown",
5-
"id": "688c88c9-24d9-47bf-a547-257d9b190097",
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"id": "323380b3-d095-4aa7-b9c9-9eccb3ed425d",
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"metadata": {
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"editable": true,
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"slideshow": {
@@ -41,8 +41,86 @@
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"\n",
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"## Signup \n",
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"\n",
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"To check for upcoming course dates and to register, please visit the Workshop Schedule and Signup page available [here](../cfrr_program_details/courses_overview.ipynb).\n",
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"To check for upcoming course dates and to register, please visit the Workshop Schedule and Signup page available [here](../cfrr_program_details/courses_overview.ipynb)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "75289504-c41d-4a3c-902c-44f9f9208d0e",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": [
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"remove-input"
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]
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},
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"outputs": [
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{
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"data": {
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"text/html": [],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"import pandas as pd\n",
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"from datetime import datetime\n",
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"from IPython.display import display, HTML\n",
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"\n",
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"\n",
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"# Define the course that is being looked at\n",
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"course_name = \"Advanced Regression Analysis with R\"\n",
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"\n",
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"# Load the CSV file\n",
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"file_path = '../data/accepting_applications.csv' # Adjust the path to your file location\n",
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"courses_df = pd.read_csv(file_path)\n",
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"\n",
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"# Strip any extra spaces in the column names\n",
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"courses_df.columns = courses_df.columns.str.strip()\n",
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"\n",
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"# Convert date columns to datetime\n",
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"courses_df['Start Date'] = pd.to_datetime(courses_df['Start Date'], dayfirst=True, errors='coerce')\n",
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"courses_df['End Date'] = pd.to_datetime(courses_df['End Date'], dayfirst=True, errors='coerce')\n",
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"\n",
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"# Get today's date\n",
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"today = datetime.now()\n",
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"\n",
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"# Function to generate markdown text based on the course dates\n",
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"def generate_html(row):\n",
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" if pd.notna(row['Start Date']) and pd.notna(row['End Date']):\n",
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" if row['Start Date'] <= today <= row['End Date']:\n",
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" return f\"<div style='font-weight: bold;'>This course is currently accepting applications.</div>\"\n",
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" return \"\"\n",
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"\n",
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"# Apply the function and create a new column for Markdown\n",
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"courses_df['HTML'] = courses_df.apply(generate_html, axis=1)\n",
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"\n",
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"# Variable for course name\n",
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"\n",
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"\n",
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"# Filter the DataFrame for the given course name and display the HTML text\n",
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"html_output = courses_df[courses_df['Course Name'] == course_name]['HTML'].values[0]\n",
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"display(HTML(html_output))\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "56db8cac-1a93-4a60-8898-5b1c133026f8",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
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"## Installation Guide \n",
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"All CfRR courses require attendees to use their own computer/laptop to follow workshop activities and take effective notes. \n",
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"\n",

‎programme_information/computational_thinking.ipynb

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"cells": [
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{
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"cell_type": "markdown",
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"id": "550fe19d-ea33-4571-828c-68c0027989cf",
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"id": "69e7d9dc-c7ef-484f-ab32-0535dc109ef6",
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"metadata": {
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"editable": true,
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"slideshow": {
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"\n",
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"## Signup \n",
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"\n",
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"To check for upcoming course dates and to register, please visit the Workshop Schedule and Signup page available [here](../cfrr_program_details/courses_overview.ipynb).\n",
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"To check for upcoming course dates and to register, please visit the Workshop Schedule and Signup page available [here](../cfrr_program_details/courses_overview.ipynb)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "12053e8e-0879-442a-b3e3-a19ed5f7ee5b",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": [
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"remove-input"
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]
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},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"from datetime import datetime\n",
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"from IPython.display import display, HTML\n",
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"\n",
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"# Define the course that is being looked at\n",
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"course_name = \"Computational Thinking\"\n",
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"\n",
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"# Load the CSV file\n",
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"file_path = '../data/accepting_applications.csv' # Adjust the path to your file location\n",
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"courses_df = pd.read_csv(file_path)\n",
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"\n",
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"# Strip any extra spaces in the column names\n",
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"courses_df.columns = courses_df.columns.str.strip()\n",
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"\n",
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"# Convert date columns to datetime\n",
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"courses_df['Start Date'] = pd.to_datetime(courses_df['Start Date'], dayfirst=True, errors='coerce')\n",
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"courses_df['End Date'] = pd.to_datetime(courses_df['End Date'], dayfirst=True, errors='coerce')\n",
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"\n",
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"# Get today's date\n",
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"today = datetime.now()\n",
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"\n",
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"# Function to generate markdown text based on the course dates\n",
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"def generate_html(row):\n",
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" if pd.notna(row['Start Date']) and pd.notna(row['End Date']):\n",
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" if row['Start Date'] <= today <= row['End Date']:\n",
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" return f\"<div style='font-weight: bold;'>This course is currently accepting applications.</div>\"\n",
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" return \"\"\n",
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"\n",
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"# Apply the function and create a new column for Markdown\n",
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"courses_df['HTML'] = courses_df.apply(generate_html, axis=1)\n",
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"\n",
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"# Variable for course name\n",
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"\n",
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"\n",
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"# Filter the DataFrame for the given course name and display the HTML text\n",
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"html_output = courses_df[courses_df['Course Name'] == course_name]['HTML'].values[0]\n",
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"display(HTML(html_output))\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "156bbe7a-3de1-4ed7-80f5-f5ce25af83c7",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
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"## Installation Guide \n",
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"All CfRR courses require attendees to use their own computer/laptop to follow workshop activities and take effective notes. \n",
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"\n",

‎programme_information/computational_thinking_overview.ipynb

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{
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"cell_type": "markdown",
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"id": "f77c5a09-dfad-495e-92d9-f622e1e6a37a",
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"metadata": {},
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
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"# Computational Thinking\n",
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"\n",

‎programme_information/high_performance_computing.ipynb

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{
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"cell_type": "markdown",
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"id": "73ea8c8f-c9ee-4ee1-aac0-c3d336dc7068",
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"metadata": {},
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
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"# High Performance Computing\n",
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"\n",

‎programme_information/intermediate_version_control.ipynb

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"cells": [
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{
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"cell_type": "markdown",
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"id": "663cd303-1115-492f-ac46-49cca337b940",
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"id": "44133fdf-b5d0-440f-a268-29ef0916aede",
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"metadata": {
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"editable": true,
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"slideshow": {
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"\n",
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"## Signup \n",
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"\n",
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"To check for upcoming course dates and to register, please visit the Workshop Schedule and Signup page available [here](../cfrr_program_details/courses_overview.ipynb).\n",
34+
"To check for upcoming course dates and to register, please visit the Workshop Schedule and Signup page available [here](../cfrr_program_details/courses_overview.ipynb)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e1595e9c-6a05-4b02-93e9-cec78e5af2ec",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": [
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"remove-input"
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]
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},
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"outputs": [],
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"source": [
52+
"import pandas as pd\n",
53+
"from datetime import datetime\n",
54+
"from IPython.display import display, HTML\n",
55+
"\n",
56+
"# Define the course that is being looked at\n",
57+
"course_name = \"Intermediate Version Control\"\n",
58+
"\n",
59+
"# Load the CSV file\n",
60+
"file_path = '../data/accepting_applications.csv' # Adjust the path to your file location\n",
61+
"courses_df = pd.read_csv(file_path)\n",
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"\n",
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"# Strip any extra spaces in the column names\n",
64+
"courses_df.columns = courses_df.columns.str.strip()\n",
3565
"\n",
66+
"# Convert date columns to datetime\n",
67+
"courses_df['Start Date'] = pd.to_datetime(courses_df['Start Date'], dayfirst=True, errors='coerce')\n",
68+
"courses_df['End Date'] = pd.to_datetime(courses_df['End Date'], dayfirst=True, errors='coerce')\n",
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"\n",
70+
"# Get today's date\n",
71+
"today = datetime.now()\n",
72+
"\n",
73+
"# Function to generate markdown text based on the course dates\n",
74+
"def generate_html(row):\n",
75+
" if pd.notna(row['Start Date']) and pd.notna(row['End Date']):\n",
76+
" if row['Start Date'] <= today <= row['End Date']:\n",
77+
" return f\"<div style='font-weight: bold;'>This course is currently accepting applications.</div>\"\n",
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" return \"\"\n",
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"\n",
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"# Apply the function and create a new column for Markdown\n",
81+
"courses_df['HTML'] = courses_df.apply(generate_html, axis=1)\n",
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"\n",
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"# Variable for course name\n",
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"\n",
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"\n",
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"# Filter the DataFrame for the given course name and display the HTML text\n",
87+
"html_output = courses_df[courses_df['Course Name'] == course_name]['HTML'].values[0]\n",
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"display(HTML(html_output))\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a7dbd44b-f6db-4d19-8e96-e319e723adf1",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
36102
"## Installation Guide \n",
37103
"All CfRR courses require attendees to use their own computer/laptop to follow workshop activities and take effective notes. \n",
38104
"\n",

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