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Template for Python Projects

This is a template for Python Projects in the Goldenberg Lab. There are three folders:

  • data All of the data stored in this repo should be located in this folder. There are subfolders for raw data and processed data.
  • processing All of the code designed for processing should be saved in this folder.
  • analysis should be used for analysis of processed data.

Your workflow should be to:

  • Place raw data in data/raw. Use .gitignore to exclude all data, raw and processed, from Github! You should never upload any remotely sensitive data on Github.
  • Write and run code in processing that takes in this raw data, does all necessary cleaning, combining, and processing, and writes processed data file(s) to data/processed. Again, this file should be ignored by Git.
  • Conduct your analysis, ideally in a Jupyter notebook, in analysis, reading in the processed data file. Visualizations should go in analysis/img, if you'd like to store them in the Github repo. (You may not need to include the images themselves, but code to produce any visualizations should be included in your analysis.)

Requirements

This is a template for Python Projects in Goldenberg Lab. To use this template, please:

  • Install Python and a version of conda (Anaconda or Miniconda). We recommend starting with the latest versions of each.
  • You should run all of your code in a dedicated conda environment -- see this guide on using conda! When you're done, include the environment.yml in the root of this repo for others to use.

Use this template for the first time (if you are not replicating/ adding on to an existing analysis)

  • Choose the repository's username/organization name.
    • Please set the owner of your analysis template to our lab (GoldenbergLab).
    • All analysis repositories should start as public, unless indicated otherwise.
  • Name the repository following the lab naming convention. Full guide on repository naming conventions can be found here. In short, github repositories are following this naming convention: project-name-analysis. So if your project is about counting kittens, your repository name is counting-kittens-analysis.
  • Add a description of your project. Please include:
    1. Project Name
    2. Date of repository creation
    3. Your name, and the names of other who worked on it
    4. The purpose of the project and the main question you asked
    5. The source of the data for the analysis (Prolific, MTURK, Qualtrics, etc.)

About

Template for Python Projects in Goldenberg Lab

Resources

Readme

Code of conduct

Code of conduct

Contributing

Contributing
Activity
Custom properties

Stars

0 stars

Watchers

2 watching

Forks

0 forks
Report repository

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
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Template for Python Projects
This is a template for Python Projects in the Goldenberg Lab. There are three folders:
  • data All of the data stored in this repo should be located in this folder. There are subfolders for raw data and processed data.
  • processing All of the code designed for processing should be saved in this folder.
  • analysis should be used for analysis of processed data.
Your workflow should be to:
  • Place raw data in data/raw. Use .gitignore to exclude all data, raw and processed, from Github! You should never upload any remotely sensitive data on Github.
  • Write and run code in processing that takes in this raw data, does all necessary cleaning, combining, and processing, and writes processed data file(s) to data/processed. Again, this file should be ignored by Git.
  • Conduct your analysis, ideally in a Jupyter notebook, in analysis, reading in the processed data file. Visualizations should go in analysis/img, if you'd like to store them in the Github repo. (You may not need to include the images themselves, but code to produce any visualizations should be included in your analysis.)
Requirements
This is a template for Python Projects in Goldenberg Lab. To use this template, please:
  • Install Python and a version of conda (Anaconda or Miniconda). We recommend starting with the latest versions of each.
  • You should run all of your code in a dedicated conda environment -- see this guide on using conda! When you're done, include the environment.yml in the root of this repo for others to use.
Use this template for the first time (if you are not replicating/ adding on to an existing analysis)
  • Choose the repository's username/organization name.

    • Please set the owner of your analysis template to our lab (GoldenbergLab).
    • All analysis repositories should start as public, unless indicated otherwise.
  • Name the repository following the lab naming convention. Full guide on repository naming conventions can be found here. In short, github repositories are following this naming convention: project-name-analysis. So if your project is about counting kittens, your repository name is counting-kittens-analysis.
  • Add a description of your project. Please include:

    1. Project Name
    2. Date of repository creation
    3. Your name, and the names of other who worked on it
    4. The purpose of the project and the main question you asked
    5. The source of the data for the analysis (Prolific, MTURK, Qualtrics, etc.)
About
Template for Python Projects in Goldenberg Lab
Resources
Readme
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Template for Python Projects
This is a template for Python Projects in the Goldenberg Lab. There are three folders:
  • data All of the data stored in this repo should be located in this folder. There are subfolders for raw data and processed data.
  • processing All of the code designed for processing should be saved in this folder.
  • analysis should be used for analysis of processed data.
Your workflow should be to:
  • Place raw data in data/raw. Use .gitignore to exclude all data, raw and processed, from Github! You should never upload any remotely sensitive data on Github.
  • Write and run code in processing that takes in this raw data, does all necessary cleaning, combining, and processing, and writes processed data file(s) to data/processed. Again, this file should be ignored by Git.
  • Conduct your analysis, ideally in a Jupyter notebook, in analysis, reading in the processed data file. Visualizations should go in analysis/img, if you'd like to store them in the Github repo. (You may not need to include the images themselves, but code to produce any visualizations should be included in your analysis.)
Requirements
This is a template for Python Projects in Goldenberg Lab. To use this template, please:
  • Install Python and a version of conda (Anaconda or Miniconda). We recommend starting with the latest versions of each.
  • You should run all of your code in a dedicated conda environment -- see this guide on using conda! When you're done, include the environment.yml in the root of this repo for others to use.
Use this template for the first time (if you are not replicating/ adding on to an existing analysis)
  • Choose the repository's username/organization name.

    • Please set the owner of your analysis template to our lab (GoldenbergLab).
    • All analysis repositories should start as public, unless indicated otherwise.
  • Name the repository following the lab naming convention. Full guide on repository naming conventions can be found here. In short, github repositories are following this naming convention: project-name-analysis. So if your project is about counting kittens, your repository name is counting-kittens-analysis.
  • Add a description of your project. Please include:

    1. Project Name
    2. Date of repository creation
    3. Your name, and the names of other who worked on it
    4. The purpose of the project and the main question you asked
    5. The source of the data for the analysis (Prolific, MTURK, Qualtrics, etc.)
About
Template for Python Projects in Goldenberg Lab
Resources
Readme
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Template for Python Projects
This is a template for Python Projects in the Goldenberg Lab. There are three folders:
  • data All of the data stored in this repo should be located in this folder. There are subfolders for raw data and processed data.
  • processing All of the code designed for processing should be saved in this folder.
  • analysis should be used for analysis of processed data.
Your workflow should be to:
  • Place raw data in data/raw. Use .gitignore to exclude all data, raw and processed, from Github! You should never upload any remotely sensitive data on Github.
  • Write and run code in processing that takes in this raw data, does all necessary cleaning, combining, and processing, and writes processed data file(s) to data/processed. Again, this file should be ignored by Git.
  • Conduct your analysis, ideally in a Jupyter notebook, in analysis, reading in the processed data file. Visualizations should go in analysis/img, if you'd like to store them in the Github repo. (You may not need to include the images themselves, but code to produce any visualizations should be included in your analysis.)
Requirements
This is a template for Python Projects in Goldenberg Lab. To use this template, please:
  • Install Python and a version of conda (Anaconda or Miniconda). We recommend starting with the latest versions of each.
  • You should run all of your code in a dedicated conda environment -- see this guide on using conda! When you're done, include the environment.yml in the root of this repo for others to use.
Use this template for the first time (if you are not replicating/ adding on to an existing analysis)
  • Choose the repository's username/organization name.

    • Please set the owner of your analysis template to our lab (GoldenbergLab).
    • All analysis repositories should start as public, unless indicated otherwise.
  • Name the repository following the lab naming convention. Full guide on repository naming conventions can be found here. In short, github repositories are following this naming convention: project-name-analysis. So if your project is about counting kittens, your repository name is counting-kittens-analysis.
  • Add a description of your project. Please include:

    1. Project Name
    2. Date of repository creation
    3. Your name, and the names of other who worked on it
    4. The purpose of the project and the main question you asked
    5. The source of the data for the analysis (Prolific, MTURK, Qualtrics, etc.)
About
Template for Python Projects in Goldenberg Lab
Resources
Readme
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Template for Python Projects
This is a template for Python Projects in the Goldenberg Lab. There are three folders:
  • data All of the data stored in this repo should be located in this folder. There are subfolders for raw data and processed data.
  • processing All of the code designed for processing should be saved in this folder.
  • analysis should be used for analysis of processed data.
Your workflow should be to:
  • Place raw data in data/raw. Use .gitignore to exclude all data, raw and processed, from Github! You should never upload any remotely sensitive data on Github.
  • Write and run code in processing that takes in this raw data, does all necessary cleaning, combining, and processing, and writes processed data file(s) to data/processed. Again, this file should be ignored by Git.
  • Conduct your analysis, ideally in a Jupyter notebook, in analysis, reading in the processed data file. Visualizations should go in analysis/img, if you'd like to store them in the Github repo. (You may not need to include the images themselves, but code to produce any visualizations should be included in your analysis.)
Requirements
This is a template for Python Projects in Goldenberg Lab. To use this template, please:
  • Install Python and a version of conda (Anaconda or Miniconda). We recommend starting with the latest versions of each.
  • You should run all of your code in a dedicated conda environment -- see this guide on using conda! When you're done, include the environment.yml in the root of this repo for others to use.
Use this template for the first time (if you are not replicating/ adding on to an existing analysis)
  • Choose the repository's username/organization name.

    • Please set the owner of your analysis template to our lab (GoldenbergLab).
    • All analysis repositories should start as public, unless indicated otherwise.
  • Name the repository following the lab naming convention. Full guide on repository naming conventions can be found here. In short, github repositories are following this naming convention: project-name-analysis. So if your project is about counting kittens, your repository name is counting-kittens-analysis.
  • Add a description of your project. Please include:

    1. Project Name
    2. Date of repository creation
    3. Your name, and the names of other who worked on it
    4. The purpose of the project and the main question you asked
    5. The source of the data for the analysis (Prolific, MTURK, Qualtrics, etc.)
About
Template for Python Projects in Goldenberg Lab
Resources
Readme
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Template for Python Projects
This is a template for Python Projects in the Goldenberg Lab. There are three folders:
  • data All of the data stored in this repo should be located in this folder. There are subfolders for raw data and processed data.
  • processing All of the code designed for processing should be saved in this folder.
  • analysis should be used for analysis of processed data.
Your workflow should be to:
  • Place raw data in data/raw. Use .gitignore to exclude all data, raw and processed, from Github! You should never upload any remotely sensitive data on Github.
  • Write and run code in processing that takes in this raw data, does all necessary cleaning, combining, and processing, and writes processed data file(s) to data/processed. Again, this file should be ignored by Git.
  • Conduct your analysis, ideally in a Jupyter notebook, in analysis, reading in the processed data file. Visualizations should go in analysis/img, if you'd like to store them in the Github repo. (You may not need to include the images themselves, but code to produce any visualizations should be included in your analysis.)
Requirements
This is a template for Python Projects in Goldenberg Lab. To use this template, please:
  • Install Python and a version of conda (Anaconda or Miniconda). We recommend starting with the latest versions of each.
  • You should run all of your code in a dedicated conda environment -- see this guide on using conda! When you're done, include the environment.yml in the root of this repo for others to use.
Use this template for the first time (if you are not replicating/ adding on to an existing analysis)
  • Choose the repository's username/organization name.

    • Please set the owner of your analysis template to our lab (GoldenbergLab).
    • All analysis repositories should start as public, unless indicated otherwise.
  • Name the repository following the lab naming convention. Full guide on repository naming conventions can be found here. In short, github repositories are following this naming convention: project-name-analysis. So if your project is about counting kittens, your repository name is counting-kittens-analysis.
  • Add a description of your project. Please include:

    1. Project Name
    2. Date of repository creation
    3. Your name, and the names of other who worked on it
    4. The purpose of the project and the main question you asked
    5. The source of the data for the analysis (Prolific, MTURK, Qualtrics, etc.)
About
Template for Python Projects in Goldenberg Lab
Resources
Readme
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Template for Python Projects
This is a template for Python Projects in the Goldenberg Lab. There are three folders:
  • data All of the data stored in this repo should be located in this folder. There are subfolders for raw data and processed data.
  • processing All of the code designed for processing should be saved in this folder.
  • analysis should be used for analysis of processed data.
Your workflow should be to:
  • Place raw data in data/raw. Use .gitignore to exclude all data, raw and processed, from Github! You should never upload any remotely sensitive data on Github.
  • Write and run code in processing that takes in this raw data, does all necessary cleaning, combining, and processing, and writes processed data file(s) to data/processed. Again, this file should be ignored by Git.
  • Conduct your analysis, ideally in a Jupyter notebook, in analysis, reading in the processed data file. Visualizations should go in analysis/img, if you'd like to store them in the Github repo. (You may not need to include the images themselves, but code to produce any visualizations should be included in your analysis.)
Requirements
This is a template for Python Projects in Goldenberg Lab. To use this template, please:
  • Install Python and a version of conda (Anaconda or Miniconda). We recommend starting with the latest versions of each.
  • You should run all of your code in a dedicated conda environment -- see this guide on using conda! When you're done, include the environment.yml in the root of this repo for others to use.
Use this template for the first time (if you are not replicating/ adding on to an existing analysis)
  • Choose the repository's username/organization name.

    • Please set the owner of your analysis template to our lab (GoldenbergLab).
    • All analysis repositories should start as public, unless indicated otherwise.
  • Name the repository following the lab naming convention. Full guide on repository naming conventions can be found here. In short, github repositories are following this naming convention: project-name-analysis. So if your project is about counting kittens, your repository name is counting-kittens-analysis.
  • Add a description of your project. Please include:

    1. Project Name
    2. Date of repository creation
    3. Your name, and the names of other who worked on it
    4. The purpose of the project and the main question you asked
    5. The source of the data for the analysis (Prolific, MTURK, Qualtrics, etc.)
About
Template for Python Projects in Goldenberg Lab
Resources
Readme
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Template for Python Projects
This is a template for Python Projects in the Goldenberg Lab. There are three folders:
  • data All of the data stored in this repo should be located in this folder. There are subfolders for raw data and processed data.
  • processing All of the code designed for processing should be saved in this folder.
  • analysis should be used for analysis of processed data.
Your workflow should be to:
  • Place raw data in data/raw. Use .gitignore to exclude all data, raw and processed, from Github! You should never upload any remotely sensitive data on Github.
  • Write and run code in processing that takes in this raw data, does all necessary cleaning, combining, and processing, and writes processed data file(s) to data/processed. Again, this file should be ignored by Git.
  • Conduct your analysis, ideally in a Jupyter notebook, in analysis, reading in the processed data file. Visualizations should go in analysis/img, if you'd like to store them in the Github repo. (You may not need to include the images themselves, but code to produce any visualizations should be included in your analysis.)
Requirements
This is a template for Python Projects in Goldenberg Lab. To use this template, please:
  • Install Python and a version of conda (Anaconda or Miniconda). We recommend starting with the latest versions of each.
  • You should run all of your code in a dedicated conda environment -- see this guide on using conda! When you're done, include the environment.yml in the root of this repo for others to use.
Use this template for the first time (if you are not replicating/ adding on to an existing analysis)
  • Choose the repository's username/organization name.

    • Please set the owner of your analysis template to our lab (GoldenbergLab).
    • All analysis repositories should start as public, unless indicated otherwise.
  • Name the repository following the lab naming convention. Full guide on repository naming conventions can be found here. In short, github repositories are following this naming convention: project-name-analysis. So if your project is about counting kittens, your repository name is counting-kittens-analysis.
  • Add a description of your project. Please include:

    1. Project Name
    2. Date of repository creation
    3. Your name, and the names of other who worked on it
    4. The purpose of the project and the main question you asked
    5. The source of the data for the analysis (Prolific, MTURK, Qualtrics, etc.)
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Template for Python Projects in Goldenberg Lab
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