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studytime

Overview

When I first started college, I needed to find a way to organize my time; I needed some sort of planner. I discovered an app called Structured. It has an inbox to list tasks that need to be done, and also a timeline where you can time-block your day. I made use of both of these features to organize my time. After my freshman year, I had learned quite a lot about doing data science in python. Since I had recorded literally all the time I spent on schoolwork into structured, I had a good source of data available to me. Then I used python to make some visualizations with pandas, matplotlib, and seaborn. After that, I used Tableau to present the data as a story.

Repository Structure

  • notebooks: contains scratch work for data exploration and visualization
  • src: contains python scripts used to produce results
  • results: contains visualizations illustrating the data

Reproducibility

This analysis is containerized using Docker and automated using Snakemake. To reproduce the results, run the docker image via the runall.sh script. However, I have not published the raw data due to privacy reasons.

Results

Tableau Story

Alt textAlt textAlt textAlt textAlt text

Matplotlib Visualizations

Alt text

The above stack plot shows how much time I spent studying on a weekly basis per class per semester. So far my fall semesters are typically lighter and Spring 2025 is proving to be especially tough.

Alt text

The above barplot shows how much time I spent studying on average each weekday per semester. My study habits can vary day to day, and I see that I typically don't do much at all on Fridays.

Alt text

The above heatmap shows at which times during the week I most frequently spend studying.

Future Work

  • Explore new visualizations to expand my knowledge of data visualization.
  • Analyze additional variables available to look at, such as assignment due dates and assignment names.
  • Draw conclusions to improve my study habits in the future.
trackgit-views

About

Analysis of my time spent studying at UIUC.

Topics

containerizationdata-sciencedocker-containerpandaspythonsnakemake-workflowtableau

Resources

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Activity

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1 watching

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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" + '

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BranchesTags
Repository files navigation
studytime
Overview
When I first started college, I needed to find a way to organize my time; I needed some sort of planner. I discovered an app called
Structured. It has an inbox to list tasks that need to be done, and also a timeline where you can time-block your day.
I made use of both of these features to organize my time. After my freshman year, I had learned quite a lot about doing data science in python.
Since I had recorded literally all the time I spent on schoolwork into structured, I had a good source of data available to me.
Then I used python to make some visualizations with pandas, matplotlib, and seaborn. After that, I used Tableau to present the data as a story.
Repository Structure
  • notebooks: contains scratch work for data exploration and visualization
  • src: contains python scripts used to produce results
  • results: contains visualizations illustrating the data
Reproducibility
This analysis is containerized using Docker and automated using Snakemake. To reproduce the results, run the docker image via the runall.sh script. However, I have not published the raw data due to privacy reasons.
Results
Tableau Story
Alt textAlt textAlt textAlt textAlt text
Matplotlib Visualizations
Alt text
The above stack plot shows how much time I spent studying on a weekly basis per class per semester. So far my fall semesters are typically lighter
and Spring 2025 is proving to be especially tough.
Alt text
The above barplot shows how much time I spent studying on average each weekday per semester. My study habits can vary day to day, and I see that
I typically don't do much at all on Fridays.
Alt text
The above heatmap shows at which times during the week I most frequently spend studying.
Future Work
  • Explore new visualizations to expand my knowledge of data visualization.
  • Analyze additional variables available to look at, such as assignment due dates and assignment names.
  • Draw conclusions to improve my study habits in the future.
trackgit-views
About
Analysis of my time spent studying at UIUC.
Topics
containerizationdata-sciencedocker-containerpandaspythonsnakemake-workflowtableau
Resources
Readme
Activity
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1 watching
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, '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
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studytime
Overview
When I first started college, I needed to find a way to organize my time; I needed some sort of planner. I discovered an app called
Structured. It has an inbox to list tasks that need to be done, and also a timeline where you can time-block your day.
I made use of both of these features to organize my time. After my freshman year, I had learned quite a lot about doing data science in python.
Since I had recorded literally all the time I spent on schoolwork into structured, I had a good source of data available to me.
Then I used python to make some visualizations with pandas, matplotlib, and seaborn. After that, I used Tableau to present the data as a story.
Repository Structure
  • notebooks: contains scratch work for data exploration and visualization
  • src: contains python scripts used to produce results
  • results: contains visualizations illustrating the data
Reproducibility
This analysis is containerized using Docker and automated using Snakemake. To reproduce the results, run the docker image via the runall.sh script. However, I have not published the raw data due to privacy reasons.
Results
Tableau Story
Alt textAlt textAlt textAlt textAlt text
Matplotlib Visualizations
Alt text
The above stack plot shows how much time I spent studying on a weekly basis per class per semester. So far my fall semesters are typically lighter
and Spring 2025 is proving to be especially tough.
Alt text
The above barplot shows how much time I spent studying on average each weekday per semester. My study habits can vary day to day, and I see that
I typically don't do much at all on Fridays.
Alt text
The above heatmap shows at which times during the week I most frequently spend studying.
Future Work
  • Explore new visualizations to expand my knowledge of data visualization.
  • Analyze additional variables available to look at, such as assignment due dates and assignment names.
  • Draw conclusions to improve my study habits in the future.
trackgit-views
About
Analysis of my time spent studying at UIUC.
Topics
containerizationdata-sciencedocker-containerpandaspythonsnakemake-workflowtableau
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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Used by
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, '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
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studytime
Overview
When I first started college, I needed to find a way to organize my time; I needed some sort of planner. I discovered an app called
Structured. It has an inbox to list tasks that need to be done, and also a timeline where you can time-block your day.
I made use of both of these features to organize my time. After my freshman year, I had learned quite a lot about doing data science in python.
Since I had recorded literally all the time I spent on schoolwork into structured, I had a good source of data available to me.
Then I used python to make some visualizations with pandas, matplotlib, and seaborn. After that, I used Tableau to present the data as a story.
Repository Structure
  • notebooks: contains scratch work for data exploration and visualization
  • src: contains python scripts used to produce results
  • results: contains visualizations illustrating the data
Reproducibility
This analysis is containerized using Docker and automated using Snakemake. To reproduce the results, run the docker image via the runall.sh script. However, I have not published the raw data due to privacy reasons.
Results
Tableau Story
Alt textAlt textAlt textAlt textAlt text
Matplotlib Visualizations
Alt text
The above stack plot shows how much time I spent studying on a weekly basis per class per semester. So far my fall semesters are typically lighter
and Spring 2025 is proving to be especially tough.
Alt text
The above barplot shows how much time I spent studying on average each weekday per semester. My study habits can vary day to day, and I see that
I typically don't do much at all on Fridays.
Alt text
The above heatmap shows at which times during the week I most frequently spend studying.
Future Work
  • Explore new visualizations to expand my knowledge of data visualization.
  • Analyze additional variables available to look at, such as assignment due dates and assignment names.
  • Draw conclusions to improve my study habits in the future.
trackgit-views
About
Analysis of my time spent studying at UIUC.
Topics
containerizationdata-sciencedocker-containerpandaspythonsnakemake-workflowtableau
Resources
Readme
Activity
Stars
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Watchers
1 watching
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0 forks
Report repository
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Used by
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, '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
studytime
Overview
When I first started college, I needed to find a way to organize my time; I needed some sort of planner. I discovered an app called
Structured. It has an inbox to list tasks that need to be done, and also a timeline where you can time-block your day.
I made use of both of these features to organize my time. After my freshman year, I had learned quite a lot about doing data science in python.
Since I had recorded literally all the time I spent on schoolwork into structured, I had a good source of data available to me.
Then I used python to make some visualizations with pandas, matplotlib, and seaborn. After that, I used Tableau to present the data as a story.
Repository Structure
  • notebooks: contains scratch work for data exploration and visualization
  • src: contains python scripts used to produce results
  • results: contains visualizations illustrating the data
Reproducibility
This analysis is containerized using Docker and automated using Snakemake. To reproduce the results, run the docker image via the runall.sh script. However, I have not published the raw data due to privacy reasons.
Results
Tableau Story
Alt textAlt textAlt textAlt textAlt text
Matplotlib Visualizations
Alt text
The above stack plot shows how much time I spent studying on a weekly basis per class per semester. So far my fall semesters are typically lighter
and Spring 2025 is proving to be especially tough.
Alt text
The above barplot shows how much time I spent studying on average each weekday per semester. My study habits can vary day to day, and I see that
I typically don't do much at all on Fridays.
Alt text
The above heatmap shows at which times during the week I most frequently spend studying.
Future Work
  • Explore new visualizations to expand my knowledge of data visualization.
  • Analyze additional variables available to look at, such as assignment due dates and assignment names.
  • Draw conclusions to improve my study habits in the future.
trackgit-views
About
Analysis of my time spent studying at UIUC.
Topics
containerizationdata-sciencedocker-containerpandaspythonsnakemake-workflowtableau
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
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
studytime
Overview
When I first started college, I needed to find a way to organize my time; I needed some sort of planner. I discovered an app called
Structured. It has an inbox to list tasks that need to be done, and also a timeline where you can time-block your day.
I made use of both of these features to organize my time. After my freshman year, I had learned quite a lot about doing data science in python.
Since I had recorded literally all the time I spent on schoolwork into structured, I had a good source of data available to me.
Then I used python to make some visualizations with pandas, matplotlib, and seaborn. After that, I used Tableau to present the data as a story.
Repository Structure
  • notebooks: contains scratch work for data exploration and visualization
  • src: contains python scripts used to produce results
  • results: contains visualizations illustrating the data
Reproducibility
This analysis is containerized using Docker and automated using Snakemake. To reproduce the results, run the docker image via the runall.sh script. However, I have not published the raw data due to privacy reasons.
Results
Tableau Story
Alt textAlt textAlt textAlt textAlt text
Matplotlib Visualizations
Alt text
The above stack plot shows how much time I spent studying on a weekly basis per class per semester. So far my fall semesters are typically lighter
and Spring 2025 is proving to be especially tough.
Alt text
The above barplot shows how much time I spent studying on average each weekday per semester. My study habits can vary day to day, and I see that
I typically don't do much at all on Fridays.
Alt text
The above heatmap shows at which times during the week I most frequently spend studying.
Future Work
  • Explore new visualizations to expand my knowledge of data visualization.
  • Analyze additional variables available to look at, such as assignment due dates and assignment names.
  • Draw conclusions to improve my study habits in the future.
trackgit-views
About
Analysis of my time spent studying at UIUC.
Topics
containerizationdata-sciencedocker-containerpandaspythonsnakemake-workflowtableau
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
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
studytime
Overview
When I first started college, I needed to find a way to organize my time; I needed some sort of planner. I discovered an app called
Structured. It has an inbox to list tasks that need to be done, and also a timeline where you can time-block your day.
I made use of both of these features to organize my time. After my freshman year, I had learned quite a lot about doing data science in python.
Since I had recorded literally all the time I spent on schoolwork into structured, I had a good source of data available to me.
Then I used python to make some visualizations with pandas, matplotlib, and seaborn. After that, I used Tableau to present the data as a story.
Repository Structure
  • notebooks: contains scratch work for data exploration and visualization
  • src: contains python scripts used to produce results
  • results: contains visualizations illustrating the data
Reproducibility
This analysis is containerized using Docker and automated using Snakemake. To reproduce the results, run the docker image via the runall.sh script. However, I have not published the raw data due to privacy reasons.
Results
Tableau Story
Alt textAlt textAlt textAlt textAlt text
Matplotlib Visualizations
Alt text
The above stack plot shows how much time I spent studying on a weekly basis per class per semester. So far my fall semesters are typically lighter
and Spring 2025 is proving to be especially tough.
Alt text
The above barplot shows how much time I spent studying on average each weekday per semester. My study habits can vary day to day, and I see that
I typically don't do much at all on Fridays.
Alt text
The above heatmap shows at which times during the week I most frequently spend studying.
Future Work
  • Explore new visualizations to expand my knowledge of data visualization.
  • Analyze additional variables available to look at, such as assignment due dates and assignment names.
  • Draw conclusions to improve my study habits in the future.
trackgit-views
About
Analysis of my time spent studying at UIUC.
Topics
containerizationdata-sciencedocker-containerpandaspythonsnakemake-workflowtableau
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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Used by
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, '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); }
})();
})();

Skip to content
BranchesTags
Repository files navigation
studytime
Overview
When I first started college, I needed to find a way to organize my time; I needed some sort of planner. I discovered an app called
Structured. It has an inbox to list tasks that need to be done, and also a timeline where you can time-block your day.
I made use of both of these features to organize my time. After my freshman year, I had learned quite a lot about doing data science in python.
Since I had recorded literally all the time I spent on schoolwork into structured, I had a good source of data available to me.
Then I used python to make some visualizations with pandas, matplotlib, and seaborn. After that, I used Tableau to present the data as a story.
Repository Structure
  • notebooks: contains scratch work for data exploration and visualization
  • src: contains python scripts used to produce results
  • results: contains visualizations illustrating the data
Reproducibility
This analysis is containerized using Docker and automated using Snakemake. To reproduce the results, run the docker image via the runall.sh script. However, I have not published the raw data due to privacy reasons.
Results
Tableau Story
Alt textAlt textAlt textAlt textAlt text
Matplotlib Visualizations
Alt text
The above stack plot shows how much time I spent studying on a weekly basis per class per semester. So far my fall semesters are typically lighter
and Spring 2025 is proving to be especially tough.
Alt text
The above barplot shows how much time I spent studying on average each weekday per semester. My study habits can vary day to day, and I see that
I typically don't do much at all on Fridays.
Alt text
The above heatmap shows at which times during the week I most frequently spend studying.
Future Work
  • Explore new visualizations to expand my knowledge of data visualization.
  • Analyze additional variables available to look at, such as assignment due dates and assignment names.
  • Draw conclusions to improve my study habits in the future.
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Analysis of my time spent studying at UIUC.
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containerizationdata-sciencedocker-containerpandaspythonsnakemake-workflowtableau
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