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spotify-history-data-analysis

This repository contains the Jupyter notebook and other relevant files relating to my spotify history exploratory analysis.


Table of Contents


  1. Description
  2. How To Get The Repository on Your Machine
  3. Running Jupyter Notebook


Description


As a avivd music fan and listener, I wanted to explore and incorporate this into a project. The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.

My learning goals for this project are:

  • Exercise my data anaylsis skills by explore my Spotify streaming history using Python
  • Visualise the data using matplotlib and seaborn.
  • Gain a detailed knowledge of my listening habits
  • How my findings will affect my listening habits

This project involved:

  1. Requesting and preparing data.
  2. Working with dates and timestamps.
  3. Checking frequency count and unique counts.
  4. Checking distributions and outliers.
  5. Visualisations.



How To Get The Repository on Your Machine


  1. Using your browser navigate to the repository:

    https://github.com/kmcd14/spotify.



  2. Under clone, copy the repository address, as seen in the above picture, using either SSH or HTTPS
  3. Open your terminal.
  4. Navigate to the location where you want to store the cloned directory.
  5. In the terminal type the command: 
    $git clone git@github.com:kmcd14/spotify.git
  6. Press enter. The cloned repository is now on your machine.





Running Jupyter Notebook


The easiest way to run the notebooks is by python installed via the Anaconda distribution. Anaconda is the most widely used python distribution in data science fields as it comes preloaded with most of the most popular packages and tools. You can find out more about Anaconda and how to install it here https://docs.anaconda.com/.


You can forgo downloading Anaconda and install each package individually in the python shell. A full list of requirements for each notebook can be found in the requirements.txt file in this repository. Full details and links to each package used can be found further down in this README.


Additionally, if you wish to view the notebook without having to install additional requirements, please click on the following badges to be redirected in your browser.



my_spotify.ipynb

nbviewer

About

The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.

Topics

jupyter-notebookmatplotlib-pyplotnumpypandaspythonpywaffleseaborntimestampwordcloud

Resources

Readme
MIT license
Activity

Stars

0 stars

Watchers

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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Repository files navigation
spotify-history-data-analysis
This repository contains the Jupyter notebook and other relevant files relating to my spotify history exploratory analysis.

Table of Contents

  1.  Description
  2. How To Get The Repository on Your Machine
  3. Running Jupyter Notebook


 Description

As a avivd music fan and listener, I wanted to explore and incorporate this into a project. The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
My learning goals for this project are:
  • Exercise my data anaylsis skills by explore my Spotify streaming history using Python
  • Visualise the data using matplotlib and seaborn.
  • Gain a detailed knowledge of my listening habits
  • How my findings will affect my listening habits
This project involved:
  1. Requesting and preparing data.
  2. Working with dates and timestamps.
  3. Checking frequency count and unique counts.
  4. Checking distributions and outliers.
  5. Visualisations.


 How To Get The Repository on Your Machine

  1. Using your browser navigate to the repository: 
    https://github.com/kmcd14/spotify.


  2. Under clone, copy the repository address, as seen in the above picture, using either SSH or HTTPS
  3.  Open your terminal.
  4.  Navigate to the location where you want to store the cloned directory.
  5. In the terminal type the command:

    $git clone git@github.com:kmcd14/spotify.git

  6. Press enter. The cloned repository is now on your machine.





Running Jupyter Notebook

The easiest way to run the notebooks is by python installed via the Anaconda distribution.
Anaconda is the most widely used python distribution in data science fields as it comes preloaded with most of the most popular packages and tools. You can find out more about Anaconda and how to install it here
https://docs.anaconda.com/.

You can forgo downloading Anaconda and install each package individually in the python shell. A full list of requirements for each notebook can be found in the requirements.txt file in this repository. Full details and links to each package used can be found further down in this README.


Additionally, if you wish to view the notebook without having to install additional requirements, please click on the following badges to be redirected in your browser. 


my_spotify.ipynb
nbviewer
About
The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
Topics
jupyter-notebookmatplotlib-pyplotnumpypandaspythonpywaffleseaborntimestampwordcloud
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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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('^' + ".*" + '

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Repository files navigation
spotify-history-data-analysis
This repository contains the Jupyter notebook and other relevant files relating to my spotify history exploratory analysis.

Table of Contents

  1.  Description
  2. How To Get The Repository on Your Machine
  3. Running Jupyter Notebook


 Description

As a avivd music fan and listener, I wanted to explore and incorporate this into a project. The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
My learning goals for this project are:
  • Exercise my data anaylsis skills by explore my Spotify streaming history using Python
  • Visualise the data using matplotlib and seaborn.
  • Gain a detailed knowledge of my listening habits
  • How my findings will affect my listening habits
This project involved:
  1. Requesting and preparing data.
  2. Working with dates and timestamps.
  3. Checking frequency count and unique counts.
  4. Checking distributions and outliers.
  5. Visualisations.


 How To Get The Repository on Your Machine

  1. Using your browser navigate to the repository: 
    https://github.com/kmcd14/spotify.


  2. Under clone, copy the repository address, as seen in the above picture, using either SSH or HTTPS
  3.  Open your terminal.
  4.  Navigate to the location where you want to store the cloned directory.
  5. In the terminal type the command:

    $git clone git@github.com:kmcd14/spotify.git

  6. Press enter. The cloned repository is now on your machine.





Running Jupyter Notebook

The easiest way to run the notebooks is by python installed via the Anaconda distribution.
Anaconda is the most widely used python distribution in data science fields as it comes preloaded with most of the most popular packages and tools. You can find out more about Anaconda and how to install it here
https://docs.anaconda.com/.

You can forgo downloading Anaconda and install each package individually in the python shell. A full list of requirements for each notebook can be found in the requirements.txt file in this repository. Full details and links to each package used can be found further down in this README.


Additionally, if you wish to view the notebook without having to install additional requirements, please click on the following badges to be redirected in your browser. 


my_spotify.ipynb
nbviewer
About
The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
Topics
jupyter-notebookmatplotlib-pyplotnumpypandaspythonpywaffleseaborntimestampwordcloud
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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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('^' + ".*" + '

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Repository files navigation
spotify-history-data-analysis
This repository contains the Jupyter notebook and other relevant files relating to my spotify history exploratory analysis.

Table of Contents

  1.  Description
  2. How To Get The Repository on Your Machine
  3. Running Jupyter Notebook


 Description

As a avivd music fan and listener, I wanted to explore and incorporate this into a project. The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
My learning goals for this project are:
  • Exercise my data anaylsis skills by explore my Spotify streaming history using Python
  • Visualise the data using matplotlib and seaborn.
  • Gain a detailed knowledge of my listening habits
  • How my findings will affect my listening habits
This project involved:
  1. Requesting and preparing data.
  2. Working with dates and timestamps.
  3. Checking frequency count and unique counts.
  4. Checking distributions and outliers.
  5. Visualisations.


 How To Get The Repository on Your Machine

  1. Using your browser navigate to the repository: 
    https://github.com/kmcd14/spotify.


  2. Under clone, copy the repository address, as seen in the above picture, using either SSH or HTTPS
  3.  Open your terminal.
  4.  Navigate to the location where you want to store the cloned directory.
  5. In the terminal type the command:

    $git clone git@github.com:kmcd14/spotify.git

  6. Press enter. The cloned repository is now on your machine.





Running Jupyter Notebook

The easiest way to run the notebooks is by python installed via the Anaconda distribution.
Anaconda is the most widely used python distribution in data science fields as it comes preloaded with most of the most popular packages and tools. You can find out more about Anaconda and how to install it here
https://docs.anaconda.com/.

You can forgo downloading Anaconda and install each package individually in the python shell. A full list of requirements for each notebook can be found in the requirements.txt file in this repository. Full details and links to each package used can be found further down in this README.


Additionally, if you wish to view the notebook without having to install additional requirements, please click on the following badges to be redirected in your browser. 


my_spotify.ipynb
nbviewer
About
The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
Topics
jupyter-notebookmatplotlib-pyplotnumpypandaspythonpywaffleseaborntimestampwordcloud
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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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" + '

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Repository files navigation
spotify-history-data-analysis
This repository contains the Jupyter notebook and other relevant files relating to my spotify history exploratory analysis.

Table of Contents

  1.  Description
  2. How To Get The Repository on Your Machine
  3. Running Jupyter Notebook


 Description

As a avivd music fan and listener, I wanted to explore and incorporate this into a project. The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
My learning goals for this project are:
  • Exercise my data anaylsis skills by explore my Spotify streaming history using Python
  • Visualise the data using matplotlib and seaborn.
  • Gain a detailed knowledge of my listening habits
  • How my findings will affect my listening habits
This project involved:
  1. Requesting and preparing data.
  2. Working with dates and timestamps.
  3. Checking frequency count and unique counts.
  4. Checking distributions and outliers.
  5. Visualisations.


 How To Get The Repository on Your Machine

  1. Using your browser navigate to the repository: 
    https://github.com/kmcd14/spotify.


  2. Under clone, copy the repository address, as seen in the above picture, using either SSH or HTTPS
  3.  Open your terminal.
  4.  Navigate to the location where you want to store the cloned directory.
  5. In the terminal type the command:

    $git clone git@github.com:kmcd14/spotify.git

  6. Press enter. The cloned repository is now on your machine.





Running Jupyter Notebook

The easiest way to run the notebooks is by python installed via the Anaconda distribution.
Anaconda is the most widely used python distribution in data science fields as it comes preloaded with most of the most popular packages and tools. You can find out more about Anaconda and how to install it here
https://docs.anaconda.com/.

You can forgo downloading Anaconda and install each package individually in the python shell. A full list of requirements for each notebook can be found in the requirements.txt file in this repository. Full details and links to each package used can be found further down in this README.


Additionally, if you wish to view the notebook without having to install additional requirements, please click on the following badges to be redirected in your browser. 


my_spotify.ipynb
nbviewer
About
The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
Topics
jupyter-notebookmatplotlib-pyplotnumpypandaspythonpywaffleseaborntimestampwordcloud
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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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('^' + ".*" + '

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streaming_history.csv
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Repository files navigation
spotify-history-data-analysis
This repository contains the Jupyter notebook and other relevant files relating to my spotify history exploratory analysis.

Table of Contents

  1.  Description
  2. How To Get The Repository on Your Machine
  3. Running Jupyter Notebook


 Description

As a avivd music fan and listener, I wanted to explore and incorporate this into a project. The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
My learning goals for this project are:
  • Exercise my data anaylsis skills by explore my Spotify streaming history using Python
  • Visualise the data using matplotlib and seaborn.
  • Gain a detailed knowledge of my listening habits
  • How my findings will affect my listening habits
This project involved:
  1. Requesting and preparing data.
  2. Working with dates and timestamps.
  3. Checking frequency count and unique counts.
  4. Checking distributions and outliers.
  5. Visualisations.


 How To Get The Repository on Your Machine

  1. Using your browser navigate to the repository: 
    https://github.com/kmcd14/spotify.


  2. Under clone, copy the repository address, as seen in the above picture, using either SSH or HTTPS
  3.  Open your terminal.
  4.  Navigate to the location where you want to store the cloned directory.
  5. In the terminal type the command:

    $git clone git@github.com:kmcd14/spotify.git

  6. Press enter. The cloned repository is now on your machine.





Running Jupyter Notebook

The easiest way to run the notebooks is by python installed via the Anaconda distribution.
Anaconda is the most widely used python distribution in data science fields as it comes preloaded with most of the most popular packages and tools. You can find out more about Anaconda and how to install it here
https://docs.anaconda.com/.

You can forgo downloading Anaconda and install each package individually in the python shell. A full list of requirements for each notebook can be found in the requirements.txt file in this repository. Full details and links to each package used can be found further down in this README.


Additionally, if you wish to view the notebook without having to install additional requirements, please click on the following badges to be redirected in your browser. 


my_spotify.ipynb
nbviewer
About
The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
Topics
jupyter-notebookmatplotlib-pyplotnumpypandaspythonpywaffleseaborntimestampwordcloud
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
1 watching
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0 forks
Report repository
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, '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('^' + ".*" + '

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my_spotify.ipynb
streaming_history.csv
streaming_history.csv
Repository files navigation
spotify-history-data-analysis
This repository contains the Jupyter notebook and other relevant files relating to my spotify history exploratory analysis.

Table of Contents

  1.  Description
  2. How To Get The Repository on Your Machine
  3. Running Jupyter Notebook


 Description

As a avivd music fan and listener, I wanted to explore and incorporate this into a project. The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
My learning goals for this project are:
  • Exercise my data anaylsis skills by explore my Spotify streaming history using Python
  • Visualise the data using matplotlib and seaborn.
  • Gain a detailed knowledge of my listening habits
  • How my findings will affect my listening habits
This project involved:
  1. Requesting and preparing data.
  2. Working with dates and timestamps.
  3. Checking frequency count and unique counts.
  4. Checking distributions and outliers.
  5. Visualisations.


 How To Get The Repository on Your Machine

  1. Using your browser navigate to the repository: 
    https://github.com/kmcd14/spotify.


  2. Under clone, copy the repository address, as seen in the above picture, using either SSH or HTTPS
  3.  Open your terminal.
  4.  Navigate to the location where you want to store the cloned directory.
  5. In the terminal type the command:

    $git clone git@github.com:kmcd14/spotify.git

  6. Press enter. The cloned repository is now on your machine.





Running Jupyter Notebook

The easiest way to run the notebooks is by python installed via the Anaconda distribution.
Anaconda is the most widely used python distribution in data science fields as it comes preloaded with most of the most popular packages and tools. You can find out more about Anaconda and how to install it here
https://docs.anaconda.com/.

You can forgo downloading Anaconda and install each package individually in the python shell. A full list of requirements for each notebook can be found in the requirements.txt file in this repository. Full details and links to each package used can be found further down in this README.


Additionally, if you wish to view the notebook without having to install additional requirements, please click on the following badges to be redirected in your browser. 


my_spotify.ipynb
nbviewer
About
The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
Topics
jupyter-notebookmatplotlib-pyplotnumpypandaspythonpywaffleseaborntimestampwordcloud
Resources
Readme
MIT license
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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); }
})();
})();

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spotify-history-data-analysis
This repository contains the Jupyter notebook and other relevant files relating to my spotify history exploratory analysis.

Table of Contents

  1.  Description
  2. How To Get The Repository on Your Machine
  3. Running Jupyter Notebook


 Description

As a avivd music fan and listener, I wanted to explore and incorporate this into a project. The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
My learning goals for this project are:
  • Exercise my data anaylsis skills by explore my Spotify streaming history using Python
  • Visualise the data using matplotlib and seaborn.
  • Gain a detailed knowledge of my listening habits
  • How my findings will affect my listening habits
This project involved:
  1. Requesting and preparing data.
  2. Working with dates and timestamps.
  3. Checking frequency count and unique counts.
  4. Checking distributions and outliers.
  5. Visualisations.


 How To Get The Repository on Your Machine

  1. Using your browser navigate to the repository: 
    https://github.com/kmcd14/spotify.


  2. Under clone, copy the repository address, as seen in the above picture, using either SSH or HTTPS
  3.  Open your terminal.
  4.  Navigate to the location where you want to store the cloned directory.
  5. In the terminal type the command:

    $git clone git@github.com:kmcd14/spotify.git

  6. Press enter. The cloned repository is now on your machine.





Running Jupyter Notebook

The easiest way to run the notebooks is by python installed via the Anaconda distribution.
Anaconda is the most widely used python distribution in data science fields as it comes preloaded with most of the most popular packages and tools. You can find out more about Anaconda and how to install it here
https://docs.anaconda.com/.

You can forgo downloading Anaconda and install each package individually in the python shell. A full list of requirements for each notebook can be found in the requirements.txt file in this repository. Full details and links to each package used can be found further down in this README.


Additionally, if you wish to view the notebook without having to install additional requirements, please click on the following badges to be redirected in your browser. 


my_spotify.ipynb
nbviewer
About
The aim of this project is to research and investigate my personal Spotify listening history, doing so by writing documentation and investigate the data using Python.
Topics
jupyter-notebookmatplotlib-pyplotnumpypandaspythonpywaffleseaborntimestampwordcloud
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Contributors
Languages