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Data Analyzing Project on Personal Google Fit Data

Welcome to my personal fitness journey with Google Fit! 🏃‍♀️📊 In this project, I'll take you through a captivating exploratory data analysis (EDA) of my very own fitness activity recorded on Google Fit. Together, we'll unlock valuable insights and make some exciting observations by applying powerful visualizations to my fitness data.

Motivation 💪🚀

Life can get challenging, and during my graduate study journey, I faced my fair share of struggles - anxiety, depression, and sleep deprivation. I also noticed a significant weight gain and experienced moments of rapid heart rate during sleep. Determined to take control of my well-being, I embarked on a personal mission to track myself and gain a deeper understanding of my fitness habits. This data analysis project is not just about numbers; it's about personal growth and transformation.

The Quest for Better Insights 💡

Equipped with my trusty Amazfit GTS 4 mini, I synced my activity data to Google Fit through the Zepp application. While the fitness experience with the watch was excellent, the insights provided felt somewhat lackluster. My data analyst instincts kicked in, and I set out on a quest to discover better ways to gain meaningful insights from my daily fitness activity. That's when I stumbled upon Google Takeout - a treasure trove of personal data waiting to be explored!

A Personal Data Adventure 🚀🗺️

Get ready to join me on an exhilarating data adventure like no other! 🌟 Armed with my trusty Amazfit GTS 4 mini and the power of Google Fit, I've embarked on an epic quest to unravel the mysteries hidden within my fitness data. While some data, like heart rate, may be missing due to my new journey with this watch, fear not! We'll work our magic with the treasure trove of data from Google Takeout, trying our best to extract meaningful insights and fascinating discoveries.

As I sync my activity data through the Zepp application, I can't help but feel a surge of excitement. The insights offered so far might be informative, but they lack that spark of personal connection that truly motivates me. That's where my data analyst prowess comes in! This is more than just data exploration; it's a quest for my personal growth and self-discovery. Let's dive into the nitty-gritty of data cleaning. From there, we'll craft dazzling visualizations that will paint a vivid picture of my activity evolution over time.

While some data may be missing, remember that every data point is a piece of the puzzle, and it can still guide us towards meaningful discoveries. Let's turn this data exploration into a thrilling ride of self-improvement and exploration. Are you ready to embrace the unknown and discover the wonders hidden within our data? Let's embark on this exciting journey of data exploration and personal growth! 🚀🔍💪

Data Extract and Setup 📦🔍

To begin the exhilarating data journey, we'll first need to extract and set up the precious fitness data from Google Fit. Fear not, for it's a straightforward process that will soon unveil a wealth of insights!

Step 1: Journey to takeout.google.com 🌐

First, embark on a virtual quest to takeout.google.com. This is where we'll find the gateway to our treasure trove of fitness data.

Step 2: Select Google Fit and Initiate Export 🏃‍♂️📅

Once at takeout.google.com, navigate to the Google Fit section and initiate an export of our fitness data. Think of it as creating our data expedition package!

Step 3: Await the Data Archive 🕰️📦 Now comes the exciting part! Keep an eager eye on our notifications, as Google will send us a signal once our Data Archive is available.

Step 4: Unleash the Data Archive 🔓🗂️ As soon as we receive the green light, unleash our data prowess and download the Data Archive. Excitement will build as we unzip the archive, revealing the invaluable fitness data within!

The stage is set, and the data awaits! Let's dive in and let the data exploration begin! 🚀🔍📈

In this exciting data analysis project, we'll be diving into the mysteries of my fitness journey using the "Daily Activity Metrics" data file. This CSV file contains a treasure trove of information about my daily fitness activities, capturing valuable insights about my move minutes count, calories burned, distance covered, step count, and more.

The "Daily Activity Metrics" data file is a key component of our analysis, allowing us to unravel the secrets of my fitness rhythms throughout the year. With the power of data visualization and the magic of Python, we'll uncover patterns, trends, and moments of triumph in my fitness journey.

So, let's embark on this adventure together! (Note: Replace "path/to/your/Daily%20activity%20metrics.csv" with the actual path or URL to your "Daily Activity Metrics" data file on GitHub.)

Curious to dive deep into the secrets of the fitness journey? Look no further! Discover the wonders of personal fitness data through the "PersonalActivityInsights.ipynb" notebook. This captivating notebook takes you on an exciting data exploration and visualization adventure, unraveling valuable insights hidden within how my fitness metrics was.

In "PersonalActivityInsights.ipynb," you'll find a treasure trove of data exploration, data visualization, and engaging graphs that shed light on my activity rhythms. This comprehensive analysis empowered me to make informed decisions on my wellness journey.

Get ready to be inspired by the power of data visualization! Uncover patterns, track progress, and identify opportunities for growth. Embrace the magic of Python as it weaves through the google fit data, creating a beautiful symphony of insights.

Please open the "PersonalActivityInsights.ipynb" notebook and let the exploration begin! 🚀📊💪

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Exploratory Data Analysis of Personal Google Fit data extracted from Google Takeout

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