A Personal Activity Tracker: Insights into Fitness and Walking

As more and more people are turning to indoor exercises to stay fit and healthy, tracking one's personal activity has become increasingly important. With the help of SQL, this task has become much easier. By selecting the type of exercise, start date, start time, sport time, and calories, we can analyze our fitness journey and make meaningful insights.

SELECT * FROM 'ACTIVITY.csv'

The first visualization is a bar chart that shows the sum of sport time for each type of exercise. This chart gives us a clear picture of how much time i am spending on each type of exercise. From this chart we can see that bigest part of my workout is indoor Fitness.

The second chart is a median of sport time for each type of exercise. This chart provides a more detailed view of how I am spending my time. It shows us the typical duration of our exercise sessions for each type.

The third visualization is a three-dimensional bar chart that combines the sum of sport time and the type of exercise with the sum of calories burned. This chart helps us see the correlation between the amount of time I spend exercising, the type of exercise, and the number of calories I burn.

In conclusion, tracking our personal activity through SQL and visualizing the data can provide valuable insights into our fitness journey. By monitoring the sum of sport time, the median of sport time, and the sum of calories burned, we can make informed decisions about how we want to shape our fitness journey and achieve our goals.

Walking is one of the simplest and most effective ways to stay active and healthy. By tracking our walking activity using SQL, we can gain valuable insights into our habits and make meaningful improvements. The data used for this analysis includes the date, day of the week, steps, distance, and calories burned.

SELECT * FROM 'WALKING_ACTIVITY.csv'

The first visualization is a line chart that shows the sum of steps taken throughout the day. This chart highlights the daily activity levels and reveals that the most active days are Friday and Saturday. After those days, the line starts to fall, indicating a decrease in activity levels.

The second visualization is a chart that represents the distance covered and the day of the week. This chart shows that Friday is the day when the most distance is covered. This information can help us understand when I am most motivated to walk and make adjustments to my routine accordingly.

The last visualization is a bar chart that compares the calories burned with the steps taken. This chart demonstrates that taking a lot of steps per day does not always result in burning more calories. This is an important insight as it helps us understand that simply increasing the number of steps taken is not enough to maximize the health benefits of walking, we need to increase the intensity of walking.

In conclusion, tracking our walking activity using SQL and visualizing the data can provide valuable insights into our habits and help us make meaningful improvements. By monitoring the daily activity levels, the distance covered, and the calories burned, we can develop an effective and efficient walking routine that will help us achieve our health and fitness goals.