My On-Job Training Analytics

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I have been working at Provincial Statistics Office of Tawi-Tawi (Philippines) which was part of the training on my OJT (On-Job Training). One of the requirements of the training is at least 80 hours of services, so I decided to work from April 19 to May 18, 2012, making it sure to surpass the required hours.

In that office, there is this daily records of our attendance which has a Sign in and Sign Out columns, where we actually put the time we arrive and dismiss, respectively. The first time I notice this, I started to get excited and very particular on the time I input, because I know that at the end of my training I’ll be collecting this and make some analysis.

Here’s the first plot below, which shows the Arrival and Dismissal time.
In the plot, notice that there are two groups of arrival and dismissal points. The first arrival points are dotted in the early morning of the day, this is due to the schedule of services of the office which opens at 8:00 am and will close at 12:00 pm. And the other one are in the afternoon, at 1:00 pm and will close at 5:00 pm. And I’m home, taking my lunch between 12:00 pm and 1:00 pm.
Now, It is clearly shown in the plot that I’ve been late in most days, as seen on the arrival points which is dotted between 12 and 14, (12:00 pm and 2:00 pm, respectively). There are cases that I went to the office at 2:00 pm, which is very late, and this happened on May 10. Similarly, I’ve been late eight times in the morning, where five of it happened in the last week of my training.

The next plot below shows the number of hours I’ve spent in the morning (8:00 am – 12:00 pm).
The trend of the blue lines are not consistent, this is expected since I was not able to maintain my arrival time, As you’ve known earlier that I was late in most days. By the way, there’s no services during weekends, but as you notice on April 28 which is Saturday I’ve spent 4.2 hours, this was actually a general cleaning in the office, and so we the trainees were ordered to report on the said date to help on cleaning also, and in change for that is nonworking day in April 30, that’s Monday. But that didn’t happen to me, since I was given a special task by my boss, and was told to report on Monday morning, and that’s why I’ve spent 3.8 hours in that day. In the average, I’ve spent about 4 hours in the morning, black horizontal line in the plot represents it.

Here’s the plot of the hours I’ve spent in the afternoon of my training, that’s from 1:00 pm to 5:00 pm. And the blank in the plot is a missing value, this is because I only reported in the morning of the April 30.
And on the average, I spent about 3.7 hours in the afternoon of my training, as shown in the plot. Now the longest hours recorded in my entire training in the afternoon is 5 hours, this is because of the whole day general cleaning which happened on April 28. And the lowest number of hours I’ve spent happened on May 10, this is because I arrived at 2:00 pm in that day.

And for overall, the number of hours I’ve spent in a day is shown below. And on the average, I’ve spent about 7.4 hours a day.
There is a huge decline on April 30, that’s 3.8 hours only a day. Well, that’s because I only reported in the morning. Finally, the largest number of hours ever recorded on my training was on April 28, since it was a whole day cleaning.

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