Example 10: What have I been doing in the New Year?
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Not analyzing by individual activity items, but packaging the analysis in cycles, is the method I moved from the books.
For example, in the account book, in addition to the separate data such as "Chinese food", "dinner", "snacks", I will also record "travel", so that when I triggered the "travel", during the travel period, no matter what happened, all the expenses are recorded as "travel", so that I can analyze the total expenses incurred during the travel afterwards.
This thinking moves to timekeeping, where we can analyze "the consumption of all time items during the Chinese New Year" to determine and predict what I will do during the Chinese New Year.
When we record in TimeTrack, we can use the tag function to add a scene tag, such as "Chinese New Year", so that the exported data can be filtered separately from the data containing the Chinese New Year tag.
The main thing is that I have a habit of making plans before I go home for New Year's Day, making a list of what I'm going to do this year, and then reviewing it every year after New Year's Day, I find that out of 10 lists, only 2 have been completed, which is amazingly inefficient.
Then I went and analyzed all the activities during the New Year period (February) and compared the time of year (Little Year to the 7th day of the first year) separately, and I was able to find that my activities changed from year to year.
A percentage stacking histogram can also be added to observe the direction of activity flow, as shown in the figure.
The purpose of this is to control the distribution of activities in the whole block of time, and I will know when I make my New Year's to-do list next year, according to my calendar year data, it is impossible for me to have a lot of exercise time, so it is basically impossible to complete the "daily running" to-do list.
Once you have your own schedule of time slot activities, you can make more reasonable time predictions.
Similarly, we can backproject what was done in the time period to produce such a change based on the change in the activity item?
As an example, the length of my "reading" time so far in 2017 is shown in the figure.
Why is there an explosion in reading hours from January 2018 to March 2019?
Matching what I've done, I found it was because of two things: "moving + cabin loan".
Therefore, the conclusion can be inferred that the "moving" in addition to the price factor, there is also a reduction in commuting time, increased study time, plus the effect of the addition of these two, when making the "moving" decision, will not just stare at the money.
Finally, in addition to the new job can not afford the rent of students, I suggest to have the ability to rent a house close to the company can walk to and from work, not to mention how much time is saved, not only do not have to squeeze the bus and subway is too much happiness, and the city village rental, industrial electricity costs do not add up to be much cheaper than the city.
