Nate Sterling

Balancing the Management of your Time and your Energy

I am going to explain the more nuanced concept of managing your energy, and how it fits into your personal time centric schedule.

Now, when managing your time and energy, the two concepts are tightly intertwined. To illustrate how, I am going to use a random week from the year:

##Using Python to randomize my month selection

import random
random.randrange(52)

47

Using 2019 as my year, here is my week…

From Date To Date
Sunday Nov. 17th, 2019 Saturday Nov. 24th, 2019

So what did this week look like…? For the best view of this viz, view in a desktop browser. Zoom in and zoom out on your phone or tablet.

This visualization was created using Power BI.

From the visualization I provided, you can see that while I have “free” time, I also have “busy” time. It’s important to not overburden oneself with too much work. What I have found helpful, is to think through the events I have planned for the day. The events could be activities, errands, and anything that is a pre-scheduled block of time. These blocks of time require different amounts of energy, and, as such, these blocks of time could either deplete or increase your energy levels.

A quick question to ask yourself when looking at an event with free time following it on your schedule is: Does this deplete my energy or increase my energy levels? Based on your answer to this question, you could 1. block out the “free” time so you don’t schedule anything over it, if there is an obvious need for energy levels to be recharged, and 2. if the event preceding the free time increased or did nothing to your energy levels, leave it as “free” so you can add to your schedule if something comes up.

I hope you found this helpful!

I followed the thread of inspiration for this post. It goes like this: a friend’s blog post<– @Haypsych <– Manage Your Energy Not Your Time by Tony Schwartz and Catherine McCarthy.

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Learning a Language? Export your Data from Duolingo.

Why learn a language? This is one avenue of life that I am constantly working on. If I had the ability to speak fluently in another language, life would be easier (emphasis on the would be). Whatever your reason for studying a language, you can keep track of your progress over time with Duolingo.

I want to show you how to export your own data from Duolingo and hopefully inspire you to do better than myself in your language learning practice. You will see what I mean… 😉

How to download your data from Duolingo?

First, you want to log into your account, then go to the “Settings.”

Next, you will want to find “Export my data,” and then click that.

There was a message that popped up stating that it could take up to 30 days for them to send my data, but the reality is, I got an email within an hour stating that the data was ready to be downloaded.

We did it!!! Now, let’s analyze the results! They should come in a csv file, so if you want to use Excel for analysis, that is an option, Tableau, R, Python, and Power BI, to name a few, are other viable options. I am going to use R. Here is a complete version of what I did: http://rpubs.com/natester/duolingoanalysis

Here is the summarized version of what I did….Looking at totals for 2019 and 2020, you will see I did better in 2019.

leaderboard_barchart <- ggplot(data=leaderboard_groupedby_year, aes(x=year, y=TOTAL_SCORE))

leaderboard_barchart + 
  geom_col(color= c('orangered','blue'),fill=c('orangered','blue'))+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_blank())+
  theme_void()+
  labs(title= "Total Score for 2019 (Orange) and 2020 (Blue)")+
  geom_text(aes(label = TOTAL_SCORE), 
            position = position_dodge(0.9),
            vjust = -0.5,
            size =5,
            color=c('orangered','blue'))

Visualizing the Data by Month

head(leaderboard)
##   leaderboard       date timestamp tier score year
## 1     leagues 2019-05-18  20:00:35    0    20 2019
## 2     leagues 2019-05-20  11:14:16    0    50 2019
## 3     leagues 2019-05-27  12:41:58    0    60 2019
## 4     leagues 2019-06-03  11:58:17    0    40 2019
## 5     leagues 2019-06-10  22:35:45    0    50 2019
## 6     leagues 2019-06-17  11:36:58    0    40 2019

leaderboard_linechart <- ggplot(data=leaderboard, aes(x=date, y=score))

leaderboard_linechart + 
  geom_line(color= c('cornflowerblue'),size =1)+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_blank())+
  labs(title= "Score Over Time for 2019 through 2020")

It looks like I reached my highest peak in my score at the beginning of 2020. What was that score?

sqldf("SELECT date, MAX(score) AS HIGHEST_SCORE
       FROM leaderboard 
       ")
##         date HIGHEST_SCORE
## 1 2020-01-27           109

109 was my highest score on ‘2020-01-27’, however, as we discovered. I showed a greater total score for 2019.

The take away from my charts are, overtime consistency matters more than one single learning sprint; especially, when it comes to learning languages.

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Failing in a New Role or Career Change

Many of us have failed… I will even go so far as to say that all mortal humans have failed. Maybe even the word “fail” sends shivers down your spine just from hearing the word. Or perhaps you remember the moment after you realized the consequences of your failure…?

Photo by **Nathan Cowley** from **Pexels**

Failing is NOT fun, however, failing can produce growth if we pay attention to the lesson(s) from the failure. When I switched from my background in English to a STEM field, I failed ALL the time. So how did I get back up on my feet after failing so many times? Well, it all started with a Google search…

Before jumping into learning a new field, I did what everyone else does when learning something new…I searched the web. I was trying to see if anyone else had made the switch from the BA side of the pool to the BS side. The first person I stumbled across was Barbara Oakley. She has a plethora of books to read and a course I took that was super helpful with learning techniques. Here is the link to that course on Coursera: http://www.coursera.org/learn/learning-how-to-learn. Why is Barbara Oakley a good source of motivation? Well, not only did she produce a boatload of content on the subject of how to excel in a STEM field and learning in general, but she also has been on this journey herself. She went from a “B.A. in Slavic Languages and Literature” to “B.S. in Electrical Engineering” (barabaraoakley.com/about-me). After reading her brief bio, I hope you feel as motivated to accomplish great things on your journey towards your new career as I did when I first dipped my toes in the new career waters myself.

Photo by **Kaique Rocha** from **Pexels**

Well, what if I am not smart enough? This is where the “grit” factor comes into play, and the specialist on the subject, Angela Duckworth. In her book The Power and Passion of Perseverance, Duckworth speaks on the power of grit and the secret to doing well in a subject. She gives personal anecdotal evidence as well as scientific evidence from studies she has performed herself as well as other reputable studies. She goes into much more depth than I could here (I listened to the Library audiobook which makes it harder to quote her awesome book ).

These two individuals should be more than enough to get you through any failures you experience. Remember that you can learn from past experiences and you are human, so mistakes and errors are bound to happen; what you do with those experiences is what matters the most.