Looking for a gift for the graduate in your life? Dr. Seuss’s Oh, the Places You’ll Go could be just the ticket. The book is a fantastic pep talk for those preparing to make their marks on the world.
Want to take this gift to the next level? If you’re hosting or participating in a graduation party for your graduate, have all the party attendees sign the book and write an encouraging note or memory in it.
Want to take this gift to the supreme level? Plan ahead: I’m talking months and even years. Every year your child or loved one is in school, make arrangements to have his favorite teachers write notes in the book–on whatever page they choose–and ask that they date their notes, as well. And don’t restrict yourself to just teachers, either: anyone who’s had a positive influence on your child should be included.
If you start this work early enough, you’ll have an amazing and heart-felt gift for your loved one at their graduation, especially if it’s many years away.
I switched to ebooks several years ago, finding it quite convenient to pack my ebook reader with hundreds of tomes that I tote around with me to school parking lots while I wait for my kids to finish their practices, haircut establishments while I await my turn, the DMV while I wait…forever, etc. Nevertheless, I still have a backlog of physical books spread throughout the house and occasionally pick one up to read in-between electronic ones.
One of these I read recently was James Rollins’s The Last Odyssey. The Last Odyssey is a fast-paced, modern day adventure that pits a secret, U.S. government special operations team against the stereotypical bad people bent on sending humanity into the dark ages.
The thread that most endeared me to the novel was the interweaving of historical texts and mysteries–especially Homer’s The Odyssey–into the fabric of the story. I find it reminiscent of Umberto Eco’s Foucault’s Pendulum or Dan Brown’s Da Vinci Code. Or maybe National Treasure, if you’re not the reading type. The villians and protagonists are out to retrace Odysseus’s 10 year trek home, which turns out to be more true than myth (thanks to much literary license). What awaits at the end of the trek could spell doom for the masses in the hands of the wrong people.
If you’re like me, you’ll want to read the author’s notes at the end where he enumerates all the books and events from which he drew inspiration. I’ve already added several of these to my watchlist.
So, if you need a break from your daily grind, The Last Odyssey will entertain you without overly taxing your exhausted prefrontal cortex.
I’ve alluded to my interest in reading a fewtimesin the past. Several years ago, I made the switch from physical books to digital and use an Amazon Kindle as my main reading vehicle.
One frustration I have with the Kindle, though, is either its inability to track the reading time metrics I’m interested in collecting or its poor way of sharing those metrics with data nerds like me.
Earlier in the year, I decided to spend more than five minutes solving this problem and found out about Kindle FreeTime. Kindle FreeTime is an application on Kindle devices with the primary focus of getting kids to read. Parents can use FreeTime to decide what books their children can read and what minimum daily reading goals they want their children to meet. A side benefit of FreeTime, though, is that it captures a lot of the metrics I’m interested in in a SQLite database: all you have to do is plug your kindle into your workstation, download the database at system\freetime\freetime.db, and start exploring.
Dayinfo
One of the tables in the FreeTime database is dayinfo. This is probably a good place to start gathering some general reading metrics. Here’s how I went about digging into the data.
Load all the standard packages
In my notebook, I started by loading all the normal packages I use including the sqlite3 package:
import pandas as pd
import numpy as np
import sqlite3
from datetime import datetime
import matplotlib.pyplot as plt
%matplotlib inline
Load and clean the data from the table
Next, I queried the data from the dayinfo table and added a few helpful columns:
conn = sqlite3.connect('./data/freetime.db')
query = "SELECT * FROM dayinfo;"
df_dayinfo = pd.read_sql_query(query,conn)
# clean up fields and do some feature engineering
df_dayinfo['accessdate'] = pd.to_datetime(df_dayinfo.accessdate)
df_dayinfo['access_month'] = df_dayinfo.accessdate.dt.month
df_dayinfo['access_dow'] = df_dayinfo.accessdate.dt.dayofweek
df_dayinfo['read_mins'] = df_dayinfo.timeread / 60
df_dayinfo['read_hours'] = df_dayinfo.timeread / 3600
Calculate some preliminary metrics
Finally, I wanted to calculate my total reading time for the year 2019 and my average daily reading time. I only started using FreeTime in March 2019, so I had to pro-rate some of my calculations. Here’s what I came up with:
df_dayinfo_2019 = df_dayinfo[(df_dayinfo.accessdate > datetime(2019, 1, 1)) & (df_dayinfo.accessdate < datetime(2020, 1, 1))]
days_in_2019 = (df_dayinfo_2019.accessdate.max() - df_dayinfo_2019.accessdate.min()).days
print('From {0:%d %b %Y} to {1:%d %b %Y} ({2} days):'.format(df_dayinfo_2019.accessdate.min(),
df_dayinfo_2019.accessdate.max(), days_in_2019))
print('I read {0:.2f} hours'.format(df_dayinfo_2019.read_hours.sum()))
print("That's an average of {0:.2f} minutes per day".format((df_dayinfo_2019.read_mins.sum())/days_in_2019))
From 10 Mar 2019 to 29 Dec 2019 (294 days):
I read 111.18 hours
That's an average of 22.69 minutes per day
Bah! Only 22 minutes reading time per day on average?! Well, I know one goal I’ll need to work on for 2020. Lets see what this data looks like in some charts:
My monthly reading totals starting in March: May was a good month
fig, ax = plt.subplots(figsize=(10, 8))
df_dayinfo_2019[['access_dow', 'read_hours']].sort_values('access_dow').groupby('access_dow').sum().plot.bar(ax=ax)
_ = ax.set_title('Hours Read by Day of Week: {0:%d %b %Y} to {1:%d %b %Y}'.format(df_dayinfo_2019.accessdate.min(),
df_dayinfo_2019.accessdate.max()))
_ = ax.set_xlabel('Day of Week')
_ = ax.set_ylabel('Hours')
_ = ax.set_xticklabels(['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'])
I read the most on Wednesdays. That makes sense because most of my Wednesday evenings in Spring are sitting in the parking lot outside a bandroom while my kid practices with his middle school orchestra. I get a lot of reading time in on those days.
There are other tables in the database including details on each of the books that I’ve read over the year. Hopefully, at some point, I’ll dig in to those details, as well. But for now, this data is sufficient to get me motivated to read more in 2020.
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