Jupyter test with R kernel

Just wanted to see if I could do a post with Nikola using an R kernel with Jupyter.

This is the test code from: https://docs.anaconda.com/anaconda/navigator/tutorials/r-lang/

In [1]:
library(dplyr)
iris
Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Sepal.Length Sepal.Width Petal.Length Petal.Width Species
5.1 3.5 1.4 0.2 setosa
4.9 3.0 1.4 0.2 setosa
4.7 3.2 1.3 0.2 setosa
4.6 3.1 1.5 0.2 setosa
5.0 3.6 1.4 0.2 setosa
5.4 3.9 1.7 0.4 setosa
4.6 3.4 1.4 0.3 setosa
5.0 3.4 1.5 0.2 setosa
4.4 2.9 1.4 0.2 setosa
4.9 3.1 1.5 0.1 setosa
5.4 3.7 1.5 0.2 setosa
4.8 3.4 1.6 0.2 setosa
4.8 3.0 1.4 0.1 setosa
4.3 3.0 1.1 0.1 setosa
5.8 4.0 1.2 0.2 setosa
5.7 4.4 1.5 0.4 setosa
5.4 3.9 1.3 0.4 setosa
5.1 3.5 1.4 0.3 setosa
5.7 3.8 1.7 0.3 setosa
5.1 3.8 1.5 0.3 setosa
5.4 3.4 1.7 0.2 setosa
5.1 3.7 1.5 0.4 setosa
4.6 3.6 1.0 0.2 setosa
5.1 3.3 1.7 0.5 setosa
4.8 3.4 1.9 0.2 setosa
5.0 3.0 1.6 0.2 setosa
5.0 3.4 1.6 0.4 setosa
5.2 3.5 1.5 0.2 setosa
5.2 3.4 1.4 0.2 setosa
4.7 3.2 1.6 0.2 setosa
... ... ... ... ...
6.9 3.2 5.7 2.3 virginica
5.6 2.8 4.9 2.0 virginica
7.7 2.8 6.7 2.0 virginica
6.3 2.7 4.9 1.8 virginica
6.7 3.3 5.7 2.1 virginica
7.2 3.2 6.0 1.8 virginica
6.2 2.8 4.8 1.8 virginica
6.1 3.0 4.9 1.8 virginica
6.4 2.8 5.6 2.1 virginica
7.2 3.0 5.8 1.6 virginica
7.4 2.8 6.1 1.9 virginica
7.9 3.8 6.4 2.0 virginica
6.4 2.8 5.6 2.2 virginica
6.3 2.8 5.1 1.5 virginica
6.1 2.6 5.6 1.4 virginica
7.7 3.0 6.1 2.3 virginica
6.3 3.4 5.6 2.4 virginica
6.4 3.1 5.5 1.8 virginica
6.0 3.0 4.8 1.8 virginica
6.9 3.1 5.4 2.1 virginica
6.7 3.1 5.6 2.4 virginica
6.9 3.1 5.1 2.3 virginica
5.8 2.7 5.1 1.9 virginica
6.8 3.2 5.9 2.3 virginica
6.7 3.3 5.7 2.5 virginica
6.7 3.0 5.2 2.3 virginica
6.3 2.5 5.0 1.9 virginica
6.5 3.0 5.2 2.0 virginica
6.2 3.4 5.4 2.3 virginica
5.9 3.0 5.1 1.8 virginica
In [2]:
library(ggplot2)
ggplot(data=iris, aes(x=Sepal.Length, y=Sepal.Width, color=Species)) + geom_point(size=3)

November 2019 pull-up challange

Well, I failed my October 2019 Pullup Challange. Going to try again in November to get up to 10 pullups a day by the end of the month.

November schedule:

Date

# of Pullups

11/1/19

1

11/2/19

1

11/3/19

2

11/4/19

2

11/5/19

2

11/6/19

3

11/7/19

3

11/8/19

3

11/9/19

4

11/10/19

4

11/11/19

4

11/13/19

5

11/14/19

5

11/15/19

6

11/16/19

6

11/17/19

6

11/18/19

7

11/19/19

7

11/20/19

7

11/21/19

8

11/22/19

8

11/23/19

8

11/24/19

9

11/25/19

9

11/26/19

9

11/27/19

10

11/28/19

10

11/29/19

10

Weekly Weight Check In: November 11, 2019

last year at this time, I was in the low 180's. Holiday tradition of gaining weight it. This year I am going to fight the pounds. Plus, I want to be 15% body fat when I do the Sprint triationlon August 2020. My current goal is to be 15% body fat August 3, 2020 or 171 pounds.

On Myfitnesspal, I am trying out checkins on the community board to help me with my weight loss. I might as well put it on my blog.

Weight will be reported using: exponentially smoothed moving average with 10% smoothing. (Hacker's Diet)

Today: 200.3 Last Monday: 201.1 Delta: 0.8

267 days to go or 0.76 pounds per week.

Weight loss over time 200.3200.3200.4200.4200.5200.5200.6200.6200.7200.7200.8200.8200.9200.9201201201.1201.111/411/11Weight loss over time201.112.3658738206025049.74601359440788411/4200.3630.6595648507277497.0466933150607411/11Weight

Just a IPython test

Just testing a anaconda jupyter notebook using examples from

https://blog.quantinsti.com/stock-market-data-analysis-python/

I just want to see how well it works with my Nikola blog

In [1]:
import pandas_datareader
pandas_datareader.__version__
Out[1]:
'0.8.0'
In [2]:
import pandas as pd
from pandas_datareader import data
# Set the start and end date
start_date = '1990-01-01'
end_date = '2019-02-01'
# Set the ticker
ticker = 'AMZN'
# Get the data
data = data.get_data_yahoo(ticker, start_date, end_date)
data.head()
Out[2]:
High Low Open Close Volume Adj Close
Date
1997-05-15 2.500000 1.927083 2.437500 1.958333 72156000.0 1.958333
1997-05-16 1.979167 1.708333 1.968750 1.729167 14700000.0 1.729167
1997-05-19 1.770833 1.625000 1.760417 1.708333 6106800.0 1.708333
1997-05-20 1.750000 1.635417 1.729167 1.635417 5467200.0 1.635417
1997-05-21 1.645833 1.375000 1.635417 1.427083 18853200.0 1.427083
In [3]:
import matplotlib.pyplot as plt
%matplotlib inline
data['Adj Close'].plot()
plt.show()
In [4]:
# Plot the adjusted close price
data['Adj Close'].plot(figsize=(10, 7))
# Define the label for the title of the figure
plt.title("Adjusted Close Price of %s" % ticker, fontsize=16)
# Define the labels for x-axis and y-axis
plt.ylabel('Price', fontsize=14)
plt.xlabel('Year', fontsize=14)
# Plot the grid lines
plt.grid(which="major", color='k', linestyle='-.', linewidth=0.5)
# Show the plot
plt.show()
In [5]:
# Plot the adjusted close price
data['Adj Close'].plot(figsize=(10, 7))
# Define the label for the title of the figure
plt.title("Adjusted Close Price of %s" % ticker, fontsize=16)
# Define the labels for x-axis and y-axis
plt.ylabel('Price', fontsize=14)
plt.xlabel('Year', fontsize=14)
# Plot the grid lines
plt.grid(which="major", color='k', linestyle='-.', linewidth=0.5)
# Show the plot
plt.show()

Ride Santa Barbara 100, a climb too far

Well, I actually tried the RIDESB100 this weekend. There where four routes: 39 miles, 100 km, 100 km with Gibraltar, and the century. I did not finish the ride. At around 43 miles and two miles to the top of Gibraltar, my legs gave out. The last climb before the top was just a killer. The final climb before the top was too much. At two miles away from the top, I just did not want to do the last climb. Also, my bike decided that it would not go into the lowest gear.

What I learned:

  • Have my bike checked out before the ride.

  • Have two water bottles on the bike.

  • Have some hydration tablets to put in the water.

  • Have some sort of concentrated calories that is easy to fit in the jersey pocket.

https://www.instagram.com/p/B3z3ZvFBXep/https://www.instagram.com/p/B3zzhbnB12Q/?utm_source=ig_web_copy_link

Night before SB 100

I am going to ride in the Santa Barbara 100. Actually going for the 100 mile ride. Part of me feels like it is hubris on my side to try it as my first ride of this sort. The 100 km or 39 mile right would have been a better choice.

Well, no guts no glory.

October 2019 Pullup Challange

Goal is to get back up to 10 pullups a day. Most challanges start with one and increase by one every day. I am going to try to do it as every third day. Goal is to get to 10 pullups.

Current schedule:

Date

# of Pullups

1-Oct

1

2-Oct

1

3-Oct

2

4-Oct

2

5-Oct

2

6-Oct

3

7-Oct

3

8-Oct

3

9-Oct

4

10-Oct

4

11-Oct

4

12-Oct

5

13-Oct

5

14-Oct

5

15-Oct

6

16-Oct

6

17-Oct

6

18-Oct

7

19-Oct

7

20-Oct

7

21-Oct

8

22-Oct

8

23-Oct

8

24-Oct

9

25-Oct

9

26-Oct

9

27-Oct

10

28-Oct

10

29-Oct

10

30-Oct

11

31-Oct

11

Without Sin

I admit, I am far from being a good Christian. It is a standard that is hard to live by. One quote has been nagging me lately, the other has to go with it.

So when they continued asking him, he lifted up himself, and said unto them, He that is without sin among you, let him first cast a stone at her.

—John 8:7

What follows is:

...And Jesus said unto her, Neither do I condemn thee: go, and sin no more

—John 8:11

Forgiveness, atonement and redemtion is important for a gentle and truly inclusive world.