Author: MichaelJ

I was born naked, and unable to care for myself. But I struggled, and people helped me along the way.

Finally a new post.

My last post was just before March Madness was to start, an event that I had worked very hard to prepare for, in order that it might be successful.

There were many times during the year, when I wanted to post something new; there were many things that happened over the last 9 months. But I was kept afloat emotionally by the post, and as the weeks and months went by I actually got stronger, better, than I was. Praise God! Psalms 91 was a special blessing to me.

So to my future self, I list these to mediate on in 2021:

Psalms 18 Psalms 27 Psalms 33 Psalms 144

Ultimately, all battles are about your relationship with God not about winning your battles.

Prayers

Before and after any Work

BEFORE ANY WORK:

O Lord Jesus Christ, the only-begotten Son of the eternal Father, Thou hast said, “Without me you can do nothing.” In faith I embrace Thy words, O Lord, and bow before Thy goodness. Help me to complete the work I am about to begin for Thine own glory: in the Name of the Father, and of the Son, and of the Holy Spirit. Amen.

AFTER ANY WORK:

Thou, O Christ, art Thyself the fulfillment of all good things! Fill my soul with joy and gladness, and save me, for Thou art all merciful.

https://www.oca.org/orthodoxy/prayers/before-and-after-any-work

Python Stats

Great journey’s start with a single step. Here is a simple linear regression plot using python. Let’s see where this takes us.

import numpy as np
from numpy.polynomial.polynomial import polyfit
from scipy import stats
import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv(“tntot-stats.csv”)
x = np.array(df[‘Pre-Roll’].values)
y = np.array(df[‘Mid-Roll’].values)

slope, intercept, r_value, p_value, std_err = stats.linregress(x,y)

print (slope, intercept, r_value, p_value)

# Fit with polyfit
b, m = polyfit(x, y, 1)

# print (“poly: “+str(m))

plt.plot(x, y, ‘.’)
plt.plot(x, b + m * x, ‘-‘)

plt.title(“Otto: Python Regression: Do TNTOT Pre-Rolls predict Midrolls?”)
plt.xlabel(‘Prerolls’)
plt.ylabel(‘Midrolls’)
plt.text(10000, 1200000,’Slope: ‘+str(round(slope,3)), ha=’left’, va=’center’)
plt.text(10000, 1100000,’Intercept: ‘+str(round(intercept,3)), ha=’left’, va=’center’)
plt.text(10000, 1000000,’R-squared: ‘+str(round(r_value,3)), ha=’left’, va=’center’)
plt.text(10000, 900000,’P-value: ‘+str(round(p_value,3)), ha=’left’, va=’center’)
plt.text(50000,400000, ‘Nov 2019 MTD’)
plt.text(50000,300000, ‘NBA.com TNTOT Desktop’)

plt.annotate(‘>95%’, xy=(30000, 1000000), xycoords=’data’,
xytext=(0.6, 0.75), textcoords=’axes fraction’,
arrowprops=dict(facecolor=’red’, shrink=0.05),
horizontalalignment=’right’, verticalalignment=’top’,
)


# plt.show() Need tkinter to have interactive
plt.savefig(“mpgraph.png”)

# plt.hist(x)
# plt.ylabel(‘No of times’)
# plt.savefig(“mpgraph2.png”)

Michael J. Pierce