Setup

import math
from matplotlib import cm
import matplotlib.pyplot as plt
import matplotlib.ticker as mt
import numpy as np
import pandas as pd

d = {'New': [0, 1/12],
     '1 m old': [0, 0],
     '2 m old': [0, 0],
     '3 m old': [0, 0],
     '4 m old': [0, 0],
     '5 m old': [0, 0],
     '6 m old': [0, 0],
     '7 m old': [0, 0],
     '8 m old': [0, 0],
     '9 m old': [0, 0],
     '10 m old': [0, 0],
     '11 m old': [0, 0],
     'Old': [1, 11/12],}

transmission = pd.DataFrame(d)

for m in range(2, 14):
    
    #New month, and 1/12 is new transmission.
    new_month = [1/12]
    
    #All last month data.
    last_month = transmission.iloc[-1]
    
    for o in range(1,12):
        #11/12 of the oil ages by 1 month.
        new_month.append(last_month[o-1]*11/12)
    
    #Old transmission is the 11th month old*11/12 of last month and all old oil minus 1/12th removed.
    old = (last_month[11] + last_month[12]) * 11/12
    new_month.append(old)
    
    #Update transmission dataframe
    transmission_new = pd.DataFrame([new_month], columns=list(transmission.columns))
    transmission = transmission.append(transmission_new, ignore_index=True)
    
transmission

	New	1 m old	2 m old	3 m old	4 m old	5 m old	6 m old	7 m old	8 m old	9 m old	10 m old	11 m old	Old
0	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000	1.000000
1	0.083333	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000	0.916667
2	0.083333	0.076389	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000	0.840278
3	0.083333	0.076389	0.070023	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000	0.770255
4	0.083333	0.076389	0.070023	0.064188	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000	0.706067
5	0.083333	0.076389	0.070023	0.064188	0.058839	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000	0.647228
6	0.083333	0.076389	0.070023	0.064188	0.058839	0.053936	0.000000	0.000000	0.000000	0.000000	0.000000	0.000	0.593292
7	0.083333	0.076389	0.070023	0.064188	0.058839	0.053936	0.049441	0.000000	0.000000	0.000000	0.000000	0.000	0.543851
8	0.083333	0.076389	0.070023	0.064188	0.058839	0.053936	0.049441	0.045321	0.000000	0.000000	0.000000	0.000	0.498530
9	0.083333	0.076389	0.070023	0.064188	0.058839	0.053936	0.049441	0.045321	0.041544	0.000000	0.000000	0.000	0.456986
10	0.083333	0.076389	0.070023	0.064188	0.058839	0.053936	0.049441	0.045321	0.041544	0.038082	0.000000	0.000	0.418904
11	0.083333	0.076389	0.070023	0.064188	0.058839	0.053936	0.049441	0.045321	0.041544	0.038082	0.034909	0.000	0.383995
12	0.083333	0.076389	0.070023	0.064188	0.058839	0.053936	0.049441	0.045321	0.041544	0.038082	0.034909	0.032	0.351996
13	0.083333	0.076389	0.070023	0.064188	0.058839	0.053936	0.049441	0.045321	0.041544	0.038082	0.034909	0.032	0.351996

fig = plt.figure()
fig.set_figheight(8)
fig.set_figwidth(13)
ax = fig.add_subplot(1,1,1)
ax.margins(x=0)

transmission.plot(ax = ax,
                  kind = "barh",
                  stacked = True,
                  cmap = 'viridis_r',
                  width = 0.95)

ax.set_title("Age Of Transmission Fluid Over Time", fontsize = 24)
ax.set_xlabel("Fraction of Transmission Fluid", fontsize = 20)
ax.xaxis.set_major_formatter(mt.PercentFormatter(1.0))
plt.xticks(fontsize = 16)
ax.set_ylabel("Month", fontsize = 20)
ax.invert_yaxis()
plt.yticks(fontsize = 16)

ax.legend(loc = 'center right',
          bbox_to_anchor = (1.08, 0.5),
          ncol = 1,
          fancybox = True,
          shadow = True);

fig.savefig("2022.01.28 Classic.png")

Rohan Lewis

2022.01.30