ah, and it actually looks like the log10 is closer to the natural coordinate system of the data only just noticed.. thanks btw hmmm
My bad ... the units are different so can't plot them on the same graph in that way ... here's the updated code: ```python import matplotlib.pyplot as plt import numpy as np import pandas as pd import requests currency = "USD" response = requests.get( f"https://mempool.space/api/v1/historical-price?currency={currency}" ) data = response.json() df = pd.DataFrame(data["prices"]) df["time"] = pd.to_datetime(df["time"], unit="s") fig, ax1 = plt.subplots() ax2 = ax1.twinx() ax1.plot(df["time"], np.log2(df[currency]), color="Black", marker="o") ax2.plot(df["time"], np.log10(df[currency]), color="#FF9900") ax1.set_xlabel("Date") ax1.set_ylabel(f"Log Base 2 Historical {currency} Price", color="Black") ax2.set_ylabel(f"Log Base 10 Historical {currency} Price", color="#FF9900") plt.show() ``` and the corresponding figure (i.e. it's the same shape): https://m.primal.net/Krre.png
nostr:nprofile1qy88wumn8ghj7mn0wvhxcmmv9uq3zamnwvaz7tmwdaehgu3wwa5kuef0qyfhwumn8ghj7ur4wfcxcetsv9njuetn9uq3vamnwvaz7tm9v3jkutnwdaehgu3wd3skuep0qqsxzsz83jdwztcapd2qulzhspnyjvn6jxcypvrl0w3aahp40j4smfgchnfr5 you are right, it is the same maybe a higher exponent will flatten it further but it's not hard to see it's already getting quite flat now anyway, like, there is a trend that is decelerating by about the same amount each cycle, but it gets closer and closer to a normal y=x*coeff as time goes on... with that power ratio though, so, just to remember in the linear it's gonna be ... well somewhere between 150-300 this time, and probably 4x as much as that next time, assuming no hyperinflation, at which point the USD value means nothing anymore
Putting aside the math for a second, let’s talk about price. Price is entirely psychology. The price of something is what one is willing to exchange for it. The price of #Bitcoin is crossing an uncomfortable chasm. $60k is too large for most people to consider buying crazy internet money, but the price of a sat is too small to reason about. People are not good with decimals. Once we hit $1M per whole coin, a sat costs $0.01. A penny stock. At that price, we’ll stop pricing in tranches of 100M sats, like a one time 1:100,000,000 stock split. Overnight, Bitcoin will go from $1M, to $0.01, keeping the BTC ticker. At that moment, everyone’s interests are aligned—the hard money advocates and the degenerate gamblers alike. That’s when the real FOMO moon pump begins. So I don’t expect us to flatten into a pure exponential growth curve (line in log scale) just yet. Personally, I think that happens somewhere between cent/sat and dollar/sat parity.