# https://matplotlib.org/stable/gallery/lines_bars_and_markers/scatter_demo2.html
from io import StringIO

import matplotlib.cbook as cbook
import matplotlib.pyplot as plt
import numpy as np

# Load a numpy record array from yahoo csv data with fields date, open, close,
# volume, adj_close from the mpl-data/example directory. The record array
# stores the date as an np.datetime64 with a day unit ('D') in the date column.
price_data = cbook.get_sample_data("goog.npz")["price_data"]
price_data = price_data[-250:]  # get the most recent 250 trading days

delta1 = np.diff(price_data["adj_close"]) / price_data["adj_close"][:-1]

# Marker size in units of points^2
volume = (15 * price_data["volume"][:-2] / price_data["volume"][0])**2
close = 0.003 * price_data["close"][:-2] / 0.003 * price_data["open"][:-2]

fig, ax = plt.subplots()
ax.scatter(delta1[:-1], delta1[1:], c=close, s=volume, alpha=0.5)

ax.set_xlabel(r"$\Delta_i$", fontsize=15)
ax.set_ylabel(r"$\Delta_{i+1}$", fontsize=15)
ax.set_title("Volume and percent change")

ax.grid(True)
fig.tight_layout()

buffer = StringIO()
plt.savefig(buffer, format="svg")
print(buffer.getvalue())