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Timothée Mazzucotelli
33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
# https://matplotlib.org/stable/gallery/lines_bars_and_markers/scatter_demo2.html
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from io import StringIO
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import matplotlib.cbook as cbook
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import matplotlib.pyplot as plt
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import numpy as np
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# Load a numpy record array from yahoo csv data with fields date, open, close,
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# volume, adj_close from the mpl-data/example directory. The record array
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# stores the date as an np.datetime64 with a day unit ('D') in the date column.
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price_data = cbook.get_sample_data("goog.npz")["price_data"]
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price_data = price_data[-250:] # get the most recent 250 trading days
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delta1 = np.diff(price_data["adj_close"]) / price_data["adj_close"][:-1]
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# Marker size in units of points^2
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volume = (15 * price_data["volume"][:-2] / price_data["volume"][0])**2
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close = 0.003 * price_data["close"][:-2] / 0.003 * price_data["open"][:-2]
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fig, ax = plt.subplots()
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ax.scatter(delta1[:-1], delta1[1:], c=close, s=volume, alpha=0.5)
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ax.set_xlabel(r"$\Delta_i$", fontsize=15)
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ax.set_ylabel(r"$\Delta_{i+1}$", fontsize=15)
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ax.set_title("Volume and percent change")
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ax.grid(True)
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fig.tight_layout()
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buffer = StringIO()
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plt.savefig(buffer, format="svg")
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print(buffer.getvalue())
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