Bitcoin Daily Trend Visualization (2024)

This notebook was inspired by a Stack Overflow question.

import pandas as pd

from lets_plot import *

LetsPlot.setup_html()

year = 2024
df = pd.read_csv("https://raw.githubusercontent.com/JetBrains/lets-plot-docs/refs/heads/master/data/Bitstamp_BTCUSD_d.csv", parse_dates=["date"])
df = df[df["date"].dt.year == year].sort_values(by="date").reset_index(drop=True)
df = df.assign(trend=(df["close"].diff().fillna(0) > 0).astype(int))
print(df.shape)
df.head()

(366, 10)

	unix	date	symbol	open	high	low	close	Volume BTC	Volume USD	trend
0	1704067200	2024-01-01	BTC/USD	42258.0	44192.0	42188.0	44187.0	1633.498618	7.217940e+07	0
1	1704153600	2024-01-02	BTC/USD	44187.0	45922.0	44167.0	44970.0	3948.659076	1.775712e+08	1
2	1704240000	2024-01-03	BTC/USD	44972.0	45510.0	41454.0	42865.0	3980.828056	1.706382e+08	0
3	1704326400	2024-01-04	BTC/USD	42863.0	44795.0	42656.0	44186.0	2918.119349	1.289400e+08	1
4	1704412800	2024-01-05	BTC/USD	44195.0	44366.0	42500.0	44184.0	3155.466383	1.394211e+08	0

ggplot(df) + \
    geom_line(aes("date", "close"), color="pen", size=1.2, tooltips='none') + \
    geom_line(aes("date", "close", color="trend"), size=.6,
              tooltips=layer_tooltips().title("^x").format("^x", "%A, %b %e")
                                       .line("Close price|^y")
                                       .anchor('top_left')
                                       .min_width(200)) + \
    scale_x_datetime(expand=[0]) + \
    scale_y_continuous(format="$.4~s") + \
    scale_color_manual(name="Trend", values={0: "red", 1: "green"},
                       labels=["Downtrend", "Uptrend"]) + \
    ylab("Close Price") + \
    ggtitle("Bitcoin Daily Close Price with Up/Down Trend Coloring ({0})".format(year)) + \
    ggsize(1000, 500) + \
    theme_light() + \
    flavor_darcula() + \
    theme(plot_title=element_text(size=18, face='bold'),
          legend_position='bottom',
          axis_title_x='blank') + \
    ggtb()