An OHLC (Open-High-Low-Close) bar chart displays financial price data using vertical bars with horizontal tick marks. Each bar shows the price range from high to low as a thin vertical line, with a left tick indicating the opening price and a right tick indicating the closing price. Unlike candlestick charts that use colored bodies, OHLC bars provide a cleaner, less cluttered view favored by technical analysts who prefer to focus on price levels rather than visual patterns.
""" anyplot.ai
ohlc-bar: OHLC Bar Chart
Library: letsplot 4.9.0 | Python 3.13.13
Quality: 91/100 | Updated: 2026-05-17
"""
import os
import numpy as np
import pandas as pd
from lets_plot import (
LetsPlot,
aes,
element_line,
element_rect,
element_text,
geom_segment,
ggplot,
ggsave,
ggsize,
labs,
scale_color_manual,
scale_x_datetime,
theme,
theme_minimal,
)
LetsPlot.setup_html()
# Theme tokens
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
RULE = "rgba(26,26,23,0.10)" if THEME == "light" else "rgba(240,239,232,0.10)"
# Okabe-Ito palette for up/down
UP_COLOR = "#009E73" # Brand green (position 1)
DOWN_COLOR = "#AE3030" # imprint red — down bars
# Data: Generate 50 trading days of OHLC data
np.random.seed(42)
n_days = 50
dates = pd.date_range("2024-06-01", periods=n_days, freq="B")
# Simulate price movements with random walk
price = 150.0
opens, highs, lows, closes = [], [], [], []
for _ in range(n_days):
daily_return = np.random.normal(0, 0.02)
daily_volatility = np.random.uniform(0.01, 0.03)
open_price = price
close_price = price * (1 + daily_return)
high_price = max(open_price, close_price) * (1 + daily_volatility)
low_price = min(open_price, close_price) * (1 - daily_volatility)
opens.append(open_price)
highs.append(high_price)
lows.append(low_price)
closes.append(close_price)
price = close_price
df = pd.DataFrame({"date": dates, "open": opens, "high": highs, "low": lows, "close": closes})
# Add direction for coloring
df["direction"] = np.where(df["close"] >= df["open"], "up", "down")
# Calculate tick offsets (in milliseconds for datetime axis)
tick_offset = pd.Timedelta(hours=8)
df["date_left"] = df["date"] - tick_offset
df["date_right"] = df["date"] + tick_offset
# Build OHLC bar chart using segments
# 1. Vertical line from low to high
# 2. Left tick at open price
# 3. Right tick at close price
anyplot_theme = theme(
plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
panel_background=element_rect(fill=PAGE_BG),
panel_grid_major_y=element_line(color=RULE, size=0.3),
panel_grid_major_x=element_line(color=RULE, size=0.3),
axis_title=element_text(size=20, color=INK),
axis_text=element_text(size=16, color=INK_SOFT),
axis_line=element_line(color=INK_SOFT, size=0.5),
plot_title=element_text(size=24, color=INK),
legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT),
legend_text=element_text(size=16, color=INK_SOFT),
legend_title=element_text(size=18, color=INK),
)
plot = (
ggplot()
# High-Low vertical line
+ geom_segment(aes(x="date", y="low", xend="date", yend="high", color="direction"), data=df, size=1.2)
# Open tick (left)
+ geom_segment(aes(x="date_left", y="open", xend="date", yend="open", color="direction"), data=df, size=1.5)
# Close tick (right)
+ geom_segment(aes(x="date", y="close", xend="date_right", yend="close", color="direction"), data=df, size=1.5)
+ scale_color_manual(values={"up": UP_COLOR, "down": DOWN_COLOR}, name="Direction")
+ scale_x_datetime(format="%b %d")
+ labs(title="ohlc-bar · letsplot · anyplot.ai", x="Date", y="Price (USD)")
+ theme_minimal()
+ anyplot_theme
+ ggsize(1600, 900)
)
# Save as PNG (scale 3x for 4800 × 2700 px) and HTML
ggsave(plot, f"plot-{THEME}.png", path=".", scale=3)
ggsave(plot, f"plot-{THEME}.html", path=".")
Part of OHLC Bar Chart on anyplot.ai.