A Relative Strength Index (RSI) chart displaying the momentum oscillator on a 0-100 scale with horizontal threshold lines at 70 (overbought) and 30 (oversold). The RSI measures the speed and magnitude of recent price changes to evaluate overbought or oversold conditions. This is a fundamental momentum indicator in technical analysis, helping traders identify potential reversal points when the market reaches extreme conditions.

""" anyplot.ai
indicator-rsi: RSI Technical Indicator Chart
Library: altair 6.1.0 | Python 3.13.13
Quality: 88/100 | Updated: 2026-05-16
"""
import os
import sys
from importlib.machinery import SourceFileLoader
import numpy as np
import pandas as pd
venv_path = sys.executable
site_packages = os.path.join(os.path.dirname(venv_path), "..", "lib", "python3.13", "site-packages")
altair_init = os.path.join(site_packages, "altair", "__init__.py")
loader = SourceFileLoader("altair", altair_init)
alt = loader.load_module()
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"
np.random.seed(42)
n_periods = 140
dates = pd.date_range(start="2024-01-01", periods=n_periods, freq="D")
price_changes = np.random.randn(n_periods) * 4
lookback = 14
gains = np.zeros(n_periods)
losses = np.zeros(n_periods)
for i in range(1, n_periods):
change = price_changes[i]
if change > 0:
gains[i] = change
else:
losses[i] = abs(change)
avg_gain = np.zeros(n_periods)
avg_loss = np.zeros(n_periods)
avg_gain[lookback] = np.mean(gains[1 : lookback + 1])
avg_loss[lookback] = np.mean(losses[1 : lookback + 1])
for i in range(lookback + 1, n_periods):
avg_gain[i] = (avg_gain[i - 1] * (lookback - 1) + gains[i]) / lookback
avg_loss[i] = (avg_loss[i - 1] * (lookback - 1) + losses[i]) / lookback
with np.errstate(divide="ignore", invalid="ignore"):
rs = np.where(avg_loss != 0, avg_gain / avg_loss, 0)
rsi = np.where(avg_loss != 0, 100 - (100 / (1 + rs)), 100)
rsi[:lookback] = 50
df = pd.DataFrame({"date": dates, "rsi": rsi})
overbought_df = pd.DataFrame({"y": [70], "y2": [100]})
oversold_df = pd.DataFrame({"y": [0], "y2": [30]})
overbought_zone = (
alt.Chart(overbought_df)
.mark_rect(opacity=0.12, color="#E74C3C")
.encode(y=alt.Y("y:Q", scale=alt.Scale(domain=[0, 100])), y2=alt.Y2("y2:Q"))
)
oversold_zone = (
alt.Chart(oversold_df)
.mark_rect(opacity=0.12, color="#27AE60")
.encode(y=alt.Y("y:Q", scale=alt.Scale(domain=[0, 100])), y2=alt.Y2("y2:Q"))
)
threshold_df = pd.DataFrame({"y": [30, 50, 70], "label": ["Oversold (30)", "Neutral (50)", "Overbought (70)"]})
threshold_lines = (
alt.Chart(threshold_df)
.mark_rule(strokeDash=[8, 4], strokeWidth=2)
.encode(
y=alt.Y("y:Q", scale=alt.Scale(domain=[0, 100])),
color=alt.Color(
"label:N",
scale=alt.Scale(
domain=["Oversold (30)", "Neutral (50)", "Overbought (70)"], range=["#27AE60", INK_SOFT, "#E74C3C"]
),
legend=alt.Legend(
title="Thresholds",
orient="bottom-left",
titleFontSize=16,
labelFontSize=14,
fillColor=ELEVATED_BG,
strokeColor=INK_SOFT,
),
),
)
)
rsi_line = (
alt.Chart(df)
.mark_line(strokeWidth=3, color="#4467A3")
.encode(
x=alt.X("date:T", title="Date", axis=alt.Axis(format="%b %Y")),
y=alt.Y("rsi:Q", title="RSI Value", scale=alt.Scale(domain=[0, 100])),
tooltip=[
alt.Tooltip("date:T", title="Date", format="%Y-%m-%d"),
alt.Tooltip("rsi:Q", title="RSI", format=".1f"),
],
)
)
chart = (
alt.layer(overbought_zone, oversold_zone, threshold_lines, rsi_line)
.properties(
width=1600,
height=900,
title=alt.Title(
"indicator-rsi · altair · anyplot.ai",
fontSize=28,
anchor="middle",
subtitle="14-Period RSI with Overbought/Oversold Zones",
subtitleFontSize=18,
),
background=PAGE_BG,
)
.configure_axis(
labelFontSize=18,
titleFontSize=22,
gridOpacity=0.10,
domainColor=INK_SOFT,
tickColor=INK_SOFT,
gridColor=INK,
labelColor=INK_SOFT,
titleColor=INK,
)
.configure_title(color=INK)
.configure_legend(fillColor=ELEVATED_BG, strokeColor=INK_SOFT, labelColor=INK_SOFT, titleColor=INK)
.configure_view(strokeWidth=0, fill=PAGE_BG)
)
chart.save(f"plot-{THEME}.png", scale_factor=3.0)
chart.save(f"plot-{THEME}.html")
Part of RSI Technical Indicator Chart on anyplot.ai.