An Exponential Moving Average (EMA) overlay chart displays price data with one or more EMA lines that give greater weight to recent prices, making them more responsive to new information than simple moving averages. The EMA calculation applies an exponential weighting factor that decreases with each older data point, allowing traders to identify trends faster. This technical indicator is fundamental in trading for spotting trend direction, dynamic support/resistance levels, and crossover signals.
""" anyplot.ai
indicator-ema: Exponential Moving Average (EMA) Indicator Chart
Library: pygal 3.1.0 | Python 3.13.13
Quality: 86/100 | Updated: 2026-05-19
"""
import os
import sys
# Prevent the local pygal.py from shadowing the installed pygal package
_here = os.path.dirname(os.path.abspath(__file__))
sys.path = [p for p in sys.path if os.path.abspath(p or ".") != _here]
import numpy as np
import pandas as pd
import pygal
from pygal.style import Style
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
IMPRINT = ("#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD", "#954477")
# Data
np.random.seed(42)
dates = pd.date_range(start="2024-01-02", periods=120, freq="B")
initial_price = 150.0
returns = np.random.normal(0.0008, 0.018, 120)
prices = initial_price * np.cumprod(1 + returns)
close = prices
ema_12 = pd.Series(close).ewm(span=12, adjust=False).mean().values
ema_26 = pd.Series(close).ewm(span=26, adjust=False).mean().values
# Detect EMA crossover points
crossover_vals = [None] * len(close)
for i in range(1, len(ema_12)):
prev_diff = ema_12[i - 1] - ema_26[i - 1]
curr_diff = ema_12[i] - ema_26[i]
if prev_diff * curr_diff < 0:
crossover_vals[i] = float(close[i])
# Style
custom_style = Style(
background=PAGE_BG,
plot_background=PAGE_BG,
foreground=INK,
foreground_strong=INK,
foreground_subtle=INK_MUTED,
colors=IMPRINT,
title_font_size=72,
label_font_size=48,
major_label_font_size=42,
legend_font_size=48,
value_font_size=36,
tooltip_font_size=36,
stroke_width=6,
opacity=0.9,
opacity_hover=1.0,
)
# Chart
chart = pygal.Line(
width=4800,
height=2700,
style=custom_style,
title="indicator-ema · python · pygal · anyplot.ai",
x_title="Date",
y_title="Price ($)",
show_dots=False,
show_x_guides=True,
show_y_guides=True,
stroke_style={"width": 6},
legend_at_bottom=True,
legend_at_bottom_columns=4,
x_label_rotation=45,
truncate_label=10,
show_minor_x_labels=False,
dots_size=10,
)
chart.x_labels = [d.strftime("%Y-%m-%d") for d in dates]
chart.x_labels_major = [dates[i].strftime("%Y-%m-%d") for i in range(0, len(dates), 20)]
chart.add("Close Price", close.tolist(), stroke_style={"width": 8})
chart.add("EMA 12-day", ema_12.tolist(), stroke_style={"width": 5, "dasharray": "10,5"})
chart.add("EMA 26-day", ema_26.tolist(), stroke_style={"width": 5, "dasharray": "5,5"})
chart.add("Crossovers", crossover_vals, show_dots=True, stroke=False)
# Save
chart.render_to_png(f"plot-{THEME}.png")
with open(f"plot-{THEME}.html", "wb") as f:
f.write(chart.render())
Part of Exponential Moving Average (EMA) Indicator Chart on anyplot.ai.