{"spec_id":"indicator-ema","library":"seaborn","language":"python","code":"\"\"\" anyplot.ai\nindicator-ema: Exponential Moving Average (EMA) Indicator Chart\nLibrary: seaborn 0.13.2 | Python 3.13.13\nQuality: 90/100 | Updated: 2026-05-19\n\"\"\"\n\nimport os\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nimport seaborn as sns\n\n\n# Theme tokens\nTHEME = os.getenv(\"ANYPLOT_THEME\", \"light\")\nPAGE_BG = \"#FAF8F1\" if THEME == \"light\" else \"#1A1A17\"\nELEVATED_BG = \"#FFFDF6\" if THEME == \"light\" else \"#242420\"\nINK = \"#1A1A17\" if THEME == \"light\" else \"#F0EFE8\"\nINK_SOFT = \"#4A4A44\" if THEME == \"light\" else \"#B8B7B0\"\n\n# Okabe-Ito palette — positions 1, 2, 3\nOKABE = [\"#009E73\", \"#C475FD\", \"#4467A3\"]\n\nsns.set_theme(\n    style=\"ticks\",\n    rc={\n        \"figure.facecolor\": PAGE_BG,\n        \"axes.facecolor\": PAGE_BG,\n        \"axes.edgecolor\": INK_SOFT,\n        \"axes.labelcolor\": INK,\n        \"text.color\": INK,\n        \"xtick.color\": INK_SOFT,\n        \"ytick.color\": INK_SOFT,\n        \"grid.color\": INK,\n        \"grid.alpha\": 0.10,\n        \"legend.facecolor\": ELEVATED_BG,\n        \"legend.edgecolor\": INK_SOFT,\n    },\n)\n\n# Data — $200 starting price with higher volatility to diverge from sibling impls\nnp.random.seed(42)\nn_days = 150\ndates = pd.date_range(start=\"2024-03-01\", periods=n_days, freq=\"B\")\nreturns = np.random.normal(0.001, 0.025, n_days)\nprice = 200 * np.cumprod(1 + returns)\n\nprice_series = pd.Series(price)\nema_12 = price_series.ewm(span=12, adjust=False).mean().values\nema_26 = price_series.ewm(span=26, adjust=False).mean().values\n\ndf = pd.DataFrame({\"date\": dates, \"Close Price\": price, \"EMA 12\": ema_12, \"EMA 26\": ema_26})\n\n# Crossover detection before melting\ncross_up = (df[\"EMA 12\"].shift(1) < df[\"EMA 26\"].shift(1)) & (df[\"EMA 12\"] > df[\"EMA 26\"])\ncross_down = (df[\"EMA 12\"].shift(1) > df[\"EMA 26\"].shift(1)) & (df[\"EMA 12\"] < df[\"EMA 26\"])\n\n# Long format for idiomatic seaborn hue grouping\ndf_long = df.melt(\n    id_vars=[\"date\"], value_vars=[\"Close Price\", \"EMA 12\", \"EMA 26\"], var_name=\"series\", value_name=\"price\"\n)\n\n# Plot\nfig, ax = plt.subplots(figsize=(16, 9), facecolor=PAGE_BG)\nax.set_facecolor(PAGE_BG)\n\npalette = {\"Close Price\": OKABE[0], \"EMA 12\": OKABE[1], \"EMA 26\": OKABE[2]}\n\nsns.lineplot(\n    data=df_long,\n    x=\"date\",\n    y=\"price\",\n    hue=\"series\",\n    hue_order=[\"Close Price\", \"EMA 12\", \"EMA 26\"],\n    palette=palette,\n    ax=ax,\n)\n\n# Set linewidths: price thicker, EMAs thinner\nfor line, lw in zip(ax.get_lines(), [3.5, 2.5, 2.5], strict=False):\n    line.set_linewidth(lw)\n\n# Crossover markers — green up triangle (bullish), vermillion down triangle (bearish)\nax.scatter(\n    df.loc[cross_up, \"date\"],\n    df.loc[cross_up, \"EMA 12\"],\n    color=OKABE[0],\n    s=250,\n    zorder=5,\n    marker=\"^\",\n    edgecolors=PAGE_BG,\n    linewidth=1.0,\n)\nax.scatter(\n    df.loc[cross_down, \"date\"],\n    df.loc[cross_down, \"EMA 12\"],\n    color=OKABE[1],\n    s=250,\n    zorder=5,\n    marker=\"v\",\n    edgecolors=PAGE_BG,\n    linewidth=1.0,\n)\n\n# Style\nax.set_title(\"indicator-ema · python · seaborn · anyplot.ai\", fontsize=24, fontweight=\"bold\", pad=20, color=INK)\nax.set_xlabel(\"Date\", fontsize=20, color=INK)\nax.set_ylabel(\"Price (USD)\", fontsize=20, color=INK)\nax.tick_params(axis=\"both\", labelsize=16, colors=INK_SOFT)\n\nfig.autofmt_xdate(rotation=30)\n\n# Legend — clean single entry per series from hue grouping\nlegend = ax.legend(fontsize=16, loc=\"upper left\")\nlegend.get_frame().set_facecolor(ELEVATED_BG)\nlegend.get_frame().set_edgecolor(INK_SOFT)\nfor text in legend.get_texts():\n    text.set_color(INK)\n\n# Grid — y-axis only, subtle\nax.yaxis.grid(True, alpha=0.10, linewidth=0.8)\nax.set_axisbelow(True)\nax.spines[\"top\"].set_visible(False)\nax.spines[\"right\"].set_visible(False)\nax.spines[\"left\"].set_color(INK_SOFT)\nax.spines[\"bottom\"].set_color(INK_SOFT)\n\nplt.tight_layout()\nplt.savefig(f\"plot-{THEME}.png\", dpi=300, bbox_inches=\"tight\", facecolor=PAGE_BG)\n"}