Typical Usage¶

In [1]:

from mplchart.chart import Chart
from mplchart.samples import sample_prices
from mplchart.primitives import Candlesticks, Volume, Pane, LinePlot
from mplchart.indicators import SMA, RSI, MACD

from mplchart.chart import Chart from mplchart.samples import sample_prices from mplchart.primitives import Candlesticks, Volume, Pane, LinePlot from mplchart.indicators import SMA, RSI, MACD

In [2]:

prices = sample_prices()
prices

prices = sample_prices() prices

Out[2]:

	open	high	low	close	volume
date
1980-12-12	0.098389	0.098817	0.098389	0.098389	469033600
1980-12-15	0.093684	0.093684	0.093256	0.093256	175884800
1980-12-16	0.086839	0.086839	0.086412	0.086412	105728000
1980-12-17	0.088550	0.088978	0.088550	0.088550	86441600
1980-12-18	0.091118	0.091545	0.091118	0.091118	73449600
...	...	...	...	...	...
2025-11-11	269.809998	275.910004	269.799988	275.250000	46208300
2025-11-12	275.000000	275.730011	271.700012	273.470001	48398000
2025-11-13	274.109985	276.700012	272.089996	272.950012	49602800
2025-11-14	271.049988	275.959991	269.600006	272.410004	47399300
2025-11-17	268.815002	270.489990	265.730011	267.459991	42862157

11325 rows × 5 columns

In [3]:

(Chart(prices, title="Example Chart", max_bars=250)
    .plot(
        Candlesticks(), Volume(), SMA(50), SMA(200),
        Pane("above", yticks=(30, 50, 70)),
        LinePlot(RSI(), overbought=70, oversold=30),
        Pane("below"),
        MACD(),
    )
    .show()
)

(Chart(prices, title="Example Chart", max_bars=250) .plot( Candlesticks(), Volume(), SMA(50), SMA(200), Pane("above", yticks=(30, 50, 70)), LinePlot(RSI(), overbought=70, oversold=30), Pane("below"), MACD(), ) .show() )

What about polars?¶

This walkthrough uses pandas data, but mplchart works the same with polars DataFrames — the charting layer is identical, with polars expressions taking the place of indicators. See the Pandas and Polars Backends reference page and the How Expressions Work tutorial.