Typical Usage¶

In [6]:

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

prices = sample_prices()

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 prices = sample_prices()

SVG charts in notebooks¶

By default notebooks display charts as PNG images. For sharper inline charts, switch the display format to SVG at the top of your notebook — as this notebook does:

In [7]:

from matplotlib_inline.backend_inline import set_matplotlib_formats

set_matplotlib_formats("svg")

from matplotlib_inline.backend_inline import set_matplotlib_formats set_matplotlib_formats("svg")

or equivalently with the IPython magic %config InlineBackend.figure_formats = {"svg"}. This is notebook display configuration (an IPython/matplotlib feature, not an mplchart one) — it has no effect on scripts or on exporting charts to files.

Plot chart with indicators¶

In [8]:

(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 and How expressions work tutorials.