LaTeX Support

Note that LaTeX formulas are not fully supported when exporting to PNG/PDF.

import numpy as np
import pandas as pd

from lets_plot import *

LetsPlot.setup_html()

Power Degree

data1 = {'x': list(range(-10, 11))}
ggplot() + \
    geom_function(aes(x='x'), data=data1, fun=lambda x: x**3 - 100 * x) + \
    ggtitle("Graph of the \( y = x^3 - 100 x \)") + \
    theme(text=element_text(family="Times New Roman"), \
          plot_title=element_text(size=20, face='bold'))

Subscript

raw_df = pd.read_csv("https://raw.githubusercontent.com/JetBrains/lets-plot-docs/refs/heads/master/data/co-emissions-per-capita.csv")
raw_df.columns = ["country", "code", "year", "co2"]
df = raw_df[raw_df["country"].isin(["World", "United States", "United Kingdom", "China", "India"])]

ggplot(df, aes("year", "co2", color="country")) + \
    geom_line(tooltips=layer_tooltips().title("@year\nin tonnes per person").format("year", "d")
                                       .line("@country: @co2").format("@co2", "{.1f} t")) + \
    scale_x_continuous(name="", format="d") + \
    scale_y_continuous(name="", format="{d} t", expand=[0, 0]) + \
    labs("Per capita \( CO_2 \) emissions",
         "Carbon dioxide (\( CO_2 \)) emissions from fossil fuels and industry. "
         "Land-use change is not included.",
         "<a href=\"https://ourworldindata.org/explorers/co2?facet=none&hideControls=false&Gas+or+Warming=CO%E2%82%82&Accounting=Production-based&Fuel+or+Land+Use+Change=All+fossil+emissions&Count=Per+capita&country=CHN~USA~IND~GBR~OWID_WRL\">Original plot</a>") + \
    ggsize(1000, 400) + \
    theme(text=element_text(family="Playfair Display"), \
          plot_title=element_text(size=20, face='bold'))

Greek Letters and Other Special Symbols

ggplot() + \
    geom_text(x=0, label=r"\( e^{i \cdot \pi} = -1 \)", \
              size=70, family="Computer Modern Math", fontface='italic') + \
    theme_void()

Place Your Formulas Anywhere!

data2 = {
    "x": [r"\( \Omega_{\rho + 1} \)"],
    r"\(\delta\)": [1],
    "f": [r"\( A \neq B^2 \)"],
}

ggplot(data2) + \
    geom_bar(aes("x", r"\(\delta\)", fill="x"), stat='identity', \
             labels=layer_labels().line("@f"), \
             tooltips=layer_tooltips().line("@f")) + \
    scale_fill_manual(["#6a3d9a"], name=r"\(\Sigma\)") + \
    xlab(r"\(\sigma\)") + \
    theme(label_text=element_text(size=20))

Curly Braces Escaping

Let’s look at the following example:

def get_data(n, seed=42):
    np.random.seed(seed)
    return {
        "x": np.random.choice([
            r"\( x^a+1 \)",
            r"\( x^{a \cdot b}+1 \)",
            r"\( x^{a \cdot b^c}+1 \)",
            r"\( x^{a \cdot b^{c - d}}+1 \)",
        ], size=n, p=[.5, .25, .2, .05]),
    }

data3 = get_data(50)

ggplot(data3, aes(x=as_discrete("x", order_by='..count..'))) + geom_bar()

As in the other bars, the unit in the last bar must be at the same level as x. But it isn’t.

Let’s find out why this is so.
In this example, the formulas are passed to the plot as a list of strings in the dataset. The Lets-Plot concludes that the default formatting for strings, "{}" (an empty placeholder), should be applied to them. This formatting causes the } bracket to be escaped. Therefore, to get }}, we must use }}}} (see Formatting):

data3["x"] = [f.replace("}}", "}}}}") for f in data3["x"]] # this accounts for curly braces escaping

ggplot(data3, aes(x=as_discrete("x", order_by='..count..'))) + geom_bar()

Or, if that works for you, you can just disable the default string formatting:

ggplot(get_data(50), aes(x=as_discrete("x", order_by='..count..'))) + geom_bar() + \
    scale_x_discrete(format="") # this disables the default formatting of the x-axis ticks