glue

definition

add a key to variables in a notebook, then display those variables in your book by referencing the key.

glue function

• name: book(page) 상세서 사용되는 유니크 명칭(key)

• variable: jupyter notebook으로 생성된 객체(str, graph etc)

• display: true/false

from myst_nb import glue

help(glue)

Help on function glue in module myst_nb:

glue(name: str, variable, display: bool = True) -> None
    Glue a variable into the notebook's cell metadata.
    
    Parameters
    ----------
    name: string
        A unique name for the variable. You can use this name to refer to the variable
        later on.
    variable: Python object
        A variable in Python for which you'd like to store its display value. This is
        not quite the same as storing the object itself - the stored information is
        what is *displayed* when you print or show the object in a Jupyter Notebook.
    display: bool
        Display the object you are gluing. This is helpful in sanity-checking the
        state of the object at glue-time.

usecase

graph

1) drawing scatter graph

# Visualize seaborn scatter chart
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_theme(style="dark")

# Simulate data from a bivariate Gaussian
n = 10000
mean = [0, 0]
cov = [(2, .4), (.4, .2)]
rng = np.random.RandomState(0)
x, y = rng.multivariate_normal(mean, cov, n).T

# Draw a combo histogram and scatterplot with density contours
f, ax = plt.subplots(figsize=(4, 4))
sns.scatterplot(x=x, y=y, s=5, color=".15")
sns.histplot(x=x, y=y, bins=50, pthresh=.1, cmap="mako")
sns.kdeplot(x=x, y=y, levels=5, color="w", linewidths=1)

glue("scatter_graph", f, display=False)

2) display the graph

• binding the graph(f) in in-line text(markdown)

example

In-line text; a figure: {glue:}`scatter_graph`.

result

In-line text; a figure:

table

1) dataframe

import numpy as np
import pandas as pd
import seaborn as sns

df = sns.load_dataset("titanic")

df.style.set_table_attributes('style="font-size: 10px"')

glue('df_tbl', df.head())

	survived	pclass	sex	age	sibsp	parch	fare	embarked	class	who	adult_male	deck	embark_town	alive	alone
0	0	3	male	22.0	1	0	7.2500	S	Third	man	True	NaN	Southampton	no	False
1	1	1	female	38.0	1	0	71.2833	C	First	woman	False	C	Cherbourg	yes	False
2	1	3	female	26.0	0	0	7.9250	S	Third	woman	False	NaN	Southampton	yes	True
3	1	1	female	35.0	1	0	53.1000	S	First	woman	False	C	Southampton	yes	False
4	0	3	male	35.0	0	0	8.0500	S	Third	man	True	NaN	Southampton	no	True

2) display(binding) in the book

example

```{glue:figure} df_tbl
:figwidth: 100px
:name: 'tbl:df'

titanic dataset

result

	survived	pclass	sex	age	sibsp	parch	fare	embarked	class	who	adult_male	deck	embark_town	alive	alone
0	0	3	male	22.0	1	0	7.2500	S	Third	man	True	NaN	Southampton	no	False
1	1	1	female	38.0	1	0	71.2833	C	First	woman	False	C	Cherbourg	yes	False
2	1	3	female	26.0	0	0	7.9250	S	Third	woman	False	NaN	Southampton	yes	True
3	1	1	female	35.0	1	0	53.1000	S	First	woman	False	C	Southampton	yes	False
4	0	3	male	35.0	0	0	8.0500	S	Third	man	True	NaN	Southampton	no	True

Fig. 1 titanic dataset