Pandas Style#
Starting with itables>=1.6.0
, ITables provides support for
Pandas Style.
import pandas as pd
import numpy as np
from itables import init_notebook_mode
init_notebook_mode(all_interactive=True)
This is the DataFrame that we are going to style:
x = np.linspace(0, np.pi, 21)
df = pd.DataFrame({"sin": np.sin(x), "cos": np.cos(x)}, index=pd.Index(x, name="alpha"))
df
sin | cos | |
---|---|---|
alpha | ||
Loading... (need help?) |
Color#
From now on we will display df.style
(a Pandas Styler
object) rather than our DataFrame df
.
Let’s start with a background gradient:
s = df.style
s.background_gradient(axis=None, cmap="YlOrRd")
sin | cos | |
---|---|---|
alpha | ||
0.000000 | 0.000000 | 1.000000 |
0.157080 | 0.156434 | 0.987688 |
0.314159 | 0.309017 | 0.951057 |
0.471239 | 0.453990 | 0.891007 |
0.628319 | 0.587785 | 0.809017 |
0.785398 | 0.707107 | 0.707107 |
0.942478 | 0.809017 | 0.587785 |
1.099557 | 0.891007 | 0.453990 |
1.256637 | 0.951057 | 0.309017 |
1.413717 | 0.987688 | 0.156434 |
1.570796 | 1.000000 | 0.000000 |
1.727876 | 0.987688 | -0.156434 |
1.884956 | 0.951057 | -0.309017 |
2.042035 | 0.891007 | -0.453990 |
2.199115 | 0.809017 | -0.587785 |
2.356194 | 0.707107 | -0.707107 |
2.513274 | 0.587785 | -0.809017 |
2.670354 | 0.453990 | -0.891007 |
2.827433 | 0.309017 | -0.951057 |
2.984513 | 0.156434 | -0.987688 |
3.141593 | 0.000000 | -1.000000 |
Format#
We can also choose how the data is formatted:
s.format("{:.3f}").format_index("{:.3f}")
sin | cos | |
---|---|---|
alpha | ||
0.000 | 0.000 | 1.000 |
0.157 | 0.156 | 0.988 |
0.314 | 0.309 | 0.951 |
0.471 | 0.454 | 0.891 |
0.628 | 0.588 | 0.809 |
0.785 | 0.707 | 0.707 |
0.942 | 0.809 | 0.588 |
1.100 | 0.891 | 0.454 |
1.257 | 0.951 | 0.309 |
1.414 | 0.988 | 0.156 |
1.571 | 1.000 | 0.000 |
1.728 | 0.988 | -0.156 |
1.885 | 0.951 | -0.309 |
2.042 | 0.891 | -0.454 |
2.199 | 0.809 | -0.588 |
2.356 | 0.707 | -0.707 |
2.513 | 0.588 | -0.809 |
2.670 | 0.454 | -0.891 |
2.827 | 0.309 | -0.951 |
2.985 | 0.156 | -0.988 |
3.142 | 0.000 | -1.000 |
Caption#
s.set_caption("A Pandas Styler object with background colors").set_table_styles(
[{"selector": "caption", "props": "caption-side: bottom; font-size:1em;"}]
)
sin | cos | |
---|---|---|
alpha | ||
0.000 | 0.000 | 1.000 |
0.157 | 0.156 | 0.988 |
0.314 | 0.309 | 0.951 |
0.471 | 0.454 | 0.891 |
0.628 | 0.588 | 0.809 |
0.785 | 0.707 | 0.707 |
0.942 | 0.809 | 0.588 |
1.100 | 0.891 | 0.454 |
1.257 | 0.951 | 0.309 |
1.414 | 0.988 | 0.156 |
1.571 | 1.000 | 0.000 |
1.728 | 0.988 | -0.156 |
1.885 | 0.951 | -0.309 |
2.042 | 0.891 | -0.454 |
2.199 | 0.809 | -0.588 |
2.356 | 0.707 | -0.707 |
2.513 | 0.588 | -0.809 |
2.670 | 0.454 | -0.891 |
2.827 | 0.309 | -0.951 |
2.985 | 0.156 | -0.988 |
3.142 | 0.000 | -1.000 |
Tooltips#
ttips = pd.DataFrame(
{
"sin": ["The sinus of {:.6f} is {:.6f}".format(t, np.sin(t)) for t in x],
"cos": ["The cosinus of {:.6f} is {:.6f}".format(t, np.cos(t)) for t in x],
},
index=df.index,
)
s.set_tooltips(ttips).set_caption("With tooltips")
sin | cos | |
---|---|---|
alpha | ||
0.000 | 0.000 | 1.000 |
0.157 | 0.156 | 0.988 |
0.314 | 0.309 | 0.951 |
0.471 | 0.454 | 0.891 |
0.628 | 0.588 | 0.809 |
0.785 | 0.707 | 0.707 |
0.942 | 0.809 | 0.588 |
1.100 | 0.891 | 0.454 |
1.257 | 0.951 | 0.309 |
1.414 | 0.988 | 0.156 |
1.571 | 1.000 | 0.000 |
1.728 | 0.988 | -0.156 |
1.885 | 0.951 | -0.309 |
2.042 | 0.891 | -0.454 |
2.199 | 0.809 | -0.588 |
2.356 | 0.707 | -0.707 |
2.513 | 0.588 | -0.809 |
2.670 | 0.454 | -0.891 |
2.827 | 0.309 | -0.951 |
2.985 | 0.156 | -0.988 |
3.142 | 0.000 | -1.000 |
Note
Unlike Pandas or Polar DataFrames, Styler
objects are rendered directly using their
to_html
method, rather than passing the underlying table data to the datatables.net
library.
Because of this, the rendering of the table might differ slightly from the rendering of the corresponding DataFrame. In particular,
The downsampling is not available - please pay attention to the size of the table being rendered
Sorting of numbers will not work if the column contains NaNs.