Word Cloud
Signature
sp.build_wordcloud(
title: str,
words: list[str],
weights: list[float],
*,
width: int = 900,
height: int = 480,
palette: list[int] | None = None,
background: str | None = None,
max_words: int = 200,
) -> Chart
Aliases: sp.wordcloud
Description
Word cloud (tag cloud) where font size reflects the weight of each word.
Words with higher weights are displayed larger. Layout is computed via a spiral placement algorithm.
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
title | str | required | Chart title |
words | list[str] | required | Word |
weights | list[float] | required | Weight per word (higher = larger) |
width | int | 900 | Canvas width |
height | int | 480 | Canvas height |
palette | list[int] | None | None | Custom color palette |
background | str | None | None | Background color |
max_words | int | 200 | Maximum number of words rendered |
Returns
Chart
Examples
Technology popularity
import seraplot as sp
from collections import Counter
text = "python python rust rust rust go go java javascript python data ml deep learning neural"
counts = Counter(text.split())
chart = sp.build_wordcloud(
"Tech Mentions",
words=list(counts.keys()),
frequencies=list(counts.values()),
palette=[0x6366f1, 0x22d3ee, 0xf43f5e, 0xf59e0b, 0x10b981],
)const sp = require('seraplot');
from collections import Counter
const text = "python python rust rust rust go go java javascript python data ml deep learning neural"
const counts = Counter(text.split())
const chart = sp.build_wordcloud("Tech Mentions",
list(counts.keys()),
{
frequencies: list(counts.values()),
palette: [0x6366f1, 0x22d3ee, 0xf43f5e, 0xf59e0b, 0x10b981]
})import * as sp from 'seraplot';
from collections import Counter
const text: string = "python python rust rust rust go go java javascript python data ml deep learning neural"
const counts = Counter(text.split())
const chart = sp.build_wordcloud("Tech Mentions",
list(counts.keys()),
{
frequencies: list(counts.values()),
palette: [0x6366f1, 0x22d3ee, 0xf43f5e, 0xf59e0b, 0x10b981]
})▶ Live Preview
See also
Signature
sp.build_wordcloud(
title: str,
words: list[str],
weights: list[float],
*,
width: int = 900,
height: int = 480,
palette: list[int] | None = None,
background: str | None = None,
max_words: int = 200,
) -> Chart
Aliases: sp.wordcloud
Description
Nuage de mots où la taille de la police reflète le poids de chaque mot. Les mots avec un weights plus élevé sont affichés en plus grand. La disposition est calculée via un algorithme de placement en spirale.
Paramètres
| Paramètre | Type | Défaut | Description |
|---|---|---|---|
title | str | requis | Titre du graphique |
words | list[str] | requis | Liste des mots |
weights | list[float] | requis | Poids par mot (plus élevé = plus grand) |
width | int | 900 | Largeur du canvas |
height | int | 480 | Hauteur du canvas |
palette | list[int] | None | None | Palette de couleurs |
background | str | None | None | Couleur de fond |
max_words | int | 200 | Nombre maximum de mots affichés |
Retourne
Chart
Exemples
Popularité des technologies
import seraplot as sp
from collections import Counter
texte = "python python rust rust rust go go java javascript python data ml deep learning neural"
counts = Counter(texte.split())
chart = sp.build_wordcloud(
"Mentions technologiques",
words=list(counts.keys()),
weights=list(counts.values()),
palette=[0x6366f1, 0x22d3ee, 0xf43f5e, 0xf59e0b, 0x10b981],
)