add support for stem plots
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- Python
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Description
Feature Request: Add support for stem plots
Description:
The stem plot is widely used in MATLAB/Octave/Python(matplotlib.pyplot.stem) to represent discrete data with markers and stems (vertical lines) connecting the data points to the x-axis. It is particularly useful for plotting sampled signals or data that has clear separation along the x-axis.
Currently, Plotly doesn't have a built-in function to replicate the stem plot, but users can manually create similar plots using go.Scatter and adding both lines and markers.
Proposal:
Introduce a native stem plot type that:
- Draws vertical lines from the x-axis to each data point.
- Places a marker on each data point.
- Allows customization of marker and line styles (similar to MATLAB).
Why it’s useful:
- It simplifies the creation of a common plot type in scientific and engineering fields.
- It would improve ease of use for users transitioning from MATLAB/Octave.
Examples:
Below is an example of how users can manually create a stem plot using Plotly’s go.Scatter, but it would be nice if this kind of function could be called as go.Scatter, by passing some parameter to transform in stem plot, or if we could call a function from plotly:
import plotly.graph_objects as go
# Counter for creating unique legend groups if not passed
legendgroup_cnt = 0
# Function to create a stem plot in Plotly
# x: data for the x-axis
# y: data for the y-axis (x and y must have the same number of elements)
# fig: if passed, plots on the given figure, otherwise creates a new one
# marker_symbol: allows changing the marker style (see options at https://plotly.com/python/marker-style/)
# color: the color of the marker and lines
# legendgroup: allows creating a group of legends with the same name
def stem_plot(x, y, fig=[], name='plot', color="blue", marker_symbol='circle-open', legendgroup=[]):
global legendgroup_cnt
# If fig is empty, create a new figure
if fig == []:
fig = go.Figure()
# If legendgroup is not provided, create a new legendgroup for each curve
if legendgroup == []:
legendgroup = legendgroup_cnt
legendgroup_cnt += 1
# Create a scatter trace for markers
scatter_trace = go.Scatter(
x=x, y=y, mode='markers',
marker_symbol=marker_symbol,
marker=dict(size=14, color=color),
name=name, legendgroup=legendgroup
)
fig.add_trace(scatter_trace)
# Create a line connecting markers to the x-axis
for xi, yi in zip(x, y):
line_trace = go.Scatter(
x=[xi, xi], y=[0, yi], mode='lines',
line=dict(color=scatter_trace.marker.color),
name=name, showlegend=False, legendgroup=legendgroup
)
fig.add_trace(line_trace)
return fig
# using the function
x = np.arange(0,10,1)
y = 2*x
fig = stem_plot(x, y, fig=[], name='mystem', color="blue", marker_symbol='circle-open', legendgroup=[])
fig.show()
Guide de contribution
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Par où commencer
- Lisez l'issue en entier, puis le guide de contribution du projet.
- Signalez en commentaire que vous la prenez — cela évite que deux personnes fassent le même travail.
- Forkez le dépôt et travaillez sur une branche.
- Ouvrez une pull request qui référence le numéro de l'issue.
Piste de recherche
Commencez par examiner le point d’entrée go.Scatter existant et la manière dont Plotly représente le style des marqueurs et des lignes. L’issue ne nomme aucun fichier du dépôt ni aucun test et laisse le choix de l’API ouvert ; le travail serait considéré comme terminé avec une interface native de stem plot qui trace les stems jusqu’à l’axe x, place des marqueurs et prend en charge la personnalisation des marqueurs et des lignes.
Rédigé par le modèle d'indexation à partir du texte de l'issue.
Évaluation
- Stack technique
- python
- Domaine
- data-visualization
- Type d'issue
- Fonctionnalité
- Difficulté
- 5/5
- Temps estimé
- Plus d'une semaine
- Activité
- À l'abandon
- Clarté
- À clarifier
- Accessibilité débutants
- 30/100