Labels & Annotations¶

Add titles, axis labels, and annotations to your plots.

In [1]:

import pandas as pd
import numpy as np
from ggplotly import *

# Sample data
np.random.seed(42)
df = pd.DataFrame({
    'x': np.random.randn(50),
    'y': np.random.randn(50),
    'category': np.random.choice(['A', 'B', 'C'], 50),
    'value': np.random.rand(50) * 10
})

import pandas as pd import numpy as np from ggplotly import * # Sample data np.random.seed(42) df = pd.DataFrame({ 'x': np.random.randn(50), 'y': np.random.randn(50), 'category': np.random.choice(['A', 'B', 'C'], 50), 'value': np.random.rand(50) * 10 })

labs()¶

The primary function for setting plot labels.

In [2]:

ggplot(df, aes(x='x', y='y', color='category')) + geom_point(size=8) + \
    labs(
        title='Main Title',
        subtitle='A subtitle with more detail',
        x='X Axis Label',
        y='Y Axis Label',
        color='Legend Title',
        caption='Data source: Sample data'
    )

ggplot(df, aes(x='x', y='y', color='category')) + geom_point(size=8) + \ labs( title='Main Title', subtitle='A subtitle with more detail', x='X Axis Label', y='Y Axis Label', color='Legend Title', caption='Data source: Sample data' )

Out[2]:

All labs() Parameters¶

Parameter	Description
title	Main plot title
subtitle	Subtitle below title
x	X-axis label
y	Y-axis label
z	Z-axis label (3D plots)
color	Color legend title
fill	Fill legend title
size	Size legend title
shape	Shape legend title
caption	Caption at bottom-right

ggtitle()¶

Quick way to set just the title.

In [3]:

ggplot(df, aes(x='x', y='y')) + geom_point() + ggtitle('My Plot')

ggplot(df, aes(x='x', y='y')) + geom_point() + ggtitle('My Plot')

Out[3]:

Annotations¶

Add text, shapes, and lines at specific positions.

Text Annotation¶

In [4]:

ggplot(df, aes(x='x', y='y')) + geom_point() + \
    annotate('text', x=0, y=2, label='Important point!')

ggplot(df, aes(x='x', y='y')) + geom_point() + \ annotate('text', x=0, y=2, label='Important point!')

Out[4]:

Rectangle Highlight¶

In [5]:

ggplot(df, aes(x='x', y='y')) + geom_point() + \
    annotate('rect', xmin=-1, xmax=1, ymin=-1, ymax=1, fill='yellow', alpha=0.3)

ggplot(df, aes(x='x', y='y')) + geom_point() + \ annotate('rect', xmin=-1, xmax=1, ymin=-1, ymax=1, fill='yellow', alpha=0.3)

Out[5]:

Line Segment¶

In [6]:

ggplot(df, aes(x='x', y='y')) + geom_point() + \
    annotate('segment', x=-2, y=-2, xend=2, yend=2, color='red')

ggplot(df, aes(x='x', y='y')) + geom_point() + \ annotate('segment', x=-2, y=-2, xend=2, yend=2, color='red')

Out[6]:

Reference Lines¶

In [7]:

ggplot(df, aes(x='x', y='y')) + geom_point() + \
    annotate('hline', y=0, color='red', linetype='dash') + \
    annotate('vline', x=0, color='blue', linetype='dot')

ggplot(df, aes(x='x', y='y')) + geom_point() + \ annotate('hline', y=0, color='red', linetype='dash') + \ annotate('vline', x=0, color='blue', linetype='dot')

Out[7]:

Annotation Parameters¶

Parameter	Description
x, y	Position coordinates
xend, yend	End coordinates (segments)
xmin, xmax, ymin, ymax	Rectangle bounds
label	Text content
color	Color
fill	Fill color
size	Size (text or point)
alpha	Transparency
hjust, vjust	Horizontal/vertical alignment

Controlling Legends¶

guides()¶

Control legend display for each aesthetic.

In [8]:

# Hide color legend
ggplot(df, aes(x='x', y='y', color='category')) + geom_point(size=8) + guides(color='none')

# Hide color legend ggplot(df, aes(x='x', y='y', color='category')) + geom_point(size=8) + guides(color='none')

Out[8]:

guide_legend()¶

Customize legend appearance.

In [9]:

ggplot(df, aes(x='x', y='y', color='category')) + geom_point(size=8) + \
    guides(color=guide_legend(title='Categories', ncol=2))

ggplot(df, aes(x='x', y='y', color='category')) + geom_point(size=8) + \ guides(color=guide_legend(title='Categories', ncol=2))

Out[9]:

guide_colorbar()¶

Customize continuous color bar.

In [10]:

ggplot(df, aes(x='x', y='y', color='value')) + geom_point(size=8) + \
    guides(color=guide_colorbar(title='Values', direction='horizontal'))

ggplot(df, aes(x='x', y='y', color='value')) + geom_point(size=8) + \ guides(color=guide_colorbar(title='Values', direction='horizontal'))

Out[10]:

Examples¶

Annotated Scatter Plot¶

In [11]:

# Find max point
max_idx = df['y'].idxmax()
max_x, max_y = df.loc[max_idx, 'x'], df.loc[max_idx, 'y']

(ggplot(df, aes(x='x', y='y', color='category'))
 + geom_point(size=8)
 + annotate('text', x=max_x, y=max_y + 0.3, label='Maximum')
 + annotate('rect', xmin=-1, xmax=1, ymin=-1, ymax=1, fill='gray', alpha=0.2)
 + labs(
     title='Scatter Plot with Annotations',
     subtitle='Highlighting a region of interest',
     x='X Variable',
     y='Y Variable',
     caption='Source: Sample Data'
 ))

# Find max point max_idx = df['y'].idxmax() max_x, max_y = df.loc[max_idx, 'x'], df.loc[max_idx, 'y'] (ggplot(df, aes(x='x', y='y', color='category')) + geom_point(size=8) + annotate('text', x=max_x, y=max_y + 0.3, label='Maximum') + annotate('rect', xmin=-1, xmax=1, ymin=-1, ymax=1, fill='gray', alpha=0.2) + labs( title='Scatter Plot with Annotations', subtitle='Highlighting a region of interest', x='X Variable', y='Y Variable', caption='Source: Sample Data' ))

Out[11]:

Clean Plot with Hidden Legend¶

In [12]:

(ggplot(df, aes(x='x', y='y', color='category'))
 + geom_point(size=8)
 + theme_minimal()
 + theme(legend_position='none')
 + labs(title='Clean Plot'))

(ggplot(df, aes(x='x', y='y', color='category')) + geom_point(size=8) + theme_minimal() + theme(legend_position='none') + labs(title='Clean Plot'))

Out[12]: