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Line plot — Matplotlib 3.11.2 documentation

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Lines, bars and markers
- Line plot
- Linestyles
- Dashed line style configuration
- Markevery Demo
- JoinStyle
- CapStyle
- Marker reference
- Infinite lines
- Multicolored lines
- Lines with a ticked patheffect
- Grouped bar chart with labels
- Bar chart with labels
- Stacked bar chart
- Bar chart with individual bar colors
- Hat graph
- Bar chart with gradients
- Horizontal bar chart
- Discrete distribution as horizontal bar chart
- Broken horizontal bars
- Scatter Demo2
- Mapping marker properties to multivariate data
- Marker examples
- Scatter plot with a legend
- Scatter plot with masked values
- Scatter plot with histograms
- Stairs Demo
- Step Demo
- Filled polygon
- fill_between with transparency
- Fill the area between two lines
- Fill the area between two vertical lines
- Stackplots and streamgraphs
- EventCollection Demo
- Eventplot demo
- Timeline with lines, dates, and text
- hlines and vlines
- Shade regions defined by a logical mask using fill_between
- Stem plot
- Plotting categorical variables
- Plotting masked and NaN values
- Spectrum representations
Images, contours and fields
- Many ways to plot images
- Image with masked values
- Multiple images with one colorbar
- Modifying the coordinate formatter
- Image resampling
- Interpolations for imshow
- Layer images with alpha blending
- Blend transparency with color in 2D images
- Shading example
- Clipping images with patches
- Placing images, preserving relative sizes
- pcolor images
- pcolormesh
- pcolormesh grids and shading
- Image nonuniform
- QuadMesh Demo
- Triplot Demo
- Tripcolor Demo
- Tricontour Demo
- Tricontour Smooth User
- Tricontour Smooth Delaunay
- Trigradient Demo
- Triinterp Demo
- Contour plot of irregularly spaced data
- Contour Demo
- Contour Label Demo
- Contourf demo
- Contour image
- Contourf and log color scale
- Contourf hatching
- Contour corner mask
- Contouring the solution space of optimizations
- Quiver Simple Demo
- Advanced quiver and quiverkey functions
- Wind barbs
- Streamplot
- Interactive adjustment of colormap range
- Colormap normalizations
- Colormap normalizations SymLogNorm
- Annotated heatmap
- Affine transform of an image
- Visualize matrices with matshow
- Spy Demos
- Spectrogram
- Barcode
- BboxImage Demo
- Figimage Demo
- Watermark image
Statistics
- Errorbar function
- Different ways of specifying error bars
- Errorbar subsampling
- Errorbar limit selection
- Including upper and lower limits in error bars
- Create boxes from error bars using PatchCollection
- Plot a confidence ellipse of a two-dimensional dataset
- Curve with error band
- Histograms
- Demo of the histogram function's different histtype settings
- Histogram bins, density, and weight
- The histogram (hist) function with multiple data sets
- Multiple histograms side by side
- Bihistogram
- Cumulative distributions
- Hexagonal binned plot
- Time Series Histogram
- Boxplots
- Artist customization in box plots
- Box plots with custom fill colors
- Separate calculation and plotting of boxplots
- Box plot vs. violin plot comparison
- Violin plot basics
- Violin plot customization
- Cross- and auto-correlation
- Power spectral density (PSD)
- Cross spectral density (CSD)
- Plotting the coherence of two signals
Pie and polar charts
- Pie charts
- Bar of pie
- Nested pie charts
- A pie and a donut with labels
- Labeling pie charts
- Bar chart on polar axis
- Polar plot
- Error bar rendering on polar axis
- Polar legend
- Scatter plot on polar axis
Subplots, axes and figures
- Multiple subplots
- Create multiple subplots using plt.subplots
- Axes Demo
- GridSpec with variable sizes and spacing
- Gridspec for multi-column/row subplot layouts
- Nested Gridspecs
- Combine two subplots using subplots and GridSpec
- subplot2grid
- Resize Axes with constrained layout
- Resize Axes with tight layout
- Subplots spacings and margins
- Programmatically control subplot adjustment
- Adjacent subplots
- Controlling view limits using margins and sticky_edges
- Axes box aspect
- Equal axis aspect ratio
- Manage multiple figures in pyplot
- Figure size in different units
- Figure subfigures
- Custom Figure subclasses
- Shared axis
- Inverted axis
- Plots with different scales
- Different scales on the same Axes
- Multiple y-axis with Spines
- Twin Axes with delta_zorder
- Secondary Axis
- Align labels and titles
- Axis label position
- Axes properties
- Figure labels: suptitle, supxlabel, supylabel
- Axes zoom effect
- Zoom region inset Axes
- Broken axis
- Geographic Projections
- Draw regions that span an Axes
Ticks
- Automatically setting tick positions
- Tick locators
- Major and minor ticks
- Align tick labels
- Move x/y-axis ticks and labels on top and right
- Center labels between ticks
- Rotated tick labels
- Multilevel (nested) ticks
- The default tick formatter
- Tick formatters
- Custom Ticker
- Dollar ticks
- Format ticks using engineering notation
- SI prefixed offsets and natural order of magnitudes
- Setting tick labels from a list of values
- Date tick labels
- Date tick locators and formatters
- Format date ticks using ConciseDateFormatter
- Date converter demo
- Placing date ticks using recurrence rules
- Custom tick formatter for time series
- Date precision and epochs
- Colorbar Tick labelling
- Customizing figure and axes appearance
- Fixing too many ticks
Scales
- Scales overview
- Asinh scale
- Loglog aspect
- Custom scale
- Log scale
- Logit scale
- Exploring normalizations
- Symlog scale
Spines
- Spines
- Spine placement
- Dropped spines
- Centered spines with arrows
Text, labels and annotations
- Text properties
- Controlling style of text and labels using a dictionary
- Text alignment
- Multiline text
- Auto-wrap text
- Text rotation mode
- Text rotation angle in data coordinates
- Concatenate text objects with different properties
- Using a text as a Path
- Annotating a plot
- Annotate plots
- Annotate polar plots
- Angle annotations on bracket arrows
- Annotation arrow style reference
- Styling text boxes
- Placing text boxes
- Labelling subplots
- Artists as annotations
- Arrow Demo
- Scale invariant angle label
- Legend Demo
- Legend using pre-defined labels
- Compose custom legends
- Figure legend demo
- Accented text
- The difference between \dfrac and \frac
- Configure the font family
- Using ttf font files
- Font table
- Fonts demo (object-oriented style)
- Fonts demo (keyword arguments)
- Convert texts to images
- Mathtext
- Mathematical expressions
- Math fontfamily
- STIX Fonts
- Render math equations using TeX
- Unicode minus
- Usetex text baseline
- Usetex font effects
- Artist within an artist
- Title positioning
- Text watermark
Shapes and collections
- Arrow guide
- Reference for Matplotlib artists
- Line, Poly and RegularPoly Collection
- Compound path
- Dolphins
- Mmh Donuts!!!
- Ellipse with orientation arrow demo
- Ellipse Collection
- Ellipse Demo
- Drawing fancy boxes
- Hatch demo
- Hatch style reference
- Hatchcolor Demo
- Plot multiple lines using a LineCollection
- Circles, Wedges and Polygons
- PathPatch object
- Bezier curve
- Scatter plot
Color
- Color Demo
- Color by y-value
- Colors in the default property cycle
- Named color sequences
- Colorbar
- Histogram as colorbar
- Colormap reference
- Create a colormap from a list of colors
- Selecting individual colors from a colormap
- List of named colors
- Ways to set a color's alpha value
Style sheets
- Bayesian Methods for Hackers style sheet
- Dark background style sheet
- FiveThirtyEight style sheet
- ggplot style sheet
- Grayscale style sheet
- Petroff style sheets
- Solarized Light stylesheet
- Style sheets reference
Module - pyplot
- Basic plot
- Two subplots using pyplot
3D plotting
- Plot 2D data on 3D plot
- Demo of 3D bar charts
- Clip the data to the axes view limits
- Create 2D bar graphs in different planes
- 3D box surface plot
- Plot contour (level) curves in 3D
- Plot contour (level) curves in 3D using the extend3d option
- Project contour profiles onto a graph
- Filled contours
- Project filled contour onto a graph
- Custom hillshading in a 3D surface plot
- 3D errorbars
- Fill between 3D lines
- Fill under 3D line graphs
- Create 3D histogram of 2D data
- 2D images in 3D
- Intersecting planes
- Parametric curve
- Lorenz attractor
- 2D and 3D Axes in same figure
- Automatic text offsetting
- Draw flat objects in 3D plot
- Generate 3D polygons
- 3D plot projection types
- 3D quiver plot
- Rotating a 3D plot
- Scales on 3D (Log, Symlog, etc.)
- 3D scatterplot
- 3D stem
- 3D plots as subplots
- 3D surface (colormap)
- 3D surface (solid color)
- 3D surface (checkerboard)
- 3D surface with polar coordinates
- Text annotations in 3D
- Triangular 3D contour plot
- Triangular 3D filled contour plot
- Triangular 3D surfaces
- More triangular 3D surfaces
- Primary 3D view planes
- 3D voxel / volumetric plot
- 3D voxel plot of the NumPy logo
- 3D voxel / volumetric plot with RGB colors
- 3D voxel / volumetric plot with cylindrical coordinates
- 3D wireframe plot
- Animate a 3D wireframe plot
- 3D wireframe plots in one direction
Module - axes_grid1
- Anchored Direction Arrow
- Axes divider
- Demo Axes Grid
- Axes Grid2
- HBoxDivider and VBoxDivider demo
- Show RGB channels using RGBAxes
- Colorbar with AxesDivider
- Control the position and size of a colorbar with inset_locator.inset_axes
- Per-row or per-column colorbars
- Axes with a fixed physical size
- ImageGrid cells with a fixed aspect ratio
- Inset locator demo
- Inset locator demo 2
- Make room for ylabel using axes_grid
- Parasite Simple
- Parasite Simple2
- Align histogram to scatter plot using locatable Axes
- Simple Anchored Artists
- Simple Axes Divider 1
- Simple axes divider 3
- Simple ImageGrid
- Simple ImageGrid 2
- Simple Axisline4
Module - axisartist
- Axis Direction
- axis_direction demo
- Axis line styles
- Curvilinear grid demo
- Demo CurveLinear Grid2
- floating_axes features
- floating_axis demo
- Parasite Axes demo
- Parasite axis demo
- Ticklabel alignment
- Ticklabel direction
- Simple axis direction
- Simple axis tick label and tick directions
- Simple axis pad
- Custom spines with axisartist
- Simple Axisline
- Simple Axisline3
Animation
- Basic animated line plot
- Decay
- Animated histogram
- pyplot animation
- The Bayes update
- The double pendulum problem
- Animated image using a precomputed list of images
- Frame grabbing
- Multiple Axes animation
- Pause and resume an animation
- Rain simulation
- Animated 3D random walk
- Animated scatter saved as GIF
- Oscilloscope
- Matplotlib unchained
Widgets
- Annotated cursor
- Buttons
- Check buttons
- Cursor
- Lasso Selector
- Menu
- Mouse Cursor
- Multicursor
- Select indices from a collection using polygon selector
- Polygon Selector
- Radio Buttons
- Radio Buttons Grid
- Image scaling using a RangeSlider
- Rectangle and ellipse selectors
- Slider
- Snap sliders to discrete values
- Span Selector
- Textbox
Event handling
- Close event
- Mouse move and click events
- Cross-hair cursor
- Data browser
- Figure/Axes enter and leave events
- Interactive functions
- Scroll event
- Keypress event
- Lasso Demo
- Legend picking
- Looking glass
- Path editor
- Pick event demo
- Pick event demo 2
- Polygon editor
- Pong
- Resampling Data
- Timers
- Trifinder Event Demo
- Viewlims
- Zoom modifies other Axes
Embedding Matplotlib in graphical user interfaces
- CanvasAgg demo
- Embed in GTK3 with a navigation toolbar
- Embed in GTK3
- Embed in GTK4 with a navigation toolbar
- Embed in GTK4
- Embed in Qt
- Embed in Tk
- Embed in wx #2
- Embed in wx #3
- Embed in wx #4
- Embed in wx #5
- Embedding WebAgg
- Fourier Demo WX
- GTK3 spreadsheet
- GTK4 spreadsheet
- Display mathtext in WX
- Matplotlib with Glade 3
- mplcvd -- an example of figure hook
- pyplot with GTK3
- pyplot with GTK4
- SVG Histogram
- SVG Tooltip
- Tool Manager
- Embed in a web application server (Flask)
- Add a cursor in WX
Units
- Annotation with units
- Artist tests
- Bar demo with units
- Group barchart with units
- Basic units
- Ellipse with units
- Evans test
- Radian ticks
- Inches and centimeters
- Unit handling
Miscellaneous
- Anchored Artists
- Identify whether artists intersect
- Manual Contour
- Coords Report
- Custom projection
- Customize Rc
- AGG filter
- Ribbon box
- Add lines directly to a figure
- Fill spiral
- Findobj Demo
- Font indexing
- Font properties
- Building histograms using Rectangles and PolyCollections
- Hyperlinks
- Plotting with keywords
- Matplotlib logo
- Multipage PDF
- Multiprocessing
- Packed-bubble chart
- Patheffect Demo
- Print image to stdout
- Rasterization for vector graphics
- Set and get properties
- Apply SVG filter to a line
- SVG filter pie
- Table Demo
- TickedStroke patheffect
- transforms.offset_copy
- Zorder Demo
Showcase
- Anatomy of a figure
- Firefox
- Integral as the area under a curve
- Shaded & power normalized rendering
- Pan/zoom events of overlapping axes
- Stock prices over 32 years
- XKCD
Specialty plots
- Hillshading
- Anscombe's quartet
- Hinton diagrams
- Ishikawa Diagram
- Left ventricle bullseye
- MRI with EEG
- Radar chart (aka spider or star chart)
- The Sankey class
- Long chain of connections using Sankey
- Rankine power cycle
- SkewT-logP diagram: using transforms and custom projections
- Topographic hillshading

Note

Go to the end to download the full example code.

Line plot#

Create a basic line plot.

import matplotlib.pyplot as plt
import numpy as np

# Data for plotting
t = np.arange(0.0, 2.0, 0.01)
s = 1 + np.sin(2 * np.pi * t)

fig, ax = plt.subplots()
ax.plot(t, s)

ax.set(xlabel='time (s)', ylabel='voltage (mV)',
       title='About as simple as it gets, folks')
ax.grid()

fig.savefig("test.png")
plt.show()

About as simple as it gets, folks

[About as simple as it gets, folks]

References

The use of the following functions, methods, classes and modules is shown in this example:

Tags: plot-type: line level: beginner

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