The coordinates of the points or line nodes are given by x, y.
The optional parameter fmt is a convenient way for defining basic formatting like color, marker and linestyle. It's a shortcut string notation described in the Notes section below.
You can use Line2D properties as keyword arguments for more control on the appearance. Line properties and fmt can be mixed. The following two calls 外匯交易教學 圖表 iq option yield identical results:
When conflicting with fmt, keyword arguments take precedence.
Plotting labelled data
There's 外匯交易教學 圖表 iq option a convenient way for plotting objects with labelled data (i.e. data that can be accessed by index obj['y'] ). Instead of giving the data in x and y, you can provide the object in the data parameter and just give the labels for x and y:
All indexable objects are supported. This could e.g. be a dict , a pandas.DataFrame or a structured numpy array.
Plotting multiple sets of data
There are various ways to plot multiple sets of data.
The most straight forward way is just to call plot multiple times. Example:
If x and/or y are 2D arrays a separate data set will be drawn for every column. If both x and y are 2D, they must have the same shape. If only one of them is 2D with shape (N, m) the other must have length N and will be used for every data set m.
is equivalent to:
The third way is to specify multiple sets 外匯交易教學 圖表 iq option of [x], y, [fmt] groups:
In this case, any additional keyword argument applies to all datasets. Also this syntax cannot be combined with the data parameter.
By default, each line is assigned a different style specified by a 'style cycle'. The fmt and line property parameters are only necessary if you want explicit deviations from these defaults. Alternatively, you can also change the style cycle using rcParams["axes.prop_cycle"] (default: cycler('color', ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf']) ).
Parameters x, y array-like or scalar
The horizontal / vertical coordinates of the data points. x values are optional and default to range(len(y)) .
Commonly, these parameters are 1D arrays.
They can also 外匯交易教學 圖表 iq option 外匯交易教學 圖表 iq option be scalars, or two-dimensional (in that case, the columns represent separate data sets).
These arguments cannot be passed as keywords.
fmt str, optional
A format string, e.g. 'ro' for red circles. See the Notes section for a full description of the format strings.
Format 外匯交易教學 圖表 iq option strings are just an abbreviation for quickly setting basic line properties. All of these and more can also be controlled by keyword arguments.
This argument cannot be passed as keyword.
data indexable object, optional
An object with labelled data. If given, provide the label names to plot in x and y.
Technically there's a slight ambiguity in calls where the second label is a valid fmt. plot('n', 'o', data=obj) could be plt(x, y) or plt(y, fmt) . In such cases, the former interpretation is chosen, but a warning is issued. You may suppress the warning by adding an empty format string 外匯交易教學 圖表 iq option plot('n', 'o', '', data=obj) .
A list of lines representing the plotted data.
Other Parameters scalex, scaley bool, default: True
These parameters determine if the view limits are adapted to the data limits. The values are passed on to autoscale_view .
**kwargs Line2D properties, optional
kwargs are used to specify properties like a line label (for auto legends), linewidth, antialiasing, marker face color. Example:
If you specify multiple lines with one plot call, the kwargs apply to all those lines. In case the label object is iterable, each element is used as labels for each set of data.
Here is a list of available Line2D properties:
a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array and two offsets from the bottom left corner of the image
外匯交易。 如何開始？ （01:01）
Matplotlib: Visualization with Python
Matplotlib 外匯交易教學 圖表 iq option 外匯交易教學 圖表 iq option is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible.
May 2, 2022
February 17, 2022
We are happy to post the 3-year Research Software Engineer position funded by the NASA ROSES-OSTFL 2020 grant. See the job description on discourse and submit an application via TypeForm.
December 11, 2021
September 15, 2021
September 9, 2021
Be sure to check the Users guide and the API docs. The full text search is a good way to discover the docs including the many examples.
Join our community at discourse.matplotlib.org to get help, share your work, and discuss contributing & development.
Check out the Matplotlib tag on StackOverflow.
Meet us at our monthly call for new contributors to the Matplotlib project. Subscribe to our community calendar at Scientific Python to get access to all our community meetings.
Short questions related to contributing to Matplotlib may be posted on the gitter channel.
Domain Specific Tools
A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, . ), and a projection and mapping toolkit (Cartopy).
seaborn is a high level interface for drawing statistical graphics with Matplotlib. It aims to make visualization a central part of exploring and understanding complex datasets.
Cartopy is a Python package designed for geospatial 外匯交易教學 圖表 iq option data processing in order to produce maps and other geospatial data analyses.
DNA Features Viewer
DNA Features Viewer is a Python library to visualize DNA features, e.g. from GenBank or Gff files, or Biopython SeqRecords.
plotnine is an implementation of a grammar of graphics in Python. The grammar allows users to compose plots by explicitly mapping data to the visual objects that make up the plot.
WCSAxes is a framework for making plots of Astronomical data in Matplotlib.
Matplotlib is a community project maintained for and by its users
You can help by answering questions on discourse, reporting a bug or requesting a feature on GitHub , or improving the documentation and code!
Matplotlib is the result of development efforts by John Hunter (1968–2012) and the project's many contributors.
If Matplotlib contributes to a project that leads to a scientific publication, please acknowledge this work by citing 外匯交易教學 圖表 iq option the project!
If you would like to support Matplotlib financially you can donate by sponsoring Matplotlib on GitHub or making a (USA) tax-deductible donation through NumFOCUS.
天生不是愛因斯坦沒關係，提升 IQ 是完全可行的
預約你的下一次加薪機會！實行向上管理的 3 個理由與 2 個絕招，讓老闆都聽你的
【全新一本】心想著東卻說出西，可能是大腦的 4 種人格在吵架！5 步驟教你召開「大腦會議」找回清晰思緒
Privacy 外匯交易教學 圖表 iq option Overview
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
|cookielawinfo-checkbox-analytics||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the 外匯交易教學 圖表 iq option user consent for the cookies in the category "Analytics".|
|cookielawinfo-checkbox-functional||11 months||The cookie is set 外匯交易教學 圖表 iq option by GDPR cookie consent to record the user consent for the cookies in the category "Functional".|
|cookielawinfo-checkbox-necessary||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".|
|cookielawinfo-checkbox-others||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.|
|cookielawinfo-checkbox-performance||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".|
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.
Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet.