pythonmatplot.pyplot.plot（）的⽤法plt.plot（）（绘制y相。。。⽂章⽬录
doc
from matplotlib.pyplot.py
# Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
@py(Axes.plot)
def plot(*args, scalex=True, scaley=True, data=None,**kwargs):
return gca().plot(
*args, scalex=scalex, scaley=scaley,**({"data": data}if data
is not None else{}),**kwargs)
from matplotlib.axes._axes.py
# Uses a custom implementation of data-kwarg handling in
# _process_plot_var_args.
在＃_process_plot_var_args中使⽤⾃定义的数据扭曲处理实现。
@docstring.dedent_interpd
def plot(self,*args, scalex=True, scaley=True, data=None,**kwargs):
"""
Plot y versus x as lines and/or markers.
绘制y相对于x的线条和/或标记。
Call signatures:: 调⽤签名
plot([x], y, [fmt], *, data=None, **kwargs)
plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)
The coordinates of the points or line nodes are given by *x*, *y*.
点或线节点的坐标由* x *，* y *给出。
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.
可选参数* fmt *是定义基本格式（如颜⾊，标记和线条样式）的便捷⽅法。
这是下⾯* Notes *部分中描述的快捷⽅式字符串符号。
>>> plot(x, y)        # plot x and y using default line style and color
使⽤默认线条样式和颜⾊绘制x和y
>>> plot(x, y, 'bo')  # plot x and y using blue circle markers
使⽤蓝⾊圆圈标记绘制x和y
>>> plot(y)          # plot y using x as index array 0..N-1
使⽤x作为索引数组0..N-1绘制y
>>> plot(y, 'r+')    # ditto, but with red plusses
同上，但带有红⾊加号
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 yield identical results:
您可以将.Line2D属性⽤作关键字参数，以更好地控制外观。
线属性和* fmt *可以混合使⽤。以下两个调⽤产⽣相同的结果：
>>> plot(x, y, 'go--', linewidth=2, markersize=12)
>>> plot(x, y, color='green', marker='o', linestyle='dashed',
...      linewidth=2, markersize=12)
When conflicting with *fmt*, keyword arguments take precedence.
与* fmt *冲突时，关键字参数优先。
**Plotting labelled data 绘制标签数据**
There's 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*
the data in *x* and *y*, you can provide the object in the *data*
parameter and just give the labels for *x* and *y*::
有⼀种⽅便的⽅法可以绘制带有标签数据的对象（即可以通过索引``obj ['y']''访问的数据）。
您可以在* data *参数中提供对象，⽽不必为* x *和* y *提供数据，⽽只需为* x *和* y *提供标签：        >>> plot('xlabel', 'ylabel', data=obj)
All indexable objects are supported. This be a `dict`, a
`pandas.DataFame` or a structured numpy array.
⽀持所有可索引对象。例如是dict，pandas.DataFrame或结构化numpy数组。
**Plotting multiple sets of data 绘制多组数据**
There are various ways to plot multiple sets of data.
有多种⽅法可以绘制多组数据。
- The most straight forward way is just to call `plot` multiple times.
- 最直接的⽅法是多次调⽤“ plot”。
Example:
>>> plot(x1, y1, 'bo')
>>> plot(x2, y2, 'go')
⽰例：
import numpy as np
import matplotlib.pyplot as plt
x1=np.array([1,2,3])
y1=np.array([1,2,3])
x2=np.array([1,2,3])
y2=np.array([5,6,7])
plt.plot(x1, y1, 'bo')
plt.plot(x2, y2, 'go')
- Alternatively, if your data is already a 2d array, you can pass it
directly to *x*, *y*. A separate data set will be drawn for every
column.
或者，如果您的数据已经是2d数组，则可以将其直接传递给* x *，* y *。
将为每⼀列绘制⼀个单独的数据集。
Example: an array ``a`` where the first column represents the *x*
values and the other columns are the *y* columns::
⽰例：数组“ a”，其中第⼀列表⽰* x *值，其他列为* y *列：：
>>> plot(a[0], a[1:])
- The third way is to specify multiple sets of *[x]*, *y*, *[fmt]*
groups::
第三种⽅法是指定多组* [x] *，* y *，* [fmt] *组：
>>> plot(x1, y1, 'g^', x2, y2, 'g-')
In this case, any additional keyword argument applies to all
datasets. Also this syntax cannot be combined with the *data*
parameter.
在这种情况下，任何其他关键字参数都适⽤于所有数据集。
同样，此语法不能与* data *参数结合使⽤。
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 the
'axes.prop_cycle' rcParam.
默认情况下，为每⾏分配⼀个由“样式循环”指定的不同样式。
* fmt *和line属性参数仅在您希望与这些默认值明显不同时才需要。
* 另外，您也可以使⽤'axes.prop_cycle'rcParam更改样式周期。
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))`.
数据点的⽔平/垂直坐标。 * x *值是可选的，默认为`range（len（y））`。
Commonly, these parameters are 1D arrays.
通常，这些参数是⼀维数组。
They can also be scalars, or two-dimensional (in that case, the
columns represent separate data sets).
columns represent separate data sets).
它们也可以是标量，也可以是⼆维的（在这种情况下，
列代表单独的数据集）。
These arguments cannot be passed as keywords.
这些参数不能作为关键字传递。
fmt : str, optional
A format string, e.g. 'ro' for red circles. See the *Notes*
section for a full description of the format strings.
格式字符串，例如红⾊圆圈为“ ro”。
有关格式字符串的完整说明，请参见* Notes *部分。
Format strings are just an abbreviation for quickly setting
basic line properties. All of these and more can also be
controlled by keyword arguments.
格式字符串只是⽤于快速设置基本⾏属性的缩写。
所有这些以及更多这些都可以通过关键字参数来控制。
This argument cannot be passed as keyword.
此参数不能作为关键字传递。
data : indexable object, optional
An object with labelled data. If given, provide the label names to
plot in *x* and *y*.
具有标签数据的对象。
如果提供，请提供要在* x *和* y *中绘制的标签名称。
.
. note::
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.
从技术上讲，第⼆个标签是有效的* fmt *时，通话中存在⼀些歧义。
plot（'n'，'o'，data = obj）`可以是`plt（x，y）`或`plt（y，fmt）`。
在这种情况下，选择前⼀种解释，但会发出警告。
You may suppress the warning by adding an empty format string
`plot('n', 'o', '', data=obj)`.
您可以通过添加⼀个空的格式字符串`plot（'n'，'o'，''，data = obj）来抑制该警告。        Other Parameters
----------------
scalex, scaley : bool, optional, default: True
These parameters determined if the view limits are adapted to
the data limits. The values are passed on to `autoscale_view`.
这些参数确定视图限制是否适合数据限制。
这些值将传递给“ autoscale_view”。
**kwargs : `.Line2D` properties, optional
*kwargs* are used to specify properties like a line label (for
auto legends), linewidth, antialiasing, marker face color.
* kwargs *⽤于指定属性，例如线标签（⽤于⾃动图例），线宽，抗锯齿，标记⾯颜⾊。            Example::
>>> plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)
>>> plot([1,2,3], [1,4,9], 'rs',  label='line 2')
If you make multiple lines with one plot command, the kwargs
apply to all those lines.
如果使⽤⼀个plot命令制作多条线，则kwarg应⽤于所有这些线。
Here is a list of available `.Line2D` properties:
这是⼀个可⽤的.Line2D属性的列表：
%(_Line2D_docstr)s
Returns
-------
lines
A list of `.Line2D` objects representing the plotted data.
代表所绘制数据的.Line2D对象列表。
See Also
--------
scatter : XY scatter plot with markers of varying size and/or color
(sometimes also called bubble chart).
带有不同⼤⼩和/或颜⾊的标记的XY散点图
（有时也称为⽓泡图）。
Notes
Notes
-----
**Format Strings**
A format string consists of a part for color, marker and line::
fmt = '[marker][line][color]'
格式字符串由颜⾊，标记和线条组成：fmt ='[marker] [line] [color]'
Each of them is optional. If not provided, the value from the style
cycle is used. Exception: If ``line`` is given, but no ``marker``,
the data will be a line without markers.
它们每个都是可选的。如果未提供，则使⽤样式周期中的值。
例外：如果给出了“ line”，但没有给出“ marker”，则数据将是没有标记的⼀⾏。
Other combinations such as ``[color][marker][line]`` are also
supported, but note that their parsing may be ambiguous.
还⽀持其他组合，例如“ [color] [marker] [line]”，但请注意，它们的解析可能不明确。        **Markers**
=============    ===============================
character        description
=============    ===============================
``'.'``          point marker
``','``          pixel marker
``'o'``          circle marker
``'v'``          triangle_down marker
``'^'``          triangle_up marker
``'<'``          triangle_left marker
``'>'``          triangle_right marker
``'1'``          tri_down marker
``'2'``          tri_up marker
``'3'``          tri_left marker
``'4'``          tri_right marker
``'s'``          square marker
``'p'``          pentagon marker 五边形标记python 定义数组
``'*'``          star marker
``'h'``          hexagon1 marker
``'H'``          hexagon2 marker
``'+'``          plus marker
``'x'``          x marker
``'D'``          diamond marker
``'d'``          thin_diamond marker
``'|'``          vline marker
``'_'``          hline marker
=============    ===============================
**Line Styles**
=============    ===============================
character        description
=============    ===============================
``'-'``          solid line style
``'--'``        dashed line style
``'-.'``        dash-dot line style
``':'``          dotted line style
=============    ===============================
Example format strings::
'b'    # blue markers with default shape
'or'  # red circles
'-g'  # green solid line
'--'  # dashed line with default color
'^k:'  # black triangle_up markers connected by a dotted line
⿊⾊上三⾓形标记，由虚线连接
**Colors**
The supported color abbreviations are the single letter codes
⽀持的颜⾊缩写是单个字母代码
=============    ===============================
character        color
=============    ===============================
``'b'``          blue
``'g'``          green
``'r'``          red
``'c'``          cyan
``'c'``          cyan
``'m'``          magenta
``'y'``          yellow
``'k'``          black
``'w'``          white
=============    ===============================
and the ``'CN'`` colors that index into the default property cycle.
以及“ CN”颜⾊可索引到默认属性周期。
If the color is the only part of the format string, you can
additionally use any  `lors` spec, e.g. full names
(``'green'``) or hex strings (``'#008000'``).
如果颜⾊是格式字符串的唯⼀部分，则可以另外使⽤任何`lors`规范，例如全名（``'green'''）或⼗六进制字符串（``'＃008000'``）。
"""
kwargs = alize_kwargs(kwargs, mlines.Line2D._alias_map)
lines =[*self._get_lines(*args, data=data,**kwargs)]
for line in lines:
self.add_line(line)
self.autoscale_view(scalex=scalex, scaley=scaley)
return lines
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