Python可视化：python画图字体设置
Python可视化：图中字体设置
- Python可视化：图中字体设置
- 首先来简单的画一个散点图
- 设置图中的字体的两种方法
- 用`font`字典的形式来设置
- 用`fontproperties`参数来设置
- 可选字体名称集合
- 可选字体格式集合
- `legend()`函数详细参数
- `scatter()`函数详细参数
Python可视化：图中字体设置
Python用于绘图还是非常方便的，利用matplotlib，可以实现很多的绘图需求，当然，如果想要一些自动设置的比较美观的图形默认设置，可以用sebornhttp://seaborn.pydata.org/,或者pyecharthttps://echarts.apache.org/examples/zh/index.html#chart-type-map
这里我们主要总结一下matplotlib中绘图时候的字体设置。
首先来简单的画一个散点图
import matplotlib.pyplot as plt
import numpy as np
x = 10 * np.random.rand(10)
y = 10 * np.random.rand(10)
'''
x =
array([7.34208212, 6.14229141, 6.99898899, 5.10833595, 7.66301418,
3.84463225, 2.97255304, 5.54680296, 2.07965563, 2.72611992])
'''
plt.scatter(x, y, marker='o', c='red', label='customer')
plt.legend()
plt.show()
结果如下：
这里我们并没有改变图例legend的字体，所以是默认字体。假如我们想要改成Arial字体，加粗，应该怎么做呢？首先来看一下scatter()函数的详细参数
plt.scatter(
x, # x 坐标
y, # y 坐标
s=None, # The marker size in points**2
c=None, # color of nodes
marker=None, # The marker style
cmap=None, # Colormap
norm=None, # Normalize
vmin=None, #
vmax=None, #
alpha=None, #
linewidths=None, # The linewidth of the marker edges
verts=None, #
edgecolors=None, # The edge color of the marker
*,
plotnonfinite=False,
data=None,
**kwargs,
)
设置图中的字体的两种方法
用font字典的形式来设置
我们再来看一下legend的参数，legend()函数有一个参数为prop，解释如下
prop : None or :class:
matplotlib.font_manager.FontPropertiesor dict
The font properties of the legend. If None (default), the current
:data:matplotlib.rcParamswill be used.
我们利用下面的代码，来设置图例legend的字体，代码如下
# 用这个来修改legend的字体，也可以用plt.rcParams['font.sans-serif']=['Arial']的方法，都可以
font = {'family':'Arial' #'serif',
# ,'style':'italic'
,'weight':'bold' # 'normal'
# ,'color':'red'
,'size':20
}
# 注解边界的默认设置就是（x0,y0,width,height）=(0,0,1,1).
# 左边，右边，顶边，底边
# 对于四个元素的bbox_to_anchor()，也就是(x, y, width, height)，情况就和上面两个元素的有所不同了。我们通过图来展示，会更清楚一点。
# https://blog.csdn.net/chichoxian/article/details/101058046
# https://blog.csdn.net/sinat_41299610/article/details/106494549?utm_medium=distribute.pc_relevant_t0.none-task-blog-BlogCommendFromMachineLearnPai2-1.channel_param&depth_1-utm_source=distribute.pc_relevant_t0.none-task-blog-BlogCommendFromMachineLearnPai2-1.channel_param
plt.legend(loc = 'upper left' # 就是指legend的box的左上角坐标是(0.1, 0.3)
, bbox_to_anchor=(0.05, 0.9) # (x, y, width, height) (0, 0.5, 0.5, 0.5)
, prop = font
, markerscale = 2 # legend里面的符号的大小
)
运行结果如下：
用fontproperties参数来设置
设置横坐标和纵坐标坐标轴标题xlabel和ylabel的时候，可以用fontproperties这个参数来设置字体，如下面的代码
import numpy as np
x = 10 * np.random.rand(10)
y = 10 * np.random.rand(10)
'''
x =
array([7.34208212, 6.14229141, 6.99898899, 5.10833595, 7.66301418,
3.84463225, 2.97255304, 5.54680296, 2.07965563, 2.72611992])
'''
plt.scatter(x, y, marker='o', c='red', label='customer')
plt.xlabel("$x$ coor",fontproperties="STLiti")
plt.ylabel("$y$ $m^2$",fontproperties="STXingkai")
plt.title("$y = x$",fontproperties="STXinwei")
# 用这个来修改legend的字体，也可以用plt.rcParams['font.sans-serif']=['Arial']的方法，都可以
font = {'family':'Arial' #'serif',
# ,'style':'italic'
,'weight':'normal'
# ,'color':'red'
,'size':20
}
plt.legend(loc = 'upper left' # 就是指legend的box的左上角坐标是(0.1, 0.3)
, bbox_to_anchor=(0.05, 0.9) # (x, y, width, height) (0, 0.5, 0.5, 0.5)
, prop = font
, markerscale = 2 # legend里面的符号的大小
)
# plt.legend(loc = 'upper left', fontsize = 20)
plt.show()
注意，坐标轴标题还支持LaTeX语法，比如在坐标轴上输入公式等的，都是可以的。
可选字体名称集合
我们可以通过输出matplotlib.font_manager.fontManager.ttflist中的字体来查看都可以设置哪些可选字体。
import matplotlib
a = sorted([f.name for f in matplotlib.font_manager.fontManager.ttflist])
previous_font = ' '
count = 0
for font_name in a:
if(font_name != previous_font):
count = count + 1
# print(font_name, '\t\t\t\t', end='')
if(count > 2):
print('{:35}'.format(font_name), end='')
if(count % 4 == 0):
print()
previous_font = font_name
结果如下,也就是可以设置的字体可选集合
Adobe Devanagari Agency FB
Algerian Arial Arial Rounded MT Bold Arial Unicode MS
Baskerville Old Face Bauhaus 93 Bell MT Berlin Sans FB
Berlin Sans FB Demi Bernard MT Condensed Blackadder ITC Bodoni MT
Book Antiqua Bookman Old Style Bookshelf Symbol 7 Bradley Hand ITC
Britannic Bold Broadway Brush Script MT Calibri
Californian FB Calisto MT Cambria Candara
Castellar Centaur Century Century Gothic
Century Schoolbook Chiller Colonna MT Comic Sans MS
Consolas Constantia Cooper Black Copperplate Gothic Bold
Copperplate Gothic Light Corbel Courier New Curlz MT
DejaVu Sans DejaVu Sans Display DejaVu Sans Mono DejaVu Serif
DejaVu Serif Display DengXian ESRI AMFM Electric ESRI AMFM Gas
ESRI AMFM Sewer ESRI AMFM Water ESRI ArcPad ESRI Arrowhead
ESRI Business ESRI Cartography ESRI Caves 1 ESRI Caves 2
ESRI Caves 3 ESRI Climate & Precipitation ESRI Commodities ESRI Conservation
ESRI Crime Analysis ESRI Default Marker ESRI Dimensioning ESRI ERS Infrastructures S1
ESRI ERS Operations S1 ESRI Elements ESRI Enviro Hazard Analysis ESRI Enviro Hazard Incident
ESRI Enviro Hazard Sites ESRI Environmental & Icons ESRI Fire Incident NFPA ESRI Geology
ESRI Geology AGSO 1 ESRI Geology USGS 95-525 ESRI Geometric Symbols ESRI Hazardous Materials
ESRI Hydrants ESRI IGL Font16 ESRI IGL Font20 ESRI IGL Font21
ESRI IGL Font22 ESRI IGL Font23 ESRI IGL Font24 ESRI IGL Font25
ESRI Meteorological 01 ESRI Mil2525C Modifiers ESRI MilMod 01 ESRI MilMod 02
ESRI MilRed 01 ESRI MilSym 01 ESRI MilSym 02 ESRI MilSym 03
ESRI MilSym 04 ESRI MilSym 05 ESRI NIMA City Graphic LN ESRI NIMA City Graphic PT
ESRI NIMA DNC LN ESRI NIMA DNC PT ESRI NIMA VMAP1&2 LN ESRI NIMA VMAP1&2 PT
ESRI North ESRI Oil, Gas, & Water ESRI Ordnance Survey ESRI Pipeline US 1
ESRI Public1 ESRI SDS 1.95 1 ESRI SDS 1.95 2 ESRI SDS 2.00 1
ESRI SDS 2.00 2 ESRI Shields ESRI Surveyor ESRI Telecom
ESRI Transportation & Civic ESRI US Forestry 1 ESRI US Forestry 2 ESRI US MUTCD 1
ESRI US MUTCD 2 ESRI US MUTCD 3 ESRI Weather Ebrima
Edwardian Script ITC Elephant Engravers MT Eras Bold ITC
Eras Demi ITC Eras Light ITC Eras Medium ITC Euclid
Euclid Extra Euclid Fraktur Euclid Math One Euclid Math Two
Euclid Symbol FZCuHeiSongS-B-GB FZLanTingHeiS-UL-GB FZShuTi
FZYaoTi FangSong Felix Titling Fences
Footlight MT Light Forte Franklin Gothic Book Franklin Gothic Demi
Franklin Gothic Demi Cond Franklin Gothic Heavy Franklin Gothic Medium Franklin Gothic Medium Cond
Freestyle Script French Script MT Gabriola Gadugi
Garamond Georgia Gigi Gill Sans MT
Gill Sans MT Condensed Gill Sans MT Ext Condensed Bold Gill Sans Ultra Bold Gill Sans Ultra Bold Condensed
Gloucester MT Extra Condensed Goudy Old Style Goudy Stout Haettenschweiler
Harlow Solid Italic Harrington High Tower Text HoloLens MDL2 Assets
Impact Imprint MT Shadow Informal Roman Javanese Text
Jokerman Juice ITC KaiTi Kristen ITC
Kunstler Script Leelawadee Leelawadee UI LiSu
Lucida Bright Lucida Calligraphy Lucida Console Lucida Fax
Lucida Handwriting Lucida Sans Lucida Sans Typewriter Lucida Sans Unicode
MS Gothic MS Outlook MS Reference Sans Serif MS Reference Specialty
MT Extra MT Extra Tiger MV Boli Magneto
Maiandra GD Malgun Gothic Marlett Matura MT Script Capitals
Meiryo Microsoft Himalaya Microsoft JhengHei Microsoft MHei
Microsoft NeoGothic Microsoft New Tai Lue Microsoft PhagsPa Microsoft Sans Serif
Microsoft Tai Le Microsoft Uighur Microsoft YaHei Microsoft Yi Baiti
MingLiU-ExtB Mistral Modern No. 20 Mongolian Baiti
Monotype Corsiva Myanmar Text Niagara Engraved Niagara Solid
Nirmala UI NumberOnly OCR A Extended Old English Text MT
Onyx OriginGISSymbols Palace Script MT Palatino Linotype
Papyrus Parchment Perpetua Perpetua Titling MT
Playbill Poor Richard Pristina Rage Italic
Ravie Rockwell Rockwell Condensed Rockwell Extra Bold
STCaiyun STFangsong STHupo STIXGeneral
STIXNonUnicode STIXSizeFiveSym STIXSizeFourSym STIXSizeOneSym
STIXSizeThreeSym STIXSizeTwoSym STKaiti STLiti
STSong STXihei STXingkai STXinwei
STZhongsong Script MT Bold Segoe MDL2 Assets Segoe Print
Segoe Script Segoe UI Segoe UI Emoji Segoe UI Historic
Segoe UI Symbol Segoe WP Showcard Gothic SimHei
SimSun SimSun-ExtB Sitka Small Snap ITC
Stencil Sylfaen Symbol Symbol Tiger
Symbol Tiger Expert Tahoma Tempus Sans ITC Tiger
Tiger Expert Times New Roman Trebuchet MS Tw Cen MT
Tw Cen MT Condensed Tw Cen MT Condensed Extra Bold Verdana Viner Hand ITC
Vivaldi Vladimir Script Webdings Wide Latin
Wingdings Wingdings 2 Wingdings 3 YouYuan
Yu Gothic ZWAdobeF cmb10 cmex10
cmmi10 cmr10 cmss10 cmsy10
cmtt10 hakuyoxingshu7000 icomoon
如果只需要中文字体，那么可以选择：
中文字体部分该部分转载自https://blog.csdn.net/qq_17753903/article/details/86260276?utm_medium=distribute.pc_relevant_t0.none-task-blog-BlogCommendFromMachineLearnPai2-1.channel_param&depth_1-utm_source=distribute.pc_relevant_t0.none-task-blog-BlogCommendFromMachineLearnPai2-1.channel_param
| 字体 | 字体名 |
|---|---|
| 黑体 | SimHei |
| 楷体 | KaiTi |
| 隶书 | LiSu |
| 幼圆 | YouYuan |
| 华文细黑 | STXihei |
| 华文楷体 | STKaiti |
| 华文宋体 | STSong |
| 华文中宋 | STZhongsong |
| 华文仿宋 | STFangsong |
| 方正舒体 | FZShuTi |
| 方正姚体 | FZYaoti |
| 华文彩云 | STCaiyun |
| 华文琥珀 | STHupo |
| 华文隶书 | STLiti |
| 华文行楷 | STXingkai |
| 华文新魏 | STXinwei |
可选字体格式集合
字体的格式可以设置为
normalbolditalic
等，根据自己的喜好进行设置即可。
legend()函数详细参数
Signature: plt.legend(*args, **kwargs)
Docstring:
Place a legend on the axes.
Call signatures::
legend()
legend(labels)
legend(handles, labels)
The call signatures correspond to three different ways how to use
this method.
**1. Automatic detection of elements to be shown in the legend**
The elements to be added to the legend are automatically determined,
when you do not pass in any extra arguments.
In this case, the labels are taken from the artist. You can specify
them either at artist creation or by calling the
:meth:`~.Artist.set_label` method on the artist::
line, = ax.plot([1, 2, 3], label='Inline label')
ax.legend()
or::
line, = ax.plot([1, 2, 3])
line.set_label('Label via method')
ax.legend()
Specific lines can be excluded from the automatic legend element
selection by defining a label starting with an underscore.
This is default for all artists, so calling `Axes.legend` without
any arguments and without setting the labels manually will result in
no legend being drawn.
**2. Labeling existing plot elements**
To make a legend for lines which already exist on the axes
(via plot for instance), simply call this function with an iterable
of strings, one for each legend item. For example::
ax.plot([1, 2, 3])
ax.legend(['A simple line'])
Note: This way of using is discouraged, because the relation between
plot elements and labels is only implicit by their order and can
easily be mixed up.
**3. Explicitly defining the elements in the legend**
For full control of which artists have a legend entry, it is possible
to pass an iterable of legend artists followed by an iterable of
legend labels respectively::
legend((line1, line2, line3), ('label1', 'label2', 'label3'))
Parameters
----------
handles : sequence of `.Artist`, optional
A list of Artists (lines, patches) to be added to the legend.
Use this together with *labels*, if you need full control on what
is shown in the legend and the automatic mechanism described above
is not sufficient.
The length of handles and labels should be the same in this
case. If they are not, they are truncated to the smaller length.
labels : sequence of strings, optional
A list of labels to show next to the artists.
Use this together with *handles*, if you need full control on what
is shown in the legend and the automatic mechanism described above
is not sufficient.
Other Parameters
----------------
loc : str or pair of floats, default: :rc:`legend.loc` ('best' for axes, 'upper right' for figures)
The location of the legend.
The strings
``'upper left', 'upper right', 'lower left', 'lower right'``
place the legend at the corresponding corner of the axes/figure.
The strings
``'upper center', 'lower center', 'center left', 'center right'``
place the legend at the center of the corresponding edge of the
axes/figure.
The string ``'center'`` places the legend at the center of the axes/figure.
The string ``'best'`` places the legend at the location, among the nine
locations defined so far, with the minimum overlap with other drawn
artists. This option can be quite slow for plots with large amounts of
data; your plotting speed may benefit from providing a specific location.
The location can also be a 2-tuple giving the coordinates of the lower-left
corner of the legend in axes coordinates (in which case *bbox_to_anchor*
will be ignored).
For back-compatibility, ``'center right'`` (but no other location) can also
be spelled ``'right'``, and each "string" locations can also be given as a
numeric value:
=============== =============
Location String Location Code
=============== =============
'best' 0
'upper right' 1
'upper left' 2
'lower left' 3
'lower right' 4
'right' 5
'center left' 6
'center right' 7
'lower center' 8
'upper center' 9
'center' 10
=============== =============
bbox_to_anchor : `.BboxBase`, 2-tuple, or 4-tuple of floats
Box that is used to position the legend in conjunction with *loc*.
Defaults to `axes.bbox` (if called as a method to `.Axes.legend`) or
`figure.bbox` (if `.Figure.legend`). This argument allows arbitrary
placement of the legend.
Bbox coordinates are interpreted in the coordinate system given by
`bbox_transform`, with the default transform
Axes or Figure coordinates, depending on which ``legend`` is called.
If a 4-tuple or `.BboxBase` is given, then it specifies the bbox
``(x, y, width, height)`` that the legend is placed in.
To put the legend in the best location in the bottom right
quadrant of the axes (or figure)::
loc='best', bbox_to_anchor=(0.5, 0., 0.5, 0.5)
A 2-tuple ``(x, y)`` places the corner of the legend specified by *loc* at
x, y. For example, to put the legend's upper right-hand corner in the
center of the axes (or figure) the following keywords can be used::
loc='upper right', bbox_to_anchor=(0.5, 0.5)
ncol : integer
The number of columns that the legend has. Default is 1.
prop : None or :class:`matplotlib.font_manager.FontProperties` or dict
The font properties of the legend. If None (default), the current
:data:`matplotlib.rcParams` will be used.
fontsize : int or float or {'xx-small', 'x-small', 'small', 'medium', 'large', 'x-large', 'xx-large'}
Controls the font size of the legend. If the value is numeric the
size will be the absolute font size in points. String values are
relative to the current default font size. This argument is only
used if `prop` is not specified.
numpoints : None or int
The number of marker points in the legend when creating a legend
entry for a `.Line2D` (line).
Default is ``None``, which will take the value from
:rc:`legend.numpoints`.
scatterpoints : None or int
The number of marker points in the legend when creating
a legend entry for a `.PathCollection` (scatter plot).
Default is ``None``, which will take the value from
:rc:`legend.scatterpoints`.
scatteryoffsets : iterable of floats
The vertical offset (relative to the font size) for the markers
created for a scatter plot legend entry. 0.0 is at the base the
legend text, and 1.0 is at the top. To draw all markers at the
same height, set to ``[0.5]``. Default is ``[0.375, 0.5, 0.3125]``.
markerscale : None or int or float
The relative size of legend markers compared with the originally
drawn ones.
Default is ``None``, which will take the value from
:rc:`legend.markerscale`.
markerfirst : bool
If *True*, legend marker is placed to the left of the legend label.
If *False*, legend marker is placed to the right of the legend
label.
Default is *True*.
frameon : None or bool
Control whether the legend should be drawn on a patch
(frame).
Default is ``None``, which will take the value from
:rc:`legend.frameon`.
fancybox : None or bool
Control whether round edges should be enabled around the
:class:`~matplotlib.patches.FancyBboxPatch` which makes up the
legend's background.
Default is ``None``, which will take the value from
:rc:`legend.fancybox`.
shadow : None or bool
Control whether to draw a shadow behind the legend.
Default is ``None``, which will take the value from
:rc:`legend.shadow`.
framealpha : None or float
Control the alpha transparency of the legend's background.
Default is ``None``, which will take the value from
:rc:`legend.framealpha`. If shadow is activated and
*framealpha* is ``None``, the default value is ignored.
facecolor : None or "inherit" or a color spec
Control the legend's background color.
Default is ``None``, which will take the value from
:rc:`legend.facecolor`. If ``"inherit"``, it will take
:rc:`axes.facecolor`.
edgecolor : None or "inherit" or a color spec
Control the legend's background patch edge color.
Default is ``None``, which will take the value from
:rc:`legend.edgecolor` If ``"inherit"``, it will take
:rc:`axes.edgecolor`.
mode : {"expand", None}
If `mode` is set to ``"expand"`` the legend will be horizontally
expanded to fill the axes area (or `bbox_to_anchor` if defines
the legend's size).
bbox_transform : None or :class:`matplotlib.transforms.Transform`
The transform for the bounding box (`bbox_to_anchor`). For a value
of ``None`` (default) the Axes'
:data:`~matplotlib.axes.Axes.transAxes` transform will be used.
title : str or None
The legend's title. Default is no title (``None``).
title_fontsize: str or None
The fontsize of the legend's title. Default is the default fontsize.
borderpad : float or None
The fractional whitespace inside the legend border.
Measured in font-size units.
Default is ``None``, which will take the value from
:rc:`legend.borderpad`.
labelspacing : float or None
The vertical space between the legend entries.
Measured in font-size units.
Default is ``None``, which will take the value from
:rc:`legend.labelspacing`.
handlelength : float or None
The length of the legend handles.
Measured in font-size units.
Default is ``None``, which will take the value from
:rc:`legend.handlelength`.
handletextpad : float or None
The pad between the legend handle and text.
Measured in font-size units.
Default is ``None``, which will take the value from
:rc:`legend.handletextpad`.
borderaxespad : float or None
The pad between the axes and legend border.
Measured in font-size units.
Default is ``None``, which will take the value from
:rc:`legend.borderaxespad`.
columnspacing : float or None
The spacing between columns.
Measured in font-size units.
Default is ``None``, which will take the value from
:rc:`legend.columnspacing`.
handler_map : dict or None
The custom dictionary mapping instances or types to a legend
handler. This `handler_map` updates the default handler map
found at :func:`matplotlib.legend.Legend.get_legend_handler_map`.
Returns
-------
:class:`matplotlib.legend.Legend` instance
Notes
-----
Not all kinds of artist are supported by the legend command. See
:doc:`/tutorials/intermediate/legend_guide` for details.
Examples
--------
.. plot:: gallery/text_labels_and_annotations/legend.py
File: c:\users\hsingluliu\anaconda3\lib\site-packages\matplotlib\pyplot.py
Type: function
scatter()函数详细参数
Signature:
plt.scatter(
x,
y,
s=None,
c=None,
marker=None,
cmap=None,
norm=None,
vmin=None,
vmax=None,
alpha=None,
linewidths=None,
verts=None,
edgecolors=None,
*,
plotnonfinite=False,
data=None,
**kwargs,
)
Docstring:
A scatter plot of *y* vs *x* with varying marker size and/or color.
Parameters
----------
x, y : array_like, shape (n, )
The data positions.
s : scalar or array_like, shape (n, ), optional
The marker size in points**2.
Default is ``rcParams['lines.markersize'] ** 2``.
c : color, sequence, or sequence of color, optional
The marker color. Possible values:
- A single color format string.
- A sequence of color specifications of length n.
- A sequence of n numbers to be mapped to colors using *cmap* and
*norm*.
- A 2-D array in which the rows are RGB or RGBA.
Note that *c* should not be a single numeric RGB or RGBA sequence
because that is indistinguishable from an array of values to be
colormapped. If you want to specify the same RGB or RGBA value for
all points, use a 2-D array with a single row. Otherwise, value-
matching will have precedence in case of a size matching with *x*
and *y*.
Defaults to ``None``. In that case the marker color is determined
by the value of ``color``, ``facecolor`` or ``facecolors``. In case
those are not specified or ``None``, the marker color is determined
by the next color of the ``Axes``' current "shape and fill" color
cycle. This cycle defaults to :rc:`axes.prop_cycle`.
marker : `~matplotlib.markers.MarkerStyle`, optional
The marker style. *marker* can be either an instance of the class
or the text shorthand for a particular marker.
Defaults to ``None``, in which case it takes the value of
:rc:`scatter.marker` = 'o'.
See `~matplotlib.markers` for more information about marker styles.
cmap : `~matplotlib.colors.Colormap`, optional, default: None
A `.Colormap` instance or registered colormap name. *cmap* is only
used if *c* is an array of floats. If ``None``, defaults to rc
``image.cmap``.
norm : `~matplotlib.colors.Normalize`, optional, default: None
A `.Normalize` instance is used to scale luminance data to 0, 1.
*norm* is only used if *c* is an array of floats. If *None*, use
the default `.colors.Normalize`.
vmin, vmax : scalar, optional, default: None
*vmin* and *vmax* are used in conjunction with *norm* to normalize
luminance data. If None, the respective min and max of the color
array is used. *vmin* and *vmax* are ignored if you pass a *norm*
instance.
alpha : scalar, optional, default: None
The alpha blending value, between 0 (transparent) and 1 (opaque).
linewidths : scalar or array_like, optional, default: None
The linewidth of the marker edges. Note: The default *edgecolors*
is 'face'. You may want to change this as well.
If *None*, defaults to rcParams ``lines.linewidth``.
edgecolors : {'face', 'none', *None*} or color or sequence of color, optional.
The edge color of the marker. Possible values:
- 'face': The edge color will always be the same as the face color.
- 'none': No patch boundary will be drawn.
- A Matplotlib color or sequence of color.
Defaults to ``None``, in which case it takes the value of
:rc:`scatter.edgecolors` = 'face'.
For non-filled markers, the *edgecolors* kwarg is ignored and
forced to 'face' internally.
plotnonfinite : boolean, optional, default: False
Set to plot points with nonfinite *c*, in conjunction with
`~matplotlib.colors.Colormap.set_bad`.
Returns
-------
paths : `~matplotlib.collections.PathCollection`
Other Parameters
----------------
**kwargs : `~matplotlib.collections.Collection` properties
See Also
--------
plot : To plot scatter plots when markers are identical in size and
color.
Notes
-----
* The `.plot` function will be faster for scatterplots where markers
don't vary in size or color.
* Any or all of *x*, *y*, *s*, and *c* may be masked arrays, in which
case all masks will be combined and only unmasked points will be
plotted.
* Fundamentally, scatter works with 1-D arrays; *x*, *y*, *s*, and *c*
may be input as 2-D arrays, but within scatter they will be
flattened. The exception is *c*, which will be flattened only if its
size matches the size of *x* and *y*.
.. note::
In addition to the above described arguments, this function can take a
**data** keyword argument. If such a **data** argument is given, the
following arguments are replaced by **data[<arg>]**:
* All arguments with the following names: 'c', 'color', 'edgecolors', 'facecolor', 'facecolors', 'linewidths', 's', 'x', 'y'.
Objects passed as **data** must support item access (``data[<arg>]``) and
membership test (``<arg> in data``).
File: c:\users\hsingluliu\anaconda3\lib\site-packages\matplotlib\pyplot.py
Type: function