Python画图之散点图（plt.scatter）

        散点图的应用很广泛，以前介绍过很多画图方法：Python画图（直方图、多张子图、二维图形、三维图形以及图中图），漏掉了这个，现在补上，用法很简单，我们可以help(plt.scatter)看下它的用法：

Help on function scatter in module matplotlib.pyplot: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, hold=None, data=None, **kwargs)Make a scatter plot of `x` vs `y`Marker size is scaled by `s` and marker color is mapped to `c`Parameters----------x, y : array_like, shape (n, )Input datas : scalar or array_like, shape (n, ), optionalsize in points^2. Default is `rcParams[&＃39;lines.markersize&＃39;] ** 2`. c : color, sequence, or sequence of color, optional, default: &＃39;b&＃39; `c` can be a single color format string, or a sequence of color specifications of length `N`, or a sequence of `N` numbers to be mapped to colors using the `cmap` and `norm` specified via kwargs (see below). 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. `c` can be a 2-D array in which the rows are RGB or RGBA, however, including the case of a single row to specify the same color for all points.marker : `~matplotlib.markers.MarkerStyle`, optional, default: &＃39;o&＃39; See `~matplotlib.markers` for more information on the different styles of markers scatter supports. `marker` can be eitheran instance of the class or the text shorthand for a particular marker.cmap : `~matplotlib.colors.Colormap`, optional, default: NoneA `~matplotlib.colors.Colormap` instance or registered 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: NoneA `~matplotlib.colors.Normalize` instance is used to scaleluminance data to 0, 1. `norm` is only used if `c` is an array of floats. If `None`, use the default :func:`normalize`.vmin, vmax : scalar, optional, default: None`vmin` and `vmax` are used in conjunction with `norm` to normalize luminance data. If either are `None`, the min and max of the color array is used. Note if you pass a `norm` instance, your settings for `vmin` and `vmax` will be ignored.alpha : scalar, optional, default: NoneThe alpha blending value, between 0 (transparent) and 1 (opaque) linewidths : scalar or array_like, optional, default: NoneIf None, defaults to (lines.linewidth,).verts : sequence of (x, y), optionalIf `marker` is None, these vertices will be used toconstruct the marker. The center of the marker is locatedat (0,0) in normalized units. The overall marker is rescaled by ``s``.edgecolors : color or sequence of color, optional, default: None If None, defaults to &＃39;face&＃39;If &＃39;face&＃39;, the edge color will always be the same asthe face color.If it is &＃39;none&＃39;, the patch boundary will notbe drawn.For non-filled markers, the `edgecolors` kwargis ignored and forced to &＃39;face&＃39; internally.Returns-------paths : `~matplotlib.collections.PathCollection`Other parameters----------------kwargs : `~matplotlib.collections.Collection` propertiesSee Also--------plot : to plot scatter plots when markers are identical in size and colorNotes-----* The `plot` function will be faster for scatterplots where markers don&＃39;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 beflattened. The exception is `c`, which will be flattened only if its size matches the size of `x` and `y`.


我们可以看到参数比较多，平时主要用到的就是大小、颜色、样式这三个参数

s：形状的大小，默认 20，也可以是个数组，数组每个参数为对应点的大小，数值越大对应的图中的点越大。
c：形状的颜色，"b"：blue   "g"：green    "r"：red   "c"：cyan(蓝绿色，青色)  "m"：magenta(洋红色，品红色) "y"：yellow "k"：black  "w"：white
marker：常见的形状有如下
"."：点                   ","：像素点           "o"：圆形
"v"：朝下三角形   "^"：朝上三角形   "<"：朝左三角形   ">"：朝右三角形
"s"：正方形           "p"：五边星          "*"：星型
"h"：1号六角形     "H"：2号六角形 

"+"：+号标记      "x"：x号标记
"D"：菱形              "d"：小型菱形 
"|"：垂直线形         "_"：水平线形

我们来看几个示例(在一张图显示了)

import matplotlib.pyplot as plt
import numpy as np
import pandas as pdx=np.array([3,5])
y=np.array([7,8])x1=np.random.randint(10,size=(25,))
y1=np.random.randint(10,size=(25,))plt.scatter(x,y,c=&＃39;r&＃39;)
plt.scatter(x1,y1,s=100,c=&＃39;b&＃39;,marker=&＃39;*&＃39;)#使用pandas来读取
x2=[]
y2=[]
rdata=pd.read_table(&＃39;1.txt&＃39;,header=None)
for i in range(len(rdata[0])):x2.append(rdata[0][i].split(&＃39;,&＃39;)[0])y2.append(rdata[0][i].split(&＃39;,&＃39;)[1])plt.scatter(x2,y2,s=200,c=&＃39;g&＃39;,marker=&＃39;o&＃39;)
plt.show()

 其中文档1.txt内容如下（上面图中的4个绿色大点）

5,6
7,9
3,4
2,7