matplotlib（4）-- 数据覆盖坐标轴时的相关处理、散点图scatter、条形图bar

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-3, 3, 50)
y1 = 2 * x + 1

#figure 1
plt.figure()
plt.plot(x, y1, linewidth = 10,zorder=1)


#横纵坐标轴显示范围设置
plt.xlim((-2, 2))
plt.ylim((-10, 10))

#坐标轴的移动 gca = “get current axis”
ax = plt.gca()
ax.spines["right"].set_color("none")
ax.spines["top"].set_color("none")
ax.xaxis.set_ticks_position("bottom")
ax.yaxis.set_ticks_position("left")
ax.spines["bottom"].set_position(("data", 0))   #Set the X and Y coordinates of the sprite simultaneously
ax.spines["left"].set_position(("data", 0))

#当出现数据覆盖坐标值的情况：

#方法一：直接将plt.plot(x, y1, linewidth = 10)修改为plt.plot(x, y1, linewidth = 10,zorder=1)即可
#方法二：将每一个坐标值取出来,作相关处理,使其覆盖在数据上,以达到可视化处理
for label in ax.get_xticklabels() + ax.get_yticklabels():
    label.set_fontsize(10)
    label.set_zorder(1)
    label.set_bbox(dict(facecolor = "White", edgecolor = "None", alpha = 0.1))

plt.show()

import matplotlib.pyplot as plt
import numpy as np

n = 1024
X = np.random.normal(0, 1, n)
Y = np.random.normal(0, 1, n)
T = np.arctan2(Y, X)

#关于scatter的相关参数介绍，参考博文 https://blog.csdn.net/qiu931110/article/details/68130199
plt.scatter(X, Y, s = 75, c = T, alpha = 0.5)

plt.xlim((-1.5, +1.5))
plt.ylim((-1.5, +1.5))

plt.show()

import matplotlib.pyplot as plt
import numpy as np

n = 1024
X = np.random.normal(0, 1, n)
Y = np.random.normal(0, 1, n)
T = np.arctan2(Y, X)

#关于scatter的相关参数介绍，参考博文 https://blog.csdn.net/qiu931110/article/details/68130199
plt.scatter(X, Y, s = 75, c = T, alpha = 0.5)
plt.xlim((-1.5, +1.5))
plt.ylim((-1.5, +1.5))

#将坐标标度隐藏
plt.xticks(())
plt.yticks(())

plt.show()

import matplotlib.pyplot as plt
import numpy as np

n = 12
X = np.arange(n)
Y1= (1 - X/float(n)) * np.random.uniform(0.5, 1.0, n)
Y2= (1 - X/float(n)) * np.random.uniform(0.5, 1.0, n)

#plt.bar()参数解释，参考博文 https://www.cnblogs.com/shine-rainbow/p/10742952.html
#绘制条形图
plt.bar(X, +Y1, facecolor = "#9999ff", edgecolor = "white")
plt.bar(X, -Y2, facecolor = "#ff9999", edgecolor = "white")

#text()参数解释
#####################
# plt.text(x, y, string, fontsize=15, verticalalignment="top", horizontalalignment="right")
# 参数：
# x,y:表示坐标值上的值
# string:表示说明文字
# fontsize:表示字体大小
# verticalalignment：垂直对齐方式 ，参数：[ ‘center’ | ‘top’ | ‘bottom’ | ‘baseline’ ]
# horizontalalignment：水平对齐方式 ，参数：[ ‘center’ | ‘right’ | ‘left’ ]

for x,y in zip(X, Y1):
    plt.text(x, y, "%.2f"%y, ha = "center", va = "bottom")

for x,y in zip(X, -Y2):
    plt.text(x, y, "%.2f"%y, ha = "center", va = "top")

plt.xticks(())
plt.yticks(())

plt.show()