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Import the matpltlib library
matplotlib is an excellent third-party library for python data visualization
. When using the matpltlib library to draw, first import it, load the pyplot inside, and name it plt, and then use the plot function to draw
import matplotlib.pyplot as plt #plt是引入模块的别名
Summary of pyplot basic icon functions
function | effect |
---|---|
plt.plot(x,y,format) | draw coordinates |
plt.plot(data,notch,position) | Draw a boxplot |
plt.bar(left,height,width,bottom) | draw a bar graph |
plt.barh(width,bottom,left,height) | Draw a horizontal bar chart |
plt.polar(theta,r) | Draw Polar Plot |
plt.pie(data,explode) | draw pie chart |
plt.hist(x,bins,normed) | draw histogram |
plt.scatter(x,y) | Draw a scatterplot |
There are many more hahaha, no longer pay attention to list
Plot function drawing syntax rules
Plot function parameters:plot([x],y,[format],**kwargs)
parameter | use |
---|---|
x | x-axis data, list or array |
y | y-axis data, list or array |
format | format string for control curve |
**quargs | second group or more (x, y, string) |
There are too many kinds of grammar, steal a few MOOC pictures and put them up~
line chart
from matplotlib import pyplot as plt
#生成数据
#横坐标数据从2017到2022,第三个参数可控制步长,可写可不写
x = range(2017, 2022)
#y对应纵坐标的值
y1 = [49, 48, 45, 52, 50]
y2 = [60, 62, 61, 65, 63]
#生成图形
plt.title("LMY and her mother's weight")
plt.xlabel('year')
plt.ylabel('kg')
plt.plot(x, y1, color='green', label='LMY')
plt.plot(x, y2, color='purple', label='mother')
plt.grid(alpha=0.5)
plt.legend(loc='upper right')
#显示图形
plt.show()
Scatterplot
from matplotlib import pyplot as plt
import numpy as np
# 生成数据
# 横坐标数据从2017到2022,第三个参数可控制步长,可写可不写
x = range(2017, 2022)
# y对应纵坐标的值
y1 = [49, 48, 45, 52, 50]
y2 = [60, 62, 61, 65, 63]
# 生成图形
plt.title("LMY and her mother's weight")
plt.xlabel('year')
plt.ylabel('kg')
# 点的大小
area = np.pi*4**2
plt.scatter(x, y1, s=area, c='yellow', alpha=1)
plt.scatter(x, y2, s=area, c='blue', alpha=1)
plt.legend()
plt.yticks(())
plt.show()
histogram
from matplotlib import pyplot as plt
import numpy as np
# 生成数据
# 横坐标数据从2017到2022,第三个参数可控制步长,可写可不写
x = [2017, 2018, 2019, 2020, 2021]
# y对应纵坐标的值
y1 = [49, 48, 45, 52, 50]
y2 = [60, 62, 61, 65, 63]
# 生成图形
plt.title("LMY and her mother's weight")
plt.ylabel('frequency')
plt.xlabel('kg')
# 点的大小
plt.hist(y1, bottom=None, color='purple')
plt.hist(y2, bottom=None, color='pink')
plt.show()
# n, bins, patches = plt.hist(arr, bins=50, normed=1, facecolor='green', alpha=0.75)
'''
arr:需要计算直方图的一维数组
bins:直方图的柱数,可选项,默认为10
normed:是否将得到的直方图向量归一化,默认为0
facecolor:直方图颜色
alpha:透明度
'''
bar chart
portrait
from matplotlib import pyplot as plt
import numpy as np
arr = np.arange(2017, 2022)
x = [49, 48, 45, 52, 50] # x轴
y = [2017, 2018, 2019, 2020, 2021]
rect = plt.bar(arr, x, width=0.5)
plt.title('LMY')
plt.xlabel('weight')
plt.ylabel('year')
plt.legend()
plt.show()
horizontal
many lines
from matplotlib import pyplot as plt
import numpy as np
arr = np.arange(2017, 2022)
x1 = [49, 48, 45, 52, 50] # x轴
x2 = [60, 62, 61, 65, 63]
y = [2017, 2018, 2019, 2020, 2021]
rects1 = plt.bar(arr, x1, 0.5, color='purple', label='LMY')
rects2 = plt.bar(arr, x2, 0.5, color='yellow', label='Mother', alpha=0.3)
plt.title("LMY and her mother's weight")
plt.xlabel('weight')
plt.ylabel('year')
plt.legend()
plt.show()
pie chart
from matplotlib import patches, pyplot as plt
import numpy as np
label_list = ['49', '48', '45', '52', '50']
size = [20, 20, 20, 20, 20]
# 各部分的颜色
color = ['red', 'pink', 'blue', 'green', 'purple']
explode = [0, 0, 0.15, 0, 0]
patches, l_text, p_text = plt.pie(size, explode=explode, colors=color, labels=label_list,
labeldistance=1.2, autopct="%1.2f%%", shadow=False, startangle=90, pctdistance=0.6)
plt.axis('equal')
plt.title("LMY's weight")
plt.legend(loc='upper left')
plt.show()