七月的summer

plt.figure()函数官方文档matplotlib.pyplot.figure(num=None, figsize=None, dpi=None, facecolor=None, edgecolor=None, frameon=True, FigureClass=<class 'matplotlib.figure.Figure'>, clear=False, **kwargs)num:int or str,figure的唯一编号。

plt绘图之自适应子图间距一、plt.subplots(constrained_layout=True)import matplotlib.pyplot as pltimport matplotlib.colors as mcolorsimport matplotlib.gridspec as gridspecimport numpy as np plt.rcParams['savefig.facecolor']='0.8' plt.rcParams['figure.figsize']=5,

自定义子图布局import matplotlib.pyplot as plt import numpy as np import pandas as pd fig=plt.figure(constrained_layout=False)gs=fig.add_gridspec(nrows=3,ncols=3,left=0.05,right=0.48,wspace=0.3) #left,right调整子图在整个figure上的位置，这样做和constrained_layout=True/figur

matplotlib绘图对坐标轴的操作import numpy as npimport pandas as pd from pandas import Series,DataFrameimport matplotlib.pyplot as plt import matplotlib.ticker as ticker①改变figure背景和坐标系背景的颜色②设置x轴的刻度标签：颜色、字体旋转角度、字体大小等③设置y轴的刻度线样式：刻度线颜色、长度、宽度每一个坐标系ax有一个xaxis和ya

matplotlib库可视化常用的图主要是四种图：直方图、柱状图、饼图、散点图。由官方文档复现。matplotlib中文文档import matplotlibimport numpy as npimport matplotlib.pyplot as pltimport pandas as pd from pandas import Series,DataFramefrom matplotlib.ticker import MaxNLocatorfrom collections impor

一、 Pyplot tutorial复现线图、散点图、直方图绘制import numpy as npimport pandas as pd from pandas import DataFrame,Seriesimport matplotlib.pyplot as plt t=np.arange(0,5.,0.2) 一、线图plt.plot(t,t,'r--',t,t**2,'bs',t,t**3,'g^') plt.show()二、散点图data={'a':np.arang