参考:how to change y axis values in matplotlib Matplotlib是一个Python库,用于绘制数据可视化图表。在使用Matplotlib绘制图表时,我们经常需要调整图表中的y轴值,以便更好地展示数据。本文将介绍如何在Matplotlib中更改y轴值的方法,并提供示例代码进行演示。 1. 更改y轴刻度值 有时候,我们希望更改y轴的刻度值,使其...
次刻度间隔为0.5ax.xaxis.set_major_locator(ticker.MultipleLocator(1))ax.xaxis.set_minor_locator(ticker.AutoMinorLocator(2))# 设置y轴的主刻度间隔为5,次刻度间隔为1ax.yaxis.set_major_locator(ticker.MultipleLocator(5))ax.yaxis.set_minor_locator(ticker.AutoMinorLocator(4))plt.show()...
plt.locator_params(axis='y', nbins=4) 来源:https://stackoverflow.com/a/13418954/13688160 很坑的是,log scale用这种方式无效,需要手动设置ticks: plt.yscale('log')# 设置成log scale似乎会清空ticks,所以要把设置ticks放后面plt.yticks([1e5,1e6,1e7], fontsize=8)# plt.yticks似乎会消除minor tic...
# We change the fontsize of minor ticks label ax.tick_params(axis='both', which='major', labelsize=10) ax.tick_params(axis='both', which='minor', labelsize=8) 2.8 ticks内嵌 import matplotlib.pyplot as plt fig, ax = plt.subplots() ax.tick_params(axis="y",direction="in", pad=-...
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f')) # Add a color bar which maps values to colors. fig.colorbar(surf, shrink=0.5, aspect=5) plt.show() 6、流线图(Streamplot) streamplot()函数绘制矢量场的流线。除了简单绘制流线之外,它还允许将流线的颜色和/或线宽映射到单独的参数中,例...
('YYYY',axis=1):plt.plot(df['YYYY'],df[column],marker='',color='grey',linewidth=1,alpha=0.4)# PA的特殊处理,用橘色且加粗plt.plot(df['YYYY'],df['PA'],marker='',color='orange',linewidth=4,alpha=0.7)# 设定每条线的label的位置,其他的都为灰色,PA的为橘色num=0foriindf.values[7][...
You can use the keyword argument linestyle, or shorter ls, to change the style of the plotted line:ExampleGet your own Python Server Use a dotted line: import matplotlib.pyplot as plt import numpy as np ypoints = np.array([3, 8, 1, 10]) plt.plot(ypoints, linestyle = 'dotted') ...
Inthisbook,you’llgethands-onwithcustomizingyourdataplotswiththehelpofMatplotlib.You’llstartwithcustomizingplots,makingahandfulofspecial-purposeplots,andbuilding3Dplots.You’llexplorenon-triviallayouts,Pylabcustomization,andmoreabouttileconfiguration.You’llbeabletoaddtext,putlinesinplots,andalsohandlepolygons,...
# Change the line plot below to a scatter plot plt.scatter(gdp_cap, life_exp) # Put the x-axis on a logarithmic scale plt.xscale('log') # Show plot plt.show() 5,Scatter plot(2) Start from scratch: import matplotlib.pyplot as plt. ...
Thisbookisforanyoneinterestedindatavisualization,togetinsightsfrombigdatawithPythonandMatplotlib2.x.WiththisbookyouwillbeabletoextendyourknowledgeandlearnhowtousepythoncodeinordertovisualizeyourdatawithMatplotlib.BasicknowledgeofPythonisexpected. 加入书架 开始阅读 手机扫码读本书 ...