matplotlib

Rotate xtick labels in seaborn boxplot?

由 佐手、 提交于 2021-01-20 14:54:15
问题 I have a question that is basically the same as a question back from 2014 (see here). However, my script still throws an error. Here is what I do: I have a pandas dataframe with a few columns. I plot a simple boxplot comparison. g = sns.boxplot(x='categories', y='oxygen', hue='target', data=df) g.set_xticklabels(rotation=30) The graph looks like this: I'd like to rotate the x-labels by 30 degrees. Hence I use g.set_xticklabels(rotation=30) . However, I get the following error: set_xticklabels

让图形变得精致：seaborn绘图基础

由 ♀尐吖头ヾ 提交于 2021-01-20 09:08:07
1、seaborn的优点 它简化了复杂数据集的表示； 可以轻松构建复杂的可视化，简洁的控制matplotlib图形样式与几个内置主题； seaborn不可以替代matplotlib，而是matplotlib的很好补充； 2、seaborn的官网 学习某个知识点，最好的东西就是照着官网的提示学习，因为官网里面的知识点，够完整、够全面。seaborn的官网链接：http://seaborn.pydata.org 3、seaborn的作者介绍 4、seaborn的缩写为什么是sns，而不是sbn？ sns的使用来自于一个内部笑话，与美剧The West Wing有关。这部剧里有一个人物，名叫Samual Norman Seaborn，首字母简写为sns，因此最终简写为sns。 5、seaborn与matplotlib的关系？ seaborn是matplotlib的更高级的封装。因此学习seaborn之前，首先要知道matplotlib的绘图原理。 我们知道，使用matplotlib绘图，需要调节大量的绘图参数，需要记忆的东西很多。而seaborn基于matplotlib做了更高级的封装，使得绘图更加容易，它不需要了解大量的底层参数，就可以绘制出很多比较精致的图形。不仅如此，seaborn还兼容numpy、pandas数据结构，在组织数据上起了很大作用

Stop gif image from repeating in matplotlib

由 て烟熏妆下的殇ゞ 提交于 2021-01-20 07:07:09
问题 I searched for other similar questions but that didn't solve my problem. Below is a simple code that generates an animation in the form of a gif image in matplotlib: import numpy as np import matplotlib.pylab as plt import matplotlib.animation as anm fig = plt.figure() def draw(i): x = np.linspace(0, 5, num = 1000) y = np.sin(x-i*0.1) plt.clf() plt.plot(x, y, 'r-') anim = anm.FuncAnimation(fig, draw, frames = 10, interval = 500, repeat = False) anim.save('test.gif', fps = 1, writer =

Stop gif image from repeating in matplotlib

由 谁都会走 提交于 2021-01-20 07:06:49
问题 I searched for other similar questions but that didn't solve my problem. Below is a simple code that generates an animation in the form of a gif image in matplotlib: import numpy as np import matplotlib.pylab as plt import matplotlib.animation as anm fig = plt.figure() def draw(i): x = np.linspace(0, 5, num = 1000) y = np.sin(x-i*0.1) plt.clf() plt.plot(x, y, 'r-') anim = anm.FuncAnimation(fig, draw, frames = 10, interval = 500, repeat = False) anim.save('test.gif', fps = 1, writer =

Matplotlib: imshow with second y axis

由 混江龙づ霸主 提交于 2021-01-20 04:17:56
问题 I'm trying to plot a two-dimensional array in matplotlib using imshow(), and overlay it with a scatterplot on a second y axis. oneDim = np.array([0.5,1,2.5,3.7]) twoDim = np.random.rand(8,4) plt.figure() ax1 = plt.gca() ax1.imshow(twoDim, cmap='Purples', interpolation='nearest') ax1.set_xticks(np.arange(0,twoDim.shape[1],1)) ax1.set_yticks(np.arange(0,twoDim.shape[0],1)) ax1.set_yticklabels(np.arange(0,twoDim.shape[0],1)) ax1.grid() #This is the line that causes problems ax2 = ax1.twinx()

Matplotlib: imshow with second y axis

由 时光总嘲笑我的痴心妄想 提交于 2021-01-20 04:15:54
问题 I'm trying to plot a two-dimensional array in matplotlib using imshow(), and overlay it with a scatterplot on a second y axis. oneDim = np.array([0.5,1,2.5,3.7]) twoDim = np.random.rand(8,4) plt.figure() ax1 = plt.gca() ax1.imshow(twoDim, cmap='Purples', interpolation='nearest') ax1.set_xticks(np.arange(0,twoDim.shape[1],1)) ax1.set_yticks(np.arange(0,twoDim.shape[0],1)) ax1.set_yticklabels(np.arange(0,twoDim.shape[0],1)) ax1.grid() #This is the line that causes problems ax2 = ax1.twinx()

Matplotlib plt.xlabel() vs ax.set_xlabel()

由 好久不见. 提交于 2021-01-19 08:27:19
问题 I am using some code that uses the singleton-version of matplotlib in Python, i.e. it has calls like plt.figure() ... plt.xlabel("abc") I am trying to convert it to the functional/memory-less version: fig,ax = plt.subplots() ... ax.set_xlabel("abc") A couple questions: Is there an option to set the xlabel of an axes directly? Something like ax.xlabel = "xlabel string" ? From the documentation, it seems like this is not possible. (not even a private attribute we can set) Or is it always

Matplotlib plt.xlabel() vs ax.set_xlabel()

由 懵懂的女人 提交于 2021-01-19 08:23:16
问题 I am using some code that uses the singleton-version of matplotlib in Python, i.e. it has calls like plt.figure() ... plt.xlabel("abc") I am trying to convert it to the functional/memory-less version: fig,ax = plt.subplots() ... ax.set_xlabel("abc") A couple questions: Is there an option to set the xlabel of an axes directly? Something like ax.xlabel = "xlabel string" ? From the documentation, it seems like this is not possible. (not even a private attribute we can set) Or is it always

How do you make the x-axis pass through (0,0) with matplotlib in Python?

由 六月ゝ 毕业季﹏ 提交于 2021-01-19 06:15:47
问题 How do I make the horizontal axis pass through the origin? import numpy as np import matplotlib.pyplot as plt rateList=[0,0.08,.1,.12,.15,.175,.225,.25,.275,.3,.325,.35] list1=[-316.8,-424,-2.8,622,658,400,83,16.8,0] NPV_Profile1=[np.npv(x,list1) for x in rateList] list2=[-496,-760,84,1050.4,658,400,83,16.8,0] NPV_Profile2=[np.npv(x,list2) for x in rateList] plt.plot(rateList,NPV_Profile1,rateList,NPV_Profile2) plt.show() 回答1: Try with: import numpy as np import matplotlib.pyplot as plt

50个最有价值的数据可视化图表

由 可紊 提交于 2021-01-19 00:14:20
点击上方 大数据学苑 即可关注哟 加个 星标 你我从此不再错过 转载自： DataCastle数据城堡 本文总结了在数据分析和可视化中最有用的 50 个 Matplotlib 图表。这些图表列表允许您使用 python 的 matplotlib 和 seaborn 库选择要显示的可视化对象。 这些图表根据可视化目标的 7 个不同情景进行分组。 例如，如果要想象两个变量之间的关系，请查看“关联”部分下的图表。或者，如果您想要显示值如何随时间变化，请查看“变化”部分，依此类推。 有效图表的重要特征： 在不歪曲事实的情况下传达正确和必要的信息。 设计简单，您不必太费力就能理解它。 从审美角度支持信息而不是掩盖信息。 信息没有超负荷。 01 关联（Correlation） 关联图表用于可视化 2 个或更多变量之间的关系。也就是说， 一个变量如何相对于另一个变化。 1. 散点图（Scatter plot） 散点图是用于研究两个变量之间关系的经典的和基本的图表。如果数据中有多个组，则可能需要以不同颜色可视化每个组。您可以使用 plt.scatterplot() 方便地执行此操作。 2. 带边界的气泡图（Bubble plot with Encircling） 有时，您希望在边界内显示一组点以强调其重要性。在这个例子中，你从数据框中获取记录，并用 encircle() 来使边界显示出来。 3.
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