pandas 图不叠加 [英] Pandas plot does not overlay

问题描述

我正尝试用下面的示例在折线图上叠加堆积的条形图，但仅显示第二个图，并且无法理解原因.

I am trying to overlay a stacked bar chart with a line plot as from the example below but only the second plot is shown and cannot understand why.

import pandas as pd
from matplotlib import pyplot as plt
df=pd.DataFrame({'yarding, mobile cable yarder on trailer': {1928: 1.4027824821879459e-20, 1924: 3.4365045943961052e-37, 1925: 6.9939032596152882e-30, 1926: 1.0712940173393567e-25, 1927: 8.6539917152671678e-23},
                 'yarding and processing, mobile cable yarder on truck': {1928: 1.1679873528237404e-20, 1924: 2.8613089094435456e-37, 1925: 5.8232768671842113e-30, 1926: 8.9198283644271726e-26, 1927: 7.2055027953028907e-23},
                 'delimbing, with excavator-based processor': {1928: 1.6998969986716558e-20, 1924: 4.1643685881703105e-37, 1925: 8.4752370448040848e-30, 1926: 1.2981979323251926e-25, 1927: 1.0486938381883222e-22}})
df2=pd.Series({1928: 3.0638184091973243e-19, 1924: 7.5056562764093482e-36, 1925: 1.5275356821475311e-28, 1926: 2.3398091372066067e-24, 1927: 1.8901157781841223e-21})

ax=df.plot(kind='bar',stacked=True,legend=False)
df2.plot(kind='line',ax=ax)
plt.show()

推荐答案

线图将数值数据相互对照.
条形图根据分类数据绘制数值数据.因此，即使条形图中的 x 值是数字，绘制它们的比例也不对应于这些数字，而是对应于某个索引.

Line plots plot numerical data against each other.
Bar plots plot numerical data against categorical data. Therefore even if the x values in the bar plot are numbers, the scale on which they are plotted does not correspond to those numbers, but rather to some index.

这意味着条形图的 x 轴刻度总是从 0 到 N，其中 N 是条形的数量(粗略地说，实际上它是 -0.5 到 N-0.5).

That means that the x axis scale of a bar plot always goes from 0 to N, where N is the number of bars (Roughly speaking, in reality it's rather -0.5 to N-0.5).

如果您现在将 1000 以上范围内的一些值添加到该比例，条形将缩小，直到它们不再可见(因此您可能认为它们甚至不存在).

If you now add some values in the range above 1000 to that scale, the bars will shrink until they cannot be seen any more (thus you may think they are not even there).

为避免此问题，您可以在两个不同的轴上工作.一个用于折线图，一个用于条形图，但它们共享相同的y轴.

To circumvent this problem, you may work on two different axes. One for the line plot, one for the bar plot, but have them shared the same y axis.

以下是一个可能的解决方案(这与 Martin 在我输入时添加的解决方案非常相似):

The following is a possible solution (which is very similar to the solution from Martin, which he has added while I was typing this):

import pandas as pd
from matplotlib import pyplot as plt
df=pd.DataFrame({'yarding, mobile cable yarder on trailer': {1928: 1.4027824821879459e-20, 1924: 3.4365045943961052e-37, 1925: 6.9939032596152882e-30, 1926: 1.0712940173393567e-25, 1927: 8.6539917152671678e-23},
                 'yarding and processing, mobile cable yarder on truck': {1928: 1.1679873528237404e-20, 1924: 2.8613089094435456e-37, 1925: 5.8232768671842113e-30, 1926: 8.9198283644271726e-26, 1927: 7.2055027953028907e-23},
                 'delimbing, with excavator-based processor': {1928: 1.6998969986716558e-20, 1924: 4.1643685881703105e-37, 1925: 8.4752370448040848e-30, 1926: 1.2981979323251926e-25, 1927: 1.0486938381883222e-22}})
df2=pd.Series({1928: 3.0638184091973243e-19, 1924: 7.5056562764093482e-36, 1925: 1.5275356821475311e-28, 1926: 2.3398091372066067e-24, 1927: 1.8901157781841223e-21})

fig, ax = plt.subplots()
# optionally make log scale
ax.set_yscale("log", nonposy='clip')
# create shared y axes
ax2 = ax.twiny()
df.plot(kind='bar',stacked=True,legend=False, ax=ax)
df2.plot(kind='line',ax=ax2)
ax2.xaxis.get_major_formatter().set_useOffset(False)
# remove upper axis ticklabels
ax2.set_xticklabels([])
# set the limits of the upper axis to match the lower axis ones
ax2.set_xlim(1923.5,1928.5)
plt.show()

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