如何从列表创建分组条形图

Question

我正在尝试绘制条形图，比较 2 种不同情况下多个项目的数量。
所需的输出将是一个条形图，其中有 4+4 = 8 个条，彼此相邻，表示每种情况下每种类型的数量。
这是我写的初始代码，它没有达到我的预期。我该如何修改它？

import numpy
import matplotlib.pyplot as plt

names = ["a","b","c","d"]
case1 = [5,7,5,6]
case2 = [7,4,8,5]

plt.hist(case1)
plt.show()

Answer 1

最简单的方法是用 pandas 创建数据框，然后用 pandas.DataFrame.plot 绘图
- 在这种情况下，数据帧索引 'names' 自动用于 x 轴，列绘制为条形图。
- matplotlib 用作绘图后端
在 python 3.8、pandas 1.3.1 和 matplotlib 3.4.2
有关长度不等的列表，请参阅

import pandas as pd
import matplotlib.pyplot as plt

names = ["a","b","c","d"]
case1 = [5,7,5,6]
case2 = [7,4,8,5]

# create the dataframe
df = pd.DataFrame({'c1': case1, 'c2': case2}, index=names)

# display(df)
   c1  c2
a   5   7
b   7   4
c   5   8
d   6   5

# plot
ax = df.plot(kind='bar', figsize=(6, 4), rot=0, title='Case Comparison', ylabel='Values')
plt.show()

为 python 2.7

fig, ax = plt.subplots(figsize=(6, 4))
df.plot.bar(ax=ax, rot=0)
ax.set(ylabel='Values')
plt.show()

Answer 2

可以通过code适应您的问题来实现。

# importing pandas library
import pandas as pd
# import matplotlib library
import matplotlib.pyplot as plt
  
# creating dataframe
df = pd.DataFrame({
    'Names': ["a","b","c","d"],
    'Case1': [5,7,5,6],
    'Case2': [7,4,8,5]
})
  
# plotting graph
df.plot(x="Names", y=["Case1", "Case2"], kind="bar")

Answer 3

仅限 Matplotlib（加上 numpy.arange）。

如果您考虑一下，就很容易正确放置条形图组。

import matplotlib.pyplot as plt
from numpy import arange

places = ["Nujiang Lisu","Chuxiong Yi","Liangshan Yi","Dehong Dai & Jingpo"]
animals = ['Pandas', 'Snow Leopards']

n_places = len(places)
n_animals = len(animals)

animals_in_place = [[5,7,5,6],[7,4,8,5]]

### prepare for grouping the bars    
total_width = 0.5 # 0 ≤ total_width ≤ 1
d = 0.1 # gap between bars, as a fraction of the bar width, 0 ≤ d ≤ ∞
width = total_width/(n_animals+(n_animals-1)*d)
offset = -total_width/2

### plot    
x = arange(n_places)
fig, ax = plt.subplots()
for animal, data in zip(animals, animals_in_place):
    ax.bar(x+offset, data, width, align='edge', label=animal)
    offset += (1+d)*width
ax.set_xticks(x) ; ax.set_xticklabels(places)
fig.legend()

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