matplotlib 如何将条形图中的xticks居中

fhity93d  于 2023-05-29  发布在  其他
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我遵循本教程在条形图link中添加值
博客中显示的代码是这样写的

from matplotlib import pyplot as plt
import numpy as np

years = [1901, 1911, 1921, 1931, 1941, 1951, 1961, 1971, 1981, 1991, 2001, 2011]
population = [237.4, 238.4, 252.09, 251.31, 278.98, 318.66, 361.09, 439.23, 548.16, 683.33, 846.42, 1028.74]

x = np.arange(len(years)) # the label locations
width = 0.35 # the width of the bars

fig, ax = plt.subplots()

ax.set_ylabel('Population(in million)')
ax.set_title('Years')
ax.set_xticks(x)
ax.set_xticklabels(years)

pps = ax.bar(x - width/2, population, width, label='population')
for p in pps:
   height = p.get_height()
   ax.annotate('{}'.format(height),
      xy=(p.get_x() + p.get_width() / 2, height),
      xytext=(0, 3), # 3 points vertical offset
      textcoords="offset points",
      ha='center', va='bottom')

plt.show()

输出结果是这样的

但是,我刚刚意识到,从条形图的xticks是不居中

我的问题是-有人知道如何中心的xticks?
我在努力寻找解决办法,但还没有找到

m3eecexj

m3eecexj1#

matplotlib 3.4.0或更高版本中,可以使用bar_label代替annotate

import numpy as np
from matplotlib import pyplot as plt

years = [1901, 1911, 1921, 1931, 1941, 1951, 1961, 1971, 1981, 1991, 2001, 2011]
population = [237.4, 238.4, 252.09, 251.31, 278.98, 318.66, 361.09, 439.23,
              548.16, 683.33, 846.42, 1028.74]

# Create Tick Locations
x = np.arange(len(years))
# Plotting
fig, ax = plt.subplots(figsize=(10, 6))
# Do not offset the values of x to center labels (default)
ax.bar(x, population, width=.35, label='population')

# Labels, ticks, etc.
ax.set_ylabel('Population(in million)')
ax.set_title('Years')
ax.set_xticks(x)
ax.set_xticklabels(years)

# Add Bar Labels
for c in ax.containers:
    ax.bar_label(c)

plt.show()

6tdlim6h

6tdlim6h2#

imo教程使绘图变得比它需要的更混乱。你很少需要从图中的艺术家那里获取坐标。直接使用您的数据:

from matplotlib import pyplot as plt
import numpy as np

years = [1901, 1911, 1921, 1931, 1941, 1951, 1961, 1971, 1981, 1991, 2001, 2011]
population = [237.4, 238.4, 252.09, 251.31, 278.98, 318.66, 361.09, 439.23, 548.16, 683.33, 846.42, 1028.74]

x_values = np.arange(len(years))
fig, ax = plt.subplots(figsize=(12, 4))

ax.bar(x_values, population, width=.35, label='population')
for x, y in zip(x_values, population):    
    ax.annotate(
        str(y),        # label is our y-value as a string
        xy=(x, y),
        xytext=(0, 3), # 3 points vertical offset
        textcoords="offset points",
        ha='center', 
        va='bottom'
    )
    
    
ax.set_xticks(x_values)
ax.set_xticklabels(years)
ax.set_ylim(0, 1200)

plt.show()

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