如何在Python Plot中将图表数值显示为X.X Million格式

我正在绘制年度乘客量图表，聚合数据为百万级，希望图表中的数值显示为X.X Million格式（例如将65,073,314,271显示为65.1 Million）。当前使用的代码如下：

现有数据处理代码 #

Pax_Major=MajorCarriers.groupby(by=["YEAR"])["PASSENGERS"].sum().reset_index().sort_values(["YEAR"])

现有绘图代码 #

fig, ax = plt.subplots(figsize=(13.33,7.5), dpi = 96)

bar1=ax.bar(Pax_Major["YEAR"], Pax_Major["PASSENGERS"], width=0.6)

ax.set_xlabel('', fontsize=12, labelpad=10)
ax.xaxis.set_label_position("bottom")
ax.xaxis.set_major_formatter(lambda s, i : f'{s:,.0f}')
ax.xaxis.set_tick_params(pad=2, labelbottom=True, bottom=True, labelsize=12, labelrotation=0)
labels = ["97", "98", "99", "00", "01", "02", "03", "04", "05", "06", "07", "08", "09", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22"]
ax.set_xticks(Pax_Major['YEAR'], labels)
 
ax.set_ylabel('Passengers per year', fontsize=12, labelpad=10)
ax.yaxis.set_label_position("left")
ax.yaxis.set_major_formatter(lambda s, i : f'{s:,.0f}')
ax.yaxis.set_major_locator(MaxNLocator(integer=True))
ax.yaxis.set_tick_params(pad=2, labeltop=False, labelbottom=True, bottom=False, labelsize=12)

ax.bar_label(bar1, labels=[f'{e:,.0f}' for e in Pax_Major['PASSENGERS']], padding=3, color='black', fontsize=8)

colours = ["#bbdefb","#2196f3"]
cmap = mpl.colors.LinearSegmentedColormap.from_list("colour_map", colours, N=256)
norm = mpl.colors.Normalize(Pax_Major['PASSENGERS'].min(), Pax_Major['PASSENGERS'].max())
bar1 = ax.bar(Pax_Major['YEAR'], Pax_Major['PASSENGERS'], color=cmap(norm(Pax_Major['PASSENGERS'])), width=0.6, zorder=2)

当前图表显示完整大数，需修改为X.X Million格式。

要实现X.X Million的显示格式，核心是将原始数值除以1000000后保留1位小数，再拼接"Million"后缀，需要修改y轴刻度格式化器和柱状图标签的逻辑：

1. 修改y轴刻度格式化器 #

替换原有的y轴格式化代码：

ax.yaxis.set_major_formatter(lambda s, i : f'{s/1000000:.1f} Million')

同时移除MaxNLocator的integer=True参数，因为数值已缩小到百万级，无需强制整数刻度：

ax.yaxis.set_major_locator(MaxNLocator())

2. 修改柱状图标签 #

替换原有的bar_label代码：

ax.bar_label(bar1, labels=[f'{e/1000000:.1f} Million' for e in Pax_Major['PASSENGERS']], padding=3, color='black', fontsize=8)

3. 完整修改后的绘图代码 #

import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
import matplotlib as mpl

fig, ax = plt.subplots(figsize=(13.33,7.5), dpi = 96)

# 可选：提前计算百万级数据，减少重复计算
Pax_Major['PASSENGERS_MILLION'] = Pax_Major['PASSENGERS'] / 1000000

bar1=ax.bar(Pax_Major["YEAR"], Pax_Major["PASSENGERS"], width=0.6)

ax.set_xlabel('', fontsize=12, labelpad=10)
ax.xaxis.set_label_position("bottom")
ax.xaxis.set_major_formatter(lambda s, i : f'{s:,.0f}')
ax.xaxis.set_tick_params(pad=2, labelbottom=True, bottom=True, labelsize=12, labelrotation=0)
labels = ["97", "98", "99", "00", "01", "02", "03", "04", "05", "06", "07", "08", "09", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22"]
ax.set_xticks(Pax_Major['YEAR'], labels)
 
# 可选：更新y轴标签说明单位
ax.set_ylabel('Passengers per year (Million)', fontsize=12, labelpad=10)
ax.yaxis.set_label_position("left")
ax.yaxis.set_major_formatter(lambda s, i : f'{s/1000000:.1f} Million')
ax.yaxis.set_major_locator(MaxNLocator())
ax.yaxis.set_tick_params(pad=2, labeltop=False, labelbottom=True, bottom=False, labelsize=12)

# 使用提前计算的百万级数据
ax.bar_label(bar1, labels=[f'{val:.1f} Million' for val in Pax_Major['PASSENGERS_MILLION']], padding=3, color='black', fontsize=8)

colours = ["#bbdefb","#2196f3"]
cmap = mpl.colors.LinearSegmentedColormap.from_list("colour_map", colours, N=256)
norm = mpl.colors.Normalize(Pax_Major['PASSENGERS'].min(), Pax_Major['PASSENGERS'].max())
bar1 = ax.bar(Pax_Major['YEAR'], Pax_Major['PASSENGERS'], color=cmap(norm(Pax_Major['PASSENGERS'])), width=0.6, zorder=2)

plt.show()

说明 #

• 若想调整小数位数，修改.1f中的数字即可（比如.2f保留两位小数）
• 提前计算PASSENGERS_MILLION列可以避免重复除以1000000的计算，提升代码效率

内容的提问来源于stack exchange，提问作者Astrid T