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python - 如何将 seaborn/matplotlib 轴刻度标签从数字格式化为数千或数百万? (125,436 至 125.4K)

转载 作者:太空狗 更新时间:2023-10-29 21:23:20 29 4
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import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import seaborn as sns
import pandas as pd
sns.set(style="darkgrid")
fig, ax = plt.subplots(figsize=(8, 5))
palette = sns.color_palette("bright", 6)
g = sns.scatterplot(ax=ax, x="Area", y="Rent/Sqft", hue="Region", marker='o', data=df, s=100, palette= palette)
g.legend(bbox_to_anchor=(1, 1), ncol=1)
g.set(xlim = (50000,250000))

enter image description here

如何将轴格式从数字更改为自定义格式?例如,125000 到 125.00K

最佳答案

IIUC 你可以格式化 xticks 并设置这些:

In[60]:
#generate some psuedo data
df = pd.DataFrame({'num':[50000, 75000, 100000, 125000], 'Rent/Sqft':np.random.randn(4), 'Region':list('abcd')})
df

Out[60]:
num Rent/Sqft Region
0 50000 0.109196 a
1 75000 0.566553 b
2 100000 -0.274064 c
3 125000 -0.636492 d

In[61]:
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import seaborn as sns
import pandas as pd
sns.set(style="darkgrid")
fig, ax = plt.subplots(figsize=(8, 5))
palette = sns.color_palette("bright", 4)
g = sns.scatterplot(ax=ax, x="num", y="Rent/Sqft", hue="Region", marker='o', data=df, s=100, palette= palette)
g.legend(bbox_to_anchor=(1, 1), ncol=1)
g.set(xlim = (50000,250000))
xlabels = ['{:,.2f}'.format(x) + 'K' for x in g.get_xticks()/1000]
g.set_xticklabels(xlabels)

Out[61]:

enter image description here

这里的关键是这一行:

xlabels = ['{:,.2f}'.format(x) + 'K' for x in g.get_xticks()/1000]
g.set_xticklabels(xlabels)

所以这会将所有刻度除以 1000 然后格式化它们并设置 xtick 标签

更新感谢@ScottBoston 提出了更好的方法:

ax.xaxis.set_major_formatter(ticker.FuncFormatter(lambda x, pos: '{:,.2f}'.format(x/1000) + 'K'))

参见 docs

关于python - 如何将 seaborn/matplotlib 轴刻度标签从数字格式化为数千或数百万? (125,436 至 125.4K),我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/53747298/

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