如何使用 pandas 绘制阴影条? [英] How do I plot hatched bars using pandas?
问题描述
我试图通过填充图案而不是(仅)颜色来实现差异化.我如何使用熊猫来做到这一点?
在 matplotlib 中,通过传递 hatch
可选参数是可能的,正如讨论的 .孵化有类似的东西吗?或者我可以通过修改 plot
返回的 Axes
对象来手动设置它?
这有点 hacky 但它有效:
df = pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])ax = plt.figure(figsize=(10, 6)).add_subplot(111)df.plot(ax=ax, kind='bar',legend=False)条 = ax.patches舱口 = ''.join(h*len(df) for h in 'x/O.')对于酒吧,拉链舱口(酒吧,舱口):bar.set_hatch(舱口)ax.legend(loc='center right', bbox_to_anchor=(1, 1), ncol=4)
I am trying to achieve differentiation by hatch pattern instead of by (just) colour. How do I do it using pandas?
It's possible in matplotlib, by passing the hatch
optional argument as discussed here. I know I can also pass that option to a pandas plot
, but I don't know how to tell it to use a different hatch pattern for each DataFrame
column.
df = pd.DataFrame(rand(10, 4), columns=['a', 'b', 'c', 'd'])
df.plot(kind='bar', hatch='/');
For colours, there is the colormap
option described here. Is there something similar for hatching? Or can I maybe set it manually by modifying the Axes
object returned by plot
?
This is kind of hacky but it works:
df = pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])
ax = plt.figure(figsize=(10, 6)).add_subplot(111)
df.plot(ax=ax, kind='bar', legend=False)
bars = ax.patches
hatches = ''.join(h*len(df) for h in 'x/O.')
for bar, hatch in zip(bars, hatches):
bar.set_hatch(hatch)
ax.legend(loc='center right', bbox_to_anchor=(1, 1), ncol=4)
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