我有三个串列:x、y 和 w,如图所示:x 是物件的名称。y 是它的高度,w 是它的宽度。
x = ["A","B","C","D","E","F","G","H"]
y = [-25, -10, 5, 10, 30, 40, 50, 60]
w = [30, 20, 25, 40, 20, 40, 40, 30]
我想在 Python 的条形图中绘制这些值,这样 y 代表高度,w 代表条形的宽度。
当我绘制它使用
colors = ["yellow","limegreen","green","blue","red","brown","grey","black"]
plt.bar(x, height = y, width = w, color = colors, alpha = 0.8)
我得到一个如图所示的情节:
接下来,我尝试标准化宽度,以便使用条形图不会相互重叠
w_new = [i/max(w) for i in w]
plt.bar(x, height = y, width = w_new, color = colors, alpha = 0.8)
#plt.axvline(x = ?)
plt.xlim((-0.5, 7.5))
如图所示,我得到了比以前更好的结果:
但是,条形之间的间隙仍然不均匀。比如B和C之间,差距很大。但F和G之间,没有差距。
我想要在两个连续条之间有均匀间隙宽度或没有间隙的图。它看起来应该如图所示:
如何在 Python 中创建这种型别的图?是否可以使用任何资料可视化库,例如 matplotlib、seaborn 或 Plotly?如果资料在资料框中可用,是否还有其他选择?
此外,我想在图的右侧添加 A、B、C 等的标签,而是将条的实际宽度作为 x 轴上的标签(例如,在 x-上面的轴图)。我还想在距离 x 轴 50 处添加一条垂直红线。我知道这可以使用添加plt.axvline(x = ...)
但我不确定我应该宣告为 x 的值是多少,因为 W 的比例与 x 轴的长度不准确。
uj5u.com热心网友回复:
IIUC,你可以试试这样的:
import matplotlib.pyplot as plt
x = ["A","B","C","D","E","F","G","H"]
y = [-25, -10, 5, 10, 30, 40, 50, 60]
w = [30, 20, 25, 40, 20, 40, 40, 30]
colors = ["yellow","limegreen","green","blue","red","brown","grey","black"]
#plt.bar(x, height = y, width = w, color = colors, alpha = 0.8)
xticks=[]
for n, c in enumerate(w):
xticks.append(sum(w[:n]) w[n]/2)
w_new = [i/max(w) for i in w]
a = plt.bar(xticks, height = y, width = w, color = colors, alpha = 0.8)
_ = plt.xticks(xticks, x)
plt.legend(a.patches, x)
输出:
或更改条形宽度的 xticklabels:
xticks=[]
for n, c in enumerate(w):
xticks.append(sum(w[:n]) w[n]/2)
w_new = [i/max(w) for i in w]
a = plt.bar(xticks, height = y, width = w, color = colors, alpha = 0.8)
_ = plt.xticks(xticks, w)
plt.legend(a.patches, x)
输出:
uj5u.com热心网友回复:
我想出了另一种方法来做到这一点。
x = ["A","B","C","D","E","F","G","H"]
y = [-25, -10, 5, 10, 30, 40, 50, 60]
w = [30, 20, 25, 40, 20, 40, 40, 30]
xpos = []
a = 0
for i in range(len(w)):
if i == 0:
a =w[i]
xpos.append(w[i]/2)
else:
a = w[i]
xpos.append(a - w[i]/2)
colors = ["yellow","limegreen","green","blue","red","brown","grey","black"]
fig = plt.bar(xpos,
height = y,
width = w,
color = colors,
alpha = 0.5,
)
plt.xticks(ticks = xpos, labels = w)
plt.xlim((0, 245))
plt.axvline(x = 150)
plt.legend(fig.patches, x)
plt.show()
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