简而言之:
解释
我正在尝试制作一个堆积条形图,并在其中标记每个条形图中的适当值。但由于某种原因,酒吧的高度是完全错误的。就像第一周一样,绿色条应该是20个点长,但它只有10个。红色条应该是10个点长,但它只有8个左右。第17周应该有多个条形,但只有一个(白色)
我猜测由于条形高度错误,标签也错位了。我不知道为什么最底层的0也显示,但这也是一个问题。
我不知道这些是否都是单独的问题,应该在不同的帖子中提出,但我觉得它们都是相互关联的,并且有一个解决方案可以解决所有问题。
import matplotlib.pyplot as plt
import numpy as np
newYearWeek =[201613, 201614, 201615, 201616, 201617, 201618, 201619, 201620, 201621, 201622]
uniqueNames = ['Word1', 'Word2', 'Word3', 'Word4', 'Word5', 'Word6',
'Word7', 'Word8', 'Word9', 'Word10', 'Word11']
#Each column in the multiarray from top to bottom represents 1 week
#Each row from left to right represents the values of that word.
#So that makes 11 rows and 10 columns.
#And yes the multidimensional array have to be like this with the 0's in it.
keywordsMuliarray = [
[20, 3, 1, 0, 0, 1, 6, 3, 1, 2],
[10, 1, 0, 0, 3, 1, 3, 1, 0, 2],
[2, 2, 5, 3, 5, 4, 5, 4, 3, 2],
[0, 4, 3, 3, 1, 0, 2, 7, 1, 2],
[0, 0, 2, 0, 1, 1, 1, 0, 1, 3],
[0, 0, 3, 2, 0, 0, 0, 1, 0, 0],
[1, 0, 1, 0, 1, 0, 0, 0, 1, 1],
[0, 0, 0, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 7, 6, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 2, 0, 1]]
fig = plt.figure(figsize=(8.5, 5.5))
ax = fig.add_subplot(111)
fig.subplots_adjust(top=0.85)
N = len(newYearWeek)
ind = np.arange(N) # the x locations for the groups
width = 0.35 # the width of the bars: can also be len(x) sequence
colors = ['seagreen', 'indianred', 'steelblue', 'darkmagenta', 'wheat',
'orange', 'mediumslateblue', 'silver',
'whitesmoke', 'black', 'darkkhaki', 'dodgerblue', 'crimson',
'sage', 'navy', 'plum', 'darkviolet', 'lightpink']
def autolabel(rects, values):
# Attach some text labels.
for (rect, value) in zip(rects, values):
ax.text(rect.get_x() + rect.get_width() / 2.,
rect.get_y() + rect.get_height() / 2.,
'%d'%value,
ha = 'center',
va = 'center')
left = np.zeros(len(uniqueNames)) # left alignment of data starts at zero
helpingNumber = 0
for i in range(0, len(newYearWeek)):
rects1 = plt.bar(ind, keywordsMuliarray[helpingNumber][:],width, color=colors[helpingNumber], label=uniqueNames[helpingNumber])
autolabel(rects1, keywordsMuliarray[helpingNumber][:])
helpingNumber = helpingNumber+1
# Shrink current axis by 20%
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 1, box.height])
# Put a legend to the right of the current axis
ax.legend(loc='center left', fontsize=9, bbox_to_anchor=(1, 0.5))
#plt.ylabel('Scores')
plt.xticks(ind + width/2., newYearWeek, fontsize=8)
#plt.yticks(np.arange(0, 81, 10))
plt.margins(x=0.02)
plt.tight_layout(rect=[0,0,0.8,1])
plt.show()
答案 0 :(得分:1)
要制作您想要的内容,您必须在当前列(列表bot_heights
)中总结所有先前小节的高度,如下所示:
import matplotlib.pyplot as plt
import numpy as np
newYearWeek =[201613, 201614, 201615, 201616, 201617, 201618, 201619, 201620, 201621, 201622]
uniqueNames = ['Word1', 'Word2', 'Word3', 'Word4', 'Word5', 'Word6',
'Word7', 'Word8', 'Word9', 'Word10', 'Word11']
#Each column in the multiarray from top to bottom represents 1 week
#Each row from left to right represents the values of that word.
#So that makes 11 rows and 10 columns.
#And yes the multidimensional array have to be like this with the 0's in it.
keywordsMuliarray = [
[20, 3, 1, 0, 0, 1, 6, 3, 1, 2],
[10, 1, 0, 0, 3, 1, 3, 1, 0, 2],
[2, 2, 5, 3, 5, 4, 5, 4, 3, 2],
[0, 4, 3, 3, 1, 0, 2, 7, 1, 2],
[0, 0, 2, 0, 1, 1, 1, 0, 1, 3],
[0, 0, 3, 2, 0, 0, 0, 1, 0, 0],
[1, 0, 1, 0, 1, 0, 0, 0, 1, 1],
[0, 0, 0, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 7, 6, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 2, 0, 1]]
fig = plt.figure(figsize=(8.5, 5.5))
ax = fig.add_subplot(111)
fig.subplots_adjust(top=0.85)
N = len(newYearWeek)
ind = np.arange(N) # the x locations for the groups
width = 0.35 # the width of the bars: can also be len(x) sequence
colors = ['seagreen', 'indianred', 'steelblue', 'darkmagenta', 'wheat',
'orange', 'mediumslateblue', 'silver',
'whitesmoke', 'black', 'darkkhaki', 'dodgerblue', 'crimson',
'sage', 'navy', 'plum', 'darkviolet', 'lightpink']
def autolabel(rects, values):
# Attach some text labels
for (rect, value) in zip(rects, values):
if value > 0:
ax.text(rect.get_x() + rect.get_width() / 2.,
rect.get_y() + rect.get_height() / 2.,
'%d'%value, ha = 'center', va = 'center', size = 9)
left = np.zeros(len(uniqueNames)) # left alignment of data starts at zero
# plot the first bars
rects1 = plt.bar(ind, keywordsMuliarray[0][:],width,
color=colors[0], label=uniqueNames[0])
autolabel(rects1, keywordsMuliarray[0][:])
# put other bars on previuos
bot_heights = [0.] * len(keywordsMuliarray[0][:])
for i in xrange(1,N):
bot_heights = [bot_heights[j] + keywordsMuliarray[i-1][j] for j in xrange(len(bot_heights))]
rects1 = plt.bar(ind, keywordsMuliarray[i][:],width,
color=colors[i], label=uniqueNames[i],
bottom=bot_heights)
autolabel(rects1, keywordsMuliarray[i][:])
# Shrink current axis by 20%
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 1, box.height])
# Put a legend to the right of the current axis
ax.legend(loc='center left', fontsize=9, bbox_to_anchor=(1, 0.5))
#plt.ylabel('Scores')
plt.xticks(ind + width/2., newYearWeek, fontsize=8)
plt.yticks(np.arange(0, 41, 5))
plt.margins(x=0.02)
plt.tight_layout(rect=[0,0,0.8,1])
plt.show()
为防止条形标签重叠,我建议您在值为零时不添加标签(查看修改后的autolabel
功能)。结果我得到了: