在使用pandas和matplotlib绘制条形图的同时，如何删除条之间的空间？

Question

我有一个pandas dataframe df，如下所示：

Base    Current level   New fan New refrigerator    Unplug unused appliances    Run washing machine with full load  Fix leakages    After three months  Install smart thermostat    Replace light bulbs with LED lights Replace desktop with laptop After six months
0   0   150.0   0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1   150 0.0 10.0    0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2   160 0.0 0.0 15.0    0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
3   160 0.0 0.0 0.0 15.0    0.0 0.0 0.0 0.0 0.0 0.0 0.0
4   145 0.0 0.0 0.0 0.0 15.0    0.0 0.0 0.0 0.0 0.0 0.0
5   140 0.0 0.0 0.0 0.0 0.0 5.0 0.0 0.0 0.0 0.0 0.0
6   0   0.0 0.0 0.0 0.0 0.0 0.0 140.0   0.0 0.0 0.0 0.0
7   115 0.0 0.0 0.0 0.0 0.0 0.0 0.0 25.0    0.0 0.0 0.0
8   105 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.0    0.0 0.0
9   95  0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.0    0.0
10  0   0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 95.0

df.to_dict（）供参考：

{'Base': {0: 0,
  1: 150,
  2: 160,
  3: 160,
  4: 145,
  5: 140,
  6: 0,
  7: 115,
  8: 105,
  9: 95,
  10: 0},
 'Current level': {0: 150.0,
  1: 0.0,
  2: 0.0,
  3: 0.0,
  4: 0.0,
  5: 0.0,
  6: 0.0,
  7: 0.0,
  8: 0.0,
  9: 0.0,
  10: 0.0},
 'New fan': {0: 0.0,
  1: 10.0,
  2: 0.0,
  3: 0.0,
  4: 0.0,
  5: 0.0,
  6: 0.0,
  7: 0.0,
  8: 0.0,
  9: 0.0,
  10: 0.0},
 'New refrigerator': {0: 0.0,
  1: 0.0,
  2: 15.0,
  3: 0.0,
  4: 0.0,
  5: 0.0,
  6: 0.0,
  7: 0.0,
  8: 0.0,
  9: 0.0,
  10: 0.0},
 'Unplug unused appliances': {0: 0.0,
  1: 0.0,
  2: 0.0,
  3: 15.0,
  4: 0.0,
  5: 0.0,
  6: 0.0,
  7: 0.0,
  8: 0.0,
  9: 0.0,
  10: 0.0},
 'Run washing machine with full load': {0: 0.0,
  1: 0.0,
  2: 0.0,
  3: 0.0,
  4: 15.0,
  5: 0.0,
  6: 0.0,
  7: 0.0,
  8: 0.0,
  9: 0.0,
  10: 0.0},
 'Fix leakages': {0: 0.0,
  1: 0.0,
  2: 0.0,
  3: 0.0,
  4: 0.0,
  5: 5.0,
  6: 0.0,
  7: 0.0,
  8: 0.0,
  9: 0.0,
  10: 0.0},
 'After three months': {0: 0.0,
  1: 0.0,
  2: 0.0,
  3: 0.0,
  4: 0.0,
  5: 0.0,
  6: 140.0,
  7: 0.0,
  8: 0.0,
  9: 0.0,
  10: 0.0},
 'Install smart thermostat': {0: 0.0,
  1: 0.0,
  2: 0.0,
  3: 0.0,
  4: 0.0,
  5: 0.0,
  6: 0.0,
  7: 25.0,
  8: 0.0,
  9: 0.0,
  10: 0.0},
 'Replace light bulbs with LED lights': {0: 0.0,
  1: 0.0,
  2: 0.0,
  3: 0.0,
  4: 0.0,
  5: 0.0,
  6: 0.0,
  7: 0.0,
  8: 10.0,
  9: 0.0,
  10: 0.0},
 'Replace desktop with laptop': {0: 0.0,
  1: 0.0,
  2: 0.0,
  3: 0.0,
  4: 0.0,
  5: 0.0,
  6: 0.0,
  7: 0.0,
  8: 0.0,
  9: 10.0,
  10: 0.0},
 'After six months': {0: 0.0,
  1: 0.0,
  2: 0.0,
  3: 0.0,
  4: 0.0,
  5: 0.0,
  6: 0.0,
  7: 0.0,
  8: 0.0,
  9: 0.0,
  10: 95.0}}

我想使用此数据绘制瀑布图。为此，我使用下面的代码绘制了一个堆叠的条形图，并使用列base作为底部。

colors = ["royalblue","green","green","red","red","red","royalblue",
        "red","red","red","royalblue"]

fig = df.loc[:,"Current level":].plot(kind = "bar",
                               bottom = df["Base"],
                     
                               color = colors)


selected_patches = fig.patches[0], fig.patches[20], fig.patches[40]


plt.legend(selected_patches, ["Base", "Rise", "Fall"], loc = "upper right")

plt.xticks(ticks = np.arange(0, len(df)), labels = df.columns[1:], rotation = 90)

plt.title("My electricity saving plan")

plt.ylabel("kWh consumption")

这给了我以下情节：

bar图的默认宽度IE 0.8 根据此文档使栏看起来太狭窄。 我可以在绘图时手动增加宽度。例如，当我在上述代码中使用宽度= 20时，如下所示，

fig = df.loc[:,"Current level":].plot(kind = "bar",
                               bottom = df["Base"],
                                      width = 20,
                               color = colors)

我会得到更宽的条形：如图所示：

但是，现在tick和标签的位置被扭曲了。我如何设置条形的宽度，以使条形看起来很宽，杆之间的空间不小或小，X轴中的tick和标签仍然与条形位置相同？

Answer 1

问题在于，X轴中的每个点都在为10个不同条的分配空间。因此，您放置的任何尺寸，您将始终有9个空的空间。相反，您应该在绘制之前重组DF：

import matplotlib.pyplot as plt

colors = ["royalblue","green","green","red","red","red","royalblue",
        "red","red","red","royalblue"]

fig = df.loc[:,"Current level":].T.max(axis=1).plot(kind='bar', bottom=df['Base'], width=1, color=colors)

selected_patches = fig.patches[0], fig.patches[2], fig.patches[4]
plt.legend(selected_patches, ["Base", "Rise", "Fall"], loc = "upper right")

plt.xticks(ticks = np.arange(0, len(df)), labels = df.columns[1:], rotation = 90)

plt.title("My electricity saving plan")

plt.ylabel("kWh consumption")
plt.show()

结果：

请注意，贴片索引也更改了，因为我们没有所有空的空白。