使用matplotlib绘制堆积的条形图,保持使用python时熊猫数据框的顺序

多马

嗨,我有3列的df:“日班”,“状态”,“秒”。

需要使用堆栈条形图可视化此数据,但要保持数据不变。

 Day-Shift   State          seconds
    Day 01-05   A              7439
    Day 01-05   STOPPED        0
    Day 01-05   B              10
    Day 01-05   C              35751
    Night 01-05 C              43200
    Day 01-06   STOPPED        7198
    Day 01-06   F              18
    Day 01-06   A              14
    Day 01-06   A              29301
    Day 01-06   STOPPED        6
    Day 01-06   A              6663
    Night 01-06 A              43200

图表X轴:“ Day-shift”,Y:“ seconds”,color:“ State”“我使用python绘制了堆栈条,但是数据顺序与dataframe中的顺序不同。 在此处输入图片说明

例如:在晚上01-08,需要按照df的顺序绘制此图(停止-> B->运行-> D)。但是图显示D-> Stopped-> B-> Running。有什么方法可以创建与使用matplotlib保持相同数据帧顺序的堆栈栏我以前没有使用过matplotlib。

DF:

df = pd.DataFrame({'Day-Shift': {0: 'Day 01-05',
  1: 'Day 01-05',
  2: 'Day 01-05',
  3: 'Day 01-05',
  4: 'Night 01-05',
  5: 'Day 01-06',
  6: 'Day 01-06',
  7: 'Day 01-06',
  8: 'Day 01-06',
  9: 'Day 01-06',
  10: 'Day 01-06',
  11: 'Night 01-06',
  12: 'Day 01-07',
  13: 'Night 01-07',
  14: 'Night 01-07',
  15: 'Night 01-07',
  16: 'Night 01-07',
  17: 'Night 01-07',
  18: 'Night 01-08',
  19: 'Night 01-08',
  20: 'Night 01-08',
  21: 'Night 01-08',
  22: 'Day 01-08',
  23: 'Day 01-08',
  24: 'Day 01-08',
  25: 'Night 01-09',
  26: 'Night 01-09',
  27: 'Night 01-09',
  28: 'Day 01-09',
  29: 'Day 01-09',
  30: 'Day 01-09',
  31: 'Day 01-09',
  32: 'Day 01-10',
  33: 'Night 01-10',
  34: 'Day 01-11',
  35: 'Day 01-11',
  36: 'Day 01-11',
  37: 'Day 01-11',
  38: 'Day 01-11',
  39: 'Night 01-11',
  40: 'Day 01-12',
  41: 'Night 01-12',
  42: 'Day 01-13',
  43: 'Day 01-13',
  44: 'Day 01-13',
  45: 'Day 01-13',
  46: 'Day 01-13',
  47: 'Day 01-13',
  48: 'Day 01-13',
  49: 'Night 01-13',
  50: 'Day 01-14',
  51: 'Day 01-14',
  52: 'Day 01-14',
  53: 'Day 01-14',
  54: 'Day 01-14',
  55: 'Day 01-14',
  56: 'Day 01-14',
  57: 'Day 01-14',
  58: 'Day 01-14',
  59: 'Night 01-14'},
 'State': {0: 'D',
  1: 'STOPPED',
  2: 'B',
  3: 'A',
  4: 'A',
  5: 'A',
  6: 'A1',
  7: 'A2',
  8: 'A3',
  9: 'A4',
  10: 'B1',
  11: 'B1',
  12: 'B1',
  13: 'B1',
  14: 'B2',
  15: 'STOPPED',
  16: 'RUNNING',
  17: 'B',
  18: 'STOPPED',
  19: 'B',
  20: 'RUNNING',
  21: 'D',
  22: 'STOPPED',
  23: 'B',
  24: 'RUNNING',
  25: 'STOPPED',
  26: 'RUNNING',
  27: 'B',
  28: 'RUNNING',
  29: 'STOPPED',
  30: 'B',
  31: 'D',
  32: 'B',
  33: 'B',
  34: 'B',
  35: 'RUNNING',
  36: 'STOPPED',
  37: 'D',
  38: 'A',
  39: 'A',
  40: 'A',
  41: 'A',
  42: 'A',
  43: 'A1',
  44: 'A2',
  45: 'A3',
  46: 'A4',
  47: 'B1',
  48: 'B2',
  49: 'B2',
  50: 'B2',
  51: 'B',
  52: 'STOPPED',
  53: 'A',
  54: 'A1',
  55: 'A2',
  56: 'A3',
  57: 'A4',
  58: 'B1',
  59: 'B1'},
 'seconds': {0: 7439,
  1: 0,
  2: 10,
  3: 35751,
  4: 43200,
  5: 7198,
  6: 18,
  7: 14,
  8: 29301,
  9: 6,
  10: 6663,
  11: 43200,
  12: 43200,
  13: 5339,
  14: 8217,
  15: 0,
  16: 4147,
  17: 1040,
  18: 24787,
  19: 1500,
  20: 14966,
  21: 1410,
  22: 2499,
  23: 1310,
  24: 39391,
  25: 3570,
  26: 17234,
  27: 47390,
  28: 36068,
  29: 270,
  30: 6842,
  31: 20,
  32: 43200,
  33: 43200,
  34: 2486,
  35: 8420,
  36: 870,
  37: 30,
  38: 31394,
  39: 43200,
  40: 43200,
  41: 43200,
  42: 36733,
  43: 23,
  44: 6,
  45: 4,
  46: 4,
  47: 3,
  48: 6427,
  49: 43200,
  50: 620,
  51: 0,
  52: 4,
  53: 41336,
  54: 4,
  55: 4,
  56: 4,
  57: 23,
  58: 1205,
  59: 43200}})
PieCot

您可以将与每个班次相对应的条形图单独绘制为堆叠条形图,从而将顺序保留在原始数据框中。这里的代码:

# Get all the possible states and associate a color to each of them
all_states = df.State.unique()
cm = plt.get_cmap('tab20')  # you can choose the colormap you want
colors = {
    s: cm(1. * i / len(all_states))  # get a different color for each state, sampling the color map
    for i, s in enumerate(all_states)
}

fig, ax = plt.subplots(1, 1)
day_shifts = df['Day-Shift'].unique()
# Plot the bar of each shift independently, so preserving the order of the stack
for i, d in enumerate(day_shifts):
    total_height = [0]  # total height of the stacked bars so far
    # stack each state on top of the previous ones
    for t in df[df['Day-Shift'] == d].itertuples():
        ax.bar((i,), (t.seconds), bottom=total_height, color=colors[t.State], label=t.State, linewidth=2, edgecolor='w')
        total_height = [total_height[0] + t.seconds]
# Add xticks with labels
ax.set_xticks(list(range(len(day_shifts))))
ax.set_xticklabels(day_shifts, rotation=45, ha='right')

# Create an unique legend, removing duplicates
handles, labels = ax.get_legend_handles_labels()
by_label = OrderedDict(zip(labels, handles))
plt.legend(by_label.values(), by_label.keys(), bbox_to_anchor=(1, 1))

在此处输入图片说明

您必须在代码中添加以下导入:

import matplotlib.pyplot as plt
from collections import OrderedDict

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