Grouped Bar graph Pandas

Question

我在名为DataFrame的pandas df中有一张表：

+--- -----+------------+-------------+----------+------------+-----------+
|avg_views| avg_orders | max_views   |max_orders| min_views  |min_orders |
+---------+------------+-------------+----------+------------+-----------+
| 23       | 123       |   135       | 500      |    3       |    1      |
+---------+------------+-------------+----------+------------+-----------+ 

我现在要寻找的是绘制一个显示我的分组条形图 （平均值，最大值，最小值）一个条形图中的视图和订单。

即在x轴上会有视图和命令以距离分隔 和3条（平均值，最大值，最小值）的视图和类似的订单。

我附上了一个示例条形图图像，只是为了了解条形图的外观。

绿色应为平均值，黄色为最大值，粉红色为平均值。

我从setting spacing between grouped bar plots in matplotlib获取了以下代码，但它对我不起作用：

plt.figure(figsize=(13, 7), dpi=300)

groups = [[23, 135, 3], [123, 500, 1]]
group_labels = ['views', 'orders']
num_items = len(group_labels)
ind = np.arange(num_items)
margin = 0.05
width = (1. - 2. * margin) / num_items

s = plt.subplot(1, 1, 1)
for num, vals in enumerate(groups):
    print 'plotting: ', vals
    # The position of the xdata must be calculated for each of the two data 
    # series.
    xdata = ind + margin + (num * width)
    # Removing the "align=center" feature will left align graphs, which is 
    # what this method of calculating positions assumes.
    gene_rects = plt.bar(xdata, vals, width)
s.set_xticks(ind + 0.5)
s.set_xticklabels(group_labels)

  

密谋：[23,135,3]   ...   ValueError：形状不匹配：无法将对象广播为单个形状

Answer 1

使用pandas：

import pandas as pd

groups = [[23,135,3], [123,500,1]]
group_labels = ['views', 'orders']

# Convert data to pandas DataFrame.
df = pd.DataFrame(groups, index=group_labels).T

# Plot.
pd.concat(
    [df.mean().rename('average'), df.min().rename('min'), 
     df.max().rename('max')],
    axis=1).plot.bar()

Answer 2

您不必只是为了以某种方式绘制数据框就可以修改数据框吗？

使用seaborn！

import seaborn as sns


sns.catplot(x = "x",       # x variable name
            y = "y",       # y variable name
            hue = "type",  # group variable name
            data = df,     # dataframe to plot
            kind = "bar")

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