分組條形圖 Pandas

Question

我在一個名為df DataFrame有一個表：

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

我現在正在尋找的是繪制一個分組條形圖，它在一個條形圖中向我顯示（平均、最大、最小）視圖和訂單。

即在 x 軸上，視圖和訂單將被分開的距離和 3 條（平均、最大值、最小值）用於視圖和類似的訂單。

我附上了一個示例條形圖圖像，只是為了了解條形圖的外觀。

綠色應該代表平均值，黃色代表最大值，粉紅色代表平均值。

我從在 matplotlib 中設置分組條形圖之間的間距中獲取了以下代碼，但它對我不起作用：

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)

繪圖：[23, 135, 3] ... ValueError：形狀不匹配：對象不能廣播到單個形狀

Answer 1

使用熊貓：

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

您不必為了以某種方式繪制它而修改您的數據框，對嗎？

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")

來源