分組條形圖熊貓

Question

我有熊貓數據幀「東風」

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

什麼，我找現在是繪製分組棒形圖我的表 的意見（平均，最大值，最小值）並在一張單獨的條形圖中下單。

即在x軸上將存在視圖和訂單，距離 和3個條（avg，max，min）對視圖和訂單類似。

我附加了一個示例條形圖圖像，以瞭解條形圖的外觀。

綠色應該是平均，黃色代表最大和粉紅色的AVG

我把下面的代碼從setting spacing between grouped bar plots in matplotlib但它不是爲我工作

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) 

Answer 1

使用熊貓：

import pandas as pd 

# 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()