我有以下資料集：
df=pd.read_csv('https://raw.githubusercontent.com/michalis0/DataMining_and_MachineLearning/master/data/sales.csv')
我想按客戶 ( Segment)型別可視化平均銷售額。
我用這個計算了細分市場的平均銷售額：
average_sales = df.groupby(['Segment','OrderYear'],as_index=True)['Sales'].agg({"mean"})
print(average_sales)
我得到以下輸出：
mean
Segment OrderYear
Consumer 2015 251.633302
2016 238.200804
2017 223.269145
2018 200.469005
Corporate 2015 212.641424
2016 189.902305
2017 263.348456
2018 243.634951
Home Office 2015 290.234240
2016 222.101830
2017 226.382196
2018 242.532951
現在我想將它繪制在一個折線圖中，x_axis 上的年份和 y_axis 上的平均銷售額，但每次我嘗試時，我只得到一條線，mean而我想要一條線Segment。一行表示“消費者”，一行表示“公司”，一行表示“內政部”。我認為這可能是因為 Segment 是一個索引而不是一個列，但我仍然無法按段繪制。
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Order Date,Segment,Sales 08/04/2018,Home Office,195.76 23/05/2015,Consumer,17.96 01/12/2018,Consumer,406.368 26/03/2016,Consumer,40.032 04/11/2015,Corporate,8.376 14/11/2017,Consumer,48.576 08/05/2017,Consumer,10.368 25/11/2015,Consumer,539.92 17/06/2017,Consumer,319.41 14/01/2015,Corporate,61.96 01/12/2018,Consumer,105.584 24/11/2016,Consumer,91.392 12/07/2015,Consumer,123.136 26/01/2018,Consumer,11.84 01/03/2015,Consumer,137.352 06/12/2016,Consumer,19.92 07/04/2017,Consumer,3.64 17/09/2016,Consumer,4228.704 29/09/2018,Home Office,7.968 17/08/2018,Corporate,2518.29 04/11/2015,Home Office,275.94 20/06/2017,Consumer,17.712 09/09/2018,Consumer,6.56 03/03/2017,Corporate,563.43 11/10/2017,Consumer,27.72 08/12/2018,Consumer,19.44 01/06/2015,Home Office,47.88 28/10/2017,Corporate,756.8 31/07/2016,Consumer,2309.65 08/11/2016,Corporate,4.712 20/10/2016,Corporate,16.02 23/12/2018,Corporate,367.96 15/02/2016,Corporate,134.97 29/12/2015,Consumer,23.976 05/10/2018,Home Office,39.92 25/06/2016,Home Office,31.104 28/10/2017,Consumer,47.952 25/09/2015,Home Office,3.264 18/12/2016,Corporate,18.432 07/09/2018,Consumer,25.16 26/06/2017,Home Office,8.02 16/06/2018,Consumer,18.54 06/12/2016,Consumer,198.272 04/05/2018,Corporate,9.396 23/10/2018,Consumer,10.272 21/02/2017,Corporate,39.98 22/07/2015,Home Office,19.68 29/09/2018,Home Office,27.968 03/08/2015,Consumer,218.75 07/10/2018,Home Office,18.936 18/04/2016,Consumer,115.44 04/04/2016,Consumer,644.076 03/07/2018,Home Office,24.56 10/11/2016,Consumer,577.584 12/05/2018,Consumer,87.4 21/02/2017,Home Office,3.762 18/08/2018,Consumer,21.38 13/07/2016,Consumer,11.808 17/12/2018,Consumer,66.284 02/12/2015,Corporate,58.36 01/12/2015,Consumer,45.84 23/05/2016,Home Office,850.5 14/10/2015,Corporate,22.92 23/10/2018,Corporate,11.56 20/07/2015,Corporate,41.94 16/06/2016,Consumer,133.98 02/09/2015,Consumer,21.24 11/11/2017,Corporate,95.968 03/10/2015,Home Office,6.192 19/11/2018,Consumer,25.06 25/08/2015,Consumer,40.096 29/12/2018,Consumer,34.58 05/12/2018,Consumer,11.07 23/07/2017,Consumer,4.448 05/03/2016,Consumer,11.212 09/06/2015,Consumer,911.424 21/11/2016,Consumer,10.92 13/02/2018,Consumer,10.71 27/04/2016,Consumer,1379.92 30/10/2018,Home Office,33.94 08/08/2016,Consumer,447.86 07/12/2016,Consumer,79.92 21/08/2018,Corporate,33.18 26/01/2015,Home Office,19.44 09/06/2015,Consumer,1706.184 26/09/2016,Consumer,79.056 05/04/2016,Home Office,547.136 27/10/2018,Corporate,5.607 03/07/2016,Consumer,294.93 16/11/2015,Home Office,169.45 08/12/2015,Corporate,60.416 23/11/2016,Consumer,16.56 05/10/2018,Home Office,75.792 19/03/2016,Consumer,17.568 21/08/2017,Corporate,2887.056 25/04/2016,Corporate,21.34 14/05/2017,Corporate,4.768 03/11/2016,Home Office,42.6 21/10/2017,Consumer,22.92 10/07/2018,Corporate,41.91 16/11/2018,Consumer,811.28 17/09/2018,Corporate,10.776 01/12/2018,Home Office,62.958 07/12/2018,Consumer,374.376 19/11/2018,Consumer,821.88 16/06/2018,Consumer,23.92 19/05/2017,Consumer,242.9 06/06/2017,Corporate,105.52 05/12/2015,Corporate,29.94 12/08/2018,Consumer,299.99 08/04/2018,Home Office,41.95 04/10/2015,Consumer,95.648 25/11/2017,Consumer,194.352 18/09/2016,Corporate,11.68 20/12/2016,Home Office,11.696 24/04/2017,Consumer,3.984 14/05/2015,Corporate,310.88 22/09/2015,Consumer,579.528 02/05/2015,Consumer,26.136 19/08/2015,Corporate,69.456 08/07/2018,Corporate,28.91 26/11/2015,Corporate,7.312 24/06/2018,Consumer,21.744 12/11/2018,Consumer,221.024 27/08/2016,Consumer,3.08 18/11/2018,Consumer,127.386 21/11/2016,Corporate,246.1328 12/05/2017,Consumer,120.0 30/12/2017,Home Office,481.32 20/07/2016,Consumer,913.43 23/11/2018,Corporate,10.688 23/04/2015,Home Office,22.336 17/09/2016,Consumer,3.264 20/10/2016,Consumer,24.56 04/06/2017,Consumer,14.94 19/11/2016,Consumer,5.984 30/07/2016,Consumer,209.93 17/09/2016,Consumer,110.96 12/10/2016,Consumer,263.96 02/09/2017,Consumer,65.94 12/10/2016,Consumer,81.96 14/05/2016,Home Office,198.272 09/12/2018,Corporate,37.208 23/05/2017,Consumer,122.382 23/09/2018,Consumer,199.95 28/12/2015,Corporate,704.25 19/01/2018,Consumer,6.0 12/10/2016,Home Office,19.9 14/11/2016,Corporate,37.0 03/10/2018,Home Office,6.63 20/07/2015,Consumer,104.85 10/09/2015,Consumer,1487.04 12/10/2018,Corporate,39.984 23/12/2015,Corporate,56.52 17/11/2016,Consumer,106.32 18/03/2015,Home Office,1856.19 01/09/2016,Home Office,1088.76 05/07/2016,Home Office,19.0 03/11/2015,Home Office,6.72 28/05/2017,Consumer,22.72 13/06/2018,Home Office,164.736 26/09/2016,Consumer,239.8 12/10/2018,Consumer,17.9 02/10/2018,Corporate,21.984 12/11/2018,Home Office,23.12 21/01/2018,Home Office,242.94 09/08/2015,Consumer,2060.744 25/04/2016,Consumer,128.058 04/03/2018,Corporate,15.25 04/08/2017,Home Office,35.06 18/12/2016,Corporate,55.936 19/12/2016,Consumer,675.96 12/07/2016,Consumer,659.168 06/04/2015,Corporate,70.95 19/05/2018,Home Office,681.408 09/07/2016,Consumer,153.36 21/08/2016,Home Office,4.28 22/05/2018,Consumer,22.344 26/08/2015,Consumer,17.34 19/09/2016,Corporate,66.36 06/11/2018,Home Office,449.568 21/11/2017,Consumer,21.568 24/12/2017,Home Office,27.882 09/07/2015,Home Office,23.92 05/08/2016,Corporate,33.488 20/11/2017,Consumer,2.628 07/03/2015,Corporate,481.568 25/11/2017,Consumer,59.98 14/07/2018,Consumer,276.69 03/10/2015,Consumer,14.48 28/07/2017,Home Office,302.72 05/09/2017,Corporate,43.6 16/03/2016,Home Office,17.52 02/09/2017,Home Office,84.272 22/06/2015,Consumer,170.058 08/07/2018,Home Office,86.376 01/11/2016,Home Office,3.168 04/11/2017,Consumer,11.376 18/12/2018,Consumer,46.672 05/12/2017,Consumer,465.18
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