我想根據(jù)前一周的銷售額創(chuàng)建另一個(gè)列。這是示例輸入：df = pd.DataFrame({'Week':[1,1,2,2,3,3,4,4,5,5,1,1,2,2,3,3,4,4,5,5], 'Category':['Red','White','Red','White','Red','White','Red','White','Red','White','Red','White','Red','White','Red','White','Red','White','Red','White'], 'id':[1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2], 'Sales':[100,200,300,400,100,200,300,400,100,200,100,200,300,400,100,200,300,400,100,200], 'Sales_others':[10,20,30,40,10,20,30,40,10,20,10,20,30,40,10,20,30,40,10,20]})print(df)基于此，我想創(chuàng)建另一個(gè)列，它只不過是前一周的銷售額。這是所需輸出的示例 df_output = pd.DataFrame({'Week':[1,1,2,2,3,3,4,4,5,5,1,1,2,2,3,3,4,4,5,5], 'Category':['Red','White','Red','White','Red','White','Red','White','Red','White','Red','White','Red','White','Red','White','Red','White','Red','White'], 'id':[1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2], 'Sales':[100,200,300,400,100,200,300,400,100,200,100,200,300,400,100,200,300,400,100,200], 'Sales_others':[10,20,30,40,10,20,30,40,10,20,10,20,30,40,10,20,30,40,10,20], 'Sales_previous_week':[0,0,100,200,300,400,100,200,300,400,0,0,100,200,300,400,100,200,300,400]})print(df_output)我發(fā)現(xiàn)很難創(chuàng)建一個(gè)自我加入的東西。前一周應(yīng)該只受銷售文件的影響，我應(yīng)該能夠保留“sales_others”列--Edit 添加原始代碼CR_UK_NL_Weeklevel['PREVIOUS_WEEK'] = CR_UK_NL_Weeklevel.groupby(['RETAIL_SITE_ID','CATEGORY_NAME'])['CURRENT_WEEK'].shift(fill_value=0)print(CR_UK_NL_Weeklevel)重命名列CR_UK_NL_Weeklevel.columns.values[4] = 'CURRENT_WEEK'CR_UK_NL_Weeklevel.columns.values[3] = 'LAST_YEAR_WEEK'CR_UK_NL_Weeklevel.columns.values嘗試實(shí)施解決方案：CR_UK_NL_Weeklevel['PREVIOUS_WEEK'] = CR_UK_NL_Weeklevel.groupby(['RETAIL_SITE_ID','CATEGORY_NAME'])['CURRENT_WEEK'].shift(fill_value=0)print(CR_UK_NL_Weeklevel)[78]：CR_UK_NL_Weeklevel['PREVIOUS_WEEK'] = CR_UK_NL_Weeklevel.groupby(['RETAIL_SITE_ID','CATEGORY_NAME'])['CURRENT_WEEK'].shift(fill_value=0)print(CR_UK_NL_Weeklevel)
1 回答
牧羊人nacy
TA貢獻(xiàn)1862條經(jīng)驗(yàn) 獲得超7個(gè)贊
如果每周總是有相同的類別并且連續(xù)幾周使用按列DataFrameGroupBy.shift分組：Category
df['Sales_PREVIOUS'] = df.groupby('Category')['Sales'].shift(fill_value=0)
print (df)
Week Category Sales Sales_PREVIOUS
0 1 Red 100 0
1 1 White 200 0
2 2 Red 300 100
3 2 White 400 200
4 3 Red 100 300
5 3 White 200 400
6 4 Red 300 100
7 4 White 400 200
8 5 Red 100 300
9 5 White 200 400
旋轉(zhuǎn)的另一個(gè)想法是 use DataFrame.pivot，然后DataFrame.shift使用DataFrame.stackforSeries和 last add new column by DataFrame.join：
s = df.pivot('Week','Category','Sales').shift(fill_value=0).stack()
df = df.join(s.rename('Sales_PREVIOUS WEEK'), on=['Week','Category'])
編輯：
使用新數(shù)據(jù)添加列id：
df['Sales_PREVIOUS'] = df.groupby(['id','Category'])['Sales'].shift(fill_value=0)
對于第二種解決方案：
s = df.set_index(['Week','id','Category'])['Sales'].unstack([1,2]).shift(fill_value=0).unstack()
df = df.join(s.rename('Sales_PREVIOUS WEEK'), on=['id','Category','Week'])
print (df)
Week Category id Sales Sales_others Sales_PREVIOUS WEEK
0 1 Red 1 100 10 0
1 1 White 1 200 20 0
2 2 Red 1 300 30 100
3 2 White 1 400 40 200
4 3 Red 1 100 10 300
5 3 White 1 200 20 400
6 4 Red 1 300 30 100
7 4 White 1 400 40 200
8 5 Red 1 100 10 300
9 5 White 1 200 20 400
10 1 Red 2 100 10 0
11 1 White 2 200 20 0
12 2 Red 2 300 30 100
13 2 White 2 400 40 200
14 3 Red 2 100 10 300
15 3 White 2 200 20 400
16 4 Red 2 300 30 100
17 4 White 2 400 40 200
18 5 Red 2 100 10 300
19 5 White 2 200 20 400
編輯：
問題在于列名，請使用：
cols = CR_UK_NL_Weeklevel.columns.tolist()
cols[4] = 'CURRENT_WEEK'
cols[3] = 'LAST_YEAR_WEEK'
CR_UK_NL_Weeklevel.columns = cols
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