@@ -129,6 +129,29 @@ pd.pivot_table(df, index=['A', 'B'], columns=['C'], values=['D','E'], aggfunc={'
129129pd.pivot_table(df, index = [' A' ' B' columns = [' C' values = [' D' ' E' aggfunc = {' D' len ,' E'
130130
131131pd.pivot_table(df, index = pd.Grouper(freq = ' M' key = ' F' columns = ' C' values = ' D' aggfunc = np.sum) # 类似 resample
132+ 133+ # 数据透视表复杂操作
134+ pv_x = pd.pivot_table(df, index = [' 商户' ' 状态'
135+ values = [' 金额'
136+ columns = [' 月份'
137+ aggfunc = [np.sum, len ],
138+ fill_value = 0 , margins = True )
139+ pv_x.columns = pv_x.columns.droplevel(level = [1 ])
140+ pv_x = pv_x.rename(columns = {' sum' ' 金额' ' len' ' 件数' level = 0 )
141+ pv_x = pv_x.T.sort_index(level = [1 ,0 ],ascending = [1 ,0 ]).T # 按列名排序
142+ pv_x.rename({' All' ' 合计' axis = 1 , inplace = True )
143+ pv_x.rename({' All' ' 合计' level = 0 , inplace = True )
144+ pv_x.rename({' ' ' 合计' level = 1 , inplace = True )
145+ pv_x.reindex(index = [(' 商户A' ' 状态1'
146+ (' 商户A' ' 状态2'
147+ (' 商户A' ' 状态3'
148+ (' 商户B' ' 状态1'
149+ (' 商户B' ' 状态2'
150+ (' 商户B' ' 状态3' 0 ) # 手动指定多层级排序
151+ pv_x1 = pv_x.iloc[:- 1 ,].reindex(index = [' 状态3' ' 状态2' ' 状态1' ' 合计' level = 1 ) # 按行排序
152+ pv_x2 = pv_x.iloc[- 1 :,]
153+ pv_x = pd.concat([pv_x1, pv_x2], axis = 0 )
154+ pv_x = pv_x.swaplevel(axis = 1 )
132155```
133156
134157<br />
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