對于表中的每條記錄，我想做一個基于兩個分類列的累積計數。在下表中，我想獲取cum_count列，它是根據列industry和deal_status計算的。這個想法是，對于每條記錄，計算同一行業以前贏得的交易數量。例如，表的最后一個記錄有cum_count = 3，因為只有3涉及deal_status =贏得了業界= X之前已經見過。該大熊貓GroupBy.cumcount功能的確，對于一個變量...對于我描述的案例，我如何才能做到這一點？pd.DataFrame({'time': [1, 2, 3, 4, 5, 6, 7], 'company' : ["ciaA", "ciaB", "ciaA", "ciaC", "ciaA", "ciaD", "ciaE"], 'industry' : ["x", "y", "x", "x", "x", "y", "x"], 'deal_status' : ["won", "lost", "won", "won", "lost", "won", "lost"], 'cum_count' : [0, 0, 1, 2, 3, 0, 3]})time company industry deal_status cum_count 1 ciaA x won 0 2 ciaB y lost 0 3 ciaA x won 1 4 ciaC x won 2 5 ciaA x lost 3 6 ciaD y won 0 7 ciaE x lost 3
1 回答
縹緲止盈
TA貢獻2041條經驗 獲得超4個贊
創建一個輔助列，您將對其進行累計總和。需要在每個組內移動，因為您的計數僅包括之前的獲勝值：
df['to_sum'] = (df.deal_status == 'won').astype(int)
df['cum_count'] = (df.groupby('industry')
.apply(lambda x: x.to_sum.shift(1).cumsum()).fillna(0)
.reset_index(0, drop=True))
輸出df：
time company industry deal_status to_sum cum_count
0 1 ciaA x won 1 0.0
1 2 ciaB y lost 0 0.0
2 3 ciaA x won 1 1.0
3 4 ciaC x won 1 2.0
4 5 ciaA x lost 0 3.0
5 6 ciaD y won 1 0.0
6 7 ciaE x lost 0 3.0
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