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楼主 |
发表于 2020-4-29 12:10:33
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测试出来了,不过感觉不好,数据量大的时候估计会很慢,请问是否有更好的方法- <pre style="background-color:#ffffff;color:#333333;font-family:'Consolas';font-size:9.8pt;"><span style="color:#a71d5d;">import </span>pandas <span style="color:#a71d5d;">as </span>pd</pre><pre style="background-color:#ffffff;color:#333333;font-family:'Consolas';font-size:9.8pt;">
- </pre>df = pd.DataFrame(table) # 假设表1为table
- df_Row = df .index
- A_mean = []
- B_mean = []
- for i in df_Row:
- x = i + 5
- if x > max(df_Row):
- x = max(df_Row)
- A_mean.append(Rate.loc[i:x, 'A'].mean())
- B_mean.append(Rate.loc[i:x, 'A'].mean())
- df_A = pd.DataFrame(A_mean,columns=['A平均值'])
- df_B = pd.DataFrame(B_mean,columns=['B平均值'])
- df = pd.concat([df, df_A, df_B],axis=1)
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