Question

我正在转换Pandas Dataframe中的Oracle SQL外间隔联接。下面是Oracle SQL：

WITH df_interval AS
          (SELECT '1' id,
                     'AAA' interval,
                     1000 begin,
                     2000 end
              FROM DUAL
            UNION ALL
            SELECT '1' id,
                     'BBB' intrvl,
                     2100 begin,
                     3000 end
              FROM DUAL
            UNION ALL
            SELECT '2' id,
                     'CCC' intrvl,
                     3100 begin,
                     4000 end
              FROM DUAL
            UNION ALL
            SELECT '2' id,
                     'DDD' intrvl,
                     4100 begin,
                     5000 end
              FROM DUAL),
      df_point AS
          (SELECT '1' id, 'X1' point, 1100 mid FROM DUAL
            UNION ALL
            SELECT '1' id, 'X2' point, 2050 mid FROM DUAL
            UNION ALL
            SELECT '1' id, 'X3' point, 3200 mid FROM DUAL
            UNION ALL
            SELECT '2' id, 'X4' point, 4200 mid FROM DUAL
            UNION ALL
            SELECT '2' id, 'X5' point, 5500 mid FROM DUAL)
SELECT pt.id,
         point,
         mid,
         interval
  FROM df_interval it RIGHT OUTER JOIN df_point pt ON pt.id = it.id AND pt.mid BETWEEN it.begin AND it.end

我试图创建数据框，但无法像上面的Oracle SQL一样以“ RIGHT OUTER JOIN interval”的身份加入：

import pandas as pd
df_interval = pd.DataFrame({
                   'ID':['1','1','2','2'],
                   'interval': ['AAA', 'BBB', 'CCC', 'DDD'],
                   'begin': [1000,2100,3100,4100],
                   'end': [2000, 3000,4000,5000]})

df_point = pd.DataFrame({
                   'ID':['1','1','1','2','2'],
                   'point': ['X1', 'X2', 'X3', 'X4','X5'],
                   'mid': [1100,2050,3200,4200,5500]})

我希望输出将是这样的：

df_out = pd.DataFrame({
                   'ID':['1','1','1','2','2'],
                   'mid': [1100,2050,3200,4200,5500],
                   'intrvl':['AAA','','','DDD','']})

赞赏有人可以帮助我吗？

Answer 1

我觉得merge_asof非常适合您的情况，只有两次不同，我们需要做两次，当结束和开始合并结果相同时，该间隔应该是匹配的

s1=pd.merge_asof(df_point,df_interval,by='ID',left_on='mid',right_on='end',direction='forward')
s2=pd.merge_asof(df_point,df_interval,by='ID',left_on='mid',right_on='begin',direction='backward')
s1.interval=s1.interval.where(s1.interval==s2.interval)
s1.drop(['end','begin'],1,inplace=True)
s1
  ID point   mid interval
0  1    X1  1100      AAA
1  1    X2  2050      NaN
2  1    X3  3200      NaN
3  2    X4  4200      DDD
4  2    X5  5500      NaN

在Python Pandas Dataframe中转换间隔外部联接SQL

1 个答案: