我將參數作為python Pandas中的dict傳遞參數后，read_sql查詢返回空數據幀

Question

我正在嘗試使用以下字典來參數化SQL查詢的某些部分：

query_params = dict(
        {'target':'status',
         'date_from':'201712',
         'date_to':'201805',
         'drform_target':'NPA'
      })

sql_data_sample = str("""select *
                                 from table_name
                                     where dt = %(date_to)s
                                     and %(target)s in (%(drform_target)s)

                        ----------------------------------------------------
                        union all
                        ----------------------------------------------------

                        (select *,
                                 from table_name
                                     where dt  = %(date_from)s
                                     and %(target)s in ('ACT')
                                     order by random() limit 50000);""")

df_data_sample = pd.read_sql(sql_data_sample,con = cnxn,params = query_params)

但是，這將返回一個完全沒有記錄的數據框。 我不確定錯誤是什么，因為沒有錯誤被拋出。

df_data_sample.shape
Out[7]: (0, 1211)

最終的PostgreSql查詢將是：

select *
        from table_name
            where dt = '201805'
            and status in ('NPA')

----------------------------------------------------
union all
----------------------------------------------------
(select *
        from table_name
            where dt  = '201712'
            and status in ('ACT')
            order by random() limit 50000);-- This part of random() is only for running it on my local and not on server.

以下是用於復制的一小部分數據示例。 原始數據有超過一百萬條記錄和1211列

service_change_3m   service_change_6m   dt  grp_m2          status
0                   -2                  201805  $50-$75     NPA
0                    0                  201805  < $25       NPA
0                   -1                  201805  $175-$200   ACT
0                    0                  201712  $150-$175   ACT
0                    0                  201712  $125-$150   ACT
-1                   1                  201805  $50-$75     NPA

有人可以幫我嗎？

更新：根據@shmee的建議。我最終使用：

target = 'status'
query_params = dict(
        {
         'date_from':'201712',
         'date_to':'201805',
         'drform_target':'NPA'
      })

sql_data_sample = str("""select *
                                 from table_name
                                     where dt = %(date_to)s
                                     and {0} in (%(drform_target)s)

                        ----------------------------------------------------
                        union all
                        ----------------------------------------------------

                        (select *,
                                 from table_name
                                     where dt  = %(date_from)s
                                     and {0} in ('ACT')
                                     order by random() limit 50000);""").format(target)

df_data_sample = pd.read_sql(sql_data_sample,con = cnxn,params = query_params)

Answer 1

是的，我非常有信心，您的問題是由於試圖通過注釋中提到的參數綁定（ and %(target)s in ('ACT')嘗試在查詢中設置列名而導致的。

這導致查詢將結果集限制為記錄'status' in ('ACT')中的'status' in ('ACT')所在的位置（即字符串'status'是僅包含字符串'ACT'的列表的元素）。 當然，這是錯誤的，因此不會選擇任何記錄，並且結果為空。

這應該可以正常工作：

import psycopg2.sql

col_name = 'status'
table_name = 'public.churn_data'
query_params = {'date_from':'201712',
                'date_to':'201805',
                'drform_target':'NPA'
               }

sql_data_sample = """select * 
                     from {0} 
                     where dt = %(date_to)s 
                     and {1} in (%(drform_target)s)
                     ----------------------------------------------------
                     union all
                     ----------------------------------------------------
                     (select * 
                      from {0} 
                      where dt  = %(date_from)s 
                      and {1} in ('ACT') 
                      order by random() limit 50000);"""

sql_data_sample = sql.SQL(sql_data_sample).format(sql.Identifier(table_name), 
                                                  sql.Identifier(col_name))

df_data_sample = pd.read_sql(sql_data_sample,con = cnxn,params = query_params)