我想创建一个函数来缩短下面的查询
查询:
SELECT
CASE
WHEN SUBS_ARPU_M1 IS NULL
THEN 'Missing'
WHEN SUBS_ARPU_M1 > 0 AND SUBS_ARPU_M1 <= 5
THEN '> 0 - <= 5'
WHEN SUBS_ARPU_M1 > 5 AND SUBS_ARPU_M1 <= 12
THEN '>
我有一个包含几个列的CSV文件,我想编写一个代码,它将读取一个名为'ARPU平均6个月w/t漫游和折扣‘的特定列,然后创建一个名为"Logical“的新列,该列将基于numpy.where()。我现在得到的是:
csv_data = pd.read_csv("Results.csv")
data = csv_data[['ARPU average 6 month w/t roaming and discount']]
data = data.to_numpy()
sol = []
for target in data:
if1 = n
我有一个包含几个列的CSV文件,我想编写一个代码,它将读取一个名为'ARPU平均6个月w/t漫游和折扣‘的特定列,然后创建一个名为"Logical“的新列,该列将基于numpy.where()。我现在得到的是:
csv_data = pd.read_csv("Results.csv")
data = csv_data[['ARPU average 6 month w/t roaming and discount']]
data = data.to_numpy()
sol = []
for target in data:
if1 = n
data,这是输出- DataFrame[features: vector, label: int]
我是如何得到“数据”的
import pyspark.sql.functions as F
from pyspark.ml.feature import VectorAssembler
...
cols = [F.col(field[0]).cast('double') if field[1] == 'int' else F.col(field[0]) for field in cdr.dtypes]
cdr = cdr.select(cols)
cdr.pri
我遇到了一些我无法解释的怪事。
我使用以下查询:
MERGE INTO Main_Table t
USING Stg_Table s
ON(s.site_id = t.site_id)
WHEN MATCHED THEN
UPDATE SET t.arpu_prev_period = s.arpu_prev_period
.... --50 more columns
where t.period_code = 201612
Stg_Table :索引(Site_Id)
Main_Table:
索引(Period_code,Site_id
尝试执行以下查询时,我遇到无效的标识符异常。
查询:
SELECT bill_start_date AS "Bill Start Date",
bill_end_date AS "Bill End Date",
usage_category AS "Usage Category",
SUM(monthly_charges)
我一直在到处寻找答案,但我在VBA中的低水平技能真的不能帮助我弄清楚我想要编写的代码。
到目前为止,我有以下代码:
Sub ADOFromExcelToAccess()
' exports data from the active worksheet to a table in an Access database
' this procedure must be edited before use
Dim cn As ADODB.Connection, rs As ADODB.Recordset, r As Long
' connect to the Access d