OpenXml DataValidation set predefined List for columns

=INDEX(Sheet1!$D$2:$D$10,MATCH($A2&"_"&B$1,Sheet1!$A$2:$A$10&"_"&Sheet1!$C$2:$C$10,0))

Sub FillTable()
    Dim rngSource As Range, rngTarget As Range
    Dim lngModeCount As Long, lngChannelCount As Long

    Set rngSource = Range("A2")
    Set rngTarget = Range("rngHeader")

    'Clear old result
    With rngTarget
        If .Offset(1) <> "" And .Offset(, 1) <> "" Then
            .Resize(.End(xlDown).Row - .Row + 1, .End(xlToRight).Column - .Column + 1).Clear
            rngTarget = "(cell is named ""rngHeader"")"
        End If
    End With

    While rngSource.Value <> ""
        If rngSource.Offset(-1) <> rngSource Then
            lngModeCount = lngModeCount + 1
            lngChannelCount = 0
            rngTarget.Offset(lngModeCount) = rngSource
            rngTarget.Offset(lngModeCount).Font.Bold = True
        End If
        lngChannelCount = lngChannelCount + 1
        If lngModeCount = 1 Then
            rngTarget.Offset(, lngChannelCount) = rngSource.Offset(, 2)
            rngTarget.Offset(, lngChannelCount).Font.Bold = True
        End If
        rngTarget.Offset(lngModeCount, lngChannelCount) = rngSource.Offset(, 3)
        Set rngSource = rngSource.Offset(1)
    Wend

End Sub

In [11]: reduce(pd.merge, tmp)
Out[11]:
  Probe Gene    RP1    RP2
0     x  foo   1.00  11.33
1     y  bar  23.22  31.25
2     z  qux  11.12  22.12

tmp[0].merge(tmp[1]).merge(tmp[2])...

DECLARE @sql varchar(500)
DECLARE @column_list varchar(100)
SET @column_list = 'col1, col2, col3'
SET @sql = 'SELECT ' + @column_list + ' FROM table_name';
EXEC (@sql)

DECLARE @sql varchar(1000)
DECLARE @column_list varchar(500)
SET @column_list = 'col1, col2, col3'

SELECT @column_list = 
    STUFF((
        SELECT ',' + COLUMN_NAME
        FROM information_schema.columns
        WHERE table_name = 'yourTable'
        FOR XML PATH(''), TYPE).value('.', 'NVARCHAR(MAX)'), 1, 1, '')

SET @sql = 'SELECT ' + @column_list + ' FROM yourTable';
EXEC (@sql)

L = ['jack', '9860', 'datasc', 'vill','0', 'stack']
df = pd.DataFrame(np.array(L).reshape(-1,3), columns= ['name', 'no','job'])
print (df)
   name    no     job
0  jack  9860  datasc
1  vill     0   stack