注意：我找到了部分解决我的问题的方法，请参阅下面的更新部分。
我目前正在尝试从 3 个单独的列中获取数据并将它们合并到另一个指定的列中。为清楚起见，请参阅下图，其中代码 1、代码 2 和代码 3 在 Merged Code 列中都连接在一起。 期望结果的例子。我写了一个for循环，可以更新指定列中每个单元格的值，请参考下面的代码。
for rows in row_id:
# Build new cell value
new_cell = smartsheet.models.Cell()
new_cell.column_id = column_id_final # column id of previously created column
# A for loop to fill in the rows with information from other rows
for rows in row_id:
new_cell.value = smart.Sheets.get_sheet(1174866712913796)
new_cell.strict = False
在第二个循环的 new_cell.value 部分，我可以简单地输入一个字符串“value”，然后用“value”填充指定列（column_id_final）的所有行。我从这里开始的思考过程是然后努力打印给定行中的所有显示值。鉴于如果我能做到这一点，我可以简单地连接三个变量，每个变量都包含给定列中的所有显示值。请参阅下面的代码以查看我的尝试。
# For loops to extract display values from each cell in a given column
cell_id = ''
row_info = ''
# Get all of the information stored within the rows of a sheet
for row in sheet.rows:
row_info += str(smart.Sheets.get_row(1174866712913796, row.id))
print(row_info)
# pull the display value from each component of the row_info variable
for cell in row_info.cell:
cell_id += string(cell.display_value) #is there a display value property?
print(cell_id)
我遇到的问题是如何显示指定列中所有单元格的值。有没有办法我可以做到这一点？
更新
感谢 Emi 的评论，我研究了 Pandas 并找到了解决我问题的部分方法。我现在可以将我想要的列连接成一个列，将此列上传到 smartsheet，然后将行移动到另一个工作表。但是，当我移动行时，它会将它们发布到目标工作表的底部。我知道这是默认位置，但我不知道移动行功能是否有位置属性。请参阅下面的代码以更好地了解我的过程。
def add_merged_column():
sheet = smart.Sheets.get_sheet(1174866712913796) # store sheet information in sheet variable
col_names = [col.title for col in
sheet.columns] # Define column names for data fram as being equal to the column titles in the sheet information variable
rows = [] # define rows
for row in sheet.rows: # for loop to iterate through the rows of 'sheet' and create a cell list for each
cells = [] # define cells
for cell in row.cells: # for each cell within every row append the updated cell value
cells.append(cell.value)
rows.append(cells)
df = pd.DataFrame(rows, columns=col_names) # create data frame using panda, define columns
df = df.set_index('Unique ID') # get rid of built in index, make desired merged column index
df['Unique ID'] = df['Column 1'].map(str) + ' ' + df['Column 2'].map(str) + ' ' + df['Column 3'].map(
str) # concatenate the desired columns into a single column
merged_data = df['Unique ID'] # assign a variable name to result
merged_data.to_csv(_dir + '\excel\proc_data.csv') # send merged_data to a csv file and specify file path
print(merged_data)
result = smart.Sheets.import_csv_sheet(_dir + '\Excel\proc_data.csv', header_row_index=0) # import newly saved csv file into smartsheet
sheet_csv = smart.Sheets.get_sheet(result.data.id)
################################################################################################################
# iterate through the rows array and build comma-delimited list of row ids
row_ids = '' # define row_id
for row in sheet_csv.rows:
row_ids += str(
row.id) + ', ' # the += adds to the existing variable each iteration, rather than defining an entirely new variable, this is what allows it to be a list, hence the addition of the ','
# x += y is the same as x = x.__iadd__(y)
# remove the final (excess) comma and space from the end of the row_ids string
row_ids = row_ids[
:len(row_ids) - 2] # Specifies that row_ids is not equal to row_ids from index 0 -> length of the ids - 2
row_ids = list(map(int, row_ids.split(',')))
response = smart.Sheets.move_rows(result.data.id, smart.models.CopyOrMoveRowDirective(
{'row_ids': row_ids, 'to': smart.models.CopyOrMoveRowDestination({'sheet_id': 1174866712913796})}))
return merged_data