如何以Excel形式附加到表格Pandas Dataframe

Question

I am trying to get Python to take a dataframe or 2D numpy array and insert it into an existing table in Excel such that the table expands with my data in the appropriate columns

I tried using xlwings to paste the dataframe into Excel and expand it within the table. Two of my tables expand how I want with the data in the appropriate spot but one of my tables doesn't expands the data as though the table did not exist and continues writing it outside the table. I'm not sure if this has something to do with the problem table having a totals row at the bottom.

import numpy as np
import xlwings as xw

sheet = wb.sheets['sheet1']

"Inserts row of data above last row in table and moves n'th row to n-1'th row"
sheet.range('table1[#Data]').last_cell.api.EntireRow.Insert()
last_row = sheet.range('table1[#Data]).end('down').end('down').row
sheet.range('A{}:F{}'.format(last_row-1, last_row-1)).value = sheet.range('A{}:F{}'.format(last_row, last_row)).value

data = np.array(my_data)
sheet.range('A{}'.format(last_row)).value = data
sheet.range('A{}'.format(last_row)).expand('table')

I was hoping this would expand my 20x6 numpy array into columns A through F in the table but can't seem to get this to work. I'm not sure if there is some easier way of appending this data within the existing table so it expands properly, but I can't figure out how to do this. I'd greatly appreciate any help

Answer 1

It would be better to convert the xlsx file to csv before adding any line.

Then you can open the file for writing and add lines.

cols = ['X1', 'X2', 'X3']
df['Y'] = df[cols].apply(lambda row: ','.join(row.values.astype(str)), axis=1)

with open('your_file.csv','wb') as f:
    for index, row in df.loc[:,Y].iterrows():
        f.write(row)
        f.write('\n')