for loop through multiple items based on a dataframe

Question

So I have several dataframes of different widths.

I want a for loop that will perform an operation on each dataframe's columns:

Table 1:

col1	col2	col3
Hi	1	Jake
Bye	2	Mike
Red	Blue	Pink

Table 2:

cl1	cl2	cl3	c4
Frank	Toy	Hello	Present
Bike	Ride	Blue	Mike
Red	Blue	Pink	Fred

These tables are in the form a list of tuples.

I want to take these two loops an effectively just have one loop that takes the number of header as the number of items to loop through.

 row = 1
 col = 0

 for col1, col2, col3 in (table):
     worksheet.write(row, col, col1)
     worksheet.write(row, col + 1, col2)
     worksheet.write(row, col + 2, col3)
     row += 1

 row = 1
 col = 0

 for cl1, cl2, cl3, cl4 in (table):
     worksheet.write(row, col, cl1)
     worksheet.write(row, col + 1, cl2)
     worksheet.write(row, col + 2, cl3)
     worksheet.write(row, col + 2, cl3)
     row += 1

Here's what I want

iterate through each column in the table no matter the number of columns. What I think it would look like

row = 1
col = 0

elements = table.column.names
for elements in (table):
    for i in elements:
        worksheet.write(row, col, i)
        col = col +1
    row = row +1

Answer 1

It looks to me that you are looking for something like this:

import pandas as pd
import xlsxwriter

book = xlsxwriter.Workbook('example.xlsx')
worksheet = book.add_worksheet("sheet1")
shape = df2.shape
for col in range(shape[1]):
    for row in range(shape[0]):
        worksheet.write(row, col, df2.iloc[row, col])
book.close()

what generate: