Copy pandas dataframe to excel using openpyxl

Question

I have some complicated formating saved in a template file into which I need to save data from a pandas dataframe. Problem is when I use pd.to_excel to save to this worksheet, pandas overwrites the formatting. Is there a way to somehow 'paste values' form the df into the worksheet? I am using pandas 0.17

import openpyxl
import pandas as pd
wb= openpyxl.load_workbook('H:/template.xlsx')
sheet = wb.get_sheet_by_name('spam')
sheet.title = 'df data'
wb.save('H:/df_out.xlsx')

xlr = pd.ExcelWriter('df_out.xlsx')
df.to_excel(xlr, 'df data')
xlr.save()

Answer 1

openpyxl 2.4 comes with a utility for converting Pandas Dataframes into something that openpyxl can work with directly. Code would look a bit like this:

from openpyxl.utils.dataframe import dataframe_to_rows
rows = dataframe_to_rows(df)

for r_idx, row in enumerate(rows, 1):
    for c_idx, value in enumerate(row, 1):
         ws.cell(row=r_idx, column=c_idx, value=value)

You can adjust the start of the enumeration to place the cells where you need them.

See openpyxl documentation for more information.

Answer 2

I slightly modified @CharlieClark's great answer to avoid the index (which is not there in the original Excel file). Here is a ready-to-run code:

import pandas as pd
from openpyxl.utils.dataframe import dataframe_to_rows
from openpyxl import load_workbook
wb = load_workbook('test.xlsx')  # load as openpyxl workbook; useful to keep the original layout
                                 # which is discarded in the following dataframe
df = pd.read_excel('test.xlsx')  # load as dataframe (modifications will be easier with pandas API!)
ws = wb.active
df.iloc[1, 1] = 'hello world'    # modify a few things
rows = dataframe_to_rows(df, index=False)
for r_idx, row in enumerate(rows, 1):
    for c_idx, value in enumerate(row, 1):
        ws.cell(row=r_idx, column=c_idx, value=value)
wb.save('test2.xlsx')

Answer 3

Here is the solution for you using clipboard:

import openpyxl
import pandas as pd
import clipboard as clp

#Copy dataframe to clipboard
df.to_clipboard()
#paste the clipboard to a valirable
cells = clp.paste()
#split text in varialble as rows and columns
cells = [x.split() for x in cells.split('\n')]

#Open the work book
wb= openpyxl.load_workbook('H:/template.xlsx')
#Get the Sheet
sheet = wb.get_sheet_by_name('spam')
sheet.title = 'df data'
#Paste clipboard values to the sheet
for i, r in zip(range(1,len(cells)), cells):
    for j, c in zip(range(1,len(r)), r):
        sheet.cell(row = i, column = j).value = c
#Save the workbook
wb.save('H:/df_out.xlsx')

Answer 4

you shoud to get your data shap first to determine the range of loop

wb_formats=load_workbook("template.xlsx")            
ws_index=wb_formats.get_sheet_by_name("index")
daily_input= pd.read_excel(self.readfile,"input")
list_item=data_analysis1.groupby(["item_id"])["product_name"].unique()
list_item_size=pd.DataFrame(list_item,columns=["product_name"]).shape[0]

#create  the index sheet:
            r = 2  # start at 4th row
            c = 1 # column 'a'
            for row in range(0,list_item_size):  
                rows = list_item.iloc[row]
                for item in rows:
                    ws_index.cell(row=r, column=c).value = item
                    c += 1 # Column 'd'
                c = 1
                r += 1
wb_formats.save(save_name)