Iterating over pandas dataframe and saving into separate sheets in xlxs file - excel

Question

I'm iterating over a pandas dataframe during and carry out and operation to obtain the information (excel sheet number) for saving the appropriate excel sheet like this:
from opnepyxl.utils.dataframe import dataframe_to_rows
for i,data in df.iterows:
sheet=data['SheetNo']
#Create excel writer
writer=pd.Excelwriter('output.xlxs')
# write dataframe to excelsheet
data.to_excel(writer, sheet)
#save the excel file
writer.save()
Dataframe:
ID SheetNo setting
2304 2 IGV5
2305 3 IGV2
2306 1 IGV6
2307 2 IGV2
2308 1 IGV1
What I wanted was for data to go into each of the created 'SheetNo' of the excel file, instead the the previous sheet is being overwritten by the following one, and you can only see the last sheet number.
What can I do to make this code work? Any other approach apart from mine above will be welcome.

Answer 1

the python code is below. Note that:
Assumption is that there is already an output.xlsx file in same dir that this code runs
It will search for worksheet names with the SheetNo column. If not available in the file, it will create a new worksheet/tab with that name and add the header row
3.The program will then add each row (append) to the sheet
Once all data in DF is added, it will save file back to same name
You can run this as many times as you want, it will keep adding new sheets or appending to existing sheets.
import pandas as pd
from openpyxl import load_workbook
data = {'ID': [2304,2305,2306,2307,2308],
'SheetNo': [2,3,1,2,1],
'setting': ['IGV5', 'IGV2', 'IGV6', 'IGV2', 'IGV1']}
df = pd.DataFrame(data)
headers = ['ID','SheetNo','setting']
FilePath = 'output.xlsx' #ASSUMPTON - File already exists
wb = load_workbook(FilePath)
for sheet in df.SheetNo.unique():
if str(sheet) in wb.sheetnames: #If sheet in excel file
ws = wb[str(sheet)]
else:
ws = wb.create_sheet(title=str(sheet)) #Create New sheet is not present
ws.append(headers) #New sheet = Need header, else not required
i =0
j = 0
for row in ws.iter_rows(min_row=ws.max_row+1, max_row=ws.max_row+len(df[df.SheetNo == sheet]), min_col=1, max_col=3):
for cell in row:
cell.value = df[df.SheetNo == sheet].iloc[i,j]
j = j + 1
j=0
i= i + 1
wb.save('output.xlsx')
Output excel after one run of the code