I have a dataframe like as shown below
Date,cust,region,Abr,Number,
12/01/2010,Company_Name,Somecity,Chi,36,
12/02/2010,Company_Name,Someothercity,Nyc,156,
df = pd.read_clipboard(sep=',')
I would like to write this dataframe to a specific sheet (called temp_data) in the file output.xlsx
Therfore I tried the below
import pandas
from openpyxl import load_workbook
book = load_workbook('output.xlsx')
writer = pandas.ExcelWriter('output.xlsx', engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
I also tried the below
path = 'output.xlsx'
with pd.ExcelWriter(path) as writer:
writer.book = openpyxl.load_workbook(path)
final_df.to_excel(writer, sheet_name='temp_data',startrow=10)
writer.save()
But am not sure whether I am overcomplicating it. I get an error like as shown below. But I verifiedd in task manager, no excel file/task is running
BadZipFile: File is not a zip file
Moreover, I also lose my formatting of the output.xlsx file when I manage to write the file based on below suggestions. I already have a neatly formatted font,color file etc and just need to put the data inside.
Is there anyway to write the pandas dataframe to a specific sheet in an existing excel file? WITHOUT LOSING FORMATTING OF THE DESTIATION FILE
You need to just use to_excel from pandas dataframe.
Try below snippet:
df1.to_excel("output.xlsx",sheet_name='Sheet_name')
If there is existing data please try below snippet:
writer = pd.ExcelWriter('output.xlsx', engine='openpyxl')
# try to open an existing workbook
writer.book = load_workbook('output.xlsx')
df.to_excel(writer,index=False,header=False,startrow=len(reader)+1)
writer.save()
writer.close()
Are you restricted to using pandas or openpyxl?
Because if you're comfortable using other libraries, the easiest way is probably using win32com to puppet excel as if you were a user manually copying and pasting the information over.
import pandas as pd
import io
import win32com.client as win32
import os
csv_text = """Date,cust,region,Abr,Number
12/01/2010,Company_Name,Somecity,Chi,36
12/02/2010,Company_Name,Someothercity,Nyc,156"""
df = pd.read_csv(io.StringIO(csv_text),sep = ',')
temp_path = r"C:\Users\[User]\Desktop\temp.xlsx" #temporary location where to write this dataframe
df.to_excel(temp_path,index = False) #temporarily write this file to excel, change the output path as needed
excel = win32.Dispatch("Excel.Application")
excel.Visible = True #Switch these attributes to False if you'd prefer Excel to be invisible while excecuting this script
excel.ScreenUpdating = True
temp_wb = excel.Workbooks.Open(temp_path)
temp_ws = temp_wb.Sheets("Sheet1")
output_path = r"C:\Users\[User]\Desktop\output.xlsx" #Path to your output excel file
output_wb = excel.Workbooks.Open(output_path)
output_ws = output_wb.Sheets("Output_sheet")
temp_ws.Range('A1').CurrentRegion.Copy(Destination = output_ws.Range('A1')) # Feel free to modify the Cell where you'd like the data to be copied to
input('Check that output looks like you expected\n') # Added pause here to make sure script doesn't overwrite your file before you've looked at the output
temp_wb.Close()
output_wb.Close(True) #Close output workbook and save changes
excel.Quit() #Close excel
os.remove(temp_path) #Delete temporary excel file
Let me know if this achieves what you were after.
I spent all day on this (and a co-worker of mine spent even longer). Thankfully, it seems to work for my purposes - pasting a dataframe into an Excel sheet without changing any of the Excel source formatting. It requires the pywin32 package, which "drives" Excel as if it a user, using VBA.
import pandas as pd
from win32com import client
# Grab your source data any way you please - I'm defining it manually here:
df = pd.DataFrame([
['LOOK','','','','','','','',''],
['','MA!','','','','','','',''],
['','','I pasted','','','','','',''],
['','','','into','','','','',''],
['','','','','Excel','','','',''],
['','','','','','without','','',''],
['','','','','','','breaking','',''],
['','','','','','','','all the',''],
['','','','','','','','','FORMATTING!']
])
# Copy the df to clipboard, so we can later paste it as text.
df.to_clipboard(index=False, header=False)
excel_app = client.gencache.EnsureDispatch("Excel.Application") # Initialize instance
wb = excel_app.Workbooks.Open("Template.xlsx") # Load your (formatted) template workbook
ws = wb.Worksheets(1) # First worksheet becomes active - you could also refer to a sheet by name
ws.Range("A3").Select() # Only select a single cell using Excel nomenclature, otherwise this breaks
ws.PasteSpecial(Format='Unicode Text') # Paste as text
wb.SaveAs("Updated Template.xlsx") # Save our work
excel_app.Quit() # End the Excel instance
In general, when using the win32com approach, it's helpful to record yourself (with a macro) doing what you want to accomplish in Excel, then reading the generated macro code. Often this will give you excellent clues as to what commands you could invoke.
The solution to your problem exists here: How to save a new sheet in an existing excel file, using Pandas?
To add a new sheet from a df:
import pandas as pd
from openpyxl import load_workbook
import os
import numpy as np
os.chdir(r'C:\workdir')
path = 'output.xlsx'
book = load_workbook(path)
writer = pd.ExcelWriter(path, engine = 'openpyxl')
writer.book = book
### replace with your df ###
x = np.random.randn(100, 2)
df = pd.DataFrame(x)
df.to_excel(writer, sheet_name = 'x')
writer.save()
writer.close()
You can try xltpl.
Create a template file based on your output.xlsx file.
Render a file with your data.
from xltpl.writerx import BookWriterx
writer = BookWriterx('template.xlsx')
d = {'rows': df.values}
d['tpl_name'] = 'tpl_sheet'
d['sheet_name'] = 'temp_data'
writer.render_sheet(d)
d['tpl_name'] = 'other_sheet'
d['sheet_name'] = 'other'
writer.render_sheet(d)
writer.save('out.xls')
See examples.
I've spent hours researching this issue but cant seem to find an answer. I have a template in Excel that has conditional formatting already applied to it. I want to import a pandas df into this already formatted excel file so that the data is being formatted accordingly (color, number format, etc.). Does anyone if this is doable? And if so, how?
Ive considered writing a macro and just importing it into python and applying to the df. Just want to see if there's an easier way that I haven't thought of/found. Thanks!
I would advise to try openpyxl
from openpyxl import load_workbook
book = load_workbook(excelpath) # load excel with formats
writer = pandas.ExcelWriter(excelpath, engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
df.to_excel(writer, "Sheet1", columns=['a', 'b'], index=False) # only columns 'a' and 'b' will be populated
writer.save()
I want to overwrite an existing sheet in an excel file with Pandas dataframe but don't want any changes in other sheets of the same file. How this can be achieved.
I tried below code but instead of overwriting, it is appending the data in 'Sheet2'.
import pandas as pd
from openpyxl import load_workbook
book = load_workbook('sample.xlsx')
writer = pd.ExcelWriter('sample.xlsx', engine = 'openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
df.to_excel(writer, 'sheet2', index = False)
writer.save()
I didn't find any other option other than this, this would be a quick solution for you.
I believe still there's no direct way to do this, correct me if I'm wrong. That's the reason we need to play with these logical ways.
import pandas as pd
def write_excel(filename,sheetname,dataframe):
with pd.ExcelWriter(filename, engine='openpyxl', mode='a') as writer:
workBook = writer.book
try:
workBook.remove(workBook[sheetname])
except:
print("Worksheet does not exist")
finally:
dataframe.to_excel(writer, sheet_name=sheetname,index=False)
writer.save()
df = pd.DataFrame({'Col1':[1,2,3,4,5,6], 'col2':['foo','bar','foobar','barfoo','foofoo','barbar']})
write_excel('PRODUCT.xlsx','PRODUCTS',df)
Let me know if you found this helpful, or ignore it if you need any other better solution.
Similar to Gavaert's answer... For Pandas 1.3.5, add the 'if_sheet_exists="replace"' option:
import pandas as pd
with pd.ExcelWriter("file.xlsx", engine="openpyxl", mode="a", if_sheet_exists="replace") as writer:
df.to_excel(writer, 'Logs', index=False)
Since Pandas version 1.3.0 on_sheet_exists is an option of ExcelWriter. It can be used as such:
import pandas as pd
with pd.ExcelWriter("my_sheet.xlsx",engine="openpyxl",mode="a",on_sheet_exists="replace") as writer:
pd.write_excel(writer,df)
Since none of the ExcelWriter methods or properties are public, it is advised to not use them.
I have scripted code for writing pandas df into excel file with openpyxl. See Fill in pd data frame into existing excel sheet (using openpyxl v2.3.2).
from openpyxl import load_workbook
import pandas as pd
import numpy as np
book=load_workbook("excel_proc.xlsx")
writer=pd.ExcelWriter("excel_proc.xlsx", engine="openpyxl")
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
data_df.to_excel(writer, sheet_name="example", startrow=100, startcol=5, index=False)
writer.save()
That procedure works fine. However, each returned excel file reports, when opening, that it is corrupted, since content is not readable. Excel can repair it and save it again. But this has to be done manually. Since I have to process many files, how can i solve/circumvent that?
Alternatively, how do I have to change the code to use "xlsxwriter" instead of "openpyxyl"?
When I just exchange "engine="openpyxl"" with "engine="xlsxwriter"" python tells me that "'Worksheet' object has no attribute 'write'" at the data_df.to_excel line.
Addition: Excel tells me "removed records named range of /xl/workbook.xml part" is the corruption and has to be repaired. I do not know, what it means
I think you'll have to use openpyxl, because xlsxwriter doesn't support yet modifying of existing Excel XLSX files.
From docs:
It cannot read or modify existing Excel XLSX files.
I am trying to use ExcelWriter to write/add some information into a workbook that contains multiple sheets.
First time when I use the function, I am creating the workbook with some data. In the second call, I would like to add some information into the workbook in different locations into all sheets.
def Out_Excel(file_name,C,col):
writer = pd.ExcelWriter(file_name,engine='xlsxwriter')
for tab in tabs: # tabs here is provided from a different function that I did not write here to keep it simple and clean
df = DataFrame(C) # the data is different for different sheets but I keep it simple in this case
df.to_excel(writer,sheet_name = tab, startcol = 0 + col, startrow = 0)
writer.save()
In the main code I call this function twice with different col to print out my data in different locations.
Out_Excel('test.xlsx',C,0)
Out_Excel('test.xlsx',D,10)
But the problem is that doing so the output is just the second call of the function as if the function overwrites the entire workbook. I guess I need to load the workbook that already exists in this case?
Any help?
Use load_book from openpyxl - see xlsxwriter and openpyxl docs:
import pandas as pd
from openpyxl import load_workbook
book = load_workbook('test.xlsx')
writer = pd.ExcelWriter('test.xlsx', engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
df.to_excel(writer, sheet_name='tab_name', other_params)
writer.save()
Pandas version 0.24.0 added the mode keyword, which allows you to append to excel workbooks without jumping through the hoops that we used to have to do. Just use mode='a' to append sheets to an existing workbook.
From the documentation:
with ExcelWriter('path_to_file.xlsx', mode='a') as writer:
df.to_excel(writer, sheet_name='Sheet3')
You could also try using the following method to create your Excel spreadsheet:
import pandas as pd
def generate_excel(csv_file, excel_loc, sheet_):
writer = pd.ExcelWriter(excel_loc)
data = pd.read_csv(csv_file, header=0, index_col=False)
data.to_excel(writer, sheet_name=sheet_, index=False)
writer.save()
return(writer.close())
Give this a try and let me know what you think.