Question or problem about Python programming:
It is quite easy to add many pandas dataframes into excel work book as long as it is different worksheets. But, it is somewhat tricky to get many dataframes into one worksheet if you want to use pandas built-in df.to_excel functionality.
# Creating Excel Writer Object from Pandas writer = pd.ExcelWriter('test.xlsx',engine='xlsxwriter') workbook=writer.book worksheet=workbook.add_worksheet('Validation') df.to_excel(writer,sheet_name='Validation',startrow=0 , startcol=0) another_df.to_excel(writer,sheet_name='Validation',startrow=20, startcol=0)
The above code won’t work. You will get the error of
Sheetname 'Validation', with case ignored, is already in use.
Now, I have experimented enough that I found a way to make it work.
writer = pd.ExcelWriter('test.xlsx',engine='xlsxwriter') # Creating Excel Writer Object from Pandas workbook=writer.book df.to_excel(writer,sheet_name='Validation',startrow=0 , startcol=0) another_df.to_excel(writer,sheet_name='Validation',startrow=20, startcol=0)
This will work. So, my purpose of posting this question on stackoverflow is twofold. Firstly, I hope this will help someone if he/she is trying to put many dataframes into a single work sheet at excel.
Secondly, Can someone help me understand the difference between those two blocks of code? It appears to me that they are pretty much the same except the first block of code created worksheet called “Validation” in advance while the second does not. I get that part.
What I don’t understand is why should it be any different ? Even if I don’t create the worksheet in advance, this line, the line right before the last one,
df.to_excel(writer,sheet_name='Validation',startrow=0 , startcol=0)
will create a worksheet anyway. Consequently, by the time we reached the last line of code the worksheet “Validation” is already created as well in the second block of code. So, my question basically, why should the second block of code work while the first doesn’t?
Please also share if there is another way to put many dataframes into excel using the built-in df.to_excel functionality !!
How to solve the problem:
Solution 1:
To create the Worksheet in advance, you need to add the created sheet to the sheets
dict:
writer.sheets['Validation'] = worksheet
Using your original code:
# Creating Excel Writer Object from Pandas writer = pd.ExcelWriter('test.xlsx',engine='xlsxwriter') workbook=writer.book worksheet=workbook.add_worksheet('Validation') writer.sheets['Validation'] = worksheet df.to_excel(writer,sheet_name='Validation',startrow=0 , startcol=0) another_df.to_excel(writer,sheet_name='Validation',startrow=20, startcol=0)
Explanation
If we look at the pandas function to_excel
, it uses the writer’s write_cells
function:
excel_writer.write_cells(formatted_cells, sheet_name, startrow=startrow, startcol=startcol)
So looking at the write_cells
function for xlsxwriter
:
def write_cells(self, cells, sheet_name=None, startrow=0, startcol=0): # Write the frame cells using xlsxwriter. sheet_name = self._get_sheet_name(sheet_name) if sheet_name in self.sheets: wks = self.sheets[sheet_name] else: wks = self.book.add_worksheet(sheet_name) self.sheets[sheet_name] = wks
Here we can see that it checks for sheet_name
in self.sheets
, and so it needs to be added there as well.
Solution 2:
user3817518: “Please also share if there is another way to put many dataframes into excel using the built-in df.to_excel functionality !!”
Here’s my attempt:
Easy way to put together a lot of dataframes on just one sheet or across multiple tabs. Let me know if this works!
— To test, just run the sample dataframes and the second and third portion of code.
Sample dataframes
import pandas as pd import numpy as np # Sample dataframes randn = np.random.randn df = pd.DataFrame(randn(15, 20)) df1 = pd.DataFrame(randn(10, 5)) df2 = pd.DataFrame(randn(5, 10))
Put multiple dataframes into one xlsx sheet
# funtion def multiple_dfs(df_list, sheets, file_name, spaces): writer = pd.ExcelWriter(file_name,engine='xlsxwriter') row = 0 for dataframe in df_list: dataframe.to_excel(writer,sheet_name=sheets,startrow=row , startcol=0) row = row + len(dataframe.index) + spaces + 1 writer.save() # list of dataframes dfs = [df,df1,df2] # run function multiple_dfs(dfs, 'Validation', 'test1.xlsx', 1)
Put multiple dataframes across separate tabs/sheets
# function def dfs_tabs(df_list, sheet_list, file_name): writer = pd.ExcelWriter(file_name,engine='xlsxwriter') for dataframe, sheet in zip(df_list, sheet_list): dataframe.to_excel(writer, sheet_name=sheet, startrow=0 , startcol=0) writer.save() # list of dataframes and sheet names dfs = [df, df1, df2] sheets = ['df','df1','df2'] # run function dfs_tabs(dfs, sheets, 'multi-test.xlsx')
Solution 3:
I would be more inclined to concatenate the dataframes first and then turn that dataframe into an excel format. To put two dataframes together side-by-side (as opposed to one above the other) do this:
writer = pd.ExcelWriter('test.xlsx',engine='xlsxwriter') # Creating Excel Writer Object from Pandas workbook=writer.book df.to_excel(writer,sheet_name='Validation',startrow=0 , startcol=0) new_df = pd.concat([df, another_df], axis=1) new_df.to_excel(writer,sheet_name='Validation',startrow=0 , startcol=0)
Solution 4:
The answer by Adrian can be simplified as follows
writer = pd.ExcelWriter('test.xlsx',engine='xlsxwriter')
df.to_excel(writer,sheet_name='Validation',startrow=0 , startcol=0)
another_df.to_excel(writer,sheet_name='Validation',startrow=20, startcol=0)
Works for pandas 0.25.3
with python 3.7.6