I am using xlsxwriter to generate a file with quite a few formulas. From there, I want to create a table on another sheet. Everything is pretty straightforward until I want to use data from a different sheet for the table.
The documentation only shows examples of already having the data you need, and then passing that to the .add_table as the 'data' parameter.
What I am trying to do is this: (Which is structured how the rest of xlsxwriter's formulas are.)
df = pd.DataFrame(stuff)
writer = pd.ExcelWriter('File.xlsx', engine = 'xlsxwriter')
df.to_excel(writer, sheet_name='Sheet1')
workbook = writer.book
worksheet1 = writer.sheets['Sheet1']
worksheet2 = workbook.add_worksheet('Summary Page')
data = f"'Sheet1'!$A$1:$D${len(df)}"
worksheet2.add_table(f'A1:D{len(df)}', {'data':data})
workbook.close()
This approach adds the new sheet, and creates a table the correct size. But then fills in the "data" with 'data' as a string down the first column with one character in each cell.
Is there a way to create a table referencing data from another sheet using xlsxwriter?
ExcelWriter is (obviously) for writing Excelfiles.
If you want to read data from Excel after writing and saving it (did I get you right?!) use
ExcelFile.parse or read_excel to convert data to dataframe and write it again to Excel by ExcelWriter. Unfortunately xlsxwriter does not support appending, so you have to load and write all sheets again. Or just use the default openpyxl as engine. Could be omitted (as said: default) but to point out it is given in minimal working example:
import pandas as pd
df = pd.DataFrame({'Data': [10, 20, 30, 20, 15, 30, 45]})
writer = pd.ExcelWriter('test.xlsx', engine='openpyxl')
df.to_excel(writer, sheet_name='Sheet1')
writer.save()
data = pd.read_excel('test.xlsx', usecols='A:B', sheet_name='Sheet1', index_col=0)
writer = pd.ExcelWriter('test.xlsx', engine='openpyxl', mode='a')
# shape our data here
data.to_excel(writer, sheet_name='Sheet2')
writer.save()
I am storing a pandas DataFrame in an Excel sheet. When I re-run my code, I want the sheet completely overwritten. This is important because my code writes to the same file a few different times, i.e., loading and saving certain sheets at different moments, not wanting to disturb the sheets not currently being changed. Because of this, if a new iteration of the code produces fewer rows or columns, the old data will still be there. For example, if iteration #1 produces 500 rows but iteration #2 only produces 499, that 500th row will still show up in my Excel file.
I'm aware I could loop through all the cells and set their values to None, but I thought it would be more efficient to remove a given sheet completely, create_sheet with the same sheet name, and then save my DataFrame to the new sheet. The code below is a MRE of what I'm trying to do. It successfully removes the sheet, creates a new one, and saves the file, but the to_excel doesn't seem to be executing. The resulting Excel file has the 'test' sheet, but it is blank.
import pandas as pd
import numpy as np
import openpyxl
from openpyxl import load_workbook
from openpyxl import Workbook
df_data = {'A': np.random.randint(1, 50, 20),
'B': np.random.randint(1, 50, 20),
'C': np.random.randint(1, 50, 20),
'D': np.random.randint(1, 50, 20)}
df = pd.DataFrame(data=df_data)
fn = 'test.xlsx'
sheet = 'test'
df.to_excel(fn, sheet_name=sheet)
df2 = pd.read_excel(fn, sheet_name=sheet, index_col=0)
df2.drop(columns=['A'], inplace=True)
book = load_workbook(fn)
writer = pd.ExcelWriter(fn, engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
s = book[sheet]
book.remove(s)
book.create_sheet(sheet, 0)
#THIS CODE WILL ACTUALLY WRITE TO THE SHEET, BUT df2 WILL NOT
#s2 = book[sheet]
#s2['A1'] = 'This will write to the sheet'
df2.to_excel(writer, sheet_name=sheet)
writer.save()
Note that my commented code will write to the proper sheet if uncommented. It seems to just be the to_excel line that doesn't work.
You could do this by using a function:
import pandas as pd
def write2excel(filename,sheetname,dataframe):
with pd.ExcelWriter(filename, engine='openpyxl', mode='a') as writer:
workBook = writer.book
try:
workBook.remove(workBook[sheetname])
except:
print("There is no such sheet in this file")
finally:
dataframe.to_excel(writer, sheet_name=sheetname,index=False)
writer.save()
After this, assuming you have a datafram df, A workbook Myfile.xlsx and the sheet you want to overwrite THE_sheet do
write2excel('Myfile.xlsx','THE_sheet',df)
I want to use excel files to store data elaborated with python. My problem is that I can't add sheets to an existing excel file. Here I suggest a sample code to work with in order to reach this issue
import pandas as pd
import numpy as np
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
x1 = np.random.randn(100, 2)
df1 = pd.DataFrame(x1)
x2 = np.random.randn(100, 2)
df2 = pd.DataFrame(x2)
writer = pd.ExcelWriter(path, engine = 'xlsxwriter')
df1.to_excel(writer, sheet_name = 'x1')
df2.to_excel(writer, sheet_name = 'x2')
writer.save()
writer.close()
This code saves two DataFrames to two sheets, named "x1" and "x2" respectively. If I create two new DataFrames and try to use the same code to add two new sheets, 'x3' and 'x4', the original data is lost.
import pandas as pd
import numpy as np
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
x3 = np.random.randn(100, 2)
df3 = pd.DataFrame(x3)
x4 = np.random.randn(100, 2)
df4 = pd.DataFrame(x4)
writer = pd.ExcelWriter(path, engine = 'xlsxwriter')
df3.to_excel(writer, sheet_name = 'x3')
df4.to_excel(writer, sheet_name = 'x4')
writer.save()
writer.close()
I want an excel file with four sheets: 'x1', 'x2', 'x3', 'x4'.
I know that 'xlsxwriter' is not the only "engine", there is 'openpyxl'. I also saw there are already other people that have written about this issue, but still I can't understand how to do that.
Here a code taken from this link
import pandas
from openpyxl import load_workbook
book = load_workbook('Masterfile.xlsx')
writer = pandas.ExcelWriter('Masterfile.xlsx', engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2'])
writer.save()
They say that it works, but it is hard to figure out how. I don't understand what "ws.title", "ws", and "dict" are in this context.
Which is the best way to save "x1" and "x2", then close the file, open it again and add "x3" and "x4"?
Thank you. I believe that a complete example could be good for anyone else who have the same issue:
import pandas as pd
import numpy as np
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
x1 = np.random.randn(100, 2)
df1 = pd.DataFrame(x1)
x2 = np.random.randn(100, 2)
df2 = pd.DataFrame(x2)
writer = pd.ExcelWriter(path, engine = 'xlsxwriter')
df1.to_excel(writer, sheet_name = 'x1')
df2.to_excel(writer, sheet_name = 'x2')
writer.close()
Here I generate an excel file, from my understanding it does not really matter whether it is generated via the "xslxwriter" or the "openpyxl" engine.
When I want to write without loosing the original data then
import pandas as pd
import numpy as np
from openpyxl import load_workbook
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
book = load_workbook(path)
writer = pd.ExcelWriter(path, engine = 'openpyxl')
writer.book = book
x3 = np.random.randn(100, 2)
df3 = pd.DataFrame(x3)
x4 = np.random.randn(100, 2)
df4 = pd.DataFrame(x4)
df3.to_excel(writer, sheet_name = 'x3')
df4.to_excel(writer, sheet_name = 'x4')
writer.close()
this code do the job!
For creating a new file
x1 = np.random.randn(100, 2)
df1 = pd.DataFrame(x1)
with pd.ExcelWriter('sample.xlsx') as writer:
df1.to_excel(writer, sheet_name='x1')
For appending to the file, use the argument mode='a' in pd.ExcelWriter.
x2 = np.random.randn(100, 2)
df2 = pd.DataFrame(x2)
with pd.ExcelWriter('sample.xlsx', engine='openpyxl', mode='a') as writer:
df2.to_excel(writer, sheet_name='x2')
Default is mode ='w'.
See documentation.
In the example you shared you are loading the existing file into book and setting the writer.book value to be book. In the line writer.sheets = dict((ws.title, ws) for ws in book.worksheets) you are accessing each sheet in the workbook as ws. The sheet title is then ws so you are creating a dictionary of {sheet_titles: sheet} key, value pairs. This dictionary is then set to writer.sheets. Essentially these steps are just loading the existing data from 'Masterfile.xlsx' and populating your writer with them.
Now let's say you already have a file with x1 and x2 as sheets. You can use the example code to load the file and then could do something like this to add x3 and x4.
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
writer = pd.ExcelWriter(path, engine='openpyxl')
df3.to_excel(writer, 'x3', index=False)
df4.to_excel(writer, 'x4', index=False)
writer.save()
That should do what you are looking for.
A simple example for writing multiple data to excel at a time. And also when you want to append data to a sheet on a written excel file (closed excel file).
When it is your first time writing to an excel. (Writing "df1" and "df2" to "1st_sheet" and "2nd_sheet")
import pandas as pd
from openpyxl import load_workbook
df1 = pd.DataFrame([[1],[1]], columns=['a'])
df2 = pd.DataFrame([[2],[2]], columns=['b'])
df3 = pd.DataFrame([[3],[3]], columns=['c'])
excel_dir = "my/excel/dir"
with pd.ExcelWriter(excel_dir, engine='xlsxwriter') as writer:
df1.to_excel(writer, '1st_sheet')
df2.to_excel(writer, '2nd_sheet')
writer.save()
After you close your excel, but you wish to "append" data on the same excel file but another sheet, let's say "df3" to sheet name "3rd_sheet".
book = load_workbook(excel_dir)
with pd.ExcelWriter(excel_dir, engine='openpyxl') as writer:
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
## Your dataframe to append.
df3.to_excel(writer, '3rd_sheet')
writer.save()
Be noted that excel format must not be xls, you may use xlsx one.
Every time you want to save a Pandas DataFrame to an Excel, you may call this function:
import os
def save_excel_sheet(df, filepath, sheetname, index=False):
# Create file if it does not exist
if not os.path.exists(filepath):
df.to_excel(filepath, sheet_name=sheetname, index=index)
# Otherwise, add a sheet. Overwrite if there exists one with the same name.
else:
with pd.ExcelWriter(filepath, engine='openpyxl', if_sheet_exists='replace', mode='a') as writer:
df.to_excel(writer, sheet_name=sheetname, index=index)
I would strongly recommend you work directly with openpyxl since it now supports Pandas DataFrames.
This allows you to concentrate on the relevant Excel and Pandas code.
Can do it without using ExcelWriter, using tools in openpyxl
This can make adding fonts to the new sheet much easier using openpyxl.styles
import pandas as pd
from openpyxl import load_workbook
from openpyxl.utils.dataframe import dataframe_to_rows
#Location of original excel sheet
fileLocation =r'C:\workspace\data.xlsx'
#Location of new file which can be the same as original file
writeLocation=r'C:\workspace\dataNew.xlsx'
data = {'Name':['Tom','Paul','Jeremy'],'Age':[32,43,34],'Salary':[20000,34000,32000]}
#The dataframe you want to add
df = pd.DataFrame(data)
#Load existing sheet as it is
book = load_workbook(fileLocation)
#create a new sheet
sheet = book.create_sheet("Sheet Name")
#Load dataframe into new sheet
for row in dataframe_to_rows(df, index=False, header=True):
sheet.append(row)
#Save the modified excel at desired location
book.save(writeLocation)
You can read existing sheets of your interests, for example, 'x1', 'x2', into memory and 'write' them back prior to adding more new sheets (keep in mind that sheets in a file and sheets in memory are two different things, if you don't read them, they will be lost). This approach uses 'xlsxwriter' only, no openpyxl involved.
import pandas as pd
import numpy as np
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
# begin <== read selected sheets and write them back
df1 = pd.read_excel(path, sheet_name='x1', index_col=0) # or sheet_name=0
df2 = pd.read_excel(path, sheet_name='x2', index_col=0) # or sheet_name=1
writer = pd.ExcelWriter(path, engine='xlsxwriter')
df1.to_excel(writer, sheet_name='x1')
df2.to_excel(writer, sheet_name='x2')
# end ==>
# now create more new sheets
x3 = np.random.randn(100, 2)
df3 = pd.DataFrame(x3)
x4 = np.random.randn(100, 2)
df4 = pd.DataFrame(x4)
df3.to_excel(writer, sheet_name='x3')
df4.to_excel(writer, sheet_name='x4')
writer.save()
writer.close()
If you want to preserve all existing sheets, you can replace above code between begin and end with:
# read all existing sheets and write them back
writer = pd.ExcelWriter(path, engine='xlsxwriter')
xlsx = pd.ExcelFile(path)
for sheet in xlsx.sheet_names:
df = xlsx.parse(sheet_name=sheet, index_col=0)
df.to_excel(writer, sheet_name=sheet)
Another fairly simple way to go about this is to make a method like this:
def _write_frame_to_new_sheet(path_to_file=None, sheet_name='sheet', data_frame=None):
book = None
try:
book = load_workbook(path_to_file)
except Exception:
logging.debug('Creating new workbook at %s', path_to_file)
with pd.ExcelWriter(path_to_file, engine='openpyxl') as writer:
if book is not None:
writer.book = book
data_frame.to_excel(writer, sheet_name, index=False)
The idea here is to load the workbook at path_to_file if it exists and then append the data_frame as a new sheet with sheet_name. If the workbook does not exist, it is created. It seems that neither openpyxl or xlsxwriter append, so as in the example by #Stefano above, you really have to load and then rewrite to append.
#This program is to read from excel workbook to fetch only the URL domain names and write to the existing excel workbook in a different sheet..
#Developer - Nilesh K
import pandas as pd
from openpyxl import load_workbook #for writting to the existing workbook
df = pd.read_excel("urlsearch_test.xlsx")
#You can use the below for the relative path.
# r"C:\Users\xyz\Desktop\Python\
l = [] #To make a list in for loop
#begin
#loop starts here for fetching http from a string and iterate thru the entire sheet. You can have your own logic here.
for index, row in df.iterrows():
try:
str = (row['TEXT']) #string to read and iterate
y = (index)
str_pos = str.index('http') #fetched the index position for http
str_pos1 = str.index('/', str.index('/')+2) #fetched the second 3rd position of / starting from http
str_op = str[str_pos:str_pos1] #Substring the domain name
l.append(str_op) #append the list with domain names
#Error handling to skip the error rows and continue.
except ValueError:
print('Error!')
print(l)
l = list(dict.fromkeys(l)) #Keep distinct values, you can comment this line to get all the values
df1 = pd.DataFrame(l,columns=['URL']) #Create dataframe using the list
#end
#Write using openpyxl so it can be written to same workbook
book = load_workbook('urlsearch_test.xlsx')
writer = pd.ExcelWriter('urlsearch_test.xlsx',engine = 'openpyxl')
writer.book = book
df1.to_excel(writer,sheet_name = 'Sheet3')
writer.save()
writer.close()
#The below can be used to write to a different workbook without using openpyxl
#df1.to_excel(r"C:\Users\xyz\Desktop\Python\urlsearch1_test.xlsx",index='false',sheet_name='sheet1')
if you want to add empty sheet
xw = pd.ExcelWriter(file_path, engine='xlsxwriter')
pd.DataFrame().to_excel(xw, 'sheet11')
if you get empty sheet
sheet = xw.sheets['sheet11']
import pandas as pd
import openpyxl
writer = pd.ExcelWriter('test.xlsx', engine='openpyxl')
data_df.to_excel(writer, 'sheet_name')
writer.save()
writer.close()
The following solution worked for me:
# dataframe to save
df = pd.DataFrame({"A":[1,2], "B":[3,4]})
# path where you want to save
path = "./..../..../.../test.xlsx"
# if an excel sheet named `test` is already present append on sheet 2
if os.path.isfile(path):
with pd.ExcelWriter(path, mode='a') as writer:
df.to_excel(writer, sheet_name= "sheet_2")
else:
# if not present then write to a excel file on sheet 1
with pd.ExcelWriter(path) as writer:
df.to_excel(writer, sheet_name= "sheet_1")
Now, if you want to write multiple dataframes on different sheets, simply add a loop and keep on changing the sheet_name.
I tried to edit an existing excel file. My file is test.xlsx, with two sheets are All and Summary. Following step:
import pandas as pd
df = pd.read_csv('abc.csv')
number_rows = len(df.index)
writer = pd.ExcelWriter('test.xlsx')
df.to_excel(writer, sheet_name = 'All',startrow = number_rows)
writer.save()
I want to edit(append data to sheet name All) but when run this code, it seem to be the sheet name Summary and All deleted and it create a new sheet name All and write my new data to it. So, how to append data to excel sheet without delete existing data? Thank you.
You can use openpyxl engine along-with startrow parameter.
You also need to ;
read csv to df first
open xlsx as workbook using openpyxl
create writer object using openpyxl as engine
Add sheets to writer object
Add df to writer object
Your Code (modified):
import pandas as pd
from openpyxl import load_workbook
df = pd.read_csv('abc.csv')
number_rows = len(df.index)
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 = 'All',startrow = number_rows)
writer.save()