I have the code where I want to read data from the current sheet, store it in df_old, append the current data to it using df = df_old.append(df) and then replace the data in the sheet with this new dataframe. However, what it does instead is create a new sheet with the exact same name where it publishes this new dataframe. I tried adding if_sheet_exists="replace" as an argument to ExcelWriter but this did not change anything. How can I force it to overwrite the data in the sheet with the current name?
df_old = pd.read_excel(r'C:\Users\XXX\Downloads\Digitalisation\mat_flow\reblend_v2.xlsx',sheet_name = ft_tags_final[i][j])
df = df_old.append(df)
with pd.ExcelWriter(r'C:\Users\XXX\Downloads\Digitalisation\mat_flow\reblend_v2.xlsx', engine="openpyxl", mode="a", if_sheet_exists="replace") as writer:
df.to_excel(writer, index=False, sheet_name = ft_tags_final[i][j])
I had the same issue and i solved it with using write instead of append. Also i used openpyxl instead of xlsxwriter
from pandas import ExcelWriter
from pandas import ExcelFile
from openpyxl import load_workbook
book = load_workbook('Wallet.xlsx')
writer = pd.ExcelWriter('Wallet.xlsx', engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
#^THIS IS THE MOST IMPORTANT LINES BECAUSE IT GIVES PANDAS THE SHEET
Data.to_excel(writer, sheet_name='Main', header=None, index=False, startcol=number,startrow=counter)
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'm currently doing an ETL process and am stuck with this data frame to excel issue. (Removed image tag due to lack of reputation)
I have an excel file template which looks like this https://i.imgur.com/VEHQHQF.png
Running a dataframe with values inside, I want to open up that template,(there will be future data in it) and dump the dataframe inside so ideally it'll look like this:
https://i.imgur.com/WPhLJV4.png
However, when i run my code, i kept getting this output: https://i.imgur.com/JhxkyWS.png
The table formatting stops at cell C2
is there anyway to push the data INTO the table formatting template(appending values)?
I have tried using openpyxl and pandas in-built excel code to_excel but it all did not work out. I kept getting the same error whereby the table format stops at the 2nd row.
I have also tried adding/removing the header in my data frame to match with the header in the excel file but there were no difference.
My current code:
import pandas as pd
import xlsxwriter
import openpyxl
import os,sys
from openpyxl import load_workbook
d = {'this': [1, 2, 3], 'is': [4, 5, 6], 'test': [7, 8, 9]}
df = pd.DataFrame(data = d)
file_descr = 'test.xlsx'
def write_data(self, file_descr):
"""
Use dataframe to_excel to write into file_descr (filename) - open first if file exists.
"""
if os.path.isfile(file_descr):
book = load_workbook(file_descr)
writer = pd.ExcelWriter(file_descr, engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
df.to_excel(writer, sheet_name='Sheet1', index=False, header= True,
float_format='%.2f')
## Using xlswriter as an engine
# writer = pd.ExcelWriter(file_descr,engine = 'xlsxwriter')
# df.to_excel(writer,index=False,sheet_name = 'Sheet1')
# workbook = writer.book
writer.save()
else:
self.data_df.to_excel(file_descr, sheet_name='Sheet1', index=False,
float_format='%.2f')
write_data(df,file_descr)
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()