Hello I would like to concatenate three excels files xlsx using python.
I have tried using openpyxl, but I don't know which function could help me to append three worksheet into one.
Do you have any ideas how to do that ?
Thanks a lot
Here's a pandas-based approach. (It's using openpyxl behind the scenes.)
import pandas as pd
# filenames
excel_names = ["xlsx1.xlsx", "xlsx2.xlsx", "xlsx3.xlsx"]
# read them in
excels = [pd.ExcelFile(name) for name in excel_names]
# turn them into dataframes
frames = [x.parse(x.sheet_names[0], header=None,index_col=None) for x in excels]
# delete the first row for all frames except the first
# i.e. remove the header row -- assumes it's the first
frames[1:] = [df[1:] for df in frames[1:]]
# concatenate them..
combined = pd.concat(frames)
# write it out
combined.to_excel("c.xlsx", header=False, index=False)
I'd use xlrd and xlwt. Assuming you literally just need to append these files (rather than doing any real work on them), I'd do something like: Open up a file to write to with xlwt, and then for each of your other three files, loop over the data and add each row to the output file. To get you started:
import xlwt
import xlrd
wkbk = xlwt.Workbook()
outsheet = wkbk.add_sheet('Sheet1')
xlsfiles = [r'C:\foo.xlsx', r'C:\bar.xlsx', r'C:\baz.xlsx']
outrow_idx = 0
for f in xlsfiles:
# This is all untested; essentially just pseudocode for concept!
insheet = xlrd.open_workbook(f).sheets()[0]
for row_idx in xrange(insheet.nrows):
for col_idx in xrange(insheet.ncols):
outsheet.write(outrow_idx, col_idx,
insheet.cell_value(row_idx, col_idx))
outrow_idx += 1
wkbk.save(r'C:\combined.xls')
If your files all have a header line, you probably don't want to repeat that, so you could modify the code above to look more like this:
firstfile = True # Is this the first sheet?
for f in xlsfiles:
insheet = xlrd.open_workbook(f).sheets()[0]
for row_idx in xrange(0 if firstfile else 1, insheet.nrows):
pass # processing; etc
firstfile = False # We're done with the first sheet.
When I combine excel files (mydata1.xlsx, mydata2.xlsx, mydata3.xlsx) for data analysis, here is what I do:
import pandas as pd
import numpy as np
import glob
all_data = pd.DataFrame()
for f in glob.glob('myfolder/mydata*.xlsx'):
df = pd.read_excel(f)
all_data = all_data.append(df, ignore_index=True)
Then, when I want to save it as one file:
writer = pd.ExcelWriter('mycollected_data.xlsx', engine='xlsxwriter')
all_data.to_excel(writer, sheet_name='Sheet1')
writer.save()
Solution with openpyxl only (without a bunch of other dependencies).
This script should take care of merging together an arbitrary number of xlsx documents, whether they have one or multiple sheets. It will preserve the formatting.
There's a function to copy sheets in openpyxl, but it is only from/to the same file. There's also a function insert_rows somewhere, but by itself it won't insert any rows. So I'm afraid we are left to deal (tediously) with one cell at a time.
As much as I dislike using for loops and would rather use something compact and elegant like list comprehension, I don't see how to do that here as this is a side-effect show.
Credit to this answer on copying between workbooks.
#!/usr/bin/env python3
#USAGE
#mergeXLSX.py <a bunch of .xlsx files> ... output.xlsx
#
#where output.xlsx is the unified file
#This works FROM/TO the xlsx format. Libreoffice might help to convert from xls.
#localc --headless --convert-to xlsx somefile.xls
import sys
from copy import copy
from openpyxl import load_workbook,Workbook
def createNewWorkbook(manyWb):
for wb in manyWb:
for sheetName in wb.sheetnames:
o = theOne.create_sheet(sheetName)
safeTitle = o.title
copySheet(wb[sheetName],theOne[safeTitle])
def copySheet(sourceSheet,newSheet):
for row in sourceSheet.rows:
for cell in row:
newCell = newSheet.cell(row=cell.row, column=cell.col_idx,
value= cell.value)
if cell.has_style:
newCell.font = copy(cell.font)
newCell.border = copy(cell.border)
newCell.fill = copy(cell.fill)
newCell.number_format = copy(cell.number_format)
newCell.protection = copy(cell.protection)
newCell.alignment = copy(cell.alignment)
filesInput = sys.argv[1:]
theOneFile = filesInput.pop(-1)
myfriends = [ load_workbook(f) for f in filesInput ]
#try this if you are bored
#myfriends = [ openpyxl.load_workbook(f) for k in range(200) for f in filesInput ]
theOne = Workbook()
del theOne['Sheet'] #We want our new book to be empty. Thanks.
createNewWorkbook(myfriends)
theOne.save(theOneFile)
Tested with openpyxl 2.5.4, python 3.4.
You can simply use pandas and os library to do this.
import pandas as pd
import os
#create an empty dataframe which will have all the combined data
mergedData = pd.DataFrame()
for files in os.listdir():
#make sure you are only reading excel files
if files.endswith('.xlsx'):
data = pd.read_excel(files, index_col=None)
mergedData = mergedData.append(data)
#move the files to other folder so that it does not process multiple times
os.rename(files, 'path to some other folder')
mergedData DF will have all the combined data which you can export in a separate excel or csv file. Same code will work with csv files as well. just replace it in the IF condition
Just to add to p_barill's answer, if you have custom column widths that you need to copy, you can add the following to the bottom of copySheet:
for col in sourceSheet.column_dimensions:
newSheet.column_dimensions[col] = sourceSheet.column_dimensions[col]
I would just post this in a comment on his or her answer but my reputation isn't high enough.
Related
I'm trying to merge a series of xlsx files into one, which works fine.
However, when I read a file, columns containing ints are transformed into floats (or dates?) when I merge and output them to csv. I have tried to visualize this in the picture. I have seen some solutions to this where dtype is used to "force" specific columns into int format. However, I do not always know the index nor the title of the column, so i need a more scalable solution.
Anyone with some thoughts on this?
Thank you in advance
#specify folder with xlsx-files
xlsFolder = "{}/system".format(directory)
dfMaster = pd.DataFrame()
#make a list of all xlsx-files in folder
xlsFolderContent = os.listdir(xlsFolder)
xlsFolderList = []
for file in xlsFolderContent:
if file[-5:] == ".xlsx":
xlsFolderList.append(file)
for xlsx in xlsFolderList:
print(xlsx)
xl = pd.ExcelFile("{}/{}".format(xlsFolder, xlsx))
for sheet in xl.sheet_names:
if "_Errors" in sheet:
print(sheet)
dfSheet = xl.parse(sheet)
dfSheet.fillna(0, inplace=True)
dfMaster = dfMaster.append(dfSheet)
print("len of dfMaster:", len(dfMaster))
dfMaster.to_csv("{}/dfMaster.csv".format(xlsFolder),sep=";")
Data sample:
Try to use dtype='object' as parameter of pd.read_csv or (ExcelFile.parse) to prevent Pandas to infer the data type of each column. You can also simplify your code using pathlib:
import pandas as pd
import pathlib
directory = pathlib.Path('your_path_directory')
xlsFolder = directory / 'system'
data = []
for xlsFile in xlsFolder.glob('*.xlsx'):
sheets = pd.read_excel(xlsFile, sheet_name=None, dtype='object')
for sheetname, df in sheets.items():
if '_Errors' in sheetname:
data.append(df.fillna('0'))
pd.concat(data).to_csv(xlsxFolder / dfMaster.csv, sep=';')
Most of the articles I'm seeing either:
a) Combine multiple excel single-sheet workbooks into one master workbook with just a single sheet or;
b) Split a multiple-sheet excel workbook into individual workbooks.
However, my goal is to grab all the excel files in a specific folder and save them as individual sheets within one new master excel workbook. I'm trying to rename each sheet name as the name of the original file.
import pandas as pd
import glob
import os
file = "C:\\File\\Path\\"
filename = 'Consolidated Files.xlsx'
pth = os.path.dirname(file)
extension = os.path.splitext(file)[1]
files = glob.glob(os.path.join(pth, '*xlsx'))
w = pd.ExcelWriter(file + filename)
for f in files:
print(f)
df = pd.read_excel(f, header = None)
print(df)
df.to_excel(w, sheet_name = f, index = False)
w.save()
How do I adjust the names for each sheet? Also, if you see any opportunities to clean this up please let me know
You cannot rename sheet with special characters because f is full path and file name. You should use only filename to names sheetname, Use os.path.basename to get file name and use split to seperate file name and extension.
for f in files:
print(f)
df = pd.read_excel(f, header = None)
print(df)
# Use basename to get filename with extension
# Use split to seperate filename and extension
new_sheet_name = os.path.basename(f).split('.')[0]
#
df.to_excel(w, sheet_name = new_sheet_name , index = False)
I decided to put my solution here as well, just in case it would be useful to anyone.
Thing is, I wanted to be able to recall where the end sheet came from. However, source workbooks can (and likely will) often have same sheet names like "Sheet 1", so I couldn't just use sheet names from original workbooks. I also could not use source filenames as sheet names since they might be longer than 31 character, which is maximum sheet name length allowed by Excel.
Therefore, I ended up assigning incremental numbers to resulting sheet names, while simultaneously inserting a new column named "source" at the start of each sheet and populating it with file name concatenated with sheet name. Hope it might help someone :)
from glob import glob
import pandas as pd
import os
files_input = glob(r'C:\Path\to\folder\*.xlsx')
result_DFs = []
for xlsx_file in files_input:
file_DFs = pd.read_excel(xlsx_file, sheet_name=None)
# save every sheet from every file as dataframe to an array
for sheet_DF in file_DFs:
source_name = os.path.basename(xlsx_file) + ":" + sheet_DF
file_DFs[sheet_DF].insert(0, 'source', source_name)
result_DFs.append(file_DFs[sheet_DF])
with pd.ExcelWriter(r'C:\Path\to\resulting\file.xlsx') as writer:
for df_index in range(len(result_DFs)):
# write dataframe to file using simple incremental number as a new sheet name
result_DFs[df_index].to_excel(writer, sheet_name=str(df_index), index=False)
# auto-adjust column width (can be omitted if not needed)
for i, col in enumerate(result_DFs[df_index].columns):
column_len = max(result_DFs[df_index][col].astype(str).str.len().max(), len(col) + 3)
_ = writer.sheets[str(df_index)].set_column(i, i, column_len)
I am trying to make a list using pandas before putting all data sets into 2D convolution layers.
And I was able to merge all data in the multiple excel files as a list.
However, the code only reads one chosen sheet name in the multiple excel files.
For example, I have 7 sheets in each excel file; named as 'gpascore1', 'gpascore2', 'gpascore3', 'gpascore4', 'gpascore5', 'gpascore6', 'gpascore7'.
And each sheet has 4 rows and 425 columns like
As shown below, you can see the code.
import os
import pandas as pd
path = os.getcwd()
files = os.listdir(path)
files_xls = [f for f in files if f[-3:] == 'xls']
df = pd.DataFrame()
for f in files_xls:
data = pd.read_excel(f, 'gpascore1') # Read only one chosen sheet available ->
gpascore1 is a sheet name.
df = df.append(data) # But there are 6 more sheets and I would like
to read data from all of the sheets
data_y = df['admit'].values
data_x = []
for i, rows in df.iterrows():
data_x.append([rows['gre'], rows['gpa'], rows['rank']])
df=df.dropna()
df.count()
Then, I got the result as below.
This is because the data from the 'gpascore1' sheet in 3 excel files were merged.
But, I want to read the data of 6 more sheets in the excel files.
Could anyone help me to find out the answer, please?
Thank you
===============<Updated code & errors>==================================
Thank you for the answers and I revised the read_excel() as
data = pd.read_excel(f, 'gpascore1') to
data = pd.read_excel(f, sheet_name=None)
But, I have key errors like below.
Could you give me any suggestions for this issue, please?
Thank you
I actually found this question under the tag of 'tensorflow'. That's hilarious. Ok, so you want to merge all Excel sheets into one dataframe?
import os
import pandas as pd
import glob
glob.glob("C:\\your_path\\*.xlsx")
all_data = pd.DataFrame()
for f in glob.glob("C:\\your_path\\*.xlsx"):
df = pd.read_excel(f)
all_data = all_data.append(df,ignore_index=True)
type(all_data)
I am trying to automate a process that basically reads in values from text files into certain excel cells. I have a template in excel that will read data from various sheets under certain names. For example, the template will read in data from "Video scores". Video scores is a .txt file that I copy and paste into excel. There are 5 different text files used in each project so it gets tedious after a while and when there are a lot of projects to complete.
How can I import or copy and paste these .txt files into excel to a specified sheet? I have been using openpyxl for the other parts of this project, but I am open to using another library if it can't be done with openpxl.
I've also tried opening and reading a file, but I couldn't figure out how to do what I want with that either. I have found a list of all the files I need, its just a matter of getting them into excel.
Thanks in advance for anyone who helps.
First, import the TXT file into a list in python, i'm asumming the TXT file is like this
1
2
3
4
....
with open(path_txt, "r") as e:
list1 = [i for i in e]
then, we paste the values of the list on the worksheet you need
from openpyxl import load_workbook
wb = load_workbook(path_xlsx)
ws = wb[sheet_name]
ws["A1"] = "values" #just a header
row = 2 #represent the 2 row of the sheet
column = 1 #represent the column "A" of the sheet
for i in list1:
ws.cell(row=row, column=column).value = i #getting the current cell, and writing the value of the list
row += 1 #just setting the current to the next
wb.save(path_xlsx)
Hope this works for you.
Pandas would do the trick!
Approach:
Have a sheet containing path to your files, separator, the corresponding target sheet names
Now read this excel sheet using pandas and iterate over each row for each file details, read the data, write it to new excel sheet of same workbook.
import pandas as pd
file_details_path = r"/Users/path for xl sheet/file details/File2XlDetails.xlsx"
target_sheet_path = r"/Users/path to target xl sheet/File samples/FiletoXl.xlsx"
# create a writer to save the file content in excel
writer = pd.ExcelWriter(target_sheet_path, engine='xlsxwriter')
file_details = pd.read_excel(file_details_path,
dtype = str,
index_col = False
)
def write_to_excel(file, trg_sheet_name):
# writes it to excel
file.to_excel(writer,
sheet_name = trg_sheet_name,
index = False,
)
# loop through each file record
for index, file_dtl in file_details.iterrows():
# you can print and check the row content for reference
print(file_dtl['File_path'])
print(file_dtl['Separator'])
print(file_dtl['Target_sheet_name'])
# reads file
file = pd.read_csv(file_dtl['File_path'],
sep = file_dtl['Separator'],
dtype = str,
index_col = False,
)
write_to_excel(file, file_dtl['Target_sheet_name'])
writer.save()
Hope this helps! Let me know if you run into any issues...
How do I open a file that is an Excel file for reading in Python?
I've opened text files, for example, sometextfile.txt with the reading command. How do I do that for an Excel file?
Edit:
In the newer version of pandas, you can pass the sheet name as a parameter.
file_name = # path to file + file name
sheet = # sheet name or sheet number or list of sheet numbers and names
import pandas as pd
df = pd.read_excel(io=file_name, sheet_name=sheet)
print(df.head(5)) # print first 5 rows of the dataframe
Check the docs for examples on how to pass sheet_name: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html
Old version:
you can use pandas package as well....
When you are working with an excel file with multiple sheets, you can use:
import pandas as pd
xl = pd.ExcelFile(path + filename)
xl.sheet_names
>>> [u'Sheet1', u'Sheet2', u'Sheet3']
df = xl.parse("Sheet1")
df.head()
df.head() will print first 5 rows of your Excel file
If you're working with an Excel file with a single sheet, you can simply use:
import pandas as pd
df = pd.read_excel(path + filename)
print df.head()
Try the xlrd library.
[Edit] - from what I can see from your comment, something like the snippet below might do the trick. I'm assuming here that you're just searching one column for the word 'john', but you could add more or make this into a more generic function.
from xlrd import open_workbook
book = open_workbook('simple.xls',on_demand=True)
for name in book.sheet_names():
if name.endswith('2'):
sheet = book.sheet_by_name(name)
# Attempt to find a matching row (search the first column for 'john')
rowIndex = -1
for cell in sheet.col(0): #
if 'john' in cell.value:
break
# If we found the row, print it
if row != -1:
cells = sheet.row(row)
for cell in cells:
print cell.value
book.unload_sheet(name)
This isn't as straightforward as opening a plain text file and will require some sort of external module since nothing is built-in to do this. Here are some options:
http://www.python-excel.org/
If possible, you may want to consider exporting the excel spreadsheet as a CSV file and then using the built-in python csv module to read it:
http://docs.python.org/library/csv.html
There's the openpxyl package:
>>> from openpyxl import load_workbook
>>> wb2 = load_workbook('test.xlsx')
>>> print wb2.get_sheet_names()
['Sheet2', 'New Title', 'Sheet1']
>>> worksheet1 = wb2['Sheet1'] # one way to load a worksheet
>>> worksheet2 = wb2.get_sheet_by_name('Sheet2') # another way to load a worksheet
>>> print(worksheet1['D18'].value)
3
>>> for row in worksheet1.iter_rows():
>>> print row[0].value()
You can use xlpython package that requires xlrd only.
Find it here https://pypi.python.org/pypi/xlpython
and its documentation here https://github.com/morfat/xlpython
This may help:
This creates a node that takes a 2D List (list of list items) and pushes them into the excel spreadsheet. make sure the IN[]s are present or will throw and exception.
this is a re-write of the Revit excel dynamo node for excel 2013 as the default prepackaged node kept breaking. I also have a similar read node. The excel syntax in Python is touchy.
thnx #CodingNinja - updated : )
###Export Excel - intended to replace malfunctioning excel node
import clr
clr.AddReferenceByName('Microsoft.Office.Interop.Excel, Version=15.0.0.0, Culture=neutral, PublicKeyToken=71e9bce111e9429c')
##AddReferenceGUID("{00020813-0000-0000-C000-000000000046}") ''Excel C:\Program Files\Microsoft Office\Office15\EXCEL.EXE
##Need to Verify interop for version 2015 is 15 and node attachemnt for it.
from Microsoft.Office.Interop import * ##Excel
################################Initialize FP and Sheet ID
##Same functionality as the excel node
strFileName = IN[0] ##Filename
sheetName = IN[1] ##Sheet
RowOffset= IN[2] ##RowOffset
ColOffset= IN[3] ##COL OFfset
Data=IN[4] ##Data
Overwrite=IN[5] ##Check for auto-overwtite
XLVisible = False #IN[6] ##XL Visible for operation or not?
RowOffset=0
if IN[2]>0:
RowOffset=IN[2] ##RowOffset
ColOffset=0
if IN[3]>0:
ColOffset=IN[3] ##COL OFfset
if IN[6]<>False:
XLVisible = True #IN[6] ##XL Visible for operation or not?
################################Initialize FP and Sheet ID
xlCellTypeLastCell = 11 #####define special sells value constant
################################
xls = Excel.ApplicationClass() ####Connect with application
xls.Visible = XLVisible ##VISIBLE YES/NO
xls.DisplayAlerts = False ### ALerts
import os.path
if os.path.isfile(strFileName):
wb = xls.Workbooks.Open(strFileName, False) ####Open the file
else:
wb = xls.Workbooks.add# ####Open the file
wb.SaveAs(strFileName)
wb.application.visible = XLVisible ####Show Excel
try:
ws = wb.Worksheets(sheetName) ####Get the sheet in the WB base
except:
ws = wb.sheets.add() ####If it doesn't exist- add it. use () for object method
ws.Name = sheetName
#################################
#lastRow for iterating rows
lastRow=ws.UsedRange.SpecialCells(xlCellTypeLastCell).Row
#lastCol for iterating columns
lastCol=ws.UsedRange.SpecialCells(xlCellTypeLastCell).Column
#######################################################################
out=[] ###MESSAGE GATHERING
c=0
r=0
val=""
if Overwrite == False : ####Look ahead for non-empty cells to throw error
for r, row in enumerate(Data): ####BASE 0## EACH ROW OF DATA ENUMERATED in the 2D array #range( RowOffset, lastRow + RowOffset):
for c, col in enumerate (row): ####BASE 0## Each colmn in each row is a cell with data ### in range(ColOffset, lastCol + ColOffset):
if col.Value2 >"" :
OUT= "ERROR- Cannot overwrite"
raise ValueError("ERROR- Cannot overwrite")
##out.append(Data[0]) ##append mesage for error
############################################################################
for r, row in enumerate(Data): ####BASE 0## EACH ROW OF DATA ENUMERATED in the 2D array #range( RowOffset, lastRow + RowOffset):
for c, col in enumerate (row): ####BASE 0## Each colmn in each row is a cell with data ### in range(ColOffset, lastCol + ColOffset):
ws.Cells[r+1+RowOffset,c+1+ColOffset].Value2 = col.__str__()
##run macro disbled for debugging excel macro
##xls.Application.Run("Align_data_and_Highlight_Issues")
import pandas as pd
import os
files = os.listdir('path/to/files/directory/')
desiredFile = files[i]
filePath = 'path/to/files/directory/%s'
Ofile = filePath % desiredFile
xls_import = pd.read_csv(Ofile)
Now you can use the power of pandas DataFrames!
This code worked for me with Python 3.5.2. It opens and saves and excel. I am currently working on how to save data into the file but this is the code:
import csv
excel = csv.writer(open("file1.csv", "wb"))