I have a .txt file with a list of keywords, I read this file and for each keyword generate some kind of string. I would like to append this string generated for each keyword to excel file. I'd like also that each time I re run the script and read .txt file with new keywords, result is always appended to the same excel file instead of overwriting it.
I have tried this, but not sure if openpyxl is a good method, also I get an error:
raise ValueError("{0} is not a valid column name".format(str_col))
ValueError: tapis roulant elettrico is not a valid column name
for line
page.append(some_result)
from openpyxl.workbook import Workbook
from openpyxl import load_workbook
headers = ['data']
workbook_name = 'Example.xlsx'
wb = Workbook()
page = wb.active
page.title = 'data'
page.append(headers)
some_result = {}
val = "some result"
with open("keywords.txt", "r") as file:
for line in file:
some_result = {line: val}
page.append(some_result)
wb.save(filename=workbook_name)
file.close()
Just my opinion, its definitely not a good idea to save your file for every entry in your loop. Itll slow things down and overall it will probably break things and make them more complicated. I think it is likely you are saving a new column name on every iteration. I made a few changes/comments that I didnt really test, but hopefully it might help you get moving in the right direction. I'm assuming you just want a single column in your excel sheet with the keywords you mention, but to give you a complete solution I would need to know details about whether youre allowing duplicates, why you need it in excel format at all, and a few other things. If a CSV is acceptable (excel can read these) then there is a much simpler solution than what youre doing if you use numpy and or pandas.
from openpyxl.workbook import Workbook
from openpyxl import load_workbook
headers = ['data']
workbook_name = 'Example.xlsx'
wb = Workbook()
page = wb.active
page.title = 'data'
page.append(headers)
some_result = {}
val = "some result"
temp_page_list = []
with open("keywords.txt", "r") as file:
for line in file:
some_result = {line: val}
#print(some_result)
#dont append to your real excel file here in the loop, doing it in a simple list will be less complicated and faster
#page.append(some_result)
temp_page_list.append(some_result)
#dont save things here
#wb.save(filename=workbook_name)
file.close()
#print some or all of temp_page_list here
#if it looks right, you can perhaps convert the list directly by iterating and saving the elements
#a better option may be to use a built in function from openpyxl to add the contents of temp_page_list if such a function exists
I have not worked with openpyxl before but I want to give you a general understanding of the python code that you wrote.
from openpyxl.workbook import Workbook
from openpyxl import load_workbook
headers = ['data']
workbook_name = 'Example.xlsx'
wb = Workbook()
page = wb.active
page.title = 'data'
page.append(headers)
some_result = {}
val = "some result"
with open("keywords.txt", "r") as file:
for line in file:
# some_result = {line: val} # this is a dictionary
some_result = val + str(line) # this is a string
page.append(some_result)
wb.save(filename=workbook_name)
file.close()
You are trying to append a dictionary with Key being the line variable and the Value associated with this key is the some_result variable. While you are trying to append this Key, Value Pair, I think it is assuming that you want to append the Value in a row that is associated with the Key as the column (but the Key doesn't exist already). So if you try the above code, I think it would append everything under one column. If you want separate column then you need to create columns if they don't exist
Related
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...
I've created a list and a for loop to iterate over each item in it to print it to a cell in excel. I'm using openpyxl. When I first started using it using easy statements like:
sheet["A1"] = "hello"
results in Cell A1 perfectly representing the hello value, without quotation marks.
I have this code:
workbook = Workbook()
sheet = workbook.active
text = ["Whistle", "Groot", "Numbers", "Mulan", "Buddy Holly"]
other = [5, 8, 100, 120]
for i in range(1,len(text)+1):
cell_letter = "A"
cell_number = str(i)
sheet[str((cell_letter + cell_number))] = str(text[i-1:i])
and it writes to the corresponding cell locations with the iterations over the variable "text". But when i open the file the format is ['Whistle'] and ['Groot']
What am I missing? Should I be passing each iteration to another variable to convert it from a list to a tuple for it to be written in then?
Sorry if my code seems a bit messy, I've literally just learned this over the past few hours and it's (kind of) doing what I need it to do, with the exception of the writing format.
Openpyxl let you write a list of lists, where the intern lists represents the 'lines' in a xlsx file.
So, you can store what you want as:
data_to_write = [["Whistle", "Groot", "Numbers", "Mulan", "Buddy Holly"]]
or, if you want some data in the next line:
data_to_write = [["Whistle", "Groot", "Numbers"], ["Mulan", "Buddy Holly"]]
then, add it to your WorkSheet:
for line in data_to_write:
sheet.append(line)
and, finally, save it:
workbook.save("filename.xlsx")
The full code could be something like:
from openpyxl import Workbook
workbook = Workbook()
sheet = workbook.active
data_to_write = [["Whistle", "Groot", "Numbers", "Mulan", "Buddy Holly"]]
for line in data_to_write:
sheet.append(line)
workbook.save('example.xlsx')
Give it a try and, then, give me a feedback, please XD
I'm writing a simple code to transform csv back to xls with Tablib on python.
As I understand, Tablib does conversion for you if you import the csv.
import tablib
imported_data = tablib.import_set(open('DB.csv',encoding='utf8').read())
f = open('workfile.xls', 'wb')
f.write(imported_data.xls)
f.close()
This code handles small sample of the database, but fails at one point (~600 lines) meaning that is compiles successfully but Excel cannot open the file at that point.
I'm not sure how to proceed - is this tablib failing or does Excel fail to read encoded data?
this two functions allow you to import from csv, after export to excel file
import csv
from xlsxwriter import Workbook
import operator
# This function for import from csv
def CSV2list_dict(file_name):
with open(file_name) as f:
a = [{k: int(v) for k, v in row.items()}
for row in csv.DictReader(f, skipinitialspace=True)]
return a
# file_name must be end with .xlsx
# The second parameter represente the header row of data in excel,
# The type of header is a list of string,
# The third paramater represente the data in list dictionaries form
# The last paramater represente the order of the key
def Export2excel(file_name, header_row, list_dict, order_by):
list_dict.sort(key=operator.itemgetter(order_by))
wb=Workbook(file_name)
ws=wb.add_worksheet("New Sheet") #or leave it blank, default name is "Sheet 1"
first_row=0
for header in header_row:
col=header_row.index(header) # we are keeping order.
ws.write(first_row,col,header) # we have written first row which is the header of worksheet also.
row=1
for art in list_dict:
for _key,_value in art.items():
col=header_row.index(_key)
ws.write(row,col,_value)
row+=1 #enter the next row
wb.close()
csv_data = CSV2list_dict('DB.csv')
header = ['col0','col1','col2']
order = 'col0' # the type of col0 is int
Export2excel('workfile.xlsx', header, csv_data, order)
As an alternative approach, you could just ask Excel to do the conversion as follows:
import win32com.client as win32
import os
excel = win32.gencache.EnsureDispatch('Excel.Application')
src_filename = r"c:\my_folder\my_file.csv"
name, ext = os.path.splitext(src_filename)
target_filename = name + '.xls'
wb = excel.Workbooks.Open(src_filename)
excel.DisplayAlerts = False
wb.DoNotPromptForConvert = True
wb.CheckCompatibility = False
wb.SaveAs(target_filename, FileFormat=56, ConflictResolution=2)
excel.Application.Quit()
Microsoft has a list of File formats that you can use, where 56 is used for xls.
If you are using the new openpyxl 2.5 this will not work. You need to remove 2.5 and instead pip install 2.4.9.
import tablib
Depending on whether it is a dataset(one page) or databook(multiple) you need to declare:(changes here)
imported_data = tablib.Dataset()
or
imported_data = tablib.Databook()
Then you can import your data.(changes here)
imported_data.csv = tablib.import_set(open('DB.csv', enconding='utf8').read())
without specifying the .csv in your example tablib doesn't know the format.
imported_data = tablib.import_set(open('DB.csv',encoding='utf8').read())
then you could print to see the various options you have.
print(imported_data)
print(imported_data.csv)
print(imported_data.xlsx)
print(imported_data.dict)
print(imported_data.db)
etc.
Then write your file.(No changes here)
f = open('workfile.xls', 'wb')
f.write(imported_data.xls) # or .xlsx
f.close()
I have several excel files that use lots of comments for saving information.
For example, one cell has value 2 and there is a comment attached to the cell saying
"2008:2#2009:4". it seems that value 2 is for the current year (2010) value. The comment keeps all previous year values separated by '#'. I would like to create a dictionary to keep all this info like {2008:2, 2009:4, 2010:2} but I don't know how to parse (or read) this comment attached to the cell. Python excel readin module has this function (reading in comment)?
You can do this without an Excel COM object using openpyxl:
from openpyxl import load_workbook
workbook = load_workbook('/tmp/data.xlsx')
first_sheet = workbook.get_sheet_names()[0]
worksheet = workbook.get_sheet_by_name(first_sheet)
for row in worksheet.iter_rows():
for cell in row:
if cell.comment:
print(cell.comment.text)
The parsing of the comments itself can be done the same as with Steven Rumbalski's answer.
(example adapted from here)
Normally for reading from Excel, I would suggest using xlrd, but xlrd does not support comments. So instead use the Excel COM object:
from win32com.client import Dispatch
xl = Dispatch("Excel.Application")
xl.Visible = True
wb = xl.Workbooks.Open("Book1.xls")
sh = wb.Sheets("Sheet1")
comment = sh.Cells(1,1).Comment.Text()
And here's how to parse the comment:
comment = "2008:2#2009:4"
d = {}
for item in comment.split('#'):
key, val = item.split(':')
d[key] = val
Often, Excel comments are on two lines with the first line noting who created the comment. If so your code would look more like this:
comment = """Steven:
2008:2#2009:4"""
_, comment = comment.split('\n')
d = {}
for item in comment.split('#'):
key, val = item.split(':')
d[key] = val
After running the last posted code here, can you store that information later in a word document?
from openpyxl import load_workbook
workbook = load_workbook('/tmp/data.xlsx')
first_sheet = workbook.get_sheet_names()[0]
worksheet = workbook.get_sheet_by_name(first_sheet)
for row in worksheet.iter_rows():
for cell in row:
if cell.comment:
print(cell.comment.text)
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"))