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Reading a .csv file in a CombiTimeTable in Dymola using SimulateExtendedModel() function through Python

I am trying to write a establish a Dymola python interface where a .csv file is read and given in the CombiTimeTable in Dymola. But I do not find any help to do that. Even with Dymola Script/Command I wasn't able to give in my csv file and a filename.
Does anyone have any idea how would i be able to do so?
P.S. I have also tried the ExternData package.
I have used
Modelica.Blocks.Sources.CombiTimeTable CombiTimeTable(tableOnFile=True, tableName="",fileName="")
And
innerparameter ExternData
Update
Found a alternative approach of doing it with simulateExtendedModel() as:
dymola.simulateExtendedModel("Model",startTime=0, stopTime=1, numberOfIntervals=0, outputInterval=300,
initialNames={"CombiTimeTable.table"}, initialValues={DataFiles.readCSVmatrix("Z:\your.csv")});
Still struggling with the errors but in the combiTimeTable it's possible to write a .csv in the table, whereas .txt and .mat under tableOnFile.

i have myself encountered a similar issue some time ago.
If you look at the documentation CombiTimeTable Documentation you can see that you can provide a .txt file as a source for the time table.
Here is a bit of python code used to process a csv into a suitable file (it may not be the best way, but it works perfectly for me). I am using the python pandas library :
import pandas as pd
"""Creating a dataframe by reading from your source csv file"""
data = pd.read_csv("Path/To/Your/SourceFile.csv")
"""Creating the entry file for the combi time table"""
f = open (file="Path/To/Dymola/Source.txt" ,mode="w+")
"""Writing whatever Dymola needs to read the file (Check the CombiTimeTable documentation for more informations) """
f.write("#1 \n")
f.write("double tab1("+str(len(data.axes[0]))+","+str(len(data.axes[1]))+") # comment line" +"\n")
f.close()
"""Using the to_csv method by pointing to an existing txt file, and using the 'a' (append) mode will cause the values from the dataframe to be next to the existing text"""
data.to_csv("Path/To/Dymola/Source.txt",mode ="a",sep = '\t', index = None, header=False)
Here is an example of what it returns me : Example of a generated CombiTimeTable source file
Some precisions :
I am assuming that your data from your csv have headers.
The first column in your csv contains time points (in my example they represent minutes).
Dymola side : Here is how you can setup the CombiTimeTable (based on my example) : CombiTimeTable setup example
I hope that you'll find this answer helpful.

Export data from MSSQL to Excel 'template' saving with a new name using Python

I am racking my brain here and have read a lot of tutorials, sites, sample code, etc. Something is not clicking for me.
Here is my desired end state.
Select data from MSSQL - Sorted, not a problem
Open an Excel template (xlsx file) - Sorted, not a problem
Export data to this Excel template and saving it with a different name - PROBLEM.
What I have achieved so far: (this works)
I can extract data from DB.
I can write that data to Excel using pandas, my line of code for doing that is: pd.read_sql(script,cnxn).to_excel(filename,sheet_name="Sheet1",startrow=19,encoding="utf-8")
filename variable is a new file that I create every time the for loop runs.
What my challenge is:
The data needs to be export to a predefined template (template has formatting that must be present in every file)
I can open the file and I can write to the file, but I do not know how to save that file with a different name through every iteration of the for loop
In my for loop I use this code:
#this does not work
pd.read_sql(script,cnxn)
writer = pd.ExcelWriter(SourcePath) #opens the source document
df.to_excel(writer)
writer.save() #how to I saveas() a different file name?????
Your help would be highly appreciated.

Your method is work. The problem is you don't need to write the data into excel file right after you read the data from the database. My suggestion is first read the data into different data frame.
df1 = pd.read_sql(script)
df2 = pd.read_sql(script)
df3 = pd.read_sql(script)
You can then write all the dataframe together to a excel file. You can refer to this link.
I hope this solution can help you. Have a nice weekend

Writing value to given filed in csv file using pandas or csv module

Is there any way you can write value to specific place in given .csv file using pandas or csv module?
I have tried using csv_reader to read the file and find a line which fits my requirements though I couldn't figure out a way to switch value which is in the file to mine.
What I am trying to achieve here is that I have a spreadsheet of names and values. I am using JSON to update the values from the server and after that I want to update my spreadsheet also.
The latest solution which I came up with was to create separate sheet from which I will get updated data, but this one is not working, though there is no sequence in which the dict is written to the file.
def updateSheet(fileName, aValues):
with open(fileName+".csv") as workingSheet:
writer = csv.DictWriter(workingSheet,aValues.keys())
writer.writeheader()
writer.writerow(aValues)
I will appreciate any guidance and tips.

You can try this way to operate the specified csv file
import pandas as pd
a = ['one','two','three']
b = [1,2,3]
english_column = pd.Series(a, name='english')
number_column = pd.Series(b, name='number')
predictions = pd.concat([english_column, number_column], axis=1)
save = pd.DataFrame({'english':a,'number':b})
save.to_csv('b.csv',index=False,sep=',')

Add data to existing excel file using python

I am trying to add data to an existing excel file, the problem I am facing is that the data is getting imported but the equation and the format is being deleted in original file.
I attached my code below
import xlwt
import xlrd
from xlutils.copy import copy
#open the excel file
rb=xlrd.open_workbook('Voltage_T.xlsx')
#make a writable copy of the opened excel file
wb=copy(rb)
#read the first sheet to write to within the writable copy
w_sheet=wb.get_sheet(0)
#write or modify the value at 2nd row first column
w_sheet.write(0,1,'WWW.GOOGLE.COM')
#the last step saving the work book
wb.save('Voltage_WW.xls')

You need to set formatting_info to true
rb=xlrd.open_workbook('Voltage_T.xlsx', formatting_info = True)
However xlrd doesn't support xlsx with formatting_info at the moment. So if you really have to use .xlsx you will need another library.
I didn't used it myself so I can't tell you if it's a good library but thanks to a quick search on google XlsxWriter seems to answer your needs.

python pandas formula to dataframe

I am creating a dataframe with a bunch of calculations and adding new columns using these formulas (calculations). Then I am saving the dataframe to an Excel file.
I lose the formula after I save the file and open the file again.
For example, I am using something like:
total = 16
for s in range(total):
df_summary['Slopes(avg)' + str(s)]= df_summary[['Slope_S' + str(s)]].mean(axis=1)*df_summary['Correction1']/df_summary['Correction2'].mean(axis=1)
How can I make sure this formula appears in my excel file I write to, similar to how we have a formula in an excel worksheet?

You can write formulas to an excel file using the XlsxWriter module. Use .write_formula() https://xlsxwriter.readthedocs.org/worksheet.html#worksheet-write-formula. If you're not attached to using an excel file to store your dataframe you might want to look into using the pickle module.
import pickle
# to save
pickle.dump(df,open('saved_df.p','wb'))
# to load
df = pickle.load(open('saved_df.p','rb'))

I think my answer here may be responsive. The short of it is you need to use openpyxl (or possibly xlrd if they've added support for it) to extract the formula, and then xlsxwriter to write the formula back in. It can definitely be done.
This assumes, of course, as #jay s pointed out, that you first write Excel formulas into the DataFrame. (This solution is an alternative to pickling.)