Develop Reference

How to use Python to automate the movement of data between two Excel workbooks with specific parameters

Thanks for taking the time to read my question.
I am working on a personal project to learn python scripting for excel, and I want to learn how to move data from one workbook to another.
In this example, I am emulating a company employee ledger that has name, position, address, and more (The organizations is by row so every employee takes up one row). But the project is to have a selected number of people be transferred to a new ledger (another excel file). So I have a list of emails in a .txt file (it could even be another excel file but I thought .txt would be easier), and I would want the script to run through the .txt file, get the emails, and look for any rows that have a matching email address(all emails are in cell 'B'). And if any are found, then copy that entire row to the new excel file.
I tried a lot of ways to make this work, but I could not figure it out. I am really new to python so I am not even sure if this is possible. Would really appreciate some help!

You have essentially two packages that will allow manipulation of Excel files. For reading in data and performing analysis the standard package for use is pandas. You can save the files as .xlsx however you are only really working with base table data and not the file itself (IE, you are extracing data FROM the file, not working WITH the file)
However what you need is really to perform manipulation on Excel files directly which is better done with openpyxl
You can also read files (such as your text file) using with open function that is native to Python and is not a third party import like pandas or openpyxl.
Part of learning to program includes learning how to use documentation.
As such, here is the documentation you require with sufficient examples to learn openpyxl: https://openpyxl.readthedocs.io/en/stable/
And you can learn about pandas here: https://pandas.pydata.org/docs/user_guide/index.html
And you can learn about python with open here: https://docs.python.org/3/tutorial/inputoutput.html
Hope this helps.
EDIT: It's possible I or another person can give you a specific example using your data / code etc, but you would have to provide it fully. Since you're learning, I suggest using the documentation or youtube.

Swamped with real time data and tasked with building a database

I work for a power company, and have been tasked with building a database. I have a pretty beginner/intermediate understanding level of python, and can fuddle decently with MSSQL. They have procured Azure for this project, and I am completely lost of how to start this task.
Here is one of the sources of data that I want to scrape every minute.
http://ets.aeso.ca/ets_web/docroot/tradingPage.html - this is a complete overview of the Alberta power market in real time.
Ideally, I would want to be able to scrape this data and other sources, and then modify it to fit into in a certain format and push it onto the SQL server.
Do I need virtual machines that are just looping over python scripts? Or do I need managed instances? This data also then needs to be able to be queried right after it is scraped. Eventually this data may feed machine learning algorithms (I don't know jack about that either but I have been told it should play friendly with that type of enviornment).
Just looking to see if anyone has any insight in how you would approach this, and can tell me what I clearly don't know and haven't thought of. Any insight is truly appreciated.
Thanks!

I need a starting point to code an app to extract text from pdf to excel

To start I just want to state that I'm an Electrical Engineer with basic knowledge of programming.
My requirement is as follows:
I want to create an app where I can load and view PDF files that
contain tables.
These PDF files tables are of irregular shapes and in a different
position on every page. (that's why tools like tabular couldn't help
me)
Each table entry is multiline and of irregular dimensions (I cannot
select a whole row at a time it has to be each element alone. simply
copying the lines to excel won't work either because it will need a
lot of formatting)
So I want to be able to select each table entry individually from the
table (like a selection or cropping box over the required text),
delete new line if there is a new line in the text and just keep spaces.
The generated excel (or access database I do not really mind any)
should be reviewable and saveable (if those are even words XD).
I have a good knowledge of python and a very elementary knowledge of Django and I'm seeking some expert who can tell me what do I really need to learn (and if possible where to learn it) to execute my project.
Is it very much for me to execute and if I can dedicate 10 hours a week, how much would it take me to execute such a project.
Thanks all for your help in advance.

Don't use Python, use Word. Open the pdf, then step through the tables collection to collect the data and put it into excel. See this for an example

Here are the advises i can provide you :
first of all, ask internet for questions :
https://lmddgtfy.net/?q=python%20library%20tabular%20pdf
-> Camelot , which is mentioned multiple time seems to be relevant
For the use of excel sheet, i present you one of the most famous library for manipulating DataFrame: Pandas
You can use small courses on internet which will offer you a quick ability to manage your project easier.
for the application, you can easily find on youtube courses on a library made by someone who will explain you how to do a basic application. It could offer you the entry point you are talking about. Then, You can just wonder what else do you need or simply want for making it better.
for the time needed, it depends on how much time do you need to understand the basics, how much time you spend on having a deeper comprehension. I think in one week, working during your free time with a real interest, it could be working( not perfect, but working, which is a good beginning)
PS: I am not sure if your question is relevant for the aims of stackoverflow. I suggest you to read this file. ( https://stackoverflow.com/help/how-to-ask)

Take data from an xls sheet and add them into python commands

I've been asked to create a Python script to automate a server deployment for 80 retail stores.
As part of this script, I have a secondary script that I call to change multiple values in 9 XML files, however, the values are unique for each store, so this script needs to be changed each time, but after I am gone, this is going to be done by semi / non-technical people, so we don't want them to change the Python scripts directly for fear of breaking them.
This in mind, I would like to have these people input the store details into an XLS sheet, and a python file read this sheet and put the data it finds into the existing python script with the data to be changed.
The file will be 2 columns, with the required data in the 2nd one.
I'm sorry if this is a long explanation, but that is the gist of it. I'm using python 2.6. Does anyone have a clue about how I can do this? Or which language might be better for this. I also know Bash and Javascript.
Thanks in advance

Depending on the complexity and the volume of your data
for small Openpyxl,
for large pandas

Automating IBM SPSS Data Collection survey export?

I'm so sorry for the vague question here, but I'm hoping an SPSS expert will be able to help me out here. We have some surveys that are done via SPSS, from which we extract data for an internal report. Right now the process is very cumbersome and requires going to the SPSS Data Collection Interviewer Server Administration page and manually exporting data from two different projects (which takes hours at a time!). We then take that data, massage it, and upload it to another database that drives the internal report.
My question is, does anyone out there know how to automate this process? Is there a SQL Server database behind the SPSS data? Where does the .mdd file come in to play? Can my team (who is well-versed in extracting data from various sources) tap into the SQL Server database behind SPSS to get our data? Or do we need some sort of Python script and plugin?
If I'm missing information that would be helpful in answering the question, please let me know. I'm happy to provide it; I just don't know what to provide.
Thanks so much.

As mentioned by other contributors, there are a few ways to achieve this. The simplest I can suggest is using the DMS (data management script) and windows scheduler. Ideally you should follow below steps.
Prerequisite:
1. You should have access to the server running IBM Data collection
2. Basic knowledge of windows task scheduler
3. Knowledge of DMS scripting
Approach:
1. Create a new DMS script from the template
2. If you want to perform only data extract / transformation, you only need input and output data source
3. In the input data source, create/build the connection string pointing to your survey on IBM Data collection server. Use the data source as SQL
4. In the select query: use "Select * from VDATA" if you want to export all variables
5. Set the output data connection string by selecting the output data format as SPSS (if you want to export it in SPSS)
6. run the script manually and see if the SPSS export is what is expected
7. Create batch file using text editor (save with .bat extension). Add below lines
cd "C:\Program Files\IBM\SPSS\DataCollection\6\DDL\Scripts\Data Management\DMS"
Call DMSRun YOURDMSFILENAME.dms
Then add a line to copy (using XCOPY) the data / files extracted to the location where you want to further process it.
Save the file and open windows scheduler to schedule the execution of this batch file for data extraction.
If you want to do any further processing, you create an mrs or dms file and add to the batch file.
Hope this helps!

There are a number of different ways you can accomplish easing this task and even automate it completely. However, if you are not an IBM SPSS Data Collection expert and don't have access to somebody who is or have the time to become one, I'd suggest getting in touch with some of the consultants who offer services on the platform. Internally IBM doesn't have many skilled SPSS resources available, so they rely heavily on external partners to do services on a lot of their products. This goes for IBM SPSS Data Collection in particular, but is also largely true for SPSS Statistics.
As noted by previous contributors there is an approach using Python for data cleaning, merging and other transformations and then loading that output into your report database. For maintenance reasons I'd probably not suggest this approach. Though you are most likely able to automate the export of data from SPSS Data Collection to a sav file with a simple SPSS Syntax (and an SPSS add-on data component), it is extremely error prone when upgrading either SPSS Statistics or SPSS Data Collection.
From a best practice standpoint, you ought to use the SPSS Data Collection Data Management module. It is very flexible and hardly requires any maintenance on upgrades, because you are working within the same data model framework (e.g. survey metadata, survey versions, labels etc. is handled implicitly) right until you load your transformed data into your reporting database.
Ideally the approach would be to build the mentioned SPSS Data Collection Data Management script and trigger it at the end of each completed interview. In this way your reporting will be close to real-time (you can make it actual real-time by triggering the DM script during the interview using the interview script events - just a FYI).
All scripting on the SPSS Data Collection platform including Data Management scripting is very VB-like, so for most people knowing VB, it is very easy to get started and it is documented very well in the SPSS Data Collection DDL. There you'll also be able to find examples of extracting survey data from SPSS Data Collection surveys (as well as reading and writing data to/from other databases, files etc.). There are also many examples of data manipulation and transformation.
Lastly, to answer your specific questions:
Yes, there is always an MS SQL Server behind SPSS Data Collection -
no exceptions. However, generally speaking the data model is way to
complex to read out data directly from it. If you have a look in it,
you'll quickly realize this.
The MDD file (short for Meta Data Document) is containing all survey meta
data including data source specifications, version history etc.
Without it you'll not be able to make anything of the survey data in
the database, which is the main reason I'd suggest to stay within the
SPSS Data Collection platform for as large part of your data handling
as possible. However, it is indeed just a readable XML file.
Note that the SPSS Data Collection Data Management Module requires a separate license and if the scripting needed is large or complex, you'd probably want base professional too, if that's not what you already use for developing the questionnaires and handling the surveys.
Hope that helps.

This isn't as clean as working directly with whatever database is holding the data, but you could do something with an exported data set:
There may or may not be a way for you to write and run an export script from inside your Admin panel or whatever. If not, you could write a simple Python script using Selenium WebDriver which logs into your admin panel and exports all data to a *.sav data file.
Then you can use the Python SPSS extensions to write your analysis scripts. Note that these scripts have to run on a machine that has a copy of SPSS installed.
Once you have your data and analysis results accessible to Python, you should be able to easily write that to your other database.