I used the Python Pandas library as a wrap-around instead of using SQL. Everything worked perfectly, except when I open the output excel file, the cells appear blank, but when I click on the cell, I can see the value in the cell above. Additionally, Python and Stata recognize the value in the cell, even though the eye cannot see it. Furthermore, if I do "text to columns", then the values in the cell become visible to the eye.
Clearly it's a pain to go through every column and click "text to columns", and I'm wondering the following:
(1) Why is the value not visible to the eye when it exists in the cell?
(2) What's the easiest way to make all the values visible to the eye aside from the cumbersome "text to columns" for all columns approach?
(3) I did a large number of tests to make sure the non-visible values in the cells in fact worked in analysis. Is my assumption that the non-visible values in the cells will always be accurate, true?
Thanks in advance for any help you can provide!
It sounds to me like your python code is inserting a carriage return either before or after the value.
I've replicated this behavior in Excel 2016 and can confirm that the cell appears blank, but does contain a value.
Furthermore, I've verified that using the text to columns will parse the carriage return out.
Related
I'm having trouble finding a solution to fill out an excel template using python. I currently have a pandas dataframe where I use openpyxl to write the necessary data to specific Rows and Cells in a for loop. The issue I have is that in my next project several of the cells I have to write are not continuous so for example instead of going A1,A2,A3 it can go A1,A5,A9. However this time if I were to list the cells like I did in the past it would be impractical.
So I was looking for something that would work similar to a Vlookup in excel. Where in the template we have Python would match the necessary Row and Column to drop the information. I know I might need to use different commands.
I added a picture below as an example. So I would need to drop values in the empty cells and ideally Python would read "USA and Revenue" and know to drop that information on cell B2. I know I might need something to map it also I am just not sure on how to start or if it is even possible.
enter image description here
I'm no sure what the right terminology to use for this ask is, but i want to create a python output that will look something like this:
With the intent of having some Data extracted from specific cells of a dataframe fill in the TEXT section of the image. Obviously i want the data to not be hard-coded so i can change it as per the topic. What packages even do this? I've never explored the "visual" component side of python before.
In my excel file, I have a list of some 7000-8000 binary chemical compounds. (Consists of 2 elements only).
And I have segregated them into their component elements, i.e., I have 2 columns of elements, namely: First Element and Second Element.
I have attached a screenshot below:
Now I want to fill in the respective Atomic Number and Atomic Weight beside every element as per a predefined list using Python.
How do I do that?
I have attached a screenshot of my predefined list below, as well:
People have told me things like, use the "CSV" package or the "pandas" package, but I would request some more procedural help wrt to the above packages or any other method you might suggest.
Also, if it cannot be done via Python, I am open to other languages as well.
I noticed that your task does not require python programming. The reason is :
You already have a predefined list of items stored in a excel sheet.
Excel already has built in function (VLOOKUP) for this task.
We just have to use VLOOKUP function in column Atomic number, Atomic weight ( you have to create columns in data2 sheet ) which will take care of searching for particular element atomic weight, number and return it in active cell.
Next, use fill handle to apply the function to all the cells or ( if data is in table , great!! no need to use fill handle because table automatically applies the function to whole column range )
I expect that you already know how to work with excel formulas and functions, if not comment down below for further assistance. Kindly upvote the answer if you liked it.
NOTE: If you need automation, then be sure to check out Excel VBA, google sheets, Apps script.
I have got a spreadsheet, in which some cells are marked as Input cells. I would like to extract only those cells into a Python variable using, for example, the excel_read() function from pandas.
Is this possible at all?
Sure, if you know beforehand where they are you can specify which columns to use by invoking the parse_cols parameter. But it doesn't look like by reading through the pandas.read_excel function docs that you can programmatically select certain cells within the function call.
However, you could always read in everything and then discard what you don't need based on how Input cells are represented in the DataFrame. Without an example it would hard to guess how to do this currently, but pandas is good for this type of data cleaning.
I'm trying to delete cells from an Excel spreadsheet using openpyxl. It seems like a pretty basic command, but I've looked around and can't find out how to do it. I can set their values to None, but they still exist as empty cells. worksheet.garbage_collect() throws an error saying that it's deprecated. I'm using the most recent version of openpyxl. Is there any way of just deleting an empty cell (as one would do in Excel), or do I have to manually shift all the cells up? Thanks.
In openpyxl cells are stored individually in a dictionary. This makes aggregate actions like deleting or adding columns or rows difficult as code has to process lots of individual cells. However, even moving to a tabular or matrix implementation is tricky as the coordinates of each cell are stored on each cell meaning that you have process all cells to the right and below an inserted or deleted cell. This is why we have not yet added any convenience methods for this as they could be really, really slow and we don't want the responsibility for that.
Hoping to move towards a matrix implementation in a future version but there's still the problem of cell coordinates to deal with.