I'm relatively new to performing data analysis with python, thus I'm sorry if this question seems too noob.
I have an excel-file with many different sheets. I've also written a script which fits and plots the data contained in these excel sheets. I have code written to perform curve fitting for only one of the sheets.
My idea was to create a loop that would iterate through all my sheets and apply the script in each one of them at a time, but I'm not really sure how to do this. Could you provide me any guidance, or any place where I could learn/read about how to do this? I have tried to search a bit around but I haven't been able to find anything useful.
Thanks!
I'm assuming you're trying to loop through different sheets of a single excel file. If so, you can use pd.read_excel's sheet_name parameter to pass sheets programmatically. (See https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html)
So, if you wanted to loop through the first three sheets, you could use:
for i in range(3):
df = pd.read_excel('path/to/file.xlsx', sheet_name=i)
do_stuff(df)
Related
I have a folder of 310 .csv files. Here is a sample of what the contents look like
I need to create a program that goes through all the files, lists the file name, then lists the top 4 values from the table and the x-value associated with it. Ideally this would all be saved to a text doc but as long as it prints in a readable format that would be ideal.
So, what is stopping you? Loop through the files, use pandas.read_csv to import each csv file and merge/join them all into one DataFrame. Use slicing to select the 4 top rows, and you can always print/visualize anything directly in a Jupyter Notebook. Exporting can be done using df.to_csv or any other method and if you need a short introduction to pandas, look here.
Keep in mind that it is always a good idea, to include a Minimal, Reproducible Example. Especially for a complicated merge operation between many DataFrames, this could help you a lot. However, there is no way around some research.
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 pretty new to Pandas and Python, but have solid coding background. I've decided to pick this up because it will help me automate certain financial reports at work..
To give you a basic background of my issue, I'm taking a PDF and using Tabula to reformat it into a CSV file, which is working fine but giving me certain formatting issues. The reports come in about 60 page PDF files, which I am exporting to a CSV and then trying to manipulate the data in Python using Pandas.
The issue: when I reformat the data, I get a CSV file that looks something like this -
The issue here is that certain tables are shifting and I think it is due to the amount of pages and multiple headings within those.
Would it be possible for me to reformat this data using Pandas, and basically create a set of rules for how it gets reformatted?
Basically, I would like to shift the rows that are misplaced back into their respective places based on something like blank spaces.
Is it possible for me to delete rows with certain strings - deleting extra/unnecessary headers.
Can I somehow save the 'Total' data at the bottom by searching for the row with 'Total' and placing it somewhere else?
In essence, is there a way to partition this data by a set of commands (without specifying row numbers - because this changes daily) and then reposition it accordingly so that I can manipulate the data however necessary?
I am writing a program that will process a bunch of data and fill a column in excel. I am using openpyxl, and strictly using write_only mode as well. Each column will have a fixed 75 cell size, and each cell in the row will have the same formula applied to it. However, I can only process the data one column at a time, I cannot process an entire row, then iterate through all of the rows.
How can I write to a column, then move onto the next column once I have filled the previous one?
This is a rather open ended question, but may I suggest using Pandas. Without some kind of example of what you are trying to achieve it's difficult to make a great recommendation, but I have used pandas in the past a ton for automating processing of excel files. Basically you would just load whatever data into a Pandas DataFrame, then do your transformations/calculations and whenever you are done write it back to either the same or a new excel file (or a number of other formats).
Because the OOXML file format is row-oriented, you must write in rows in write-only mode, it is simply not possible otherwise.
What you might be able to do is to create some kind transitional object that will allow to fill it with columns and then use this to write to openpyxl. A Pandas DataFrame would probably be suitable for this and openpyxl supports converting these into rows.
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.