Data Desired Doing first create derived column Any suggestion is helpful Answer You aren’t using a correct aggregation function. You should be using sum on both your “used” and “total” columns:
Tag: pandas
Finding what is most commonly purchased with a specific product – PANDAS
I am trying to find the most common products purchased with the product ‘SWE’ but am currently stuck. I have the variables ‘product’ and ‘sales_invoice’ So far I have this code: it results in a list of sales invoices containing SWE but does not list the remaining info of the sales invoice(specifically the other products listed on that sales invoice
Pandas on Apple Silicon M1 chip within the Ubuntu container
I have a trouble understanding the issue here: We have Docker image ubuntu:20.04 MacBook Pro on M1 chip Old pandas version wheel (legacy system) Within our Docker image, we use Poetry to manage dependencies: But when we try to build this image on the M1 machine, we face the error ERROR: pandas-0.24.0-cp38-cp38-linux_x86_64.whl is not a supported wheel on this platform.,
Divide ‘count’ and ‘sum’ inside agg function in pandas
Using groupby and agg, is it possible to, in the same expression, get the ‘count’ divided by ‘sum’ returned? Answer Assuming this is a dummy example (else just compute the mean), yes it is possible to combine aggregators using apply: Better alternative in my opinion: output:
saving appended list/dictionary to pandas dataframe
I am working on a code like below, which slices the address column. For this I have created a dictionary and created an empty list final to append all the pre processing.see code After preprocessing I am appending the empty list. Now, I want to update the df_dict with the final list. and convert the df_dict to pandas dataframe. sample
Find string in a dataframe from a list in another dataframe
I have 2 pandas dataframes in python which are set up as folows: Where Paragraph is a string of multiple words. Name is just a string identifying the Words. And Words is a list of strings. So what I want to do is have an expression that will identify which Paragraphs in Dataframe 1 contain Words from Dataframe 2. And
Grouped pandas dataframe from nested list
I have a nested list in this format mydata=[[01/01/20,[‘point1′,’point2’,’point3,…]],[02/01/20,[‘point1′,’point2′,’point3’]],…] I want to create a pandas dataframe grouped by date with every point as a different row. I have tried manually adding each row through a for loop, but other than taking more than an hour, the dataframe ended up being empty. Not sure how to go about this. Can I
Check result of chi square test on pandas columns data
I wrote the test according to an approach I found. When looking in Stack Overflow I saw another approach (can be seen here) which was a little more complicated, and made me wonder if I chose the right one. I’m looking for ways to check if my calculation is correct. Here is the relevant code: Any suggestions will be welcomed.
Column dictionary values into separate Dataframe
I have a dataframe which has a column that contains a list of dictionaries. This is what an example column value it looks like: I want to create a separate dataframe that takes the above column values for each row, and produces a dataframe where ‘category’ is a column, and the values for that columns are score and threshold. For
How to recalculate data from table in flask/python?
I want to show df in my app, im using flask to do it. But how can i make the table editable and calculated sum value by using button? I couldn’t found good and easy way to edit that html table, and somehow send it to backend to recalculate. Most tips i found abuot editables tables involve data from sql