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Error message that I get is as below: Source Code : Answer This is not an error. It’s printing the correct thing. What you are doing is not calling a function instead printing it as an object as in python everything is an object. Solution: This will print your desired output i.e “2019 Tesla Model S”

Dynamic SQL queries with SQLite3

I would like to allow users to query a sql database. The database is here So the user will be able to enter the queries they want: and then the query will execute: If the user enters both variables like city=’SQL City’ and type=’murder’ it works as it finds both values in the same row, but if the user leaves

python: label position lineplot() with secondary y-axes

I have a produce a plot with secondary y-axes and the labels are on top of each other: The code is the following: is there a way to manually change the position of label C so it does not get on top of A? Answer One way to do this is to remove the individual legends (ax and ax2) and

Adding secondary group by clause using groupby_dynamic() operation in polar

I would like to groupby the data in interval of a hourly/daily/weekly and further group by certain other clauses. I was able to acheive groupby hourly/daily/weekly basis by using groupby_dynamic option provided by polars. How do we add a secondary non datetime groupby clause to the polars dataframe after using groupby_dynamic operation in polar? The sample dataframe read from csv

Django queryset to list of ids with integer values

I need to retrieve IDs from multiple queries and add them into a list. Then I tried This raised error as list cannot be added to queryset. so, I tried, This works but, all_products has a mix of int and tuple values [10, 20, 30, (2,), (2,), (1,)] I need them to be [10, 20, 30, 2, 2, 1] Answer

Updating columns of list based on match

Purpose The main purpose is to be able to compute the share of resources used by node i in relation to its neighbors: r_i / sum_j^i{r_j} where r_i are node i resources and sum_j^i{r_j} is the sum of i’s neighbors’ resources. I am open to any R, python or eventually stata solutions, that are able to achieve this task on