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I'm new to Python. I have a dictionary where some fields are dates ( datetime.datetime type) and I need to use comprehension to convert those to MM/DD/YYYY strings in a new cloned dictionary.

I was getting started with

I see that jq can calculate addition as simply as jq 'map(.duration) | add' but I've got a more complex command and I can't figure out how to perform this add at the end of it.

I'm starting with data like this:

Sorry if this is a noob question!

I have two tables - a movie and a comment table.

I am trying to return output of the movie name and each comment for that movie as long as that movie has more than 1 comment associated to it.

Here are my tables

I am writing a program in python to have a user input multiple websites then request and scrape those websites for their titles and output it. However, when the program surpasses 8 websites the program crashes every time. I am not sure if it is a memory problem, but I have been looking all over and can't find any one who has had the same problem. The code is below (I added 9 lists so all you have to do is copy and paste the code to see the issue).

I have bitcoin historical data. I split the "DATE" Colum as "year month days and hour" because I wanted to sort data based on hours["AS it is hourly base data"]. the data goes up to 2021-12 ie Decmber["the dates goes from 1 to 30 every month"]. I want to sort this data further as:- "2019-Jan, 2020-Jan 20201-Jan" then "2019-Feb,2020-Feb, 2021-Feb" and soon on

can this be done by saying I have split the "DATE" column? if YES please any suggestion on how this can be achieved

The original "DATE" colum was as follows :- 2019-01-01T00:00:00Z

People of Stack Overflow!

Thanks for taking the time to read this question. What I am trying to accomplish is to pivot some data all from just one table. The original table has multiple datetime entries of specific events (e.g. when the customer was added add_time and when the customer was lost lost_time). This is one part of two rows of the deals table:

I want to create a view of this table. A view that has one row for each distinct date and counts the number of events at this specific time.

This is the goal (times do not match with the example!):

I have working code, like this:

I have a dataset with the name of Danish ministers and their position from 1990 to 2020 (data comes from dataset called WhoGovern; https://politicscentre.nuffield.ox.ac.uk/whogov-dataset/). The dataset consists of the ministers name, the ministers position, the prestige of that position, and the year in which the minister had that given position.

My problem is that some ministers are counted twice in the same year (i.e., the rows aren't unique in terms of name and year). See the example in the picture below, where "Bertel Haarder" was both Minister of Health and Minister of Interior Affairs in 2010 and 2021.

I want to create a dataset, where all the rows are unique combinations of name and year. However, I do not want to remove any information from the dataset. Instead, I want to use the information in the prestige column to combine the duplicated rows into one. The observations with the highest prestige should be the main observations, where the other information should be added in a new column, e.g., position2 and prestige2. In the example with Bertel Haarder the data should look like this:

(PS: Sorry for bad presenting of the tables, but didn't know how to create a nice looking table...)

Here's the dataset for creating a reproducible example with observations from 2010-2020:

I have the following dictionary of exchange rates:

I've upgraded to the M1 chip 2020 Macbook Air from a 7th gen. Intel chip pc. Overall, I'm very happy and content with it but when it comes to Android Studio performance, which I use quite often, it is very disappointing I'm sorry to say. When will an Apple Silicon compatible version be available? Are any of you guys have any clue?