chui | Declarative containerized chisel for punching holes | Dependency Injection library
kandi X-RAY | chui Summary
kandi X-RAY | chui Summary
A small wrapper around Chisel. The goal of this project is to make it easier to work with chisel in a declarative way.
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QUESTION
Here's a snippet of my JSON object (EDITED) -
...ANSWER
Answered 2022-Feb-14 at 03:49QUESTION
I have the following html that I need to parse, how access all items of window.WIZ_global_data
as a normal dictionary? Is window.WIZ_global_data
is also an attribute of script tag?
I am able to access the script
tag through soup.head.script
ANSWER
Answered 2021-Nov-19 at 12:22You can go with re
to search for the variable, extracting its value and then json.loads()
to access it like a dictionary
:
QUESTION
I have a daily transactional dataset with gaps. I want to see whether a product with a reference price websiteprice
of $X on date T had an actual sold price actualsoldprice
$Y >= $X for at least 10% of previous T – 90 days. In other words, for each transaction where sale_at_or_above_refprice
== 1, we need to count how many times the actual sold price for prior transactions (of a given product) within the previous 90 days met or exceeded that transaction's reference price.
I have included first step results that I am looking for in the wanted
variable.
My data is as follows,
...ANSWER
Answered 2021-Jun-04 at 23:50*Start by converting date to Stata date
gen stata_date = date(orderdate,"DM20Y")
format stata_date %td
*Sort data and product code as stop conditions in while loop expect them to be sorted
sort productcode stata_date
*Create varialbe to store result
gen count_less = .
*Loop over all rows
count
forvalue row = 1/`r(N)' {
*Only applicable to
if sale_at_or_above_refprice[`row'] == 1 {
*Set result variable to 0 for this row
replace count_less = 0 if _n == `row'
*Initate locals used in while loop
local true = 1
local row_skip = 1
local count = 0
local last_date = stata_date[`row']
*Loop until any stop condition sets local true to 0
while `true' == 1 {
*Test if row_skip hits top of data set (i.e row 0)
if `row'-`row_skip' == 0 local true = 0
*Test that product is same in compare row
else if productcode[`row'] != productcode[`row'-`row_skip'] local true = 0
*Test that previous order is within 90 days
else if stata_date[`row'] - stata_date[`row'-`row_skip'] > 90 local true = 0
*Test if actualsoldprice is less thatn old websiteprice
else if websiteprice[`row'] <= actualsoldprice[`row'-`row_skip'] {
* Each date can only be counted once, so test if date is last date counted
if `last_date' != stata_date[`row'-`row_skip'] {
*Compare row fits condition, add 1 to counter
local count = `count' + 1
*Update last counted date
local last_date = stata_date[`row'-`row_skip']
}
}
*Skip one more prevuous row
local row_skip = `row_skip' + 1
}
*Add the count result to the result varaible for this row
replace count_less = `count' if _n == `row'
}
}
QUESTION
I have two files:
file1.txt
:
ANSWER
Answered 2020-Mar-22 at 02:48I think you're making doing what you want much harder than it needs to be, in a relatively slow way that's using a lot more memory than necessary.
To speed up the whole process, a dictionary named geo_dict
is first created from the second file. It maps each unique (lat, log) pair of value to a place name. This will make checking for matches much quicker than doing a linear-search through the list of all of them.
It also unnecessary to convert the values to float
s and int
s, in fact it might be better to not do it because comparing float
values can be problematic on a computer.
Anyway, after the dictionary is created, each line in the first file can be read and processed sequentially. Note that lines with no match are skipped.
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