calc3 | Simple javascript calculator for course labs | Apps library
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Simple javascript calculator for course labs
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QUESTION
Table_exaple Hello,
I need some help.
My problem is that I can't figure out how to do this. The whole point of my simple project is to create a table only with input text boxes where only integers will be added, and I need to sum columns only.
As Quantity sum I mean to calculate the whole column and by Calculated sum I need to calculate the Quantity * value of the Heading.
For example: Quantity of column 5$ is 50 therefore the calculated cell must be 250$.
I would also like to add a button that adds columns dynamically and the heading is Custom... so somehow the heading value should be saved as a variable too.
I tried something with jQuery, but it's not relevant because I want that to be calculated dynamically no matter what input I enter in the heading.
Here is my bad jQuery for each column, it works, but that's not the goal.
...ANSWER
Answered 2021-Jun-08 at 21:23The pattern you're looking to follow is called 'Don't Repeat Yourself', or DRY. It's core principle is to create reusable generic structures which do not contain identifiers, but simply any metadata required for processing.
In this case you can provide all the input
elements with common class names, not incremental ones nor id
. Then in the JS you can determine which column the user is interacting with using index()
. From there you can use map()
to build an array of all the values in that column and sum them. Finally you can store the column price in a data
attribute on the heading and multiply the quantity by that figure to give you your calculated total.
In practice it will look something like the below. Note that this JS will work for an infinite number of rows and columns, all it depends on is the data
attribute on the th
in order to provide the unit price.
QUESTION
I am pretty good with simple Pandas but am struggling with data reshaping and multi indices. I have a multindex dataframe that looks like so (it doesnt have to be a multindex but it seems the right thing to do)
name index f1 f2 f3 calc1 calc2 calc3 fox 1 red white fur 0.21 1.67 -0.34 2 0.76 2.20 -1.02 3 0.01 1.12 -0.22 chicken 1 white yellow feathers 0.04 1.18 -2.01 2 0.18 0.73 -1.21 grain 1 yellow bag corn 0.89 1.65 -1.03 2 0.34 2.45 -0.45 3 0.87 1.11 -0.97and all I want is:
name f1 f2 f3 calc1_1 calc2_1 calc3_1 calc1_2 calc2_2 calc3_2 calc1_3 calc2_3 calc3_3 fox red white fur 0.21 1.67 -0.34 0.76 2.20 -1.02 0.01 1.12 -0.22 chicken white yellow feathers 0.04 1.18 -2.01 0.18 0.73 -1.21 NaN NaN NaN grain yellow bag corn 0.89 1.65 -1.03 0.34 2.45 -0.45 0.87 1.11 -0.97I figure this has got to be an easy one for the pandas gurus out there. Thanks all for your help!!
Drew
...ANSWER
Answered 2021-May-28 at 18:16QUESTION
I'm trying to make a calculation on multiple rows for every row in a dataframe.
My current solution takes so much time when I run 2971000 rows. it almost takes more than 2hours.
So, I want know other solutions to speed up a function
my data looks like this for example.
...ANSWER
Answered 2021-Apr-02 at 13:08Iteration is easy to code but slow for dataframe. Here is a hint to your solution. You need to vectorize the code inside the while loop while n < len(sig_p):
.
For example, previously your code:
QUESTION
1. I have created a class to have the basic functions of a calculator and the class is named Calculator
class Calculator:
def __init__(self, num1, num2):
self.num1 = num1
self.num2 = num2
def addition(self, num1, num2):
finalNum = num1 + num2
print(finalNum)
def extraction(self, num1, num2):
finalNum = num1 - num2
return finalNum
def multiplication(self, num1, num2):
finalNum = num1 * num2
return finalNum
def division(self, num1, num2):
finalNum = num1 / num2
return finalNum
calc = Calculator()
calc2 = Calculator()
calc3 = Calculator()
calc4 = Calculator()
print(calc.addition(14,76))
...ANSWER
Answered 2021-Mar-25 at 07:20the init function is constructor,so you have to declare the variable like: calc = Calculator(74, 23)
or you can change the init function like
QUESTION
Forgive the question as I'm a science major, not computer science and I'm teaching myself Python to help with a class project.
I have a Pandas data frame that I've imported from a .csv that looks like:
...ANSWER
Answered 2020-Oct-21 at 01:10You can use groupby
followed by agg
methods to do that.
First, define your calculations as functions:
QUESTION
Referring to GCC website. It is stated that
The tls_model attribute sets thread-local storage model (see Thread-Local) of a particular __thread variable, overriding -ftls-model= command-line switch on a per-variable basis. The tls_model argument should be one of global-dynamic, local-dynamic, initial-exec or local-exec. Not all targets support this attribute.
In order to look into the differences of the assembly generated for different TLS models, a class was created with three __thread variables.
...ANSWER
Answered 2020-Aug-26 at 10:35This is a bug, possibly in the C++ frontend, and/or in attribute merging code. If you move or duplicate the attribute from the declaration on the definition, it works as intended. If you eliminate the definitions, and leave only the declarations, it also works according to the documentation. Basically, each definition does not appear to properly inherit the attribute from the preceding declaration. This is worthy of a bugreport at https://gnu.gnu.org/bugzilla
QUESTION
def calc1(tentative_valuations, previous_buying_price):
return tentative_valuations - previous_buying_price
#mortgage calculator
def calc2(loanper, previous_buying_price):
return loanper * previous_buying_price
#indicative paid interest to date **REQUIRES ACCESSOR** ###################
calc3 = int(lookups((ym_between(b, a)[0]), (ym_between(b, a)[1]), 'Cum Interest Paid'))
# #net indicative capital gain today #######################################
calc4 = calc1(tentative_valuations, previous_buying_price) - calc3
#print(calc4)
# #to calculate psf before
def calc5(previous_buying_price, area):
return previous_buying_price/area
# #to calculate psf after
def calc6(tentative_valuations, area):
return tentative_valuations/area
#print(calc5(previous_buying_price,area))
#print(calc6(tentative_valuations, area))
# #annualised ##########################################
def calc7():
return round((((calc6(tentative_valuations, area)/calc5(previous_buying_price, area))**(1/(ym_between(b,a)[0]+ ym_between(b,a)[1]/12))) - 1)*100,2)
#no problem
#print(calc7())
#indicative paid principal to date
calc8 = int(lookups((ym_between(b, a)[0]), (ym_between(b, a)[1]), 'Cumulative Paid Principal'))
#indicative balance
calc9 = (loanper * previous_buying_price) - calc8
...ANSWER
Answered 2020-Jul-29 at 03:20Calling df2 directly won't do anything.
Change the last line to this:
QUESTION
int add(int n1,int n2) {
return n1+n2;
}
1.Function calc1=add;
2.Function calc2=(int n1,int n2) {
return n1+n2;
};
3.var calc3=(int n1,int n2)=>{
n1+n2
};
4.var callc=(int n1,int n2) {
return n1+n2;
};
...ANSWER
Answered 2020-May-07 at 07:26These do slightly different things that may or may not act the same depending on how you use them.
1.
QUESTION
I want to programm a simple 'calculator'.. Some Input fields, then some calculations with those inputs in the background and then I want to see output.
In a simple form it looks like that:
a-e: are input fields.
f-h: output fields.
The calculations in the background and the showing of output goes well.
Now I want to have a line between e and f that says: Output
Without any entry field or sth.. just a textfield. Can someone help me, how to insert a textfield on a specific place ? This is the code:
...ANSWER
Answered 2020-Apr-02 at 08:58You can use below code to create a separator with text:
QUESTION
I have a query I'm writing that needs to run on both SQL Server and MySQL that involves performing a very lengthy calculation. If I write it all in one query, it involves a ton of copy and pasting and redundant, hard-to-maintain code. Therefore, I wrote a much more compact version that essentially looks like this:
...ANSWER
Answered 2019-Nov-19 at 19:36I only have access to a small testing dataset, so I can't run it and time it, since it takes less than a second to run with the small dataset. And I don't have permissions to view the execution plan. So I'm not sure how to go about verifying that this won't be a disaster, performance-wise. (I can test it on copies of the productive databases, but it's a long and painful process)
That's the problem you need to fix. Strangers' speculation on the performance of imaginary queries on multiple database engines is nothing to go on.
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