Is it possible to make the price including taxes appearing and how to make it?
Thanks!
The tax calculation requires the customer's address, so unfortunately it's not possible to have that full price display (in an accurate way) outside of the Checkout area, without heavy code modification.
You may want to consider adding a note in your product descriptions that mentions where the tax is applicable and what the rate is - so your customers in that area have an idea before they are at the Checkout page.
Related
I am trying to create a formula to use in a budget spreadsheet. This particular section I am struggling with is in the savings section. I want to create a formula that will pull money from my paycheck balance (reflected in one cell) if it reflects a negative number (meaning I am taking money from my savings), however if it is a positive number (meaning I am adding money to my savings) it will just add to the current balance of the savings (another cell). I hope this makes sense and someone can help.
I can't think of the right formula to even begin.
I am interested in creating different product options within options in Opencart. For example, I am selling art prints in various sizes and would like to add an additional option of framing, however the price of the frame must change according to the print size. So if a customer chooses a print of 11 in x 18 in, the framing price would display as less than if they opted for an 18 in x 24in. How can I do this in Opencart so the framing price will automatically adjust depending on print size?
I don't want to just say "Google it" but what you are looking for is an extension that implements "Dependent Options" of which there are several.
There are many in the extension store but a Google Search works better than the built-in search, so try these:
https://www.google.com/search?q=opencart+dependent+options
As always look for extensions from reputable OpenCart developers with loads of downloads, 5 star votes and positive comments.
Here is an example:
https://www.opencart.com/index.php?route=marketplace/extension/info&extension_id=13882
838 sales. 5 stars and "MarketInSG" are well known and good developers.
Go to products->edit(or) add product->option tab. Here you can add the sizes of the product. once you add one size you automatically get the price tab. You can decrease or increase the price of your product for that specific size there.
I need help regarding Magento 1.9.2, I want to show the Tax amount but don't want to include in SubTotal and in GrandTotal amount.
i have already play around with Tax Settings admin-->System-->Configuration-->Sales-->Tax-->Shopping Cart Display Settings
But still no Result. I have also visited similar question's post on this Forum or any other forums but all in vain.
Please have look at the image below
Anyone, please help to purpose any solution.
I am still not sure what you want to achieve. Grand total = Subtotal + Tax. this is common logic.
but whatever. Answer to your question is:
You may manipulate renderer templates for totals.
Located at app/design/frontend/base/default/template/tax/checkout
(or in the Theme app/design/frontend/Your Theme/Path/template/tax/checkout)
You can simply use this getter $this->getTotal()->getValueExclTax() in renderer template ../template/tax/checkout/grandtotal.phtml
to get Grandtotal without Tax.
I would like to construct a spot curve from supplied bond prices. I know that the curve has to be constructed from dirty prices (i.e. the ones that include accrued interest). However, from FittedBondCurve.cpp example posted on quantlib.org, it appears that FixedRateBondHelper class is initialized with clean prices.
So, my question is: does it mean that FixedRateBondHelper takes care of computing accrued interest and converting clean price to dirty price? Or is it something that a user should do? I believe it's the former but wanted to make sure.
The helper doesn't, but the fitting algorithm does. If you look at the FittedBondDiscountCurve::FittingMethod::FittingCost::value method, you'll cringe a bit at the nested inner classes, but then you'll see that the model price is calculated by adding the discounted future cash flows and subtracting the accrued amount.
A further note: in recent releases, the bond helpers have been given the possibility to work with quoted dirty prices when bootstrapping a curve (see the last parameter of their constructors, useCleanPrice, which defaults to true but can be set to false to use dirty prices. However, the FittedBondDiscountCurve class is not yet aware of this change, and thus setting useCleanPrice to false would break the algorithm. I'll try to fix this in a future release.
Having implemented an algorithm to recommend products with some success, I'm now looking at ways to calculate the initial input data for this algorithm.
My objective is to calculate a score for each product that a user has some sort of history with.
The data I am currently collecting:
User order history
Product pageview history for both anonymous and registered users
All of this data is timestamped.
What I'm looking for
There are a couple of things I'm looking for suggestions on, and ideally this question should be treated more for discussion rather than aiming for a single 'right' answer.
Any additional data I can collect for a user that can directly imply an interest in a product
Algorithms/equations for turning this data into scores for each product
What I'm NOT looking for
Just to avoid this question being derailed with the wrong kind of answers, here is what I'm doing once I have this data for each user:
Generating a number of user clusters (21 at the moment) using the k-means clustering algorithm, using the pearsons coefficient for the distance score
For each user (on demand) calculating their a graph of similar users by looking for their most and least similar users within their cluster, and repeating for an arbitrary depth.
Calculating a score for each product based on the preferences of other users within the user's graph
Sorting the scores to return a list of recommendations
Basically, I'm not looking for ideas on what to do once I have the input data (I may need further help with that later, but it's not the point of this question), just for ideas on how to generate this input data in the first place
Here's a haymaker of a response:
time spent looking at a product
semantic interpretation of comments left about the product
make a discussion page about a product, brand, or product category and semantically interpret the comments
if they Shared a product page (email, del.icio.us, etc.)
browser (mobile might make them spend less time on the page vis-à-vis laptop while indicating great interest) and connection speed (affects amt. of time spent on the page)
facebook profile similarity
heatmap data (e.g. à la kissmetrics)
What kind of products are you selling? That might help us answer you better. (Since this is an old question, I am addressing both #Andrew Ingram and anyone else who has the same question and found this thread through search.)
You can allow users to explicitly state their preferences, the way netflix allows users to assign stars.
You can assign a positive numeric value for all the stuff they bought, since you say you do have their purchase history. Assign zero for stuff they didn't buy
You could do some sort of weighted value for stuff they bought, adjusted for what's popular. (if nearly everybody bought a product, it doesn't tell you much about a person that they also bought it) See "term frequency–inverse document frequency"
You could also assign some lesser numeric value for items that users looked at but did not buy.