by using these two tables we have to create third table in this format
where categories will be on the top and transaction will be in the rows,

On 30 August 2017 at 16:42, Hemant Sain <hemantsai...@gmail.com> wrote:

> Hello Ulrik,
> Can you please once check this code again on the following data set
> because it doesn't giving same output to me due to absence of quantity,a
> compare to previous demo data set becaue spiting is getting done on the
> basis of quantity and in real data set quantity is missing. so please use
> following data set and help me out please consider this mail is my final
> email i won't bother you again but its about my job please help me
> .
>
> Note* the file I'm attaching is very confidential
>
> On 30 August 2017 at 15:02, Ulrik Stervbo <ulrik.ster...@gmail.com> wrote:
>
>> Hi Hemant,
>>
>> Does this help you along?
>>
>> table_1 <- textConnection("Item_1;Item_2;Item_3
>> 1KG banana;300ML milk;1kg sugar
>> 2Large Corona_Beer;2pack Fries;
>> 2 Lux_Soap;1kg sugar;")
>>
>> table_1 <- read.csv(table_1, sep = ";", na.strings = "", stringsAsFactors
>> = FALSE, check.names = FALSE)
>>
>> table_2 <- 
>> textConnection("Toiletries;Fruits;Beverages;Snacks;Vegetables;Clothings;Dairy
>> Products
>> Soap;banana;Corona_Beer;King Burger;Pumpkin;Adidas Sport Tshirt XL;milk
>> Shampoo;Mango;Red Label Whisky;Fries;Potato;Nike Shorts Black L;Butter
>> Showergel;Oranges;grey Cocktail;cheese pizza;Tomato;Puma Jersy red M;sugar
>> Lux_Soap;;2 Large corona Beer;;Cheese;Toothpaste")
>>
>> table_2 <- read.csv(table_2, sep = ";", na.strings = "", stringsAsFactors
>> = FALSE, check.names = FALSE)
>>
>> library(tidyr)
>> library(dplyr)
>>
>> table_2 <- gather(table_2, "Category", "Item")
>>
>> table_1 <- gather(table_1, "Foo", "Item") %>%
>>   filter(!is.na(Item))
>>
>> table_1 <- separate(table_1, col = "Item", into = c("Quantity", "Item"),
>> sep = " ")
>>
>> table_3 <- left_join(table_1, table_2, by = "Item") %>%
>>   mutate(Item = paste(Quantity, Item)) %>%
>>   select(-Quantity)
>>
>> table_3 %>%
>>   group_by(Foo, Category) %>%
>>   summarise(Item = paste(Item, collapse = ", ")) %>%
>>   spread(key = "Category", value = "Item")
>>
>> You need to figure out how to handle words written with different cases
>> and how to get the quantity in an universal way. For the code above, I
>> corrected these things by hand in the example data.
>>
>> HTH
>> Ulrik
>>
>> On Wed, 30 Aug 2017 at 10:16 Hemant Sain <hemantsai...@gmail.com> wrote:
>>
>>> Hey PIKAL,
>>> It's not a homework neithe that is the real dataset i have signer NDA for
>>> my company so that i can share the original data file, Actually I'm
>>> working
>>> on a market basket analysis task but not able to convert my existing data
>>> table to appropriate format so that i can apply Apriori algorithm using
>>> R,
>>> and this is very important me to get it done because I'm an intern and
>>> if i
>>> won't get it done they will not  going to hire me as a full-time
>>> employee.
>>> i tried everything by myself but not able to get it done.
>>> your precious 10-15 can save my upcoming years. so please if you can
>>> please
>>> help me through this.
>>> i want another dataset based on first two dataset i have mentioned .
>>>
>>> Thanks
>>>
>>> On 30 August 2017 at 12:49, PIKAL Petr <petr.pi...@precheza.cz> wrote:
>>>
>>> > Hi
>>> >
>>> > It seems to me like homework, there is no homework policy on this help
>>> > list.
>>> >
>>> > What do you want to do with your table 3? It seems to me futile.
>>> >
>>> > Anyway, some combination of melt, merge, cast and regular expressions
>>> > could be employed in such task, but it could be rather tricky.
>>> >
>>> > But be aware that
>>> >
>>> > Suger does not match sugar (I wonder that sugar is dairy product)
>>> >
>>> > and you mix uppercase and lowercase letters which could be also
>>> > problematic, when matching words.
>>> >
>>> > Cheers
>>> > Petr
>>> >
>>> > > -----Original Message-----
>>> > > From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of
>>> Hemant
>>> > Sain
>>> > > Sent: Wednesday, August 30, 2017 8:28 AM
>>> > > To: r-help@r-project.org
>>> > > Subject: [R] Dataframe Manipulation
>>> > >
>>> > > i want to do a market basket analysis and I’m trying to create a
>>> dataset
>>> > for that
>>> > > i have two tables, one table contains daily transaction of products
>>> in
>>> > which
>>> > > each row of table shows item purchased by the customer, The second
>>> table
>>> > > contains parent group under those products are fallen, for example
>>> under
>>> > fruit
>>> > > category there are several fruits like mango, banana, apple etc.
>>> > > i want to create a third table in which parent group are mentioned as
>>> > header
>>> > > which can be extracted from Table 2, and all the rows represent
>>> > transaction of
>>> > > products
>>> > >
>>> > > with their names, and if there is no transaction for any parent
>>> category
>>> > then
>>> > > the cell supposed to fill as NA. please help me with R or C/c++
>>> code( R
>>> > would be
>>> > >
>>> > > preferred) here I’m attaching you all three tables for better
>>> reference
>>> > i have
>>> > > first two tables and i want to get a table like table 3
>>> > >
>>> > > Tables are explained in the attached doc.
>>> > >
>>> > > --
>>> > > hemantsain.com
>>> >
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>>> --
>>> hemantsain.com
>>>
>>>         [[alternative HTML version deleted]]
>>>
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>>
>>
>
>
> --
> hemantsain.com
>



-- 
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