I have two CSV files, the first like so:
Book1:
ID,TITLE,SUBJECT
0001,BLAH,OIL
0002,BLAH,HAMSTER
0003,BLAH,HAMSTER
0004,BLAH,PLANETS
0005,BLAH,JELLO
0006,BLAH,OIL
0007,BLAH,HAMSTER
0008,BLAH,JELLO
0009,BLAH,JELLO
0010,BLAH,HAMSTER
0011,BLAH,OIL
0012,BLAH,OIL
0013,BLAH,OIL
0014,BLAH,JELLO
0015,BLAH,JELLO
0016,BLAH,HAMSTER
0017,BLAH,PLANETS
0018,BLAH,PLANETS
0019,BLAH,HAMSTER
0020,BLAH,HAMSTER
And then a second CSV with items associated with the first list, with ID being the common attribute between the two.
Book2:
ID,ITEM
0001,PURSE
0001,STEAM
0001,SEASHELL
0002,TRUMPET
0002,TRAMPOLINE
0003,PURSE
0003,DOLPHIN
0003,ENVELOPE
0004,SEASHELL
0004,SERPENT
0004,TRUMPET
0005,CAR
0005,NOODLE
0006,CANNONBALL
0006,NOODLE
0006,ORANGE
0006,SEASHELL
0007,CREAM
0007,CANNONBALL
0007,GUM
0008,SERPENT
0008,NOODLE
0008,CAR
0009,CANNONBALL
0009,SERPENT
0009,GRAPE
0010,SERPENT
0010,CAR
0010,TAPE
0011,CANNONBALL
0011,GRAPE
0012,ORANGE
0012,GUM
0012,SEASHELL
0013,NOODLE
0013,CAR
0014,STICK
0014,ORANGE
0015,GUN
0015,GRAPE
0015,STICK
0016,BASEBALL
0016,SEASHELL
0017,CANNONBALL
0017,ORANGE
0017,TRUMPET
0018,GUM
0018,STICK
0018,GRAPE
0018,CAR
0019,CANNONBALL
0019,TRUMPET
0019,ORANGE
0020,TRUMPET
0020,CHERRY
0020,ORANGE
0020,GUM
The real datasets are millions of records, so I'm sorry in advance for my simple example.
The problem I need to solve is getting the data merged and collated in a way where I can see which item groupings most commonly appear together on the same ID. (e.g. GRAPE,GUM,SEASHELL appear together 340 times, ORANGE and STICK 89 times, etc...)
Then I need to see if there is any change/deviation to the general results in common appearance when grouped by SUBJECT.
Tools I'm familiar with are Excel and SQL, but I also have PowerBI and Alteryx at my disposal.
Full disclosure: Not homework, or work, but a volunteer project, thus my unfamiliarity with this kind of data manipulation.
Thanks in advance.
An Alteryx solution:
Drag the two .csv files onto your canvas (seen as book1.csv and book2.csv in my picture; Alteryx will create "Input" tools for you.
Drag a "Join" tool on and connect the two .csv files to its inputs; select "ID" as the join field; unselect the "Right_ID" as output since it's merely a duplicate of "ID"
Drag a "Summary" tool on and connect the Join tool's output to the Summary tool's input; select all three of the outputs and add as a "group by"... then add the ID column with a "count"
Drag a browse tool on and connect the summary's output to the browse tool's input.
run the workflow
After all that, click on the browse tool and you should see what is seen in my screenshot: (which is showing just the first ten rows of output):
+1 for taking on a volunteer project - I think anyone who knows data can have a big impact in support of their favourite group or cause.
I would just pull the 2 files into Power BI as 2 separate tables (Get Data / From File). Create a relationship between the 2 tables based on ID (it might get auto-generated). It should be one to many.
Then I would add a Calculated Column to the Book1 table to Concatenate the related ITEM values, eg.
Items =
CALCULATE (
CONCATENATEX (
DISTINCT ( 'Book2'[ITEM] ),
'Book2'[ITEM],
", ",
'Book2'[ITEM], ASC
)
)
Now you can use that Items field in visuals (e.g. a Table), along with Count of ID to get the frequency.
Adding Subject to a copy of the table (e.g. to the Columns well of a Matrix) will produce your grouped scenario, or you could add a Subject Slicer.
As you will be comparing subsets of varying size, I would change Count of ID to Show value as - % of grand total.
Little different solution using Alteryx.
With this dataset, there are very few repeating 3 or 4 item groups. You can do the two item affinity analysis and get a probability of 3 or 4 item groups, or you can count the 3 and 4 item groups individually. I believe what you want is the latter as your probability of getting grapes with oranges may be altered by whether you have bananas in the cart or not.
Anyway, I did not join in the subject until after finding all of my combinations. I found all the combinations by taking the Cartesian join of two, then three, then four of the original set. I then removed all duplicates by ensuring items were always in alphabetical order in each row. I then counted occurrences of each combination. More joins can be added in the same pattern to count groups of 5,6,7...
Once you have the counts of occurrences, then I would join back with the subjects and perform this analysis on each group and compare to the overall results.
I'm supposed to disclose that I work for Alteryx.
first of all if you are using windows
just navigate to the directory which contains the CSV and write the following command:
copy pattern newfileName.csv
#example
copy *.csv merged.csv
now you created one csv file, the file is too large now you can't process it once, depending on your programming language you can use appropriate way, for python you can use generators to process line by line, or pandas you can read chunk by chunk it will be easy.
I hope this help you.
This is my first post to StackOverflow and I hope I have absorbed some of the conventions in posting after reading and browsing and using the site some. I am having an issue in that I'd like to separate a csvfile which has all of the data in one column under 1 header into multiple columns for analyzing the data. My data looks like the following:
School ID,name,type,size,budget
0
0,Huang High School,District,2917,1910635
1
1,Figueroa High School,District,2949,1884411
2
2,Shelton High School,Charter,1761,1056600
3
3,Hernandez High School,District,4635,3022020
4
4,Griffin High School,Charter,1468,917500
and I want each of the words in the header (School ID, name, type, size etc.) to head their own column.
I tried the command
pd.read_csv('../Desktop/schools_complete.csv', sep='\,')
as in this page
How to split a pandas dataframe into multiple columns
but this had no effect and the data remained in one header. Please advise; any input would be much appreciated. thanks.
I'm working with the craziest file format I've seen. It is fixed width, and contains multiple record types (in the sense that each row may have different columns and widths). There's a file header, trailer, and then a static number of rows that when put together make up one record. The problem I'm having is that there is nothing in the rows that tell you they belong to the same record other than their sort order and a row number attribute.
Example:
001 David Wellingsworth Mr.
002 312-555-5555 3060 W Maple St. Chicago
001 Jimothy Bogendath Dr.
002 563-555-5432 123 Main St. Davenport
My question is therefore: is it possible, without using a Script Component, to process a file like this? I understand the basic concept of how to handle disparate record types in a fixed width file (making use of conditional splits and substrings), but I can't get past how to join up all this data after the splits if the rows don't have identifiers.
If it helps, my question is basically this previous question but in reverse.
Possible but with some work. I've worked with data like these and this was our approach on how we solved them.
You will need to build a table that will give them their own unique RecordID
Create another table for your Files to log in your filename and unique fileID
Link your fileID to the RecordID so you know which file each record came from
Build all your sub tables linking to each unique RecordID
Building your tables this way will give you:
Unique recordID for each row (though there maybe duplicate in the file, in your tables they are unique).
Knowing which file each record comes from.
I have few tables as shown below
Polls
PollId Question Option
1 What 1
2 Why 4
Updates
UpdateId Text
1 Sleep
2 Play
Polls and updates are just two sample tables (In reality there are more tables like ,photos, videos,links etc). But when a user visit his home (like facebook new feed) he must be displayed with data relevant to him (no such data included in this example). ie I want to select data from all tables with less number of query executions. (ie, I want to present a mixture of datas, ie polls, photos, videos etc )
Currently, I'm fetching only ids and type (ie which table) from all of the tables and gather further data while iterating through this resultset. (ie from c# calling another SqlQuery) .
Is there a way to query the data from whole tables at once? (OUTER JOIN?, UNION?)
Or simply,
How can I select different type of entities at once in a single sql Query?
You could write your query so that you have one long select list for everything you want and it all comes back in one result set but I suspect that wouldn't work too well because you might have varying numbers of different types of items per user.
If you really must have it all in one hit then you can issue multiple queries in one go and get multiple result sets back. To handle this you can use an ADO.Net DataSet. See this SO example (but not the accepted answer - see Vikram Dibyal's answer as that gives a very basic overview of what I think you're asking for).
I won't copy and paste the stuff from the linked thread, just head over and take a look.
I am having a problem trying to achieve the following:
I'd like to have a page with 'infinite' scrolling functionality and all the results fetched to be sorted by certain attributes. The way the code currently works is, it places the query, sorts the results, and displays them. The problem is, that once the user reaches the bottom of the page and new query is placed, the results from this query are sorted, but in its own context. That is, if you have a total of 100 results, and the first query display only 50, then they are sorted. But the next query (for the next 50) sorts the results only based on these 50 results, not based on the 100 (total results).
So, do I have to fetch all the results at once, sort them, and then apply some pagination logic to them or there's a way for MongoDB to actually have infinite scrolling (AJAX requests) with sorting applying to the results?
There's a few ways to do this with MongoDB. You can use the .skip() and .limit() commands (documented here: http://www.mongodb.org/display/DOCS/Advanced+Queries#AdvancedQueries-CursorMethods) to apply pagination to the query.
Alternatively, you could add a clause to your query like: {sorted_field : {$gt : <value from last record>}}. In other words, filter out matches of the query whose sorted value is less than that of the last resulting item from the current page of results. For example, if page 1 of results returns documents A through D, then to retrieve the next page 2 you repeat the same query with the additional filter x > D.
Let me preface this by saying that I have no experience with MongoDB (though I am aware that it is a NoSQL database).
This question, however, is somewhat of a general database one (you'd probably get more responses tagging it as such). I've implemented such a feature using Cassandra (another, albiet quite different NoSQL database), however the same principles apply.
Use the sorted-by attribute of the last retrieved record, and conduct a range search based on it in the database. So, assuming your database consists of the following set of letters:
A
B
C
D
E
F
G
..and you were retrieving 2 letters at a time, you'd retrieve A, B first. When more records are needed, you'd use B to conduct a range search on the set of letters in the database. In plain English this would be something like:
Get the letters that appear after B, limit the results to 2
From a brief look at the MongoDB tutorial, it looks like you have conditional operators to help you implement this.