I have six columns in a dataframe:
1.vins
2.mileage
3.complaints_flag
4.ro_opened_date
5.complained_date
6.date_flag
i want to flag the date_flag as yes or no for every vin where the ro_opened_date is nearest to the complained_date
and take out that mileage for that particular vin.
how to do it in python pandas.?
Related
For two tables each with datetime and ticker symbol columns, how can we achieve the functionality of the binary function bin within each ticker group. That is, instead of returning the latest index from the entire left-table prior to the time of each right-table row, for a given right-table row it should return the latest index from the left-table amongst only the rows of the same ticker symbol as the right-table row.
My first thought would be to add a per-group index in the left-table, apply bin on each ticker group for it’s group-index and then use the unique (ticker,group-index) pair to find the index on the full left-table. However, I am not sure how to implement this or if this is the best way to achieve the desired functionality.
Could you give some sample inputs and desired output?
This sounds like something you can solve with aj
Check https://code.kx.com/q/ref/aj/ for details
I'm using Dataprep on GCP to wrangle a large file with a billion rows. I would like to limit the number of rows in the output of the flow, as I am prototyping a Machine Learning model.
Let's say I would like to keep one million rows out of the original billion. Is this possible to do this with Dataprep? I have reviewed the documentation of sampling, but that only applies to the input of the Transformer tool and not the outcome of the process.
You can do this, but it does take a bit of extra work in your Recipe--set up a formula in a new column using something like RANDBETWEEN to give you a random integer output between 1 and 1,000 (in this million-to-billion case). From there, you can filter rows based on whatever random integer between 1 and 1,000 as what you'll keep, and then your output will only have your randomized subset. Just have your last part of the recipe remove this temporary column.
So indeed there are 2 approaches to this.
As Courtney Grimes said, you can use one of the 2 functions that create random-number out of a range.
randbetween :
rand :
These methods can be used to slice an "even" portion of your data. As suggested, a randbetween(1,1000) , then pick 1<x<1000 to filter, because it's 1\1000 of data (million out of a billion).
Alternatively, if you just want to have million records in your output, but either
Don't want to rely on the knowledge of the size of the entire table
just want the first million rows, agnostic to how many rows there are -
You can just use 2 of these 3 row filtering methods: (top rows\ range)
P.S
By understanding the $sourcerownumber metadata parameter (can read in-product documentation), you can filter\keep a portion of the data (as per the first scenario) in 1 step (AKA without creating an additional column.
BTW, an easy way of "discovery" of how-to's in Trifacta would be to just type what you're looking for in the "search-transtormation" pane (accessed via ctrl-k). By searching "filter", you'll get most of the relevant options for your problem.
Cheers!
I am looking for a logic which will help me in coverting a string to number in teradata and hive.
It should be easily implementable in Tearadata as I dont have permission to deploy a UDF in TD. In hive if it is not simple I can easily write a UDF.
My requirement - Lets say I have columns sender_country, receiver country. I want to generate a number for concat('sender_country','_','receiver_country')
The number should always be same if the countries appear again.
Below is the illustration
UID sender_country receiver_country concat number
1 US UK US_UK 198760
2 FR IN FR_IN 146785
3 CH RU CH_RU 467892
4 US UK US_UK 198760
It should be in a way where all unique combinations of a country should have unique values. Like in above example US_US is repeated, it has same corresponding number.
I tried hashbucket(hashrow('concat')) in TD, but don't know its equivalent implementation in hive.
Similarly we have hash() function in hive, but don't have its equivalent function in TD.
I could not find any hash functions which returns similar values in TD and Hive too
You can simply convert each character into a number:
Ascii(Substr(sender_country,1,1))*1000000+
Ascii(Substr(sender_country,2,1))*10000+
Ascii(Substr(receiver_country,1,1))*100+
Ascii(Substr(receiver_country,2,1))
returns 85838575 for US,UK
I will try to explain the problem on an abstract level first:
I have X amount of data as input, which is always going to have a field DATE. Before, the dates that came as input (after some process) where put in a table as output. Now, I am asked to put both the input dates and any date between the minimun date received and one year from that moment. If there was originally no input for some day between this two dates, all fields must come with 0, or equivalent.
Example. I have two inputs. One with '18/03/2017' and other with '18/03/2018'. I now need to create output data for all the missing dates between '18/03/2017' and '18/04/2017'. So, output '19/03/2017' with every field to 0, and the same for the 20th and 21st and so on.
I know to do this programmatically, but on powercenter I do not. I've been told to do the following (which I have done, but I would like to know of a better method):
Get the minimun date, day0. Then, with an aggregator, create 365 fields, each has that "day0"+1, day0+2, and so on, to create an artificial year.
After that we do several transformations like sorting the dates, union between them, to get the data ready for a joiner. The idea of the joiner is to do an Full Outer Join between the original data, and the data that is going to have all fields to 0 and that we got from the previous aggregator.
Then a router picks with one of its groups the data that had actual dates (and fields without nulls) and other group where all fields are null, and then said fields are given a 0 to finally be written to a table.
I am wondering how can this be achieved by, for starters, removing the need to add 365 days to a date. If I were to do this same process for 10 years intead of one, the task gets ridicolous really quick.
I was wondering about an XOR type of operation, or some other function that would cut the number of steps that need to be done for what I (maybe wrongly) feel is a simple task. Currently I now need 5 steps just to know which dates are missing between two dates, a minimun and one year from that point.
I have tried to be as clear as posible but if I failed at any point please let me know!
Im not sure what the aggregator is supposed to do?
The same with the 'full outer' join? A normal join on a constant port is fine :) c
Can you calculate the needed number of 'dublicates' before the 'joiner'? In that case a lookup configured to return 'all rows' and a less-than-or-equal predicate can help make the mapping much more readable.
In any case You will need a helper table (or file) with a sequence of numbers between 1 and the number of potential dublicates (or more)
I use our time-dimension in the warehouse, which have one row per day from 1753-01-01 and 200000 next days, and a primary integer column with values from 1 and up ...
You've identified you know how to do this programmatically and to be fair this problem is more suited to that sort of solution... but that doesn't exclude powercenter by any means, just feed the 2 dates into a java transformation, apply some code to produce all dates between them and for a record to be output for each. Java transformation is ideal for record generation
You've identified you know how to do this programmatically and to be fair this problem is more suited to that sort of solution... but that doesn't exclude powercenter by any means, just feed the 2 dates into a java transformation, apply some code to produce all dates between them and for a record to be output for each. Java transformation is ideal for record generation
Ok... so you could override your source qualifier to achieve this in the selection query itself (am giving Oracle based example as its what I'm used to and I'm assuming your data in is from a table). I looked up the connect syntax here
SQL to generate a list of numbers from 1 to 100
SELECT (MIN(tablea.DATEFIELD) + levquery.n - 1) AS Port1 FROM tablea, (SELECT LEVEL n FROM DUAL CONNECT BY LEVEL <= 365) as levquery
(Check if the query works for you - haven't access to pc to test it at the minute)
I am trying to calculate the zscore with Rolling window. I need to actually calculate standard deviation for a 3 year rolling window to calculate z-score. A minimal working example is given below:
use http://dss.princeton.edu/training/Panel101.dta
xtset country year
rolling sd_x1=r(sd), step(1) window(3) saving(sd_x1, replace) keep(year): sum x1, detail
Now after this I need to merge it back with the original file. But the variable year does not appear but a column name date appears with all missing values. I am trying to merge it using the following command:
merge 1:1 country year using sd_x1
However, I get the error that variable year is not found and actually this variable is not kept while running the rolling command. Any help will be much appreciated.
I am always surprised that people have interest or faith in standard deviations based on three values.
A more direct approach would be to use rangestat (SSC). The syntax could be something like
use http://dss.princeton.edu/training/Panel101.dta
xtset country year
rangestat (sd) sd=x1, interval(year 0 2) by(country)
except that I cannot test this at the moment.
The key difference here is that rangestat produces new variables in the current dataset. Search the Statalist archives for examples of rangestat use.
Note that in your example the detail option is unnecessary as summarize by itself produces standard deviations.
You can extend this approach to get the mean at the same time.