在SAS中进行2向查找

Question

Let's say I have a (9000x9000) table like the following:

 zone 304  305  306  307  308 ...

  001   1    2    8    9   12 ...
  002   6    8    3    7    1 ...
  003   4    8    1   12    9 ...
  004   2    7    3   16   34 ...
  ...

The main data table looks like this:

  package #    weight    origin    destination    zone
       123      2oz       004          305        7 to be inputted here
        .
        .
        .

I need SAS to output the "zone" corresponding to a given ordered pair. I fear the only way would be with some type of loop. For instance, in the example above, the orgin value is from the row labels and the destination from the column labels. The intersection is the target value I need assigned to "zone".

A solution using python data wrangling libraries would work also.

Also, the 9000x9000 table is an Excel CSV file.

Answer 1

My approach:

1. Load the data set into a temporary array (9000x9000) and then lookup each element as needed. Could be memory intensive, but 9000*9000 seems small enough to me.

2. Another safe approach, transpose the data to be in a long format:

    Key1 Key2 Value 001 304 1 001 305 2 ... 

Then, in any language, it becomes a join/merge instead of lookup.

3. You can also use PROC IML, which loads the data as a matrix and then you can access using the indexes.

There are also ways in SAS to do this lookup via a merge, primarily using VVALUEX.

Without knowing how you're going to use it, I can't provide any more information.

EDIT: added 3'rd option which is IML. Basically there are many ways to do this, the best depends on how you're planning to use it overall.

EDIT2: 1. Import first data set into SAS (PROC IMPORT) 2. Transpose using PROC TRANSPOSE 3. Merge either data step or PROC SQL, by ORIGIN DESTINATION, which will be straight forward. At this point it's really a standard lookup with 2 keys.

Answer 2

You could use pandas , it has a built in function to read from an excel document: pandas.read_excel()

So for this file:

import pandas as pd

df = pd.read_excel('test.xlsx')
print(df[101][502])

Output:

67