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finding the sum of columns for each row in pig


finding the sum of columns for each row in pig

By : Spaceone
Date : November 20 2020, 01:01 AM
it should still fix some issue I need to find the sum of columns in a every row. , You can define the schema and try the below approach.
input:
code :
A,1,5,45,25,20
B,5,50,5,23,12
C,1,25,4,15,23
A = LOAD 'input' USING PigStorage(',') AS(f1:chararray,f2:int,f3:int,f4:int,f5:int,f6:int);
B = FOREACH A GENERATE f1,SUM(TOBAG(f2..));
DUMP B;
(A,96)
(B,95)
(C,68)


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Python : Separating a .txt file into columns and finding the most frequent data item in one of the columns

Python : Separating a .txt file into columns and finding the most frequent data item in one of the columns


By : Snehal
Date : March 29 2020, 07:55 AM
hope this fix your issue I'm sure there is a more succint way of doing it, but this should get you started:
code :
# returns a df grouped by ArtistID and Tag
tag_counts = artists_tags.groupby(['ArtistID', 'Tag'])
# sum up tag counts and sort in descending order
tag_counts = tag_counts.sum().sort('Count', ascending=False).reset_index()
# keep only the top ranking tag per artist
top_tags = tag_counts.groupby('ArtistID').first()
# top_tags is now a dataframe which contains the top tag for every artist
# We can simply lookup the top tag for Nirvana via it's index:
top_tags.ix['5b11f4ce-a62d-471e-81fc-a69a8278c7da'][0]
# 'Grunge'
2-D Matrix: Finding and deleting columns that are subsets of other columns

2-D Matrix: Finding and deleting columns that are subsets of other columns


By : Jack27
Date : March 29 2020, 07:55 AM
this one helps. Since the A matrices I'm actually dealing with are 5000x5000 and sparse with about 4% density, I decided to try a sparse matrix approach combined with Python's "set" objects. Overall it's much faster than my original solution, but I feel like my process of going from matrix A to list of sets D is not as fast it could be. Any ideas on how to do this better are appreciated.
Solution
code :
import numpy as np

A = np.array([[1, 0, 0, 0, 0, 1],
              [0, 1, 1, 1, 1, 0],
              [1, 0, 1, 0, 1, 1],
              [1, 1, 0, 1, 0, 1],
              [1, 1, 0, 1, 0, 0],
              [1, 0, 0, 0, 0, 0],
              [0, 0, 1, 1, 1, 0],
              [0, 0, 1, 0, 1, 0]])

rows,cols = A.shape
drops = np.zeros(cols).astype(bool)

# sparse nonzero elements
C = np.nonzero(A)

# create a list of sets containing the indices of non-zero elements of each column
D = [set() for j in range(cols)]
for i in range(len(C[0])):
    D[C[1][i]].add(C[0][i])

# find subsets, ignoring columns that are known to already be subsets
for i in range(cols):
    if drops[i]==True:
        continue
    col1 = D[i]
    for j in range(i+1,cols):
        col2 = D[j]
        if col2.issubset(col1):
            # I tried `if drops[j]==True: continue` here, but that was slower
            print "%d is a subset of %d" % (j, i)
            drops[j] = True
        elif col1.issubset(col2):
            print "%d is a subset of %d" % (i, j)
            drops[i] = True
            break

B = A[:, ~drops]
print B
Taking two excel sheets in same workbook and finding same values in certain columns and copy data from other columns

Taking two excel sheets in same workbook and finding same values in certain columns and copy data from other columns


By : user5649904
Date : March 29 2020, 07:55 AM
I hope this helps . to Scott, here is what I was trying to do. I guess I was kind of close. =INDEX(Sheet2!L$3:L$14119,MATCH($E3,Sheet2!$K$3:$K$14119,0))
Change value at columns when finding values at column on the right for multiple pairs of columns without loop

Change value at columns when finding values at column on the right for multiple pairs of columns without loop


By : thomas120
Date : March 29 2020, 07:55 AM
it fixes the issue You can locate all 4 and 5 values with ismember and then circshift the resulting boolean to the left and replace with NaN
code :
bool = ismember(data, [4 5]);

shifted = circshift(bool, [0 -1]);

data(shifted) = NaN;
data(circshift(ismember(data, [4 5]), [0 -1])) = NaN;
to_be_nan = ismember(data(:,2:end), [4 5]);
to_be_nan(:,end+1) = false;

data(to_be_nan) = NaN;
Finding duplicates across multiple columns repeated in more than certain number of columns

Finding duplicates across multiple columns repeated in more than certain number of columns


By : Fangpeng Liu
Date : March 29 2020, 07:55 AM
will help you With subtle changes to akrun code, I guess I found out this is what I wanted:
names(table(unlist(d1)))[table(unlist(d1))>=3]
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