如何创建每行库存的二进制矩阵? (右) [英] How to create a binary matrix of inventory per row? (R)

问题描述

我有一个9列的数据框，其中包含因素清单.每行可以填满所有9列(因为该行包含9个事物")，但是大多数却没有(大多数都在3-4之间).列也不是特定的，就像第1列和第3列中出现了第200项一样.我想为每个包含所有因素的行创建一个二进制矩阵.

I have a dataframe of 9 columns consisting of an inventory of factors. Each row can have all 9 columns filled (as in that row is holding 9 "things"), but most don't (most have between 3-4). The columns aren't specific either, as in if item 200 shows up in columns 1 and 3, it's the same thing. I'd like to create a matrix that is binary for each row that includes all factors.

Ex(缩短到4列只是为了指出一点)

Ex (shortened to 4 columns just to get point across)

R1 3  4   5   8
R2 4  6   7   NA
R3 1  5  NA   NA
R4 2  6   8   9

应该变成

     1  2  3  4  5  6  7  8  9 
r1   0  0  1  1  1  0  0  1  0
r2   0  0  0  1  0  1  1  0  0
r3   1  0  0  0  1  0  0  0  0
r4   0  1  0  0  0  1  0  1  1

我研究过writeBin/readBin，K聚类(这是我想做的事情，但我需要先消除NA)，模糊聚类，标签聚类.只是有点迷失方向.

I've looked into writeBin/readBin, K-clustering (which is something I'd like to do, but I need to get rid of the NAs first), fuzzy clustering, tag clustering. Just kinda lost about what direction to go.

我尝试编写两个for循环，分别按列/行从矩阵中提取数据，然后分别在新矩阵中保存0和1，但是我认为存在范围问题.

I've tried writing two for loops that pull the data from the matrix by column/row and then save 0s and 1s respectively in a new matrix, but I think there were scope issues.

你们是最棒的.谢谢！

推荐答案

这是基本的R解决方案:

Here's a base R solution:

# Read in the data, and convert to matrix form
df <- read.table(text = "
3  4   5   8
4  6   7   NA
1  5  NA   NA
2  6   8   9", header = FALSE)
m <- as.matrix(df)

# Create a two column matrix containing row/column indices of cells to be filled 
# with 'one's
id <- cbind(rowid = as.vector(t(row(m))), 
            colid = as.vector(t(m)))
id <- id[complete.cases(id), ]

# Create output matrix
out <-  matrix(0, nrow = nrow(m), ncol = max(m, na.rm = TRUE))
out[id] <- 1
#      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
# [1,]    0    0    1    1    1    0    0    1    0
# [2,]    0    0    0    1    0    1    1    0    0
# [3,]    1    0    0    0    1    0    0    0    0
# [4,]    0    1    0    0    0    1    0    1    1

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