在R中线性估算缺失值 [英] Imputing missing values linearly in R

问题描述

我有一个缺少值的数据框:

I have a data frame with missing values:

X   Y   Z
54  57  57
100 58  58
NA  NA  NA
NA  NA  NA
NA  NA  NA
60  62  56
NA  NA  NA
NA  NA  NA
69  62  62

我想根据已知值线性推算NA值，以使数据框看起来像这样:

I want to impute the NA values linearly from the known values so that the dataframe looks:

X   Y    Z
54  57  57
100 58  58
90  59  57.5
80  60  57
70  61  56.5
60  62  56
63  62  58
66  62  60
69  60  62

谢谢

推荐答案

Base R的approxfun()返回一个函数，该函数将线性插值处理的数据.

Base R's approxfun() returns a function that will linearly interpolate the data it is handed.

## Make easily reproducible data
df <- read.table(text="X   Y   Z
54  57  57
100 58  58
NA  NA  NA
NA  NA  NA
NA  NA  NA
60  62  56
NA  NA  NA
NA  NA  NA
69  62  62", header=T)

## See how this works on a single vector
approxfun(1:9, df$X)(1:9)
# [1]  54 100  90  80  70  60  63  66  69

## Apply interpolation to each of the data.frame's columns
data.frame(lapply(df, function(X) approxfun(seq_along(X), X)(seq_along(X))))
#     X  Y    Z
# 1  54 57 57.0
# 2 100 58 58.0
# 3  90 59 57.5
# 4  80 60 57.0
# 5  70 61 56.5
# 6  60 62 56.0
# 7  63 62 58.0
# 8  66 62 60.0
# 9  69 62 62.0

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