Add a Column with Count of Nas and Mean

Add a column with count of NAs and Mean

library(dplyr)

count_na <- function(x) sum(is.na(x))    

df1 %>%
  mutate(means = rowMeans(., na.rm = T),
         count_na = apply(., 1, count_na))

#### ANSWER FOR RADEK ####
elected_cols <- c('b', 'c')

df1 %>%
  mutate(means = rowMeans(.[elected_cols], na.rm = T),
         count_na = apply(.[elected_cols], 1, count_na))

Count NAs per row in dataframe

You could add a new column to your data frame containing the number of NA values per batch_id:

df$na_count <- apply(df, 1, function(x) sum(is.na(x)))

Count the number of NAs in multiple columns after grouping a dataframe in R

I propose two ways:

using dplyr:

df %>% 
  group_by(Region,ID) %>%
  summarise_each(list(na_count = ~sum(is.na(.))))

or data.table:

library(data.table)
setDT(df)[, lapply(.SD, function(x) sum(is.na(x))), by = .(Region, ID)]

R: how to total the number of NA in each col of data.frame

You could try:

colSums(is.na(df))
#  V1 V2 V3 V4 V5 
#   2  4  2  4  4 

data

set.seed(42)
df <- as.data.frame(matrix(sample(c(NA,0:4), 5*20,replace=TRUE), ncol=5))

How to fill mean for NAs in column by groups in r?

You can use :

library(dplyr)

df %>%
  group_by(Category) %>%
  mutate(across(starts_with('column'), 
                ~replace(., is.na(.), mean(., na.rm = TRUE)))) %>%
  ungroup

#     PID Category column1 column2 column3
#   <int>    <int>   <dbl>   <dbl>   <dbl>
# 1   123        1    54      2.4     23.4
# 2   324        1    52      3       21.1
# 3   356        1    53      3.6     25.6
# 4   378        2    56      3.2     27.1
# 5   395        2    50.5    3.5     29.9
# 6   362        2    45      3.35    24.3
# 7   789        3    65     12.6     23.8
# 8   759        3    66     10.6     26.8
# 9   762        3    66.7   10.6     27.2
#10   741        3    69      8.5     23.3

row wise NA count across some columns - grouped by id

library(tidyverse)

threshold = 10

df %>% group_by(id) %>%
  mutate(evidence = ifelse(n()*5 - sum(na_count) >= threshold, "yes", "no"))

The 5 comes from the number of columns you have, q1:q5.

---

Related Topics