loading combined data in R - r

Question

I have got several Excel files (see link: we.tl/t-qJl3kVcY0j) that I combine together.
Each Excel file have columns from A to AF as below:
t-ph
Load
HR
BF
V'E
V'O2
V'CO2
d O2/dW
RER
EqO2
EqCO2
PETCO2
VES (ml)
VESi (ml/m²)
FC (bpm)
QC (l/min)
IC (l/min/m²)
PAS (mmHg)
PAD (mmHg)
PAM (mmHg)
ICT
TEV (ms)
RPD (%)
WCI (kg.m/m²)
RVSi (dyn.s/cm5.m²)
RVS (dyn.s/cm5)
VTD est (ml)
FE est (%)
O2Hb
HHb
tHb
HbDiff
My previous code was working, but since I have added columns AC (HHb) to AF (HbDiff), I can't load them anymore. I have tried to match the number of columns, the title, but still not. I can't produce a reproducible example since I can't load my data.
Here is the code I used:
pacman::p_load(tidyverse, readxl, ggpubr)
library(dplyr)
library(ggplot2)
library(afex) ##statistic package
# load data and format
load_files <- function(files){
temp <- read_excel(files) %>%
select(-(c(8:11, 14:15, 18:23))) %>%
mutate(id = pull(.[4,1])) %>% ##ID
mutate(body_mass = pull(.[7,3])) %>% ##body mass
mutate(training = pull(.[4,2])) %>% ##training group
set_names(c("time", "power", "hr", "fr", "VE", "absVO2", "VCO2", "PETCO2", "VES", "QC", "IC", "WCI", "RVSi", "RVS", "VTD", "FE", "O2Hb", "HHb", "tHb", "HbDiff", "id", "body_mass", "training")) %>%
slice(86:which(grepl("ration", VE))-1) %>% ##until recovery period
mutate_at(vars(1:16), as.numeric) %>%
mutate_at(vars(18), as.numeric) %>%
mutate(time = format(as.POSIXct(Sys.Date() + time), "%H:%M", tz="UTC"),
absVO2 = absVO2/1000,
VCO2 = VCO2/1000)
}
# apply function to all files
df <- map_df(file_list, load_files)
# remove those with who have less than four similar power
df <- df %>%
mutate(len_seq = rep(rle(power)$lengths, rle(power)$lengths)) %>%
filter(len_seq == 4) %>%
mutate(seq_id = rep(1:(n()/4), each = 4)) %>%
group_by(id) %>%
select(-seq_id)%>%
select(-(20))
# group data
df_sum <- df %>%
type.convert(as.is = TRUE) %>%
group_by(id, power, training) %>%
summarise_if(is.numeric, mean) %>%
group_by(id) %>%
mutate(percent_absVO2 = absVO2/max(absVO2)*100,
percent_power = power/max(power)*100,
percent_QC = QC/max(QC)*100,
percent_SV = VES/max(VES)*100,
percent_VCO2 = VCO2/max(VCO2)*100,
percent_VE = VE/max(VE)*100) %>%
mutate(VE_VO2 = VE/absVO2,
VE_VCO2 = VE/VCO2) %>%
mutate(RER = VCO2/absVO2, VT = VE/fr) %>%
mutate(relVO2 = absVO2/body_mass*1000,
percent_relVO2 = relVO2/max(relVO2)*100) %>%
mutate(BF = VE/VT) %>%
mutate(mech_perf = (power/(((0.003*power+0.1208)*1000*body_mass)/60))*100) %>%
mutate(group = ifelse(grepl(".*-PRD-C", id), "CAD", "Healthy")) %>%
mutate(temps = ifelse(grepl(".*-PRD-C1", id), "1", ifelse(grepl(".*-PRD-S1", id), "1", "2")))
Then the outcome I get:
Error in `set_names()`:
! The size of `nm` (23) must be compatible with the size of `x` (20).
Run `rlang::last_error()` to see where the error occurred.
Thank you very much for your precious help.