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# Load the raw training data and replace missing values with NA | |
training.data.raw <- read.csv('train.csv',header=T,na.strings=c("")) | |
# Output the number of missing values for each column | |
sapply(training.data.raw,function(x) sum(is.na(x))) | |
# Quick check for how many different values for each feature | |
sapply(training.data.raw, function(x) length(unique(x))) | |
# A visual way to check for missing data |
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su - root | |
# gpinitsystem fails to change the postgresql.conf port setting without ed | |
yum install ed unzip -y | |
groupadd -g 8000 gpadmin | |
useradd -m -s /bin/bash -d /home/gpadmin -g gpadmin -u 8000 gpadmin | |
passwd gpadmin | |
mkdir -p /data/master |