I want to cbind
two data frames and remove duplicated columns. For example:
df1 <- data.frame(var1=c('a','b','c'), var2=c(1,2,3))
df2 <- data.frame(var1=c('a','b','c'), var3=c(2,4,6))
cbind(df1,df2) #this creates a data frame in which column var1 is duplicated
I want to create a data frame with columns var1
, var2
and var3
, in which column var2
is not repeated.
To drop duplicate columns from pandas DataFrame use df. T. drop_duplicates(). T , this removes all columns that have the same data regardless of column names.
By use + operator simply you can concatenate two or multiple text/string columns in pandas DataFrame.
merge() to merge multiple Dataframes. Merging multiple Dataframes is similar to SQL join and supports different types of join inner , left , right , outer , cross . In this article, we will learn how to merge multiple (three or more) Dataframes with examples. Yields below the output of three DataFrames.
merge
will do that work.
try:
merge(df1, df2)
In case you inherit someone else's dataset and end up with duplicate columns somehow and want to deal with them, this is a nice way to do it:
for (name in unique(names(testframe))) {
if (length(which(names(testframe)==name)) > 1) {
## Deal with duplicates here. In this example
## just print name and column #s of duplicates:
print(name)
print(which(names(testframe)==name))
}
}
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With