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I want to produce a new dataframe from an old big one (many variables)
I use the cbind.data.frame function and it goes like this
new <- cbind.data.frame(old$var1, old$var2, old$var3)
str(new)
'data.frame': 100 obs. of 3 variables:
$ old$var1 : num
Why does the var1 still belong to old$ ?
I wanted to use just new$var1 but it returns object not found.
What am I doing wrong?
382
To create a PySpark DataFrame from an existing RDD, we will first create an RDD using the . parallelize() method and then convert it into a PySpark DataFrame using the . createDatFrame() method of SparkSession.
To convert an old data frame to a new data frame, we can simply set the new name. For example, if we have a data frame called df and want to convert it to a new one let's say df_new then it can be done as df_new<-df. But if we want to change the column names as well then data.
Another way to combine DataFrames is to use columns in each dataset that contain common values (a common unique id). Combining DataFrames using a common field is called “joining”. The columns containing the common values are called “join key(s)”.
Combine both of the other other answers by doing this:
New <- data.frame("var1" = old$var1,
"var2" = old$var2,
"var3" = old$var3)
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