# write csv in r write.csv(mydata, file = "mydata.csv") the above writes the data data frame mydata into a csv that it creates called mydata.csv. note that the file is written to your working directory .. Say that you want to export pandas dataframe to a csv file. how would you go about it? in a nutshell, you can use the following structure in python in order to export your pandas dataframe to a csv file: df.to_csv(r'path where you want to store the exported csv filefile name.csv'). Another option is to save your data frame as a csv file. the benefit of this option is that it provides long term storage, i.e. you will (likely) be able to open your csv file on any platform in ten years time. with an rdata file, you can only open it with r and i wouldn't like to bet money on opening it between versions.. to save the file as a csv, just use: read.csv and write.csv, so:.
What's new for spark sql in apache spark 1.3 - the
Column label for index column(s) if desired. if none is given, and header and index are true, then the index names are used. a sequence should be given if the dataframe uses multiindex. if false do not print fields for index names.. One of the easiest ways to save an r dataframe is to write it to a comma-separated value (csv) file. csv files are human-readable (e.g., in a text editor) and can be opened by essentially any statistical software (excel, stata, spss, sas, etc.) making them one of the best formats for data sharing.. This assumes that the .rda file contains only a single r object, and that it is a data frame or matrix. it would be nice if write.csv had a way to accept the name of an object instead of the object itself (so get() was unnecessary), but i don't know of one..
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