September 2016
Beginner to intermediate
346 pages
6h 35m
English
Content preview from Julia for Data ScienceBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Summary
In this chapter, we learned what data munging is and why it is necessary for data science. Julia provides functionalities to facilitate data munging with the DataFrames.jl package, with features such as these:
NA: A missing value in Julia is represented by a specific data type, NA.DataArray: DataArray provided in theDataFrames.jlprovides features such as allowing us to store some missing values in an array.DataFrame: DataFrame is 2-D data structure like spreadsheets. It is very similar to R or pandas's dataframes, and provides many functionalities to represent and analyze data. DataFrames has many features well suited for data analysis and statistical modeling.- A dataset can have different types of data in different columns.
- Records have ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.