As it is not a registered Julia package, use it with :
It implements the following functions:
addCols!(df, colsName, colsType)- Adds to the DataFrame empty column(s) colsName of type(s) colsType
pivot(df::AbstractDataFrame, rowFields, colField, valuesField; <kwd args>)- Pivot and optionally filter and sort in a single function
customSort!(df, sortops)- Sort a DataFrame by multiple cols, each specifying sort direction and custom sort order
toDict(df, dimCols, valueCol)- Convert a DataFrame in a dictionary, specifying the dimensions to be used as key and the one to be used as value.
findall(pattern,string,caseSensitive=true)- Find all the occurrences of pattern in string
In particular the pivot() function accepts the following arguments:
df::AbstractDataFrame: the original dataframe, in stacked version (dim1,dim2,dim3... value)
rowFields: the field(s) to be used as row categories (also known as IDs or keys)
colField::Symbol: the field containing the values to be used as column headers
valuesField::Symbol: the column containing the values to reshape
ops=sum: the operation(s) to perform on the data, default on summing them
filter::Dict: an optional filter, in the form of a dictionary of column_to_filter => [list of ammissible values]
sort: optional row field(s) to sort
While an updated, expanded and revised version of this chapter is available in "Chapter 9 - Working with Data" of Antonello Lobianco (2019), "Julia Quick Syntax Reference", Apress, this tutorial remains in active development.