Add a column to the DataFrame, evaluating to 'expr' at each individual row index.
Add a column to the DataFrame, evaluating to 'expr' at each individual row index. Use the 'as' method on Expr to give the column a name.
the Expr to evaluate as the new column
new DataFrame
Select a subset of columns from this DataFrame.
Select a subset of columns from this DataFrame.
names of columns to select
new DataFrame
Retrieve a subset of rows from this DataFrame based on range of indices.
Retrieve a subset of rows from this DataFrame based on range of indices.
range of row indices to retrieve
new DataFrame
Retrieve a single row by index.
Retrieve a single row by index.
row index
row as a sequence of values
Typecast this DataFrame to a TypedView of the type parameter 'T'.
Typecast this DataFrame to a TypedView of the type parameter 'T'. All columns in this DataFrame will have to be accounted for in the given type. A DataFrame with multiple columns will have its rows represented as tuples of the individual types of these columns.
the type of a row in this DataFrame
TypedView on the contents of this DataFrame
Explode this DataFrame on the given expression, flattening its contents and repeating all other cells on the row for every element in the sequence.
Explode this DataFrame on the given expression, flattening its contents and repeating all other cells on the row for every element in the sequence. The given Expr must evaluate to a list type. Use the 'as' method on Expr to name the flattened column.
the Expr to explode on
new DataFrame
Retrieve a subset of rows from this DataFrame based on the boolean evaluation of the given expression.
Retrieve a subset of rows from this DataFrame based on the boolean evaluation of the given expression.
the Expr to evaluate, if 'true' the given row will appear in the output
new DataFrame
Partition this DataFrame into groups, defined by the given set of expressions.
Partition this DataFrame into groups, defined by the given set of expressions. The evaluation of each of the 'keyExprs' will appear as a column in the output.
the list of com.audienceproject.crossbow.expr.Expr that will evaluate to the keys of the groups
GroupedView on this DataFrame
Join this DataFrame on another DataFrame, with the key evaluated by 'joinExpr'.
Join this DataFrame on another DataFrame, with the key evaluated by 'joinExpr'. The resulting DataFrame will contain all the columns of this DataFrame and the other, where the column names of the other will be prepended with "#".
DataFrame to join with this one
Expr to evaluate as join key
JoinType as one of Inner, FullOuter, LeftOuter or RightOuter
new DataFrame
'joinExpr' must evaluate to a type with a natural ordering
Remove one or more columns from the DataFrame.
Remove one or more columns from the DataFrame.
the names of the columns to remove
new DataFrame
Rename the columns of this DataFrame by applying the given function.
Rename the columns of this DataFrame by applying the given function.
function to map over the names of the columns
new DataFrame
Rename the columns of this DataFrame.
Rename the columns of this DataFrame.
list of new names for each column of this DataFrame
new DataFrame
Map over this DataFrame, selecting a set of expressions which will become the columns of a new DataFrame.
Map over this DataFrame, selecting a set of expressions which will become the columns of a new DataFrame. Use the 'as' method on Expr to give names to the new columns. An expression which is only a column accessor will inherit the accessed column's name (unless it is renamed).
the list of Expr to evaluate as a new DataFrame
new DataFrame
Sort this DataFrame by the evaluation of 'expr'.
Sort this DataFrame by the evaluation of 'expr'. If a natural ordering exists on this value, it will be used. User-defined orderings on other types or for overwriting the natural orderings with an explicit ordering can be supplied through the 'givenOrderings' argument.
the Expr to evaluate as a sort key
explicit Order to use on the sort key, or list of Order if the key is a tuple
whether the sorting should be stable or not - quicksort is used if not, else mergesort
new DataFrame
Union this DataFrame with another DataFrame.
Union this DataFrame with another DataFrame. Columns will be matched by name, and if matched they must have the same type. Columns that are not present in one or the other DataFrame will contain null-values in the output for the rows of the DataFrame in which the column was not present.
DataFrame to union with this one
new DataFrame
(Since version ) see corresponding Javadoc for more information.