Documentation

O(k) Apply a function to a given column in a dataframe.

O(1) Creates an empty dataframe

O(n * k) Filter rows by a given condition.

filter "x" even df

By default we assume the file has a header, we infer the types on read and we convert any rows with nullish objects into Maybe (safeRead).

O(k * n) Take a range of rows of a DataFrame.

O(k * n) Take the first n rows of a DataFrame.

O(k * n) groups the dataframe by the given rows aggregating the remaining rows into vector that should be reduced later.

O(k log n) Sorts the dataframe by a given row.

sortBy "Age" df

O(n) Selects a number of columns in a given dataframe.

select ["name", "age"] df

Our representation of a column is a GADT that can store data in either a vector with boxed elements or

O(n) select columns by column predicate name.

O(1) Gets the number of elements in the column.

O(1) Get DataFrame dimensions i.e. (rows, columns)

Essentially a "functor" instance of our type-erased Column.

tranform with index.

Converts a an unboxed vector to a column making sure to put the vector into an appropriate column type by reflection on the vector's type parameter.

Applies a function that returns an unboxed result to an unboxed vector, storing the result in a column.

Filter column with index.

O(k) Get column names of the DataFrame in order of insertion.

O(n) Adds a vector to the dataframe.

O(n) Adds an unboxed vector to the dataframe.

O(k) Add a column to the dataframe providing a default. This constructs a new vector and also may convert it to an unboxed vector if necessary. Since columns are usually large the runtime is dominated by the length of the list, k.

O(1) Get the number of elements in a given column.

O(n) Returns the number of non-null columns in the dataframe and the type associated with each column.

O (k * n) Counts the occurences of each value in a given column.

Sort order taken as a parameter by the sortby function.

O(k) Apply a function to a combination of columns in a dataframe and add the result into alias column.

O(k) Apply a function to a given column in a dataframe and add the result into alias column.

O(k * n) Apply a function to given column names in a dataframe.

O(k) Convenience function that applies to an int column.

O(k) Convenience function that applies to an double column.

O(k * n) Apply a function to a column only if there is another column value that matches the given criterion.

applyWhere "Age" (<20) "Generation" (const "Gen-Z")

O(k) Apply a function to the column at a given index.

O(k) a version of filter where the predicate comes first.

filterBy even "x" df

O(k) filters the dataframe with a row predicate. The arguments in the function must appear in the same order as they do in the list.

filterWhere (["x", "y"], func (\x y -> x + y > 5)) df

O(k) removes all rows with Nothing in a given column from the dataframe.

filterJust df

O(n * k) removes all rows with Nothing from the dataframe.

filterJust df

O(k) cuts the dataframe in a cube of size (a, b) where a is the length and b is the width.

cube (10, 5) df

O(n) select columns by index range of column names.

O(n) select columns by index range of column names.

O(n) inverse of select

exclude ["Name"] df

This hash function returns the hash when given a non numeric type but the value when given a numeric.

Record for CSV read options.

Reads a CSV file from the given path. Note this file stores intermediate temporary files while converting the CSV from a row to a columnar format.

Reads a character separated file into a dataframe using mutable vectors.

Reads a tab separated file from the given path. Note this file stores intermediate temporary files while converting the CSV from a row to a columnar format.

First pass to count rows for exact allocation

Reads rows from the handle and stores values in mutable vectors.

Freezes a mutable vector into an immutable one, trimming it to the actual row count.

Writes a value into the appropriate column, resizing the vector if necessary.