Safe Haskell | None |
---|---|
Language | Haskell2010 |
A module for storing Tabular Data as Tensors
Synopsis
- data DataFrame a = DataFrame {}
- nRows :: DataFrame Tensor -> Int
- nCols :: DataFrame Tensor -> Int
- fromFile' :: [String] -> FilePath -> IO (DataFrame Tensor)
- fromFile :: FilePath -> IO (DataFrame Tensor)
- lookup :: [String] -> DataFrame Tensor -> DataFrame Tensor
- (??) :: DataFrame Tensor -> String -> Tensor
- rowSelect' :: [Int] -> DataFrame Tensor -> DataFrame Tensor
- rowSelect :: Tensor -> DataFrame Tensor -> DataFrame Tensor
- rowFilter :: Tensor -> DataFrame Tensor -> DataFrame Tensor
- sort :: Bool -> String -> DataFrame Tensor -> DataFrame Tensor
- rowDrop :: Tensor -> DataFrame Tensor -> DataFrame Tensor
- rowDrop' :: [Int] -> DataFrame Tensor -> DataFrame Tensor
- idxNan :: DataFrame Tensor -> Tensor
- dropNan :: DataFrame Tensor -> DataFrame Tensor
- update :: [String] -> Tensor -> DataFrame Tensor -> DataFrame Tensor
- union :: DataFrame Tensor -> DataFrame Tensor -> DataFrame Tensor
- insert :: [String] -> Tensor -> DataFrame Tensor -> DataFrame Tensor
- join :: DataFrame Tensor -> DataFrame Tensor -> DataFrame Tensor
- concat :: [DataFrame Tensor] -> DataFrame Tensor
- sampleIO :: Int -> Bool -> DataFrame Tensor -> IO (DataFrame Tensor)
- shuffleIO :: DataFrame Tensor -> IO (DataFrame Tensor)
- trainTestSplit :: [String] -> [String] -> Float -> DataFrame Tensor -> (Tensor, Tensor, Tensor, Tensor)
Documentation
Data Frame
fromFile' :: [String] -> FilePath -> IO (DataFrame Tensor) Source #
Load Tensor from file and construct DataFrame with given Header
fromFile :: FilePath -> IO (DataFrame Tensor) Source #
Load Tensor from file and construct DataFrame with default Header
sort :: Bool -> String -> DataFrame Tensor -> DataFrame Tensor Source #
Sort Data Frame Ascending or Descending
dropNan :: DataFrame Tensor -> DataFrame Tensor Source #
Drop all Rows with NaNs and Infs (just calls idxNan and rowDrop)
update :: [String] -> Tensor -> DataFrame Tensor -> DataFrame Tensor Source #
Update given columns with new values (Tensor dimensions must match)
join :: DataFrame Tensor -> DataFrame Tensor -> DataFrame Tensor Source #
Join 2 DataFrames, columns must line up