Safe Haskell	Safe-Inferred
Language	Haskell2010

Data.DataFrame

Synopsis

data Function where
- F1 :: forall a b. (Columnable a, Columnable b) => (a -> b) -> Function
- F2 :: forall a b c. (Columnable a, Columnable b, Columnable c) => (a -> b -> c) -> Function
- F3 :: forall a b c d. (Columnable a, Columnable b, Columnable c, Columnable d) => (a -> b -> c -> d) -> Function
- F4 :: forall a b c d e. (Columnable a, Columnable b, Columnable c, Columnable d, Columnable e) => (a -> b -> c -> d -> e) -> Function
- Cond :: forall a. Columnable a => (a -> Bool) -> Function
- ICond :: forall a. Columnable a => (Int -> a -> Bool) -> Function
data Column where
- BoxedColumn :: Columnable a => Vector a -> Column
- UnboxedColumn :: (Columnable a, Unbox a) => Vector a -> Column
- OptionalColumn :: Columnable a => Vector (Maybe a) -> Column
- GroupedBoxedColumn :: Columnable a => Vector (Vector a) -> Column
- GroupedUnboxedColumn :: (Columnable a, Unbox a) => Vector (Vector a) -> Column
- GroupedOptionalColumn :: Columnable a => Vector (Vector (Maybe a)) -> Column
- MutableBoxedColumn :: Columnable a => IOVector a -> Column
- MutableUnboxedColumn :: (Columnable a, Unbox a) => IOVector a -> Column
data DataFrame = DataFrame (Vector (Maybe Column)) (Map Text Int) [Int] (Int, Int)
type Row = Vector RowValue
data Aggregation
- = Count
- | Mean
- | Minimum
- | Median
- | Maximum
- | Sum
data DataFrameException where
- TypeMismatchException :: forall a b. (Typeable a, Typeable b) => TypeRep a -> TypeRep b -> Text -> Text -> DataFrameException
- TypeMismatchException' :: forall a. Typeable a => TypeRep a -> String -> Text -> Text -> DataFrameException
- ColumnNotFoundException :: Text -> Text -> [Text] -> DataFrameException
type Columnable a = (Typeable a, Show a, Ord a, Eq a)
data RowValue where
- Value :: Columnable a => a -> RowValue
class Transformable a where
- transform :: forall b c. (Columnable b, Columnable c) => (b -> c) -> a -> Maybe a
data TypeRepList (xs :: [Type]) where
- Nil :: TypeRepList '[]
- Cons :: Typeable x => TypeRep x -> TypeRepList xs -> TypeRepList (x ': xs)
class WrapFunction a where
- wrapFunction :: a -> Function
class Columnable a => Columnify a where
- toColumn' :: Vector a -> Column
class Columnable a => ColumnifyList a where
- toColumn :: [a] -> Column
data ColumnInfo = ColumnInfo {
- nameOfColumn :: !Text
- nonNullValues :: !Int
- nullValues :: !Int
- partiallyParsedValues :: !Int
- uniqueValues :: !Int
- typeOfColumn :: !Text
}
data HistogramOrientation
- = VerticalHistogram
- | HorizontalHistogram
data PlotColumns
- = PlotAll
- | PlotSubset [Text]
data HistogramConfig = HistogramConfig {
- width :: Int
- height :: Int
- barChar :: Char
- title :: Maybe String
}
data SortOrder
- = Ascending
- | Descending
data ReadOptions = ReadOptions {
- hasHeader :: Bool
- inferTypes :: Bool
- safeRead :: Bool
}
pattern Empty :: Vector a
pattern (:<|) :: a -> Vector a -> Vector a
fromList :: [(Text, Column)] -> DataFrame
apply :: forall b c. (Columnable b, Columnable c) => (b -> c) -> Text -> DataFrame -> DataFrame
empty :: DataFrame
null :: DataFrame -> Bool
filter :: forall a. Columnable a => Text -> (a -> Bool) -> DataFrame -> DataFrame
defaultOptions :: ReadOptions
range :: (Int, Int) -> DataFrame -> DataFrame
take :: Int -> DataFrame -> DataFrame
sortBy :: SortOrder -> [Text] -> DataFrame -> DataFrame
groupBy :: [Text] -> DataFrame -> DataFrame
uncons :: Vector a -> Maybe (a, Vector a)
sum :: Text -> DataFrame -> Maybe Double
drop :: Int -> DataFrame -> DataFrame
rotate :: [String] -> [String]
readInt :: HasCallStack => Text -> Maybe Int
fold :: (a -> DataFrame -> DataFrame) -> [a] -> DataFrame -> DataFrame
readInteger :: HasCallStack => Text -> Maybe Integer
select :: [Text] -> DataFrame -> DataFrame
median :: Text -> DataFrame -> Maybe Double
variance :: Text -> DataFrame -> Maybe Double
mean :: Text -> DataFrame -> Maybe Double
skewness :: Text -> DataFrame -> Maybe Double
correlation :: Text -> Text -> DataFrame -> Maybe Double
formatNumber :: Double -> String
clip :: Int -> Int -> Int -> Int
rename :: Text -> Text -> DataFrame -> DataFrame
selectBy :: (Text -> Bool) -> DataFrame -> DataFrame
mkRowRep :: DataFrame -> Set Text -> Int -> Int
isNullish :: Text -> Bool
columnLength :: Column -> Int
columnTypeString :: Column -> String
expandColumn :: Int -> Column -> Column
getColumn :: Text -> DataFrame -> Maybe Column
dimensions :: DataFrame -> (Int, Int)
mkRowFromArgs :: [Text] -> DataFrame -> Int -> Row
toRowValue :: forall a. Columnable a => a -> RowValue
frequencies :: Text -> DataFrame -> DataFrame
itransform :: forall b c. (Columnable b, Columnable c) => (Int -> b -> c) -> Column -> Maybe Column
ifoldrColumn :: forall a b. (Columnable a, Columnable b) => (Int -> a -> b -> b) -> b -> Column -> Maybe b
funcApply :: forall c. Columnable c => Vector RowValue -> Function -> c
parseDefaults :: Bool -> DataFrame -> DataFrame
getIndicesUnboxed :: Unbox a => Vector Int -> Vector a -> Vector a
getIndices :: Vector Int -> Vector a -> Vector a
freezeColumn' :: [(Int, Text)] -> Column -> IO Column
writeColumn :: Int -> Text -> Column -> IO (Either Text Bool)
func :: forall fn. WrapFunction fn => fn -> Function
addCallPointInfo :: Text -> Maybe Text -> String -> String
typeMismatchError :: TypeRep a -> TypeRep b -> String
typeMismatchError' :: String -> String -> String
columnNotFound :: Text -> Text -> [Text] -> String
guessColumnName :: Text -> [Text] -> Text
typeAnnotationSuggestion :: String -> String
editDistance :: Text -> Text -> Int
readValue :: (HasCallStack, Read a) => Text -> a
readByteStringInt :: HasCallStack => ByteString -> Maybe Int
readDouble :: HasCallStack => Text -> Maybe Double
readIntegerEither :: HasCallStack => Text -> Either Text Integer
readIntEither :: HasCallStack => Text -> Either Text Int
readDoubleEither :: HasCallStack => Text -> Either Text Double
safeReadValue :: Read a => Text -> Maybe a
readWithDefault :: (HasCallStack, Read a) => a -> Text -> a
unboxableTypes :: TypeRepList '[Int, Int8, Int16, Int32, Int64, Word, Word8, Word16, Word32, Word64, Char, Double, Float, Bool]
numericTypes :: TypeRepList '[Int, Int8, Int16, Int32, Int64, Double, Float]
matchesAnyType :: forall a xs. Typeable a => TypeRepList xs -> TypeRep a -> Bool
testUnboxable :: forall a. Typeable a => TypeRep a -> Bool
testNumeric :: forall a. Typeable a => TypeRep a -> Bool
isGrouped :: Column -> Bool
columnVersionString :: Column -> String
toColumnUnboxed :: forall a. (Columnable a, Unbox a) => Vector a -> Column
takeColumn :: Int -> Column -> Column
takeLastColumn :: Int -> Column -> Column
sliceColumn :: Int -> Int -> Column -> Column
atIndices :: Set Int -> Column -> Column
atIndicesStable :: Vector Int -> Column -> Column
sortedIndexes :: Bool -> Column -> Vector Int
transformUnboxed :: forall a b. (Columnable a, Unbox a, Columnable b) => (a -> b) -> Vector a -> Column
itransformUnboxed :: forall a b. (Columnable a, Unbox a, Columnable b) => (Int -> a -> b) -> Vector a -> Column
ifilterColumn :: forall a. Columnable a => (Int -> a -> Bool) -> Column -> Maybe Column
ifilterColumnF :: Function -> Column -> Maybe Column
ifoldlColumn :: forall a b. (Columnable a, Columnable b) => (b -> Int -> a -> b) -> b -> Column -> Maybe b
reduceColumn :: forall a b. Columnable a => (a -> b) -> Column -> b
safeReduceColumn :: forall a b. Typeable a => (a -> b) -> Column -> Maybe b
zipColumns :: Column -> Column -> Column
nulls :: Column -> Int
asText :: DataFrame -> Text
initialColumnSize :: Int
metadata :: DataFrame -> String
toRowList :: [Text] -> DataFrame -> [Row]
toRowVector :: [Text] -> DataFrame -> Vector Row
sortedIndexes' :: Bool -> Vector Row -> Vector Int
columnNames :: DataFrame -> [Text]
insertColumn :: forall a. Columnable a => Text -> Vector a -> DataFrame -> DataFrame
insertColumn' :: Text -> Maybe Column -> DataFrame -> DataFrame
cloneColumn :: Text -> Text -> DataFrame -> DataFrame
insertUnboxedColumn :: forall a. (Columnable a, Unbox a) => Text -> Vector a -> DataFrame -> DataFrame
insertColumnWithDefault :: forall a. Columnable a => a -> Text -> Vector a -> DataFrame -> DataFrame
columnSize :: Text -> DataFrame -> Maybe Int
columnInfo :: DataFrame -> DataFrame
partiallyParsed :: Column -> Int
valueCounts :: forall a. Columnable a => Text -> DataFrame -> [(a, Int)]
plotHistograms :: HasCallStack => PlotColumns -> HistogramOrientation -> DataFrame -> IO ()
plotForColumn :: HasCallStack => Text -> Maybe Column -> HistogramOrientation -> DataFrame -> IO ()
plotHistogramsBy :: HasCallStack => Text -> PlotColumns -> HistogramOrientation -> DataFrame -> IO ()
plotForColumnBy :: HasCallStack => Text -> Text -> Maybe Column -> Maybe Column -> HistogramOrientation -> DataFrame -> IO ()
countOccurrences :: Ord a => Vector a -> [(a, Int)]
plotGivenCounts' :: HasCallStack => Text -> [((String, String), Int)] -> IO ()
numericHistogram :: forall a. (HasCallStack, Columnable a) => Text -> Vector a -> String
plotVerticalGivenCounts :: HasCallStack => Text -> [(String, Int)] -> IO ()
plotGivenCounts :: HasCallStack => Text -> [(String, Int)] -> IO ()
leftJustify :: String -> Int -> String
smallestPartition :: Ord a => a -> [a] -> a
intPlotRanges :: [Int]
defaultConfig :: HistogramConfig
createHistogram :: HistogramConfig -> [Double] -> String
largestPartition :: Ord a => a -> [a] -> a
calculateBins :: [Double] -> Int -> [(Double, Int)]
applyStatistic :: (Vector Double -> Double) -> Text -> DataFrame -> Maybe Double
standardDeviation :: Text -> DataFrame -> Maybe Double
interQuartileRange :: Text -> DataFrame -> Maybe Double
_getColumnAsDouble :: Text -> DataFrame -> Maybe (Vector Double)
applyStatistics :: (Vector Double -> Vector Double) -> Text -> DataFrame -> Maybe (Vector Double)
summarize :: DataFrame -> DataFrame
deriveFrom :: ([Text], Function) -> Text -> DataFrame -> DataFrame
derive :: forall b c. (Columnable b, Columnable c) => Text -> (b -> c) -> Text -> DataFrame -> DataFrame
applyMany :: (Columnable b, Columnable c) => (b -> c) -> [Text] -> DataFrame -> DataFrame
applyInt :: Columnable b => (Int -> b) -> Text -> DataFrame -> DataFrame
applyDouble :: Columnable b => (Double -> b) -> Text -> DataFrame -> DataFrame
applyWhere :: forall a b. (Columnable a, Columnable b) => (a -> Bool) -> Text -> (b -> b) -> Text -> DataFrame -> DataFrame
applyAtIndex :: forall a. Columnable a => Int -> (a -> a) -> Text -> DataFrame -> DataFrame
takeLast :: Int -> DataFrame -> DataFrame
dropLast :: Int -> DataFrame -> DataFrame
filterBy :: Columnable a => (a -> Bool) -> Text -> DataFrame -> DataFrame
filterWhere :: ([Text], Function) -> DataFrame -> DataFrame
filterJust :: Text -> DataFrame -> DataFrame
cube :: (Int, Int) -> DataFrame -> DataFrame
selectIntRange :: (Int, Int) -> DataFrame -> DataFrame
selectRange :: (Text, Text) -> DataFrame -> DataFrame
exclude :: [Text] -> DataFrame -> DataFrame
appendWithFrontMin :: Ord a => a -> [a] -> [a]
groupColumns :: Vector (Vector Int) -> DataFrame -> DataFrame -> Text -> DataFrame
mkGroupedColumns :: Vector Int -> DataFrame -> DataFrame -> Text -> DataFrame
hash' :: Columnable a => a -> Double
groupByAgg :: Aggregation -> [Text] -> DataFrame -> DataFrame
reduceBy :: forall a b. (Columnable a, Columnable b) => (forall v. Vector v a => v a -> b) -> Text -> DataFrame -> DataFrame
reduceByAgg :: Aggregation -> Text -> DataFrame -> DataFrame
aggregate :: [(Text, Aggregation)] -> DataFrame -> DataFrame
parseDefault :: Bool -> Maybe Column -> Maybe Column
readCsv :: String -> IO DataFrame
readSeparated :: Char -> ReadOptions -> String -> IO DataFrame
readTsv :: String -> IO DataFrame
countRows :: Char -> FilePath -> IO Int
parseSep :: Char -> Text -> [Text]
getInitialDataVectors :: Int -> IOVector Column -> [Text] -> IO ()
fillColumns :: Int -> Char -> IOVector Column -> IOVector [(Int, Text)] -> Handle -> IO ()
freezeColumn :: IOVector Column -> Vector [(Int, Text)] -> ReadOptions -> Int -> IO (Maybe Column)
inferValueType :: Text -> Text
parseRow :: Char -> Parser [Text]
writeValue :: IOVector Column -> IOVector [(Int, Text)] -> Int -> Int -> Text -> IO ()
record :: Char -> Parser [Text]
field :: Char -> Parser Text
lineEnd :: Parser ()
quotedField :: Parser Text
unquotedField :: Char -> Parser Text
unquotedTerminators :: Char -> Set Char
writeCsv :: String -> DataFrame -> IO ()
writeSeparated :: Char -> String -> DataFrame -> IO ()
getRowAsText :: DataFrame -> Int -> [Text]
(|>) :: a -> (a -> b) -> b

Documentation

data Function where Source #

Constructors

F1 :: forall a b. (Columnable a, Columnable b) => (a -> b) -> Function
F2 :: forall a b c. (Columnable a, Columnable b, Columnable c) => (a -> b -> c) -> Function
F3 :: forall a b c d. (Columnable a, Columnable b, Columnable c, Columnable d) => (a -> b -> c -> d) -> Function
F4 :: forall a b c d e. (Columnable a, Columnable b, Columnable c, Columnable d, Columnable e) => (a -> b -> c -> d -> e) -> Function
Cond :: forall a. Columnable a => (a -> Bool) -> Function
ICond :: forall a. Columnable a => (Int -> a -> Bool) -> Function

data Column where Source #

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

Constructors

BoxedColumn :: Columnable a => Vector a -> Column
UnboxedColumn :: (Columnable a, Unbox a) => Vector a -> Column
OptionalColumn :: Columnable a => Vector (Maybe a) -> Column
GroupedBoxedColumn :: Columnable a => Vector (Vector a) -> Column
GroupedUnboxedColumn :: (Columnable a, Unbox a) => Vector (Vector a) -> Column
GroupedOptionalColumn :: Columnable a => Vector (Vector (Maybe a)) -> Column
MutableBoxedColumn :: Columnable a => IOVector a -> Column
MutableUnboxedColumn :: (Columnable a, Unbox a) => IOVector a -> Column

Instances

Instances details

Show Column Source #
Instance details Defined in Data.DataFrame.Internal.Column Methods showsPrec :: Int -> Column -> ShowS # show :: Column -> String # showList :: [Column] -> ShowS #
Transformable Column Source #
Instance details Defined in Data.DataFrame.Internal.Column Methods transform :: (Columnable b, Columnable c) => (b -> c) -> Column -> Maybe Column Source #
Eq Column Source #
Instance details Defined in Data.DataFrame.Internal.Column Methods (==) :: Column -> Column -> Bool # (/=) :: Column -> Column -> Bool #

data DataFrame Source #

Constructors

DataFrame (Vector (Maybe Column)) (Map Text Int) [Int] (Int, Int)

Instances

Instances details

Show DataFrame Source #
Instance details Defined in Data.DataFrame.Internal.DataFrame Methods showsPrec :: Int -> DataFrame -> ShowS # show :: DataFrame -> String # showList :: [DataFrame] -> ShowS #
Eq DataFrame Source #
Instance details Defined in Data.DataFrame.Internal.DataFrame Methods (==) :: DataFrame -> DataFrame -> Bool # (/=) :: DataFrame -> DataFrame -> Bool #

type Row = Vector RowValue Source #

data Aggregation Source #

Constructors

Count
Mean
Minimum
Median
Maximum
Sum

Instances

Instances details

Show Aggregation Source #
Instance details Defined in Data.DataFrame.Operations.Aggregation Methods showsPrec :: Int -> Aggregation -> ShowS # show :: Aggregation -> String # showList :: [Aggregation] -> ShowS #
Eq Aggregation Source #
Instance details Defined in Data.DataFrame.Operations.Aggregation Methods (==) :: Aggregation -> Aggregation -> Bool # (/=) :: Aggregation -> Aggregation -> Bool #

data DataFrameException where Source #

Constructors

TypeMismatchException
Fields :: forall a b. (Typeable a, Typeable b) => TypeRep a given type -> TypeRep b expected type -> Text column name -> Text call point -> DataFrameException
TypeMismatchException'
Fields :: forall a. Typeable a => TypeRep a expected type -> String given type -> Text column name -> Text call point -> DataFrameException
ColumnNotFoundException :: Text -> Text -> [Text] -> DataFrameException

Instances

Instances details

Exception DataFrameException Source #
Instance details Defined in Data.DataFrame.Errors Methods toException :: DataFrameException -> SomeException # fromException :: SomeException -> Maybe DataFrameException # displayException :: DataFrameException -> String #
Show DataFrameException Source #
Instance details Defined in Data.DataFrame.Errors Methods showsPrec :: Int -> DataFrameException -> ShowS # show :: DataFrameException -> String # showList :: [DataFrameException] -> ShowS #

type Columnable a = (Typeable a, Show a, Ord a, Eq a) Source #

data RowValue where Source #

Constructors

Value :: Columnable a => a -> RowValue

Instances

Instances details

Show RowValue Source #
Instance details Defined in Data.DataFrame.Internal.Types Methods showsPrec :: Int -> RowValue -> ShowS # show :: RowValue -> String # showList :: [RowValue] -> ShowS #
Eq RowValue Source #
Instance details Defined in Data.DataFrame.Internal.Types Methods (==) :: RowValue -> RowValue -> Bool # (/=) :: RowValue -> RowValue -> Bool #
Ord RowValue Source #
Instance details Defined in Data.DataFrame.Internal.Types Methods compare :: RowValue -> RowValue -> Ordering # (<) :: RowValue -> RowValue -> Bool # (<=) :: RowValue -> RowValue -> Bool # (>) :: RowValue -> RowValue -> Bool # (>=) :: RowValue -> RowValue -> Bool # max :: RowValue -> RowValue -> RowValue # min :: RowValue -> RowValue -> RowValue #

class Transformable a where Source #

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

Methods

transform :: forall b c. (Columnable b, Columnable c) => (b -> c) -> a -> Maybe a Source #

Instances

Instances details

Transformable Column Source #
Instance details Defined in Data.DataFrame.Internal.Column Methods transform :: (Columnable b, Columnable c) => (b -> c) -> Column -> Maybe Column Source #

data TypeRepList (xs :: [Type]) where Source #

Constructors

Nil :: TypeRepList '[]
Cons :: Typeable x => TypeRep x -> TypeRepList xs -> TypeRepList (x ': xs)

class WrapFunction a where Source #

Methods

wrapFunction :: a -> Function Source #

Instances

Instances details

(Columnable a, Columnable b, Columnable c, Columnable d, Columnable e) => WrapFunction (a -> b -> c -> d -> e) Source #
Instance details Defined in Data.DataFrame.Internal.Function Methods wrapFunction :: (a -> b -> c -> d -> e) -> Function Source #
(Columnable a, Columnable b, Columnable c, Columnable d) => WrapFunction (a -> b -> c -> d) Source #
Instance details Defined in Data.DataFrame.Internal.Function Methods wrapFunction :: (a -> b -> c -> d) -> Function Source #
(Columnable a, Columnable b, Columnable c) => WrapFunction (a -> b -> c) Source #
Instance details Defined in Data.DataFrame.Internal.Function Methods wrapFunction :: (a -> b -> c) -> Function Source #
(Columnable a, Columnable b) => WrapFunction (a -> b) Source #
Instance details Defined in Data.DataFrame.Internal.Function Methods wrapFunction :: (a -> b) -> Function Source #

class Columnable a => Columnify a where Source #

Methods

toColumn' :: Vector a -> Column Source #

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

Instances

Instances details

Columnable a => Columnify a Source #
Instance details Defined in Data.DataFrame.Internal.Column Methods toColumn' :: Vector a -> Column Source #
Columnable a => Columnify (Vector a) Source #
Instance details Defined in Data.DataFrame.Internal.Column Methods toColumn' :: Vector (Vector a) -> Column Source #
(Columnable a, Unbox a) => Columnify (Vector a) Source #
Instance details Defined in Data.DataFrame.Internal.Column Methods toColumn' :: Vector0 (Vector a) -> Column Source #
Columnable a => Columnify (Maybe a) Source #
Instance details Defined in Data.DataFrame.Internal.Column Methods toColumn' :: Vector (Maybe a) -> Column Source #

class Columnable a => ColumnifyList a where Source #

Methods

toColumn :: [a] -> Column Source #

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

Instances

Instances details

Columnable a => ColumnifyList a Source #
Instance details Defined in Data.DataFrame.Internal.Column Methods toColumn :: [a] -> Column Source #
Columnable a => ColumnifyList (Maybe a) Source #
Instance details Defined in Data.DataFrame.Internal.Column Methods toColumn :: [Maybe a] -> Column Source #

data ColumnInfo Source #

Constructors

ColumnInfo
Fields nameOfColumn :: !Text nonNullValues :: !Int nullValues :: !Int partiallyParsedValues :: !Int uniqueValues :: !Int typeOfColumn :: !Text

data HistogramOrientation Source #

Constructors

VerticalHistogram
HorizontalHistogram

data PlotColumns Source #

Constructors

PlotAll
PlotSubset [Text]

data HistogramConfig Source #

Constructors

HistogramConfig
Fields width :: Int height :: Int barChar :: Char title :: Maybe String

data SortOrder Source #

Sort order taken as a parameter by the sortby function.

Constructors

Ascending
Descending

Instances

Instances details

Eq SortOrder Source #
Instance details Defined in Data.DataFrame.Operations.Sorting Methods (==) :: SortOrder -> SortOrder -> Bool # (/=) :: SortOrder -> SortOrder -> Bool #

data ReadOptions Source #

Record for CSV read options.

Constructors

ReadOptions
Fields hasHeader :: Bool inferTypes :: Bool safeRead :: Bool

pattern Empty :: Vector a Source #

pattern (:<|) :: a -> Vector a -> Vector a Source #

fromList :: [(Text, Column)] -> DataFrame Source #

apply Source #

Arguments

:: forall b c. (Columnable b, Columnable c)
=> (b -> c)	function to apply
-> Text	Column name
-> DataFrame	DataFrame to apply operation to
-> DataFrame

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

empty :: DataFrame Source #

O(1) Creates an empty dataframe

null :: DataFrame -> Bool Source #

filter Source #

Arguments

:: forall a. Columnable a
=> Text	Column to filter by
-> (a -> Bool)	Filter condition
-> DataFrame	Dataframe to filter
-> DataFrame

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

defaultOptions :: ReadOptions Source #

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).

range :: (Int, Int) -> DataFrame -> DataFrame Source #

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

take :: Int -> DataFrame -> DataFrame Source #

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

sortBy :: SortOrder -> [Text] -> DataFrame -> DataFrame Source #

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

sortBy "Age" df

groupBy :: [Text] -> DataFrame -> DataFrame Source #

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

uncons :: Vector a -> Maybe (a, Vector a) Source #

sum :: Text -> DataFrame -> Maybe Double Source #

drop :: Int -> DataFrame -> DataFrame Source #

rotate :: [String] -> [String] Source #

readInt :: HasCallStack => Text -> Maybe Int Source #

fold :: (a -> DataFrame -> DataFrame) -> [a] -> DataFrame -> DataFrame Source #

readInteger :: HasCallStack => Text -> Maybe Integer Source #

select :: [Text] -> DataFrame -> DataFrame Source #

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

select ["name", "age"] df

median :: Text -> DataFrame -> Maybe Double Source #

variance :: Text -> DataFrame -> Maybe Double Source #

mean :: Text -> DataFrame -> Maybe Double Source #

skewness :: Text -> DataFrame -> Maybe Double Source #

correlation :: Text -> Text -> DataFrame -> Maybe Double Source #

formatNumber :: Double -> String Source #

clip :: Int -> Int -> Int -> Int Source #

rename :: Text -> Text -> DataFrame -> DataFrame Source #

selectBy :: (Text -> Bool) -> DataFrame -> DataFrame Source #

O(n) select columns by column predicate name.

mkRowRep :: DataFrame -> Set Text -> Int -> Int Source #

isNullish :: Text -> Bool Source #

columnLength :: Column -> Int Source #

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

columnTypeString :: Column -> String Source #

expandColumn :: Int -> Column -> Column Source #

getColumn :: Text -> DataFrame -> Maybe Column Source #

dimensions :: DataFrame -> (Int, Int) Source #

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

mkRowFromArgs :: [Text] -> DataFrame -> Int -> Row Source #

toRowValue :: forall a. Columnable a => a -> RowValue Source #

frequencies :: Text -> DataFrame -> DataFrame Source #

itransform :: forall b c. (Columnable b, Columnable c) => (Int -> b -> c) -> Column -> Maybe Column Source #

tranform with index.

ifoldrColumn :: forall a b. (Columnable a, Columnable b) => (Int -> a -> b -> b) -> b -> Column -> Maybe b Source #

funcApply :: forall c. Columnable c => Vector RowValue -> Function -> c Source #

parseDefaults :: Bool -> DataFrame -> DataFrame Source #

getIndicesUnboxed :: Unbox a => Vector Int -> Vector a -> Vector a Source #

getIndices :: Vector Int -> Vector a -> Vector a Source #

freezeColumn' :: [(Int, Text)] -> Column -> IO Column Source #

writeColumn :: Int -> Text -> Column -> IO (Either Text Bool) Source #

func :: forall fn. WrapFunction fn => fn -> Function Source #

addCallPointInfo :: Text -> Maybe Text -> String -> String Source #

typeMismatchError :: TypeRep a -> TypeRep b -> String Source #

typeMismatchError' :: String -> String -> String Source #

columnNotFound :: Text -> Text -> [Text] -> String Source #

guessColumnName :: Text -> [Text] -> Text Source #

typeAnnotationSuggestion :: String -> String Source #

editDistance :: Text -> Text -> Int Source #

readValue :: (HasCallStack, Read a) => Text -> a Source #

readByteStringInt :: HasCallStack => ByteString -> Maybe Int Source #

readDouble :: HasCallStack => Text -> Maybe Double Source #

readIntegerEither :: HasCallStack => Text -> Either Text Integer Source #

readIntEither :: HasCallStack => Text -> Either Text Int Source #

readDoubleEither :: HasCallStack => Text -> Either Text Double Source #

safeReadValue :: Read a => Text -> Maybe a Source #

readWithDefault :: (HasCallStack, Read a) => a -> Text -> a Source #

unboxableTypes :: TypeRepList '[Int, Int8, Int16, Int32, Int64, Word, Word8, Word16, Word32, Word64, Char, Double, Float, Bool] Source #

numericTypes :: TypeRepList '[Int, Int8, Int16, Int32, Int64, Double, Float] Source #

matchesAnyType :: forall a xs. Typeable a => TypeRepList xs -> TypeRep a -> Bool Source #

testUnboxable :: forall a. Typeable a => TypeRep a -> Bool Source #

testNumeric :: forall a. Typeable a => TypeRep a -> Bool Source #

isGrouped :: Column -> Bool Source #

columnVersionString :: Column -> String Source #

toColumnUnboxed :: forall a. (Columnable a, Unbox a) => Vector a -> Column Source #

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.

takeColumn :: Int -> Column -> Column Source #

takeLastColumn :: Int -> Column -> Column Source #

sliceColumn :: Int -> Int -> Column -> Column Source #

atIndices :: Set Int -> Column -> Column Source #

atIndicesStable :: Vector Int -> Column -> Column Source #

sortedIndexes :: Bool -> Column -> Vector Int Source #

transformUnboxed :: forall a b. (Columnable a, Unbox a, Columnable b) => (a -> b) -> Vector a -> Column Source #

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

itransformUnboxed :: forall a b. (Columnable a, Unbox a, Columnable b) => (Int -> a -> b) -> Vector a -> Column Source #

ifilterColumn :: forall a. Columnable a => (Int -> a -> Bool) -> Column -> Maybe Column Source #

Filter column with index.

ifilterColumnF :: Function -> Column -> Maybe Column Source #

ifoldlColumn :: forall a b. (Columnable a, Columnable b) => (b -> Int -> a -> b) -> b -> Column -> Maybe b Source #

reduceColumn :: forall a b. Columnable a => (a -> b) -> Column -> b Source #

safeReduceColumn :: forall a b. Typeable a => (a -> b) -> Column -> Maybe b Source #

zipColumns :: Column -> Column -> Column Source #

nulls :: Column -> Int Source #

asText :: DataFrame -> Text Source #

initialColumnSize :: Int Source #

metadata :: DataFrame -> String Source #

toRowList :: [Text] -> DataFrame -> [Row] Source #

toRowVector :: [Text] -> DataFrame -> Vector Row Source #

sortedIndexes' :: Bool -> Vector Row -> Vector Int Source #

columnNames :: DataFrame -> [Text] Source #

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

insertColumn Source #

Arguments

:: forall a. Columnable a
=> Text	Column Name
-> Vector a	Vector to add to column
-> DataFrame	DataFrame to add column to
-> DataFrame

O(n) Adds a vector to the dataframe.

insertColumn' Source #

Arguments

:: Text	Column Name
-> Maybe Column	Column to add
-> DataFrame	DataFrame to add to column
-> DataFrame

cloneColumn :: Text -> Text -> DataFrame -> DataFrame Source #

insertUnboxedColumn Source #

Arguments

:: forall a. (Columnable a, Unbox a)
=> Text	Column Name
-> Vector a	Unboxed vector to add to column
-> DataFrame	DataFrame to add to column
-> DataFrame

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

insertColumnWithDefault Source #

Arguments

:: forall a. Columnable a
=> a	Default Value
-> Text	Column name
-> Vector a	Data to add to column
-> DataFrame	DataFrame to add to column
-> 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.

columnSize :: Text -> DataFrame -> Maybe Int Source #

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

columnInfo :: DataFrame -> DataFrame Source #

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

partiallyParsed :: Column -> Int Source #

valueCounts :: forall a. Columnable a => Text -> DataFrame -> [(a, Int)] Source #

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

plotHistograms :: HasCallStack => PlotColumns -> HistogramOrientation -> DataFrame -> IO () Source #

plotForColumn :: HasCallStack => Text -> Maybe Column -> HistogramOrientation -> DataFrame -> IO () Source #

plotHistogramsBy :: HasCallStack => Text -> PlotColumns -> HistogramOrientation -> DataFrame -> IO () Source #

plotForColumnBy :: HasCallStack => Text -> Text -> Maybe Column -> Maybe Column -> HistogramOrientation -> DataFrame -> IO () Source #

countOccurrences :: Ord a => Vector a -> [(a, Int)] Source #

plotGivenCounts' :: HasCallStack => Text -> [((String, String), Int)] -> IO () Source #

numericHistogram :: forall a. (HasCallStack, Columnable a) => Text -> Vector a -> String Source #

plotVerticalGivenCounts :: HasCallStack => Text -> [(String, Int)] -> IO () Source #

plotGivenCounts :: HasCallStack => Text -> [(String, Int)] -> IO () Source #

leftJustify :: String -> Int -> String Source #

smallestPartition :: Ord a => a -> [a] -> a Source #

intPlotRanges :: [Int] Source #

defaultConfig :: HistogramConfig Source #

createHistogram :: HistogramConfig -> [Double] -> String Source #

largestPartition :: Ord a => a -> [a] -> a Source #

calculateBins :: [Double] -> Int -> [(Double, Int)] Source #

applyStatistic :: (Vector Double -> Double) -> Text -> DataFrame -> Maybe Double Source #

standardDeviation :: Text -> DataFrame -> Maybe Double Source #

interQuartileRange :: Text -> DataFrame -> Maybe Double Source #

_getColumnAsDouble :: Text -> DataFrame -> Maybe (Vector Double) Source #

applyStatistics :: (Vector Double -> Vector Double) -> Text -> DataFrame -> Maybe (Vector Double) Source #

summarize :: DataFrame -> DataFrame Source #

deriveFrom :: ([Text], Function) -> Text -> DataFrame -> DataFrame Source #

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

derive Source #

Arguments

:: forall b c. (Columnable b, Columnable c)
=> Text	New name
-> (b -> c)	function to apply
-> Text	Derivative column name
-> DataFrame	DataFrame to apply operation to
-> DataFrame

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

applyMany :: (Columnable b, Columnable c) => (b -> c) -> [Text] -> DataFrame -> DataFrame Source #

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

applyInt Source #

Arguments

:: Columnable b
=> (Int -> b)	Column name \| function to apply
-> Text
-> DataFrame	DataFrame to apply operation to
-> DataFrame

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

applyDouble Source #

Arguments

:: Columnable b
=> (Double -> b)	Column name \| function to apply
-> Text
-> DataFrame	DataFrame to apply operation to
-> DataFrame

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

applyWhere :: forall a b. (Columnable a, Columnable b) => (a -> Bool) -> Text -> (b -> b) -> Text -> DataFrame -> DataFrame Source #

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")

applyAtIndex Source #

Arguments

:: forall a. Columnable a
=> Int	Index
-> (a -> a)	function to apply
-> Text	Column name
-> DataFrame	DataFrame to apply operation to
-> DataFrame

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

takeLast :: Int -> DataFrame -> DataFrame Source #

dropLast :: Int -> DataFrame -> DataFrame Source #

filterBy :: Columnable a => (a -> Bool) -> Text -> DataFrame -> DataFrame Source #

filterWhere :: ([Text], Function) -> DataFrame -> DataFrame Source #

filterJust :: Text -> DataFrame -> DataFrame Source #

cube :: (Int, Int) -> DataFrame -> DataFrame Source #

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

selectIntRange :: (Int, Int) -> DataFrame -> DataFrame Source #

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

selectRange :: (Text, Text) -> DataFrame -> DataFrame Source #

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

exclude :: [Text] -> DataFrame -> DataFrame Source #

O(n) inverse of select

exclude ["Name"] df

appendWithFrontMin :: Ord a => a -> [a] -> [a] Source #

groupColumns :: Vector (Vector Int) -> DataFrame -> DataFrame -> Text -> DataFrame Source #

mkGroupedColumns :: Vector Int -> DataFrame -> DataFrame -> Text -> DataFrame Source #

hash' :: Columnable a => a -> Double Source #

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

groupByAgg :: Aggregation -> [Text] -> DataFrame -> DataFrame Source #

reduceBy :: forall a b. (Columnable a, Columnable b) => (forall v. Vector v a => v a -> b) -> Text -> DataFrame -> DataFrame Source #

reduceByAgg :: Aggregation -> Text -> DataFrame -> DataFrame Source #

aggregate :: [(Text, Aggregation)] -> DataFrame -> DataFrame Source #

parseDefault :: Bool -> Maybe Column -> Maybe Column Source #

readCsv :: String -> IO DataFrame Source #

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.

readSeparated :: Char -> ReadOptions -> String -> IO DataFrame Source #

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

readTsv :: String -> IO DataFrame Source #

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.

countRows :: Char -> FilePath -> IO Int Source #

First pass to count rows for exact allocation

parseSep :: Char -> Text -> [Text] Source #

getInitialDataVectors :: Int -> IOVector Column -> [Text] -> IO () Source #

fillColumns :: Int -> Char -> IOVector Column -> IOVector [(Int, Text)] -> Handle -> IO () Source #

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

freezeColumn :: IOVector Column -> Vector [(Int, Text)] -> ReadOptions -> Int -> IO (Maybe Column) Source #

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

inferValueType :: Text -> Text Source #

parseRow :: Char -> Parser [Text] Source #

writeValue :: IOVector Column -> IOVector [(Int, Text)] -> Int -> Int -> Text -> IO () Source #

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

record :: Char -> Parser [Text] Source #

field :: Char -> Parser Text Source #

lineEnd :: Parser () Source #

quotedField :: Parser Text Source #

unquotedField :: Char -> Parser Text Source #

unquotedTerminators :: Char -> Set Char Source #

writeCsv :: String -> DataFrame -> IO () Source #

writeSeparated Source #

Arguments

:: Char	Separator
-> String	Path to write to
-> DataFrame
-> IO ()

getRowAsText :: DataFrame -> Int -> [Text] Source #

(|>) :: a -> (a -> b) -> b Source #