Terminal defaults: 10 rows plus the standard column and cell caps.

Render a DataFrame to stdout according to DisplayOptions.

A runtime tag for a column’s element type.

Construct a SchemaType for the given a.

Construct a Schema from a list of (columnName, schemaType) pairs.

Derive an untyped Schema value and per-column accessors from a record.

CSV read parameters.

How a reader decides each column's type.

Where a reader's column names come from.

The default ReadOptions: infer from 100 rows, header row, all data.

Read a CSV file from a path into a dataframe.

Read a CSV, coercing columns to the types declared in a Schema.

Read a CSV file from a path using the given ReadOptions.

Read a tab-separated file into a dataframe.

Read a text file with a chosen delimiter into a dataframe.

Write a dataframe to a comma-separated file.

Write a dataframe to a file using the given field separator.

Parse a CSV string into a DataFrame using default options.

Parse a lazy ByteString of CSV data using default options.

Options for reading Parquet data.

Default Parquet read options.

Read a parquet file from path and load it into a dataframe.

Read a Parquet file using explicit read options.

Read Parquet files from a directory or glob path.

Read multiple Parquet files (directory or glob) using options.

Optimise and stream-execute the lazy query into a DataFrame.

A lazy query: a LogicalPlan whose execution waits for run.

Lift an already-loaded eager DataFrame into the lazy plan.

Scan a CSV file with the default comma separator and strict reader.

Like scanCsv but with an explicit CsvReader.

Scan a character-separated file with the default strict reader.

Like scanSeparated but with an explicit CSV reader.

Scan a Parquet file, directory of files, or glob pattern.

How parse failures are surfaced: throw, Nothing, or Left raw text.

Options controlling how text columns are parsed into typed values.

Sensible out-of-the-box parse options: infer from 100 rows, ISO dates.

Resolve a column's effective SafeReadMode: override if present.

O(k) Filter the dataframe with a boolean expression.

Sample a dataframe; the fraction must be between 0 and 1 inclusive.

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) Drop the first n rows of a DataFrame.

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

O(n * k) Keep rows whose value of the expression satisfies the predicate.

O(k) Remove all rows with Nothing in a given column.

O(k) Return all rows with Nothing in a given column.

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

O(n * k) Keep any row with a null value.

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

O(k * n) Drop the last n rows of a DataFrame.

O(k) Cut the dataframe to a cube of size (length, width).

O(k * n) Select rows by index.

Split a dataset in two: a sample of fraction p and the remainder.

Create n folds of a dataframe.

Sample a dataframe, preserving per-stratum proportions.

Split a dataframe into two, preserving per-stratum proportions.

O(n) select columns by column predicate name.

O(n) Inverse of select.

Criteria for selecting a column by name.

Criteria for selecting columns whose property satisfies a predicate.

Criteria for selecting columns whose name satisfies a predicate.

Criteria for selecting columns whose names are in a lexicographic range.

Criteria for selecting columns whose indices are in an inclusive range.

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

O(k) Derive a new column named alias from an expression.

O(k) Like derive but also returns a reference to the new column.

Replace all instances of Nothing in a column with the given value.

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 given column names in a dataframe.

O(k * n) Apply a function to a column where another column matches.

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

O(k) Safe version of apply. Returns the error instead of throwing.

O(k * n) group the dataframe by the given key columns via a hash table.

Aggregate a grouped dataframe using the expressions given.

Filter out all non-unique values in a dataframe.

O(k log n) Sort the dataframe by the given sort orders.

Sort order taken as a parameter by the sortBy function.

The rows a sortBy would place at positions [offset, offset + count).

Join two dataframes using SQL join semantics.

Equivalent to SQL join types.

Join on (leftKey, rightKey) pairs; the result keeps the left names.

Inner join on two dataframes using the specified key columns.

Left join on two dataframes, keeping every row from the left dataframe.

Right join on two dataframes, keeping every row from the right dataframe.

Bridge a Haskell record type to a typed-dataframe schema.

Build an untyped DataFrame from a list of records.

Parse a list of records out of an untyped DataFrame.

The column names a schema declares, in schema order.

Splice an Expr T binding for every column of a CSV file.

Like declareColumnsFromCsvFile but with custom ReadOptions.

Splice a binding for every column of a parquet file or directory.

Splice a binding for every column of df, named after the column.

Like declareColumns but prefixes every binding name with prefix_.

Like declareColumnsWithPrefix but takes an optional prefix.

Splice a runtime Schema for df along with per-column Expr refs.