golars / polars API surface

Last synced: 2026-04-24.

Authoritative map between polars' Python API (pl.*) and golars' Go surface. Status column values:

done shipped and covered by tests
partial shipped for a common subset; documented gaps
todo not yet

The package-level facade at the repo root (import "github.com/Gaurav-Gosain/golars") re-exports the most commonly needed symbols so casual users do not need to know which sub-package each name lives in.

Top-level functions (`pl.` / `golars.`)

polars	golars	Status	Notes
`pl.DataFrame({...})`	`golars.FromMap(...)`	done	slice-of-go map constructor
`pl.from_arrow(tbl)`	`dataframe.FromArrowTable(tbl)`	done
`pl.concat([...])`	`dataframe.Concat(...)`	done	vertical
`pl.col(name)`	`golars.Col(name)`	done	also typed: `expr.C[T]`, `expr.Int`, `expr.Float`, `expr.Str`, `expr.Bool`, `expr.Int32`, `expr.Float32`
`pl.lit(v)`	`golars.Lit(v)`	done	plus `LitInt64`/`LitFloat64`/`LitString`/`LitBool`; generic `expr.LitOf[T]`
`pl.when(p).then(a).otherwise(b)`	`golars.When(p).Then(a).Otherwise(b)`	done	executor uses compute.Where with dtype promotion
`pl.sum(col)`, `mean`, `min`, `max`, `count`, `first`, `last`, `median`, `std`, `var`	`golars.Sum(col)` and friends	done	col-scoped agg sugar
`pl.read_csv`	`golars.ReadCSV`	done
`pl.read_parquet`	`golars.ReadParquet`	done
`pl.read_ipc` / `read_arrow`	`golars.ReadIPC`	done
`pl.read_json` / `read_ndjson`	`golars.ReadJSON` / `golars.ReadNDJSON`	done
`pl.read_database`	`io/sql.ReadSQL`	done
`pl.read_clipboard`	`io/clipboard.Read`	done	CSV transport
`pl.read_avro`		todo	defer
`pl.read_excel`		todo	needs xuri/excelize dep
`pl.read_delta` / `read_iceberg`		todo	RFC required
`pl.scan_csv`	`io/csv.Scan`	done	LazyFrame source
`pl.scan_parquet`	`io/parquet.Scan`	done
`pl.scan_ipc`	`io/ipc.Scan`	done
`pl.scan_ndjson`	`io/json.ScanNDJSON`	done

DataFrame methods

polars	golars	Status
`df.shape`	`df.Shape()`	done
`df.height` / `.width`	`df.Height()` / `.Width()`	done
`df.columns`	`df.ColumnNames()`	done
`df.dtypes`	`df.DTypes()`	done
`df.schema`	`df.Schema()`	done
`df.is_empty`	`df.IsEmpty()`	done
`df.estimated_size`	`df.EstimatedSize()`	done
`df.equals`	`df.Equals(other)`	done
`df.glimpse`	`df.Glimpse(n)`	done
`df.head` / `.tail` / `.limit`	`df.Head` / `.Tail` / `.Limit`	done
`df.slice`	`df.Slice(offset, length)`	done
`df.select(exprs)`	`df.Select(names...)` / `golars.SelectExpr(ctx, df, exprs...)`	done
`df.with_columns(exprs)`	`df.WithColumns(series...)` / `golars.WithColumnsExpr(ctx, df, exprs...)`	done
`df.with_column`	`df.WithColumn(series)`	done
`df.rename`	`df.Rename(old, new)`	done
`df.drop`	`df.Drop(names...)`	done
`df.filter(mask)`	`df.Filter(ctx, mask)`	done
`df.sort(by)`	`df.Sort` / `.SortBy`	done
`df.reverse`	`df.Reverse(ctx)`	done
`df.sample(n)`	`df.Sample(ctx, n, replacement, seed)`	done
`df.shuffle`	`df.Shuffle(ctx, seed)`	done
`df.clone`	`df.Clone()`	done
`df.clear`	`df.Clear()`	done
`df.group_by(...).agg(...)`	`df.GroupBy(...).Agg(ctx, [expr...])`	done
`df.join(other, on, how)`	`df.Join(ctx, right, on, how)`	done
`df.vstack` / `.hstack`	`df.VStack(other)` / `df.HStack(other)`	done
`df.concat`	top-level `dataframe.Concat(...)`	done
`df.describe`	`df.Describe(ctx)`	done
`df.null_count`	`df.NullCount()`	done
`df.row(i)`	`df.Row(i)`	done
`df.rows()`	`df.Rows()`	done
`df.to_dict`	`df.ToMap()`	done
`df.to_arrow` / `to_pandas`	`df.ToArrow()` / `df.ToArrowTable()`	done (n/a for pandas)
`df.write_csv` / `write_parquet` / `write_ipc` / `write_json` / `write_ndjson`	`io/*.WriteFile(ctx, path, df, ...)`	done
`df.gather(indices)`	`df.Gather(ctx, indices)`	done
`df.pivot`	`df.Pivot(ctx, index, on, values, PivotAgg)`	done
`df.unpivot` (melt)	`df.Unpivot(ctx, idVars, valueVars)`	done
`df.transpose`	`df.Transpose(ctx, headerCol, prefix)`	done (numeric/bool)
`df.partition_by`	`df.PartitionBy(ctx, keys...)`	done
`df.top_k` / `df.bottom_k`	`df.TopK(ctx, k, col)` / `df.BottomK(ctx, k, col)`	done
`df.pipe(fn)`	`df.Pipe(fn)`	done
`df.corr` / `df.cov`	`df.Corr(ctx)` / `df.Cov(ctx, ddof)`	done
`df.explode`	`df.Explode(ctx, col)`	done
`df.unnest`	`df.Unnest(ctx, col)`	done
`df.upsample`	`df.Upsample(ctx, col, every)`	done

Series methods

Inspection

polars	golars	Status
`s.dtype`	`s.DType()`	done
`s.name`	`s.Name()`	done
`s.len`	`s.Len()`	done
`s.null_count`	`s.NullCount()`	done
`s.has_nulls`	`s.HasNulls()`	done
`s.is_empty`	`s.IsEmpty()`	done
`s.n_chunks`	`s.NumChunks()`	done
`s.n_unique`	`s.NUnique()`	done
`s.is_sorted`	`s.IsSorted(order)`	done

Math (scalar)

polars	golars	Status
`s.abs`	`s.Abs()`	done
`s.sqrt`	`s.Sqrt()`	done
`s.exp`	`s.Exp()`	done
`s.log`	`s.Log()`	done
`s.log2` / `log10`	`s.Log2` / `.Log10`	done
`s.sin` / `cos` / `tan`	`s.Sin` / `.Cos` / `.Tan`	done
`s.round(d)`	`s.Round(d)`	done
`s.floor` / `ceil`	`s.Floor` / `.Ceil`	done
`s.sign`	`s.Sign()`	done
`s.clip(lo, hi)`	`s.Clip(lo, hi)`	done
`s.pow(exp)`	`s.Pow(exp)`	done

Aggregations (scalar-returning)

polars	golars	Status
`s.sum`	`s.Sum()`	done
`s.mean`	`s.Mean()`	done
`s.min` / `max`	`s.Min()` / `.Max()`	done
`s.median`	`s.Median()`	done
`s.std` / `var`	`s.Std()` / `.Var()`	done
`s.quantile(q)`	`s.Quantile(q)`	done
`s.any` / `all`	`s.Any()` / `.All()`	done
`s.product`	`s.Product()`	done

Position / argsort

polars	golars	Status
`s.arg_min` / `arg_max`	`s.ArgMin()` / `.ArgMax()`	done
`s.arg_sort`	`s.ArgSort()`	done
`s.top_k(k)` / `bottom_k`	`s.TopK(k)` / `.BottomK(k)`	done

Transform

polars	golars	Status
`s.head` / `tail`	`s.Head` / `.Tail`	done
`s.slice`	`s.Slice`	done
`s.reverse`	`s.Reverse`	done
`s.sample`	`s.Sample`	done
`s.shuffle`	`s.Shuffle`	done
`s.sort`	`compute.Sort(ctx, s, opts)`	done
`s.unique`	`s.Unique()`	done
`s.value_counts`	`s.ValueCounts(sort)`	done
`s.rename` / `alias`	`s.Rename(name)`	done
`s.clone`	`s.Clone()`	done
`s.cast`	`compute.Cast(ctx, s, dt)`	done
`s.rechunk` / `chunks`	`s.Rechunk()` / `s.Chunk(i)` / `.Chunked()`	done

Null handling

polars	golars	Status
`s.is_null` / `is_not_null`	`s.IsNull()` / `.IsNotNull()`	done
`s.is_nan` / `is_finite` / `is_infinite`	`s.IsNaN()` / `.IsFinite()` / `.IsInfinite()`	done
`s.fill_null(v)`	`s.FillNull(v)`	done
`s.drop_nulls`	`s.DropNulls()`	done

Cumulative

polars	golars	Status
`s.cum_sum`	`s.CumSum()`	done
`s.cum_min` / `cum_max`	`s.CumMin()` / `.CumMax()`	done
`s.cum_prod`	`s.CumProd()`	done
`s.cum_count`	`s.CumCount()`	done
`s.diff(periods)`	`s.Diff(periods)`	done
`s.shift(periods)`	`s.Shift(periods)`	done
`s.pct_change(periods)`	`s.PctChange(periods)`	done
`s.mode`	`s.Mode()`	done

Rolling / windowed

polars	golars	Status
`s.rolling_sum` / `rolling_mean` / `rolling_min` / `rolling_max` / `rolling_std` / `rolling_var`	matching methods with `RollingOptions`	done
`s.ewm_mean` / `s.ewm_var` / `s.ewm_std`	`s.EWMMean(alpha)` / `.EWMVar(alpha)` / `.EWMStd(alpha)`	done

String namespace (`s.str.*`)

polars	golars	Status
`str.len_bytes` / `len_chars`	`.Str().LenBytes()` / `.LenChars()`	done
`str.to_uppercase` / `to_lowercase`	`.Str().Upper()` / `.Lower()`	done
`str.title`	`.Str().Title()`	done
`str.contains`	`.Str().Contains(sub)`	done
`str.starts_with` / `ends_with`	`.Str().StartsWith()` / `.EndsWith()`	done
`str.replace` / `replace_all`	`.Str().Replace()` / `.ReplaceAll()`	done
`str.strip_chars`	`.Str().Trim()` / `.LStrip()` / `.RStrip()`	done
`str.strip_prefix` / `strip_suffix`	`.Str().StripPrefix()` / `.StripSuffix()`	done
`str.pad_start` / `pad_end` / `zfill`	`.Str().PadStart()` / `.PadEnd()` / `.ZFill()`	done
`str.reverse`	`.Str().Reverse()`	done
`str.slice`	`.Str().Slice(start, len)`	done
`str.count_matches`	`.Str().CountMatches()`	done
`str.concat`	`.Str().Concat()` / `.Str().Prefix()`	done
`str.extract`	`.Str().Extract(pattern, group)`	done
`str.contains_regex` / `count_matches_regex` / `replace_regex`	matching `.Str().*Regex`	done
`str.split_exact`	`.Str().SplitExact(sep)` (List<String>) / `.Str().SplitN(sep, idx)` / `.Str().SplitExactNullShort(sep, idx)`	done

Arrow interop

polars	golars	Status
`s.to_arrow`	`s.ToArrow()` / `s.ToArrowChunked()`	done
`pl.from_arrow(arr)`	`series.FromArrowArray` / `FromArrowChunked`	done
`df.to_arrow`	`df.ToArrow()` / `df.ToArrowTable()`	done
`pl.from_arrow(tbl)`	`dataframe.FromArrowTable(tbl)`	done

Expr methods

polars	golars	Status
`pl.col(x)` with `+ - * /`	`Col(x).Add/Sub/Mul/Div(...)`	done
`== != < <= > >=`	`Eq/Ne/Lt/Le/Gt/Ge`	done
`and / or / not`	`And / Or / Not`	done
`.alias(name)`	`.Alias(name)`	done
`.cast(dt)`	`.Cast(dt)`	done
`.is_null` / `.is_not_null`	`.IsNull()` / `.IsNotNull()`	done
`.sum .mean .min .max .count .first .last .null_count`	matching methods	done
`.median .std .var .any .all .product .quantile`	matching methods	done
`.abs .sqrt .exp .log .log2 .log10 .sin .cos .tan .sign`	matching methods	done
`.round(d) .floor .ceil .clip(lo, hi) .pow(x)`	matching methods	done
`.fill_null(v)`	`.FillNull(v)` / `.FillNullExpr(e)`	done
`.reverse .head(n) .tail(n) .slice(off, len) .shift(p)`	matching methods	done
`.between(lo, hi)`	`.Between(lo, hi)`	done
`.is_in([...])`	`.IsIn(v...)`	done
`.over(partition)`	`.Over(keys...)`	done (scalar-agg fast path + generic gather-eval-scatter)
`.sort`	`.Sort(desc)` (fluent via FunctionNode)	done
`.rank(method)`	`.Rank(method)`	done
`.rolling_sum` / `.rolling_mean` / ...	matching `.Rolling*(size, minPeriods)`	done
`.ewm_mean` / `.ewm_var` / `.ewm_std`	matching `.EWM*(alpha)`	done

LazyFrame methods

polars	golars	Status
`lf.filter` / `.select` / `.with_columns`	`lf.Filter / .Select / .WithColumns`	done
`lf.with_column`	`lf.WithColumn(expr)`	done
`lf.sort / .group_by / .agg / .join`	matching	done
`lf.slice / .head / .limit / .tail`	matching	done
`lf.reverse`	`lf.Reverse()`	done
`lf.unique`	`lf.Unique()`	done
`lf.drop / .rename`	matching	done
`lf.collect` / `.collect_unoptimized`	matching	done
`lf.explain / .show_graph`	`lf.Explain()` / `lf.ExplainTree()` / `lf.ShowGraph()`	done
`lf.sink_csv / sink_parquet / sink_ipc / sink_ndjson`	`lf.Sink(ctx, writer)` plus `io/*.WriteFile` in writer	done

dtype

polars	golars	Status
Bool, Int8, Int16, Int32, Int64, UInt8 through UInt64, Float32, Float64	`dtype.Bool()`, `dtype.Int64()` and friends	done
String / Utf8	`dtype.String()`	done
Binary	`dtype.Binary()`	done
Null	`dtype.Null()`	done
Date / Datetime(unit, tz) / Duration / Time	`dtype.Date / Datetime / Duration / Time` + `series.FromTime`	done
List(inner) / Array / Struct / Field	`dtype.List / FixedList / Struct` + `series.{ListOps, StructOps}`	done
Categorical / Enum		todo
Decimal / Float16 / Int128		todo
Object / Unknown		todo (polars-internal)

See roadmap.md for the perf side of the same picture (throughput ratios vs polars 1.39 on the bench suite).

golars / polars API surface

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