infer_objects / convert_dtypes

What it does

These utilities refine dtypes automatically — useful after reading data from CSV/JSON where everything starts as object or string:

• inferObjectsSeries — promotes an object-typed Series to a more specific dtype (int, float, bool, string) when all values have a consistent type.
• inferObjectsDataFrame — applies per-column inference to every column.
• convertDtypesSeries — like inferObjectsSeries but also parses string columns as numbers when possible.
• convertDtypesDataFrame — per-column convertDtypesSeries.

inferObjectsSeries — promote object → typed

import { Series, Dtype, inferObjectsSeries } from "tsb";

// Object series holding integers
const s = new Series({ data: [1, 2, 3], dtype: Dtype.object });
s.dtype.kind;  // "object"

const better = inferObjectsSeries(s);
better.dtype.kind; // "int"
better.values;     // [1, 2, 3]

// Mixed types — cannot infer, returns original
const mixed = new Series({ data: [1, "a", true], dtype: Dtype.object });
inferObjectsSeries(mixed).dtype.kind; // "object"

// All null — no inference possible
const nulls = new Series({ data: [null, null], dtype: Dtype.object });
inferObjectsSeries(nulls).dtype.kind; // "object"

inferObjectsDataFrame — all columns at once

import { DataFrame, inferObjectsDataFrame } from "tsb";

const df = DataFrame.fromColumns({
  ints:   [1, 2, 3],
  floats: [1.1, 2.2, 3.3],
  strs:   ["a", "b", "c"],
  bools:  [true, false, true],
});

const inferred = inferObjectsDataFrame(df);
inferred.col("ints").dtype.kind;   // "int"
inferred.col("floats").dtype.kind; // "float"
inferred.col("strs").dtype.kind;   // "string"
inferred.col("bools").dtype.kind;  // "bool"

convertDtypesSeries — also parses numeric strings

import { Series, convertDtypesSeries } from "tsb";

// String values that look like integers
const ints = new Series({ data: ["1", "2", "3"] });
const result = convertDtypesSeries(ints);
result.dtype.kind; // "int"
result.values;     // [1, 2, 3]

// String values that look like floats
const floats = new Series({ data: ["1.5", "2.5", "3.5"] });
convertDtypesSeries(floats).dtype.kind; // "float"

// Non-numeric strings: unchanged
const text = new Series({ data: ["apple", "banana"] });
convertDtypesSeries(text);  // same Series, dtype "string"

// Int series with nulls → can convert to float for NA safety
import { Dtype } from "tsb";
const withNull = new Series({ data: [1, null, 3], dtype: Dtype.int64 });
convertDtypesSeries(withNull, { convertIntegerToFloat: true }).dtype.kind;
// "float"  (null becomes NaN-compatible)

convertDtypesDataFrame — per-column conversion

import { DataFrame, convertDtypesDataFrame } from "tsb";

// After reading a CSV, all columns come back as strings:
const raw = DataFrame.fromColumns({
  age:   ["25", "30", "22"],
  score: ["88.5", "92.1", "78.0"],
  name:  ["Alice", "Bob", "Charlie"],
});

const typed = convertDtypesDataFrame(raw);
typed.col("age").dtype.kind;   // "int"
typed.col("score").dtype.kind; // "float"
typed.col("name").dtype.kind;  // "string" (unchanged — not numeric)

API reference

InferObjectsOptions

ConvertDtypesOptions

When to use which