v0.1.7

Release v0.1.7

This release implements several changes to the behavior of `CSVNormalizer` to increase its usefulness:

**New `CSVNormalizer.toObject()` static method**: This method is useful when users only need to **read the values of a normalized CSV row**. Previously, users would have to search the row by column name, then get the value of the field. Now, users can simply call `CSVNormalizer.toObject(row)` and destructure the resulting object normally.

**New `CSVNormalizer.toFieldMap()` static method**: This method is useful when users need to **both read and write values of a normalized CSV row**. This method implements a subset of the `Map` interface that keeps the underlying `CSVNormalizerField` objects in sync with changes made on the field values.

**Parse Unix timestamps**: In addition to Excel native date values, the normalizer can now also parse Unix timestamps (both seconds and milliseconds). It uses a simple heuristic with arbitrary cutoffs to pick which one of the three was the most likely intended value.

**Column names are now case-insensitive**: The normalizer is now **case-insensitive** when parsing column names. This change aligns with the overall opinionated nature of the normalizer and is consistent with the already strong opinions about neutralizing whitespace in column names.

**All empty rows before the header are now deleted**: Sometimes users insert empty rows before the data for formatting purposes. These empty rows are now deleted by the normalizer.

**Clarify data casting**: `CSVNormalizer` now emits native data types (e.g., `BigInt` or `Date`) instead of casting to `string`. As a complementary change, `CSVDenormalizer` now always emits `string`. This change aligns these two classes to serve complementary roles (`CSVNormalizer` converts `Array<string>` to `Array<CSVNormalizerField>` and `CSVDenormalizer` converts `Array<CSVNormalizerField>` to `Array<string>`).
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