All Versions
14
Latest Version
Avg Release Cycle
159 days
Latest Release
723 days ago

Changelog History
Page 2

  • v0.3.0 Changes

    February 18, 2016

    ➕ Added in 0.3.0

    • Getter and setter methods for the column names of a DataFrame
    • Bool column type has been made available
    • 🆕 New Bool() interface
    • A column now can now if any of it's elements is NA and a list of said NA elements ([]bool).

    🔄 Changed in 0.3.0

    • 📇 Renamed cell interface elements to be more idiomatic:
      • ToInteger() is now Int()
      • ToFloat() is now Float()
    • The cell interface has changed. Int() and Float() now return pointers instead of values to prevent future conflicts when returning an error.
    • The cell interface has changed. Checksum() [16]byte added.
    • Using cell.Checksum() for identification of unique elements instead of raw strings.
    • The cell interface has changed, now also requires ToBool() method.
    • String type now does not contain a string, but a pointer to a string.

    🛠 Fixed in 0.3.0

    • 📜 Bool type constructor function Bools now parses bool and []bool elements correctly.
    • 📜 Int type constructor function Ints now parses bool and []bool elements correctly.
    • 📜 Float type constructor function Floats now parses bool and []bool elements correctly.
    • 📜 String type constructor function Strings now parses bool and []bool elements correctly.

  • v0.2.1 Changes

    February 14, 2016

    🛠 Fixed in 0.2.1

    • 🛠 Fixed a bug when the maximum number of characters on a column was not being updated properly when subsetting.

  • v0.2.0 Changes

    February 13, 2016

    ➕ Added in 0.2.0

    • ➕ Added a lot of unit tests

    🔄 Changed in 0.2.0

    • The base types are now df.String, df.Int, and df.Float.
    • Restructured the project in different files.
    • 🔨 Refactored the project so that it will allow columns to be of any type as long as it complies with the necessary interfaces.

  • v0.1.0 Changes

    February 06, 2016

    ➕ Added in 0.1.0

    • Load csv data to DataFrame.
    • 📜 Parse data to four supported types: int, float64, date & string.
    • Row/Column subsetting (Indexing, column names, row numbers, range).
    • Unique/Duplicated row subsetting.
    • DataFrame combinations by rows and columns (cbind/rbind).