Gota: DataFrames, Series and Data Wrangling for Go
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Gota2 is a more typesafe version of Gota. Gota has limitations, because it's difficult to build a 1:1 implementation of an untyped API in a typed language. This led to bloated, hard to maintain code. Gota2 uses Go 1.18 with type parameters to support arbitrary data types. This causes a big and hard breaking change with no simple upgrade path. Onn the other hand, the new code is simpler and easier to maintain and extend.
This is an implementation of DataFrames, Series and data wrangling methods for the Go programming language. The API is still in flux so use at your own risk.
DataFrame
The term DataFrame typically refers to a tabular dataset that can be viewed as a two dimensional table. Often the columns of this dataset refers to a list of features, while the rows represent a number of measurements. As the data on the real world is not perfect, DataFrame supports non measurements or NaN elements.
Common examples of DataFrames can be found on Excel sheets, CSV files or SQL database tables, but this data can come on a variety of other formats, like a collection of JSON objects or XML files.
The utility of DataFrames resides on the ability to subset them, merge them, summarize the data for individual features or apply functions to entire rows or columns, all while keeping column type integrity.
Series
Series are essentially vectors of elements of the same type with support for missing values. Series are the building blocks for DataFrame columns.
License
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.