README
¶
godf
A simple dataframe handler for golang, inspired by pandas from python. I used @jedib0t's go-pretty to render the table.
It can handle simple data manipulation such as :
- One hot encoding
- Sorting
- Shuffling data
- Filtering
Install
go get -u github.com/kevinmtanadi/godf
Usage
Basic Usage
x := []float64{0.1, 0.2, 0.3, 0.4, 0.5}
y := []float64{1.1, 1.2, 1.3, 1.4, 1.5}
z := []float64{21, 22, 23, 24, 25}
df := godf.DataFrame(map[string]interface{}{
"x": x,
"y": y,
"z": z,
})
df.Show()
┌───┬─────┬─────┬────┐
│ # │ X │ Y │ Z │
├───┼─────┼─────┼────┤
│ 1 │ 0.1 │ 1.1 │ 21 │
│ 2 │ 0.2 │ 1.2 │ 22 │
│ 3 │ 0.3 │ 1.3 │ 23 │
│ 4 │ 0.4 │ 1.4 │ 24 │
│ 5 │ 0.5 │ 1.5 │ 25 │
└───┴─────┴─────┴────┘
Read CSV File
df := godf.ReadCSV("data.csv")
df.Show()
License
MIT
Documentation
¶
Index ¶
- func AutoCast(data interface{}) any
- func Average(d *dataframe)
- func CastArrayFloat64(data interface{}) []float64
- func CastArrayInt(data interface{}) []int
- func CastArrayString(data interface{}) []string
- func CastFloat64(data interface{}) float64
- func CastHeaders(headers []string) []interface{}
- func CastInt(data interface{}) int
- func CastString(data interface{}) string
- func DataFrame(data map[string]interface{}, opts ...DataframeOption) *dataframe
- func GetDatatype(data interface{}) reflect.Kind
- func Median(d *dataframe)
- func ReadCSV(filename string) *dataframe
- func Zero(d *dataframe)
- type DataframeOption
- type Eq
- type Filter
- type GT
- type GTE
- type In
- type LT
- type LTE
- type NotEq
- type Preprocessing
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func CastArrayFloat64 ¶
func CastArrayFloat64(data interface{}) []float64
func CastArrayInt ¶
func CastArrayInt(data interface{}) []int
func CastArrayString ¶
func CastArrayString(data interface{}) []string
func CastFloat64 ¶
func CastFloat64(data interface{}) float64
func CastHeaders ¶
func CastHeaders(headers []string) []interface{}
func CastString ¶
func CastString(data interface{}) string
func DataFrame ¶
func DataFrame(data map[string]interface{}, opts ...DataframeOption) *dataframe
DataFrame initializes and returns a dataframe
This function takes a map[string]interface{} as a variable where the string will be the header name and the interface{} will be the contained data
Returns a pointer to the dataframe
func GetDatatype ¶ added in v0.0.5
Types ¶
type DataframeOption ¶ added in v0.0.6
type DataframeOption struct {
StringLimit int
// contains filtered or unexported fields
}
type Eq ¶ added in v0.0.5
type Eq map[string]interface{}
Eq filter rows where a data in the given column is equal to given value
Example of usage:
df.Where(Eq{"x": 5})
will only get data with x = 5
type GT ¶ added in v0.0.5
type GT map[string]interface{}
GT filter rows where a data in the given column is greater than the given value
Example of usage:
df.Where(GT{"x": 5})
will only get data with x > 5
type GTE ¶ added in v0.0.5
type GTE map[string]interface{}
GTE filter rows where a data in the given column is greater than or equal to the given value
Example of usage:
df.Where(GTE{"x": 5})
will only get data with x >= 5
type In ¶ added in v0.0.5
type In map[string]interface{}
In filter all data which value is in the given slice
Example of usage:
df.Where(In{"x": []int{1, 2, 3, 4}})
will only get data with x = [1, 2, 3, 4]
type LT ¶ added in v0.0.5
type LT map[string]interface{}
LT filter rows where a data in the given column is less than the given value
Example of usage:
df.Where(LT{"x": 5})
will only get data with x < 5
type LTE ¶ added in v0.0.5
type LTE map[string]interface{}
LTE filter rows where a data in the given column is less than or equal to the given value
Example of usage:
df.Where(LTE{"x": 5})
will only get data with x <= 5
type NotEq ¶ added in v0.0.5
type NotEq map[string]interface{}
NotEq filter rows where a data in the given column is not equal to given value
Example of usage:
df.Where(NotEq{"x": 5})
will get all data except the data with x = 5
type Preprocessing ¶ added in v0.0.6
type Preprocessing interface {
Standardize()
Normalize()
OneHotEncode()
}
Source Files