DataFrame Module

The DataFrame module provides a data structure for storing and manipulating tabular data in Go. It offers functionalities similar to popular DataFrame libraries in other programming languages, allowing you to work with structured data efficiently.

Features

• Create a DataFrame with column names
• Add columns to the DataFrame
• Modify existing columns in the DataFrame
• Change the order of columns in the DataFrame
• Count non-nil values in a column
• Sum values in a numeric column
• Calculate the mean (average) of values in a numeric column
• Filter the DataFrame based on conditions
• Sort the DataFrame based on one or more columns
• Group the DataFrame by one or more columns and perform aggregation functions
• Join multiple DataFrames based on common columns
• Handle missing values, duplicates, and perform data type conversion
• Perform statistical analysis such as variance, standard deviation, correlation, and covariance
• Serialize the DataFrame to JSON or CSV format
• Access and manipulate data in the DataFrame

Installation

To use the DataFrame module in your Go project, you need to include it as a dependency:

go get github.com/your-username/your-module/dataframe

Usage

package main

import (
	"fmt"
	"github.com/your-username/your-module/dataframe"
)

func main() {
	// Create a new DataFrame
	df, err := dataframe.NewDataFrame([]string{"Name", "Age", "City", "Salary"})
	if err != nil {
		fmt.Println("Error creating DataFrame:", err)
		return
	}

	// Add columns to the DataFrame
	names := []interface{}{"John", "Alice", "Bob", "Jane"}
	df.AddColumn("Name", names)

	ages := []interface{}{25, 30, 35, 28}
	df.AddColumn("Age", ages)

	cities := []interface{}{"New York", "London", "Tokyo", "Paris"}
	df.AddColumn("City", cities)

	salaries := []interface{}{50000, 60000, 75000, 55000}
	df.AddColumn("Salary", salaries)

	// Perform operations on the DataFrame

	// Print header and data of the DataFrame
	fmt.Println("DataFrame Header:")
	df.PrintHeader()
	fmt.Println()

	fmt.Println("DataFrame Data:")
	df.PrintData()
	fmt.Println()

	// Count the number of ages
	count, err := df.Count("Age")
	if err != nil {
		fmt.Println("Error counting values:", err)
		return
	}
	fmt.Println("Count of Ages:", count)
	fmt.Println()

	// Sum the salaries
	sum, err := df.Sum("Salary")
	if err != nil {
		fmt.Println("Error summing values:", err)
		return
	}
	fmt.Println("Sum of Salaries:", sum)
	fmt.Println()

	// Calculate the mean age
	mean, err := df.Mean("Age")
	if err != nil {
		fmt.Println("Error calculating mean:", err)
		return
	}
	fmt.Println("Mean Age:", mean)
	fmt.Println()

	// Filter the DataFrame
	filteredDF, err := df.Filter(func(row int) bool {
		return df.columns["Age"][row].(int) > 28
	})
	if err != nil {
		fmt.Println("Error filtering DataFrame:", err)
		return
	}

	fmt.Println("Filtered DataFrame:")
	filteredDF.PrintHeader()
	filteredDF.PrintData()
	fmt.Println()

	// Sort the DataFrame
	err = df.Sort([]string{"Age", "Salary"}, true)
	if err != nil {
		fmt.Println("Error sorting DataFrame:", err)
		return
	}

	fmt.Println("Sorted DataFrame:")
	df.PrintHeader()
	df.PrintData()
	fmt.Println()

	// Group and aggregate the DataFrame
	groupedDF, err := df.GroupBy([]string{"City"})
	if err != nil {
		fmt.Println("Error grouping DataFrame:", err)
		return
	}

	fmt.Println("Grouped DataFrame:")
	groupedDF.PrintHeader()
	groupedDF.PrintData()
	fmt.Println()

	// Join DataFrames
	joinDF1, err := dataframe.NewDataFrame([]string{"Name", "Age", "City"})
	if err != nil {
		fmt.Println("Error creating join DataFrame 1:", err)
		return
	}

	joinNames := []interface{}{"John", "Alice"}
	joinDF1.AddColumn("Name", joinNames)

	joinAges := []interface{}{25, 30}
	joinDF1.AddColumn("Age", joinAges)

	joinCities := []interface{}{"New York", "London"}
	joinDF1.AddColumn("City", joinCities)

	joinDF2, err := dataframe.NewDataFrame([]string{"City", "Population"})
	if err != nil {
		fmt.Println("Error creating join DataFrame 2:", err)
		return
	}

	joinCities2 := []interface{}{"New York", "London"}
	joinDF2.AddColumn("City", joinCities2)

	joinPopulations := []interface{}{8500000, 9000000}
	joinDF2.AddColumn("Population", joinPopulations)

	joinedDF, err := dataframe.Join([]*dataframe.DataFrame{joinDF1, joinDF2}, []string{"City"})
	if err != nil {
		fmt.Println("Error joining DataFrames:", err)
		return
	}

	fmt.Println("Joined DataFrame:")
	joinedDF.PrintHeader()
	joinedDF.PrintData()
	fmt.Println()

	// Serialize DataFrame to JSON
	jsonData, err := df.SerializeToJSON()
	if err != nil {
		fmt.Println("Error serializing DataFrame to JSON:", err)
		return
	}

	fmt.Println("Serialized DataFrame (JSON):")
	fmt.Println(jsonData)
	fmt.Println()

	// Serialize DataFrame to CSV
	csvData, err := df.SerializeToCSV()
	if err != nil {
		fmt.Println("Error serializing DataFrame to CSV:", err)
		return
	}

	fmt.Println("Serialized DataFrame (CSV):")
	fmt.Println(csvData)
	fmt.Println()
}

Contributing

Contributions to the DataFrame module are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.

License

This DataFrame module is open-source and distributed under the MIT License. See the LICENSE file for more information.