Data Wrangling in C# QuickStart Sample
Illustrates how to perform basic data wrangling or data munging operations on data frames using classes in the Extreme.DataAnalysis namespace in C#.
View this sample in: Visual Basic F#
using System;
using System.Collections.Generic;
using Extreme.DataAnalysis;
using Extreme.Mathematics;
using Index = Extreme.DataAnalysis.Index;
namespace Extreme.Numerics.QuickStart.CSharp {
/// <summary>
/// Illustrates how to perform basic data wrangling operations
/// on data frames.
/// </summary>
class DataWrangling {
static void Main(string[] args) {
// The license is verified at runtime. We're using
// a demo license here. For more information, see
// https://numerics.net/trial-key
Extreme.License.Verify("Demo license");
//
// Joining and reshaping
//
// When data comes from different sources,
// the Append method lets you join the two
// data frames:
var frame = DataFrame.FromColumns(new Dictionary<string, object>() {
{ "A", new string[] { "A0", "A1", "A2", "A3"} },
{ "B", new string[] { "B0", "B1", "B2", "B3"} },
{ "C", new string[] { "C0", "C1", "C2", "C3"} },
{ "D", new string[] { "D0", "D1", "D2", "D3" } } },
Index.Default(0, 3));
var df2 = DataFrame.FromColumns(new Dictionary<string, object>() {
{ "A", new string[] { "A4", "A5", "A6", "A7"} },
{ "B", new string[] { "B4", "B5", "B6", "B7"} },
{ "C", new string[] { "C4", "C5", "C6", "C7"} },
{ "D", new string[] { "D4", "D5", "D6", "D7" } } },
Index.Default(4, 7));
var df12 = frame.Append(df2);
// It is possible to join more than 2 data frames:
var df3 = DataFrame.FromColumns(new Dictionary<string, object>() {
{ "A", new string[] { "A8", "A9", "A10", "A11"} },
{ "B", new string[] { "B8", "B9", "B10", "B11"} },
{ "C", new string[] { "C8", "C9", "C10", "C11"} },
{ "D", new string[] { "D8", "D9", "D10", "D11" } } },
Index.Default(8, 11));
var df123 = DataFrame.Append(frame, df2, df3);
// When the columns don't match, you can specify
// a join operation which determines which columns
// to keep in the result. If a column is missing
// in a data frame and present in the result,
// missing values are inserted.
frame = DataFrame.FromColumns(new Dictionary<string, object>() {
{ "A", new string[] { "A0", "A1", "A2", "A3"} },
{ "B", new string[] { "B0", "B1", "B2", "B3"} },
{ "C", new string[] { "C0", "C1", "C2", "C3"} } },
Index.Default(0, 3));
df2 = DataFrame.FromColumns(new Dictionary<string, object>() {
{ "A", new string[] { "A4", "A5", "A6", "A7"} },
{ "B", new string[] { "B4", "B5", "B6", "B7"} },
{ "D", new string[] { "D4", "D5", "D6", "D7" } } },
Index.Default(4, 7));
var df12outer = frame.Append(df2, JoinType.Outer);
var df12Inner = frame.Append(df2, JoinType.Inner);
// Left column join is equivalent to using the left column index:
var df12Left = frame.Append(df2, JoinType.Left);
var df12Left2 = frame.Append(df2, frame.ColumnIndex);
// Again, these are equivalent:
var df12Right = frame.Append(df2, JoinType.Right);
var df12Right2 = frame.Append(df2, df2.ColumnIndex);
// One to one joins match rows on their keys:
var dates1 = Index.CreateDateRange(new DateTime(2015, 11, 11), 5, Recurrence.Daily);
var df4 = Vector.CreateRandom(5).ToDataFrame(dates1, "values1");
var dates2 = Index.CreateDateRange(dates1[2], 5, Recurrence.Daily);
var df5 = Vector.CreateRandom(5).ToDataFrame(dates2, "values2");
var df6 = DataFrame.Join(df4, JoinType.Outer, df5);
Console.WriteLine(df6);
// One to many joins match one data frame's index to another's
// column.
// Create a list of presidents:
var numbers = Index.Create(new[] { 44, 43, 42, 41, 40 });
var names = Vector.Create("Barack Obama", "George W. Bush", "Bill Clinton",
"George H.W. Bush", "Ronald Reagan");
var homeStates = Vector.Create("IL", "TX", "AR", "TX", "CA");
var presidents = DataFrame.FromColumns(new Dictionary<string, object>() {
{ "Name", names }, { "Home state", homeStates } }, numbers);
// And a list of states indexed by their abbreviations:
var abbreviations = Index.Create(new[] { "AR", "CA", "GA", "MI", "IL", "TX" });
var stateNames = Vector.Create("Arkansas", "California", "Georgia",
"Michigan", "Illinois", "Texas");
var states = DataFrame.FromColumns(new Dictionary<string, object>() {
{ "Full name", stateNames} }, abbreviations);
// Now get the full names of states in the list:
var presidentsWithState = DataFrame.Join(presidents, JoinType.Left, states, key: "Home state");
Console.WriteLine(presidentsWithState);
// When the indexes are sorted, it is possible
// to do an inexact join to the nearest value.
// This is useful for time series where one series
// if offset by a few hours relative to the other:
var dates7 = Index.CreateDateRange(new DateTime(2015, 11, 11), 5, Recurrence.Daily);
var df7 = Vector.CreateRandom(5).ToDataFrame(dates7, "values1");
var dates8 = Index.CreateDateRange(dates7[0].AddHours(3), 5, Recurrence.Daily);
var df8 = Vector.CreateRandom(5).ToDataFrame(dates8, "values2");
var df9 = df7.JoinOnNearest(df8, Direction.Backward);
Console.WriteLine(df9);
//
// Sorting and filtering
//
// Data frames can be sorted by their index or by
// a column. The sort methods always return a new data frame.
dates2 = Index.CreateDateRange(new DateTime(2015, 11, 11), 15, Recurrence.Daily);
var frame2 = DataFrame.FromColumns(new Dictionary<string, object>() {
{ "values1", Vector.CreateRandom(dates2.Length) },
{ "values2", Vector.CreateRandom(dates2.Length) },
{ "values3", Vector.CreateRandom(dates2.Length) } }, dates2);
var frame3 = frame2.SortByIndex(SortOrder.Descending);
var frame4 = frame2.SortBy("values1", SortOrder.Ascending);
Console.Write("Press Enter key to exit...");
Console.ReadLine();
}
}
}