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Select multiple columns in a LINQ query

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LINQ is useful for querying as we can query different various data sources such as XML documents,SQL databases, CSV Files, JSON documents etc. , using C# or any other .NET language.

LINQ provides two different ways to write queries:

  • Declarative query syntax which is SQL like syntax.It’s important to understand that the declarative syntax is also converted to extension method syntax at compile time.
  • Query operators  which are defined as extension methods in the System.Linq namespace. Examples of these are Where,Select and OrderBy.

We can select values from a data source such as a c# list using Select operation in LINQ.Select operation also allows us to select multiple columns in a Linq query.

Select multiple columns in a LINQ query

Selecting List items using  LINQ where clause

Suppose we have a List of items and we want to search for some values in the list. We can easily do that using the LINQ select operator.
For example, if we have a list of Employee classes declared as:


 var employeesLst = new List<Employee> { new Employee { Name = "emp1", Id = "1",Dept="Accounts" },
 new Employee { Name = "emp2", Id = "2",Dept="Finance" },
 new Employee { Name = "emp3", Id = "3",Dept="Finance" },
};

then we can filter the employees based on the Id, using the declarative syntax as:


 var selectedLst=from item in employeesLst
 where item.Id=2
 select item.Name;

The equivalent method chaining syntax , using LINQ extension methods is:

employeesLst.Where(item=>item.Id=2).Select(item=>item.Name);

But if now we want to select multiple Dept and Name fields then we can not use this since this will be invalid syntax in LINQ:


var selectedLst=from item in employeesLst
select item.Id,item.Name;

Remember Select is a projection operation.Projection operations are used to transform an object into a new object containing properties which are required.

Select multiple columns in a LINQ query

Since in this scenario we require properties which are not contained by any existing object, we can use the anonymous type using the following syntax:


 var selectedLst=from item in employeesLst
 where item.Id=2
 select new { item.Id, item.Name };

Anonymous type is used to define a type that contains just read-only properties, using object initializer syntax. It is a convenient way to define a type you don’t need to reuse in multiple places. Since we don’t need to use the properties defined by the anonymous type outside our LINQ query, so we use the anonymous type here. But anonymous type can not contain any other type of members such as methods or constructors.

Select multiple columns using extension methods and lambdas

We can write the above query using extension methods and lambdas as:


 employeesLst.Where(x.Id > 5)
 .Select(x=>new {
  item.Id, item.Name
  });

To order the values by a specific column you can use the OrderBy method and pass the column you want to order upon as a lambda:

employeesLst.Where(x.Id >5)
.Select(x=>new {
  item.Id, item.Name
  }).OrderBy(x => x.Id);

 

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Basics of ML.NET

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In traditional applications developer designs and implement functionality for a specific requirement.The application which provides this functionality is supposed to give same result with the same set of input values and this is defined by how the application is implemented.In contrast in machine learning the out of application can vary with the same set of input values.This is because in Machine Learning ,application can learn and correct itself based on the accuracy of the outcome.

As the application learns from experience over time so it is called Machine Learning application.We use Machine learning for developing applications where we have the inputs and outputs but don’t have algorithm to give you expected output.Machine learning application identifies a function f(x) which helps generate output “y” from input “x“.This function is called model in machine learning.

The predictions or outcomes provided by Machine Learning application are normally unpredictable using conventional applications.

ML.NET is used for creating and training the Model and using the Model for making predictions.Azure Cognitive services uses prebuilt Models unlike ML.NET which is used for creating custom Models.

there are different types of problems which could be solved by machine learning and there are different categories of Machine Learning for solving those problems:

  • Supervised learning Input consists of both the input values and the expected outcomes for those input values.
  • Unsupervised learning Input consists of only input values and not the desired outcomes.

Classification and Regression are types of Supervised Machine learning.

  • classification algorithm is used in classifying the data into different groups or labels e.g A,B.
  • regression  algorithm is used in finding values in a range of values such as the price of an item.

Some of the examples of unsupervised learning are:

  • Clustering algorithm is used in finding groups in the data with similar data in each group.

ML.NET is a framework for building custom Machine learning models.It provides set of APIs for building models.Azure cognitive services provides pre trained machine learning models
ml.net while ml.net allows building custom models.

Though Python has been the preferred choice  for developing Machine learning applications,ML.NET is used for developing Machine learning applications for the .NET platform.So if you are a .NET developer and have experience with languages such as C# then ML.NET is your best option.

We can have labelled data representing input and output but don’t have the application to generate output from input.

Datasets defines inputs and outputs to consumed in the application. Datasets have labels or classifier for each item in the Dataset. Machine learning application accepts input Dataset and identifies the function f(x) that relates the input to the output.

Libraries such as Tensorflow are complex to use while ML.NET API’s are relatively developer friendly.Also components in ML.NET are extensible .In fact functionalities such as loading data,transform data and deployment are easy to implement and are extensible.

For developing Machine Learning applications using ML.NET you first need to install .NET SDK. This  can be installed from the following URL:

.NET SDK

Once you have .NET SDK installed you are ready to create ML.NET application.You can use either Visual Studio or Visual Studio Code for developing Machine Learning Applications.To implement Machine Learning application you can create any .NET application such as a console application.You just need to add a Nuget for ML.NET to this application.Following the URL for ML.NET Nuget Microsoft.ML.

In machine learning application Model is responsible for the prediction of outcome and returns Labelled data as output.Features are characteristic of input which are used for the creating Model.If we are creating a Model related to Geography of a country we will need appropriate features to represent a Country.Such features could be Plains,Deserts,Mountains,Islands.

After we create a Model based on features appropriate to the problem we evaluate the Model to verify the correctness of Model.

Following are the general steps used in machine learning:

  1. Load data
  2. Transform data before generating model
  3. Generate Model.This is the most important component of any Machine learning application.
  4. Train model
  5. Evaluate model

ML.NET also follows the same approach and following steps are used when developing application using ML.NET

  1. create data(training and evaluation data) in any valid format such as CSVformat. Learning
  2. pipelines are used in ML.NET for creating model
  3. create class corresponding to this data
  4. train model
  5. Verify model     In ML.NET there is an evaluate() method for this.

Following are the main components used in ML.NET application:

  • IDataReader Uses for getting data.TextLoader is an example.
  • Data is rerpresented using IDataView
  • Transformer takes data and returns data after transforming it.
  • Estimator This is the main component in ML.NET.It produces model.It is represented using

We can use ML.NET for classification and regression tasks.We need to train and generate model (saved as zip file).To do this we call the predictionModel method and pass the main class and class and get the model.

 

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LINQ Group By clause in C#

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Group clause is used in LINQ for grouping collection into groups based on a specific key.LINQ Group By clause in C# returns a sequence of  IGrouping<TKey,TElement> objects.

For example if you have a collection of int values then you can group the values based on the integer value.This is a simple example of group by clause.Following list consists of 6 items but there are 4 groups:

List<int> nums = new List<int> { 1, 1, 2, 3, 4, 4 };

var numColl = from num in nums
group num by num;

foreach(var num in numColl)
{
Console.WriteLine("num={0} key={1}", num.Key, num);
}

If you run the above query then you will get result consisting of 4 groups:

LINQ group by clause in C#

In another example we have declared Employee class which consists of FirstName and joiningDate properties.

class Employee
{
public string FirstName { get; set; }
public DateTime joiningDate { get; set; }
}

We are then creating a list of Employee objects:

static List<Employee> employees = new List<Employee>
{
new Employee {FirstName = "Marc",joiningDate= DateTime.Now.AddHours(1) },
new Employee {FirstName = "John", joiningDate = DateTime.Now.AddHours(1) },
new Employee {FirstName = "Robin",joiningDate= DateTime.Now.AddHours(2) },
new Employee {FirstName = "Mike", joiningDate= DateTime.Now.AddDays(2) }
};

Finally we are grouping the employee objects  based on the department Employee works:

static void Main(string[] args)
{

var emps = from employee in employees
group employee by employee.Department into empGroup
select new
{
key = empGroup.Key,
items = empGroup
};

foreach (var item in emps)
{
Console.WriteLine("group ");
Console.WriteLine("Department={0} Total Employeees in department={1}", item.key, item.items.Count());
foreach (var groupItems in item.items)
{
Console.WriteLine("Employee {0}", groupItems.FirstName);
}

}
Console.ReadLine();

Group items based on multiple keys

In the above examples we have grouped items for single keys only.We can group items based on multiple keys.For example we can group the employee objects based on department and joining date as:

var emps = from employee in employees
group employee by new
{
employee.Department,
joinDate=employee.joiningDate > employee.joiningDate.AddYears(-1)
} into empGroup
select empGroup;
foreach (var item in emps)
{
Console.WriteLine("group consists of following items {0}", item.Count());
foreach (var groupItems in item)
{

Console.WriteLine("Employee {0}", groupItems.FirstName);
}

}

 

 

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Filed Under: C#

ArraySegment in C#

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ArraySegment is a generic collection implemented as a structure. ArraySegment is used to create a collection based on an array.We can use ArraySegment in C# if we are using the framework version 4.7.2 .

So if you have defined an array as:

int[] nums = { 1, 2, 3, 4, 5 };

then you need to define arraysegment based on the above array as below.please note that we are passing integer type as arraysegment type parameter.This is because arraysegment is based on integer array.

ArraySegment<int> arrObj = new ArraySegment<int>(nums);

So the following is not valid:

ArraySegment<string> arrObj = new ArraySegment<string>(nums);

In this example we are defining an arraysegment for the entire array.If we want we can also define arraysegment for a portion of the array instead of entire array.
For example the following will print the items 3 and 4 as we starting from index 2 and including 2 elements.

int[] nums = { 1, 2, 3, 4, 5 };
ArraySegment<int> arrObj = new ArraySegment<int>(nums,2,2);
foreach(var item in arrObj)
{
Console.WriteLine("item ={0}", item);
}

So if you need perform different operations on different parts of the array then you can use ArraySegment struct.

Array property

If you require to access the original array wrapped by the array segment then you can use the Array property.For example if you want to refer to the array referred to by the arrObj then you can use the Array property as:

arrObj.Array

Offset property

If you need to find the difference between the first element in the array segment from the initial element in the original array then you can use the Offset property.For example if you want to find the Offset of the arrObj then you use:

arrObj.Offset

 

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Filed Under: C#

GroupJoin operator in C# using LINQ

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GroupJoin operator works on two sequences or collections.It joins the sequences based on a key and returns group for the given key.

Following is the signature of groupjoin operator:

GroupJoin<Outer,Inner, Key, Result>(
this IEnumerable<Outer> outer,
IEnumerable<Inner> inner,
Func<TOuter, Key> outerKeySelector,
Func<TInner, Key> innerKeySelector,
Func<TOuter, Enumerable<TInner>, TResult> resultSelector
)

Following are the type parameters of the GroupJoin() method:

  1. outer 1st collection
  2. inner 2nd collection
  3. outerKeySelector key of 1st collection
  4. innerKeySelector key of 2nd collection
  5. resultSelector result.The result of the GroupJoin method is of type IEnumerable<TResult>

The method is not executed until the result enumeration is iterated in a foreach collection.

In the following example we have 2 classes Manager and Employees.Each manager can have multiple employees reporting to him.We are grouping the Manager and his reportees based on the ManagerId key.

Class Manager

public class Manager
{
public int ManagerId { get; set; }
public string Name { get; set; }
}

Class Employees

public class Employees
{
public int ManagerId { get; set; }
public int Id { get; set; }
public string Name { get; set; }
}

Using outerJoin to group the 2 collections based on Manager Id:

class Program
{
static void Main(string[] args)
{
IList<Manager> managerlist = new List<Manager>() {
new Manager() {ManagerId=1,Name="Mnager1" },
new Manager() {ManagerId=2,Name="Mnager2" }
};

IList<Employees> employeelist = new List<Employees>() {
new Employees(){ Id = 1, Name="Standard 1",ManagerId=1},
new Employees(){ Id = 2, Name="Standard 2",ManagerId=1}
};

var groupJoin = managerlist.GroupJoin(employeelist, //inner sequence
manager => manager.ManagerId, //outerKey
employee => employee.ManagerId, //innerKey
(manager, employeeGroup) => new // result
{
employees = employeeGroup,
manager = manager.Name
});

foreach (var item in groupJoin)
{
Console.WriteLine(item.manager);

foreach (var emp in item.employees)
Console.WriteLine(emp.Name);
}

Console.ReadLine();

}
}

 

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