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The concept of loops is available in almost all programming languages. Python loops help to iterate over a list, tuple, string, dictionary, and a set. There are two types of loop supported in Python “for” and “while”. The block of code is executed multiple times inside the loop until the condition fails.
The loop control statements break the flow of execution and terminate/skip the iteration as per our need. Python break and continue are used inside the loop to change the flow of the loop from its standard procedure.
A for-loop or while-loop is meant to iterate until the condition given fails. When you use a break or continue statement, the flow of the loop is changed from its normal way.
In this Python tutorial, you will learn:
Python break statementThe break statement takes care of terminating the loop in which it is used. If the break statement is used inside nested loops, the current loop is terminated, and the flow will continue with the code followed that comes after the loop.
The flow chart for the break statement is as follows:
The following are the steps involved in the flowchart.
Step 1)
The loop execution starts.
Step 2)
If the loop condition is true, it will execute step 2, wherein the body of the loop will get executed.
Step 3)
If the loop’s body has a break statement, the loop will exit and go to Step 6.
Step 4)
After the loop condition is executed and done, it will proceed to the next iteration in Step 4.
Step 5)
If the loop condition is false, it will exit the loop and go to Step 6.
Step 6)
End of the loop.
Break statement execution flowWhen the for-loop starts executing, it will check the if-condition. If true, the break statement is executed, and the for–loop will get terminated. If the condition is false, the code inside for-loop will be executed.
When the while loop executes, it will check the if-condition; if it is true, the break statement is executed, and the while –loop will exit. If if the condition is false, the code inside while-loop will get executed.
Example: Break statement inside for-loopThe list my_list = [‘Siya’, ‘Tiya’, ‘Guru’, ‘Daksh’, ‘Riya’, ‘Guru’] is looped using chúng tôi are interested in searching for the name ‘Guru ‘ from the list my_list.
Inside the for-loop, the if-condition compares each item from the list with the name ‘Guru’. If the condition becomes true, it will execute the break statement, and the loop will get terminated.
The working example using break statement is as shown below:
my_list = ['Siya', 'Tiya', 'Guru', 'Daksh', 'Riya', 'Guru'] for i in range(len(my_list)): print(my_list[i]) if my_list[i] == 'Guru': print('Found the name Guru') break print('After break statement') print('Loop is Terminated')Expected Output:
Siya Tiya Guru Found the name Guru Loop is Terminated Example: Break statement inside while-loop my_list = ['Siya', 'Tiya', 'Guru', 'Daksh', 'Riya', 'Guru'] i = 0 while True: print(my_list[i]) if (my_list[i] == 'Guru'): print('Found the name Guru') break print('After break statement') i += 1 print('After while-loop exit')Expected Output:
Siya Tiya Guru Found name Guru After while-loop exit Example: Break Statement inside nested loopsIn the example, we have 2 for-loops. Both for-loops are iterating from a range of 0 to 3. In the second for-loop, we have added a condition where-in if the value of the second for-loop index is 2, it should break.
So because of the break statement, the second for-loop will never iterate for 2 and 3.
for i in range(4): for j in range(4): if j==2: break print("The number is ",i,j);Expected Output:
The number is 0 0 The number is 0 1 The number is 1 0 The number is 1 1 The number is 2 0 The number is 2 1 The number is 3 0 The number is 3 1 Python continue statementThe continue statement skips the code that comes after it, and the control is passed back to the start for the next iteration.
Syntax: continue Continue flow ChartThe following are the steps involved in the flowchart.
Step 1)
The loop execution starts.
Step 2)
The execution of code inside the loop will be done. If there is a continued statement inside the loop, the control will go back to Step 4, i.e., the start of the loop for the next iteration.
Step 3)
The execution of code inside the loop will be done.
Step 4)
If there is a continue statement or the loop execution inside the body is done, it will call the next iteration.
Step 5)
Once the loop execution is complete, the loop will exit and go to step 7.
Step 6)
If the loop condition in step 1 fails, it will exit the loop and go to step 7.
Step 7)
End of the loop.
Continue statement execution flowThe for –loop, loops through my_list array given. Inside the for-loop, the if-condition gets executed. If the condition is true, the continue statement is executed, and the control will pass to the start of the loop for the next iteration.
The flow of the code is as shown below:
When the while loop executes, it will check the if-condition, if it is true, the continue statement is executed. The control will go back to the start of while –loop for the next iteration. If if the condition is false, the code inside while-loop will get executed.
The flow of the code is as shown below:
Example : Continue inside for-loop for i in range(10): if i == 7: continue print("The Number is :" , i)Expected Output:
The Number is : 0 The Number is : 1 The Number is : 2 The Number is : 3 The Number is : 4 The Number is : 5 The Number is : 6 The Number is : 8 The Number is : 9 Example : Continue inside while-loop i = 0 while i <= 10: if i == 7: i += 1 continue print("The Number is :" , i) i += 1Expected Output:
The Number is : 0 The Number is : 1 The Number is : 2 The Number is : 3 The Number is : 4 The Number is : 5 The Number is : 6 The Number is : 8 The Number is : 9 The Number is : 10 Example: Continue inside nested-loopThe below example shows using 2 for-loops. Both for-loops are iterating from a range of 0 to 3. In the second for-loop, there is a condition, wherein if the value of the second for-loop index is 2, it should continue. So because of the continue statement, the second for-loop will skip iteration for 2 and proceed for 3.
for i in range(4): for j in range(4): if j==2: continue print("The number is ",i,j);Expected Output:
The number is 0 0 The number is 0 1 The number is 0 3 The number is 1 0 The number is 1 1 The number is 1 3 The number is 2 0 The number is 2 1 The number is 2 3 The number is 3 0 The number is 3 1 The number is 3 3 Python pass statementPython pass statement is used as a placeholder inside loops, functions, class, if-statement that is meant to be implemented later.
Syntax pass What is pass statement in Python?Python pass is a null statement. When the Python interpreter comes across the across pass statement, it does nothing and is ignored.
When to use the pass statement?Consider you have a function or a class with the body left empty. You plan to write the code in the future. The Python interpreter will throw an error if it comes across an empty body.
The pass statement can be used inside the body of a function or class body. During execution, the interpreter, when it comes across the pass statement, ignores and continues without giving any error.
Example: pass statement inside a functionIn the example, the pass is added inside the function. It will get executed when the function is called as shown below:
def my_func(): print('pass inside function') pass my_func()Expected Output:
pass inside function Example: pass statement inside the classIn the example below, we have created just the empty class that has a print statement followed by a pass statement. The pass statement is an indication that the code inside the class “My_Class” will be implemented in the future.
classMy_Class: print("Inside My_Class") passOutput:
Inside My_Class Example: pass statement inside the loopIn the example below, the string ‘Guru’ is used inside for-loop. The if-condition checks for character ‘r’ and calls the print statement followed by pass.
# Pass statement in for-loop test = "Guru" for i in test: if i == 'r': print('Pass executed') pass print(i)Expected Output:
G u Pass executed r u Example : pass statement inside if-loopIn the example the if loop checks for the value of a and if the condition is true it goes and prints the statement “pass executed” followed by pass.
a=1 if a==1: print('pass executed') passExpected Output:
pass executed When to use a break and continue statement?
A break statement, when used inside the loop, will terminate the loop and exit. If used inside nested loops, it will break out from the current loop.
A continue statement will stop the current execution when used inside a loop, and the control will go back to the start of the loop.
The main difference between break and continue statement is that when break keyword is encountered, it will exit the loop.
In case of continue keyword, the current iteration that is running will be stopped, and it will proceed with the next iteration.
Summary:
Python break and continue are used inside the loop to change the flow of the loop from its normal procedure.
A for-loop or while-loop is meant to iterate until the condition given fails. When you use a break or continue statement, the flow of the loop is changed from its normal way.
A break statement, when used inside the loop, will terminate the loop and exit. If used inside nested loops, it will break out from the current loop.
A continue statement, when used inside a loop, will stop the current execution, and the control will go back to the start of the loop.
The main difference between break and continue statement is that when break keyword is encountered, it will exit the loop.
Python Pass Statement is used as a placeholder inside loops, functions, class, if-statement that is meant to be implemented later.
Python pass is a null statement. When the execution starts and the interpreter comes across the pass statement, it does nothing and is ignored.
You're reading Python Break, Continue, Pass Statements With Examples
4 Different Methods With Examples
What is CONCATENATE in Excel?
CONCATENATE in Excel is an essential function that allows users to combine data from different cells and display the result in a single cell. For instance, if you have a list of addresses with the name, street name, city, etc., in different columns, you could use the CONCATENATE function to combine each section into a complete address.
You can then copy the combined address or use it elsewhere.
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The CONCATENATE in Excel function is helpful for those who work with large volumes of data and want to combine the values of different columns into one. The utility of the function extends from connecting first and last names to linking data sections for generating unique codes.
Key Highlights
The function CONCATENATE in Excel can combine a maximum of 30 values.
This function always gives a text string, even if the source contains all numbers.
To work correctly, we must provide at least one text argument in the formula for the CONCATENATE function.
It gives a #N/A error if we provide an invalid value to an argument.
The function CONCATENATE in Excel combines the source values and displays the result in a new cell. Therefore, it does not alter the source giving users the flexibility to work on new and old values.
Syntax of CONCATENATE in ExcelThe syntax for CONCATENATE function is as follows-
Text 1: It’s a required argument and the first item to join. It can be a text value, cell reference, or number.
Text 2: It’s also a required argument. We can join up to 255 items that are up to 8192 characters.
How to Use CONCATENATE Function in Excel?
You can download this CONCATENATE in Excel Template here – CONCATENATE in Excel Template
1. Using the FormulaSuppose we have a list of Names in Column A and a list of Dates in Column B and want to display the Name & Date together in Column C.
Here’s how we can do it:
Explanation of the formula:
A6: This is the first value we want to combine.
“: To insert a space between the combined values, we enclose it in double quotes.
TEXT(B6, “DD-MM-YYYY” ): The TEXT formula converts the number into a readable format. B6 represents the date, and DD-MM-YYYY is the format to display the same.
Note: Excel will display the output in a non-readable format if we concatenate a date with text without converting it.
2. Using the Function “fx.”Step 1: Create a new column with the heading Product Code.
Step 2: Select the cell where you want to display the combined result. In this case, it is cell E6.
3. Using Ampersand Operator (&)Suppose we have a list of Employee names in Column A and their Email IDs in column B. We want to concatenate these values to create a list of Employee Emails with their Display name using the Ampersand Operator (&).
Put the “=” sign and select the first cell to combine (A6). Enter the & operator and open double quotes. Put a space and open angle brackets. Enclose the second value (B6) between ampersand operators and double quotes. And lastly, end the formula with double quotes. The double quotes indicate that we want the output in text format.
Step 3: Press Enter key to get the combined result
To concatenate the Email ID with the Names of the remaining cells, drag the formula into the other cells.
4. Combine Text String and Cell Value Using CONCATENATE FunctionExplanation of the formula
A6: The cell contains the first value we want to combine.
“: A space enclosed with double quotes to separate the combined values with space.
B6: We want to combine the cell containing the second value.
“MICROSOFT EXCEL”: It is the third value to combine. It is enclosed in double quotes to indicate that we want to display a text value.
Things to Remember
Same Order: The CONCATENATE function combines the values in the same order as in the data set. For example, if a column contains the alphabets in random order, i.e., A, C, D, F, and H, then the formula =CONCATENATE(A, C, D, F, H) will display it as
Manual Cell Reference: If you want to combine the values of a cell range, you cannot use an array (such as B1:B10). You must refer to each cell manually, e.g., =CONCATENATE(B1, B2, B3,..).
CONCAT function: In EXCEL 2023 and later versions of Excel, the CONCAT function in Excel has replaced the CONCATENATE function. However, it is still available to use for compatibility.
Frequently Asked Questions (FAQs)Answer: The shortcut for CONCATENATE uses the ampersand operator (&). To combine values using the (&) operator, follow the steps:
Step 2: Type the formula,
=A6&” “&B6
Note: To separate the values with space, we enclose space with double quotes in the formula.
Answer: Working with numerical data in Excel is relatively easy to manipulate, but combining or manipulating text can be challenging. This is where the CONCATENATE function comes in handy. This function allows users to merge text strings without changing the original values, making it an ideal option for financial reporting or presentations.
Unlike merging cells, the CONCATENATE function does not alter the original values. It also allows for combining different data types, such as text strings, numbers, and dates, which is beneficial for data analysis and presentation.
The CONCATENATE formula is =CONCATENATE(text1, text2, text3,…), where,
text1, text2, text3,… are the values we want to combine. We can combine up to 255 strings and 8192 characters in one formula.
Recommended ArticlesThe above article is a guide to CONCATENATE in Excel using different methods and downloadable templates. To learn more about such useful functions of Excel, you can read the following articles.
Expressions In Sql With Examples
Introduction to SQL Expressions
SQL expressions are the collective formula consisting of values, column names, operators, and functions present in SQL. The expressions in SQL are further classified as Boolean expressions, numeric expressions, and date-time expressions. The expressions are formulas that evaluate a particular value that can be further used according to our necessity. Boolean expressions are used to evaluate a condition that results in either true or false and can be used anywhere but mostly used in the where clause to perform restrictions on column values.
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The numeric expressions are used to evaluate the summarized and cumulative numeric values that are mostly used for reporting purposes. The numeric expressions can be formed by using aggregate functions of SQL such as SUM, COUNT, AVG, etc, and operators like addition, subtraction, multiplication, etc. Date and time-related expressions are used to evaluate and retrieve the current date and time or some manipulated dates and times.
Expressions in SQL with Examples 1. Boolean ExpressionsThe use of Boolean expressions is mainly done in the where clause of the SQL queries which can be either SELECT, INSERT, UPDATE, and DELETE. Note that the conditions and expressions used in the WHERE clause can make the use of AND, OR, NOT, etc operators so that the final value retrieved from the condition will be a Boolean value. This is called a Boolean expression. Let us see the syntax of the usage of Boolean expressions in SELECT query inside the WHERE clause
SELECT column_name1, column_name2, column_nameN FROM name of the table WHERE boolean expression;Let us consider a simple example where we have an existing table named educba_writers_demo that has the contents as retrieved from the following query statement –
SELECT * FROM educba_writers_demo ;The execution of the above query statement will give the following output:
Now, we will apply a boolean condition in where a clause specifies that the value of the rate column should be greater than 700. The condition will return either true or false for each of the records in the table. If it’s true then the record will be added in the final resultset or not. Let us execute the following query and observe the output –
SELECT * FROM educba_writers_demoThe execution of the above query statement will give the following output:
2. Numeric ExpressionsNumeric expressions involve usage of literal values and column values and that are manipulated with the usage of operators like add, subtract, divide and multiply and different functions that are available in SAQL such as aggregate functions containing SUM(), COUNT(), AVG(), MAX(), MIN(), etc to retrieve a value that can be used further. Most of the time, numerical expressions are used in the retrieval list of the SELECT query statement to retrieve the summarized data that is sent to the client mostly for analysis purposes such as reporting and dashboarding. Let us consider simple examples that use numerical expressions. Syntax of using numerical expressions is as shown below:
SELECT Numerical expression FROM name of the table [WHERE restriction];Let us firstly consider a simple example that we used above to explain the working of the AVG() function. We will calculate the average value of SQL numbers using the AVG() function. Let us create one simple table named numbers and store the num column value in it. We will use the following query statement to create our table –
CREATE TABLE numbers (num INT) ;The execution of the above query statement will give the following output:
Now, we will insert the above records in the table. Our query statement will be as follows –
INSERT INTO numbers(num) VALUES (50), (100), (150), (200);Let us now retrieve the records once:
SELECT * FROM numbers ;The execution of the above query statement will give the following output:
Now, we will calculate the average of num column of numbers table using AVG() function using the following query statement –
SELECT AVG(num) FROM numbers ;The execution of the above query statement will give the following output:
Similarly, we can use COUNT(), MAX(), and various other functions and also formulas involving operators. Let us consider the usage of operators along with avg() function in the following example –
SELECT AVG((num * 10) + 1) FROM numbers ;Now, we will calculate the total of num column of numbers table using SUM() function using the following query statement –
SELECT SUM(num) FROM numbers ;The execution of the above query statement will give the following output:
3. Date Time ExpressionsThe expressions that are related to date and time help in fetching the information such as current date, time, and timestamp. This is used for informative purposes and to store temporal values in the table to record the time and date during which the data was being inserted and also for assigning a default value to the fields with datatype like date, time, DateTime, and timestamp. Let us firstly use a simple query statement that retrieves the current timestamp –
SELECT CURRENT_TIMESTAMP;The execution of the above query statement will give the following output:
Further, we can use the different functions that are available in SQL to handle temporal values such as GETDATE() to retrieve the current date and so on.
ConclusionSQL expressions can be used to evaluate a value that results from the combination of functions, operators, literal values, and column values. The returned value of the expression is further used either for decision making as summarized data or informational purposes. The expressions are classified into three types in SQL that are boolean expressions, numerical expressions, and date time-related expressions respectively.
Recommended ArticlesWe hope that this EDUCBA information on “SQL Expressions” was beneficial to you. You can view EDUCBA’s recommended articles for more information.
Learn How It Works With Javafx With Examples?
Introduction to JavaFX FXML
JavaFX FXML is defined as a GUI format with XML-based language launched by Oracle Corporation that enables to compose of the GUIs’ layout or the application of GUIs. The Primary purpose of FXML is to define a user interface. Placing XML mark-up here is to describe a component of UI in the hierarchy structure. A controller takes managing interactions by defining components and link them with them. FXML file has an extension .fxml and it is loaded by FXML Loader by JavaFX,
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JavaFX FXML is created as below
How does JavaFX FXML work?JavaFX is used to create the Desktop Application, which allows to code the User-interface by making the application easier. In FXML XML elements are a class, script, property, static. A typical JavaFX FXML works like below:
FXML document has a user interface of an FXML application.
FXML Controller handles all the event handling process.
Next, FXML Loader parses the given FXML document and creates a graph. Simultaneously the Main Class initiates the execution of a Program.
For example, when a user accessing a website, he/she checks with the updated information of their needs; therefore, we need to recompile a code. In such a case FXML controller plays a role.
In this article, I have used NetBeans IDE, which supports JavaFX. This IDE typically provides a visual Layout for designing a UI. Deploying the first JavaFx application is needed. To take up the process:
Java file: This takes up a java code for an application (Main Application)
.fxml file: Here FXML source file is created to define a user interface part.
Below is the NetBeans IDE screenshots that support JavaFX. Here we could see three application files in the name JAVAFXApplication1
The following image shows the application that executes with the button event handlers. FXML specifies two event handlers, namely script and Controller event handlers. FXML Layout file could be created for more parts; this keeps the controller and views independently. And the scene Builder doesn’t need XML directly to work with. The stage is the main container, and the Scene is the UI elements here.
Adding Scripts
mainButton.setText(“press me!”); }
Vbox here is a component that makes a form in a vertical order (child elements). We can insert text, labels, and buttons to create a form Layout. Namespaces are added to the root element.
FXML containing stackPane
Using Border Panel
<HBox prefHeight="110.0" prefWidth="210.0"Adding Component inside FXML file
public class load extends VBox implements Initializable { @FXML private void handleAction(ActionEvent eve) { } @Override public void initialize(URL u, ResourceBundle re) { } }FXML annotation is given as
public class layout @FXML private TextField txt; @FXML private Button btn; @FXML private VBox dataContainer; @FXML private TableView tab; ExamplesIn this section, we will show you how to use chúng tôi in Net Beans IDE.
The respective Java class is given as
FXMLsample.java
package fxmlsample; import javafx.application.Application; import javafx.fxml.FXMLLoader; import javafx.scene.Parent; import javafx.scene.Scene; import javafx.stage.Stage; public class FXMLsample extends Application { @Override public void start(Stage st) throws Exception { Parent root = FXMLLoader.load(getClass().getResource("FXMLdoc.fxml")); Scene sc = new Scene(root, 200, 215); st.setTitle("FXML Welcome"); st.setScene(sc); st.show(); } public static void main(String[] args) { launch(args); } }FXMLdoc.fxml
<Text text="Welcome Page" GridPane.columnIndex="0" GridPane.rowIndex="0" <GridPane fx:controller="FXMLdoc.FXML_ctrl"
Next is the controller class with the response to the FXML file for the UI application
FXML_ctrl.java
package FXMLsample; import javafx.event.ActionEvent; import javafx.fxml.FXML; import javafx.scene.text.Text; import javafx.scene.control.Label; public class FXML_ctrl { @FXML private Text actiontarget; @FXML protected void handleSubmitButtonAction(ActionEvent event) { actiontarget.setText("Submit the button"); } }Explanation
The above code section shows to run an FXML application by loading a loader. Similarly, we could see how the components get to each other.
Output:
Features
They have a large set of built-in GUI components like checkboxes; buttons also come with a built-in charts library to create charts.
JavaFX FXML is an XML mark-up language and has a rich set of APIs. It’s a powerful tool and keeps the code easier. Used to develop rich Internet applications using java Files.
JavaFX has CSS styling and gives a declarative layout through FXML.
FXML uses namespaces with the prefix ‘fx’ in which all elements and attributes are assigned. Also, well simple to debug and modify.
ConclusionThis is all about JavaFX FXML. In this article, we had discussed their definition and how it works with JavaFX, along with the examples. Generally, the basics of JavaFX demonstration would not work wells. To build a larger application, we need a system FXML. Therefore, we have explained how it could be used in the development of JavaFX implementation.
Recommended ArticlesThis is a guide to JavaFX FXML. Here we discuss the definition and how it works with JavaFX, along with the examples and features. You may also have a look at the following articles to learn more –
Machine Learning With Python: Logistic Regression
This article was published as a part of the Data Science Blogathon
What Is Logistic Regression?This article assumes that you possess basic knowledge and understanding of Machine Learning Concepts, such as Target Vector, Features Matrix, and related terms.
Source: DZone
Logistic Regression in its base form (by default) is a Binary Classifier. This means that the target vector may only take the form of one of two values. In the Logistic Regression Algorithm formula, we have a Linear Model, e.g., β0 + β1x, that is integrated into a Logistic Function (also known as a Sigmoid Function). The Binary Classifier formula that we have at the end is as follows:
Where:
Β0 and β1 are the parameters that are to be learned.
e represents Euler’s Number.
Main Aim of Logistic Regression Formula.The Logistic Regression formula aims to limit or constrain the Linear and/or Sigmoid output between a value of 0 and 1. The main reason is for interpretability purposes, i.e., we can read the value as a simple Probability; Meaning that if the value is greater than 0.5 class one would be predicted, otherwise, class 0 is predicted.
Source: GraphPad
Python Implementation.We shall now look at the implementation of the Python Programming Language. For this exercise, we will be using the Ionosphere dataset which is available for download from the UCI Machine Learning Repository.
# We begin by importing the necessary packages # to be used for the Machine Learning problem import pandas as pd import numpy as np from sklearn.linear_model import LogisticRegression from sklearn.preprocessing import StandardScaler # We read the data into our system using Pandas' # 'read_csv' method. This transforms the .csv file # into a Pandas DataFrame object. dataframe = pd.read_csv('ionosphere.data', header=None) # We configure the display settings of the # Pandas DataFrame. pd.set_option('display.max_rows', 10000000000) pd.set_option('display.max_columns', 10000000000) pd.set_option('display.width', 95) # We view the shape of the dataframe. Specifically # the number of rows and columns present. print('This DataFrame Has %d Rows and %d Columns'%(dataframe.shape))Output to the above code would be as follows (the shape of the dataframe):
# We print the first five rows of our dataframe. print(dataframe.head())Output to the above code will be seen as follows (below output is truncated):
# We isolate the features matrix from the DataFrame. features_matrix = dataframe.iloc[:, 0:34] # We isolate the target vector from the DataFrame. target_vector = dataframe.iloc[:, -1] # We check the shape of the features matrix, and target vector. print('The Features Matrix Has %d Rows And %d Column(s)'%(features_matrix.shape)) print('The Target Matrix Has %d Rows And %d Column(s)'%(np.array(target_vector).reshape(-1, 1).shape))Output for the shape of our Features Matrix and Target Vector would be as below:
# We use scikit-learn's StandardScaler in order to # preprocess the features matrix data. This will # ensure that all values being inputted are on the same # scale for the algorithm. features_matrix_standardized = StandardScaler().fit_transform(features_matrix) # We create an instance of the LogisticRegression Algorithm # We utilize the default values for the parameters and # hyperparameters. algorithm = LogisticRegression(penalty='l2', dual=False, tol=1e-4, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=None, random_state=None, solver='lbfgs', max_iter=100, multi_class='auto', verbose=0, warm_start=False, n_jobs=None, l1_ratio=None) # We utilize the 'fit' method in order to conduct the # training process on our features matrix and target vector. Logistic_Regression_Model = algorithm.fit(features_matrix_standardized, target_vector) # We create an observation with values, in order # to test the predictive power of our model. observation = [[1, 0, 0.99539, -0.05889, 0.8524299999999999, 0.02306, 0.8339799999999999, -0.37708, 1.0, 0.0376, 0.8524299999999999, -0.17755, 0.59755, -0.44945, 0.60536, -0.38223, 0.8435600000000001, -0.38542, 0.58212, -0.32192, 0.56971, -0.29674, 0.36946, -0.47357, 0.56811, -0.51171, 0.41078000000000003, -0.46168000000000003, 0.21266, -0.3409, 0.42267, -0.54487, 0.18641, -0.453]] # We store the predicted class value in a variable # called 'predictions'. predictions = Logistic_Regression_Model.predict(observation) # We print the model's predicted class for the observation. print('The Model Predicted The Observation To Belong To Class %s'%(predictions))Output to the above block of code should be as follows:
# We view the specific classes the model was trained to predict. print('The Algorithm Was Trained To Predict One Of The Two Classes: %s'%(algorithm.classes_))Output to the above code block will be seen as follows:
print("""The Model Says The Probability Of The Observation We Passed Belonging To Class ['b'] Is %s"""%(algorithm.predict_proba(observation)[0][0])) print() print("""The Model Says The Probability Of The Observation We Passed Belonging To Class ['g'] Is %s"""%(algorithm.predict_proba(observation)[0][1]))The expected output would be as follows:
Conclusion.This concludes my article. We now understand the Logic behind this Supervised Machine Learning Algorithm and know how to implement it in a Binary Classification Problem.
Thank you for your time.
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How Distinct Command Works With Examples
Introduction to MongoDB Distinct
MongoDB distinct is used to find distinct values from a single collection and retrieved results of the query in an array, MongoDB distinct is used to retrieve distinct values from the collection. Distinct in MongoDB is very important and useful to retrieve distinct data from a single collection. Distinct is different from MongoDB find the method, distinct will returns the array of all the distinct values from the collection. This will return only distinct data from the collection, if in one collection thousands of documents and we need only those documents which were distinct each other same time we have used distinct in MongoDB.
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SyntaxBelow is the syntax of distinct in MongoDB.
collection_name.distinct (field, query)
collection_name.distinct (field, query, options)
Parameter
Collection name: Collection name is defined as retrieved documents from the collection by using a distinct method. We can retrieve distinct values from the collection by using distinct methods.
Distinct: This will return only distinct data from the collection. This is very important and useful to retrieve distinct data from a single collection. This is used to retrieve distinct values from the collection.
Field: Field has specified that return distinct value from the field we have specified with distinct methods. The field is an essential and useful parameter in a distinct method.
Options: This is an optional parameter in MongoDB distinct command. This is an additional option used in the distinct command. It is available only if the document specifies the options.
Query: Query distinct method defines the document from which we have to retrieve the collection’s distinct value. The query is a handy and important parameter in a distinct method.
How Distinct Command works in MongoDB?Below is the working of distinct command:
The distinct method in MongoDB uses an index on the field while doing a distinct operation on collection.
This will return only distinct data from the collection, if in one collection thousands of documents and we need only those documents which were distinct each other same time we have used distinct in MongoDB.
When we have used or specifies collation in a distinct method, we need to specify a mandatory locale to define the field with collation in a distinct method.
If the field’s values were an array, then distinct methods consider each element of the field as a separate value.
If suppose array contains a value as [1, 2, 1, [1], 2], then distinct methods consider it as [1, 2, [1]] as a result.
Below example states will consider the array field as each element as separate values.
Code #1
use stud_array
Output:
Code #2
db.stud_array.insert({"stud_id" : 1, "semester" : 5, "grades" : [ 90, 90, [92], 92 ] })
Output:
Code #3
db.stud_array.distinct("grades")
Output:
Examples to Implement MongoDB DistinctBelow is the example of a distinct method in MongoDB.
We have taken an example of student_datatable to describe an example of a distinct method is as follows. Below is the data description of the student_data table are as follows.
Example #1use student_data
Example #2db.student_data.find()
1. Return distinct values from fieldThe below example shows that return distinct value from the field. We have used the semester field from the student_data table to describe distinct values from the field.
Code:
db.student_data.distinct ("semester")
Output:
Explanation: In the above example, we have retrieved distinct values from the semester field. The result of values from the customer field is 3, 4, and 5.
2. Return distinct values from fieldThe below example shows that return distinct value from the array field. We have used the grade array field from the student_data table to describe distinct values from the array field.
Code:
db.student_data.distinct ("grades")
Explanation: In the above example, we have retrieved distinct values from the grades field. The above example states that distinct methods in MongoDB consider the array field as each element of the field as a separate value. In the above example output of 92 and 95 occur double because distinct considered it a separate element.
3. Query with a distinct methodThe below example shows that query with the distinct value from the field. We have used semester and grades field from the student_data table to describe queries with distinct fields.
Code:
db.student_data.distinct ("semester",{ grades: 90 })
Output:
4. Using collation with a distinct methodThe below example shows that collation with the distinct method in MongoDB. We have used the semester field from the student_data table to describe collation with the method.
Code:
db.student_data.distinct( "semester", {}, { collation: { locale: "fr", strength: 1 } } )
Output:
Recommended ArticlesThis is a guide to MongoDB Distinct. Here we discuss syntax, parameter, the working of distinct command with examples to implement. You can also go through our other related articles to learn more –
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