Amari Yost

Amari Yost

1608047400

Java Tutorial For Beginners | Java If Else Statement | Java Conditional Statements

This Video on “Java If-Else Statement” will help you learn the fundamentals of the if-else conditional statement in java. To make things better, the video will include practical examples.

#java #programming #developer

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Java Tutorial For Beginners | Java If Else Statement | Java Conditional Statements
Tyrique  Littel

Tyrique Littel

1600135200

How to Install OpenJDK 11 on CentOS 8

What is OpenJDK?

OpenJDk or Open Java Development Kit is a free, open-source framework of the Java Platform, Standard Edition (or Java SE). It contains the virtual machine, the Java Class Library, and the Java compiler. The difference between the Oracle OpenJDK and Oracle JDK is that OpenJDK is a source code reference point for the open-source model. Simultaneously, the Oracle JDK is a continuation or advanced model of the OpenJDK, which is not open source and requires a license to use.

In this article, we will be installing OpenJDK on Centos 8.

#tutorials #alternatives #centos #centos 8 #configuration #dnf #frameworks #java #java development kit #java ee #java environment variables #java framework #java jdk #java jre #java platform #java sdk #java se #jdk #jre #open java development kit #open source #openjdk #openjdk 11 #openjdk 8 #openjdk runtime environment

Sival Alethea

Sival Alethea

1624312800

Learn Java 8 - Full Tutorial for Beginners. DO NOT MISS!!!

Learn Java 8 and object oriented programming with this complete Java course for beginners.
⭐️Contents ⭐️

⌨️ (0:00:00) 1 - Basic Java keywords explained
⌨️ (0:21:59) 2 - Basic Java keywords explained - Coding Session
⌨️ (0:35:45) 3 - Basic Java keywords explained - Debriefing
⌨️ (0:43:41) 4 - Packages, import statements, instance members, default constructor
⌨️ (0:59:01) 5 - Access and non-access modifiers
⌨️ (1:11:59) 6 - Tools: IntelliJ Idea, Junit, Maven
⌨️ (1:22:53) 7 - If/else statements and booleans
⌨️ (1:42:20) 8 - Loops: for, while and do while loop
⌨️ (1:56:57) 9 - For each loop and arrays
⌨️ (2:14:21) 10 - Arrays and enums
⌨️ (2:41:37) 11 - Enums and switch statement
⌨️ (3:07:21) 12 - Switch statement cont.
⌨️ (3:20:39) 13 - Logging using slf4j and logback
⌨️ (3:51:19) 14 - Public static void main
⌨️ (4:11:35) 15 - Checked and Unchecked Exceptions
⌨️ (5:05:36) 16 - Interfaces
⌨️ (5:46:54) 17 - Inheritance
⌨️ (6:20:20) 18 - Java Object finalize() method
⌨️ (6:36:57) 19 - Object clone method. [No lesson 20]
⌨️ (7:16:04) 21 - Number ranges, autoboxing, and more
⌨️ (7:53:00) 22 - HashCode and Equals
⌨️ (8:38:16) 23 - Java Collections
⌨️ (9:01:12) 24 - ArrayList
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=grEKMHGYyns&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=9
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Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#java #java 8 #learn java 8 #learn java 8 - full tutorial for beginners #beginners #java course for beginners.

Samanta  Moore

Samanta Moore

1621096440

Functions for Strings in Java

In this tutorial, you will learn how to make better use of built-in functions for Strings in Java to program more quickly, effectively, and aesthetically.

What Is a String?

Firstly, of course, we have to initialize our string. What is a string used for?

  • You want to look at your string as a line, not as a mass of symbols.
  • If you have a long text, you want to work with the words, not the letters.
  • If you have lots of information, you need functions that solve questions as quickly as possible.

#java #tutorial #java strings #java tutorial for beginners #java string #string tutorial

Alec  Nikolaus

Alec Nikolaus

1596330300

Add a Column in a Pandas DataFrame Based on an If-Else Condition

When we’re doing data analysis with Python, we might sometimes want to add a column to a pandas DataFrame based on the values in other columns of the DataFrame.

Although this sounds straightforward, it can get a bit complicated if we try to do it using an if-else conditional. Thankfully, there’s a simple, great way to do this using numpy!

To learn how to use it, let’s look at a specific data analysis question. We’ve got a dataset of more than 4,000 Dataquest tweets. Do tweets with attached images get more likes and retweets? Let’s do some analysis to find out!

We’ll start by importing pandas and numpy, and loading up our dataset to see what it looks like. (If you’re not already familiar with using pandas and numpy for data analysis, check out our interactive numpy and pandas course).

import pandas as pd
import numpy as np

df = pd.read_csv('dataquest_tweets_csv.csv')
df.head()

adding a column to a dataframe in pandas step 1: baseline dataframe

We can see that our dataset contains a bit of information about each tweet, including:

  • date — the date the tweet was posted
  • time — the time of day the tweet was posted
  • tweet — the actual text of the tweet
  • mentions — any other twitter users mentioned in the tweet
  • photos — the url of any images included in the tweet
  • replies_count — the number of replies on the tweet
  • retweets_count — the number of retweets of the tweet
  • likes_count — the number of likes on the tweet

We can also see that the photos data is formatted a bit oddly.

Adding a Pandas Column with a True/False Condition Using np.where()

For our analysis, we just want to see whether tweets with images get more interactions, so we don’t actually need the image URLs. Let’s try to create a new column called hasimage that will contain Boolean values — True if the tweet included an image and False if it did not.

To accomplish this, we’ll use numpy’s built-in [where()](https://numpy.org/doc/stable/reference/generated/numpy.where.html) function. This function takes three arguments in sequence: the condition we’re testing for, the value to assign to our new column if that condition is true, and the value to assign if it is false. It looks like this:

np.where(condition, value if condition is true, value if condition is false)

In our data, we can see that tweets without images always have the value [] in the photos column. We can use information and np.where() to create our new column, hasimage, like so:

df['hasimage'] = np.where(df['photos']!= '[]', True, False)
df.head()

new column based on if-else has been added to our pandas dataframe

Above, we can see that our new column has been appended to our data set, and it has correctly marked tweets that included images as True and others as False.

#data science tutorials #add column #beginner #conditions #dataframe #if else #pandas #python #tutorial #tutorials #twitter

Ida  Nader

Ida Nader

1599099600

How to Use If-Else Statements and Loops in R – Dataquest

When we’re programming in R (or any other language, for that matter), we often want to control when and how particular parts of our code are executed. We can do that using control structures like if-else statements, for loops, and while loops.

Control structures are blocks of code that determine how other sections of code are executed based on specified parameters. You can think of these as a bit like the instructions a parent might give a child before leaving the house:

“If I’m not home by 8pm, make yourself dinner.”

Control structures set a condition and tell R what to do when that condition is met or not met. And unlike some kids, R will always do what we tell it to! You can learn more about control structures in the R documentation if you would like.

In this tutorial, we assume you’re familiar with basic data structures, and arithmetic operations in R.

Not quite there yet? Check out our Introductory R Programming course that’s part of our Data Analyst in R path. It’s free to start learning, there are no prerequisites, and there’s nothing to install — you can start learning in your browser right now.

install.packages(“Dataquest”)

Start learning R today with our Introduction to R course — no credit card required!

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(This tutorial is based on our intermediate R programming course, so check that out as well! It’s interactive and will allow you to write and run code right in your browser.)

Comparison Operators in R

In order to use control structures, we need to create statements that will turn out to be either TRUE or FALSE. In the kids example above, the statement “It’s 8pm. Are my parents home yet?” yields TRUE (“Yes”) or FALSE (“No”). In R, the most fundamental way to evaluate something as TRUE or FALSE is through comparison operators.

Below are six essential comparison operators for working with control structures in R:

  • == means equality. The statement x == a framed as a question means “Does the value of x equal the value of a?”
  • != means “not equal”. The statement x == b means “Does the value of x not equal the value of b?”
  • < means “less than”. The statement x < c means “Is the value of x less than the value of c?”
  • <= means “less than or equal”. The statement x <= d means “Is the value of x less or equal to the value of d?”
  • > means “greater than”. The statement x > e means “Is the value of x greater than the value of e?”
  • >= means “greater than or equal”. The statement x >= f means “Is the value of xgreater than or equal to the value of f?”

#data science tutorials #beginner #for loop #for loops #if #if else #learn r #r #r tutorial #rstats #tutorial #tutorials #while loop #while loops