Omar  Amin

Omar Amin

1611206280

Assign QLabel Keyboard Shortcut to Set Focus on a Widget with SetBuddy Method | PyQt5 Tutorial

In this PyQt5 tutorial, I will be covering how to assign a QLabel keyboard shortcut to a paired widget with QLabel’s setBuddy method.

When the user presses the shortcut key indicated by this label, the keyboard focus is transferred to the label’s buddy widget.

The buddy mechanism is only available for QLabels that contain text in which one character is prefixed with an ampersand, ‘&’.

🔔 Subscribe: https://www.youtube.com/channel/UCvVZ19DRSLIC2-RUOeWx8ug

Source Code:


import sys
from PyQt5.QtWidgets import QApplication, QWidget, QLabel, QLineEdit, QPushButton, QFormLayout

# Use setBuddy method to quickly assign shortcut key to set focus on the buddy widget

class MyApp(QWidget):
    def __init__(self):
        super().__init__()
        self.setWindowTitle('setBuddy tutorial')
        layout = QFormLayout()
        self.setLayout(layout)

        labelUsername = QLabel('&Username: ')
        editUsername = QLineEdit('')
        layout.addRow(labelUsername, editUsername)

        labelPassword = QLabel('&Password: ')
        editPassword = QLineEdit()
        layout.addRow(labelPassword, editPassword)

        btn = QPushButton('&Enter')
        btn.setMinimumWidth(400)
        btn.clicked.connect(lambda: print('Hello World'))
        layout.addRow(btn, QLabel())

        labelUsername.setBuddy(editUsername)
        labelPassword.setBuddy(editPassword)


if __name__ == '__main__':
    app = QApplication(sys.argv)
    app.setStyleSheet('''
        QWidget {
            font-size: 35px;
        }
    ''')
    
    myApp = MyApp()
    myApp.show()

    try:
        sys.exit(app.exec_())
    except SystemExit:
        print('Closing Window...')


#python #pyqt5

What is GEEK

Buddha Community

Assign QLabel Keyboard Shortcut to Set Focus on a Widget with SetBuddy Method | PyQt5 Tutorial
Omar  Amin

Omar Amin

1611206280

Assign QLabel Keyboard Shortcut to Set Focus on a Widget with SetBuddy Method | PyQt5 Tutorial

In this PyQt5 tutorial, I will be covering how to assign a QLabel keyboard shortcut to a paired widget with QLabel’s setBuddy method.

When the user presses the shortcut key indicated by this label, the keyboard focus is transferred to the label’s buddy widget.

The buddy mechanism is only available for QLabels that contain text in which one character is prefixed with an ampersand, ‘&’.

🔔 Subscribe: https://www.youtube.com/channel/UCvVZ19DRSLIC2-RUOeWx8ug

Source Code:


import sys
from PyQt5.QtWidgets import QApplication, QWidget, QLabel, QLineEdit, QPushButton, QFormLayout

# Use setBuddy method to quickly assign shortcut key to set focus on the buddy widget

class MyApp(QWidget):
    def __init__(self):
        super().__init__()
        self.setWindowTitle('setBuddy tutorial')
        layout = QFormLayout()
        self.setLayout(layout)

        labelUsername = QLabel('&Username: ')
        editUsername = QLineEdit('')
        layout.addRow(labelUsername, editUsername)

        labelPassword = QLabel('&Password: ')
        editPassword = QLineEdit()
        layout.addRow(labelPassword, editPassword)

        btn = QPushButton('&Enter')
        btn.setMinimumWidth(400)
        btn.clicked.connect(lambda: print('Hello World'))
        layout.addRow(btn, QLabel())

        labelUsername.setBuddy(editUsername)
        labelPassword.setBuddy(editPassword)


if __name__ == '__main__':
    app = QApplication(sys.argv)
    app.setStyleSheet('''
        QWidget {
            font-size: 35px;
        }
    ''')
    
    myApp = MyApp()
    myApp.show()

    try:
        sys.exit(app.exec_())
    except SystemExit:
        print('Closing Window...')


#python #pyqt5

Adele Hansley

Adele Hansley

1625577097

Tips For Writing A Biology Assignment

Writing a biology assignment could be a tedious task; with the amount of information that is presented before a student, it becomes pretty complicated to process all that information and then simplify it and present it in the form of an assignment. To ease the burden off students’ shoulders, some online writing services provide academic writings online where one can seek biology assignment help.

Structure Of An Assignment

Research should always begin with narrowing down possible topics. After deciding upon the topic, a student should put on thorough research on that topic. One can also seek help from a biology assignment writer; these professional academic writers have helped students worldwide finish their assignments well before the deadline
Let your interest and curiosity carry you to that topic. After contracting a case doing bulks of research, and studying all that you can. After selection of the subject comes the part of studying and writing all that you can about that topic. All the material for your assignment would come from studying and writing about that topic.

After you have exhausted your research into that topic, the next task that follows is choosing material relevant enough to go into your assignment among all the bundles of knowledge you have with you. Simplifying the complicated text of your research to fit into your assignment would be the next task on your table.

Assignment Format

Start your paper with an introduction, an introduction to the topic you are about to explore, and a brief overview of it. Follow it by two to three paragraphs of your research into that paper. There is also an option of a biology assignment helper who can help you get that desired grade.

Suffering From Writer’s Block?

Sometimes it so happens that words stop flowing in your mind if so happens then don’t be afraid, what you seek is online biology assignment help, there are various assignment writing services to help you in your endeavor. Writers on these online portals are professional writers who have expertise on a particular subject. If you seek someone to do your assignment, then that is just a click away.

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Max Willor

Max Willor

1596170547

Is My Assignment Help Legit?

Yes, the assignment help is quite legitimate. If you are struggling to complete the assignment then you can take the support of My Assignment Help Sydney. We are discussing certain features that will help to get good grades in the assignment.

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Willie  Beier

Willie Beier

1596728880

Tutorial: Getting Started with R and RStudio

In this tutorial we’ll learn how to begin programming with R using RStudio. We’ll install R, and RStudio RStudio, an extremely popular development environment for R. We’ll learn the key RStudio features in order to start programming in R on our own.

If you already know how to use RStudio and want to learn some tips, tricks, and shortcuts, check out this Dataquest blog post.

Table of Contents

#data science tutorials #beginner #r tutorial #r tutorials #rstats #tutorial #tutorials

Tutorial: Loading and Cleaning Data with R and the tidyverse

1. Characteristics of Clean Data and Messy Data

What exactly is clean data? Clean data is accurate, complete, and in a format that is ready to analyze. Characteristics of clean data include data that are:

  • Free of duplicate rows/values
  • Error-free (e.g. free of misspellings)
  • Relevant (e.g. free of special characters)
  • The appropriate data type for analysis
  • Free of outliers (or only contain outliers have been identified/understood), and
  • Follows a “tidy data” structure

Common symptoms of messy data include data that contain:

  • Special characters (e.g. commas in numeric values)
  • Numeric values stored as text/character data types
  • Duplicate rows
  • Misspellings
  • Inaccuracies
  • White space
  • Missing data
  • Zeros instead of null values

2. Motivation

In this blog post, we will work with five property-sales datasets that are publicly available on the New York City Department of Finance Rolling Sales Data website. We encourage you to download the datasets and follow along! Each file contains one year of real estate sales data for one of New York City’s five boroughs. We will work with the following Microsoft Excel files:

  • rollingsales_bronx.xls
  • rollingsales_brooklyn.xls
  • rollingsales_manhattan.xls
  • rollingsales_queens.xls
  • rollingsales_statenisland.xls

As we work through this blog post, imagine that you are helping a friend launch their home-inspection business in New York City. You offer to help them by analyzing the data to better understand the real-estate market. But you realize that before you can analyze the data in R, you will need to diagnose and clean it first. And before you can diagnose the data, you will need to load it into R!

3. Load Data into R with readxl

Benefits of using tidyverse tools are often evident in the data-loading process. In many cases, the tidyverse package readxl will clean some data for you as Microsoft Excel data is loaded into R. If you are working with CSV data, the tidyverse readr package function read_csv() is the function to use (we’ll cover that later).

Let’s look at an example. Here’s how the Excel file for the Brooklyn borough looks:

The Brooklyn Excel file

Now let’s load the Brooklyn dataset into R from an Excel file. We’ll use the readxlpackage. We specify the function argument skip = 4 because the row that we want to use as the header (i.e. column names) is actually row 5. We can ignore the first four rows entirely and load the data into R beginning at row 5. Here’s the code:

library(readxl) # Load Excel files
brooklyn <- read_excel("rollingsales_brooklyn.xls", skip = 4)

Note we saved this dataset with the variable name brooklyn for future use.

4. View the Data with tidyr::glimpse()

The tidyverse offers a user-friendly way to view this data with the glimpse() function that is part of the tibble package. To use this package, we will need to load it for use in our current session. But rather than loading this package alone, we can load many of the tidyverse packages at one time. If you do not have the tidyverse collection of packages, install it on your machine using the following command in your R or R Studio session:

install.packages("tidyverse")

Once the package is installed, load it to memory:

library(tidyverse)

Now that tidyverse is loaded into memory, take a “glimpse” of the Brooklyn dataset:

glimpse(brooklyn)
## Observations: 20,185
## Variables: 21
## $ BOROUGH <chr> "3", "3", "3", "3", "3", "3", "…
## $ NEIGHBORHOOD <chr> "BATH BEACH", "BATH BEACH", "BA…
## $ `BUILDING CLASS CATEGORY` <chr> "01 ONE FAMILY DWELLINGS", "01 …
## $ `TAX CLASS AT PRESENT` <chr> "1", "1", "1", "1", "1", "1", "…
## $ BLOCK <dbl> 6359, 6360, 6364, 6367, 6371, 6…
## $ LOT <dbl> 70, 48, 74, 24, 19, 32, 65, 20,…
## $ `EASE-MENT` <lgl> NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `BUILDING CLASS AT PRESENT` <chr> "S1", "A5", "A5", "A9", "A9", "…
## $ ADDRESS <chr> "8684 15TH AVENUE", "14 BAY 10T…
## $ `APARTMENT NUMBER` <chr> NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `ZIP CODE` <dbl> 11228, 11228, 11214, 11214, 112…
## $ `RESIDENTIAL UNITS` <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1…
## $ `COMMERCIAL UNITS` <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ `TOTAL UNITS` <dbl> 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1…
## $ `LAND SQUARE FEET` <dbl> 1933, 2513, 2492, 1571, 2320, 3…
## $ `GROSS SQUARE FEET` <dbl> 4080, 1428, 972, 1456, 1566, 22…
## $ `YEAR BUILT` <dbl> 1930, 1930, 1950, 1935, 1930, 1…
## $ `TAX CLASS AT TIME OF SALE` <chr> "1", "1", "1", "1", "1", "1", "…
## $ `BUILDING CLASS AT TIME OF SALE` <chr> "S1", "A5", "A5", "A9", "A9", "…
## $ `SALE PRICE` <dbl> 1300000, 849000, 0, 830000, 0, …
## $ `SALE DATE` <dttm> 2020-04-28, 2020-03-18, 2019-0…

The glimpse() function provides a user-friendly way to view the column names and data types for all columns, or variables, in the data frame. With this function, we are also able to view the first few observations in the data frame. This data frame has 20,185 observations, or property sales records. And there are 21 variables, or columns.

#data science tutorials #beginner #r #r tutorial #r tutorials #rstats #tidyverse #tutorial #tutorials