1607741942

Extract Text From an Image Using Python | OCR For an Image to Text Conversion

Python-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and “read” the text embedded in images.
Python-tesseract is a wrapper for Google’s Tesseract-OCR Engine. It is also useful as a stand-alone invocation script to tesseract, as it can read all image types supported by the Pillow and Leptonica imaging libraries, including jpeg, png, gif, BMP, tiff, and others. Additionally, if used as a script, Python-tesseract will print the recognized text instead of writing it to a file.

Setting Things Up
When it comes to setting up Python libraries to use, it’s usually a one-step process. With PyTesseract, however, we will need to do two things:

Install the Python Library
Install the Tesseract application

In this video, We are going to show how to extract an image by using python. This program will extract text from the selected image.

Source Code: https://drive.google.com/drive/folders/1pEQl797o3ta2yTxgarDIpp5Auu3xhGx0

Subscribe:https://www.youtube.com/channel/UCNs6a3HlrbYw7dSUEXk9W3A

#python

What is GEEK

Buddha Community

Extract Text From an Image Using Python | OCR For an Image to Text Conversion

Queenie Davis

1653123600

EasyMDE: Simple, Beautiful and Embeddable JavaScript Markdown Editor

EasyMDE - Markdown Editor

This repository is a fork of SimpleMDE, made by Sparksuite. Go to the dedicated section for more information.

A drop-in JavaScript text area replacement for writing beautiful and understandable Markdown. EasyMDE allows users who may be less experienced with Markdown to use familiar toolbar buttons and shortcuts.

In addition, the syntax is rendered while editing to clearly show the expected result. Headings are larger, emphasized words are italicized, links are underlined, etc.

EasyMDE also features both built-in auto saving and spell checking. The editor is entirely customizable, from theming to toolbar buttons and javascript hooks.

Try the demo

Preview

Quick access

EasyMDE - Markdown Editor

Install EasyMDE

Via npm:

npm install easymde

Via the UNPKG CDN:

<link rel="stylesheet" href="https://unpkg.com/easymde/dist/easymde.min.css">
<script src="https://unpkg.com/easymde/dist/easymde.min.js"></script>

Or jsDelivr:

<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/easymde/dist/easymde.min.css">
<script src="https://cdn.jsdelivr.net/npm/easymde/dist/easymde.min.js"></script>

How to use

Loading the editor

After installing and/or importing the module, you can load EasyMDE onto the first textarea element on the web page:

<textarea></textarea>
<script>
const easyMDE = new EasyMDE();
</script>

Alternatively you can select a specific textarea, via JavaScript:

<textarea id="my-text-area"></textarea>
<script>
const easyMDE = new EasyMDE({element: document.getElementById('my-text-area')});
</script>

Editor functions

Use easyMDE.value() to get the content of the editor:

<script>
easyMDE.value();
</script>

Use easyMDE.value(val) to set the content of the editor:

<script>
easyMDE.value('New input for **EasyMDE**');
</script>

Configuration

Options list

autoDownloadFontAwesome: If set to true, force downloads Font Awesome (used for icons). If set to false, prevents downloading. Defaults to undefined, which will intelligently check whether Font Awesome has already been included, then download accordingly.
autofocus: If set to true, focuses the editor automatically. Defaults to false.
autosave: Saves the text that's being written and will load it back in the future. It will forget the text when the form it's contained in is submitted.
- enabled: If set to true, saves the text automatically. Defaults to false.
- delay: Delay between saves, in milliseconds. Defaults to 10000 (10 seconds).
- submit_delay: Delay before assuming that submit of the form failed and saving the text, in milliseconds. Defaults to autosave.delay or 10000 (10 seconds).
- uniqueId: You must set a unique string identifier so that EasyMDE can autosave. Something that separates this from other instances of EasyMDE elsewhere on your website.
- timeFormat: Set DateTimeFormat. More information see DateTimeFormat instances. Default locale: en-US, format: hour:minute.
- text: Set text for autosave.
autoRefresh: Useful, when initializing the editor in a hidden DOM node. If set to { delay: 300 }, it will check every 300 ms if the editor is visible and if positive, call CodeMirror's refresh().
blockStyles: Customize how certain buttons that style blocks of text behave.
- bold: Can be set to ** or __. Defaults to **.
- code: Can be set to ``` or ~~~. Defaults to ```.
- italic: Can be set to * or _. Defaults to *.
unorderedListStyle: can be *, - or +. Defaults to *.
scrollbarStyle: Chooses a scrollbar implementation. The default is "native", showing native scrollbars. The core library also provides the "null" style, which completely hides the scrollbars. Addons can implement additional scrollbar models.
element: The DOM element for the textarea element to use. Defaults to the first textarea element on the page.
forceSync: If set to true, force text changes made in EasyMDE to be immediately stored in original text area. Defaults to false.
hideIcons: An array of icon names to hide. Can be used to hide specific icons shown by default without completely customizing the toolbar.
indentWithTabs: If set to false, indent using spaces instead of tabs. Defaults to true.
initialValue: If set, will customize the initial value of the editor.
previewImagesInEditor: - EasyMDE will show preview of images, false by default, preview for images will appear only for images on separate lines.
imagesPreviewHandler: - A custom function for handling the preview of images. Takes the parsed string between the parantheses of the image markdown ![]( ) as argument and returns a string that serves as the src attribute of the <img> tag in the preview. Enables dynamic previewing of images in the frontend without having to upload them to a server, allows copy-pasting of images to the editor with preview.
insertTexts: Customize how certain buttons that insert text behave. Takes an array with two elements. The first element will be the text inserted before the cursor or highlight, and the second element will be inserted after. For example, this is the default link value: ["[", "](http://)"].
- horizontalRule
- image
- link
- table
lineNumbers: If set to true, enables line numbers in the editor.
lineWrapping: If set to false, disable line wrapping. Defaults to true.
minHeight: Sets the minimum height for the composition area, before it starts auto-growing. Should be a string containing a valid CSS value like "500px". Defaults to "300px".
maxHeight: Sets fixed height for the composition area. minHeight option will be ignored. Should be a string containing a valid CSS value like "500px". Defaults to undefined.
onToggleFullScreen: A function that gets called when the editor's full screen mode is toggled. The function will be passed a boolean as parameter, true when the editor is currently going into full screen mode, or false.
parsingConfig: Adjust settings for parsing the Markdown during editing (not previewing).
- allowAtxHeaderWithoutSpace: If set to true, will render headers without a space after the #. Defaults to false.
- strikethrough: If set to false, will not process GFM strikethrough syntax. Defaults to true.
- underscoresBreakWords: If set to true, let underscores be a delimiter for separating words. Defaults to false.
overlayMode: Pass a custom codemirror overlay mode to parse and style the Markdown during editing.
- mode: A codemirror mode object.
- combine: If set to false, will replace CSS classes returned by the default Markdown mode. Otherwise the classes returned by the custom mode will be combined with the classes returned by the default mode. Defaults to true.
placeholder: If set, displays a custom placeholder message.
previewClass: A string or array of strings that will be applied to the preview screen when activated. Defaults to "editor-preview".
previewRender: Custom function for parsing the plaintext Markdown and returning HTML. Used when user previews.
promptURLs: If set to true, a JS alert window appears asking for the link or image URL. Defaults to false.
promptTexts: Customize the text used to prompt for URLs.
- image: The text to use when prompting for an image's URL. Defaults to URL of the image:.
- link: The text to use when prompting for a link's URL. Defaults to URL for the link:.
uploadImage: If set to true, enables the image upload functionality, which can be triggered by drag and drop, copy-paste and through the browse-file window (opened when the user click on the upload-image icon). Defaults to false.
imageMaxSize: Maximum image size in bytes, checked before upload (note: never trust client, always check the image size at server-side). Defaults to 1024 * 1024 * 2 (2 MB).
imageAccept: A comma-separated list of mime-types used to check image type before upload (note: never trust client, always check file types at server-side). Defaults to image/png, image/jpeg.
imageUploadFunction: A custom function for handling the image upload. Using this function will render the options imageMaxSize, imageAccept, imageUploadEndpoint and imageCSRFToken ineffective.
- The function gets a file and onSuccess and onError callback functions as parameters. onSuccess(imageUrl: string) and onError(errorMessage: string)
imageUploadEndpoint: The endpoint where the images data will be sent, via an asynchronous POST request. The server is supposed to save this image, and return a JSON response.
- if the request was successfully processed (HTTP 200 OK): {"data": {"filePath": "<filePath>"}} where filePath is the path of the image (absolute if imagePathAbsolute is set to true, relative if otherwise);
- otherwise: {"error": "<errorCode>"}, where errorCode can be noFileGiven (HTTP 400 Bad Request), typeNotAllowed (HTTP 415 Unsupported Media Type), fileTooLarge (HTTP 413 Payload Too Large) or importError (see errorMessages below). If errorCode is not one of the errorMessages, it is alerted unchanged to the user. This allows for server-side error messages. No default value.
imagePathAbsolute: If set to true, will treat imageUrl from imageUploadFunction and filePath returned from imageUploadEndpoint as an absolute rather than relative path, i.e. not prepend window.location.origin to it.
imageCSRFToken: CSRF token to include with AJAX call to upload image. For various instances like Django, Spring and Laravel.
imageCSRFName: CSRF token filed name to include with AJAX call to upload image, applied when imageCSRFToken has value, defaults to csrfmiddlewaretoken.
imageCSRFHeader: If set to true, passing CSRF token via header. Defaults to false, which pass CSRF through request body.
imageTexts: Texts displayed to the user (mainly on the status bar) for the import image feature, where #image_name#, #image_size# and #image_max_size# will replaced by their respective values, that can be used for customization or internationalization:
- sbInit: Status message displayed initially if uploadImage is set to true. Defaults to Attach files by drag and dropping or pasting from clipboard..
- sbOnDragEnter: Status message displayed when the user drags a file to the text area. Defaults to Drop image to upload it..
- sbOnDrop: Status message displayed when the user drops a file in the text area. Defaults to Uploading images #images_names#.
- sbProgress: Status message displayed to show uploading progress. Defaults to Uploading #file_name#: #progress#%.
- sbOnUploaded: Status message displayed when the image has been uploaded. Defaults to Uploaded #image_name#.
- sizeUnits: A comma-separated list of units used to display messages with human-readable file sizes. Defaults to B, KB, MB (example: 218 KB). You can use B,KB,MB instead if you prefer without whitespaces (218KB).
errorMessages: Errors displayed to the user, using the errorCallback option, where #image_name#, #image_size# and #image_max_size# will replaced by their respective values, that can be used for customization or internationalization:
- noFileGiven: The server did not receive any file from the user. Defaults to You must select a file..
- typeNotAllowed: The user send a file type which doesn't match the imageAccept list, or the server returned this error code. Defaults to This image type is not allowed..
- fileTooLarge: The size of the image being imported is bigger than the imageMaxSize, or if the server returned this error code. Defaults to Image #image_name# is too big (#image_size#).\nMaximum file size is #image_max_size#..
- importError: An unexpected error occurred when uploading the image. Defaults to Something went wrong when uploading the image #image_name#..
errorCallback: A callback function used to define how to display an error message. Defaults to (errorMessage) => alert(errorMessage).
renderingConfig: Adjust settings for parsing the Markdown during previewing (not editing).
- codeSyntaxHighlighting: If set to true, will highlight using highlight.js. Defaults to false. To use this feature you must include highlight.js on your page or pass in using the hljs option. For example, include the script and the CSS files like:
  <script src="https://cdn.jsdelivr.net/highlight.js/latest/highlight.min.js"></script>
  <link rel="stylesheet" href="https://cdn.jsdelivr.net/highlight.js/latest/styles/github.min.css">
- hljs: An injectible instance of highlight.js. If you don't want to rely on the global namespace (window.hljs), you can provide an instance here. Defaults to undefined.
- markedOptions: Set the internal Markdown renderer's options. Other renderingConfig options will take precedence.
- singleLineBreaks: If set to false, disable parsing GitHub Flavored Markdown (GFM) single line breaks. Defaults to true.
- sanitizerFunction: Custom function for sanitizing the HTML output of Markdown renderer.
shortcuts: Keyboard shortcuts associated with this instance. Defaults to the array of shortcuts.
showIcons: An array of icon names to show. Can be used to show specific icons hidden by default without completely customizing the toolbar.
spellChecker: If set to false, disable the spell checker. Defaults to true. Optionally pass a CodeMirrorSpellChecker-compliant function.
inputStyle: textarea or contenteditable. Defaults to textarea for desktop and contenteditable for mobile. contenteditable option is necessary to enable nativeSpellcheck.
nativeSpellcheck: If set to false, disable native spell checker. Defaults to true.
sideBySideFullscreen: If set to false, allows side-by-side editing without going into fullscreen. Defaults to true.
status: If set to false, hide the status bar. Defaults to the array of built-in status bar items.
- Optionally, you can set an array of status bar items to include, and in what order. You can even define your own custom status bar items.
styleSelectedText: If set to false, remove the CodeMirror-selectedtext class from selected lines. Defaults to true.
syncSideBySidePreviewScroll: If set to false, disable syncing scroll in side by side mode. Defaults to true.
tabSize: If set, customize the tab size. Defaults to 2.
theme: Override the theme. Defaults to easymde.
toolbar: If set to false, hide the toolbar. Defaults to the array of icons.
toolbarTips: If set to false, disable toolbar button tips. Defaults to true.
direction: rtl or ltr. Changes text direction to support right-to-left languages. Defaults to ltr.

Options example

Most options demonstrate the non-default behavior:

const editor = new EasyMDE({
    autofocus: true,
    autosave: {
        enabled: true,
        uniqueId: "MyUniqueID",
        delay: 1000,
        submit_delay: 5000,
        timeFormat: {
            locale: 'en-US',
            format: {
                year: 'numeric',
                month: 'long',
                day: '2-digit',
                hour: '2-digit',
                minute: '2-digit',
            },
        },
        text: "Autosaved: "
    },
    blockStyles: {
        bold: "__",
        italic: "_",
    },
    unorderedListStyle: "-",
    element: document.getElementById("MyID"),
    forceSync: true,
    hideIcons: ["guide", "heading"],
    indentWithTabs: false,
    initialValue: "Hello world!",
    insertTexts: {
        horizontalRule: ["", "\n\n-----\n\n"],
        image: ["![](http://", ")"],
        link: ["[", "](https://)"],
        table: ["", "\n\n| Column 1 | Column 2 | Column 3 |\n| -------- | -------- | -------- |\n| Text     | Text      | Text     |\n\n"],
    },
    lineWrapping: false,
    minHeight: "500px",
    parsingConfig: {
        allowAtxHeaderWithoutSpace: true,
        strikethrough: false,
        underscoresBreakWords: true,
    },
    placeholder: "Type here...",

    previewClass: "my-custom-styling",
    previewClass: ["my-custom-styling", "more-custom-styling"],

    previewRender: (plainText) => customMarkdownParser(plainText), // Returns HTML from a custom parser
    previewRender: (plainText, preview) => { // Async method
        setTimeout(() => {
            preview.innerHTML = customMarkdownParser(plainText);
        }, 250);

        return "Loading...";
    },
    promptURLs: true,
    promptTexts: {
        image: "Custom prompt for URL:",
        link: "Custom prompt for URL:",
    },
    renderingConfig: {
        singleLineBreaks: false,
        codeSyntaxHighlighting: true,
        sanitizerFunction: (renderedHTML) => {
            // Using DOMPurify and only allowing <b> tags
            return DOMPurify.sanitize(renderedHTML, {ALLOWED_TAGS: ['b']})
        },
    },
    shortcuts: {
        drawTable: "Cmd-Alt-T"
    },
    showIcons: ["code", "table"],
    spellChecker: false,
    status: false,
    status: ["autosave", "lines", "words", "cursor"], // Optional usage
    status: ["autosave", "lines", "words", "cursor", {
        className: "keystrokes",
        defaultValue: (el) => {
            el.setAttribute('data-keystrokes', 0);
        },
        onUpdate: (el) => {
            const keystrokes = Number(el.getAttribute('data-keystrokes')) + 1;
            el.innerHTML = `${keystrokes} Keystrokes`;
            el.setAttribute('data-keystrokes', keystrokes);
        },
    }], // Another optional usage, with a custom status bar item that counts keystrokes
    styleSelectedText: false,
    sideBySideFullscreen: false,
    syncSideBySidePreviewScroll: false,
    tabSize: 4,
    toolbar: false,
    toolbarTips: false,
});

Toolbar icons

Below are the built-in toolbar icons (only some of which are enabled by default), which can be reorganized however you like. "Name" is the name of the icon, referenced in the JavaScript. "Action" is either a function or a URL to open. "Class" is the class given to the icon. "Tooltip" is the small tooltip that appears via the title="" attribute. Note that shortcut hints are added automatically and reflect the specified action if it has a key bind assigned to it (i.e. with the value of action set to bold and that of tooltip set to Bold, the final text the user will see would be "Bold (Ctrl-B)").

Additionally, you can add a separator between any icons by adding "|" to the toolbar array.

Name	Action	Tooltip Class
bold	toggleBold	Bold fa fa-bold
italic	toggleItalic	Italic fa fa-italic
strikethrough	toggleStrikethrough	Strikethrough fa fa-strikethrough
heading	toggleHeadingSmaller	Heading fa fa-header
heading-smaller	toggleHeadingSmaller	Smaller Heading fa fa-header
heading-bigger	toggleHeadingBigger	Bigger Heading fa fa-lg fa-header
heading-1	toggleHeading1	Big Heading fa fa-header header-1
heading-2	toggleHeading2	Medium Heading fa fa-header header-2
heading-3	toggleHeading3	Small Heading fa fa-header header-3
code	toggleCodeBlock	Code fa fa-code
quote	toggleBlockquote	Quote fa fa-quote-left
unordered-list	toggleUnorderedList	Generic List fa fa-list-ul
ordered-list	toggleOrderedList	Numbered List fa fa-list-ol
clean-block	cleanBlock	Clean block fa fa-eraser
link	drawLink	Create Link fa fa-link
image	drawImage	Insert Image fa fa-picture-o
table	drawTable	Insert Table fa fa-table
horizontal-rule	drawHorizontalRule	Insert Horizontal Line fa fa-minus
preview	togglePreview	Toggle Preview fa fa-eye no-disable
side-by-side	toggleSideBySide	Toggle Side by Side fa fa-columns no-disable no-mobile
fullscreen	toggleFullScreen	Toggle Fullscreen fa fa-arrows-alt no-disable no-mobile
guide	This link	Markdown Guide fa fa-question-circle
undo	undo	Undo fa fa-undo
redo	redo	Redo fa fa-redo

Toolbar customization

Customize the toolbar using the toolbar option.

Only the order of existing buttons:

const easyMDE = new EasyMDE({
    toolbar: ["bold", "italic", "heading", "|", "quote"]
});

All information and/or add your own icons

const easyMDE = new EasyMDE({
    toolbar: [
        {
            name: "bold",
            action: EasyMDE.toggleBold,
            className: "fa fa-bold",
            title: "Bold",
        },
        "italics", // shortcut to pre-made button
        {
            name: "custom",
            action: (editor) => {
                // Add your own code
            },
            className: "fa fa-star",
            title: "Custom Button",
            attributes: { // for custom attributes
                id: "custom-id",
                "data-value": "custom value" // HTML5 data-* attributes need to be enclosed in quotation marks ("") because of the dash (-) in its name.
            }
        },
        "|" // Separator
        // [, ...]
    ]
});

Put some buttons on dropdown menu

const easyMDE = new EasyMDE({
    toolbar: [{
                name: "heading",
                action: EasyMDE.toggleHeadingSmaller,
                className: "fa fa-header",
                title: "Headers",
            },
            "|",
            {
                name: "others",
                className: "fa fa-blind",
                title: "others buttons",
                children: [
                    {
                        name: "image",
                        action: EasyMDE.drawImage,
                        className: "fa fa-picture-o",
                        title: "Image",
                    },
                    {
                        name: "quote",
                        action: EasyMDE.toggleBlockquote,
                        className: "fa fa-percent",
                        title: "Quote",
                    },
                    {
                        name: "link",
                        action: EasyMDE.drawLink,
                        className: "fa fa-link",
                        title: "Link",
                    }
                ]
            },
        // [, ...]
    ]
});

Keyboard shortcuts

EasyMDE comes with an array of predefined keyboard shortcuts, but they can be altered with a configuration option. The list of default ones is as follows:

Shortcut (Windows / Linux)	Shortcut (macOS)	Action
Ctrl-'	Cmd-'	"toggleBlockquote"
Ctrl-B	Cmd-B	"toggleBold"
Ctrl-E	Cmd-E	"cleanBlock"
Ctrl-H	Cmd-H	"toggleHeadingSmaller"
Ctrl-I	Cmd-I	"toggleItalic"
Ctrl-K	Cmd-K	"drawLink"
Ctrl-L	Cmd-L	"toggleUnorderedList"
Ctrl-P	Cmd-P	"togglePreview"
Ctrl-Alt-C	Cmd-Alt-C	"toggleCodeBlock"
Ctrl-Alt-I	Cmd-Alt-I	"drawImage"
Ctrl-Alt-L	Cmd-Alt-L	"toggleOrderedList"
Shift-Ctrl-H	Shift-Cmd-H	"toggleHeadingBigger"
F9	F9	"toggleSideBySide"
F11	F11	"toggleFullScreen"

Here is how you can change a few, while leaving others untouched:

const editor = new EasyMDE({
    shortcuts: {
        "toggleOrderedList": "Ctrl-Alt-K", // alter the shortcut for toggleOrderedList
        "toggleCodeBlock": null, // unbind Ctrl-Alt-C
        "drawTable": "Cmd-Alt-T", // bind Cmd-Alt-T to drawTable action, which doesn't come with a default shortcut
    }
});

Shortcuts are automatically converted between platforms. If you define a shortcut as "Cmd-B", on PC that shortcut will be changed to "Ctrl-B". Conversely, a shortcut defined as "Ctrl-B" will become "Cmd-B" for Mac users.

The list of actions that can be bound is the same as the list of built-in actions available for toolbar buttons.

Advanced use

Event handling

You can catch the following list of events: https://codemirror.net/doc/manual.html#events

const easyMDE = new EasyMDE();
easyMDE.codemirror.on("change", () => {
    console.log(easyMDE.value());
});

Removing EasyMDE from text area

You can revert to the initial text area by calling the toTextArea method. Note that this clears up the autosave (if enabled) associated with it. The text area will retain any text from the destroyed EasyMDE instance.

const easyMDE = new EasyMDE();
// ...
easyMDE.toTextArea();
easyMDE = null;

If you need to remove registered event listeners (when the editor is not needed anymore), call easyMDE.cleanup().

Useful methods

The following self-explanatory methods may be of use while developing with EasyMDE.

const easyMDE = new EasyMDE();
easyMDE.isPreviewActive(); // returns boolean
easyMDE.isSideBySideActive(); // returns boolean
easyMDE.isFullscreenActive(); // returns boolean
easyMDE.clearAutosavedValue(); // no returned value

How it works

EasyMDE is a continuation of SimpleMDE.

SimpleMDE began as an improvement of lepture's Editor project, but has now taken on an identity of its own. It is bundled with CodeMirror and depends on Font Awesome.

CodeMirror is the backbone of the project and parses much of the Markdown syntax as it's being written. This allows us to add styles to the Markdown that's being written. Additionally, a toolbar and status bar have been added to the top and bottom, respectively. Previews are rendered by Marked using GitHub Flavored Markdown (GFM).

SimpleMDE fork

I originally made this fork to implement FontAwesome 5 compatibility into SimpleMDE. When that was done I submitted a pull request, which has not been accepted yet. This, and the project being inactive since May 2017, triggered me to make more changes and try to put new life into the project.

Changes include:

FontAwesome 5 compatibility
Guide button works when editor is in preview mode
Links are now https:// by default
Small styling changes
Support for Node 8 and beyond
Lots of refactored code
Links in preview will open in a new tab by default
TypeScript support

My intention is to continue development on this project, improving it and keeping it alive.

Hacking EasyMDE

You may want to edit this library to adapt its behavior to your needs. This can be done in some quick steps:

Follow the prerequisites and installation instructions in the contribution guide;
Do your changes;
Run gulp command, which will generate files: dist/easymde.min.css and dist/easymde.min.js;
Copy-paste those files to your code base, and you are done.

Contributing

Want to contribute to EasyMDE? Thank you! We have a contribution guide just for you!

Author: Ionaru
Source Code: https://github.com/Ionaru/easy-markdown-editor
License: MIT license

#react-native #react

Flutter Dev

1679035563

How to Add Splash Screen in Android and iOS with Flutter

When your app is opened, there is a brief time while the native app loads Flutter. By default, during this time, the native app displays a white splash screen. This package automatically generates iOS, Android, and Web-native code for customizing this native splash screen background color and splash image. Supports dark mode, full screen, and platform-specific options.

What's New

[BETA] Support for flavors is in beta. Currently only Android and iOS are supported. See instructions below.

You can now keep the splash screen up while your app initializes! No need for a secondary splash screen anymore. Just use the preserve and remove methods together to remove the splash screen after your initialization is complete. See details below.

Usage

Would you prefer a video tutorial instead? Check out Johannes Milke's tutorial.

First, add flutter_native_splash as a dependency in your pubspec.yaml file.

dependencies:
  flutter_native_splash: ^2.2.19

Don't forget to flutter pub get.

1. Setting the splash screen

Customize the following settings and add to your project's pubspec.yaml file or place in a new file in your root project folder named flutter_native_splash.yaml.

flutter_native_splash:
  # This package generates native code to customize Flutter's default white native splash screen
  # with background color and splash image.
  # Customize the parameters below, and run the following command in the terminal:
  # flutter pub run flutter_native_splash:create
  # To restore Flutter's default white splash screen, run the following command in the terminal:
  # flutter pub run flutter_native_splash:remove

  # color or background_image is the only required parameter.  Use color to set the background
  # of your splash screen to a solid color.  Use background_image to set the background of your
  # splash screen to a png image.  This is useful for gradients. The image will be stretch to the
  # size of the app. Only one parameter can be used, color and background_image cannot both be set.
  color: "#42a5f5"
  #background_image: "assets/background.png"

  # Optional parameters are listed below.  To enable a parameter, uncomment the line by removing
  # the leading # character.

  # The image parameter allows you to specify an image used in the splash screen.  It must be a
  # png file and should be sized for 4x pixel density.
  #image: assets/splash.png

  # The branding property allows you to specify an image used as branding in the splash screen.
  # It must be a png file. It is supported for Android, iOS and the Web.  For Android 12,
  # see the Android 12 section below.
  #branding: assets/dart.png

  # To position the branding image at the bottom of the screen you can use bottom, bottomRight,
  # and bottomLeft. The default values is bottom if not specified or specified something else.
  #branding_mode: bottom

  # The color_dark, background_image_dark, image_dark, branding_dark are parameters that set the background
  # and image when the device is in dark mode. If they are not specified, the app will use the
  # parameters from above. If the image_dark parameter is specified, color_dark or
  # background_image_dark must be specified.  color_dark and background_image_dark cannot both be
  # set.
  #color_dark: "#042a49"
  #background_image_dark: "assets/dark-background.png"
  #image_dark: assets/splash-invert.png
  #branding_dark: assets/dart_dark.png

  # Android 12 handles the splash screen differently than previous versions.  Please visit
  # https://developer.android.com/guide/topics/ui/splash-screen
  # Following are Android 12 specific parameter.
  android_12:
    # The image parameter sets the splash screen icon image.  If this parameter is not specified,
    # the app's launcher icon will be used instead.
    # Please note that the splash screen will be clipped to a circle on the center of the screen.
    # App icon with an icon background: This should be 960×960 pixels, and fit within a circle
    # 640 pixels in diameter.
    # App icon without an icon background: This should be 1152×1152 pixels, and fit within a circle
    # 768 pixels in diameter.
    #image: assets/android12splash.png

    # Splash screen background color.
    #color: "#42a5f5"

    # App icon background color.
    #icon_background_color: "#111111"

    # The branding property allows you to specify an image used as branding in the splash screen.
    #branding: assets/dart.png

    # The image_dark, color_dark, icon_background_color_dark, and branding_dark set values that
    # apply when the device is in dark mode. If they are not specified, the app will use the
    # parameters from above.
    #image_dark: assets/android12splash-invert.png
    #color_dark: "#042a49"
    #icon_background_color_dark: "#eeeeee"

  # The android, ios and web parameters can be used to disable generating a splash screen on a given
  # platform.
  #android: false
  #ios: false
  #web: false

  # Platform specific images can be specified with the following parameters, which will override
  # the respective parameter.  You may specify all, selected, or none of these parameters:
  #color_android: "#42a5f5"
  #color_dark_android: "#042a49"
  #color_ios: "#42a5f5"
  #color_dark_ios: "#042a49"
  #color_web: "#42a5f5"
  #color_dark_web: "#042a49"
  #image_android: assets/splash-android.png
  #image_dark_android: assets/splash-invert-android.png
  #image_ios: assets/splash-ios.png
  #image_dark_ios: assets/splash-invert-ios.png
  #image_web: assets/splash-web.png
  #image_dark_web: assets/splash-invert-web.png
  #background_image_android: "assets/background-android.png"
  #background_image_dark_android: "assets/dark-background-android.png"
  #background_image_ios: "assets/background-ios.png"
  #background_image_dark_ios: "assets/dark-background-ios.png"
  #background_image_web: "assets/background-web.png"
  #background_image_dark_web: "assets/dark-background-web.png"
  #branding_android: assets/brand-android.png
  #branding_dark_android: assets/dart_dark-android.png
  #branding_ios: assets/brand-ios.png
  #branding_dark_ios: assets/dart_dark-ios.png

  # The position of the splash image can be set with android_gravity, ios_content_mode, and
  # web_image_mode parameters.  All default to center.
  #
  # android_gravity can be one of the following Android Gravity (see
  # https://developer.android.com/reference/android/view/Gravity): bottom, center,
  # center_horizontal, center_vertical, clip_horizontal, clip_vertical, end, fill, fill_horizontal,
  # fill_vertical, left, right, start, or top.
  #android_gravity: center
  #
  # ios_content_mode can be one of the following iOS UIView.ContentMode (see
  # https://developer.apple.com/documentation/uikit/uiview/contentmode): scaleToFill,
  # scaleAspectFit, scaleAspectFill, center, top, bottom, left, right, topLeft, topRight,
  # bottomLeft, or bottomRight.
  #ios_content_mode: center
  #
  # web_image_mode can be one of the following modes: center, contain, stretch, and cover.
  #web_image_mode: center

  # The screen orientation can be set in Android with the android_screen_orientation parameter.
  # Valid parameters can be found here:
  # https://developer.android.com/guide/topics/manifest/activity-element#screen
  #android_screen_orientation: sensorLandscape

  # To hide the notification bar, use the fullscreen parameter.  Has no effect in web since web
  # has no notification bar.  Defaults to false.
  # NOTE: Unlike Android, iOS will not automatically show the notification bar when the app loads.
  #       To show the notification bar, add the following code to your Flutter app:
  #       WidgetsFlutterBinding.ensureInitialized();
  #       SystemChrome.setEnabledSystemUIOverlays([SystemUiOverlay.bottom, SystemUiOverlay.top]);
  #fullscreen: true

  # If you have changed the name(s) of your info.plist file(s), you can specify the filename(s)
  # with the info_plist_files parameter.  Remove only the # characters in the three lines below,
  # do not remove any spaces:
  #info_plist_files:
  #  - 'ios/Runner/Info-Debug.plist'
  #  - 'ios/Runner/Info-Release.plist'

2. Run the package

After adding your settings, run the following command in the terminal:

flutter pub run flutter_native_splash:create

When the package finishes running, your splash screen is ready.

To specify the YAML file location just add --path with the command in the terminal:

flutter pub run flutter_native_splash:create --path=path/to/my/file.yaml

3. Set up app initialization (optional)

By default, the splash screen will be removed when Flutter has drawn the first frame. If you would like the splash screen to remain while your app initializes, you can use the preserve() and remove() methods together. Pass the preserve() method the value returned from WidgetsFlutterBinding.ensureInitialized() to keep the splash on screen. Later, when your app has initialized, make a call to remove() to remove the splash screen.

import 'package:flutter_native_splash/flutter_native_splash.dart';

void main() {
  WidgetsBinding widgetsBinding = WidgetsFlutterBinding.ensureInitialized();
  FlutterNativeSplash.preserve(widgetsBinding: widgetsBinding);
  runApp(const MyApp());
}

// whenever your initialization is completed, remove the splash screen:
    FlutterNativeSplash.remove();

NOTE: If you do not need to use the preserve() and remove() methods, you can place the flutter_native_splash dependency in the dev_dependencies section of pubspec.yaml.

4. Support the package (optional)

If you find this package useful, you can support it for free by giving it a thumbs up at the top of this page. Here's another option to support the package:

Android 12+ Support

Android 12 has a new method of adding splash screens, which consists of a window background, icon, and the icon background. Note that a background image is not supported.

Be aware of the following considerations regarding these elements:

1: image parameter. By default, the launcher icon is used:

App icon without an icon background, as shown on the left: This should be 1152×1152 pixels, and fit within a circle 768 pixels in diameter.
App icon with an icon background, as shown on the right: This should be 960×960 pixels, and fit within a circle 640 pixels in diameter.

2: icon_background_color is optional, and is useful if you need more contrast between the icon and the window background.

3: One-third of the foreground is masked.

4: color the window background consists of a single opaque color.

PLEASE NOTE: The splash screen may not appear when you launch the app from Android Studio on API 31. However, it should appear when you launch by clicking on the launch icon in Android. This seems to be resolved in API 32+.

PLEASE NOTE: There are a number of reports that non-Google launchers do not display the launch image correctly. If the launch image does not display correctly, please try the Google launcher to confirm that this package is working.

PLEASE NOTE: The splash screen does not appear when you launch the app from a notification. Apparently this is the intended behavior on Android 12: core-splashscreen Icon not shown when cold launched from notification.

Flavor Support

If you have a project setup that contains multiple flavors or environments, and you created more than one flavor this would be a feature for you.

Instead of maintaining multiple files and copy/pasting images, you can now, using this tool, create different splash screens for different environments.

Pre-requirements

In order to use the new feature, and generate the desired splash images for you app, a couple of changes are required.

If you want to generate just one flavor and one file you would use either options as described in Step 1. But in order to setup the flavors, you will then be required to move all your setup values to the flutter_native_splash.yaml file, but with a prefix.

Let's assume for the rest of the setup that you have 3 different flavors, Production, Acceptance, Development.

First this you will need to do is to create a different setup file for all 3 flavors with a suffix like so:

flutter_native_splash-production.yaml
flutter_native_splash-acceptance.yaml
flutter_native_splash-development.yaml

You would setup those 3 files the same way as you would the one, but with different assets depending on which environment you would be generating. For example (Note: these are just examples, you can use whatever setup you need for your project that is already supported by the package):

# flutter_native_splash-development.yaml
flutter_native_splash:
  color: "#ffffff"
  image: assets/logo-development.png
  branding: assets/branding-development.png
  color_dark: "#121212"
  image_dark: assets/logo-development.png
  branding_dark: assets/branding-development.png

  android_12:
    image: assets/logo-development.png
    icon_background_color: "#ffffff"
    image_dark: assets/logo-development.png
    icon_background_color_dark: "#121212"

  web: false

# flutter_native_splash-acceptance.yaml
flutter_native_splash:
  color: "#ffffff"
  image: assets/logo-acceptance.png
  branding: assets/branding-acceptance.png
  color_dark: "#121212"
  image_dark: assets/logo-acceptance.png
  branding_dark: assets/branding-acceptance.png

  android_12:
    image: assets/logo-acceptance.png
    icon_background_color: "#ffffff"
    image_dark: assets/logo-acceptance.png
    icon_background_color_dark: "#121212"

  web: false

# flutter_native_splash-production.yaml
flutter_native_splash:
  color: "#ffffff"
  image: assets/logo-production.png
  branding: assets/branding-production.png
  color_dark: "#121212"
  image_dark: assets/logo-production.png
  branding_dark: assets/branding-production.png

  android_12:
    image: assets/logo-production.png
    icon_background_color: "#ffffff"
    image_dark: assets/logo-production.png
    icon_background_color_dark: "#121212"

  web: false

Great, now comes the fun part running the new command!

The new command is:

# If you have a flavor called production you would do this:
flutter pub run flutter_native_splash:create --flavor production

# For a flavor with a name staging you would provide it's name like so:
flutter pub run flutter_native_splash:create --flavor staging

# And if you have a local version for devs you could do that:
flutter pub run flutter_native_splash:create --flavor development

Android setup

You're done! No, really, Android doesn't need any additional setup.

Note: If it didn't work, please make sure that your flavors are named the same as your config files, otherwise the setup will not work.

iOS setup

iOS is a bit tricky, so hang tight, it might look scary but most of the steps are just a single click, explained as much as possible to lower the possibility of mistakes.

When you run the new command, you will need to open xCode and follow the steps bellow:

Assumption

In order for this setup to work, you would already have 3 different schemes setup; production, acceptance and development.

Preparation

Open the iOS Flutter project in Xcode (open the Runner.xcworkspace)
Find the newly created Storyboard files at the same location where the original is {project root}/ios/Runner/Base.lproj
Select all of them and drag and drop into Xcode, directly to the left hand side where the current LaunchScreen.storyboard is located already
After you drop your files there Xcode will ask you to link them, make sure you select 'Copy if needed'
This part is done, you have linked the newly created storyboards in your project.

xCode

Xcode still doesn't know how to use them, so we need to specify for all the current flavors (schemes) which file to use and to use that value inside the Info.plist file.

Open the iOS Flutter project in Xcode (open the Runner.xcworkspace)
Click the Runner project in the top left corner (usually the first item in the list)
In the middle part of the screen, on the left side, select the Runner target
On the top part of the screen select Build Settings
Make sure that 'All' and 'Combined' are selected
Next to 'Combine' you have a '+' button, press it and select 'Add User-Defined Setting'
Once you do that Xcode will create a new variable for you to name. Suggestion is to name it LAUNCH_SCREEN_STORYBOARD
Once you do that, you will have the option to define a specific name for each flavor (scheme) that you have defined in the project. Make sure that you input the exact name of the LaunchScreen.storyboard that was created by this tool
- Example: If you have a flavor Development, there is a Storyboard created name LaunchScreenDevelopment.storyboard, please add that name (without the storyboard part) to the variable value next to the flavor value
After you finish with that, you need to update Info.plist file to link the newly created variable so that it's used correctly
Open the Info.plist file
Find the entry called 'Launch screen interface file base name'
The default value is 'LaunchScreen', change that to the variable name that you create previously. If you follow these steps exactly, it would be LAUNCH_SCREEN_STORYBOARD, so input this $(LAUNCH_SCREEN_STORYBOARD)
And your done!

Congrats you finished your setup for multiple flavors,

FAQs

I got the error "A splash screen was provided to Flutter, but this is deprecated."

This message is not related to this package but is related to a change in how Flutter handles splash screens in Flutter 2.5. It is caused by having the following code in your android/app/src/main/AndroidManifest.xml, which was included by default in previous versions of Flutter:

<meta-data
 android:name="io.flutter.embedding.android.SplashScreenDrawable"
 android:resource="@drawable/launch_background"
 />

The solution is to remove the above code. Note that this will also remove the fade effect between the native splash screen and your app.

Are animations/lottie/GIF images supported?

Not at this time. PRs are always welcome!

I got the error AAPT: error: style attribute 'android:attr/windowSplashScreenBackground' not found

This attribute is only found in Android 12, so if you are getting this error, it means your project is not fully set up for Android 12. Did you update your app's build configuration?

I see a flash of the wrong splash screen on iOS

This is caused by an iOS splash caching bug, which can be solved by uninstalling your app, powering off your device, power back on, and then try reinstalling.

I see a white screen between splash screen and app

It may be caused by an iOS splash caching bug, which can be solved by uninstalling your app, powering off your device, power back on, and then try reinstalling.
It may be caused by the delay due to initialization in your app. To solve this, put any initialization code in the removeAfter method.

Can I base light/dark mode on app settings?

No. This package creates a splash screen that is displayed before Flutter is loaded. Because of this, when the splash screen loads, internal app settings are not available to the splash screen. Unfortunately, this means that it is impossible to control light/dark settings of the splash from app settings.

Notes

If the splash screen was not updated correctly on iOS or if you experience a white screen before the splash screen, run flutter clean and recompile your app. If that does not solve the problem, delete your app, power down the device, power up the device, install and launch the app as per this StackOverflow thread.

This package modifies launch_background.xml and styles.xml files on Android, LaunchScreen.storyboard and Info.plist on iOS, and index.html on Web. If you have modified these files manually, this plugin may not work properly. Please open an issue if you find any bugs.

How it works

Android

Your splash image will be resized to mdpi, hdpi, xhdpi, xxhdpi and xxxhdpi drawables.
An <item> tag containing a <bitmap> for your splash image drawable will be added in launch_background.xml
Background color will be added in colors.xml and referenced in launch_background.xml.
Code for full screen mode toggle will be added in styles.xml.
Dark mode variants are placed in drawable-night, values-night, etc. resource folders.

iOS

Your splash image will be resized to @3x and @2x images.
Color and image properties will be inserted in LaunchScreen.storyboard.
The background color is implemented by using a single-pixel png file and stretching it to fit the screen.
Code for hidden status bar toggle will be added in Info.plist.

Web

A web/splash folder will be created for splash screen images and CSS files.
Your splash image will be resized to 1x, 2x, 3x, and 4x sizes and placed in web/splash/img.
The splash style sheet will be added to the app's web/index.html, as well as the HTML for the splash pictures.

Acknowledgments

This package was originally created by Henrique Arthur and it is currently maintained by Jon Hanson.

Bugs or Requests

If you encounter any problems feel free to open an issue. If you feel the library is missing a feature, please raise a ticket. Pull request are also welcome.

Use this package as a library

Depend on it

Run this command:

With Flutter:

 $ flutter pub add flutter_native_splash

This will add a line like this to your package's pubspec.yaml (and run an implicit flutter pub get):

dependencies:
  flutter_native_splash: ^2.2.19

Alternatively, your editor might support flutter pub get. Check the docs for your editor to learn more.

Import it

Now in your Dart code, you can use:

import 'package:flutter_native_splash/flutter_native_splash.dart';

example/lib/main.dart

import 'package:flutter/material.dart';
import 'package:flutter_native_splash/flutter_native_splash.dart';

void main() {
  WidgetsBinding widgetsBinding = WidgetsFlutterBinding.ensureInitialized();
  FlutterNativeSplash.preserve(widgetsBinding: widgetsBinding);
  runApp(const MyApp());
}

class MyApp extends StatelessWidget {
  const MyApp({super.key});

  // This widget is the root of your application.
  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      title: 'Flutter Demo',
      theme: ThemeData(
        // This is the theme of your application.
        //
        // Try running your application with "flutter run". You'll see the
        // application has a blue toolbar. Then, without quitting the app, try
        // changing the primarySwatch below to Colors.green and then invoke
        // "hot reload" (press "r" in the console where you ran "flutter run",
        // or simply save your changes to "hot reload" in a Flutter IDE).
        // Notice that the counter didn't reset back to zero; the application
        // is not restarted.
        primarySwatch: Colors.blue,
      ),
      home: const MyHomePage(title: 'Flutter Demo Home Page'),
    );
  }
}

class MyHomePage extends StatefulWidget {
  const MyHomePage({super.key, required this.title});

  // This widget is the home page of your application. It is stateful, meaning
  // that it has a State object (defined below) that contains fields that affect
  // how it looks.

  // This class is the configuration for the state. It holds the values (in this
  // case the title) provided by the parent (in this case the App widget) and
  // used by the build method of the State. Fields in a Widget subclass are
  // always marked "final".

  final String title;

  @override
  State<MyHomePage> createState() => _MyHomePageState();
}

class _MyHomePageState extends State<MyHomePage> {
  int _counter = 0;

  void _incrementCounter() {
    setState(() {
      // This call to setState tells the Flutter framework that something has
      // changed in this State, which causes it to rerun the build method below
      // so that the display can reflect the updated values. If we changed
      // _counter without calling setState(), then the build method would not be
      // called again, and so nothing would appear to happen.
      _counter++;
    });
  }

  @override
  void initState() {
    super.initState();
    initialization();
  }

  void initialization() async {
    // This is where you can initialize the resources needed by your app while
    // the splash screen is displayed.  Remove the following example because
    // delaying the user experience is a bad design practice!
    // ignore_for_file: avoid_print
    print('ready in 3...');
    await Future.delayed(const Duration(seconds: 1));
    print('ready in 2...');
    await Future.delayed(const Duration(seconds: 1));
    print('ready in 1...');
    await Future.delayed(const Duration(seconds: 1));
    print('go!');
    FlutterNativeSplash.remove();
  }

  @override
  Widget build(BuildContext context) {
    // This method is rerun every time setState is called, for instance as done
    // by the _incrementCounter method above.
    //
    // The Flutter framework has been optimized to make rerunning build methods
    // fast, so that you can just rebuild anything that needs updating rather
    // than having to individually change instances of widgets.
    return Scaffold(
      appBar: AppBar(
        // Here we take the value from the MyHomePage object that was created by
        // the App.build method, and use it to set our appbar title.
        title: Text(widget.title),
      ),
      body: Center(
        // Center is a layout widget. It takes a single child and positions it
        // in the middle of the parent.
        child: Column(
          // Column is also a layout widget. It takes a list of children and
          // arranges them vertically. By default, it sizes itself to fit its
          // children horizontally, and tries to be as tall as its parent.
          //
          // Invoke "debug painting" (press "p" in the console, choose the
          // "Toggle Debug Paint" action from the Flutter Inspector in Android
          // Studio, or the "Toggle Debug Paint" command in Visual Studio Code)
          // to see the wireframe for each widget.
          //
          // Column has various properties to control how it sizes itself and
          // how it positions its children. Here we use mainAxisAlignment to
          // center the children vertically; the main axis here is the vertical
          // axis because Columns are vertical (the cross axis would be
          // horizontal).
          mainAxisAlignment: MainAxisAlignment.center,
          children: <Widget>[
            const Text(
              'You have pushed the button this many times:',
            ),
            Text(
              '$_counter',
              style: Theme.of(context).textTheme.headlineMedium,
            ),
          ],
        ),
      ),
      floatingActionButton: FloatingActionButton(
        onPressed: _incrementCounter,
        tooltip: 'Increment',
        child: const Icon(Icons.add),
      ), // This trailing comma makes auto-formatting nicer for build methods.
    );
  }
}

Download Details:

Author: jonbhanson
Download Link: Download The Source Code
Official Website: https://github.com/jonbhanson/flutter_native_splash
License: MIT license

#flutter #ios #android

Arvilla Medhurst

1669188856

What Is R Programming Language? introduction & Basics

In this R article, we will learn about What Is R Programming Language? introduction & Basics. R is a programming language developed by Ross Ihaka and Robert Gentleman in 1993. R possesses an extensive catalog of statistical and graphical methods. It includes machine learning algorithms, linear regression, time series, statistical inference to name a few. Most of the R libraries are written in R, but for heavy computational tasks, C, C++, and Fortran codes are preferred.

Data analysis with R is done in a series of steps; programming, transforming, discovering, modeling and communicating the results

Program: R is a clear and accessible programming tool
Transform: R is made up of a collection of libraries designed specifically for data science
Discover: Investigate the data, refine your hypothesis and analyze them
Model: R provides a wide array of tools to capture the right model for your data
Communicate: Integrate codes, graphs, and outputs to a report with R Markdown or build Shiny apps to share with the world.

What is R used for?

Statistical inference
Data analysis
Machine learning algorithm

As conclusion, R is the world’s most widely used statistics programming language. It’s the 1st choice of data scientists and supported by a vibrant and talented community of contributors. R is taught in universities and deployed in mission-critical business applications.

R-environment setup

Windows Installation – We can download the Windows installer version of R from R-3.2.2 for windows (32/64)

As it is a Windows installer (.exe) with the name “R-version-win.exe”. You can just double click and run the installer accepting the default settings. If your Windows is a 32-bit version, it installs the 32-bit version. But if your windows are 64-bit, then it installs both the 32-bit and 64-bit versions.

After installation, you can locate the icon to run the program in a directory structure “R\R3.2.2\bin\i386\Rgui.exe” under the Windows Program Files. Clicking this icon brings up the R-GUI which is the R console to do R Programming.

R basic Syntax

R Programming is a very popular programming language that is broadly used in data analysis. The way in which we define its code is quite simple. The “Hello World!” is the basic program for all the languages, and now we will understand the syntax of R programming with the “Hello world” program. We can write our code either in the command prompt, or we can use an R script file.

R command prompt

Once you have R environment setup, then it’s easy to start your R command prompt by just typing the following command at your command prompt −
$R
This will launch R interpreter and you will get a prompt > where you can start typing your program as follows −

>myString <- "Hello, World"
>print (myString)
[1] "Hello, World!"

Here the first statement defines a string variable myString, where we assign a string “Hello, World!” and then the next statement print() is being used to print the value stored in myString variable.

R data-types

While doing programming in any programming language, you need to use various variables to store various information. Variables are nothing but reserved memory locations to store values. This means that when you create a variable you reserve some space in memory.

In contrast to other programming languages like C and java in R, the variables are not declared as some data type. The variables are assigned with R-Objects and the data type of the R-object becomes the data type of the variable. There are many types of R-objects. The frequently used ones are −

Vectors
Lists
Matrices
Arrays
Factors
Data Frames

Vectors

#create a vector and find the elements which are >5
v<-c(1,2,3,4,5,6,5,8)
v[v>5]

#subset
subset(v,v>5)

#position in the vector created in which square of the numbers of v is >10 holds good
which(v*v>10)

#to know the values 
v[v*v>10]

Output: [1] 6 8 Output: [1] 6 8 Output: [1] 4 5 6 7 8 Output: [1] 4 5 6 5 8

Matrices

A matrix is a two-dimensional rectangular data set. It can be created using a vector input to the matrix function.

#matrices: a vector with two dimensional attributes
mat<-matrix(c(1,2,3,4))
 
mat1<-matrix(c(1,2,3,4),nrow=2)
mat1

Output: [,1] [,2] [1,] 1 3 [2,] 2 4

mat2<-matrix(c(1,2,3,4),ncol=2,byrow=T)
mat2

Output: [,1] [,2] [1,] 1 2 [2,] 3 4

mat3<-matrix(c(1,2,3,4),byrow=T)
mat3

#transpose of matrix
mattrans<-t(mat)
mattrans

#create a character matrix called fruits with elements apple, orange, pear, grapes
fruits<-matrix(c("apple","orange","pear","grapes"),2)
#create 3×4 matrix of marks obtained in each quarterly exams for 4 different subjects 
X<-matrix(c(50,70,40,90,60, 80,50, 90,100, 50,30, 70),nrow=3)
X

#give row names and column names
rownames(X)<-paste(prefix="Test.",1:3)
subs<-c("Maths", "English", "Science", "History")
colnames(X)<-subs
X

Output: [,1] [1,] 1 [2,] 2 [3,] 3 [4,] 4 Output: [,1] [,2] [,3] [,4] [1,] 1 2 3 4 Output: [,1] [,2] [,3] [,4] [1,] 50 90 50 50 [2,] 70 60 90 30 [3,] 40 80 100 70 Output: Maths English Science History Test. 1 50 90 50 50 Test. 2 70 60 90 30 Test. 3 40 80 100 70

Arrays

While matrices are confined to two dimensions, arrays can be of any number of dimensions. The array function takes a dim attribute which creates the required number of dimensions. In the below example we create an array with two elements which are 3×3 matrices each.

#Arrays
arr<-array(1:24,dim=c(3,4,2))
arr

#create an array using alphabets with dimensions 3 rows, 2 columns and 3 arrays
arr1<-array(letters[1:18],dim=c(3,2,3))

#select only 1st two matrix of an array
arr1[,,c(1:2)]

#LIST
X<-list(u=2, n='abc')
X
X$u

 [,1] [,2] [,3] [,4]

 [,1] [,2] [,3] [,4]

 [,1] [,2]

 [,1] [,2]

Dataframes

Data frames are tabular data objects. Unlike a matrix in a data frame, each column can contain different modes of data. The first column can be numeric while the second column can be character and the third column can be logical. It is a list of vectors of equal length.

#Dataframes
students<-c("J","L","M","K","I","F","R","S")
Subjects<-rep(c("science","maths"),each=2)
marks<-c(55,70,66,85,88,90,56,78)
data<-data.frame(students,Subjects,marks)
#Accessing dataframes
data[[1]]

data$Subjects
data[,1]

Output: [1] J L M K I F R S Levels: F I J K L M R S Output: data$Subjects [1] science science maths maths science science maths maths Levels: maths science

Factors

Factors are the r-objects which are created using a vector. It stores the vector along with the distinct values of the elements in the vector as labels. The labels are always character irrespective of whether it is numeric or character or Boolean etc. in the input vector. They are useful in statistical modeling.

Factors are created using the factor() function. The nlevels function gives the count of levels.

#Factors
x<-c(1,2,3)
factor(x)

#apply function
data1<-data.frame(age=c(55,34,42,66,77),bmi=c(26,25,21,30,22))
d<-apply(data1,2,mean)
d

#create two vectors age and gender and find mean age with respect to gender
age<-c(33,34,55,54)
gender<-factor(c("m","f","m","f"))
tapply(age,gender,mean)

Output: [1] 1 2 3 Levels: 1 2 3 Output: age bmi 54.8 24.8 Output: f m 44 44

R Variables

A variable provides us with named storage that our programs can manipulate. A variable in R can store an atomic vector, a group of atomic vectors, or a combination of many R objects. A valid variable name consists of letters, numbers, and the dot or underlines characters.

Rules for writing Identifiers in R

Identifiers can be a combination of letters, digits, period (.), and underscore (_).
It must start with a letter or a period. If it starts with a period, it cannot be followed by a digit.
Reserved words in R cannot be used as identifiers.

Valid identifiers in R

total, sum, .fine.with.dot, this_is_acceptable, Number5

Invalid identifiers in R

tot@l, 5um, _fine, TRUE, .0ne

Best Practices

Earlier versions of R used underscore (_) as an assignment operator. So, the period (.) was used extensively in variable names having multiple words. Current versions of R support underscore as a valid identifier but it is good practice to use a period as word separators.
For example, a.variable.name is preferred over a_variable_name or alternatively we could use camel case as aVariableName.

Constants in R

Constants, as the name suggests, are entities whose value cannot be altered. Basic types of constant are numeric constants and character constants.

Numeric Constants

All numbers fall under this category. They can be of type integer, double or complex. It can be checked with the typeof() function.
Numeric Constants followed by L are regarded as integers and those followed by i are regarded as complex.

> typeof(5)
> typeof(5L)
> typeof(5L)

[1] “double” [1] “double” [[1] “double”

Character Constants

Character constants can be represented using either single quotes (‘) or double quotes (“) as delimiters.

> 'example'
> typeof("5")

[1] "example" [1] "character"

R Operators

Operators – Arithmetic, Relational, Logical, Assignment, and some of the Miscellaneous Operators that R programming language provides.

There are four main categories of Operators in the R programming language.

Arithmetic Operators
Relational Operators
Logical Operators
Assignment Operators
Mixed Operators

x <- 35
y<-10

x+y > x-y > x*y > x/y > x%/%y > x%%y > x^y [1] 45 [1] 25 [1] 350 [1] 3.5 [1] 3 [1] 5 [1]2.75e+15

Logical Operators

The below table shows the logical operators in R. Operators & and | perform element-wise operation producing result having a length of the longer operand. But && and || examines only the first element of the operands resulting in a single length logical vector.

a <- c(TRUE,TRUE,FALSE,0,6,7)
b <- c(FALSE,TRUE,FALSE,TRUE,TRUE,TRUE)
a&b 
[1] FALSE TRUE FALSE FALSE TRUE TRUE
a&&b
[1] FALSE
> a|b
[1] TRUE TRUE FALSE TRUE TRUE TRUE
> a||b
[1] TRUE
> !a
[1] FALSE FALSE TRUE TRUE FALSE FALSE
> !b
[1] TRUE FALSE TRUE FALSE FALSE FALSE

R functions

Functions are defined using the function() directive and are stored as R objects just like anything else. In particular, they are R objects of class “function”. Here’s a simple function that takes no arguments simply prints ‘Hi statistics’.

#define the function
f <- function() {
print("Hi statistics!!!")
}
#Call the function
f()

Output: [1] "Hi statistics!!!"

Now let’s define a function called standardize, and the function has a single argument x which is used in the body of a function.

#Define the function that will calculate standardized score.
standardize = function(x) {
m = mean(x)
sd = sd(x)
result = (x – m) / sd
result
}
input<- c(40:50) #Take input for what we want to calculate a standardized score.
standardize(input) #Call the function

Output: standardize(input) #Call the function [1] -1.5075567 -1.2060454 -0.9045340 -0.6030227 -0.3015113 0.0000000 0.3015113 0.6030227 0.9045340 1.2060454 1.5075567

Loop Functions

R has some very useful functions which implement looping in a compact form to make life easier. The very rich and powerful family of applied functions is made of intrinsically vectorized functions. These functions in R allow you to apply some function to a series of objects (eg. vectors, matrices, data frames, or files). They include:

lapply(): Loop over a list and evaluate a function on each element
sapply(): Same as lapply but try to simplify the result
apply(): Apply a function over the margins of an array
tapply(): Apply a function over subsets of a vector
mapply(): Multivariate version of lapply

There is another function called split() which is also useful, particularly in conjunction with lapply.

R Vectors

A vector is a sequence of data elements of the same basic type. Members in a vector are officially called components. Vectors are the most basic R data objects and there are six types of atomic vectors. They are logical, integer, double, complex, character, and raw.

The c() function can be used to create vectors of objects by concatenating things together. 
x <- c(1,2,3,4,5) #double
x #If you use only x auto-printing occurs
l <- c(TRUE, FALSE) #logical
l <- c(T, F) ## logical
c <- c("a", "b", "c", "d") ## character
i <- 1:20 ## integer
cm <- c(2+2i, 3+3i) ## complex
print(l)
print(c)
print(i)
print(cm)

You can see the type of each vector using typeof() function in R.
typeof(x)
typeof(l)
typeof(c)
typeof(i)
typeof(cm)

Output: print(l) [1] TRUE FALSE print(c) [1] "a" "b" "c" "d" print(i) [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 print(cm) [1] 2+2i 3+3i Output: typeof(x) [1] "double" typeof(l) [1] "logical" typeof(c) [1] "character" typeof(i) [1] "integer" typeof(cm) [1] "complex"

Creating a vector using seq() function:

We can use the seq() function to create a vector within an interval by specifying step size or specifying the length of the vector.

seq(1:10) #By default it will be incremented by 1
seq(1, 20, length.out=5) # specify length of the vector
seq(1, 20, by=2) # specify step size

Output: > seq(1:10) #By default it will be incremented by 1 [1] 1 2 3 4 5 6 7 8 9 10 > seq(1, 20, length.out=5) # specify length of the vector [1] 1.00 5.75 10.50 15.25 20.00 > seq(1, 20, by=2) # specify step size [1] 1 3 5 7 9 11 13 15 17 19

Extract Elements from a Vector:

Elements of a vector can be accessed using indexing. The vector indexing can be logical, integer, or character. The [ ] brackets are used for indexing. Indexing starts with position 1, unlike most programming languages where indexing starts from 0.

Extract Using Integer as Index:

We can use integers as an index to access specific elements. We can also use negative integers to return all elements except that specific element.

x<- 101:110
x[1]   #access the first element
x[c(2,3,4,5)] #Extract 2nd, 3rd, 4th, and 5th elements
x[5:10]        #Extract all elements from 5th to 10th
x[c(-5,-10)] #Extract all elements except 5th and 10th
x[-c(5:10)] #Extract all elements except from 5th to 10th

Output: x[1] #Extract the first element [1] 101 x[c(2,3,4,5)] #Extract 2nd, 3rd, 4th, and 5th elements [1] 102 103 104 105 x[5:10] #Extract all elements from 5th to 10th [1] 105 106 107 108 109 110 x[c(-5,-10)] #Extract all elements except 5th and 10th [1] 101 102 103 104 106 107 108 109 x[-c(5:10)] #Extract all elements except from 5th to 10th [1] 101 102 103 104

Extract Using Logical Vector as Index:

If you use a logical vector for indexing, the position where the logical vector is TRUE will be returned.

x[x < 105]
x[x>=104]

Output: x[x < 105] [1] 101 102 103 104 x[x>=104] [1] 104 105 106 107 108 109 110

Modify a Vector in R:

We can modify a vector and assign a new value to it. You can truncate a vector by using reassignments. Check the below example.

x<- 10:12
x[1]<- 101 #Modify the first element
x
x[2]<-102 #Modify the 2nd element
x
x<- x[1:2] #Truncate the last element
x

Output: x [1] 101 11 12 x[2]<-102 #Modify the 2nd element x [1] 101 102 12 x<- x[1:2] #Truncate the last element x [1] 101 102

Arithmetic Operations on Vectors:

We can use arithmetic operations on two vectors of the same length. They can be added, subtracted, multiplied, or divided. Check the output of the below code.

# Create two vectors.
v1 <- c(1:10)
v2 <- c(101:110)

# Vector addition.
add.result <- v1+v2
print(add.result)
# Vector subtraction.
sub.result <- v2-v1
print(sub.result)
# Vector multiplication.
multi.result <- v1*v2
print(multi.result)
# Vector division.
divi.result <- v2/v1
print(divi.result)

Output: print(add.result) [1] 102 104 106 108 110 112 114 116 118 120 print(sub.result) [1] 100 100 100 100 100 100 100 100 100 100 print(multi.result) [1] 101 204 309 416 525 636 749 864 981 1100 print(divi.result) [1] 101.00000 51.00000 34.33333 26.00000 21.00000 17.66667 15.28571 13.50000 12.11111 11.00000

Find Minimum and Maximum in a Vector:

The minimum and the maximum of a vector can be found using the min() or the max() function. range() is also available which returns the minimum and maximum in a vector.

x<- 1001:1010
max(x) # Find the maximum
min(x) # Find the minimum
range(x) #Find the range

Output: max(x) # Find the maximum [1] 1010 min(x) # Find the minimum [1] 1001 range(x) #Find the range [1] 1001 1010

R Lists

The list is a data structure having elements of mixed data types. A vector having all elements of the same type is called an atomic vector but a vector having elements of a different type is called list.
We can check the type with typeof() or class() function and find the length using length()function.

x <- list("stat",5.1, TRUE, 1 + 4i)
x
class(x)
typeof(x)
length(x)

Output: x [[1]] [1] "stat" [[2]] [1] 5.1 [[3]] [1] TRUE [[4]] [1] 1+4i class(x) [1] “list” typeof(x) [1] “list” length(x) [1] 4

You can create an empty list of a prespecified length with the vector() function.

x <- vector("list", length = 10)
x

Output: x [[1]] NULL [[2]] NULL [[3]] NULL [[4]] NULL [[5]] NULL [[6]] NULL [[7]] NULL [[8]] NULL [[9]] NULL [[10]] NULL

How to extract elements from a list?

Lists can be subset using two syntaxes, the $ operator, and square brackets []. The $ operator returns a named element of a list. The [] syntax returns a list, while the [[]] returns an element of a list.

# subsetting
l$e
l["e"]
l[1:2]
l[c(1:2)] #index using integer vector
l[-c(3:length(l))] #negative index to exclude elements from 3rd up to last.
l[c(T,F,F,F,F)] # logical index to access elements

Output: > l$e [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 1 0 0 0 0 0 0 0 0 0 [2,] 0 1 0 0 0 0 0 0 0 0 [3,] 0 0 1 0 0 0 0 0 0 0 [4,] 0 0 0 1 0 0 0 0 0 0 [5,] 0 0 0 0 1 0 0 0 0 0 [6,] 0 0 0 0 0 1 0 0 0 0 [7,] 0 0 0 0 0 0 1 0 0 0 [8,] 0 0 0 0 0 0 0 1 0 0 [9,] 0 0 0 0 0 0 0 0 1 0 [10,] 0 0 0 0 0 0 0 0 0 1 > l["e"] $e [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 1 0 0 0 0 0 0 0 0 0 [2,] 0 1 0 0 0 0 0 0 0 0 [3,] 0 0 1 0 0 0 0 0 0 0 [4,] 0 0 0 1 0 0 0 0 0 0 [5,] 0 0 0 0 1 0 0 0 0 0 [6,] 0 0 0 0 0 1 0 0 0 0 [7,] 0 0 0 0 0 0 1 0 0 0 [8,] 0 0 0 0 0 0 0 1 0 0 [9,] 0 0 0 0 0 0 0 0 1 0 [10,] 0 0 0 0 0 0 0 0 0 1 > l[1:2] [[1]] [1] 1 2 3 4 [[2]] [1] FALSE > l[c(1:2)] #index using integer vector [[1]] [1] 1 2 3 4 [[2]] [1] FALSE > l[-c(3:length(l))] #negative index to exclude elements from 3rd up to last. [[1]] [1] 1 2 3 4 [[2]] [1] FALSE l[c(T,F,F,F,F)] [[1]] [1] 1 2 3 4

Modifying a List in R:

We can change components of a list through reassignment.

l[["name"]] <- "Kalyan Nandi"
l

Output: [[1]] [1] 1 2 3 4 [[2]] [1] FALSE [[3]] [1] “Hello Statistics!” $d function (arg = 42) { print(“Hello World!”) } $name [1] “Kalyan Nandi”

R Matrices

In R Programming Matrix is a two-dimensional data structure. They contain elements of the same atomic types. A Matrix can be created using the matrix() function. R can also be used for matrix calculations. Matrices have rows and columns containing a single data type. In a matrix, the order of rows and columns is important. Dimension can be checked directly with the dim() function and all attributes of an object can be checked with the attributes() function. Check the below example.

Creating a matrix in R

m <- matrix(nrow = 2, ncol = 3)
dim(m)
attributes(m)
m <- matrix(1:20, nrow = 4, ncol = 5)
m

Output: dim(m) [1] 2 3 attributes(m) $dim [1] 2 3 m <- matrix(1:20, nrow = 4, ncol = 5) m [,1] [,2] [,3] [,4] [,5] [1,] 1 5 9 13 17 [2,] 2 6 10 14 18 [3,] 3 7 11 15 19 [4,] 4 8 12 16 20

Matrices can be created by column-binding or row-binding with the cbind() and rbind() functions.

x<-1:3
y<-10:12
z<-30:32
cbind(x,y,z)
rbind(x,y,z)

Output: cbind(x,y,z) x y z [1,] 1 10 30 [2,] 2 11 31 [3,] 3 12 32 rbind(x,y,z) [,1] [,2] [,3] x 1 2 3 y 10 11 12 z 30 31 32

By default, the matrix function reorders a vector into columns, but we can also tell R to use rows instead.

x <-1:9
matrix(x, nrow = 3, ncol = 3)
matrix(x, nrow = 3, ncol = 3, byrow = TRUE)

Output cbind(x,y,z) x y z [1,] 1 10 30 [2,] 2 11 31 [3,] 3 12 32 rbind(x,y,z) [,1] [,2] [,3] x 1 2 3 y 10 11 12 z 30 31 32

R Arrays

In R, Arrays are the data types that can store data in more than two dimensions. An array can be created using the array() function. It takes vectors as input and uses the values in the dim parameter to create an array. If you create an array of dimensions (2, 3, 4) then it creates 4 rectangular matrices each with 2 rows and 3 columns. Arrays can store only data type.

Give a Name to Columns and Rows:

We can give names to the rows, columns, and matrices in the array by setting the dimnames parameter.

v1 <- c(1,2,3)
v2 <- 100:110
col.names <- c("Col1","Col2","Col3","Col4","Col5","Col6","Col7")
row.names <- c("Row1","Row2")
matrix.names <- c("Matrix1","Matrix2")
arr4 <- array(c(v1,v2), dim=c(2,7,2), dimnames = list(row.names,col.names, matrix.names))
arr4

Output: , , Matrix1 Col1 Col2 Col3 Col4 Col5 Col6 Col7 Row1 1 3 101 103 105 107 109 Row2 2 100 102 104 106 108 110 , , Matrix2 Col1 Col2 Col3 Col4 Col5 Col6 Col7 Row1 1 3 101 103 105 107 109 Row2 2 100 102 104 106 108 110

Accessing/Extracting Array Elements:

# Print the 2nd row of the 1st matrix of the array.
print(arr4[2,,1])
# Print the element in the 2nd row and 4th column of the 2nd matrix.
print(arr4[2,4,2])
# Print the 2nd Matrix.
print(arr4[,,2])

Output: > print(arr4[2,,1]) Col1 Col2 Col3 Col4 Col5 Col6 Col7 2 100 102 104 106 108 110 > > # Print the element in the 2nd row and 4th column of the 2nd matrix. > print(arr4[2,4,2]) [1] 104 > > # Print the 2nd Matrix. > print(arr4[,,2]) Col1 Col2 Col3 Col4 Col5 Col6 Col7 Row1 1 3 101 103 105 107 109 Row2 2 100 102 104 106 108 110

R Factors

Factors are used to represent categorical data and can be unordered or ordered. An example might be “Male” and “Female” if we consider gender. Factor objects can be created with the factor() function.

x <- factor(c("male", "female", "male", "male", "female"))
x
table(x)

Output: x [1] male female male male female Levels: female male table(x) x female male 2 3

By default, Levels are put in alphabetical order. If you print the above code you will get levels as female and male. But if you want to get your levels in a particular order then set levels parameter like this.

x <- factor(c("male", "female", "male", "male", "female"), levels=c("male", "female"))
x
table(x)

Output: x [1] male female male male female Levels: male female table(x) x male female 3 2

R Dataframes

Data frames are used to store tabular data in R. They are an important type of object in R and are used in a variety of statistical modeling applications. Data frames are represented as a special type of list where every element of the list has to have the same length. Each element of the list can be thought of as a column and the length of each element of the list is the number of rows. Unlike matrices, data frames can store different classes of objects in each column. Matrices must have every element be the same class (e.g. all integers or all numeric).

Creating a Data Frame:

Data frames can be created explicitly with the data.frame() function.

employee <- c('Ram','Sham','Jadu')
salary <- c(21000, 23400, 26800)
startdate <- as.Date(c('2016-11-1','2015-3-25','2017-3-14'))
employ_data <- data.frame(employee, salary, startdate)
employ_data
View(employ_data)

Output: employ_data employee salary startdate 1 Ram 21000 2016-11-01 2 Sham 23400 2015-03-25 3 Jadu 26800 2017-03-14 View(employ_data)

Get the Structure of the Data Frame:

If you look at the structure of the data frame now, you see that the variable employee is a character vector, as shown in the following output:

str(employ_data)

Output: > str(employ_data) 'data.frame': 3 obs. of 3 variables: $ employee : Factor w/ 3 levels "Jadu","Ram","Sham": 2 3 1 $ salary : num 21000 23400 26800 $ startdate: Date, format: "2016-11-01" "2015-03-25" "2017-03-14"

Note that the first column, employee, is of type factor, instead of a character vector. By default, data.frame() function converts character vector into factor. To suppress this behavior, we can pass the argument stringsAsFactors=FALSE.

employ_data <- data.frame(employee, salary, startdate, stringsAsFactors = FALSE)
str(employ_data)

Output: 'data.frame': 3 obs. of 3 variables: $ employee : chr "Ram" "Sham" "Jadu" $ salary : num 21000 23400 26800 $ startdate: Date, format: "2016-11-01" "2015-03-25" "2017-03-14"

R Packages

The primary location for obtaining R packages is CRAN.

You can obtain information about the available packages on CRAN with the available.packages() function.
a <- available.packages()

head(rownames(a), 30) # Show the names of the first 30 packages
Packages can be installed with the install.packages() function in R. To install a single package, pass the name of the lecture to the install.packages() function as the first argument.
The following code installs the ggplot2 package from CRAN.
install.packages(“ggplot2”)
You can install multiple R packages at once with a single call to install.packages(). Place the names of the R packages in a character vector.
install.packages(c(“caret”, “ggplot2”, “dplyr”))

Loading packages
Installing a package does not make it immediately available to you in R; you must load the package. The library() function is used to load packages into R. The following code is used to load the ggplot2 package into R. Do not put the package name in quotes.
library(ggplot2)
If you have Installed your packages without root access using the command install.packages(“ggplot2″, lib=”/data/Rpackages/”). Then to load use the below command.
library(ggplot2, lib.loc=”/data/Rpackages/”)
After loading a package, the functions exported by that package will be attached to the top of the search() list (after the workspace).
library(ggplot2)

search()

R – CSV() files

In R, we can read data from files stored outside the R environment. We can also write data into files that will be stored and accessed by the operating system. R can read and write into various file formats like CSV, Excel, XML, etc.

Getting and Setting the Working Directory

We can check which directory the R workspace is pointing to using the getwd() function. You can also set a new working directory using setwd()function.

# Get and print current working directory.
print(getwd())

# Set current working directory.
setwd("/web/com")

# Get and print current working directory.
print(getwd())

Output: [1] "/web/com/1441086124_2016" [1] "/web/com"

Input as CSV File

The CSV file is a text file in which the values in the columns are separated by a comma. Let’s consider the following data present in the file named input.csv.

You can create this file using windows notepad by copying and pasting this data. Save the file as input.csv using the save As All files(*.*) option in notepad.

Reading a CSV File

Following is a simple example of read.csv() function to read a CSV file available in your current working directory −

data <- read.csv("input.csv")
print(data)

  id,   name,    salary,   start_date,     dept

R- Charts and Graphs

R- Pie Charts

Pie charts are created with the function pie(x, labels=) where x is a non-negative numeric vector indicating the area of each slice and labels= notes a character vector of names for the slices.

Syntax

The basic syntax for creating a pie-chart using the R is −

pie(x, labels, radius, main, col, clockwise)

Following is the description of the parameters used −

x is a vector containing the numeric values used in the pie chart.
labels are used to give a description of the slices.
radius indicates the radius of the circle of the pie chart. (value between −1 and +1).
main indicates the title of the chart.
col indicates the color palette.
clockwise is a logical value indicating if the slices are drawn clockwise or anti-clockwise.

Simple Pie chart

# Simple Pie Chart
slices <- c(10, 12,4, 16, 8)
lbls <- c("US", "UK", "Australia", "Germany", "France")
pie(slices, labels = lbls, main="Pie Chart of Countries")

3-D pie chart

The pie3D( ) function in the plotrix package provides 3D exploded pie charts.

# 3D Exploded Pie Chart
library(plotrix)
slices <- c(10, 12, 4, 16, 8)
lbls <- c("US", "UK", "Australia", "Germany", "France")
pie3D(slices,labels=lbls,explode=0.1,
   main="Pie Chart of Countries ")

R -Bar Charts

A bar chart represents data in rectangular bars with a length of the bar proportional to the value of the variable. R uses the function barplot() to create bar charts. R can draw both vertical and Horizontal bars in the bar chart. In the bar chart, each of the bars can be given different colors.

Let us suppose, we have a vector of maximum temperatures (in degree Celsius) for seven days as follows.

max.temp <- c(22, 27, 26, 24, 23, 26, 28)
barplot(max.temp)

Some of the frequently used ones are, “main” to give the title, “xlab” and “ylab” to provide labels for the axes, names.arg for naming each bar, “col” to define color, etc.

We can also plot bars horizontally by providing the argument horiz=TRUE.

# barchart with added parameters
barplot(max.temp,
main = "Maximum Temperatures in a Week",
xlab = "Degree Celsius",
ylab = "Day",
names.arg = c("Sun", "Mon", "Tue", "Wed", "Thu", "Fri", "Sat"),
col = "darkred",
horiz = TRUE)

Simply doing barplot(age) will not give us the required plot. It will plot 10 bars with height equal to the student’s age. But we want to know the number of students in each age category.

This count can be quickly found using the table() function, as shown below.

> table(age)
age
16 17 18 19 
1  2  6  1

Now plotting this data will give our required bar plot. Note below, that we define the argument “density” to shade the bars.

barplot(table(age),
main="Age Count of 10 Students",
xlab="Age",
ylab="Count",
border="red",
col="blue",
density=10
)

A histogram represents the frequencies of values of a variable bucketed into ranges. Histogram is similar to bar chat but the difference is it groups the values into continuous ranges. Each bar in histogram represents the height of the number of values present in that range.

R creates histogram using hist() function. This function takes a vector as an input and uses some more parameters to plot histograms.

Syntax

The basic syntax for creating a histogram using R is −

hist(v,main,xlab,xlim,ylim,breaks,col,border)

Following is the description of the parameters used −

v is a vector containing numeric values used in the histogram.
main indicates the title of the chart.
col is used to set the color of the bars.
border is used to set the border color of each bar.
xlab is used to give a description of the x-axis.
xlim is used to specify the range of values on the x-axis.
ylim is used to specify the range of values on the y-axis.
breaks are used to mention the width of each bar.

Example

A simple histogram is created using input vector, label, col, and border parameters.

The script given below will create and save the histogram in the current R working directory.

# Create data for the graph.
v <-  c(9,13,21,8,36,22,12,41,31,33,19)

# Give the chart file a name.
png(file = "histogram.png")

# Create the histogram.
hist(v,xlab = "Weight",col = "yellow",border = "blue")

# Save the file.
dev.off()

Range of X and Y values

To specify the range of values allowed in X axis and Y axis, we can use the xlim and ylim parameters.

The width of each bar can be decided by using breaks.

# Create data for the graph.
v <- c(9,13,21,8,36,22,12,41,31,33,19)

# Give the chart file a name.
png(file = "histogram_lim_breaks.png")

# Create the histogram.
hist(v,xlab = "Weight",col = "green",border = "red", xlim = c(0,40), ylim = c(0,5),
   breaks = 5)

# Save the file.
dev.off()

R vs SAS – Which Tool is Better?

The debate around data analytics tools has been going on forever. Each time a new one comes out, comparisons transpire. Although many aspects of the tool remain subjective, beginners want to know which tool is better to start with.
The most popular and widely used tools for data analytics are R and SAS. Both of them have been around for a long time and are often pitted against each other. So, let’s compare them based on the most relevant factors.

Availability and Cost: SAS is widely used in most private organizations as it is a commercial software. It is more expensive than any other data analytics tool available. It might thus be a bit difficult buying the software if you are an individual professional or a student starting out. On the other hand, R is an open source software and is completely free to use. Anyone can begin using it right away without having to spend a penny. So, regarding availability and cost, R is hands down the better tool.
Ease of learning: Since SAS is a commercial software, it has a whole lot of online resources available. Also, those who already know SQL might find it easier to adapt to SAS as it comes with PROC SQL option. The tool has a user-friendly GUI. It comes with an extensive documentation and tutorial base which can help early learners get started seamlessly. Whereas, the learning curve for R is quite steep. You need to learn to code at the root level and carrying out simple tasks demand a lot of time and effort with R. However, several forums and online communities post religiously about its usage.
Data Handling Capabilities: When it comes to data handling, both SAS and R perform well, but there are some caveats for the latter. While SAS can even churn through terabytes of data with ease, R might be constrained as it makes use of the available RAM in the machine. This can be a hassle for 32-bit systems with low RAM capacity. Due to this, R can at times become unresponsive or give an ‘out of memory’ error. Both of them can run parallel computations, support integrations for Hadoop, Spark, Cloudera and Apache Pig among others. Also, the availability of devices with better RAM capacity might negate the disadvantages of R.
Graphical Capabilities: Graphical capabilities or data visualization is the strongest forte of R. This is where SAS lacks behind in a major way. R has access to packages like GGPlot, RGIS, Lattice, and GGVIS among others which provide superior graphical competency. In comparison, Base SAS is struggling hard to catch up with the advancements in graphics and visualization in data analytics. Even the graphics packages available in SAS are poorly documented which makes them difficult to use.
Advancements in Tool: Advancements in the industry give way to advancements in tools, and both SAS and R hold up pretty well in this regard. SAS, being a corporate software, rolls out new features and technologies frequently with new versions of its software. However, the updates are not as fast as R since it is open source software and has many contributors throughout the world. Alternatively, the latest updates in SAS are pushed out after thorough testing, making them much more stable, and reliable than R. Both the tools come with a fair share of pros & cons.
Job Scenario: Currently, large corporations insist on using SAS, but SMEs and start-ups are increasingly opting for R, given that it’s free. The current job trend seems to show that while SAS is losing its momentum, R is gaining potential. The job scenario is on the cusp of change, and both the tools seem strong, but since R is on an uphill path, it can probably witness more jobs in the future, albeit not in huge corporates.
Deep Learning Support: While SAS has just begun work on adding deep learning support, R has added support for a few packages which enable deep learning capabilities in the tool. You can use KerasR and keras package in R which are mere interfaces for the original Keras package built on Python. Although none of the tools are excellent facilitators of deep learning, R has seen some recent active developments on this front.
Customer Service Support and Community: As one would expect from full-fledged commercial software, SAS offers excellent customer service support as well as the backing of a helpful community. Since R is free open-source software, expecting customer support will be hard to justify. However, it has a vast online community that can help you with almost everything. On the other hand, no matter what problem you face with SAS, you can immediately reach out to their customer support and get it solved without any hassles.

Final Verdict
As per estimations by the Economic Times, the analytics industry will grow to $16 billion till 2025 in India. If you wish to venture into this domain, there can’t be a better time. Just start learning the tool you think is better based on the comparison points above.

Original article source at: https://www.mygreatlearning.com

#r #programming

Chloe Butler

1667425440

Pdf2gerb: Perl Script Converts PDF Files to Gerber format

pdf2gerb

Perl script converts PDF files to Gerber format

Pdf2Gerb generates Gerber 274X photoplotting and Excellon drill files from PDFs of a PCB. Up to three PDFs are used: the top copper layer, the bottom copper layer (for 2-sided PCBs), and an optional silk screen layer. The PDFs can be created directly from any PDF drawing software, or a PDF print driver can be used to capture the Print output if the drawing software does not directly support output to PDF.

The general workflow is as follows:

Design the PCB using your favorite CAD or drawing software.
Print the top and bottom copper and top silk screen layers to a PDF file.
Run Pdf2Gerb on the PDFs to create Gerber and Excellon files.
Use a Gerber viewer to double-check the output against the original PCB design.
Make adjustments as needed.
Submit the files to a PCB manufacturer.

Please note that Pdf2Gerb does NOT perform DRC (Design Rule Checks), as these will vary according to individual PCB manufacturer conventions and capabilities. Also note that Pdf2Gerb is not perfect, so the output files must always be checked before submitting them. As of version 1.6, Pdf2Gerb supports most PCB elements, such as round and square pads, round holes, traces, SMD pads, ground planes, no-fill areas, and panelization. However, because it interprets the graphical output of a Print function, there are limitations in what it can recognize (or there may be bugs).

See docs/Pdf2Gerb.pdf for install/setup, config, usage, and other info.

pdf2gerb_cfg.pm

#Pdf2Gerb config settings:
#Put this file in same folder/directory as pdf2gerb.pl itself (global settings),
#or copy to another folder/directory with PDFs if you want PCB-specific settings.
#There is only one user of this file, so we don't need a custom package or namespace.
#NOTE: all constants defined in here will be added to main namespace.
#package pdf2gerb_cfg;

use strict; #trap undef vars (easier debug)
use warnings; #other useful info (easier debug)


##############################################################################################
#configurable settings:
#change values here instead of in main pfg2gerb.pl file

use constant WANT_COLORS => ($^O !~ m/Win/); #ANSI colors no worky on Windows? this must be set < first DebugPrint() call

#just a little warning; set realistic expectations:
#DebugPrint("${\(CYAN)}Pdf2Gerb.pl ${\(VERSION)}, $^O O/S\n${\(YELLOW)}${\(BOLD)}${\(ITALIC)}This is EXPERIMENTAL software.  \nGerber files MAY CONTAIN ERRORS.  Please CHECK them before fabrication!${\(RESET)}", 0); #if WANT_DEBUG

use constant METRIC => FALSE; #set to TRUE for metric units (only affect final numbers in output files, not internal arithmetic)
use constant APERTURE_LIMIT => 0; #34; #max #apertures to use; generate warnings if too many apertures are used (0 to not check)
use constant DRILL_FMT => '2.4'; #'2.3'; #'2.4' is the default for PCB fab; change to '2.3' for CNC

use constant WANT_DEBUG => 0; #10; #level of debug wanted; higher == more, lower == less, 0 == none
use constant GERBER_DEBUG => 0; #level of debug to include in Gerber file; DON'T USE FOR FABRICATION
use constant WANT_STREAMS => FALSE; #TRUE; #save decompressed streams to files (for debug)
use constant WANT_ALLINPUT => FALSE; #TRUE; #save entire input stream (for debug ONLY)

#DebugPrint(sprintf("${\(CYAN)}DEBUG: stdout %d, gerber %d, want streams? %d, all input? %d, O/S: $^O, Perl: $]${\(RESET)}\n", WANT_DEBUG, GERBER_DEBUG, WANT_STREAMS, WANT_ALLINPUT), 1);
#DebugPrint(sprintf("max int = %d, min int = %d\n", MAXINT, MININT), 1); 

#define standard trace and pad sizes to reduce scaling or PDF rendering errors:
#This avoids weird aperture settings and replaces them with more standardized values.
#(I'm not sure how photoplotters handle strange sizes).
#Fewer choices here gives more accurate mapping in the final Gerber files.
#units are in inches
use constant TOOL_SIZES => #add more as desired
(
#round or square pads (> 0) and drills (< 0):
    .010, -.001,  #tiny pads for SMD; dummy drill size (too small for practical use, but needed so StandardTool will use this entry)
    .031, -.014,  #used for vias
    .041, -.020,  #smallest non-filled plated hole
    .051, -.025,
    .056, -.029,  #useful for IC pins
    .070, -.033,
    .075, -.040,  #heavier leads
#    .090, -.043,  #NOTE: 600 dpi is not high enough resolution to reliably distinguish between .043" and .046", so choose 1 of the 2 here
    .100, -.046,
    .115, -.052,
    .130, -.061,
    .140, -.067,
    .150, -.079,
    .175, -.088,
    .190, -.093,
    .200, -.100,
    .220, -.110,
    .160, -.125,  #useful for mounting holes
#some additional pad sizes without holes (repeat a previous hole size if you just want the pad size):
    .090, -.040,  #want a .090 pad option, but use dummy hole size
    .065, -.040, #.065 x .065 rect pad
    .035, -.040, #.035 x .065 rect pad
#traces:
    .001,  #too thin for real traces; use only for board outlines
    .006,  #minimum real trace width; mainly used for text
    .008,  #mainly used for mid-sized text, not traces
    .010,  #minimum recommended trace width for low-current signals
    .012,
    .015,  #moderate low-voltage current
    .020,  #heavier trace for power, ground (even if a lighter one is adequate)
    .025,
    .030,  #heavy-current traces; be careful with these ones!
    .040,
    .050,
    .060,
    .080,
    .100,
    .120,
);
#Areas larger than the values below will be filled with parallel lines:
#This cuts down on the number of aperture sizes used.
#Set to 0 to always use an aperture or drill, regardless of size.
use constant { MAX_APERTURE => max((TOOL_SIZES)) + .004, MAX_DRILL => -min((TOOL_SIZES)) + .004 }; #max aperture and drill sizes (plus a little tolerance)
#DebugPrint(sprintf("using %d standard tool sizes: %s, max aper %.3f, max drill %.3f\n", scalar((TOOL_SIZES)), join(", ", (TOOL_SIZES)), MAX_APERTURE, MAX_DRILL), 1);

#NOTE: Compare the PDF to the original CAD file to check the accuracy of the PDF rendering and parsing!
#for example, the CAD software I used generated the following circles for holes:
#CAD hole size:   parsed PDF diameter:      error:
#  .014                .016                +.002
#  .020                .02267              +.00267
#  .025                .026                +.001
#  .029                .03167              +.00267
#  .033                .036                +.003
#  .040                .04267              +.00267
#This was usually ~ .002" - .003" too big compared to the hole as displayed in the CAD software.
#To compensate for PDF rendering errors (either during CAD Print function or PDF parsing logic), adjust the values below as needed.
#units are pixels; for example, a value of 2.4 at 600 dpi = .0004 inch, 2 at 600 dpi = .0033"
use constant
{
    HOLE_ADJUST => -0.004 * 600, #-2.6, #holes seemed to be slightly oversized (by .002" - .004"), so shrink them a little
    RNDPAD_ADJUST => -0.003 * 600, #-2, #-2.4, #round pads seemed to be slightly oversized, so shrink them a little
    SQRPAD_ADJUST => +0.001 * 600, #+.5, #square pads are sometimes too small by .00067, so bump them up a little
    RECTPAD_ADJUST => 0, #(pixels) rectangular pads seem to be okay? (not tested much)
    TRACE_ADJUST => 0, #(pixels) traces seemed to be okay?
    REDUCE_TOLERANCE => .001, #(inches) allow this much variation when reducing circles and rects
};

#Also, my CAD's Print function or the PDF print driver I used was a little off for circles, so define some additional adjustment values here:
#Values are added to X/Y coordinates; units are pixels; for example, a value of 1 at 600 dpi would be ~= .002 inch
use constant
{
    CIRCLE_ADJUST_MINX => 0,
    CIRCLE_ADJUST_MINY => -0.001 * 600, #-1, #circles were a little too high, so nudge them a little lower
    CIRCLE_ADJUST_MAXX => +0.001 * 600, #+1, #circles were a little too far to the left, so nudge them a little to the right
    CIRCLE_ADJUST_MAXY => 0,
    SUBST_CIRCLE_CLIPRECT => FALSE, #generate circle and substitute for clip rects (to compensate for the way some CAD software draws circles)
    WANT_CLIPRECT => TRUE, #FALSE, #AI doesn't need clip rect at all? should be on normally?
    RECT_COMPLETION => FALSE, #TRUE, #fill in 4th side of rect when 3 sides found
};

#allow .012 clearance around pads for solder mask:
#This value effectively adjusts pad sizes in the TOOL_SIZES list above (only for solder mask layers).
use constant SOLDER_MARGIN => +.012; #units are inches

#line join/cap styles:
use constant
{
    CAP_NONE => 0, #butt (none); line is exact length
    CAP_ROUND => 1, #round cap/join; line overhangs by a semi-circle at either end
    CAP_SQUARE => 2, #square cap/join; line overhangs by a half square on either end
    CAP_OVERRIDE => FALSE, #cap style overrides drawing logic
};
    
#number of elements in each shape type:
use constant
{
    RECT_SHAPELEN => 6, #x0, y0, x1, y1, count, "rect" (start, end corners)
    LINE_SHAPELEN => 6, #x0, y0, x1, y1, count, "line" (line seg)
    CURVE_SHAPELEN => 10, #xstart, ystart, x0, y0, x1, y1, xend, yend, count, "curve" (bezier 2 points)
    CIRCLE_SHAPELEN => 5, #x, y, 5, count, "circle" (center + radius)
};
#const my %SHAPELEN =
#Readonly my %SHAPELEN =>
our %SHAPELEN =
(
    rect => RECT_SHAPELEN,
    line => LINE_SHAPELEN,
    curve => CURVE_SHAPELEN,
    circle => CIRCLE_SHAPELEN,
);

#panelization:
#This will repeat the entire body the number of times indicated along the X or Y axes (files grow accordingly).
#Display elements that overhang PCB boundary can be squashed or left as-is (typically text or other silk screen markings).
#Set "overhangs" TRUE to allow overhangs, FALSE to truncate them.
#xpad and ypad allow margins to be added around outer edge of panelized PCB.
use constant PANELIZE => {'x' => 1, 'y' => 1, 'xpad' => 0, 'ypad' => 0, 'overhangs' => TRUE}; #number of times to repeat in X and Y directions

# Set this to 1 if you need TurboCAD support.
#$turboCAD = FALSE; #is this still needed as an option?

#CIRCAD pad generation uses an appropriate aperture, then moves it (stroke) "a little" - we use this to find pads and distinguish them from PCB holes. 
use constant PAD_STROKE => 0.3; #0.0005 * 600; #units are pixels
#convert very short traces to pads or holes:
use constant TRACE_MINLEN => .001; #units are inches
#use constant ALWAYS_XY => TRUE; #FALSE; #force XY even if X or Y doesn't change; NOTE: needs to be TRUE for all pads to show in FlatCAM and ViewPlot
use constant REMOVE_POLARITY => FALSE; #TRUE; #set to remove subtractive (negative) polarity; NOTE: must be FALSE for ground planes

#PDF uses "points", each point = 1/72 inch
#combined with a PDF scale factor of .12, this gives 600 dpi resolution (1/72 * .12 = 600 dpi)
use constant INCHES_PER_POINT => 1/72; #0.0138888889; #multiply point-size by this to get inches

# The precision used when computing a bezier curve. Higher numbers are more precise but slower (and generate larger files).
#$bezierPrecision = 100;
use constant BEZIER_PRECISION => 36; #100; #use const; reduced for faster rendering (mainly used for silk screen and thermal pads)

# Ground planes and silk screen or larger copper rectangles or circles are filled line-by-line using this resolution.
use constant FILL_WIDTH => .01; #fill at most 0.01 inch at a time

# The max number of characters to read into memory
use constant MAX_BYTES => 10 * M; #bumped up to 10 MB, use const

use constant DUP_DRILL1 => TRUE; #FALSE; #kludge: ViewPlot doesn't load drill files that are too small so duplicate first tool

my $runtime = time(); #Time::HiRes::gettimeofday(); #measure my execution time

print STDERR "Loaded config settings from '${\(__FILE__)}'.\n";
1; #last value must be truthful to indicate successful load


#############################################################################################
#junk/experiment:

#use Package::Constants;
#use Exporter qw(import); #https://perldoc.perl.org/Exporter.html

#my $caller = "pdf2gerb::";

#sub cfg
#{
#    my $proto = shift;
#    my $class = ref($proto) || $proto;
#    my $settings =
#    {
#        $WANT_DEBUG => 990, #10; #level of debug wanted; higher == more, lower == less, 0 == none
#    };
#    bless($settings, $class);
#    return $settings;
#}

#use constant HELLO => "hi there2"; #"main::HELLO" => "hi there";
#use constant GOODBYE => 14; #"main::GOODBYE" => 12;

#print STDERR "read cfg file\n";

#our @EXPORT_OK = Package::Constants->list(__PACKAGE__); #https://www.perlmonks.org/?node_id=1072691; NOTE: "_OK" skips short/common names

#print STDERR scalar(@EXPORT_OK) . " consts exported:\n";
#foreach(@EXPORT_OK) { print STDERR "$_\n"; }
#my $val = main::thing("xyz");
#print STDERR "caller gave me $val\n";
#foreach my $arg (@ARGV) { print STDERR "arg $arg\n"; }

Download Details:

Author: swannman
Source Code: https://github.com/swannman/pdf2gerb

License: GPL-3.0 license

#perl

Shardul Bhatt

1626775355

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities.

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.

5 Reasons to Utilize Python for Programming Web Apps

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.

Simple to read and compose

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.

Utilized by the best

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.

Massive community support

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.

Progressive applications

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development