xiesixia

# For detailed explaination of this function, check this blog post: https://asterhu.com/post/2023-05-11-coalesce-join-in-r/
# Reference: https://alistaire.rbind.io/blog/coalescing-joins/
require(dplyr)
require(stringr)

coalesce_join <- function(x, y, 
                          by = NULL, 
                          keep = c("left", "right"), # "left" means keep value from left table if there's any duplicate value in both tables.
                          suffix = c(".x", ".y"), 
                          join = c("full_join","left_join", "right_join", "inner_join")) {

kepano

javascript: Promise.all([import('https://unpkg.com/[email protected]?module'), import('https://unpkg.com/@tehshrike/[email protected]'), ]).then(async ([{
    default: Turndown
}, {
    default: Readability
}]) => {

  /* Optional vault name */
  const vault = "";

  /* Optional folder name such as "Clippings/" */

XueshiQiao

/**
* 使用方法：
* 1. 用 Chrome 打开歌单的 web 页面（可以通过分享拿到链接，链接类似这样：http://music.163.com/playlist?id=xxx&userid=yyy）
* 2. 然后右键“检查”（如果有左上角有 device 选项，需要选择 Laptop 开头的，可以在 Edit/编辑 里添加，添加的时候注意 “User Agent string” 里选择 Desktop）
* 3. 在 console 里输入下面脚本，即可输出 “歌曲名 - 歌手名” 格式的内容：

    Springsteen - Eric Church
    Chattahoochee - Alan Jackson
    Baby Now That I Found You - Alison Krauss
    Check Yes or No - George Strait

kepi

;; org-archive-subtree-hierarchical.el
;;
;; version 0.2
;; modified from https://lists.gnu.org/archive/html/emacs-orgmode/2014-08/msg00109.html
;; modified from https://stackoverflow.com/a/35475878/259187

;; In orgmode
;; * A
;; ** AA
;; *** AAA

KoheiKanagu

import nbformat
import os
import sys

file_name = sys.argv[1]


def parse(code: list) -> nbformat.v4:
    nb = nbformat.v4.new_notebook()
    nb["cells"] = []

conormm

R to python data wrangling snippets

The dplyr package in R makes data wrangling significantly easier. The beauty of dplyr is that, by design, the options available are limited. Specifically, a set of key verbs form the core of the package. Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe. Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R. The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package).

dplyr is organised around six key verbs:

bradleybossard

javascript:(function() {

function copyToClipboard(text) {
    if (window.clipboardData && window.clipboardData.setData) {
        /*IE specific code path to prevent textarea being shown while dialog is visible.*/
        return clipboardData.setData("Text", text); 

    } else if (document.queryCommandSupported && document.queryCommandSupported("copy")) {
        var textarea = document.createElement("textarea");
        textarea.textContent = text;