BenjaminWolfe

import numpy as np, pandas as pd

df_len = 1000  # integer multiple of 4
np.random.seed(42)

# create a random data frame
df = pd.DataFrame(
    {
        "group_a": np.random.randint(0, df_len / 4, size=df_len),
        "group_b": np.random.randint(0, df_len / 4, size=df_len),

BenjaminWolfe

# how to use np.where with multiple columns at once, even whole data frames?

import numpy as np
import pandas as pd

np.random.seed(42)

df1 = pd.DataFrame(np.random.randint(0, 100, size=(100, 4)), columns=list("ABCD"))
df2 = pd.DataFrame(np.random.randint(0, 100, size=(100, 4)), columns=list("ABCD"))
condition = pd.Series(np.random.choice(a=[False, True], size=100, p=[.1, .9]))

BenjaminWolfe

# See `curl.md`. Here is the R equivalent.

library(httr)
library(jsonlite)

make_page <- function(url, headers, data) {
  response <- POST(
    url = url,
    body = toJSON(data, auto_unbox = TRUE),
    config = add_headers(.headers = headers)

BenjaminWolfe

// background
function timer(ms) { return new Promise(res => setTimeout(res, ms)); }
async function keepGoing(direction, i) {
    await timer(500);
    const directions = {"up": "previous", "down": "next"};
    document.querySelectorAll(`[data-qa="fixed-footer-navigation-${directions[direction]}"]`)[0].click()
    
    await timer(500);
    let focusQ = document.querySelectorAll('[data-qa-focused="true"]')[0]
    let qId = focusQ.getAttribute('data-qa-blockref');