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#' @title Convert a numeric value into a natural language approximation string
#' 
#' @description 
#' This function takes a numeric value and returns a string that approximates the value in natural language.
#' 
#' @param x A numeric value.
#' 
#' @examples 
#' approx_num(0.5)
#' # [1] "increased by a half"

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# data cleaning and utility
import numpy as np
import pandas as pd
import vivainsights as vi
import os

# timing code
import time 
import random
import sys

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import requests
import pandas as pd

package_name = "vivainsights"
api_endpoint = f"https://pypistats.org/api/packages/{package_name}/overall"

response = requests.get(api_endpoint)

if response.status_code == 200:
    data = response.json()

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# See <https://rpubs.com/mbounthavong/sample_size_power_analysis_R>

library(pwr)

# Sample size estimations for two proportions
# `pwr::ES.h()` computes effect size for two proportions
# n provides required sample size

p0 <- pwr.2p.test(h = ES.h(p1 = 0.60, p2 = 0.50), sig.level = 0.05, power = .80)
plot(p0)

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# estimate sample size via power analysis
from statsmodels.stats.power import TTestIndPower

# parameters for power analysis
effect = 0.8
alpha = 0.05
power = 0.8

# perform power analysis
analysis = TTestIndPower()

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#' @title
#' Rank a data frame by grouping variable using base R
#'
#' @description
#' This function ranks a specified column in a data frame by group using entirely base R functions. 
#' The underlying function is `rank()`, where additional arguments can be passed with `...`. 
#' The grouping variable is specified as a string using the argument `group_var`, and the variable to rank is 
#' specified using the argument `rank_var`. The operation is analogous to using `group_by()` followed by 
#' `mutate()` in {dplyr}.
#' See example below using the base dataset `iris`. 

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# multiply values based on weights

wtest <-
  data.frame(
    x = c("cats", "dogs", "birds", "cats"),
    y = c(1, 2, 3, 2)
  )


wtest[rep(seq_len(nrow(wtest)), wtest$y),]

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Sub FilterTwoSeriesCopyAndPaste()

    Dim S1_String, S2_String As String
    
    'READ VALUES FROM SETTING SHEET -------------------------------------------------------
    
    S1_String = Worksheets("Settings").Range("B2").Value
    S2_String = Worksheets("Settings").Range("B3").Value
    
    Debug.Print S1_String

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# Load packages -----------------------------------------------------------


library(tidyverse)

# Path where all Rd files live --------------------------------------------

man_path <-
  here::here("man")

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## Implement Information Value in base?

iris_iv <-
  iris %>%
  mutate(IsSetosa = ifelse(Species == "setosa", 1, 0))

## Information
infoTables <- 
  Information::create_infotables(
    data = iris_iv,