AdamSpannbauer

from collections import defaultdict
import numpy as np


def api_call(response_ok=True):
    if response_ok:
        return {'Released': 2010, 'Ratings': [{'Value': 98}]}
    else:
        return defaultdict(lambda: np.nan)
    

AdamSpannbauer

import warnings
import statsmodels.api as sm
from statsmodels.stats.outliers_influence import variance_inflation_factor


def print_vif(x):
    """Utility for checking multicollinearity assumption
    
    :param x: input features to check using VIF. This is assumed to be a pandas.DataFrame
    :return: nothing is returned the VIFs are printed as a pandas series

AdamSpannbauer

("exit" to quit) Question: What market does FitBit compete in?
   Search Rank  Squad Rank  Combined Rank                           Answer                     Context
0  2.0          6.0         1.5            crowded market                   ... rather   crowded ma...
1  7.0          1.0         1.5            oncology                         ...te in the oncology  ...
2  8.0          3.0         3.0            streaming services market        ...trate the streaming ...
3  5.0          7.0         4.0            leash                            ...ck a long leash. Boe...
4  4.0          9.0         5.0            iPhones                          ...io of new iPhones - ...
5  1.0          13.0        6.5            wearables                        ...hough, is wearables,...
6  9.0          5.0         6.5            murky                            ...'re in a "murky" mar...
7  15.0         2.0         8.0            ad market                        ...ce in the ad market ...

AdamSpannbauer

>>> from whoosh.analysis import StandardAnalyzer
>>>
>>> [token.text for token in StandardAnalyzer()("This is an example analysis")]

AdamSpannbauer

# Experimental utility function

message("--------------------------------------------------------------------------------\n")
message("Overwriting `?` function with custom utility to display in memory function help.\n")
message("--------------------------------------------------------------------------------\n\n")

help2 = function(f, ...) {
  #' Extend `help()` to show in memory function documentation
  #'
  #' @details Supports python docstring-esque roxygen documentation.

AdamSpannbauer

class A:
    def x(self):
        print('x: A')


class B(A):
    def x(self):
        super().x()
        print('x: B')

AdamSpannbauer

library(ggplot2)
library(gganimate)
library(data.table)

gen_heart_y = function(x, a) {
  # source: https://i.imgur.com/avE8cxJ.gifv
  (x^2)^(1 / 3) + 0.9 * (3.3 - x^2)^(1 / 2) * sin(a * pi * x)
}

heart_dt_list = lapply(seq(1, 15, by = 0.1), function(a) {

AdamSpannbauer

library(R6)
library(ggplot2)
library(uuid)
options(stringsAsFactors = FALSE)

branch_base = R6Class('branch_base',
                      public = list(
                          start_x = NA_integer_,
                          start_y = NA_integer_,
                          end_x = NA_integer_,

AdamSpannbauer

# Create/animate fractal trees at various angles for branch splits

library(gganimate)
library(ggplot2)
library(uuid)
options(stringsAsFactors = FALSE)

# create line segment from (0, 0) to (0, len) to be trunk of fractal tree
create_trunk = function(len = 1) {
  end_point = c(0, len)

AdamSpannbauer

# Create/Draw a Binary Fractal Tree

library(ggplot2)
library(uuid)
options(stringsAsFactors = FALSE)

# create line segment from (0, 0) to (0, len) to be trunk of fractal tree
create_trunk = function(len = 1) {
  end_point = c(0, len)
  trunk_df = data.frame(x=c(0, 0),