tmasjc

#!/usr/bin/env python3
import argparse
import configparser
import sqlite3
import openai
import pinecone
config = configparser.ConfigParser()
config.read("config.ini")

tmasjc

from getpass import getpass
from pprint import pprint
from neo4j import GraphDatabase
from pymongo import MongoClient

## get data from document database ----
mongodb_password = getpass("Enter Atlas password:")
client = MongoClient(
    f"mongodb+srv://admin:{mongodb_password}@serverlessinstance0.9vrdx.mongodb.net"
)

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// if x is a multiple of 3  then output "fizz",
// if x is a multiple of 5  then output "buzz"
// if x is a multiple of 15 then output "fizz buzz"

// basic
func fizz_buzz_alpha(max: Int) -> () {
    for number in 1...max {
        if number % 15 == 0 {
            print("fizz buzz")
        } else if number % 3 == 0 {

tmasjc

library(tidyverse)
library(hrbrthemes)
library(janitor)
library(survival)
library(survminer)
library(shiny)
library(miniUI)

theme_set(theme_ipsum())
pals <- rownames(RColorBrewer::brewer.pal.info)

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library(tidyverse)
library(networkD3)

raw <- pins::pin_get("projects", "local")

df <- raw %>% 
    mutate(associate = str_split(associate, pattern = "，|、")) %>% 
    unnest_longer(associate) %>% 
    filter(!is.na(associate)) %>% 
    count(owner, associate)

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emacs --daemon to run in the background. emacsclient.emacs24 <filename/dirname> to open in terminal

NOTE: "M-m and SPC can be used interchangeably".

• Undo - C-/
• Redo - C-?
• Change case: 1. Camel Case : M-c 2. Upper Case : M-u

3. Lower Case : M-l

tmasjc

library(tidyverse)
library(tidymodels)

sf_trees <- read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-01-28/sf_trees.csv")

trees_df <- sf_trees %>%
    mutate(
        legal_status = case_when(
            legal_status == "DPW Maintained" ~ legal_status,
            TRUE ~ "Other"

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Primary Approaches to Local Interpretation

source: https://bradleyboehmke.github.io/HOML/iml.html

Local Interpretable Model-Agnostic Explanations

Assumptions:

• Every model is linear on a local scale;
• It is possible to fit a simple surrogate model around a single observation that will mimic how the global model behaves at the locality;

tmasjc

# %%
import configparser
import mysql.connector
from mysql.connector import Error
import pandas as pd
from openpyxl import load_workbook
from openpyxl.utils.dataframe import dataframe_to_rows

config = configparser.ConfigParser()
config.read("config.ini")

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# %%
import configparser
import pandas as pd
import smtplib
from socket import gaierror
from email import encoders
from email.mime.base import MIMEBase
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText