toandaominh1997

import pandas as pd 

def split_dataframe(df, chunk_size, file_name = "shopee"):
    """
    Splits a Dataframe into smaller chunks of a specified size and saves each chunk as a separate CSV file. 
    Parameters:
    - df (pandas.DataFrame): The DataFrame to be split.
    - chunk_size (int): The number of rows each chunk should contain.
    - file_name (str, optional): The base name for the output CSV files. Defaults to "shopee".

toandaominh1997

{
	"deploy": {
		"VM:-": {
			"linkReferences": {},
			"autoDeployLib": true
		},
		"main:1": {
			"linkReferences": {},
			"autoDeployLib": true
		},

toandaominh1997

\documentclass[letterpaper,11pt]{article}

\usepackage{latexsym}
\usepackage[empty]{fullpage}
\usepackage{titlesec}
\usepackage{marvosym}
\usepackage[usenames,dvipsnames]{color}
\usepackage{verbatim}
\usepackage{enumitem}
\usepackage[hidelinks]{hyperref}

toandaominh1997

from functools import wraps
import pandas as pd
import numpy as np
from pandas import DataFrame, Series


def inputvalidator(input_="ohlc"):
    def dfcheck(func):
        @wraps(func)
        def wrap(*args, **kwargs):

toandaominh1997

toandaominh1997

numpy
pandas
scipy
# visualization
matplotlib
seaborn
plotly
yellowbrick
# cloud service
google-cloud-bigquery

toandaominh1997

import threading

x = 0

def increament(): global x x +=1

def thread_task(lock): for _ in range(100000):
        lock.acquire() increament() lock.release()

def main_task(): global x x = 0 lock = threading.Lock() t1 = threading.Thread(target=thread_task, args=(lock, )) t2 = threading.Thread(target=thread_task, args=(lock, )) t3 = 

toandaominh1997

import threading

x = 0

def increament():
    global x
    x +=1

def thread_task(lock):
    for _ in range(100000):

toandaominh1997

{
    //
    // EDITOR CONFIG
    // 
    "editor.fontSize": 12,
    "editor.lineHeight": 0,
    "editor.lineNumbers": true,
    "editor.tabSize": 4,

toandaominh1997

class DBMongo{
    constructor(url){
        this.url = url
        this.MongoClient = require('mongodb').MongoClient;
    }

    createcollection(clt="hardware", dbase="mydb"){
        this.MongoClient.connect(this.url, function(err, db){
            if(err) throw err;
            var dbo = db.db(dbase)