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General Snippets

1. Prime Factors of a number

• Step1 : divide number by 2 and add 2 as factor till possible
• Step2 : Start k from 3 with step of 2 till sqrt(number), divide number by k and add k as factor till possible
• Step3 : Check if number remaining is greater than 1, add that number as another factor.

def getPrimeFactors(n):
    factors = []
    while n%2==0:
        factors.append(2)

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"""
Author : Aditya Jain
Contact: https://adityajn105.github.io
"""
import gym
import numpy as np
#create game
game = gym.make('FrozenLake-v0')

#get game env object

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/*
 * Scala - Scalable Language, hybrid functional Programming language
 * Integrates features of OOP and functional languages
 * Compliled on JVM
 * Can use all classes of JAVA SDK and also own custom classes
 * Some different features from JAVA
 * 1. All types are objects
 * 2. Tpye inference
 * 3. Nested Functions

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Axis in Dataframes

1. Axis 0 means along row ( for a particular feature of all samples ) |/
2. Axis 1 means along columns (of a particular sample for all features ) --->
3. Remember this by a matrix 2x3 matrix. Here axis 0 has length 2 and axis 1 has length 1

Groupby

1. Perform aggregation on one or more than one columns
2. If more than one column in used then it is considered as multi-indexing

df.groupby( columns ).colname.aggfunc()

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from bs4 import BeautifulSoup
import urllib3
import re
import pandas as pd

http = urllib3.PoolManager()

link = "https://www.sitejabber.com/reviews/dream11.com"

#making http get request

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System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

1. Clarify and agree on the scope of the system

• User cases (description of sequences of events that, taken together, lead to a system doing something useful)
  • Who is going to use it?
  • How are they going to use it?

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def settleDebt(debt_dict):
    """
    Function to settle debt among group of people
    
    Parameters
    ----------
    debt_dict : dictionary of names and debt(expenses-paid)
        sum of debts should be approximately zero
        -ve means negative debt, +ve means positive debt
    

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from flask import Flask, request
from werkzeug import secure_filename
import os

app = Flask(__name__)
app.config['UPLOAD_FOLDER'] = os.path.join(app.root_path,'uploads/')
if not os.path.exists(app.config['UPLOAD_FOLDER']): os.mkdir(app.config['UPLOAD_FOLDER']) 

def make_page(notification=""):
	return f"""

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# Decile chart, LIFT, KS 
def getDeciles(models, X, y, n=10):
    probs = predict_probas(gbms,X)[:,1]
    cuts =  pd.qcut(probs,n)
    df = pd.DataFrame({'DECILE':cuts,"P":probs,'Y':y}).groupby('DECILE').Y.value_counts().unstack(fill_value=0)[::-1]
    df.index = [ f"{i+1} {df.index[i]}" for i in range(n) ]
    df.columns = ['ZEROS','ONES']
    df['POPULATION'] = df.ZEROS+df.ONES
    df['EVENT_RATE'] = df.ONES/df.POPULATION
    df['CUMULATIVE_EVENT_RATE'] = df.ONES.cumsum()/df.POPULATION.cumsum()