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# The Best Medium-Hard Data Analyst SQL Interview Questions  

By Zachary Thomas ([zthomas.nc@gmail.com](mailto:zthomas.nc@gmail.com), [Twitter](https://twitter.com/zach_i_thomas), [LinkedIn](https://www.linkedin.com/in/thomaszi/)) 

**Tip: **See the Table of Contents (document outline) by hovering over the vertical line on the right side of the page 

## Background & Motivation

> The first 70% of SQL is pretty straightforward but the remaining 30% can be pretty tricky.

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# Start a Scylla cluster
########################

docker run --name some-scylla -d scylladb/scylla --smp 1 --memory 750M --overprovisioned 1 --api-address 0.0.0.0
# Do not use the above --api-address for production. Exposing API IP is not secure.
SEED=$(docker inspect --format='{{ .NetworkSettings.IPAddress }}' some-scylla)
echo $SEED
docker run --name some-scylla2 -d scylladb/scylla --smp 1 --memory 750M --overprovisioned 1 --api-address 0.0.0.0 --seeds="$SEED"
docker run --name some-scylla3 -d scylladb/scylla --smp 1 --memory 750M --overprovisioned 1 --api-address 0.0.0.0 --seeds="$SEED"

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Using Windows Subsystem for Linux combined with Docker for Windows

Docker CE for Windows

• Install Docker CE for Windows
• Go to Docker for Windows Settings -> General and enable Expose daemon on tcp://localhost:2375 without TLS.
  This will enable the Docker remote API for requests, coming from localhost, not from another computer in your network. A TLS secured version is not yet supported in Docker for Windows. See docker/for-win#453 for more information. I also tried a daemon.json file with options tlscacert, tlscert, tlskey and tlsverify, but Docker for Windows crashed on booting.

Install Windows Subsystem for Linux (WSL)

• Enable Developer Mode as described in Enable your device for development
• Install WSL by running the following in Powershell as Administrator: `E

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import streamlit as st
import pandas as pd
import numpy as np

def display_dataframe_quickly(df, max_rows=5000, **st_dataframe_kwargs):
    """Display a subset of a DataFrame or Numpy Array to speed up app renders.
    
    Parameters
    ----------
    df : DataFrame | ndarray

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#!/usr/bin/python
import re
import sys

def removeComments(text):
    """ remove c-style comments.
        text: blob of text with comments (can include newlines)
        returns: text with comments removed
    """
    pattern = r"""

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# -*- coding: utf-8 -*-

import datetime

from numpy import asarray, ceil
import pandas
import rpy2.robjects as robjects

def stl(data, ns, np=None, nt=None, nl=None, isdeg=0, itdeg=1, ildeg=1,
        nsjump=None, ntjump=None, nljump=None, ni=2, no=0, fulloutput=False):

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What

Roll your own iPython Notebook server with Amazon Web Services (EC2) using their Free Tier.

What are we using? What do you need?

• An active AWS account. First time sign-ups are eligible for the free tier for a year
• One Micro Tier EC2 Instance
• With AWS we will use the stock Ubuntu Server AMI and customize it.
• Anaconda for Python.
• Coffee/Beer/Time

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#!/usr/bin/env python
# Author: Chris Eberle <eberle1080@gmail.com>
# Watch for any changes in a module or package, and reload it automatically

import pyinotify
import imp
import os

class ModuleWatcher(pyinotify.ProcessEvent):
    """