Grant Williams grantmwilliams

## df_plot_example.ipynb

      
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                grantmwilliams
                / df_plot_example.ipynb
            
            
              Created
              March 25, 2022 18:41
            
              
                Example showing common plotting problems with bar charts in pandas data frames
              
          
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## example.py
import pyarrow as pa
import pyarrow.parquet as pq

file_name_mapping = {
    pa.int32(): "int32",
    pa.uint32(): "uint32",
    pa.int64(): "int64",
    pa.uint64(): "uint64"
}

## iter_parquet.py
import s3fs
import pyarrow as pa
import pyarrow.parquet as pq


from itertools import chain
from typing import Tuple, Any

def iter_parquet(s3_uri: str, columns = None, batch_size=1_000) -> Tuple[Any]:

## Decision_Tree_Classifier_Example.py
""" This file uses a decision tree to classify the input data
and then loads the appropriate auxiliary dataset from the classification result

Uses SKlearn's  decision tree implementation and as an example the
SKlearn iris dataset
"""
import sys
import numpy as np # only used to create our example datasets.
import pandas as pd # only used to create our example datasets.
from sklearn.datasets import load_iris

## Captain Prime.erl
-module(solution).
-export([main/0]).

% 1. If contains a "0" return DEAD
% 2. Use Deterministic Miller-Rabin Primality To Check Primality
% 3. If stripping from Left and Right gives primes return "CENTRAL"
% 4. Else If stripping from Left gives primes return "LEFT"
% 5. Else If stripping from Right gives primes return "RIGHT"
% 6. Else Return "DEAD"

## pe7.cpp
#include <iostream>
#include <vector>
#include <cmath> // std::sqrt
#include <algorithm> // std::fill
#include <chrono>

// implementation of sieve of eratosthenes.
long get_primes(const unsigned long limit)
{
    int count_lim = 10001;

## euler7_pueso_code
arr[10001] = {0}
count = 1;
arr[0] = 2;
num = 2;
bool is_prime;
while (count < 10001) //  loop through all numbers
{
  num++; // starts with 3

  is_prime = true; // sets the number to prime unless we find otherwise

## pe77.cpp
std::vector<int> get_primes(int limit)
{
    std::vector<char> primes(limit + 1, 1);
    std::vector<int> final;

    // 0 and 1 are nonprime by definition
    primes[0] = 0; primes[1] = 0;

    for (int i = 2; i * i <= limit; i++)
    {

## sieve_of_eratosthenes.cpp
std::vector<int> get_primes(int limit)
{
    std::vector<char> primes(limit, 1);
    std::vector<int> final;

    // 0 and 1 are nonprime by definition
    primes[0] = 0; primes[1] = 0;

    for (int i = 2; i * i <= limit; i++)
    {

## fib_method.cpp
// fib_method.cpp -- Grant Williams \\

#include <stdio.h>
#include <fstream>
#include <math.h>
using namespace std;

//Uses matrix operations \\

void multiply(int F[2][2], int M[2][2]);
	import pyarrow as pa
	import pyarrow.parquet as pq

	file_name_mapping = {
	pa.int32(): "int32",
	pa.uint32(): "uint32",
	pa.int64(): "int64",
	pa.uint64(): "uint64"
	}
	import s3fs
	import pyarrow as pa
	import pyarrow.parquet as pq


	from itertools import chain
	from typing import Tuple, Any

	def iter_parquet(s3_uri: str, columns = None, batch_size=1_000) -> Tuple[Any]:
	""" This file uses a decision tree to classify the input data
	and then loads the appropriate auxiliary dataset from the classification result

	Uses SKlearn's decision tree implementation and as an example the
	SKlearn iris dataset
	"""
	import sys
	import numpy as np # only used to create our example datasets.
	import pandas as pd # only used to create our example datasets.
	from sklearn.datasets import load_iris
	-module(solution).
	-export([main/0]).

	% 1. If contains a "0" return DEAD
	% 2. Use Deterministic Miller-Rabin Primality To Check Primality
	% 3. If stripping from Left and Right gives primes return "CENTRAL"
	% 4. Else If stripping from Left gives primes return "LEFT"
	% 5. Else If stripping from Right gives primes return "RIGHT"
	% 6. Else Return "DEAD"
	#include <iostream>
	#include <vector>
	#include <cmath> // std::sqrt
	#include <algorithm> // std::fill
	#include <chrono>

	// implementation of sieve of eratosthenes.
	long get_primes(const unsigned long limit)
	{
	int count_lim = 10001;
	arr[10001] = {0}
	count = 1;
	arr[0] = 2;
	num = 2;
	bool is_prime;
	while (count < 10001) // loop through all numbers
	{
	num++; // starts with 3

	is_prime = true; // sets the number to prime unless we find otherwise
	std::vector<int> get_primes(int limit)
	{
	std::vector<char> primes(limit + 1, 1);
	std::vector<int> final;

	// 0 and 1 are nonprime by definition
	primes[0] = 0; primes[1] = 0;

	for (int i = 2; i * i <= limit; i++)
	{
	std::vector<int> get_primes(int limit)
	{
	std::vector<char> primes(limit, 1);
	std::vector<int> final;

	// 0 and 1 are nonprime by definition
	primes[0] = 0; primes[1] = 0;

	for (int i = 2; i * i <= limit; i++)
	{
	// fib_method.cpp -- Grant Williams \\

	#include <stdio.h>
	#include <fstream>
	#include <math.h>
	using namespace std;

	//Uses matrix operations \\

	void multiply(int F[2][2], int M[2][2]);