aodin

## income_inequality_top1_murder_rate.csv

          
            country
            year
            murder_rate
            top1

            
              Afghanistan
              2018
              6.6555611518
              0.1508

            
              Albania
              2018
              2.2894924438
              0.0929

            
              Algeria
              2015
              1.3642763974
              0.0991

            
              Angola
              2012
              4.8470751765
              0.1958

            
              Argentina
              2018
              5.3244787387
              0.145

            
              Armenia
              2018
              1.693915557
              0.1746

            
              Australia
              2018
              0.89163240342
              0.0967

            
              Austria
              2018
              0.96722860774
              0.0982

            
              Azerbaijan
              2018
              2.2011074485
              0.1399

## us_metro_with_state_fips.csv

          
            CBSA
            Metro
            State
            Postal
            State FIPS

            
              10180
              Abilene, TX
              Texas
              TX
              48

            
              10380
              Aguadilla, PR
              Puerto Rico
              PR
              72

            
              10420
              Akron, OH
              Ohio
              OH
              39

            
              10500
              Albany, GA
              Georgia
              GA
              13

            
              10540
              Albany, OR
              Oregon
              OR
              41

            
              10580
              Albany-Schenectady-Troy, NY
              New York
              NY
              36

            
              10740
              Albuquerque, NM
              New Mexico
              NM
              35

            
              10780
              Alexandria, LA
              Louisiana
              LA
              22

            
              10900
              Allentown-Bethlehem-Easton, PA-NJ
              Pennsylvania
              PA
              42

## states_fips.csv

          
            State
            Postal
            FIPS

            
              Alabama
              AL
              1

            
              Alaska
              AK
              2

            
              Arizona
              AZ
              4

            
              Arkansas
              AR
              5

            
              California
              CA
              6

            
              Colorado
              CO
              8

            
              Connecticut
              CT
              9

            
              Delaware
              DE
              10

            
              District of Columbia
              DC
              11

## synesthesia.py
import colorsys

FNV_OFFSET = 0x811C9DC5  # 2166136261, FNV-1 32-bit offset basis
FNV_PRIME = 0x01000193  # FNV-1a 32-bit prime


def fnv1a_32(value: str) -> int:
    """
    Compute the FNV-1a (32-bit) hash of a given data string.
    https://en.wikipedia.org/wiki/Fowler–Noll–Vo_hash_function

## gist:9493190
package main

import (
	"encoding/json"
	"io/ioutil"
	"log"
	"net/http"
)

type Message struct {

## parse_nginx_access_log.py
"""
Parse an Nginx access.log file into a Pandas DataFrame. Also works with gzipped files.
"""
import argparse
import pathlib

import pandas as pd


parser = argparse.ArgumentParser()
country	year	murder_rate	top1
Afghanistan	2018	6.6555611518	0.1508
Albania	2018	2.2894924438	0.0929
Algeria	2015	1.3642763974	0.0991
Angola	2012	4.8470751765	0.1958
Argentina	2018	5.3244787387	0.145
Armenia	2018	1.693915557	0.1746
Australia	2018	0.89163240342	0.0967
Austria	2018	0.96722860774	0.0982
Azerbaijan	2018	2.2011074485	0.1399
CBSA	Metro	State	Postal	State FIPS
10180	Abilene, TX	Texas	TX	48
10380	Aguadilla, PR	Puerto Rico	PR	72
10420	Akron, OH	Ohio	OH	39
10500	Albany, GA	Georgia	GA	13
10540	Albany, OR	Oregon	OR	41
10580	Albany-Schenectady-Troy, NY	New York	NY	36
10740	Albuquerque, NM	New Mexico	NM	35
10780	Alexandria, LA	Louisiana	LA	22
10900	Allentown-Bethlehem-Easton, PA-NJ	Pennsylvania	PA	42
State	Postal	FIPS
Alabama	AL	1
Alaska	AK	2
Arizona	AZ	4
Arkansas	AR	5
California	CA	6
Colorado	CO	8
Connecticut	CT	9
Delaware	DE	10
District of Columbia	DC	11
	import colorsys

	FNV_OFFSET = 0x811C9DC5 # 2166136261, FNV-1 32-bit offset basis
	FNV_PRIME = 0x01000193 # FNV-1a 32-bit prime


	def fnv1a_32(value: str) -> int:
	"""
	Compute the FNV-1a (32-bit) hash of a given data string.
	https://en.wikipedia.org/wiki/Fowler–Noll–Vo_hash_function
	package main

	import (
	"encoding/json"
	"io/ioutil"
	"log"
	"net/http"
	)

	type Message struct {
	"""
	Parse an Nginx access.log file into a Pandas DataFrame. Also works with gzipped files.
	"""
	import argparse
	import pathlib

	import pandas as pd


	parser = argparse.ArgumentParser()