Skip to content

Instantly share code, notes, and snippets.

View gjreda's full-sized avatar

Greg Reda gjreda

684 followers · 117 following
View GitHub Profile
@gjreda
gjreda / saban-seasons.py
Created November 11, 2018 01:39
Scraping Nick Saban's seasons as Alabama head coach
"""
Scraping Nick Saban's seasons as Alabama head coach
I was curious what % of his time Alabama has spent at #1
"""
from collections import Counter
from bs4 import BeautifulSoup
import requests
@gjreda
gjreda / towed.json
Created October 7, 2018 21:25
This file has been truncated, but you can view the full file.
[{"sid": 327097, "id": "031C6ADB-4539-4B7B-84DE-97C2E51D67DC", "position": 327097, "created_at": 1532611892, "created_meta": "878752", "updated_at": 1532611892, "updated_meta": "878752", "meta": null, "tow_date": "2018-07-25T00:00:00", "make": "JEEP", "style": "LL", "model": null, "color": "TAN", "plate": null, "state": null, "towed_to_address": "701 N. Sacramento", "tow_facility_phone": "(773) 265-7605", "inventory_number": "6929506"}, {"sid": 333929, "id": "D5B40DE5-805D-46A8-B9B4-76817ABF2540", "position": 333929, "created_at": 1535108478, "created_meta": "878752", "updated_at": 1535108478, "updated_meta": "878752", "meta": null, "tow_date": "2018-08-24T00:00:00", "make": "KIA", "style": "4D", "model": null, "color": "MAR", "plate": "AB95643", "state": "IL", "towed_to_address": "701 N. Sacramento", "tow_facility_phone": "(773) 265-7605", "inventory_number": "6932266"}, {"sid": 340538, "id": "B6A3FC62-8F7A-4AA6-B769-1CB0EC0BBC37", "position": 340538, "created_at": 1537569098, "created_meta": "878752", "upda
@gjreda
gjreda / senators.json
Last active July 21, 2018 14:06
{
"meta": {
"limit": 100,
"offset": 0,
"total_count": 100
},
"objects": [
{
"caucus": null,
"congress_numbers": [
@gjreda
gjreda / gjreda-tweets.csv
Created May 2, 2017 02:33
id text
805168201126518784 @ryanisaac this is the weirdest quarter of football I’ve seen in a while
804818096942968833 @SportsTribution I don't follow.
804816669281546240 Looking for a weekend longread? @samhinkie's resignation letter is still one of the best things I've read in 2016 https://t.co/y7464DISgX
804759041318813696 Have used Postico to query our Redshift cluster for the last few months and it's been great. Similar to Sequel Pro. https://t.co/NN0DvdCpa6
804699067590840320 @jrmontag @tanehisicoates Agreed. Important book.
804690839221964801 The Year of the Looking Glass: Building Products https://t.co/0MVAbxeSze
804469380352446464 "So how do we build trust? The easy answer is by producing high quality work. The hard part is how you get there." https://t.co/M4MgJYU2Wm
804015210621239297 Holywow this looks awesome. Continuously impressed by the data products the @awscloud team keeps churning out: https://t.co/jmkLqFjyn7
803734870706896896 RT @jevnin: I'd recommend working with this guy. https://t.
@gjreda
gjreda / gjreda-tweets.json
Created May 2, 2017 02:26
my (@gjreda) tweets
[
{
"id": "805168201126518784",
"text": "@ryanisaac this is the weirdest quarter of football I’ve seen in a while"
},
{
"id": "804818096942968833",
"text": "@SportsTribution I don't follow."
},
{
@gjreda
gjreda / useful-one-liners.sh
Last active April 11, 2017 03:45
Random bash one-liners that are useful but I always forget
# Installing/upgrading old requirements.txt from python2 to python3
sed s/\=/\ /g requirements.txt | awk '{print $1}' | xargs -n1 pip3 install --upgrade
@gjreda
gjreda / concurrent_futures_example.py
Created September 25, 2016 21:14
example of using Python3's concurrent.futures module
from concurrent.futures import ProcessPoolExecutor
import concurrent.futures
from halas.parsers import boxscore
GAMES = [ ... ]
results = []
with ProcessPoolExecutor(max_workers=4) as executor:
future_results = {executor.submit(boxscore, game):
@gjreda
gjreda / pandas-groupby-cumulative-count-with-reset.py
Last active August 2, 2016 14:51
days since last login -- pandas groupby cumulative count with reset
# for creating a column like "days since last login"
df = pd.read_clipboard(index_col=['customer_id', 'days'])
(df
.groupby(level='customer_id')
.did_login
.cumsum()
.to_frame()
.groupby(level='customer_id')
.apply(lambda g: g.groupby('did_login').cumcount())
@gjreda
gjreda / pandas-groupby-cumsum.py
Last active October 19, 2018 03:45
add grouped cumulative sum column to pandas dataframe
"""
add grouped cumulative sum column to pandas dataframe
Add a new column to a pandas dataframe which holds the cumulative sum for a given grouped window
Desired output:
user_id,day,session_minutes,cumulative_minutes
516530,0,NaN,0
516530,1,0,0
516532,0,5,5
@gjreda
gjreda / coding-music.md
Last active August 18, 2017 15:33
Music to code by