This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# Brute Force D20 Roll Simulator | |
# Import random module | |
import random | |
# Create a variable with a TRUE value | |
rolling = True | |
# while rolling is true | |
while rolling: |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# coding: utf-8 | |
# # Map Your Google Location History | |
# | |
# ## Step 1: Download your Google Location History | |
# | |
# Google makes this process very easy. Go here to [download your location history data](https://www.google.com/settings/takeout) and unzip it. | |
# ## Step 2: Run this script |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
{ | |
"metadata": { | |
"name": "", | |
"signature": "sha256:c3353bdfe380793a0b7eb927af7533bc567dd752cb852517d89eac65a196723b" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
{ | |
"metadata": { | |
"name": "", | |
"signature": "sha256:63da596dd1a5eb6dfdf934f5552fb0616c2fd21bf522ac0cafe519eda3351981" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
{ | |
"total": 46830, | |
"data": [ | |
{ | |
"remoteID": "44268-1248", | |
"tags": [ | |
{ | |
"confidence": 1, | |
"name": "Furniture" | |
} |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import numpy as np | |
x = ['Family Practice', 'Internal Medicine', 'Family Practice', 'Family Practice'] | |
y = [0,0,0,1] | |
score = 0 | |
def hardcoded_rules(x,y,score): | |
if len(x) < 3 and max(y) < 3: | |
score = -1 | |
elif np.unique(y)[0] == 1: |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Testing Popily Embeds In Project Jupyter" | |
] | |
}, | |
{ |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
{'Alabama': 4849377, | |
'Alaska': 736732, | |
'Arizona': 6731484, | |
'Arkansas': 2966369, | |
'California': 38802500, | |
'Colorado': 5355866, | |
'Connecticut': 3596677, | |
'Delaware': 935614, | |
'District of Columbia': 658893, | |
'Florida': 19893297, |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import pandas as pd | |
index = pd.date_range('1/1/2000', periods=20000, freq='30min') | |
series = pd.Series(range(20000), index=index) | |
series.groupby(series.index.hour).sum() |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
### Keybase proof | |
I hereby claim: | |
* I am chrisalbon on github. | |
* I am chrisalbon (https://keybase.io/chrisalbon) on keybase. | |
* I have a public key ASBI8zFqR11PMiDce5FTxa7M57P8WLTxMkdLD-tt72qjjAo | |
To claim this, I am signing this object: |
OlderNewer