abehmiel

function toTitleCase(str)
{
    return str.replace(/\w\S*/g, function(txt){return txt.charAt(0).toUpperCase() + txt.substr(1).toLowerCase();});
}

abehmiel

import pandas as pd
from datetime import datetime, date

"""
Cleaning time!

This script will clean data downloaded from the fitbit website.
A little bit of preprocessing is useful. First, Separate the activities 
and sleep data into different csv files and make sure there's only 
one header row in each. Multiple months may be concatenated together, 

abehmiel

Monday, May 22

Weather/Transportation

Rainy. I took the 6 from GCS to Canal St and walked about 4 blocks.

Plans

General

Intense! Met a lot of people!

abehmiel

import requests

headers = {"token": "API TOKEN"}
params = {"something": "SOMETHING"}

response = requests.get("https://www.something.com", headers=headers, params=params)
json_data = response.json()
status = response.status_code

abehmiel

some_dict = {'one': 1, 'two':2, 'three': 3480394803840, 'four': 4}
max_key = max(some_dict, key=some_dict.get)

abehmiel

# Thanks to Chris Albon. Shamelessly lifted from: https://chrisalbon.com/python/pandas_dataframe_importing_csv.html

import pandas as pd
import numpy as np

# Create dataframe (that we will be importing)
raw_data = {'first_name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'],
        'last_name': ['Miller', 'Jacobson', ".", 'Milner', 'Cooze'],
        'age': [42, 52, 36, 24, 73],
        'preTestScore': [4, 24, 31, ".", "."],

abehmiel

-- pico-8 starter code
-- by @hypirlink

-- _init() is called when 
-- you 'run' the program
function _init()
 -- states: menu, game, end
 state = "menu"
end

abehmiel

#!/bin/sh

gifsicle --resize 120x120 file.gif > out-120.gif

abehmiel

# List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

# Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

# Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(valuelist)]

abehmiel

col1 = (0/255.,107/255.,164/255.)    # dark blue
col2 = (255/255.,128/255.,14/255.)   # orange
col3 = (171/255.,171/255.,171/255.)  # half-gray
col4 = (89/255.,89/255.,89/255.)     # mostly gray
col5 = (95/255.,158/255.,209/255.)   # sky blue
col6 = (200/255.,82/255.,0/255.)     # burnt sienna
col7 = (137/255.,137/255.,137/255.)  # 3/4 gray
col8 = (162/255.,200/255.,236/255.)  # periwinkle
col9 = (255/255.,188/255.,121/255.)  # peach
col10 = (207/255.,207/255.,207/255.) # 1/4 gray