mathcass

def build_equivalence_classes(a_collection, comparer):
    """Given a collection of items that can be compared,
    and a comparer for those items, return a new collection
    of sublists that are equivalence classes of items in the
    original collection.

    """

    classes = []
    accounted_for = [False] * len(a_collection)

mathcass

# You can call this with:
# make -j N all_csv
# where N can be the number of processors you wish to use in parallel


# This Make rule uses the Python script `tsv2csv.py` to turn the first argument (the .tsv file) and dumps it to the output file
%.csv: %.tsv
        python tsv2csv.py $< > $@

# This gets all files in this directory that end in .tsv

mathcass

#!/usr/bin/env python

import pandas as pd
from sklearn.ensemble import RandomForestClassifier


@profile
def infinite_loading():
    """Exceeds available memory"""
    train = pd.read_csv('big.csv')

mathcass

I hereby claim:

• I am mathcass on github.
• I am mathcass (https://keybase.io/mathcass) on keybase.
• I have a public key ASBURwDb_4-jp5hUjLFgtQbaLz9CbS1fMxQL3pNEFfZO2go

To claim this, I am signing this object:

{

mathcass

#!/bin/bash

# Deploys application to default service setting version to current time, thus
# mimicking how `gcloud app deploy` works

APP="$PROJECT_NAME"  # Or, just replace with your project
VERSION=$(date +%Y%m%dt%H%M%S) # ${year}${month}${day}t${24hour}${minute}${second}

gcloud config set project "$APP"

mathcass

alias alert='notify-send --urgency=low -i "$([ $? = 0 ] && echo terminal || echo error)" "$(history|tail -n1|sed -e '\''s/^\s*[0-9]\+\s*//;s/[;&|]\s*alert$//'\'')"'
alias egrep='egrep --color=auto'
alias fgrep='fgrep --color=auto'
alias grep='grep --color=auto'
alias l='ls -CF'
alias la='ls -A'
alias ll='ls -alF'
alias ls='ls --color=auto'

mathcass

// javascript:(function(){// your code here })();
// document.activeElement.value = '2018-03-23-cp-.ipynb'

javascript:(function () {


initials = 'cp';
d = new Date();
dateStr = d.toISOString().slice(0, 10);
notebookTpl = dateStr + '-' + initials + '-.ipynb';

mathcass

pip freeze | xargs -L1 pip uninstall -y

mathcass

// Demonstrates how to do "lazy" JSON Unmarshaling if you suspect that the main
// JSON container is formatted correctly but some sub-items may not be formatted
// correctly.

package main

import (
	"encoding/json"
	"log"
)

mathcass