seanickle

scatter plot

• Plot x vs y , w/ color based on the hue.

%matplotlib inline

import seaborn as sns
import pandas as pd

# Quick scatter plot
df = pd.read_csv(filename)

seanickle

remote-pdb

• https://pypi.python.org/pypi/remote-pdb

• pip install remote-pdb

• usage:

from remote_pdb import RemotePdb; RemotePdb('127.0.0.1', 4444).set_trace()

seanickle

nice pattern for counting after a groupby without dealing with the MultiIndex .

• First apply the x if not pd.isnull(x) else 'NaN' mapping function concept to columns which have np.nan in them.
• (that might not be necessary in pandas 0.17.1 not sure yet. )
• This feels like a really obvious function combo now in retrospect.

Out[194]: (16037, 21)

• After writing custom ways to do it finally came across the df[cols].groupby(by=colx).size().reset_index() combo …

seanickle

similar to ipdb, pdb

from celery.contrib import rdb
rdb.set_trace()

a

netstat -plant|grep LIST 

seanickle

def get_all_issue_events(issue_id):
    url = 'https://app.getsentry.com/api/0/issues/%s/events/' % issue_id
    all_data = get_all_data(url)
    return all_data


def get_all_data(url):

seanickle

get_tag_migrations () {

    last_n=$1
    migrations_directory=$2
    tags=($(git tag --sort version:refname | egrep '^[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}$'))
    begin=`expr ${#tags[@]} - ${last_n}`
    subset_tags=(${tags[@]:${begin}})
    
    for (( i=0; i< `expr ${#subset_tags[@]} - 1` ; i+=1 )) ;   # forwards
    do