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Learning about knowledge graphs.

Shaurita Hutchins sdhutchins

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Learning about knowledge graphs.
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# 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)]
@sdhutchins
sdhutchins / parhttp.py
Created March 27, 2017 23:12 — forked from hoffrocket/parhttp.py
Python parallel http requests using multiprocessing
#!/usr/bin/env python
from multiprocessing import Process, Pool
import time
import urllib2
def millis():
return int(round(time.time() * 1000))
def http_get(url):
import yaml
import json
import pandas as pd
df = pd.DataFrame({'one': [1.0, 2.1, 3.2], 'two': [4.3, 5.4, 6.5]})
with open('df.yml', 'w') as file:
yaml.dump({'result': json.loads(df.to_json(orient='records'))}, file, default_flow_style=False)
@sdhutchins
sdhutchins / server.R
Created July 20, 2017 15:49 — forked from sidderb/server.R
A Shiny/R app to display the Illumina human body map dataset. I have not included the expression data due to it's size (19Gb) but this should work with any RNA-seq data set analysed with a TopHat->Cufflinks->CuffDiff pipeline.
library(shiny)
library(deSolve)
library(cummeRbund)
# load cuffDiff data, must be in top dir and called cuffData.db:
cuff = readCufflinks()
shinyServer(function(input,output) {
getData = reactive(function() {