olp-cs

## test-type-error.ipynb

      
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              July 16, 2024 10:15
            
              
                GEOparse - Failing test: `test_merge_and_average` fails with a TypeError
              
          
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## network_viz.r
library(igraph)		        # to work with graphs
library(RColorBrewer)    	# to use a color palette
library(plotrix) 	      	# to rescale variables


# Read the data
raw_data <- read.csv("network_data.csv")
names(raw_data) <- c("Source", "Target", "Count", "Money")

# reformat data for igraph library

## function_lengths.py
import os
import sys

import numpy as np
import matplotlib.pyplot as plt

from pandas import DataFrame
from pandas.util.testing import set_trace

dirs = []

## print_cm.py
from sklearn.metrics import confusion_matrix

def print_cm(cm, labels, hide_zeroes=False, hide_diagonal=False, hide_threshold=None):
    """pretty print for confusion matrixes"""
    columnwidth = max([len(x) for x in labels]+[5]) # 5 is value length
    empty_cell = " " * columnwidth
    # Print header
    print "    " + empty_cell,
    for label in labels:
        print "%{0}s".format(columnwidth) % label,

## gist:8ac9e6e6f82d8e21cebe

      
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                olp-cs
                / gist:8ac9e6e6f82d8e21cebe
            
            
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              September 10, 2015 19:25
                — forked from debasishg/gist:8172796
            
              
                A collection of links for streaming algorithms and data structures
              
          
General Background and Overview


Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
Models and Issues in Data Stream Systems
Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
[Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&amp;rep


## bokeh.ipynb

      
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                olp-cs
                / bokeh.ipynb
            
            
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              August 29, 2015 13:59
            
              
                https://raw.githubusercontent.com/ContinuumIO/bokeh/master/examples/plotting/notebook/glucose.ipynb
              
          
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## test.json
{
 "metadata": {
  "name": "exploring_a_single_data_file"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

## corpus-linguistics.md

      
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                olp-cs
                / corpus-linguistics.md
            
            
              Created
              December 30, 2013 13:35
            
              
                Corpus linguistics: method, analysis, interpretation - A Seasonal, Corpus Linguistics, Gift!
              
          
    Corpus linguistics: method, analysis, interpretation - A Seasonal, Corpus Linguistics, Gift!
FutureLearn please.do.not.reply@futurelearn.com
Dec 24 (6 days ago)
Well, in the UK it is Christmas Eve and the giving of presents will begin in the morning. So I thought I would start a little early and send you a note to say what the Corpus Linguistics course has in store for you in 2014! OK – a very academic present, I know, but I think it is one you will appreciate. Each week will be split into four. There will be an introductory lecture on a topic, one or more advanced lectures covering similar topics (or just plain interesting topics), a ‘how to’ session where you can develop corpus searching and building skills and, last but not least, one or more ‘in conversation’ videos where I talk to a friend about their use of corpus linguistics. Some of this you know if you have been following my emails and tweets so far (for those of you who are not but would like to follow the tweets follow me @TonyMcEn

  
## python-study-group.md

      
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              November 18, 2016 11:35
            
              
                Учебная группа по Python: скайп-чат
              
          
    Учебная группа по Python: скайп-чат

Ссылка на скайп-чат

skype:?chat&blob=hMiRW3mVON1wnwnIEefLw2U5HrI-NeHRiPLX_til6rAVsSIr1oYX0NZboKY6PPMnxQfbTGxA7tK5D9HwnjIRWo42_HcyU6aGTWTAZRM_k_kvj8IqFwBl-qJOjDEcSoWeJCHND8o6ltmHl_TEgCMmssW84IZIT73H68Ppl80oe6UGSziKYzst-WK_Bz9Ws_TV4A

Как присоединиться к скайп-чату


Попробуйте открыть ссылку в каком-нибудь браузере (например, Firefox). Должен открыться Skype с окном чата.


## head.html
> head(simplyStats)

[1] "<!DOCTYPE html>"
[2] "<script>var __pbpa = true;</script><script>var translated_warning_string = 'Warning: Never enter your Tumblr password unless \\u201chttps://www.tumblr.com/login\\u201d\\x0ais the address in your web browser.\\x0a\\x0aYou should also see a green \\u201cTumblr, Inc.\\u201d identification in the address bar.\\x
	library(igraph) # to work with graphs
	library(RColorBrewer) # to use a color palette
	library(plotrix) # to rescale variables


	# Read the data
	raw_data <- read.csv("network_data.csv")
	names(raw_data) <- c("Source", "Target", "Count", "Money")

	# reformat data for igraph library
	import os
	import sys

	import numpy as np
	import matplotlib.pyplot as plt

	from pandas import DataFrame
	from pandas.util.testing import set_trace

	dirs = []
	from sklearn.metrics import confusion_matrix

	def print_cm(cm, labels, hide_zeroes=False, hide_diagonal=False, hide_threshold=None):
	"""pretty print for confusion matrixes"""
	columnwidth = max([len(x) for x in labels]+[5]) # 5 is value length
	empty_cell = " " * columnwidth
	# Print header
	print " " + empty_cell,
	for label in labels:
	print "%{0}s".format(columnwidth) % label,
	{
	"metadata": {
	"name": "exploring_a_single_data_file"
	},
	"nbformat": 3,
	"nbformat_minor": 0,
	"worksheets": [
	{
	"cells": [
	{
	> head(simplyStats)

	[1] "<!DOCTYPE html>"
	[2] "<script>var __pbpa = true;</script><script>var translated_warning_string = 'Warning: Never enter your Tumblr password unless \\u201chttps://www.tumblr.com/login\\u201d\\x0ais the address in your web browser.\\x0a\\x0aYou should also see a green \\u201cTumblr, Inc.\\u201d identification in the address bar.\\x