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/*
 * sor_iteration.c
 *
 *  Created on: Jul 7, 2014
 *      Author: du
 */

#include <stdio.h>
#include <string.h>
#include <math.h>

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#!/usr/bin/env pypy
# -*- coding: utf-8 -*-
'''
Created on 2013/09/03

@author: Shiqiao Du

run
cat <input> | ./mapred.py -m mapper | sort | ./mapred.py -m reducer
'''

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$ conda remove readline
$ pip install readline

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# postgresユーザーのパスワードを変更
sudo passwd postgres

# 新しいユーザーを作成
sudo -u postgres createuser du -P --interactive

# DBの作成
create databese test_db owner du

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import pandas as pd
import sqlalchemy
from sklearn import datasets

# create iris dataframe
iris = datasets.load_iris()
iris_data = pd.DataFrame(iris.data)
iris_data.columns = ["sep_length", "sepal_width","petal_length","petal_width" ]
iris_data["species"] = map(lambda i:iris.target_names[i], iris.target)

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from gdata.spreadsheet import service, text_db
client = text_db.DatabaseClient(username=user, password=password)
db = client.GetDatabases(name=spreadsheet_name)[0]
table = db.GetTables(name=worksheet_name)[0]

# notice that even if it is shown as some thing like "DD/MM/YY" in the table, timestamp or date should be YYYY-MM-DD 
for row in table.FindRecords("timestamp > 2014-10-01"):
    print row.content

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# -*- coding: utf-8 -*-

import datetime

from numpy import asarray, ceil
import pandas
import rpy2.robjects as robjects

def stl(data, ns, np=None, nt=None, nl=None, isdeg=0, itdeg=1, ildeg=1,
        nsjump=None, ntjump=None, nljump=None, ni=2, no=0, fulloutput=False):

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%matplotlib inline
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt

plt.style.use("ggplot")
plt.rcParams["font.size"] = 14
plt.rcParams["figure.figsize"] = 10, 6

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$(function () {

    $(document).ready(function () {

        // Build the chart
        Highcharts.setOptions({
            colors: ['#4572A7', '#AA4643', '#89A54E', '#80699B', '#3D96AE', '#DB843D', '#92A8CD', '#A47D7C', '#B5CA92', '#0000cd', '#dda0dd']
        });

        $('#container').highcharts({

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def colorHist(img):
    size = img.size / 3.0
    ret = {}
    color = ('b','g','r')
    for i,col in enumerate(color):
        histr = cv2.calcHist([img],[i],None,[100],[0,256])
        ret[col] = histr.flatten() / size
    return ret