Next Page: 10000

          Research Associate (Full Stack/Data Visualization Developer) - Singapore University of Technology and Design - Changi      Cache   Translate Page   Web Page Cache   
Vue.js and d3.js do the heavy lifting on the frontend, while our backend software is mostly written in node.js and R (tidyverse)....
From Singapore University of Technology and Design - Fri, 20 Jul 2018 11:19:29 GMT - View all Changi jobs
          Front End Reactive Functional Engineer - DNAnexus - Mount View, WI      Cache   Translate Page   Web Page Cache   
Good sense of visual and interaction design, data visualization experience a plus. Key investors include Google Ventures, Foresite Capital, TPG Biotech, and...
From DNAnexus - Thu, 14 Jun 2018 20:33:02 GMT - View all Mount View, WI jobs
          Research Associate (Full Stack/Data Visualization Developer) - Singapore University of Technology and Design - Changi      Cache   Translate Page   Web Page Cache   
Vue.js and d3.js do the heavy lifting on the frontend, while our backend software is mostly written in node.js and R (tidyverse)....
From Singapore University of Technology and Design - Fri, 20 Jul 2018 11:19:29 GMT - View all Changi jobs
          Front End Reactive Functional Engineer - DNAnexus - Mount View, WI      Cache   Translate Page   Web Page Cache   
Good sense of visual and interaction design, data visualization experience a plus. Key investors include Google Ventures, Foresite Capital, TPG Biotech, and...
From DNAnexus - Thu, 14 Jun 2018 20:33:02 GMT - View all Mount View, WI jobs
          Aug 15, 2018: Jupyter Notebooks at Snell Library      Cache   Translate Page   Web Page Cache   

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

This session will introduce you to Jupyter Notebooks and we will spend time installing Jupyter Notebooks locally.

View on site | Email this event


          Lecturer,Asst - University of Wyoming - Laramie, WY      Cache   Translate Page   Web Page Cache   
Strong statistical and psychometric knowledge, e.g., multiple regression, logistic regression, data visualization, relational databases, SQL, IRT,...
From University of Wyoming - Sat, 04 Aug 2018 15:48:20 GMT - View all Laramie, WY jobs
          Tableau Developer      Cache   Translate Page   Web Page Cache   
AZ-Phoenix, Tableau Developer Eclaro is looking for a Tableau Developer for our client in Phoenix, AZ. Qualifications: Business Intelligence experience, with Tableau Desktop and Tableau Server Years of demonstrated hands-on development experience with Tableau Strong experience in design and development of building Tableau reports and dashboards Proficiency in data visualization, dashboard design, and workflow
          Lecturer,Asst - University of Wyoming - Laramie, WY      Cache   Translate Page   Web Page Cache   
Strong statistical and psychometric knowledge, e.g., multiple regression, logistic regression, data visualization, relational databases, SQL, IRT,...
From University of Wyoming - Sat, 04 Aug 2018 15:48:20 GMT - View all Laramie, WY jobs
          Update: Mobikul Opencart Marketplace (Shopping)      Cache   Translate Page   Web Page Cache   

Mobikul Opencart Marketplace 1.19


Device: iOS Universal
Category: Shopping
Price: Free, Version: 1.17 -> 1.19 (iTunes)

Description:

Mobikul marketplace is a OpenCart mobile application for OpenCart based Marketplace websites. By installing mobikul marketplace your customers can access your marketplace on the go. Your Store's Customers can access their whole Account information and can also edit it, and also can view all sellers information for particular productand can also contact to sellers.

Your Store's Sellers can view their, order history and dashboard, they can also contact the admin from the mobile app.

In mobikul marketplace mobile app we have given separate seller product collection page and separate seller with feedback support rating and commissions.

Currently all the products, customer, category, etc (including all the data visible on mobile) are synced with the website http://oc.webkul.com/mobikul/MP/.

To check Admin click http://oc.webkul.com/mobikul/Network/MP/index.php

Highlighted Features are :
1. Seller List.
2. Seller Profile.
3. Seller Dashboard.
4. Seller Order History.
5. Invoice Creation and Credit Memo.
6. Seller Location on Map.
7. Marketplace Landing Page.
8. Can Review Sellers.
9. Seller Collection Page.
10. Seller Details on Product Page.
11. Localization (multi lingual support).
12. Push Notification.

You can buy Mobikul Marketplace from here https://store.webkul.com/mobikul-marketplace.html
For the customization of this app drop us mail at support@webkul.com

Mobikul Marketplace OpenCart Mobile Application is pre-build mobile app you just need to configure it with you OpenCart store through soap api(web service), change app name, replace app icon and banner with your store icon and banner and just release it on play store.

This configuration can be done by yourself, or we can do it for you.


"Continued use of GPS running in the background can dramatically decrease battery life."

What's New

fix minor bugs

Mobikul Opencart Marketplace


          Lecturer,Asst - University of Wyoming - Laramie, WY      Cache   Translate Page   Web Page Cache   
Strong statistical and psychometric knowledge, e.g., multiple regression, logistic regression, data visualization, relational databases, SQL, IRT,...
From University of Wyoming - Sat, 04 Aug 2018 15:48:20 GMT - View all Laramie, WY jobs
          Telecommute Senior Business Analytics Analyst      Cache   Translate Page   Web Page Cache   
A real estate company is searching for a person to fill their position for a Telecommute Senior Business Analytics Analyst. Core Responsibilities Include: Performing technical lead and project manager responsibilities for business intelligence projects Creating, maintaining and optimizing creative data visualizations and dashboards Aggregating and analyzing quantitative data Applicants must meet the following qualifications: Bachelor's degree (BA/BS) from four-year college or university Minimum 5+ years of related experience Excellent data management, manipulation, and analysis skills Advanced Tableau skills
          SQL Server 2017 Machine Learning services with R book      Cache   Translate Page   Web Page Cache   

This blog post is slighty different, since it brings you the tittle of the book , that my dear friend Julie Koesmarno ( blog | twitter ) and I have written in and it was published in March 2018 at Packt Publishing .


SQL Server 2017 Machine Learning services with R book

Book covers the aspect of the R Machine Learning services available in Microsoft SQL Server 2017 (and 2016), how to start, handle and operationalise R code, deploy and manage your predictive models and how to bring the complete solution to your enterprise environment. Exploring the CD/CI, diving into examples supporting RevoScaleR algorithms , bringing closer the data science to database administrators and data analysts.

More specifically, content of the book is following (as noted in table of content):

1: Introduction to R and SQL Server

2: Overview of Microsoft Machine Learning Server and SQL Server

3: Managing Machine Learning Services for SQL Server 2017 and R

4: Data Exploration and Data Visualization

5: RevoScaleR Package

6: Predictive Modeling

7: Operationalizing R Code

8: Deploying, Managing, and Monitoring Database Solutions containing R Code

9: Machine Learning Services with R for DBAs

10: R and SQL Server 2016/2017 Features Extended

My dear friend, co-author and long time SQL Server community dedicated tech and data science lover, Julie and myself, we had great time working on this book, sharing the code, the ideas and collaborating on what was the great end product. Thank you, Julie.

I would also like to thank all the people involved, with their help, expertise, inspirations, people at the Packt Publishing, to Hamish Watson and also a special thanks, to you, Marlon Ribunal ( blog | twitter ), for your reviews and comments in the time of the writing and your review and to you, dear David Wentzel ( website | linkedin ) for your chapter comments and your review .

Finally, thank you Microsoft SQL Server community, SQL friends and SQL family, R community and R Consortium , and the Revolution Analytics community, gather and led by David Smith ( twitter ). Not only did this concept of R in Microsoft SQL Server, but also the intersection of technologies brought together so many beautiful people, minds and ideas, that will in future time help so many business and industries world-wide.

Much appreciated!

Book is available on Amazon or you can get your copy at the Packt .

Happy reading and coding!


          (USA-TX-Irving) Tableau Developer      Cache   Translate Page   Web Page Cache   
**Tableau Developer in Irving, TX at Volt** # Date Posted: _8/9/2018_ # Job Snapshot + **Employee Type:** Contingent + **Location:** 2101 West John Carpenter Freeway Irving, TX + **Job Type:** Software Engineering + **Duration:** 12 weeks + **Date Posted:** 8/9/2018 + **Job ID:** 130965 + **Pay Rate** $0.0 - $32.45/Hour + **Contact Name** Volt Branch + **Phone** 919-782-7440 # Job Description Volt is working with a leading Insurance company to find motivated Tableau Developers in Irving, TX to create Tableau presentations based on discussing the needs and pain points for Business Leaders throughout this company’s enterprise. If you are interested in learning more about this position, please apply. **Are you a fit?** Do you have experience with technology development? Do you like learning about new businesses? Do you have experience/training in using data analysis and quantitative modeling techniques (e.g. statistical, optimization, demand forecasting, and simulation)? As a tableau developer, you will be creating and maintaining campaign data requirements and ad hoc databases, act as department data steward, and collaborate with IT and stakeholders to ensure continuity and consistency. # Assignment Generalities: + Work collaboratively with various business partners to develop common approaches to campaign evaluation and data collection/processing. + Develop interactive dashboards using Tableau, SQL and ETL tools to provide on-demand reporting, powerful visualizations and insights to senior leaders. + Automate data transfers and dashboard updates. + Perform proactive and ad hoc analyses ranging from identifying partner opportunities, evaluating success by assessing the contribution of other related functions which impact partnership performance. # Requirements: + Bachelor’s degree preferred (specialization in data science or quantitative field preferred) + Minimum of 3-5 years of experience in handling duties as detailed above + SQL skills are required, with experience working on at least one of Oracle, SQL server or Big Data. + Experience/training in using data analysis and quantitative modeling techniques (e.g. statistical, optimization, demand forecasting, and simulation) to answer business questions and to assess the added value of recommendations. + Experience developing dashboards and reporting using common data visualization tools within Tableau + Experience with data ETL (SQL, Alteryx, SAS) and coding using one or more statistical computer languages (R, Python, SAS.) to manipulate data and draw insights from large data sets. + Adept at presenting insights and analyses to any level of an organization. + Demonstrated ability to take the initiative, be self-driven, work across functional groups, build collaborative relationships and drive projects to closure. + Tableau Desktop Associate certification or equivalent QlikView Business Analyst certification is preferred # Volt is an equal opportunity employer. **Pay is based on experience.** In order to promote this harmony in the workplace and to obey the laws related to employment, Volt maintains a strong commitment to equal employment opportunity without unlawful regard to race, color, national origin, citizenship status, ancestry, religion (including religious dress and grooming practices), creed, sex (including pregnancy, childbirth, breastfeeding and related medical conditions), sexual orientation, gender identity, gender expression, marital or parental status, age, mental or physical disability, medical condition, genetic information, military or veteran status or any other category protected by applicable law.
          Azure HDInsight Interactive Query: Ten tools to analyze big data faster      Cache   Translate Page   Web Page Cache   

Customers use HDInsight Interactive Query (also called Hive LLAP, or Low Latency Analytical Processing) to query data stored in Azure storage & Azure Data Lake Storage in super-fast manner. Interactive query makes it easy for developers and data scientist to work with the big data using BI tools they love the most. HDInsight Interactive Query supports several tools to access big data in easy fashion. In this blog we have listed most popular tools used by our customers:

Microsoft Power BI

Microsoft Power BI Desktop has a native connector to perform direct query against HDInsight Interactive Query cluster. You can explore and visualize the data in interactive manner. To learn more see Visualize Interactive Query Hive data with Power BI in Azure HDInsight and Visualize big data with Power BI in Azure HDInsight .


Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Apache Zeppelin

Apache Zeppelin interpreter concept allows any language/data-processing-backend to be plugged into Zeppelin. You can access Interactive Query from Apache Zeppelin using a JDBC interpreter. To learn more please see Use Zeppelin to run Hive queries in Azure HDInsight .


Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Visual Studio Code

With HDInsight Tools for VS Code, you can submit interactive queries as well at look at job information in HDInsight interactive query clusters. To learn more please see Use Visual Studio Code for Hive, LLAP or pySpark .


Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Visual Studio

Visual Studio integration helps you create and query tables in visual fashion. You can create a Hive tables on top of data stored in Azure Data Lake Storage or Azure Storage. To learn more please see Connect to Azure HDInsight and run Hive queries using Data Lake Tools for Visual Studio .


Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Ambari Hive View

Hive View is designed to help you author, optimize, and execute queries. With Hive Views you can:

Browse databases. Write queries or browse query results in full-screen mode, which can be particularly helpful with complex queries or large query results. Manage query execution jobs and history. View existing databases, tables, and their statistics. Create/upload tables and export table DDL to source control. View visual explain plans to learn more about query plan.

To learn more please see Use Hive View with Hadoop in Azure HDInsight .


Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Beeline

Beeline is a Hive client that is included on the head nodes of HDInsight cluster. Beeline uses JDBC to connect to HiveServer2, a service hosted on HDInsight cluster. You can also use Beeline to access Hive on HDInsight remotely over the internet. To learn more please see Use Hive with Hadoop in HDInsight with Beeline .


Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Hive ODBC

Open Database Connectivity (ODBC) API, a standard for the Hive database management system, enables ODBC compliant applications to interact seamlessly with Hive through a standard interface. Learn more about how HDInsight publishes HDInsight Hive ODBC driver .


Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Tableau

Tableau is very popular data visualization tool. Customers can build visualizations by connecting Tableau with HDInsight interactive Query.


Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Apache DBeaver

Apache DBeaver is SQL client and a database administration tool. It is free and open-source (ASL). DBeaver use JDBC API to connect with SQL based databases. To learn more, see How to use DBeaver with Azure #HDInsight .


Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Excel

Microsoft Excel is the most popular data analysis tool and connecting it with big data is even more interesting for our customers. Azure HDInsight Interactive Query cluster can be integrated with Excel with ODBC connectivity.To learn more, see Connect Excel to Hadoop in Azure HDInsight with the Microsoft Hive ODBC driver .


Azure HDInsight Interactive Query: Ten tools to analyze big data faster
Try HDInsight now

We hope you will take full advantage fast query capabilities of HDInsight Interactive Query using your favorite tools. We are excited to see what you will build with Azure HDInsight. Read this developer guide and follow the quick start guide to learn more about implementing these pipelines and architectures on Azure HDInsight. Stay up-to-date on the latest Azure HDInsight news and features by following us on Twitter #HDInsight and @AzureHDInsight . For questions and feedback, please reach out to AskHDInsight@microsoft.com .

About HDInsight

Azure HDInsight is Microsoft’s premium managed offering for running open source workloads on Azure. Azure HDInsight powers mission critical applications ranging in a wide variety of sectors including, manufacturing, retail education, nonprofit, government, healthcare, media, banking, telecommunication, insurance, and many more industries ranging in use cases from ETL to Data Warehousing, from Machine Learning to IoT, and more.

Additional resources Get started with HDInsight Interactive Query Cluster in Azure . Zero
          REDCap module brings new charting functionality to clinical research projects      Cache   Translate Page   Web Page Cache   
The Oregon Clinical and Translational Research Institute’s informatics team has launched a new REDCap module for data visualization at OHSU. Over 2,400 OHSU researchers use REDCap to manage research data for their collective 1,600 projects. While REDCap includes a wide variety of research data collection, management, reporting and security features that robustly support clinical research, Vizr … Continued
          Data Visualization with Chart.js & HTML5 Canvas      Cache   Translate Page   Web Page Cache   
They say information is power, but to transform information into work, you need to make it compelling and accessible.  Sure, you can kludge something together out in Office or beg your graphic design to...

Source


          Highcharting Jobs Friday      Cache   Translate Page   Web Page Cache   
Today, in honor of last week’s jobs report from the Bureau of Labor Statistics (BLS), we will visualize jobs data with ggplot2 and then, more extensively with highcharter. Our aim is to explore highcharter and its similarity with ggplot and to create some nice interactive visualizations. In the process, we will cover how to import BLS data from FRED and then wrangle it for visualization. We won’t do any modeling or statistical analysis today, though it wouldn’t be hard to extend this script into a forecasting exercise. One nice thing about today’s code flow is that it can be refreshed and updated on each BLS release date. Let’s get to it! We will source our data from FRED and will use the tq_get() function from tidyquant which enables us to import many data series at once in tidy, tibble format. We want to get total employment numbers, ADP estimates, and the sector-by-sector numbers that make up total employment. Let’s start by creating a tibble to hold the FRED codes and more intuitive names for each data series. library(tidyverse) library(tidyquant) codes_names_tbl % slice(1) # A tibble: 15 x 3 # Groups: symbol [15] symbol date price 1 MANEMP 2007-01-01 14008 2 NPPTTL 2007-01-01 115437. 3 PAYEMS 2007-01-01 137497 4 USCONS 2007-01-01 7725 5 USEHS 2007-01-01 18415 6 USFIRE 2007-01-01 8389 7 USGOVT 2007-01-01 22095 8 USINFO 2007-01-01 3029 9 USLAH 2007-01-01 13338 10 USMINE 2007-01-01 706 11 USPBS 2007-01-01 17834 12 USSERV 2007-01-01 5467 13 USTPU 2007-01-01 26491 14 USTRADE 2007-01-01 15443. 15 USWTRADE 2007-01-01 5969. The symbols are the FRED codes, which are unrecognizable unless you have memorized how those codes map to more intuitive names. Let’s replace them with the better_names column of codes_names_tbl. We will do this with a left_join(). (This explains why I labeled our original column as symbol - it makes the left_join() easier.) Special thanks to Jenny Bryan for pointing out this code flow! fred_empl_data %__% left_join(codes_names_tbl, by = "symbol" ) %__% select(better_names, everything(), -symbol) %__% group_by(better_names) %__% slice(1) # A tibble: 15 x 3 # Groups: better_names [15] better_names date price 1 ADP Estimate 2007-01-01 115437. 2 Construction 2007-01-01 7725 3 Financial 2007-01-01 8389 4 Gov 2007-01-01 22095 5 Health Care 2007-01-01 18415 6 Info Sys 2007-01-01 3029 7 Leisure 2007-01-01 13338 8 Manufact 2007-01-01 14008 9 Mining 2007-01-01 706 10 Nonfarm Employment 2007-01-01 137497 11 Other Services 2007-01-01 5467 12 Prof/Bus Serv 2007-01-01 17834 13 Retail/Trade 2007-01-01 15443. 14 Transportation 2007-01-01 26491 15 Wholesale Trade 2007-01-01 5969. That looks much better, but we now have a column called price, that holds the monthly employment observations, and a column called better_names, that holds the more intuitive group names. Let’s change those column names to employees and sector. fred_empl_data % left_join(codes_names_tbl, by = "symbol" ) %__% select(better_names, everything(), -symbol) %__% rename(employees = price, sector = better_names) head(fred_empl_data) # A tibble: 6 x 3 sector date employees 1 ADP Estimate 2007-01-01 115437. 2 ADP Estimate 2007-02-01 115527. 3 ADP Estimate 2007-03-01 115647 4 ADP Estimate 2007-04-01 115754. 5 ADP Estimate 2007-05-01 115809. 6 ADP Estimate 2007-06-01 115831. fred_empl_data has the names and organization we want, but it still has the raw number of employees per month. We want to visualize the month-to-month change in jobs numbers, which means we need to perform a calculation on our data and store it in a new column. We use mutate() to create the new column and calculate monthly change with value - lag(value, 1). We are not doing any annualizing or seasonality work here - it’s a simple substraction. For yearly change, it would be value - lag(value, 12). empl_monthly_change % group_by(sector) %__% mutate(monthly_change = employees - lag(employees, 1)) %__% na.omit() Our final data object empl_monthly_change is tidy, has intuitive names in the group column, and has the monthly change that we wish to visualize. Let’s build some charts. We will start at the top and use ggplot to visualize how total non-farm employment (Sorry farmers. Your jobs don’t count, I guess) has changed since 2007. We want an end-user to quickly glance at the chart and find the months with positive jobs growth and negative jobs growth. That means we want months with positive jobs growth to be one color, and those with negative jobs growth to be another color. There is more than one way to accomplish this, but I like to create new columns and then add geoms based on those columns. (Check out this post by Freddie Mac’s Len Kiefer for another way to accomplish this by nesting ifelse statements in ggplot's aesthetics. In fact, if you like data visualization, check out all the stuff that Len writes.) Let’s walk through how to create columns for shading by positive or negative jobs growth. First, we are looking at total employment here, so we call filter(sector == "Nonfarm Employment") to get only total employment. Next, we create two new columns with mutate(). The first is called col_pos and is formed by if_else(monthly_change __ 0, monthly_change,...). That logic is creating a column that holds the value of monthly change if monthly change is positive, else it holds NA. We then create another column called col_neg using the same logic. empl_monthly_change %__% filter(sector == "Nonfarm Employment") %__% mutate(col_pos = if_else(monthly_change __ 0, monthly_change, as.numeric(NA)), col_neg = if_else(monthly_change __ 0, monthly_change, as.numeric(NA))) %__% dplyr::select(sector, date, col_pos, col_neg) %__% head() # A tibble: 6 x 4 # Groups: sector [1] sector date col_pos col_neg 1 Nonfarm Employment 2007-02-01 85 NA 2 Nonfarm Employment 2007-03-01 214 NA 3 Nonfarm Employment 2007-04-01 59 NA 4 Nonfarm Employment 2007-05-01 153 NA 5 Nonfarm Employment 2007-06-01 77 NA 6 Nonfarm Employment 2007-07-01 NA -30 Have a qucik look at the col_pos and col_neg columns and make sure they look right. col_pos should have only positive and NA values, col_neg shoud have only negative and NA values. Now we can visualize our monthly changes with ggplot, adding a separate geom for those new columns. empl_monthly_change %__% filter(sector == "Nonfarm Employment") %__% mutate(col_pos = if_else(monthly_change __ 0, monthly_change, as.numeric(NA)), col_neg = if_else(monthly_change __ 0, monthly_change, as.numeric(NA))) %__% ggplot(aes(x = date)) + geom_col(aes(y = col_neg), alpha = .85, fill = "pink", color = "pink") + geom_col(aes(y = col_pos), alpha = .85, fill = "lightgreen", color = "lightgreen") + ylab("Monthly Change (thousands)") + labs(title = "Monthly Private Employment Change", subtitle = "total empl, since 2008", caption = "inspired by @lenkiefer") + scale_x_date(breaks = scales::pretty_breaks(n = 10)) + theme_minimal() + theme(axis.text.x = element_text(angle = 90, hjust = 1), plot.title = element_text(hjust = 0.5), plot.subtitle = element_text(hjust = 0.5), plot.caption = element_text(hjust=0)) That plot is nice, but it’s static! Hover on it and you’ll see what I mean. Let’s head to highcharter and create an interactive chart that responds when we hover on it. By way of brief background, highcharter is an R hook into the fantastic highcharts JavaScript library. It’s free for personal use but a license is required for commercial use. One nice feature of highcharter is that we can use very similar aesthetic logic to what we used for ggplot. It’s not identical, but it’s similar and let’s us work with tidy data. Before we get to the highcharter logic, we will add one column to our tibble to hold the color scheme for our positive and negative monthly changes. Notice how this is different from the ggplot flow above where we create one column to hold our positive changes for coloring and one column to hold our negative changes for coloring. I want to color positive changes light blue and negative changes pink, and put the rgb codes for those colors directly in the new column. The rgb code for light blue is “#6495ed” and for pink is “#ffe6ea”. Thus we use ifelse to create a column called color_of_bars that holds “#6495ed” (light blue) when monthly_change is postive and “#ffe6ea” (pink) when it’s negative. total_employ_hc % filter(sector == "Nonfarm Employment") %__% mutate(color_of_bars = ifelse(monthly_change __ 0, "#6495ed", "#ffe6ea")) head(total_employ_hc) # A tibble: 6 x 5 # Groups: sector [1] sector date employees monthly_change color_of_bars 1 Nonfarm Employment 2007-02-01 137582 85 #6495ed 2 Nonfarm Employment 2007-03-01 137796 214 #6495ed 3 Nonfarm Employment 2007-04-01 137855 59 #6495ed 4 Nonfarm Employment 2007-05-01 138008 153 #6495ed 5 Nonfarm Employment 2007-06-01 138085 77 #6495ed 6 Nonfarm Employment 2007-07-01 138055 -30 #ffe6ea Now we are ready to start the highcharter flow. We start by calling hchart to pass in our data object. Note the similarity to ggplot where we started with ggplot. Now, intead of waiting for a call to geom_col, we set type = "column" to let hchart know that we are building a column chart. Next, we use hcaes(x = date, y = monthly_change, color = color_of_bars) to specify our aesthetics. Notice how we can control the colors of the bars from values in the color_of_bars column. We also supply a name = "monthly change" because we want monthly change to appear when a user hovers on the chart. That wasn’t a consideration with ggplot. library(highcharter) hchart(total_employ_hc, type = "column", pointWidth = 5, hcaes(x = date, y = monthly_change, color = color_of_bars), name = "monthly change") %__% hc_title(text = "Monthly Employment Change") %__% hc_xAxis(type = "datetime") %__% hc_yAxis(title = list(text = "monthly change (thousands)")) %__% hc_exporting(enabled = TRUE) Let’s stay in the highcharter world and visualize how each sector changed in the most recent month, which is July of 2018. First, we isolate the most recent month by filtering on the last date. We also don’t want the ADP Estimate and filter that out as well. empl_monthly_change %__% filter(date == (last(date))) %__% filter(sector != "ADP Estimate") # A tibble: 14 x 4 # Groups: sector [14] sector date employees monthly_change 1 Nonfarm Employment 2018-07-01 149128 157 2 Construction 2018-07-01 7242 19 3 Retail/Trade 2018-07-01 15944 7.1 4 Prof/Bus Serv 2018-07-01 21019 51 5 Manufact 2018-07-01 12751 37 6 Financial 2018-07-01 8568 -5 7 Mining 2018-07-01 735 -4 8 Health Care 2018-07-01 23662 22 9 Wholesale Trade 2018-07-01 5982. 12.3 10 Transportation 2018-07-01 27801 15 11 Info Sys 2018-07-01 2772 0 12 Leisure 2018-07-01 16371 40 13 Gov 2018-07-01 22334 -13 14 Other Services 2018-07-01 5873 -5 That filtered flow has the data we want, but we have two more tasks. First, we want to arrange this data so that it goes from smallest to largest. If we did not do this, our chart would still “work”, but the column heights would not progress from lowest to highest. Second, we need to create another column to hold colors for negative and positive values, with the same ifelse() logic as we used before. emp_by_sector_recent_month % filter(date == (last(date))) %__% filter(sector != "ADP Estimate") %__% arrange(monthly_change) %__% mutate(color_of_bars = if_else(monthly_change __ 0, "#6495ed", "#ffe6ea")) Now we pass that object to hchart, set type = "column", and choose our hcaes values. We want to label the x-axis with the different sectors and do that with hc_xAxis(categories = emp_by_sector_recent_month$sector). last_month % hc_title(text = paste(last_month, "Employment Change", sep = " ")) %__% hc_xAxis(categories = emp_by_sector_recent_month$sector) %__% hc_yAxis(title = list(text = "Monthly Change (thousands)")) Finally, let’s compare the ADP Estimates to the actual Nonfarm payroll numbers since 2017. We start with filtering again. adp_bls_hc % filter(sector == "ADP Estimate" | sector == "Nonfarm Employment") %__% filter(date __= "2017-01-01") We create a column to hold different colors, but our logic is not whether a reading is positive or negative. We want to color the ADP and BLS reports differently. adp_bls_hc % mutate(color_of_bars = ifelse(sector == "ADP Estimate", "#ffb3b3", "#4d94ff")) head(adp_bls_hc) # A tibble: 6 x 5 # Groups: sector [1] sector date employees monthly_change color_of_bars 1 ADP Estimate 2017-01-01 123253. 245. #ffb3b3 2 ADP Estimate 2017-02-01 123533. 280. #ffb3b3 3 ADP Estimate 2017-03-01 123655 122. #ffb3b3 4 ADP Estimate 2017-04-01 123810. 155. #ffb3b3 5 ADP Estimate 2017-05-01 124012. 202. #ffb3b3 6 ADP Estimate 2017-06-01 124166. 154. #ffb3b3 tail(adp_bls_hc) # A tibble: 6 x 5 # Groups: sector [1] sector date employees monthly_change color_of_bars 1 Nonfarm Employment 2018-02-01 148125 324 #4d94ff 2 Nonfarm Employment 2018-03-01 148280 155 #4d94ff 3 Nonfarm Employment 2018-04-01 148455 175 #4d94ff 4 Nonfarm Employment 2018-05-01 148723 268 #4d94ff 5 Nonfarm Employment 2018-06-01 148971 248 #4d94ff 6 Nonfarm Employment 2018-07-01 149128 157 #4d94ff And now we pass that object to our familiar hchart flow. hchart(adp_bls_hc, type = 'column', hcaes(y = monthly_change, x = date, group = sector, color = color_of_bars), showInLegend = FALSE ) %__% hc_title(text = "ADP v. BLS") %__% hc_xAxis(type = "datetime") %__% hc_yAxis(title = list(text = "monthly change (thousands)")) %__% hc_add_theme(hc_theme_flat()) %__% hc_exporting(enabled = TRUE) That’s all for today. Try revisiting this script on September 7th, when the next BLS jobs data is released, and see if any new visualizations or code flows come to mind. See you next time and happy coding!
          IT Manager, Data Visualization Lead (551477)      Cache   Translate Page   Web Page Cache   
IN-Warsaw, Job Summary Zimmer Biomet Named Among the 100 Best Places to Work in IT in 2018 by Computerworld Magazine Zimmer Biomet is looking for diverse and talented individuals to join our Information Technology Team. As a Lead - Data Visualization, you will help to drive the analytics transformation from traditional reporting to Data as a Service using Tableau at Zimmer Biomet. You will be the Subject Mat
          Ensembl Front-End Web Developer      Cache   Translate Page   Web Page Cache   
Job Description Ensembl seeks a front end web developer (JavaScript, CSS and HTML) to work on our next generation website. The Genomics Technology Infrastructure team, based at the European Bioinformatics Institute (EMBL-EBI), both designs and develops web-based data visualisations for genomic data. Ensembl, and its associated projects, are a suite of highly valued scientific resource that support biological research worldwide with millions of visitors per year.   You will be working withi...
          Sr. Data Scientist - Data Visualization Specialist - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
You'll be required to figure out what's important to the business, to specific partners, and intuit core needs from people before they even realize they need it...
From Amazon.com - Thu, 19 Jul 2018 07:49:53 GMT - View all Seattle, WA jobs
          Wrong month names and date format for DateTimeGroupDescription      Cache   Translate Page   Web Page Cache   
Hello Zlatko,

I'm uncertain why the error you shared is observed, but you can try to disable the Warn if changing between secure and not secure mode option, if you're using Internet Explorer as suggested here.

If you're not using Internet Explorer or the aforementioned suggestion does not work for you, what I can suggest is to check for any previous versions of the demos, uninstall them, reboot your machine and try installing them again. You can also try downloading the demos from the Windows Store.

If none of this helps, you can download the source code of the demos from your Telerik account and manually build them.

Please let me know how all of this goes.

Regards,
Dilyan Traykov
Progress Telerik
Try our brand new, jQuery-free Angular 2 components built from ground-up which deliver the business app essential building blocks - a grid component, data visualization (charts) and form elements.

          Library: Assistant Professor as Digital Learning and Instruction Librarian - UW Eau Claire - Eau Claire, WI      Cache   Translate Page   Web Page Cache   
Recent academic coursework or professional experience relevant to digital scholarship, data visualization or instructional design....
From University of Wisconsin System - Fri, 27 Jul 2018 19:32:15 GMT - View all Eau Claire, WI jobs
          CMSC 201 Computer Science I for Non-CS Disciplines      Cache   Translate Page   Web Page Cache   

Gain a competitive advantage in your field!

Programming and problem-solving skills are musts for today’s college graduates!

Enroll in a special section of CMSC 201 Computer Science I that emphasizes programming topics applicable to the social and biological sciences and other majors. Sample topics include statistical analysis, working with large data sets, and data visualization using the popular Python programming language. You will also receive more individual attention in this smaller CMSC 201 section!

This section fulfills any major’s requirement for CMSC 201 and is open to all non-CS, non-engineering majors.

No programming experience is required. Click here for more details about this unique opportunity.


          10 significant visualisation developments: January to June 2018      Cache   Translate Page   Web Page Cache   

To mark each mid-year and end of year milestone I try to take a reflective glance over the previous 6 months period in the data visualisation field and compile a collection of some of the most significant developments. These are the main projects, events, new sites, trends, personalities and general observations that have struck me as being important to help further the development of this field.

The post 10 significant visualisation developments: January to June 2018 appeared first on Visualising Data.


          Senior Interaction Designer - Top Startup!      Cache   Translate Page   Web Page Cache   
CA-Berkley, Based in Berkeley, we are a cloud- based software platform focused on providing battery intelligence through advanced data visualization and analytics tools for companies that manufacture or use batteries. Our platform tracks batteries from early R&D through their lifetime in the field in order to increase productivity, drive innovation, and improve performance and reliability. What You Will Be Do
          Senior Front-End Engineer      Cache   Translate Page   Web Page Cache   
CA-Berkley, Based in Berkeley, we are a cloud- based software platform focused on providing battery intelligence through advanced data visualization and analytics tools for companies that manufacture or use batteries. Our platform tracks batteries from early R&D through their lifetime in the field in order to increase productivity, drive innovation, and improve performance and reliability. What You Will Be Do
           GE Transportation technology pilot project begins at Port of Long Beach      Cache   Translate Page   Web Page Cache   
A pilot project between GE Transportation and the Port of Long Beach to enhance advance planning at the busiest port complex in North America is officially underway. Over the next two months, stakeholders across the Port will use GE's Port Optimizer™ software to access data that will allow them to move cargo containers more efficiently.Port Optimizer enhances cargo flow as participating terminal operators and other stakeholders receive much improved advance notice of cargo arrival, coordinated with data on the availability of equipment, labor and other resources needed to move that cargo through the supply chain.Three of the Port's six container terminals are involved – Long Beach Container Terminal, Total Terminals International and International Transportation Service. The system debuted at the Port of Los Angeles last year. "We welcome the opportunity to have this exciting technology demonstrated here in our Port," said Port of Long Beach Executive Director Mario Cordero. "We are always searching for new means toward improving operational efficiencies in the supply chain as it moves through this port complex. We look forward to observing Port Optimizer in action.""We're excited about the potential of this technology," said Long Beach Harbor Commission President Lou Anne Bynum. "Moving goods more efficiently through this important gateway is the key to accommodating future cargo growth. The data collected during this pilot at some of our busiest terminals could help to accomplish this, and we look forward to seeing the results.""We are proud to launch our Port Optimizer software in Long Beach," said Jen Schopfer, VP, General Manager of Transport Logistics for GE Transportation. "Not only will GE be piloting our product's core capabilities around advanced visibility and planning, but we are also launching some Long Beach-centric functionality – marine terminal operator and landside transportation integrations for better planning and gate transactions, including MatchBack Systems for dual transactions, and advanced/predictive analytics addressing truck congestion using GeoStamp's IOT platform."These capabilities serve many stakeholders across the port complex, including but not limited to marine terminal operators, ocean and motor carriers, railroads and beneficial cargo owners."The Harbor Trucking Association is excited that GE's Port Optimizer is expanding its operational footprint to include the Port of Long Beach and will now serve the broader San Pedro Bay port complex," said Weston LaBar, CEO of the Harbor Trucking Association. "The HTA is committed to the rapid adoption of technology and digitization of the supply chain. As we become a proactive, rather than reactive, industry, the Port Optimizer is the key tool that will enable the necessary data visibility and multi-stakeholder systems integrations for these efforts to be successful. This project has the potential to be the single most impactful enhancement to our industry since the adoption of containerization."

Source: Transportweekly
          Senior Interaction Designer - Top Startup!      Cache   Translate Page   Web Page Cache   
CA-Berkley, Based in Berkeley, we are a cloud- based software platform focused on providing battery intelligence through advanced data visualization and analytics tools for companies that manufacture or use batteries. Our platform tracks batteries from early R&D through their lifetime in the field in order to increase productivity, drive innovation, and improve performance and reliability. What You Will Be Do
          Sr. Data Scientist - Data Visualization Specialist - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
You'll be required to figure out what's important to the business, to specific partners, and intuit core needs from people before they even realize they need it...
From Amazon.com - Thu, 19 Jul 2018 07:49:53 GMT - View all Seattle, WA jobs
          Virtual Space Data Manager in Chicago      Cache   Translate Page   Web Page Cache   
A real estate professional services is filling a position for a Virtual Space Data Manager in Chicago. Must be able to: Be accountable for the performance of the space data management team Be accountable for space data integrity and accuracy within a CAFM database Define, categorize, measure, and audit client space data Must meet the following requirements for consideration: Some travel may be required Bachelor’s Degree in Management, Architecture, Real Estate, Construction, Interior Design, Project Managment or a related field 2 to 4 years work experience in CAFM/IWMS administration, occupancy or space planning in a corporate environment Demonstrated knowledge of office space categorization principles (BOMA, OSCRE, etc.), CAFM procedures and AutoCAD Moderate experience in CAFM/IWMS database management and design Demonstrated abilities in analytics, data visualization, and trend reporting using PowerPivot, Tableau, etc
          Oracle data visualization (DVD/DVCS) implementation for advanced analytics and machine learning      Cache   Translate Page   Web Page Cache   
Oracle DVD is a Tableau like interactive tool which helps to create analysis on the fly, using any type data from any platform, be it on premise or cloud. Read on to know more about the benefits of Oracle data visualization (DVD/DVCS).
          Top 20 Best data visualization tools      Cache   Translate Page   Web Page Cache   
There are lots and lots of data churned every day across all industries. Data is a valuable resource for businesses that can get unmanageable. Moreover, raw data does not really make sense in its actual form. While some big firms have specialized teams to perform big data analysis, not every company has that kind of resources to carry it out. Fortunately, technology has gifted us with data visualization tools that help streamline business functions, improve efficiencies internally, and even help understand your customers better. From charts, videos, or infographics to modern solutions like AR and VR (augmented reality and virtual
          Research Associate (Full Stack/Data Visualization Developer) - Singapore University of Technology and Design - Changi      Cache   Translate Page   Web Page Cache   
Vue.js and d3.js do the heavy lifting on the frontend, while our backend software is mostly written in node.js and R (tidyverse)....
From Singapore University of Technology and Design - Fri, 20 Jul 2018 11:19:29 GMT - View all Changi jobs
          Research Associate (Full Stack/Data Visualization Developer) - Singapore University of Technology and Design - Changi      Cache   Translate Page   Web Page Cache   
Vue.js and d3.js do the heavy lifting on the frontend, while our backend software is mostly written in node.js and R (tidyverse)....
From Singapore University of Technology and Design - Fri, 20 Jul 2018 11:19:29 GMT - View all Changi jobs
          Software Developer for Data Visualization - JDSAT - San Diego, CA      Cache   Translate Page   Web Page Cache   
Strong experience developing automated data feeds in SharePoint, Microsoft .NET, and/or asp.net. We are seeking an enthusiastic, self-driven, and experienced... $80,000 - $110,000 a year
From JDSAT - Fri, 10 Aug 2018 14:43:01 GMT - View all San Diego, CA jobs
          Research Associate (Full Stack/Data Visualization Developer) - Singapore University of Technology and Design - Changi      Cache   Translate Page   Web Page Cache   
Vue.js and d3.js do the heavy lifting on the frontend, while our backend software is mostly written in node.js and R (tidyverse)....
From Singapore University of Technology and Design - Fri, 20 Jul 2018 11:19:29 GMT - View all Changi jobs
          Lecturer,Asst - University of Wyoming - Laramie, WY      Cache   Translate Page   Web Page Cache   
Strong statistical and psychometric knowledge, e.g., multiple regression, logistic regression, data visualization, relational databases, SQL, IRT,...
From University of Wyoming - Sat, 04 Aug 2018 15:48:20 GMT - View all Laramie, WY jobs
          Mer enn hvert tredje plagg vi kjøper blir ikke brukt      Cache   Translate Page   Web Page Cache   
Nordmenn svarer at 36 prosent av klærne de kjøper blir hengende i skapet. Andre data viser at andelen er langt høyere.
          (USA-TN-Memphis) Operations Manager - FLOW - Shelby Facility      Cache   Translate Page   Web Page Cache   
Become a Part of the NIKE, Inc. Team NIKE, Inc. does more than outfit the world's best athletes. It is a place to explore potential, obliterate boundaries and push out the edges of what can be. The company looks for people who can grow, think, dream and create. Its culture thrives by embracing diversity and rewarding imagination. The brand seeks achievers, leaders and visionaries. At Nike, it’s about each person bringing skills and passion to a challenging and constantly evolving game. Nike Supply Chain experts ensure that every year 900 million pieces of footwear, apparel and equipment arrive at the right destination on time. That’s no easy task. The complex process involves more than 50 distribution centers, a network of thousands of accounts, and more than 100,000 retail stores around the world. Supply Chain professionals from Laakdal, Belgium, to São Paulo, Brasil, make it happen. They constantly push for ways to make Nike’s supply chain faster, more efficient and more responsive to Nike’s always-changing consumer needs. **Description** As a Flow Ops / Business Analyst, you will have an exceptional opportunity to leverage your strong data expertise to create automated tools that enable fact-based, real-time decisions within the DC environment. You will work closely with the North America Supply Chain senior leadership team, program leaders and functional leaders in DC Operations, planning, customer service, transportation and retail. You will: + Ensure all departmental safety, service, quality, on-time delivery, and financial objectives are met or exceeded. + Communicate the business of our operation to lead and influence the input/output of 2-4 exempt level managers and 10 full-time employees. + Actively contribute to the distribution management team by assisting in the development of distribution goals and objectives, working effectively across departmental boundaries within the operation and manage the overall shift and departmental production /efficiency goals. + Create interactive, automated, and user-friendly analytical tools that enable fact-based, real-time decision-making process + Drive analytics and performance measurement within the distribution center and provide recommendations for process improvement + Develop high-impact presentations to communicate the strategic plan, roadmap and initiatives to the broader organization. + Manage a wide range of inputs and simplify to establish clear goals while communicating to all stakeholders Core Accountabilities Build knowledge of the company, processes and customers. Understand key business drivers and use this knowledge in analysis. Solve a range of problems; analyze possible solutions using standard procedures. Develop, document, and execute on strategic plans which will drive optimal customer service and profitability. Be a resident data expert. Create and automate data collection/manipulation processes. Data mining using state-of-the-art methods. Processing, cleansing, and verifying the integrity of data used for analysis. Create automated, analytical tools and visual dashboards. Develop and maintain business KPI’s and analyze data; present findings and recommendations to drive key business decisions. Support the business using statistical methods for process and performance assessment. Problem solving and solution creation. Respond to requests from internal/external customers. Investigate these requests and partner on a solution enabling the effective and efficient distribution of products and services. Provide solutions to achieve the targeted sales goals while aggressively pursuing customer service standards. Collaborate to drive operational excellence and best practices across the network by providing analytical information to enhance results. **Qualifications** + Bachelor's degree in Business, Supply Chain, Distribution, Engineering, Finance, or related field + FLOW Center Management Experience preferred + 5+ years of experience working with data in Supply Chain, Merchandising or Finance field + Proficiency in using query languages such as SQL and data blending tools such as Alteryx + Intermediate skills with data visualization tools such as Tableau + Advanced skills in MS Excel & Access, and experience in SAP + Good applied statistics skills, modeling, such as distributions, statistical testing, regression, etc + Proficiency in Manhattan WMS and Cognos preferred + Strong project management, problem structuring, and strategic problem solving skills + Demonstrated ability to complete quantitative and qualitative analysis + Experience managing complex cross-functional stakeholder engagements, including facilitating workshops, is preferred + Exceptional interpersonal and communication skills (written and verbal), and the ability to work cross-functionally + Great listening skills and openness for different viewpoints + Strong presentation and influencing skills and the ability to interact with senior leadership + Self-starter, eager to learn, result-oriented and creative strategic thinker + Shift Flexibility will be required. Candidate may be required to work the day shift, night shift or split shift depending on the needs of the business **Qualifications** + Bachelor's degree in Business, Supply Chain, Distribution, Engineering, Finance, or related field + FLOW Center Management Experience preferred + 5+ years of experience working with data in Supply Chain, Merchandising or Finance field + Proficiency in using query languages such as SQL and data blending tools such as Alteryx + Intermediate skills with data visualization tools such as Tableau + Advanced skills in MS Excel & Access, and experience in SAP + Good applied statistics skills, modeling, such as distributions, statistical testing, regression, etc + Proficiency in Manhattan WMS and Cognos preferred + Strong project management, problem structuring, and strategic problem solving skills + Demonstrated ability to complete quantitative and qualitative analysis + Experience managing complex cross-functional stakeholder engagements, including facilitating workshops, is preferred + Exceptional interpersonal and communication skills (written and verbal), and the ability to work cross-functionally + Great listening skills and openness for different viewpoints + Strong presentation and influencing skills and the ability to interact with senior leadership + Self-starter, eager to learn, result-oriented and creative strategic thinker + Shift Flexibility will be required. Candidate may be required to work the day shift, night shift or split shift depending on the needs of the business NIKE, Inc. is a growth company that looks for team members to grow with it. Nike offers a generous total rewards package, casual work environment, a diverse and inclusive culture, and an electric atmosphere for professional development. No matter the location, or the role, every Nike employee shares one galvanizing mission: To bring inspiration and innovation to every athlete* in the world. NIKE, Inc. is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability. **Job ID:** 00405522 **Location:** United States-Tennessee-Memphis **Job Category:** Supply Chain
          Software Developer for Data Visualization - JDSAT - San Diego, CA      Cache   Translate Page   Web Page Cache   
Strong experience developing automated data feeds in SharePoint, Microsoft .NET, and/or asp.net. We are seeking an enthusiastic, self-driven, and experienced... $80,000 - $110,000 a year
From JDSAT - Fri, 10 Aug 2018 14:43:01 GMT - View all San Diego, CA jobs
          Research Associate (Full Stack/Data Visualization Developer) - Singapore University of Technology and Design - Changi      Cache   Translate Page   Web Page Cache   
Vue.js and d3.js do the heavy lifting on the frontend, while our backend software is mostly written in node.js and R (tidyverse)....
From Singapore University of Technology and Design - Fri, 20 Jul 2018 11:19:29 GMT - View all Changi jobs
          Business Intelligence & Reporting Analyst - ProViso Consulting - Toronto, ON      Cache   Translate Page   Web Page Cache   
With Data visualizatrion. Accuracy and attention to detail with a strong understanding of data management and data integrity....
From ProViso Consulting - Fri, 10 Aug 2018 19:53:13 GMT - View all Toronto, ON jobs
          Update: MEEM Memory (Utilities)      Cache   Translate Page   Web Page Cache   

MEEM Memory 3.1.1


Device: iOS Universal
Category: Utilities
Price: Free, Version: 3.1.0 -> 3.1.1 (iTunes)

Description:

The MEEM App works exclusively with the patented MEEM device – a USB cable with built in memory module.

The charger that automatically backs up while it charges.

•100% Visible.
Every photo, every video, every date, every contact, everything….

•Three Devices.
Any 3 devices on the cable. Phone or tablet.

•Lost Phone/Upgrade?
Restoring data is easy – just a single swipe

•More Space.
Delete from your device and save on the cable

•Platform Neutral.
Back up and share across devices and platforms on the same cable. All 100% visible.

• Desktops/Laptops.
Back up to desktop/laptop and have all data visible and useable by WiFi or connecting the cable.

For More information on all these features please visit www.meemmemory.com

Latest Features, or refer to Help in the MEEM App menu that is available with or without the cable being attached.
The intuitive interface allows you to seamlessly transfer all your important data from one phone to another with a simple swipe.

MEEM can even selectively copy data between phones - a task that until now was virtually impossible.

What's New

Bug fixes & Performance improvements.

MEEM Memory




Next Page: 10000

Site Map 2018_01_14
Site Map 2018_01_15
Site Map 2018_01_16
Site Map 2018_01_17
Site Map 2018_01_18
Site Map 2018_01_19
Site Map 2018_01_20
Site Map 2018_01_21
Site Map 2018_01_22
Site Map 2018_01_23
Site Map 2018_01_24
Site Map 2018_01_25
Site Map 2018_01_26
Site Map 2018_01_27
Site Map 2018_01_28
Site Map 2018_01_29
Site Map 2018_01_30
Site Map 2018_01_31
Site Map 2018_02_01
Site Map 2018_02_02
Site Map 2018_02_03
Site Map 2018_02_04
Site Map 2018_02_05
Site Map 2018_02_06
Site Map 2018_02_07
Site Map 2018_02_08
Site Map 2018_02_09
Site Map 2018_02_10
Site Map 2018_02_11
Site Map 2018_02_12
Site Map 2018_02_13
Site Map 2018_02_14
Site Map 2018_02_15
Site Map 2018_02_15
Site Map 2018_02_16
Site Map 2018_02_17
Site Map 2018_02_18
Site Map 2018_02_19
Site Map 2018_02_20
Site Map 2018_02_21
Site Map 2018_02_22
Site Map 2018_02_23
Site Map 2018_02_24
Site Map 2018_02_25
Site Map 2018_02_26
Site Map 2018_02_27
Site Map 2018_02_28
Site Map 2018_03_01
Site Map 2018_03_02
Site Map 2018_03_03
Site Map 2018_03_04
Site Map 2018_03_05
Site Map 2018_03_06
Site Map 2018_03_07
Site Map 2018_03_08
Site Map 2018_03_09
Site Map 2018_03_10
Site Map 2018_03_11
Site Map 2018_03_12
Site Map 2018_03_13
Site Map 2018_03_14
Site Map 2018_03_15
Site Map 2018_03_16
Site Map 2018_03_17
Site Map 2018_03_18
Site Map 2018_03_19
Site Map 2018_03_20
Site Map 2018_03_21
Site Map 2018_03_22
Site Map 2018_03_23
Site Map 2018_03_24
Site Map 2018_03_25
Site Map 2018_03_26
Site Map 2018_03_27
Site Map 2018_03_28
Site Map 2018_03_29
Site Map 2018_03_30
Site Map 2018_03_31
Site Map 2018_04_01
Site Map 2018_04_02
Site Map 2018_04_03
Site Map 2018_04_04
Site Map 2018_04_05
Site Map 2018_04_06
Site Map 2018_04_07
Site Map 2018_04_08
Site Map 2018_04_09
Site Map 2018_04_10
Site Map 2018_04_11
Site Map 2018_04_12
Site Map 2018_04_13
Site Map 2018_04_14
Site Map 2018_04_15
Site Map 2018_04_16
Site Map 2018_04_17
Site Map 2018_04_18
Site Map 2018_04_19
Site Map 2018_04_20
Site Map 2018_04_21
Site Map 2018_04_22
Site Map 2018_04_23
Site Map 2018_04_24
Site Map 2018_04_25
Site Map 2018_04_26
Site Map 2018_04_27
Site Map 2018_04_28
Site Map 2018_04_29
Site Map 2018_04_30
Site Map 2018_05_01
Site Map 2018_05_02
Site Map 2018_05_03
Site Map 2018_05_04
Site Map 2018_05_05
Site Map 2018_05_06
Site Map 2018_05_07
Site Map 2018_05_08
Site Map 2018_05_09
Site Map 2018_05_15
Site Map 2018_05_16
Site Map 2018_05_17
Site Map 2018_05_18
Site Map 2018_05_19
Site Map 2018_05_20
Site Map 2018_05_21
Site Map 2018_05_22
Site Map 2018_05_23
Site Map 2018_05_24
Site Map 2018_05_25
Site Map 2018_05_26
Site Map 2018_05_27
Site Map 2018_05_28
Site Map 2018_05_29
Site Map 2018_05_30
Site Map 2018_05_31
Site Map 2018_06_01
Site Map 2018_06_02
Site Map 2018_06_03
Site Map 2018_06_04
Site Map 2018_06_05
Site Map 2018_06_06
Site Map 2018_06_07
Site Map 2018_06_08
Site Map 2018_06_09
Site Map 2018_06_10
Site Map 2018_06_11
Site Map 2018_06_12
Site Map 2018_06_13
Site Map 2018_06_14
Site Map 2018_06_15
Site Map 2018_06_16
Site Map 2018_06_17
Site Map 2018_06_18
Site Map 2018_06_19
Site Map 2018_06_20
Site Map 2018_06_21
Site Map 2018_06_22
Site Map 2018_06_23
Site Map 2018_06_24
Site Map 2018_06_25
Site Map 2018_06_26
Site Map 2018_06_27
Site Map 2018_06_28
Site Map 2018_06_29
Site Map 2018_06_30
Site Map 2018_07_01
Site Map 2018_07_02
Site Map 2018_07_03
Site Map 2018_07_04
Site Map 2018_07_05
Site Map 2018_07_06
Site Map 2018_07_07
Site Map 2018_07_08
Site Map 2018_07_09
Site Map 2018_07_10
Site Map 2018_07_11
Site Map 2018_07_12
Site Map 2018_07_13
Site Map 2018_07_14
Site Map 2018_07_15
Site Map 2018_07_16
Site Map 2018_07_17
Site Map 2018_07_18
Site Map 2018_07_19
Site Map 2018_07_20
Site Map 2018_07_21
Site Map 2018_07_22
Site Map 2018_07_23
Site Map 2018_07_24
Site Map 2018_07_25
Site Map 2018_07_26
Site Map 2018_07_27
Site Map 2018_07_28
Site Map 2018_07_29
Site Map 2018_07_30
Site Map 2018_07_31
Site Map 2018_08_01
Site Map 2018_08_02
Site Map 2018_08_03
Site Map 2018_08_04
Site Map 2018_08_05
Site Map 2018_08_06
Site Map 2018_08_07
Site Map 2018_08_08
Site Map 2018_08_09
Site Map 2018_08_10