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In the previous post “Stock Data 1. Capture via API and Excel from Web” I used Excel to grab some data from the Web & show it as a Table inside Excel. After bringing the data in I had trouble creating a chart from the Table. So, after messing around with the Charts again today

I started looking at getting financial data from the Web, looking at the NZX (NZ stock Exchange) but no-one had free API’s. Actually Quandl did but it was only monthly on overall stocks/bonds and stops the previous month. So I spent a little time fluffing with their free API before realising that was the case.

In Knime you can go to the EXAMPLES from the Knime Server  in the KNIME EXPLORER Tab and open/save to local workspace some examples to play with. You may need to see about getting some API keys for the examples. I tested  Translate using Google API Example. I needed an Google Translate API key and

The above image is for LinkedIn viewers as the API doesn’t seem to fire when viewed from linkedIn. Go here to see web page where the API displays the information. There is also an Extended page with weather & forecast for Wellington, NZ, London, UK & Boston, Ma, USA. Find it here. Output from API

There is a lot of data that can be linked to via API’s (Application programming interface’s), so I’m interested in how to hook up to them to be able to use “GET” requests to download specific data (rather than downloading all the dataset). My first attempt was using Python & Stats.NZ API. I got a

I had a thought of embedding metadata into images after a building survey. This would capture the surveyors comments on the survey and store them in the the actual image files. So the next time the photo is inspected in the office the information on that image is easily inspected. Rather than looking for 2

This post was instigated by the Weka tutorial on image processing. I worked through the video and then thought about testing the datasets using the different analytic tools to see which ones were easy to set up and use and also for reviewing results. Weka Image Processing In the Advanced Weka videos there was one

I have been using Knime for a while. I note I have only written about the Database connections with Knime so far. An updated version (3.6.0) came out this month and I decided to update the programme on my computers. There are a few new features from when I last had a good look at

Following on from the first Weka post, which was based on information gleaned from the Data Mining with Weka course that I followed. This post is based on the following More Data Mining with Weka videos. Some of  the screenshots below from the video’s that have been developed and are presented by Ian Witten of

  In exploring the data analytics tools (Knime, Rapid Miner, FME, Orange..) there has been references to WEKA. Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression,