wazirx

PancakeSwap

trezor.io/start

Toobit Exchange

https://toobit-exchange.com

Trezor Suite

Trezor Suite

https://trezorsuite-web.com

trezor.io/start

wazirx exchange

https://wazirxexchange.com

ledger live

https://ledger-live-app.com

Toobit

Orion Stars

https://orionstars.asia

Trezor Bridge

https://trezorbridge.org

trezor.io/start

Berachain Airdrop

https://berachainairdrop.org

Berachain

ledger live

https://docs-ledgerlive.com

Articles ← Winwaed Blog ← Page 2

Beware of Choropleth Maps!

Beware of Choropleth Maps!
I was recently experimenting with the new Maptitude data of 2018 Zip Code Business Counts. Free for existing customers, this data lists the total number of businesses by type (NAICS code) for every zip code in the USA. This data represents a huge number of data fields, and it is recommended that users read Caliper’s ...

Drawing SVG Superellipses with Python

Drawing SVG Superellipses with Python
Superellipses are a little bit of a mathematical oddity, resembling rounded squares or square-ish circles. They are, however, becoming popular for icon outlines. iOS currently uses them, as do recent versions of Android. This article shows you how to use Python to create an arbitrary superellipse in SVG. This can then be used as an ...

Close all Views with GISDK

Thanks to Paul Lucassen and Stewart Berry, here is a short piece of GISDK macro code to close all Data View windows: {window_list} = GetWindows("Editor") for i = 1 to window_list.length do CloseEditor(window_list[i]) end To use this code, open the Immediate Execution window in Maptitude (far right button on the GISDK Toolbox with the lightning ...

Plotting Place Names from Natural Text in Python 3

This example uses Maptitude’s new Python 3 interface to draw annotation on a map. The annotation is in the form of place names mentioned in H.G. Wells’ War of the Worlds. This also serves as a basic demonstration of using NLTK (Natural Language Toolkit) to identify named entities (proper nouns) in the book text. Annotation ...

Using Python to Filter and Correct Data

This example uses a Python script to create a new layer within Maptitude from an input file of Oklahoma well injection data. The input data has a number of erroneous coordinates, so the script filters the bad coordinates out. A few of these coordinates have incorrect signs (e.g. negative latitude or positive longitude), so these ...

Mapping Earthquakes

Maptitude can also be used plot earthquakes, examine patterns in earthquakes, and even look for correlations with other factors such as oil industry activity. Earthquake catalogs from recent years can be downloaded from the US Geological Survey at http://earthquake.usgs.gov/earthquakes/search/ . For the following maps, the data is downloaded as a CSV (comma separated value) file, ...

Why is it important to practice defensive driving, and how can it benefit 

Why is it important to practice defensive driving, and how can it benefit  Defensive driving is the technique in which you drive cautiously and smoothly, minimising the chances of engaging in an accident and damaging your car and that of third parties. Car accidents mainly occur due to reckless and rash driving. A defensive driver ...

NLTK on the Raspberry PI

If you haven’t heard of it yet, the Raspberry Pi is a $25/$35 barebones computer intended to excite kids with programming and hardware projects. It is very much modeled on the British experience of home computing in the early 1980s and even has a “Model A” and a “Model B” in homage to the BBC ...

Sentence Segmentation: Handling multiple punctuation characters

Previously, I showed you how to segment words and sentences whilst also taking into account full stops (periods) and abbreviations. The problem with this implementation is that it is easily confused by contiguous punctuation characters. For example “).” is not recognized as the end of a sentence. This article shows you how to correct this.

Using BerkeleyDB to Create a Large N-gram Table

Previously, I showed you how to create N-Gram frequency tables from large text datasets. Unfortunately, when used on very large datasets such as the English language Wikipedia and Gutenberg corpora, memory limitations limited these scripts to unigrams. Here, I show you how to use the BerkeleyDB database to create N-gram tables of these large datasets.