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Joshua Ebner Profile picture
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28 Aug, 5 tweets, 3 min read
@JoshuaSteinman Regarding: An American Shenzhen

There's a *lot* of good ports along the Texas coast, and I think much of it under-used.

Great for logistics into the American Heartland, and also into LatAm and Mexico.
@JoshuaSteinman The Texas/Mexico combo provides a unique mix of high-skill, medium-skill, and low-skill labor.

High end design and MFG in TX, lower skill MFG and assembly in MX.
@JoshuaSteinman Also great energy resources in TX (although nuclear would augment).
@JoshuaSteinman Slightly longer thread detailing some similar thoughts, here:

@JoshuaSteinman For data nerds who are interested, here's how I made that map:

Part 1: sharpsightlabs.com/blog/mapping-t…

Part 2: sharpsightlabs.com/blog/mapping-t…

• • •

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More from @Josh_Ebner

Joshua Ebner Profile picture
31 Aug
The big thing that I'd change here is the color palette.

This color palette is hard to interpret and frankly, just look a little ugly.

#datascience #DataVisualization

[1/11]
[2/11]

The fix here is pretty simple.

The data are sequential in nature. There's a low and a high.

When you have sequential data, you should almost always look at sequential color palettes.

[3/11]

More specifically:

For sequential data, your go-to palettes should almost always be perceptually uniform sequential palettes like viridis or magma.

Read 11 tweets
Joshua Ebner Profile picture
30 Aug
If you want to create great data visualizations, you need to understand color palettes.

Here are a few quick tips:

[1/n]

#datascience #datavisualization #Python #rstats
[2/n]

For data that has a sequential ordering (i.e., low to high), you should use sequential color scales.

matplotlib.org/stable/tutoria…

#Python #matplotlib Image
[3/n]

Sequential color scales incrementally change saturation or lightness.

For example, this is a red-sequential color palette: Image
Read 24 tweets
Joshua Ebner Profile picture
28 Aug
@JoshuaSteinman My understanding based on some research last year and beyond, is that these are deep-water.

... and there's possibly more ports with shallow depth
@JoshuaSteinman For example, @PeterZeihan wrote that Texas has "thirteen world-class deepwater ports"

amzn.to/3BihKN6
@JoshuaSteinman @PeterZeihan Army Corps of Engineers puts it at "15 deep draft ports" and "13 shallow draft ports" along the TX coast.

swd.usace.army.mil/About/Texas-Po…
Read 5 tweets
Joshua Ebner Profile picture
27 Aug
If you want to master data science in Python, you need to learn Pandas method chaining.



[thread: 1/14]

#data #datascience #Python
[2/14]

Pandas method chains enable you to combine together several individual Pandas techniques in complex ways.
[3/14]

When most people do this, they do it with very long chains of techniques, *all on a single line*.

These are hard to read and hard to debug.

They get more challenging the longer they get.
Read 14 tweets
Joshua Ebner Profile picture
26 Aug
How to Add New Variables to a Python Dataframe

sharpsightlabs.com/blog/pandas-as…

[Thread: 1/9]

#data #datascience #Python Image
[2/9]

There are several ways to add a variable to a Python dataframe ...

But my preferred way is the Pandas "assign" method.
[3/9]

The Pandas assign method has fairly simple syntax.

You can use the technique to add a single new variable like this: Image
Read 9 tweets
Joshua Ebner Profile picture
3 May 20
If there's a large migration of talented people from SF and NYC to Austin, Austin has a shot at being the next Silicon Valley.

#SF #NewYork #SiliconValley #technology #Austin #Texas

(Thread)
2/n
Remember: Texas actually has a long tradition of innovation.

For example, the integrated circuit was invented at Texas Instruments.

en.wikipedia.org/wiki/Texas_Ins…

#technology #tech #Texas ImageImage
3/n
More recently, Amazon, Facebook, Google, and Apple have announced major campuses in Austin.

Google is building a new riverside building, and Facebook already has one.

austin.curbed.com/2019/4/2/18291… ImageImage
Read 15 tweets

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