fabiochiu/medium-articles huggingface dataset:
Roadmap to Becoming a Successful Data Scientist
By: Mustufa Ansari
Tags: Machine Learning, Artificial Intelligence, AI, Data Science, Data

1) Python Basics

In order to become a data scientist, you need to understand the basics of Python first. Because Python is the favored language for data science.

By going through this course of edX “Introduction to Python for Data Science” you will have some basic understanding of python.

2) Statistics & Probability

Stats is a key part of Data Science. If I am not wrong Data Science is all about statistics. This course of KhanAcademy will help you to understand the basic concepts of statistics and probability.

3) Data Analysis

Data preprocessing and visualization of data is one of the main components of data science. This course will teach you how computing and mathematics come together. The data analysis involves the collection of data preprocessing and interactive visualization of data. If you want to master this key component, click here.

4) Machine Learning for Data Science and Analytics

Now its time to learn some Machine learning stuff. After taking this course

“Machine Learning For Data Science & Analytics” you will be able to understand algorithms and how to create ML models.

5) Deep Learning

This is a complete book of Deep Learning in which you will have got clear and very precise knowledge about deep learning.

6) Intro to Relational Databases (SQL, DB-API & More..)

If you have learned python completely, this course will help you a lot to understand this course, because it is all about SQL queries and how you will use the relational database from your code using python example. You will learn the basics of SQL along with Python API for connecting python code to the database.

7) Intro to Hadoop and MapReduce

For the handling of Big Data, Apache Hadoop develops open-source software for the manipulation of Big Data. This course will make you understand the basics of Hadoop and the principles behind it.

8) Data Storytelling

To be a data scientist is not enough, you have to learn the way of representing data and its insights to the management, executives and other stakeholders. So, it is necessary to learn the data storytelling skill so that you wouldn’t get confused at the time of data representation. Click here.

*Important*

Learning is not enough if you don’t practice what you have learned. So I urged you to do at least 2 to 3 Kaggle projects to polish your data science skills.

This roadmap is enough for you to start your career as a data scientist. You don’t need to go anywhere or enrolled $1000 of courses to become a data scientist. You can do it on your own. You just need to start once with passion!
Searching for Kindness on the Interwebs
By: Elizabeth Reese
Tags: Bots, Cortana, AI, Artificial Intelligence, Microsoft

The talk that resonated with me most at D&CC came from Beth Dean, who spoke about Facebook’s efforts to imbue kindness into its interactions. Facebook’s problems are unique, complicated, and usually unintentional, in the same way Tay’s downfall was never intended. A grieving parent sees “memories” collected by Facebook featuring a deceased child. Mother’s Day reminders tear at the hearts of those without mothers. Your news feed shouts out the political diatribes of the day, every day, while your community adds to the stream of angry comments.

As software developers at any tech company become more skilled at using our data to customize and personalize our experiences on the web, we are in turn demanding a higher level of thoughtfulness from our interactions. Are we setting higher expectations from artificial entities because our interactions with people on the web have become more tense? From the venom spewed about immigrants in certain corners of the Internet to the threats leveled at two Republican Senators who disagreed with their leadership over the recent healthcare fights, it’s as though we’ve accepted this behavior as the new normal, and now turn to AI to give us the kindness that’s missing from our human interactions.

I don’t have any answers to this question. But amidst this disconnect that I struggle with — creating a positive, welcoming environment for Microsoft’s customers, while feeling as if I can’t expect the same courtesy from certain parts of the media, or in my political leaders — what I try to keep top of mind in all this is my aunt-in-law. We’ve had different political leanings since I married into the family when I was 22. But in the end, the only thing that ever really mattered was that she loved my first husband, who passed away 5 years ago, and now simply wants to know that his children are growing up into good men who will follow in their father’s footsteps. With her in mind, those on the opposite side of the political spectrum no longer are the “other.”

And maybe the reason that those of us in the tech field are focused now on ensuring that our creations reflect a kindness is to provide a proxy for my aunt-in-law. A techy reminder that if bots and other AIs can be courteous and careful of our feelings, we shouldn’t forget that it’s possible in our human-to-human interactions too. Whether you’re engaging with a bot, your social media audience, your political representatives, or your best friends, your words — and the humanity behind those words — matter more than ever.
Write Cleaner Code by Using JavaScript Destructuring
By: Juan Cruz Martinez
Tags: Nodejs, React, Programming, JavaScript, Typescript

Destructuring Objects

In the example above, all the magic happens in the following line:

const { title, rating, author: { name } } = article

Now it may seem a bit weird to have those brackets like that on the left side of the assignment, but that’s how we tell JavaScript that we are destructuring an object.

Destructuring objects lets you bind to different properties of an object at any depth. Let’s start with an even simpler example:

const me = {

name: "Juan"

} const { name } = me

In the case above, we are declaring a variable called name that will be initialized from the property with the same name in the object me so that when we evaluate the value of name , we get Juan . Awesome! The same can be applied to any depth. Heading back to our example:

const { title, rating, author: { name } } = article

For title and rating , it’s exactly the same as we already explained. But in author , things are a bit different. When we get to a property that is either an object or an array, we can choose whether to create the variable author with a reference to the article.author object or do a deep destructuring and get immediate access to the properties of the inner object.

Accessing the object property:

Doing a deep or nested destructuring:

Wait, what? If I destructured author , why is it not defined? It is actually quite simple. When we ask JavaScript to also destructure the author object, that binding itself is not created and we instead get access to all the author properties we selected. So please always remember that.

Spread operator ( … ):

Additionally, we can use the spread operator ... to create an object with all the properties that did not get destructured.

If you are interested in learning more about the spread operator, check out my article.

Renaming properties

One great property of destructuring is the ability to choose a different name for the variable to the property we are extracting. Let’s look at the following example:

By using : on a property, we can provide a new name for it (in our case, newName ). And then we can access that variable in our code. It’s important to note that a variable with the original property name won’t be defined.

Missing properties

So what would happen if we tried to destructure a property that is not defined in our object?

In this case, the variable is created with value undefined .

Default values

Expanding on missing properties, it’s possible to assign a default value when the property does not exist. Let’s see some examples of this:
Building a Treemap with JavaScript
By: Clément Bataille
Tags: Data Visualization, Software Engineering, JavaScript, Vuejs, Technology

Building a Treemap with JavaScript

At Foxintelligence, while building our data visualization platform we wanted to challenge the pie chart. This is our journey of building a Treemap in JavaScript from scratch.

EDIT: an open source JavaScript package

I published an open source JavaScript package that calculates the Treemap. It uses the algorithm described in this article and is available both with npm and in the browser.

https://www.npmjs.com/package/treemap-squarify

The goal: an effective data visualization

The goal was to find the best way to represent market shares among categories in e-commerce. The pie chart representation is the first one that comes to mind for this kind of data.

Colorful pie charts

However, it can be hard to compare different categories in a pie chart. The pain points of this type of visualization are:

It’s hard to compare pie slices

It’s hard to display labels on pie slices

It’s hard to compare two pie charts

What kind of data visualization can we use instead?

🙌 The Treemap

That’s where we discovered the Treemap. A Treemap is a way to visualize hierarchical data in a rectangle (hence tree in Treemap). The value of one data point is proportional to its area in the main rectangle. One popular use is to visualize a computer file system. Here is an example of the initial tree and its counterpart on a Treemap.

A tree and its Treemap from [1]

In our case however, we don’t use it this way as we have a list of data instead of a tree. Nevertheless, we wanted to keep the idea of having one data point represented by an area on one main rectangle. In the following example, we have one main rectangle which represents 100% and each rectangle is a category market share of x%.

Market shares on a Treemap

Why is it better?

First it’s visually easier to compare rectangle area than pie slices. It’s also easier for the label of each area to be displayed on the graphic instead of having to refer to the legend each time you need to. Plus we wanted to compare one merchant with the market (or with another merchant), and having two pie charts next to each other is not readable.

🎯 The specifications

So we’ve decided to use a Treemap as our data visualization. Let’s now talk about the specifications from the design/product team.

Each area should be a rectangle that is as square as possible (which is the Squarified Treemap type of Treemap)

type of Treemap) We want 100% customization possibility over the UI (colors, hover effects, label or icon inside each square)
It’s Just Us Down Here
By: Karie Luidens
Tags: Wildfires, Health, Mental Health, Climate Change, Life

After the fire comes the smoke.

It blew into Albuquerque last Tuesday on, oddly, a cold front. I’d seen the photos of orange skies raining ash and heat a thousand miles west of us, so I guess that’s what I expected: winds that burn. Instead they were frigid. They chilled us and pricked goosebumps from our skin.

Earlier that morning, the weather was so mild that we’d opened all our windows. Then came the crash of icy air off the West Mesa. Around midday, the screens started to rattle and howl. The sky took on that close-hanging dirt-colored tinge I associate with tornado warnings from back when I lived in the Midwest. Here in New Mexico, it meant wildfire smoke, sweeping a desert’s worth of sand along with it. A fine grain of dirt slanted in through the still-open windows with each gust. Its grit gradually collected on our dining room table.

We’d already placed a grocery order to pick up curbside — a new pandemic routine. After another day working from home, we drove across town together, Harrison behind the wheel. Strapped in passively beside him, I could feel the wind driving against the car, strong enough to make its metal shudder.

I knew the wind had picked up, but I didn’t expect such detritus all around. The roads were littered with blowing leaves, twigs, whole branches — whole trees knocked cockeyed, root balls half-ripped from the earth.

The power was out at some intersections. As we approached San Mateo and I-40, we saw the traffic lights sputter and go dark before us like candles in a storm. It was the worst place for it to happen, for us to be: three northbound lanes, three southbound, an off-ramp funneling interstate traffic out into the mix. Everyone clumsily came to a standstill. Then ten hulking beasts at a time tentatively revved their engines as drivers jerked and dodged, hesitant to believe everyone agreed this was now a four-way stop. Did we? Did we all agree, without being able to speak across our sealed-up containers?

Harrison and I didn’t even speak to each other. What was there to say? I just dug my nails into the fabric under my legs and hunched slightly. My body anticipated the lurch and smash of getting T-boned; I shook the thought. There’s nothing you can do. Nothing. Just keep your seat belt fastened and wait this out.
The Power of Song
By: Yael Wolfe
Tags: Creativity, Magic, Soul, Spirituality, Music

As I get older, I find myself singing more and more often. Part of this, I think, is the fact that I have been separated from my beloved piano. This beautiful instrument that I so love to play lives at my mother’s house now because it does not really fit into my little “cottage.”

I own a guitar and a banjo, yet I don’t know how to play either because I am lazy and distracted and impatient, and I don’t like the calluses they leave on my fingertips — I’m a knitter and callousy fingertips can be very dangerous to my beautiful yarn.

So what do I do? I strum my instruments clumsily and without even the slightest competence, just to have a little something in the background to sing to.

Or I just sing without them.

I sing in my garden. I sing in the shower. I sing in my bed. I sing in the woods. I sing to my nieces and nephews.

Sometimes I think the more I sing, or rather, the more music we all make, the better we can shield ourselves against the darkness. When I start to think that the world is filled with people who only want to hurt others, flinging the cruelest words at strangers on the internet, I sing more often and I sing louder because I know my song will drown out their hateful words. I sing to disarm them. I sing to interrupt their cruelty. I sing to welcome more light into this world.

I also sing to fortify the earth. I sing as a way to restore dignity to the natural world. To tell the trees and land and flowers and birds and coyotes that I recognize them as my kin. I recognize their right to be here. I appreciate their place in this world. I honor what they have to teach me.

And I sing like I’m casting magic spells, weaving threads of melodies between myself and my loved ones. I sing Be with Me now not so much for my owls, who have grown and flown away to find their own territory, but for my little nephew, Alex, who I hope will always remember me, even though he is moving far away.

River runs to the sea

Salmon runs to the sea

If you need someone

You can run to me

I pray that the river will always run to the sea, that he will always run to me.

I believe so deeply in this. I might lose my faith in so much, but I never seem to lose faith in song. I remember once, all those years ago when I was observing my three baby owls, I couldn’t find them one afternoon, so I took a little drum out to a glade that I love and played a rhythm on it while singing a Tori Amos tune, my eyes closed so I could feel the full energy of the song.

When I opened my eyes, one of the baby owls streaked past me, a white and brown blur, and then she disappeared into the shadowy grove of trees just beyond.

I knew she heard me and liked my song and wanted to let me know that she was there, somewhere just beyond where I could see.

© Yael Wolfe 2020
The Strategy That Increases Model Accuracy, Every Time, Guaranteed
By: Andre Ye
Tags: Machine Learning, Data Science, AI, Kaggle, Data

The goal is to predict ConfirmedCases and Fatalities . This is a perfect example of real-world data. We’re given the country, the latitude and longitude of the country, and the date.

First, we must preprocess the date. A machine learning model cannot intake a date, so instead, I created a new column days_from_start that represents the number of days that have passed from 1/22, the date of first data.

Let’s first train a Random Forest model on the raw data. The latitude (how north or south the country is) may be of use because some studies have shown that hotter countries (closer to the equator) are less at risk of the coronavirus.

The mean absolute error is 67.8. On average, a prediction made by our model is 67.8 cases off the target.

As for fatalities,

We are about 2.6 deaths off on average. The low number is because of the scale (not many people have died, and the countries that do have lots of deaths like China the model can exploit via longitude and latitude. It cannot find much relation between location and deaths that can be generalized beyond the training set).

When one thinks about factors that might influence the coronavirus, the first thing that may come to mind is population of a country. A country that has more people will probably have more interactions, meaning the transmissibility of the virus is increased.

So let’s add the data! Wikipedia is usually a good source full of tables, but there are plenty of other sites that have scrapable data. The easiest way to scrape online data is with pandas ’ read_html function.

We will use the most recent population count (collected July 1st, 2019) to use as a feature, and map the Country or area column to each of the countries within the coronavirus forecasting dataset.

This is where a lot of work using external data comes in — Wikipedia pages have different naming conventions for names than the ones in our data. For instance, ‘United States’ might be ‘US’ or ‘U.S.’ or ‘United States of America’.

Additionally, in Wikipedia there are often footnotes, and to reference them, there are often brackets next to country names, like in the example below.
Most Read & Interesting Stories from Technicity in 2020
By: Faisal Khan
Tags: Space, Bitcoin, Business, Health, Artificial Intelligence

This year will undoubtedly go down in history as one for the record books. Although there were a lot of important events that transpired in 2020, the onset and the continuation of the pandemic has affected the lives of the global population in more ways than one. The effects of COVID-19 have been so far-reaching that it has eclipsed almost everything else.

For Technicity, it was the first full year of publication on Medium, after starting in Oct. 2019. And I would like to take this opportunity to thank each and every one of you for your support — for me personally and the publication as we enter the new year with renewed hope & vigor for the future. Technicity has a following of 2,653 followers at the time of writing and growing every day.

Wishing you all a happy, healthy & prosperous 2021, and here’s a look back at some of the most popular & interesting blogs from 2020. Meanwhile, I will continue to bring the best content.

JANUARY 2020
After the Workshop
By: Sean Conner
Tags: Innovation, Comics, Creativity, Design Thinking, Startup

Spiralbound

Comics for life, brought to life by Edith Zimmerman.
Building a ChatBot in Python — The Beginner’s Guide
By: Behic Guven
Tags: Machine Learning, Artificial Intelligence, Technology, Future, Programming

Step 4 — Relation Function

This is an extra function that I’ve added after testing the chatbot with my crazy questions. So, if you want to understand the difference, try the chatbot with and without this function. You will see why I decided to write this function. And one good part about writing the whole chatbot from scratch is that we can add our personal touches to it.

In the Chatbot responses step, we defined answers lists to specific questions. And since we are using dictionaries, if the question is not exactly the same (literally), the chatbot will not return the response for that question we tried to ask. Sometimes, we might forget the question mark, or a letter in the sentence or something else.

In this finding relation function, we are checking the question and trying to find the key terms that might help us to understand the question. You will understand what I mean when you see the function:

def related(x_text):

if "name" in x_text:

y_text = "what's your name?" elif "weather" in x_text:

y_text = "what's today's weather?" elif "robot" in x_text:

y_text = "are you a robot?" elif "how are" in x_text:

y_text = "how are you?" else:

y_text = "" return y_text

I used if and else statements, but it could be done using switch cases too. Feel free to convert it to a switch case. Also, this is just to give some idea. There are many other techniques to increase the understanding, for example, by using NLP (Natural Language Processing) techniques.

Here is a simple example of how the function returns the question that probably asked by the user:
AWS — How to build a static website with S3 in 5 min
By: Bhargav Bachina
Tags: Programming, AWS, Cloud Computing, Software Development, Web Development

In this article, we will build a static website on AWS. we are going to use Simple Storage Service (s3) to host the static website.

static website hosting on AWS

Here is the step by step guide for creating a static website on AWS using S3.

There are some prerequisites for this project. you need to have

AWS account

Domain name

HTML and CSS

AWS Account

you can create an AWS account with the free tier for 12 months. Let’s create and log into the console.

once logged in you can see the console like below. You logged in as a root account. The best practice is to create an IAM user to access s3 and route 53 but, for simplicity, we are not doing that and out of scope for this tutorial.

Domain Name

you can buy a domain from route 53 from the AWS. it’s pretty easy and straight forward. You can check if there are available or not and add to cart. it might take some time to have that appear on registered domains like in the second figure. I bought myagileboard.com for this tutorial.

Route 53

Registered Domains

HTML and CSS

Let’s create some simple HTML and CSS files for our index.html. when the users hit the domain, these are pages that loads. clone the bwlow repo for the files.

sample page

Now we have completed all the prerequisites, Let’s start the process.

upload to S3

since our domain name is myagileboard.com, Let’s create two buckets called myagileboard.com and www.myagileboard.com. The reason that we create two buckets is to display the coming soon page for both these domains. Sometimes we omit the www before the website URL. Make sure you create these buckets as public.

upload files to both www.myagileboard.com and myagilleboard.com bucket with public access permissions.

let’s enable static website hosting on www.myagileboard.com bucket by going to the properties tab and do redirect on agileboard.com bucket.

use this bucket to host a website

use this to redirect all the routes

check the URL working or not by copying endpoint.

s3 URL is working fine

configure Route53

now go to route 53 and create a new record set called www.agileboard.com and give it an alias target to the bucket name www.agileboard.com

hit the URL in the browser www.myagileboard.com. That completes our static website hosting!!!.

Conclusion

Static website hosting on the AWS is pretty straight forward and your bucket name and your domain name should be same. I omitted a lot of details for simplicity purpose and you can find a lot of documentation on AWS.
GAN — Role of Individual Units in a Deep Network
By: Mikhail Raevskiy
Tags: Machine Learning, Artificial Intelligence, Deep Learning, AI, Data Science

When a neural network is trained on a high-level task like classifying a place or generating a scene, individual neuron units in the network are often responsible for concepts that are interpreted to humans. For example, trees, windows or human faces. However, at the moment, the task of analyzing parts of the model remains relevant.

To solve the problem of analyzing neural networks, researchers consider two neural networks that contain interpreted parts:

Networks that have been trained to classify scene images with a teacher; Networks that have been trained to generate scene images ( GAN )

Analysis of the parts of the classifier and generator

To recognize the units that are responsible for human-readable concepts, the researchers compare the outputs of the units to the outputs of a semantic segmentation model that has been trained to tag pixels with classes of objects, parts, materials, and colors. This technique is called network dissection. It allows you to standardize and scale the process of finding parts of a model that belong to the same semantic classes.
Reach a Little Higher
By: Dr. Christine Bradstreet
Tags: Mental Health, Health, Inspiration, Spirituality, Mindset

Reach a little higher

Stretch beyond a limit

Stride a bit longer

Breathe deeper

Exhale longer

Forgive one more time

Release another grudge

Surrender an attachment

Accept something new

Choose peace over strife

Pause an extra moment

Listen like the words are new

Act with intent

Hear the inner voice

Trust your intuition

Choose the healthy snack

Know you don’t need the drug

Move your body even if it hurts

Take action when you’re inspired

Rest when you need rest

Say the words that are hard to say

Draw a line in the sand

Be honest about what you want

Take a risk

Have faith

Get my new book Happy Ever After and learn how to cultivate true and lasting happiness in your life.

I made a free 5-day Mastering Happiness email course, and I want to share it with you! Visit me at christinebradstreet.com where you can get your course for free.

All images open source from https://pixabay.com/
Exploratory Data Analysis(Part I)
By: Sehan Farooqui
Tags: Data Science, Matplotlib, Data Visualization, Machine Learning, Exploratory Data Analysis

Bivariate Analysis:

As name suggest Bi means two so the analysis of exactly two variable is what we call a bivariate analysis. It is more interesting analysis compared to the univariate analysis because we can actually see if there is any impact of one variable on the other variable such as if there is any impact of patient age over recovery time? Or if women are more vulnerable to a pandemic than men?

Following are the visualizations often used in bivariate analysis,

Bar Plot:

The bar plot is used for comparing items and in EDA we often use bar plot to find if one group is different from the others such as are females more likely to survive than males in a tragedy like titanic? Ideally bar plots are used when we have at least one categorical and one numeric variable.

Bar Plot With Two Variables

Scatter Plot:

The scatter plot is used to find the relationship between at least two numerical variables such as what will be the impact of increase in square yards of the house on its price? Before using more advanced algorithms (non-linear) we often plot the data to see if the data is linearly separable or not. If it is linearly separable (rarely that happened in real world) we would like to go with linear algorithms like logistic regression in a classification problem.

Scatter Plot

Line Plot:

From cricket score to electrocardiogram (ECG or EKG) line plots are almost everywhere. They are used to show the change in trend over a period of time such as how mortality rate increase with age? Line plots are usually used with two numerical variables in a way that one variable represent an interval.

Line Plot

Cross table:

Cross tables are used to see if one group is significantly different from the other groups. We use cross tables when we have at least two categorical variables. Cross tables are also used to find the association between categorical variables using more advanced methods such as chi square.

Cross Table

Box Plot With Two Variables:

Often we would like to compare the distributions of different groups within one variable such as marital status can have groups like single, married, divorced, separated and widow. Box plots with two variables required one categorical variable (groups) and a numerical variable (distributions). Based on initial findings from this type of analysis we decide to run statistical hypothesis test such as t-test or ANOVA to confirm our hypothesis.

Box Plot With Two Variables

Summary:

Initially start with univariate analysis to build the general understanding of each variable in your data then move to bivariate to find out the more interesting relations between different variables in your data. I will be discussing multivariate analysis in my next blog of this series.

I hope this blog helped you in someway furthermore I would love to hear from you in the comment section. You can also connect with me on twitter at @SehanFarooqui

Feel free to clone the code from github and starting doing your own analysis.
6 Essential Things I Wish I Knew When I Started Programming
By: Nick Bull
Tags: Python, Programming, Software Development, Productivity, JavaScript

Communication Skills More Important Than Coding Skills

When I just started my career, lack of social skills was not my main problem. But when I moved higher, to the middle, senior, and leadership position, my weak soft skills became my Achilles heel.

When you work on a product with a group of different people (engineers, designers, managers), communication is the only thing that makes you a “team” and helps you effectively develop the product.

Lack of social skills does the opposite — it decreases the product development time and overall productivity.

Here is the real situation you might face:

The leadership team tells your product manager that they want to create a new product feature and put it in the next product release. It’s not urgent, they just want to release it as soon as possible (as always).

The product manager calls you on Zoom, tells you what you need to build, and asks, “How much time do you need to build it?”

You are doing a rough calculation and say, “I need 20 hours.”

The product manager is not satisfied with your answer. He wants to release it as soon as possible and show the management that he can deliver results fast (this is a very common situation).

So he asks you, “Can you build it for 10 hours? We really need this feature in the next product release!”

And you know that you can if you cut the corners (no tests, messy code) but then you will need to refactor it, and it will take an additional 30 hours. Because other engineers will work with your messy code when you release it. And after refactoring, you will need to integrate their code with yours.

So here’s what will happen next. If you have bad social skills, you will not convince the product manager that you actually need 20 hours to build this feature.

Why?

Product managers often have good social skills, from my experience. So if you can’t convince them that refactoring later is worse than spending 20 hours right now, they will easily argue with you and convince you that “refactoring later is OK.” And the whole team will lose an additional 30 hours for this refactoring (I don’t count the time to fix unpredictable bugs after).

But if you have good communication skills you will be able to convince them of the opposite.

So improve your social skills as well as coding skills (send memes in the group chats on Slack or something).

And remember one simple truth:

People work with people, not machines.
#WorldMentalHealthDay: Look Beyond Yourself & Care for Others.
By: Iccdi Africa
Tags: Health, Youth Development, Mental Health, Climate Change, Women

Mental health is a trending 21st-century issue that affects a person’s emotional state and physical output. Mental health becomes negative when you begin to engage in toxic activities or unhealthy/abusive relationships which could lead to depression and some times suicide.

The World Health Organization estimates that about 1 million people die of suicide annually around the world. Despite these frightening statistics, poor mental health can be addressed and extreme results like depression and suicide can be prevented if:

1. You talk to someone you trust like close friends, parents, colleagues, mentors or religious leaders to confide in them on issues bothering you

2. Seek professional counselling from a psychologist to get expert advice.
Radio #LatentVoices. Intro. 01–04
By: Vlad Alex, Merzmensch
Tags: Music, Culture, Artificial Intelligence, Art, Jukebox

Do you know this feeling: you wake up with a melody in your ears, a beautiful, unique song. And while you are trying to capture it (with a notation if you can scores, humming if you have a recording device near your pillow), this unearthly music vanishes, being overlayered by everyday sounds, thoughts, and needs.

It’s gone.

And you realize you were the only one person who could listen to this melody. Nobody else in this world. Because it was inside your dreams.

Then you are deluged by the melancholy of happiness. Happiness — because you are the lucky one to experience this harmonious sensation. Melancholy — because you won’t be able ever to share it with somebody.

Entering the epoche of Artificial Intelligence, you can. Well, it isn’t quite your dream, it’s a dream of a machine. But you can embrace its uniqueness and share it with the world.

That is what I love in JukeBox:

But let’s forget technology for a while. Because of the Music in the Air.
How to Kill a Dragon
By: Eliot Peper
Tags: Leadership, Philosophy, Self, Psychology, Creativity

Photo by Massimo Negrello on Unsplash

My friend Derek has a six year old grandson who came for a visit. They were exploring the basement together when the boy pointed to the door on the left and asked, “What’s in there grandpa?”

“Canned foods and supplies for the kitchen,” said Derek.

His grandson pointed to the door ahead of them, “What’s in there grandpa?”

“Your grandmother’s files,” said Derek. “Nothing too exciting.”

He pointed to the door on the right, “What’s in there grandpa?”

“I don’t know,” responded Derek, entirely truthfully. “I have no idea. Maybe dragons?”

“Dragons!” he said, eyes lighting up. “Get me a broomstick!”

“What?”

“A broomstick!”

After a quick search, Derek returned with a broomstick and handed it to his grandson.

“What are you going to do?” asked Derek.

“You’re going to open the door,” said his grandson. “And then I’ll run in there and see what happens. Okay, go!”

Derek complied and his grandson rushed headlong into the dark room, smashing everything right and left. After a few seconds of commotion, grandpa hit the light switch, hoping that nothing too valuable or dangerous had been shattered. The light revealed his grandson stomping his foot onto the floor with great enthusiasm.

“What are you doing?” asked Derek.

“I’m killing the dragon, grandpa!” he said.

“But I don’t see it,” said Derek.

“You’re silly, grandpa,” he said. “Don’t you know how to kill dragons? If you run away they get bigger and bigger and you’ll never escape. But if you charge forward and face them down they get smaller and smaller until they disappear. I just squished it.”
Handy Data Visualization Functions in matplotlib & Seaborn to Speed Up Your EDA
By: Manu Kalia
Tags: Python, Eda, Matplotlib, Data Science, Data Visualization

For ease of demonstration, I’ll start out by fetching one of the datasets available via Sklearn, the California housing prices dataset. This happens to be a dataset that lends itself to a regression type problem, but the graphing functions I describe below work just as well for categoricals and classification-oriented exercises, either as they are or with minor modifications. If and when you use the plotting functions, you should, of course, use the dataframe that you have set up and ignore this particular dataset.

First, the basic imports:

fig. 1 … basic imports

Next, fetch the demonstration dataset and stick it in a pandas dataframe. There are 20,648 observations in this Sklearn dataset of California housing prices. The eight feature columns reside in the dataset.data structure.

fig. 2 … fetch dataset

Finally, create the target column price (prices in $000,000) which resides in the dataset.target structure. It happens to be placed into a multilevel column index, so I will need to flatten that to one level, as below. I also verified that there were no null values, just to be sure.
Chilean Artist Draws from Covid-19 Hospital Bed
By: Linda Freund
Tags: Creativity, Life Lessons, Coronavirus, Art, Covid 19

What happens when an artist treks the inscrutable space between life and death? Covid-19 survivor Guillermo del Valle coped the way he knows best: he drew.

The Chilean visual artist nearly died, having spent 18 days in a Barcelona hospital. Between oxygen doses, del Valle took whatever supplies he could find near his hospital bed and sketched visual fragments of his coronavirus fight.

“It felt like a Pac-Man was eating my insides making it difficult for me to breathe,” said del Valle about his battle with Covid-19 in March 2020 in Spain.

“I had been in the ICU, my immune system was in crisis, my tired body was ready to let go, and my mind was struggling, alert, sleepless,” the 65-year-old said. At one point, sensing he might not live past the night, del Valle emailed goodbye letters to his wife and children.

“He was about to cross over and came back to life,” said Doctor Ivan Pelegrin of del Valle’s illness.

As Covid-19 wards fill to capacity in large swaths of the United States, del Valle’s sketches offer a unique glimpse into the mental battles unfolding amongst ICU patients.

And his art conveys a simple truth: creation persists in the face of this destructive virus.

“The art became a way to look at myself, at my limit, and to register my fragility, the beauty of life, and the natural part of death,” del Valle said.

“The art became a way to look at myself, at my limit, and to register my fragility, the beauty of life, and the natural part of death,” del Valle said. “I think that by stepping outside of myself in this way, it helped me to fight against the virus. It helped the force of the mind prevail over exhaustion and the tendency to surrender to the body.”
The Enigma Guide to Avoiding an Actual Pandas Pandemonium
Tags: Python, Software Development, Engineering, Tutorial, Pandas

By Pam Wu

When you first start out using Pandas, it’s often best to just get your feet wet and deal with problems as they come up. Then, the years pass, the amazing things you’ve been able to build with it start to accumulate, but you have a vague inkling that you keep making the same kinds of mistakes and that your code is running really slowly for what seems like pretty simple operations. This is when it’s time to dig into the inner workings of Pandas and take your code to the next level. Like with any library, the best way to optimize your code is to understand what’s going on underneath the syntax.

It can be hard to know where to start, though. There are tools out there that can help boost productivity — but what exactly are these tools, and where can you find them?

In the spirit of learning — and sharing! — I recently culled together some of the Pandas tips and tricks I’ve come across over the years. Some of these methods I’ve learned at conferences, others I’ve picked up in books or from colleagues. After running a few tutorials at Enigma — including a session with our Software Craftsmanship Guild, an internal club that promotes the learning and practice of software engineering skills — I realized this information was worth sharing more broadly.

So, here is The Enigma Guide to Avoiding an Actual Pandas Pandemonium, which digs into coding best practices, common silent failures, how to speed up your runtime, and ways to lower your memory footprint. This is a bunch of suggestions for optimizing your Pandas code, conveniently packaged together in one place.

Have thoughts on the tutorial, or tips you want to share? Let us know!

_______________________

Interested in joining the team? Enigma is hiring!
The Trouble with Metaphor
By: Bradley Wester
Tags: Nonfiction, Poet, Creativity, Metaphor, Art

That’s the trouble with metaphor. Many of my students were taught it equaled art. They were trained to come up with something that represented something else. Of course, sometimes, to get to the “thing itself,” we must enlist metaphor. Take writing. It’s filled with them. Used well, crafted well, metaphor can coax out the thing itself. A problem I’ve noticed in the visual arts, especially with young students, is that metaphor can be the end goal. Therefore, all too often, the result is a cliché and ultimately a cop-out.

A bad painting of a butterfly, for example, could have a moving story behind it. At a junior level critique, everyone is enthralled with the student’s story of struggle and transformation, of a new gender designation or the lack of one. How brave they are, is the consensus.

But wait, it’s an awful painting! When metaphor is the objective, this important fact can be ignored. Why did they choose to paint the butterfly in the first place? What would the work be doing if they had cast the butterfly in cement? If they made it out of diaphanous paper? Performed it? Why is the craft meticulous or slapdash? An idea must be transformed through its making to have significance.

“What are the materials doing? What is your artwork doing?” I’d ask.

Never, “What does your artwork represent?” — to my student’s consternation.

A similar dilemma can happen with political work, particularly with political painting, drawing, sculpture, where the artwork itself takes a backseat to the message. Take, for example, a student of Armenian descent who paints a picture depicting some aspect of the Armenian Genocide by the Ottoman Empire during WWI. Again, a compelling story, a righteous intention. But the painting sucks. That critical detail that it’s a shitty painting, or perhaps shouldn’t be a painting at all, can get lost or even regarded as irrelevant.

Political art, almost by definition, stands against. But in his book The Aesthetic Dimension: Toward a critique of Marxist Aesthetics, the German-American philosopher Herbert Marcuse observed that what is in opposition to something else, is horizontally equal to what it opposes. It puts art on the same level as what it counters, becoming one-dimensional, straightforward, intelligible.

When it comes to art with a message, the difficult part is not to mediate with righteous intention all the mystery out of it. The distinction of art is in its ability to transcend social determination and retain its poetical aesthetic nature. In this way, art is autonomous, so it may rise above opposition and conflict even when its stance is critical. To be any kind of artist, one must remain a poet, Rainer Maria Rilke taught me.

When art is autonomous, it is free. Free from all authority but its own. Therein lies its radicality.

This immunity from external authority includes never being contingent on it. Art, including the literary arts, must be entirely itself — other, in some ways mysterious, and true.
When to Write, and When Not to Write
By: Nicole Bryan
Tags: Writing, Writing Tips, Creativity, Art, Writer

ON WRITING

When to Write, and When Not to Write

Simple ideas that will put this debate to bed once and for all

Photo by Mark Landman on Unsplash

Writing is self-expression on steroids. It is penning beautiful thoughts that destroy painful realities.

Writing is meaning multiplied. It is the miracle of taking six deep breaths in, and the magic of taking six deep breaths out.

Writing is discipline dominated. It’s the delirium of dancing with your prince until midnight, then dutifully dashing back home to avoid a bitter disaster.

Writing gives entrance and allows escape.

It takes the burdens off our shoulders and rests them at our feet.

It gives us solace in a world where there’s sometimes victory, and oftentimes defeat.

Oh, dearest writing! Wisdom we dost seek.

To understand when we will — when we won’t.

Or when we do — and when we don’t.

When to write

We write when there’s nothing to write. When, like Hemingway, we “sit down at a typewriter and bleed.”

We write when there’s something to write. When the words pour out and it seems like we’re writing faster than we can read.

We write when we’re sick of life; when life gives us no respect.

“We write to taste life twice, in the moment and in retrospect.”― Anais Nin

We write when we’re scared, when we don’t know where to start.

We write when we’re prepared, oozing passion and creative art.

We write when we’re lonely, facing all kinds of winter blues.

We write when we’re excited, brandishing our laundry list of to-dos.

We write in the middle of the night, inspired by a dream.

We write right after a fight, trying to find the guts to come clean.

We write through the tears, desperately seeking peace.

We write through our fears, praying for a release.

Photo by Seven Shooter on Unsplash

We write when we read, when we learn from the best.

We write when we need to share great experiences with the rest.

We write when we’re obsessed when it’s mind over matter.

We write when we’re depressed, to quiet the inner chatter.

We write when we’re in love, dopamine hits to the heart.

We write when those above demand we sit six feet apart.

We write to survive, to quench our thirst to tell stories.

We also write to thrive, to leverage our glories.

We “write to be a poet, even in prose.” — Charles Baudelaire

We write for various reasons, some so private we’ll never disclose.

We write to discover what we think we might know.

We write to uncover what may get us to flow.

Photo by Daan Mooij on Unsplash

We write when life tells us we have only months left to live.

We write when life yells — and on our knees we finally forgive.

We write when we mourn from the depths of our soul.

We write to ease the pain, to find peace is our goal.

When not to Write

When not to write?

I admit I don’t know.

Is there really a debate?

It’s always a “hell yes!” and never a “hell no.”
How To Get Away
By: Harper Thorpe
Tags: Music, Satire, Poetry, Creativity, Humor

NCiR’ Pilin’ On

How To Get Away

It’s been a while since I gave thought

to gore and death that monster’s wrought.

Memories of being distraught

by doors ajar and clowns Mom bought.

The dark recesses in my room

hid monsters plotting this kid’s doom.

When I’m asleep, they’ll leave their tomb.

Their midnight snack’s me, I assume.

I used to think best stay in my bed

the covers pulled-up o’er my head,

better than going under the bed

where the monster hides to my dread.

But if the monster’s joining me,

I’ll not wait here, his face to see.

So he won’t know my plan to flee,

I’ll say “Excuse me, got to pee!”

©2020 HHThorpe. All rights reserved.
Nightingale’s First All-Visual Article
By: Isaac Levy-Rubinett
Tags: Programming, Data Visualization, History, Books, Music

It’s the most wonderful time of the year.

That’s a common refrain around the holidays, and here at Nightingale, we tend to agree. I mean, when else is there so much time to catch up on reading? And where else will you find articles about the resurgence of vinyl or maps of the Roman Empire’s road networks?

Happy Holidays!

This week, Nightingale published our first graphic article, Surasti Puri’s “An Illustrated Look at the Booker Prize.” In addition to its stunning visuals, the article sheds some light on the gender breakdown of the Booker prize and has some ideas to get you started on your 2020 reading list.

If you haven’t quite finished your holiday shopping, don’t worry — Coleman Harris has you covered with his “Gift Guide for the Data Viz Practitioner.” These books, activities, and tools will make great gifts for anyone who loves making data visualizations.

In 2019, vinyl outsold CDs for the first time since 1986. Allen Hillery wondered, “Is the Resurgence of Vinyl Driven By Nostalgia or Fad?” To help find an answer, he dove into the data.

Paul Kahn continued his series on global information design with “Visualizing Overland Travel, When All Roads Led to Rome.” Learn about the design trick in these early road maps that forms the basis for many of today’s subway maps.

Krishna P wrote “Getting Started With Small Multiples,” in which he explains what small multiples are as well as how you can use them. The upshot is that small multiples are a powerful and effective data viz tool that is extremely underused.