Discover and read the best of Twitter Threads about #DataAnalytics

Most recents (24)


Learn 21 pandas tricks that will help you to work faster, write better pandas code, and impress your friends!

Click here to watch:
👉 👈

#Python #DataScience #DataAnalytics Image
Here are a few of my favorites from the video:

6. Convert one set of values to another
11. Read and write from compressed files
14. Transpose a wide DataFrame
16. Identify rows that are missing from a DataFrame
17. Use query to avoid intermediate variables
And if you haven't seen my top 25 pandas tricks, definitely check that out as well! 👇

Read 3 tweets
Problem types Data Analysts work with...

A thread👇
1. Making Predictions: this involves using data to make informed decisions about how things may be in the future.

2. Categorizing things: this has to do with assigning information to different groups or clusters based on common features/characteristics.
3. Spotting something unusual: everything follows a particular trend, a data analyst is able to solve problems if (s)he is able to identify data that is different from the norm.

4. Identifying themes: this takes categorization a step further by grouping information into broader
Read 5 tweets
Qué lindo es el #Plugin #QuickOSM de #QGIS!!! Con él se pueden consultar datos de #OpenStreetMap de forma rápida dentro de QGIS.
#Hilo con ejemplos ->
Por ejemplo, se pueden consultar depósitos de agua, tipo cisternas o tanques australianos. Para el Partido de Pergamino la cuenta da aproximadamente 1500 tanques!
También se pueden traer a QGIS molinos de viento. Más de 1000 elementos.
Read 5 tweets

"roc_auc_score" is defined as the area under the ROC curve, which is the curve having False Positive Rate on the x-axis and True Positive Rate on the y-axis at all classification thresholds.

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python
Read 17 tweets
Just restarted the Google Data Analytics professional course on Coursera, done with part one and moving on. Fun fact, some employers even in USA rate the course as equivalent to a degree in Data Analytics. If you want to take the course, follow for details shortly #DataAnalytics
The Google Data Analytics professional Certificate course is an entry level course that trains individuals to become data analyst from scratch. There is no prior knowledge required as the course will take you through from the basics.
It is structured into eight different courses with a certificate for each course and a final Data Analyst certification when you have completed the entire program with exams and quizzes. It has courses that covers spreadsheet, data visualization, data presentation, SQL, R etc.
Read 11 tweets
Often get asked how to apply for the Google Data Analytics Certification Course financial aid on Coursera.

Here is a question based template for the two questions asked.


You are applying for financial aid because
1. Where are you from? e.g a third world country.
2. How hard is it to make a decent living there?

3. What will you be left with if you pay the required sub amount? e.g little to nothing.

4. Why don't you want to miss out of the privilege?
Read 7 tweets
Here's a thread of 30+ FREE Courses. From AWS Exam Prep, SQL, Cloud, Machine Learning, Analytics, Data Governance and Security courses.

Cloud based roles are the future of work, build your own learning roadmap and start today!🧵
AWS Cloud Practitioner Essentials…
Exam Readiness: AWS Certified Solutions Architect – Professional…

Exam Readiness: AWS Certified DevOps Engineer – Professional…

#DataAnalytics #datascience #data #cloud Image
Read 10 tweets
My Project Management journey!
I just stated the Google Project Management: Professional Certificate through Coursera and I have decided to update my learning journey, so this will be a thread of my progress. #BlackTechTwitter #womenintech #projectmanagement #baddiesintech
Day 1
Course: Foundations of Project Management
Now I have basic understanding of project management and what a project manager does (planning and organizing, managing tasks, budgeting and controlling costs).
Read 100 tweets
7 Secrets To Help You Master Python Data Science


#Python #datascience #dataanalytics
1. Focus on Foundations ImageImage
Many people try to start with the coolest, sexiest topics (like machine learning).

You'll do much better if you focus on foundational topics like data wrangling, data visualization, and data analysis.

#datascience #Python #datavisualization
Read 19 tweets
How to Make Small Multiple Charts in Python, with Plotly


#datascience #datavisualization #Python #pythonlearning
Remember: small multiple charts break out a visualization by a categorical variable.

We take a simple chart and break it out into panels.

#Datavisualization #datascience
There are a variety of tools to make small multiple charts in Python, including the Seaborn FacetGrid technique.

#Python #Datavisualization #datascience

Read 14 tweets
In Canada, for example, #DataAnalytics collected from 5,682 youth, aged 9 to 17 years, indicates that 99% reported having used the Internet at least to some extent, and 79% reported having Internet access at home (Media Awareness Network, 2001).… While 40% of secondary students reported using the Internet for playing/downloading games, 62% of elementary school age students did so similarly. Data from the 2000 Programme for International Student Assessment (PISA) indicates that 90% of… 15-year-olds have computers at home, and that 48% reported playing games on the Internet, at least a few times per week (Willms & Corbett, 2003).
Read 7 tweets
Thread 🧵-

Here's how you can produce a clean chart that your audience can easily read and understand, without much ado.

Follow along 🤗

#RStats #DataScience #dataviz #DataAnalytics #DataFam
1. Remove gridlines and axis lines from your chart, unless it's difficult to track the points you've plotted without them.

#RStats #tidyverse #datafam #dataviz #DataScience
2. Add trend lines/reference lines to guide the audience on what the numbers were expected to look like vis-a-vis what they actually look like.

Ensure the color scheme of the trend lines doesn't overshadow the plot. Keep them subtle, probably in grey

#RStats #dataviz #tidyverse
Read 6 tweets
It is Estimated to have 11,000,000+ job openings 🚀in Data Science industry by 2026.

Building is portfolio to stand out is absolutely necessary.

Tips to build your #datascience portfolio. A Thread 🧵 Image
1. GitHub Profile - @github
▶️Over 65 million developers and more than 3 million companies use GitHub . GitHub says that 72% of Fortune 50 companies use the site.
▶️ There is always debate about GitHub over blog. I started with blog and later created GitHub profile
1.1 GitHub Profile - @github
▶️A crucial part of data science jobs is to be able to code, and GitHub serves as a perfect platform to access the coding skills and display hands-on ability to solve problems.
▶️If you are beginner or a student @github is must to stand out
Read 15 tweets
Continuing the #learningpath series
⭐Next skill in #DataScience industry is R programming (One of the most important and my favorite)
⭐There always been a debate around R v/s Python
⭐Step by step learning path for R programming

A Thread 🧵
1. Introduction to R
⭐Introduction to R
⭐Arithmetic operation
⭐Variable assignment
⭐Basic Data types
⭐Vectors, Matrix, List, Array and Data Frames
⭐Factors, Factor levels, Ordered factors
2. Data Input and Output in R
⭐Intro to import data
⭐Reading csv, txt, flat and excel files
⭐Saving output
Read 10 tweets
Data is the new oil. And we are truly guzzling it. We have come a long way since Kbs of data with dial up networks to Gbs of data on broadband connections. Data Analytics has become key and is used by Netflix, Facebook & Instagram to keep us hooked on their platforms.
Data Analytics business opportunities are like the IT opportunities of the late 1990s, and India has a massive engineering talent base with excellent mathematics skills, available at a very low cost. This provides India with the perfect ability to capture the opportunity.
That’s where #latentview comes in. Latent View Analytics is a pure-play data analytics company. Its expertise includes customer profiling, targeted marketing, supply chain management, finance and risk management, and HR functions.
Read 5 tweets
Continuing the #learningpath series
⭐Next skill in #DataScience industry is @MSPowerBI (One of the fastest growing #skills 🚀)
⭐Power BI is one of the leaders in Analytics and BI platforms in @gartner magic quadrant
⭐Step by step learning path for Power BI

A Thread 🧵
1- Getting Started with @MSPowerBI
⭐Power BI Interface
⭐Design flow
⭐Type of data sources
⭐Data Terminology
2.1- Connecting to Data and Intro to Query Editor
⭐Type of Data Sources
⭐Intro to the @MSPowerBI Query Editor
⭐Table Transformations
⭐Text, Number & Date calculations
⭐Index & Conditional Columns
⭐Grouping & Aggregating Data
⭐Pivoting & Unpivoting
Read 13 tweets
Continuing the #learningpath series.
Next skill in #DataScience industry is SQL (One of the most In-Demand Skills )
⭐There are 1,000,000+ jobs available in USA with requirement of SQL as a skill

Step by step learning SQL for data scientists

A thread🧵
#data #datascience #sql Image
1. SQL Basics
⭐ Creating Tables
⭐ Inserting values
⭐ Adding a New column in the existing Table
⭐ Deleting a Column from a Table
⭐ Deleting the Table
2. SQL start with Commands
⭐ Learn basic SQL commands: SELECT, FROM and WHERE
⭐ Learn logical operators in SQL
⭐ Learn commands: IN , AND, OR, NOT, LIKE, NULL, ISNULL, BETWEEN
Read 11 tweets
Continuing the #learningpath series.
Next skill in #DataScience industry is @tableau.
Industry leader in Business intelligence and data visualization (one of the most demanding skill)

Step by step learning @tableau
#datafam #dataviz
A thread 🧵
1. Getting Started with @tableau -
⭐ The Tableau Interface
⭐Design Flow
⭐File Types
⭐Data Types
⭐ Show Me
⭐ Data Terminology

#datafam #dataviz
2. Connecting with Data in @tableau -
⭐Data Sources
⭐Custom Data View
⭐Extracting Data
⭐Fields Operations

#datafam #dataviz
Read 10 tweets
There are some other skills you can use as an #SEO to find new ideas or to diversify your role.

They involve different fields where you can try to expand your knowledge and I think that some mixes can be quite interesting.

This is a thread 🧵
1. Coding: be it web development or any other form, coding can actually improve your logic and make you stronger in Tech SEO.

More and more jobs will probably integrate programming languages and knowing either Javascript or #Python3 can help you in getting started.
2. Data Analytics/Science: they don't involve coding alone, you have to know some mathematical/statistical concepts as well.

This is an interesting mix right now and could prove more invaluable in the next future.

#DataScience #DataAnalytics
Read 11 tweets
Over the next few days I’ll sharing the learning path for the tools used in #datascience industry.
First and MUST HAVE skill if you want to break into #datascience is @msexcel
A thread 🧵
1. Enter Data and create basic Tables in @msexcel
2. Start with Building, Formatting, Editing, Proofing, Managing and Printing Worksheets in @msexcel
Read 12 tweets
How to Create Small Multiple Charts in Python, with Plotly


#python #datascience #pythoncode #datavisualization

Before I get into the mechanics of how to create a small multiple charts in Python, let me quickly explain why they are so important.

Small multiple charts are one of my favorite chart types.

They are very powerful, and also highly under-used.

#datascience #dataanalytics #datavisualization
Read 23 tweets
How to Do a Data Analysis


#datascience #DataAnalytics #Python #rstats

When you do data analysis, you first need to start by clarifying objectives.

Why are you doing the analysis?
What’s the end goal? (e.g., the thing you’re trying to improve, understand, etc)

#datascience #DataAnalytics #data

To do this in a business setting, you’ll typically talk with stakeholders, business partners, and other team members who are familiar with the subject of the analysis.
Read 42 tweets
Thread 🧵-

Creating a good #dataviz with the right colours might seem like a herculean task, but it's not.

So, here are six pointers that might help ease your process. Follow along 🤗

#datafam #DataAnalytics #RStats #DataScience
1. Use as few colours as possible to convey your idea - try & look for means to group your variables in such a way that fewer colours can be used to convey your point better.
Eg: Top N products in one colour & the others in another, instead of one colour for each product
2. Use gray in your chart - it is strong enough to be distinguished from white so your variable won't blend into the background, and you can easily combine it with a stronger colour like red if you want to show contrast or highlight another variable

#datafam #dataviz #Rstats
Read 7 tweets

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