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VLOOKUP implementation in Python in three simple steps
Oftentimes, in the field of data analytics, it’s the data cleaning and processing that takes the most amount of time and effort. While the steps such as data cleaning, filtering, and pre-processing are generally under-evaluated or overlooked as compared to more juicy components such as the model development, it’s the quality of data that determines the quality of output. As it is rightly said, (…)
#019 Wykres świecowy (Candlestick Chart)
Wykres świecowy (ang. Candlestick Chart) jest używany głównie jako narzędzie do wizualizacji i analizy ruchów cen w czasie dla papierów wartościowych, instrumentów pochodnych, walut, akcji, obligacji, towarów itp. Chociaż symbole używane na wykresach świecowych przypominają wykres pudełkowy, działają one inaczej i dlatego nie należy ich mylić ze sobą. Wykres świecowy … Artykuł #019 Wykres (…)
17 Killer Websites for Web Developers
99.8% don’t know all of them. Keeping websites handy can be the ultimate productivity hack, Here are some of the best websites I use to make my life easier. Let’s take a look at them one by one. 1. Random Image via API Link The most powerful photo engine in the world. The Unsplash API is a modern JSON API that surfaces all of the info you’ll need to build any experience for your users Unsplash 2. (…)
How to create fast and accurate scatter plots with lots of data in python
Create scatter plots with hundreds of millions of samples in milliseconds without trial and error. Scatter plots are quite basic and easy to create — or so I thought. Recently I had to visualize a dataset with hundreds of millions of data points. If you’re a Python developer you’ll immediately import matplotlib and get started. But it turns out there are better, faster, and more intuitive ways to (…)
4 Python Libraries that Make It Easier to Work with Large Datasets
Essential guide to read and process large size datasets Image by LEEROY Agency from Pixabay Pandas is one of the popular Python libraries in the data science community. It comes up with high performance, easy-to-use data structures, and data analytics tools for the Python language. But when it comes to handling large-size data, it fails miserably. Pandas mainly use a single core of CPU to process (…)
Beginner’s Guide on Data Visualization with Google Data Studio
Beginner tutorial to visualize and understand data better with Data Studio Introduction Data Science is all about dealing with data and an important subset is Data Visualization where you communicate and present the information of your final result in an interactive and visual manner. Other than using data visualization for presenting results to end-user, I often used data visualization in (…)
Computer Vision Web API : Flask + base64
Computer Vision Web API : Flask + base64 Over the past twenty years, we’ve seen the WWW evolve from static to dynamic pages, from data to services. And soon AI has developed over ubiquity, on-demand and integration. Privacy and end-user concern: files or data? If you want to develop a computer vision WebAPI , you will soon have to dive into privacy and end-user concerns ( “Hey man, what will you (…)
How to convert a Python Jupyter notebook into an RMarkdown file
Pythonist, give RMarkdown a try and prepare to be amazed! 1. Introduction NOTE: If you want to jump right into my code, go straight to section 3 (“From Jupyter to the RMarkdown world”) . Python was my first love when I started my journey in the programming world a couple of years ago, and it is still my favorite language. However, for the last few months, I’ve been more and more into R, due to (…)
Mastering Web Scraping in Python: From Zero to Hero – ZenRows
Master Pro techniques & tips for scraping any website at scale. Everything from hidden endpoints to rich-content metadata.
Combining Python and R for FIFA Football World Ranking Analysis
Showcasing the complementary strengths of Python and R in the field of data science and analytics Summary Both Python and R are excellent programming languages for data analysis, and each has its rightful place in the data science toolkit. If you are focused on statistical modelling or generating graph visualizations from your data, R is a more straightforward option. On the other hand, Python is (…)
How To Discover The Laws Of Physics With Deep Learning and Symbolic Regression
Deep Learning From https://www.pinterest.ru/pin/801781539891918164/?amp_client_id=CLIENT_ID(_)&mweb_unauth_id=&simplified=true Scientist vs Machine Learning “ I am turned into a sort of machine for observing facts and grinding out conclusions .” — Charles Darwin Science cannot work without data. Similarly, machine learning cannot work without data. The scientific method and machine (…)
Animating Network Evolutions with gganimate
People regularly ask me if it is possible to animate a network evolution with {{ggraph}} and {{gganimate}}. Unfortunately this is not yet possible. But fear not! There is a way to still get it done with some hacking around the ggraph package. In th… Continue reading : Animating Network Evolutions with gganimate
How to Implement Cloud APIs: Google Drive API, Dropbox API, and OneDrive API
Practical application of Cloud APIs such as Dropbox, Google Drive, and OneDrive can be tricky. To simplify, we described the integration process step-by-step. Read the full story
Recommender System from Scratch
An Intuitive Walkthrough Source: Creative Commons Introduction When I started my Machine Learning Journey, there were a few concepts that fascinated me a lot one such thing was the recommender systems. This was one of those ML applications you could see in see extensively in your day-to-day life. While shopping on amazon, buying clothes at Myntra, watching movies on Netflix, we had (…)
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