Hey There fellas, i'm back with an amazing easy to go tutorial. W will be discussing one of the key factors for Data Science and Data Analytics i.e DataVisulaization
I personally find difficulty in DataVisualization , when to plot what to plot and how to plot. After a couple of hours digging into the internet i realized the best way to
learn DataVisulaization is to analyze the pre existing datasets instead of spending days understanding each and every plot. I thought why not share my personal notebooks and help people learn too?, The notebooks in this repo contains all you need to know to understand DataVisulization. I tried my best to cover as many topics i could. In the 1st notebook we will be looking into the one of the most famous IRIS datset which contains species of flowers, we will be analysing the species and their relation using matplotlib, in the second notebook we will be analysing the Titanic Dataset using core plots in Seaborn library, not gonna lie seaborn offer the best plots with amazing visual aesthetic.In the second notebook we will be analysing the Penguins dataset using seaborn. Remeber this notebooks are not intended to teach matplot or seaborn or plotly my main intention is to make DATAVISUALIZATION easier and fun. That being said for people of who dont know WHAT IS DATAVISUALIZATION, here is the explanantion:
- Data visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from. The main goal of data visualization is to make it easier to identify patterns, trends and outliers in large data sets. The term is often used interchangeably with others, including information graphics, information visualization and statistical graphics.
- Data visualization is one of the steps of the data science process, which states that after data has been collected, processed and modeled, it must be visualized for conclusions to be made. Data visualization is also an element of the broader data presentation architecture (DPA) discipline, which aims to identify, locate, manipulate, format and deliver data in the most efficient way possible.
- Data visualization is important for almost every career. It can be used by teachers to display student test results, by computer scientists exploring advancements in artificial intelligence (AI) or by executives looking to share information with stakeholders. It also plays an important role in big data projects. As businesses accumulated massive collections of data during the early years of the big data trend, they needed a way to quickly and easily get an overview of their data. Visualization tools were a natural fit.
- Visualization is central to advanced analytics for similar reasons. When a data scientist is writing advanced predictive analytics or machine learning (ML) algorithms, it becomes important to visualize the outputs to monitor results and ensure that models are performing as intended.
- Data visualization provides a quick and effective way to communicate information in a universal manner using visual information. The practice can also help businesses identify which factors affect customer behavior; pinpoint areas that need to be improved or need more attention; make data more memorable for stakeholders; understand when and where to place specific products; and predict sales volumes.
Other benefits of data visualization include the following:
- the ability to absorb information quickly, improve insights and make faster decisions;
- an increased understanding of the next steps that must be taken to improve the organization;
- an improved ability to maintain the audience's interest with information they can understand;
- an easy distribution of information that increases the opportunity to share insights with everyone involved;
- eliminate the need for data scientists since data is more accessible and understandable; and
- an increased ability to act on findings quickly and, therefore, achieve success with greater speed and less mistakes.
yup that's it for now, you are free to download the release or click HERE to download zip or go on to the kaggle and find my notebooks there. On kaggle you can directly run the notebok via internet and you're system resources.
- Learn-DataVisulization-WithMe-part-1
- Learn-DataVisulization-WithMe_seaborn-1
- Learn-DataVisulization-WithMe_seaborn-2
note:
- will shortly add plotly notebook, still in process of learning it. will update asap