MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 10 lectures (2h 1m) | Size: 1.77 GB
Get a kick start on exploratory data analysis using Descriptionly library
What you’ll learn:
Exploratory data analysis using Descriptionly library
Making different Descriptions like BarDescription, ScatterDescription etc.
Visualizing data through graphs
Using different functions to make the graph look more accurate
Applying conditions to the dataset
Basic knowledge of python programming language
Welcome to the Descriptionly library Tips exploratory data analysis course! An excellent choice for beginners and professionals looking to expand their knowledge on one of the most popular Python libraries in the world i.e Descriptionly library. This course includes case study for drawing meaningful insights out of given data.
Descriptionly library Tips exploratory data analysis course offers video tutorials on the most powerful data analysis toolkit available today.
Why learn Data Analysis and Insights Visualization using Python?
If you’ve spent time in a spreadsheet software like Microsoft Excel, Google Sheets or any form of tabular data such as database tables, delimited files or csv files and are eager to take your data analysis skills to the next level using python, this course is for you!
Descriptionly Python Open Source Graphing Library
Descriptionly’s Python graphing library makes interactive, publication-quality graphs. Examples of how to make line Descriptions, scatter Descriptions, area charts, bar charts, error bars, box Descriptions, histograms, heatmaps, subDescriptions, multiple-axes, polar charts, and bubble charts.
The Descriptionly Python library is an interactive open-source library. This can be a very helpful tool for data visualization and understanding the data simply and easily. Descriptionly graph objects are a high-level interface to Descriptionly which are easy to use. It can Description various types of graphs and charts like scatter Descriptions, line charts, bar charts, box Descriptions, histograms, pie charts, etc.
So you all must be wondering why Descriptionly over other visualization tools or libraries? Here’s the answer –
Descriptionly has hover tool capabilities that allow us to detect any outliers or anomalies in a large number of data points.
It is visually attractive that can be accepted by a wide range of audiences.
It allows us for the endless customization of our graphs that makes our Description more meaningful and understandable for others.
So in this course you will get to learn visualization using the Descriptionly library
Who this course is for
Data Science enthusiasts interested in learning exploratory data analysis using library