Python is very accessible, it is new to many users. This makes the individuals clean up data and perform advanced operation. The functionality such as enabling the row-and-column datasets import as CSV files and beyond makes Python a widely used tool for data analysis. Pandas is one such tool built based on Python for data analysis and manipulation tool. Also, there are numerous other specialized libraries which are all used for the same purpose such as SymPy for statistical applications, matplotlib which is for plotting and visualization. These and a couple of other libraries support in machine learning to data processing to neural networks. As already mentioned, Python is accessible and flexible in nature that hugely encourages data scientists to use the tool.
What you will Learn?
- Learn how to use Python to create data visualizations.
- Read and write data with Python, Webdev 101, also extracting data off the web with Python.
- Data Visualization, Development Setup and Language Learning Bridge between Python and JS.
- Learn Scraping with Scrapy, Plotting and Visualization, Data Aggregation and Group Operations.
- Financial and Economic data application.
This course is primarily useful for:
- Business Analysts
- Data Scientists
- The individuals who are interested in data science and visualization
- Software Developers and Programmers who have the desire to upgrade and explore their career in data science and machine learning path