Python is a programming language used for data analysis, artificial intelligence, create software, apps and automation.
Reason for Python Popularity
-It is east to read and learn because of its syntax.
-It works well with large datasets thus do ETL processes.
-It is good for visualization.
-Python can also automate tasks e.g generating reports
-It also has powerful libraries e.g pandas, matplotlib, scikit-learn.
Python Libraries used in Data Analysis
Pandas- It is used for tables and datasets
Matplotlib-It is used for charts and graphs.
Numpy-It is the fundamental package for computing in python. It provides support for large, multi-dimensional arrays and matrices.
Scikit-learn-It is the go to machine learning library in python
Real World examples of Python in Data Analytics
1.Business and Finance-Used for customer and revenue analytics, customer lifetime modelling and risk and fraud detection.
2.Healthcare-Used for clinical data analysis by processing electronic health records extracts to identify patient cohorts,
treatment outcomes and adverse event patterns.
3.Operations and Supply Chain-Retailers like Walmart use python to build time-series model, predict inventory needs by region.
4.Public Sector and Research-Governments use Python to weight survey responses, impute missing data and generate population estimates.
Beginners should learn python because it removes friction at nearly every stage of learning, lets you focus on problem-solving rather than fighting the language itself
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