The Python programming language includes sophisticated database programming tools. Python supports a variety of databases, including SQLite, MySQL, Oracle, Sybase, and PostgreSQL. Data Definition Language (DDL), Data Manipulation Language (DML), and Data Query Statements are also supported by Python. The Python DB-API is the database interface standard in Python. This standard is followed by the majority of Python database interfaces.
Python provides several advantages for Data Analysts and Data Scientists. It is an extremely valuable tool for any Data Analyst because to the large number of open-source modules.
For data analysis, we have pandas, NumPy, and Vaex; for visualization, we have Matplotlib, seaborn, and Bokeh; and for machine learning applications, we have TensorFlow, scikit-learn, and PyTorch (plus many, many more).
Python is one of the fastest-growing programming languages, thanks to its (relatively) simple learning curve and versatility. So, if we're using Python for data analysis, it's worth wondering where all this data is coming from.
While datasets might come from a wide range of sources, in many circumstances – particularly in corporate firms – data will be kept in a relational database. If you're looking forward to learning Python you can start with the free resource from
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