Python is often the ideal choice. It is also ideal for implementing algorithms, which is something that data scientists need to do often.The three best and most important Python libraries for data science are NumPy, Pandas, and Matplotlib. For more info: https://datamites.com/data-science-course-training-bangalore/

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Python for Data
Analysis
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Python Libraries for Data Analytics
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Pandas - Data Manipulation
Numpy, SciPy - Technical and Scientific Computing
Tensorflow, Keras - Deep Learning
Matplotlib, Seaborn - Visualisation
Beautifulsoup, Scrapy - Web Scraping

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R v/s Python
R is mainly used for statistical analysis.
Python is a programming language used for writing codes.
Python is the most opted programming language used by Data Scientists, than
R. However, R and Python enjoy equal importance.
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Python Libraries for Data Science
Numpy
Facilitates in the performing of mathematical operations easily
Helps in the vectorisation of mathematical operations on matrices
and arrays.
Other Python libraries are built on Numpy
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Python Libraries for Data Science
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SciPy
Collection Linear Algebra algorithms, Optimisation Statistics, Numerical
Integration, differential equations.
It is built on Numpy.

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Python Libraries for Data Science
Pandas
➔ Facilitates in providing tools for Data Manipulation, Sorting, Slicing, Aggregation.
➔ It helps in handling missing data.
➔ Add data structures and the tools which are created to work with table like data.
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