python essentials for data science
Is only Python enough for data science?
There's no wrong choice when it comes to learning Python or R.
Both are in-demand skills and will allow you to perform just about any data analytics task you'll encounter.
Which one is better for you will ultimately come down to your background, interests, and career goals.What Python library is required for data science?
Pandas.
Next in the list of python librabries is Pandads.
Pandas (Python data analysis) is a must in the data science life cycle.
It is the most popular and widely used Python library for data science, along with NumPy in matplotlib.Comprehensive learning path – Data Science in Python
Comprehensive learning path – Data Science in Python
1Step 0: Warming up.
2) Step 2: Learn the basics of Python language.
3) Step 3: Learn Regular Expressions in Python.
4) Step 4: Learn Scientific libraries in Python – NumPy, SciPy, Matplotlib and Pandas.
5) Step 5: Effective Data Visualization.
What is needed in Python for data science?
Python has libraries with large collections of mathematical functions and analytical tools.
In this course, we will use the following libraries: Pandas - This library is used for structured data operations, like import CSV files, create dataframes, and data preparation.
Numpy - This is a mathematical library.
- Data types. Python offers many built-in data types, including floats, integers, and strings.
- Operators.
- Variables.
- Lists.
- Dictionaries.
- Functions.
- Control structures.
- Modules and packages.
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