Top Python Libraries Every Data science Aspirant Must know !

1.NumPy

What is NumPy ?

NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

• A matrix is a two-dimensional data structure where numbers are arranged into rows and columns.
• In Numpy dimensions are called axes. The number of axes is rank.
• The first axis ( i.e. axis-0 ) is running vertically downwards across rows, and the second (axis-1) running horizontally across columns.

NumPy Topics

• Array
• Shape and Reshape
• Shape and Reshape with Arange
• Swapaxes
• Understanding Axes
• Matrix Operations
• Slicing - Two-dimensional Numpy Arrays
• Slice a Range of Values from Two-dimensional Numpy Arrays
• Masking and Filtering
• Transposing
• Sorting
• Concatenation
• Ones
• Zeros

2.Pandas

What is Pandas ?

Pandas is a software library written for the python programming language for data manipulation and analysis.

• Pandas is built on top of the NumPy package, meaning a lot of the structure of NumPy is used or replicated in Pandas.
• Data in pandas is often used to feed statistical analysis in SciPy, plotting functions from Matplotlib, and machine learning algorithms in Scikit-learn.
• The primary two components of pandas are the Series and DataFrame.

1.Pandas Series and Dataframe

• Series in Pandas
• DataFrame in Pandas
• Quick Recap

2.Pandas Viewing Data

• Pandas dataframe.head() and dataframe.tail() functions
• Pandas dataframe dropna(), describe(), unique() and to_numpy() function
• Dealing with Columns in Pandas DataFrame
• Dealing with Rows in Pandas DataFrame
• Select multiple columns in a Pandas Dataframe
• Extracting multiple rows using .loc[]
• Extracting multiple rows using .iloc[]
• Indexing and Selecting Data with Pandas
• Boolean Indexing in Pandas Dataframe
• Applying a boolean mask to a dataframe
• Quick Recap