[Learning Notes] [Data analysis] 01.Python Getting Started

1. Install Python and environment configuration

①

② installing PIP and using Pip to install the Python library

2, Anaconda Installation

Conda list to be in the root environment

3. Common Data Analysis Library

①numpy

Installation: Conda install NumPy (Conda installed on Anaconda, Pip is installed locally)

Provides commonly used numeric, array, matrix functions.

Based on the "vectorization" operation, the numerical operation is higher than the list.

②scipy

Installation: Conda Install scipy

is an expansion pack that uses NumPy to do advanced math, signal processing, optimization, and statistics.

③pandas

Installation: Conda Install pandas

It is also a numpy-based extension package that supports CSV file input, integrates time series, and handles data processing.

Important data structures: Series and DataFrame

Specific operation:

Show entire table All rows: Head (), Presentation table first row: Head (1)

Some properties of the presentation table:

Table goto rank:

To sort a column in a table:

④matplotlib

Installation: Conda Install Matplotlib

Seaborn Library

[Learning Notes] [Data analysis] 01.Python Getting Started