Using Python for data analysis basic series summary, python Data Analysis
A total of 15 essays, mainly to record some small demos in the data analysis process and share them with other users who need them. In order to facilitate future viewing, 15 essays, the content of each article is based on a description and a piece of code to keep it simple, small, and clear. It can be divided into three parts: The first part briefly introduces data analysis, A small example illustrates what data analysis and IPython tools are. The second part is the basic use of NumPy. NumPy is a Python package that provides scientific computing functions, mainly ndarray objects; the third part is the basic use of pandas, mainly the Series and DataFrame objects. These two objects provide data structures and functions related to processing structured data. pandas vector operations are very convenient for arrays, it can easily process a lot of data, such as data cleansing, conversion, and merging.
The first section briefly introduces(1) Brief Introduction (2) Try to process a piece of JSON data and generate a bar chart (3) Use IPython to improve development efficiency
Part 1 NumPy Basics(4) NumPy basics: ndarray (5) NumPy basics: ndarray indexing and slicing (6) NumPy basics: vector computing
Part 1 pandas Basics(7) pandas basics: Brief introduction of Series and DataFrame (8) pandas basics: basic operations of Series and DataFrame (9) pandas basics: summary statistics and computing (10) pandas basics: processing of missing data (11) pandas basics: hierarchical indexing (12) pandas basics: data merging (13) pandas basics: Data remodeling/axial rotation (14) pandas basics: data conversion (15) pandas basics: String operations
In fact, data analysis is not just about this, but there are several other major aspects that have not yet been involved, such as data reading and storage and data visualization. However, I plan to learn about data mining first, I think this is more suitable for me, so I will continue to record and share someData collectionInterested parties are welcome to follow this blog, and you are also welcome to add comments for discussion.