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股票的K线图的均线的数据是怎么计算出来的

股票的K线图的均线的数据是怎么计算出来的

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股票的K线图的均线的数据是怎么计算出来的

Python tutorial: Taught you how to build your own 股票的K线图的均线的数据是怎么计算出来的 database of quantitative analysis

introduction:

Financial data is an important basis for quantitative analysis of historical transaction data including stock listed company fundamental data, macro and industry data. With the ever-expanding flow of information, learn acquisition, data processing and query information 股票的K线图的均线的数据是怎么计算出来的 is becoming increasingly important. For people 股票的K线图的均线的数据是怎么计算出来的 who tinker with quantitative trading, how can you say the database will not play it? The most commonly used open source (free) database has MySQL, Postgresql, Mongodb and SQLite (Python comes), among the top ten (see below) in the 2018- 2019 DB-Engines list, showing its use and popularity higher. These databases have their own characteristics and application environment, learning how to learn 股票的K线图的均线的数据是怎么计算出来的 on the Internet or which have a lot of relevant information. This article is a brief introduction on how to use Python operate Postgresql database (similar to other databases), use psycopg2 and sqlalchemy achieve dataframe postgresql interact with pandas, step by step to build their own quantitative analysis database.

Installation and use of PostgreSQL

Install PostgreSQL. To its official website to choose their own computer configuration download version can 股票的K线图的均线的数据是怎么计算出来的 be installed, the installation process in addition to set a password (This article is set to "123456"), all the other optional default, truthfully do not 股票的K线图的均线的数据是怎么计算出来的 refer to the article on the CSDN: PostgreSQL installation detailed steps (windows). After 股票的K线图的均线的数据是怎么计算出来的 installation can also be seen in the installation directory pgAdmin4, this 股票的K线图的均线的数据是怎么计算出来的 is the database that comes with graphical tools, the latest version of a Web application, somewhat similar to Python's Jupyter Notebook, it can be used to view and manipulate the postgresql database.

Psycopg2 installation and sqlalchemy library on Python. Python is psycopg2 PostgreSQL database interface, SQLAlchemy broader application, may be connected to a database (MySQL, SQLite, PostgreSQL), especially for data type dataframe pandas, the operation is very convenient. The two had a lot of python libraries introduce online, not to proceed here in detail, using pip install xxx can be installed on cmd.

Examples of applications

First, tushare get more than 3000 stock market data to local, psycopg2 and sqlalchemy use the interface, the data is stored in a local PostgreSQL database, to facilitate further inquiries and operations.

Data acquisition 股票的K线图的均线的数据是怎么计算出来的 function, the default time can be 股票的K线图的均线的数据是怎么计算出来的 changed at any time.

Insert PostgreSQL database operations, functions in use try . except . pass in order to avoid some data errors cause the program to crash.

Due to the huge amount of market data download more slowly, to download the daily trading period 20190101-20190425

Data, subsequent re constantly updated.

Construction of a data update function can be downloaded, and other data inserted into 股票的K线图的均线的数据是怎么计算出来的 the time period. January 1, 2018 to April 25, 2019, data had reached 1.08 million.

Check stock quotes Japanese stocks rose more than 9.5%, data distribution:

股票名称前出现N、C、U、W和V代表什么意思?

4、补充解释:除权简称"XR",除息简称"XD",除权除息统称为DR,它要对前收盘价进行修正。 除息日当天即除息基准日会出现除息报价,即基准日前一天的市场收盘价减去该公司应发放的现金股利,它是除息日当天开盘价的参考价。 除权日当天叫除权基准日会出现除权报价。除权价格的计算,分三种情况:1.送股时:除权价格=(除权日前一天收盘价)÷( 1+送股率)。2.有偿配股时;除权价格=( 除权日前一天收盘价+配股价×配股率)÷(1+配股率)。3.送股与有偿配股相结合时:除权价=除权日前一天收盘价=配股价×配股率÷(1+送股率+配股率) 如除权和除息同时进行,计算公式为:当日除权除息报价=(前一日收盘价-股息金额+配股价×配股率)÷(1+配股率+送股率)