Wdatabase 2.2.0a0

A database with multiple data sets that support drawing, These data sets are: World population data set, World Carbon dioxide Concentration data set, World Number of Cities data set, China number of population data set, China number of space vehicles data set......

A database with multiple data sets that support drawing, These data sets are: World population data set, World Carbon dioxide Concentration data set, World Number of Cities data set, China number of population data set, China number of space vehicles data set......

简体中文

• Function introduction
• download
• use
  • Get data
  • import data
  • drawing
  • Data save
• Additional Features
  • Cosine similarity function
  • Distance formula
• What data do we have
• Donation
• About Pypi
• license

Features

This project is a dataset with multiple functions, there are many datasets in it, and it has been uploaded to Pypi.

Download

This project uses Pypi, so it is recommended to use Pypi to download

Code: pip3 install Wdatabase

Use

The package name when we upload is not the same as the package name used in actual use When importing, use the following code

from Wdata import WdataMain as main

The main class has the following functions:

Functions	Introduction	Syntax	Return Type
draw	Draw	Func()	None
Save_file	Save file	Func(filename:str)	bool

Import Data

Wdata has a lot of data sets, here we use 200 years of population growth data as an example

The syntax of Wdata_class is as follows: WdataMain(json_fname: str)

json_fname is the name of the dataset

from Wdata import WdataMain as main

test = main('Population_growth')  # import population growth over 200 years

Get data

We can use the dict() function to fetch the data

such as these codes

from Wdata import WdataMain as main

test = main('Population_growth')  # import population growth over 200 years
print(dict(test))

after running

~/python test.py
{
    '1800': 900000000,
    '1820': 1100000000,
    '1840': 1200000000,
    '1860': 1300000000,
    '1880': 1400000000,
    '1900': 1650000000,
    '1920': 1800000000,
    '1940': 2200000000,
    '1960': 3000000000,
    '1980': 4400000000,
    '2000': 5900000000,
    '2022': 7400000000
    }

Drawing

Drawing functions use the draw() function as the following code

from Wdata import WdataMain as main

test = main('Population_growth')  # import population growth over 200 years
test.draw()

The result is this

Data save

You can use the Save_file() function to save data

The syntax of Save_file is Save_file(filename:str, type=JSON) -> None

Parameter description: The filename 'parameter is used to describe saving a file The type 'parameter is used to describe the file type The file types are as follows:

File Type	Usage	Description
Csv	Wdata. CSV	Save File file.csv
Json	Wdata. JSON	Save the file 'file. json' as the default option
Such as the following code

from Wdata import WdataMain as main
from Wdata import CSV
test=main ('Population_growth ') # Import the Population growth in the past 200 years
test. Save_File ('Package_test ', CSV) # This function will automatically add the. csv suffix

Additional Features

Cosine similarity function

The cosine similarity function can calculate the cosine similarity of two coordinates in two-dimensional space according to the cosine similarity formula usage method:

from Wdata import mathfunc
Xy1=(2, 3) # First coordinate
Xy2=(3, 5) # Second coordinate
Result=mathfunc.similarity (xy1, xy2) # Cosine similarity
print(result)

Distance formula

Distance formula Use Euclid distance formula to calculate the distance between two coordinates in two-dimensional space usage method:

from Wdata import mathfunc
xy1 = (2, 3)
xy2 = (3, 5)
Result=mathfunc.distance (xy1, xy2) # Distance formula
print(result)

What data do we have

Currently we have the following data

name	description	unit of measure
Population_growth	Population Growth 1800-2022	People
Chinese_spacecraft	2017-2020.06 Chinese spacecraft launches	Spacecraft
World_spacecraft	2017-2020.06 World Spacecraft Launches	Spacecraft

The above data comes from Bing and Baidu. The author cannot guarantee the accuracy of the data and should not be used for professional purposes

Donate

Due to special reasons, the author was unable to register a Paypal account and was forced to use Alipay

For details, please see Donation Instructions

About Pypi

The Wdataorg team has used twine to upload this library to Pypi

Wdataorg Pypi account

Wdatabase Pypi warehouse address

License

This open source project uses Apache License 2.0

In the process of using this open source project, please use it strictly in accordance with the license

The final interpretation right belongs to the development team Wdataorg

Project License Link