Wdatabase 2.3.0

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 There are some dependent libraries, please paste the following code into the terminal

pip3 install simplejson
pip3 install openpyxl
pip3 install matplotlib
pip3 install setuptools

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, type='json', Sheet='Data', RowOrColumn=True)	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, Sheet='Data',RowOrColumn=True) -> None

Parameter description: The filename 'parameter is used to describe saving a file The type 'parameter is used to describe the file type Sheet only takes effect when saving a .xlsx file, representing a saved worksheet

RowOrColumn only takes effect when saving a .xlsx file, indicating the saved format 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
XLSX	Wdata.XLSX	Save File file.xlsx

Such as the following code

from Wdata import WdataMain as main
test = main('Population_growth') 
test. Save_file('Package_test') # Default option

Save the code for the CSV file

from Wdata import WdataMain as main
from Wdata import XLSX
test = main('Population_growth') # Population growth over the past 200 years
test. Save_file('Package_test', CSV) # The function automatically adds .csv suffix

Saving .xlsx files uses the Sheet and RowOrColumn parameters

Sheet means save cell, which defaults to Data

RowOrColumn means saved form, defaulting to True

from Wdata import WdataMain as main
from Wdata import XLSX
test = main('Population_growth') # Population growth over the past 200 years
test. Save_file('Package_test', XLSX) # This function automatically adds .xlsx suffix
# test. Save_file('Package_test', XLSX, RowOrColumn=False) This code is saved as a column

When RowOrColumn is True, the saved form looks like this

1820	1840	1860	1880	1900	1920	1940	1960	1980	2000	2022
1100000000	1200000000	1300000000	1400000000	1650000000	1800000000	2200000000	3000000000	4400000000	5900000000	7400000000

On the contrary, it is like this

1820	1100000000
1840	1200000000
1860	1300000000
1880	1400000000
1900	1650000000
1920	1800000000
1940	2200000000
1960	3000000000
1980	4400000000
2000	5900000000
2022	7400000000

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