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

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

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

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:

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

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 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

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:

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

On the contrary, it is like this

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 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)

Currently we have the following data

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

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

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

Wdataorg Pypi account

Wdatabase Pypi warehouse address

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