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https://github.com/econcz/pyconvertu
Tools for creation or conversion of lists from/to desired classification (the default is ISO 3166-1)
https://github.com/econcz/pyconvertu
alpha-2 alpha-3 classification english french iso-3166 numeric pypi python3 regular-expressions
Last synced: 24 days ago
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Tools for creation or conversion of lists from/to desired classification (the default is ISO 3166-1)
- Host: GitHub
- URL: https://github.com/econcz/pyconvertu
- Owner: econcz
- License: mit
- Created: 2021-05-28T21:47:46.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-02-22T13:44:15.000Z (9 months ago)
- Last Synced: 2024-04-24T11:11:26.776Z (7 months ago)
- Topics: alpha-2, alpha-3, classification, english, french, iso-3166, numeric, pypi, python3, regular-expressions
- Language: Python
- Homepage:
- Size: 41 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# Tools for creation and conversion from/to desired classification (the default is ISO 3166-1)
This project was inspired by **[pycountry](https://pypi.org/project/pycountry/)** and **[pycountry-convert](https://pypi.org/project/pycountry-convert/)** modules and is a port of the **Stata package** **[pyconvertu](https://ideas.repec.org/c/boc/bocode/s458892.html)** *(Stata module to convert a string variable into a classification from the default or user-provided JSON file with the help of Python 3)* written in Python 3 and ADO. The tools can, for example, be used together with **[pandas](https://pypi.org/project/pandas/)** to process **pandas.DataFrame()**, `data`, `index`, and / or `columns` (consult examples):
- ``convert(source_file=None, from_list=[], to_classification='')`` converts a **tuple** or a **list** into a classification from a built-in or user-defined JSON file using **regular expressions**.
- ``classification(source_file=None, from_classification='')`` returns a **list** created from a classification.
- ``info(source_file=None)`` prints metadata and sources from the built-in or user-defined JSON file.
## Parameters:
- `source_file` : *raw str* or *unicode*, optional.
Relative or absolute path to the user-defined JSON file.
- `from_list` : *sequence* of *iterable*.
Input data.
- `to_classification` : *str* or *unicode*.
'name_en' (English name), 'name_fr' (French name), 'iso3' (ISO 3166-1 alpha-3), 'iso2' (ISO 3166-1 alpha-2), or 'isoN' (ISO 3166-1 numeric).
- `from_classification` : *str* or *unicode*.
'name_en' (English name), 'name_fr' (French name), 'iso3' (ISO 3166-1 alpha-3), 'iso2' (ISO 3166-1 alpha-2), or 'isoN' (ISO 3166-1 numeric).
`source_file` (if defined) replaces the default classification (ISO 3166-1). The file must contain a list of dictionaries where `regex` is a compulsory key in each one. The default JSON file was prepared with the help of **[json](https://docs.python.org/3/library/json.html)** module:
```
[
{
"regex": "^(.*afgh.*|\\s*AFG\\s*|\\s*AF\\s*|\\s*4\\s*)$",
"name_en": "Afghanistan", # classification A
"name_fr": "Afghanistan (l')", # classification B
"iso3": "AFG", # ...
"iso2": "AF",
"isoN": "4"
},
...
{
"metadata": {
"name_en": "English short name",
"name_fr": "French short name",
"iso3": "alpha-3 code",
"iso2": "alpha-2 code",
"isoN": "numeric"
}
},
{
"sources": [
"[https://www.iso.org/iso-3166-country-codes.html](ISO 3166 COUNTRY CODES)",
"[https://en.wikipedia.org/wiki/List_of_alternative_country_names](ALTERNATIVE NAMES)"
]
}
]
```
## Returns:
- `l` : *list*.
Processed data.
## Examples:
```
import pandas as pd
from pyconvertu import convert
from pyconvertu import classification
from pyconvertu import info
# Create a pandas dataframe with ISO 3166-1 alpha-3 as `index'
data = [1, 2, 3, 4, 5, 6, 7]
iso3 = convert(
from_list=['Canada', 'France', 'Germany', 'Italy', 'Japan', 'United Kingdom', 'United States'],
to_classification='iso3'
)
pd.DataFrame(data, index=iso3)
# Create a pandas dataframe from available classifications
df = pd.DataFrame()
df['iso3'] = classification(from_classification='iso3')
for s in ['iso2', 'isoN', 'name_en', 'name_fr']:
df[s] = convert(
from_list=df['iso3'],
to_classification=s
)
print(df)
# Print information and metadata for the built-in JSON file and my_file.json
info()
info(source_file=r'my_file.json')
```