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covidmx-0.3.1
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مشاهده بیشترتوضیحات
Python API to get information about COVID-19 in México.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | covidmx-0.3.1 |
| نام | covidmx |
| نسخه کتابخانه | 0.3.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Federico Garza |
| ایمیل نویسنده | fede.garza.ramirez@gmail.com |
| آدرس صفحه اصلی | https://github.com/FedericoGarza/covidmx |
| آدرس اینترنتی | https://pypi.org/project/covidmx/ |
| مجوز | - |
[](https://github.com/FedericoGarza/covidmx/tree/master)
[](https://pypi.python.org/pypi/covidmx/)
[](https://doi.org/10.5281/zenodo.3758590)
[](https://pepy.tech/project/covidmx)
[](https://www.python.org/downloads/release/python-350+/)
[](https://github.com/FedericoGarza/covidmx/blob/master/LICENSE)
# covidmx
Python API to get information about COVID-19 in México.
# Requirements
```
more-itertools>=6.0.0
pandas>=0.25.2
Unidecode>=1.1.1
requests==2.21.0
xlrd==1.2.0
mapsmx==0.0.3
matplotlib==3.0.3
mapclassify==2.2.0
descartes==1.1.0
```
# How to install
```
pip install covidmx
```
# How to use
## Dirección General de Epidemiología
The mexican *Dirección General de Epidemiología* [has released open data](https://www.gob.mx/salud/documentos/datos-abiertos-152127) about COVID-19 in México. This source contains information at the individual level such as gender, municipality and health status (smoker, obesity, etc). The package `covidmx` now can handle this source as default. Some variables are encoded as integers and the source also includes a data dictionary with all relevant information. When you pass `clean=True` (default option) returns the decoded data. You can also have access to the catalogue using `return_catalogo=True` and to the description of each one of the variables with `return_descripcion=True`. When you use some of this parameters, the API returns a tuple.
```python
from covidmx import CovidMX
covid_dge_data = CovidMX().get_data()
raw_dge_data = CovidMX(clean=False).get_data()
covid_dge_data, catalogo_data = CovidMX(return_catalogo=True).get_data()
covid_dge_data, descripcion_data = CovidMX(return_descripcion=True).get_data()
covid_dge_data, catalogo_data, descripcion_data = CovidMX(return_catalogo=True, return_descripcion=True).get_data()
```
To get historical data use:
```python
covid_dge_data = CovidMX(date='12-04-2020').get_data()
```
Default date format is `%d-%m-%Y`, but you can also use a particular format with:
```python
covid_dge_data = CovidMX(date='2020-04-12', date_format='%Y-%m-%d').get_data()
```
### Plot module
As of version 0.3.0, `covidmx` includes a module to create maps of different COVID-19 status at the national and state levels, with the possibility of including municipalities (using information of the *Dirección General de Epidemiologia*).
```python
from covidmx import CovidMX
dge_plot = CovidMX().get_plot()
```
You can check available status and available states using:
```python
dge_plot.available_states
array(['MÉXICO', 'CIUDAD DE MÉXICO', 'TAMAULIPAS', 'BAJA CALIFORNIA',
'YUCATÁN', 'GUERRERO', 'BAJA CALIFORNIA SUR', 'JALISCO',
'NUEVO LEÓN', 'SONORA', 'VERACRUZ DE IGNACIO DE LA LLAVE',
'PUEBLA', 'CAMPECHE', 'GUANAJUATO', 'SAN LUIS POTOSÍ',
'MICHOACÁN DE OCAMPO', 'COAHUILA DE ZARAGOZA', 'QUERÉTARO',
'AGUASCALIENTES', 'TABASCO', 'HIDALGO', 'ZACATECAS', 'DURANGO',
'CHIHUAHUA', 'CHIAPAS', 'SINALOA', 'QUINTANA ROO', 'MORELOS',
'TLAXCALA', 'NAYARIT', 'OAXACA', 'COLIMA'], dtype=object)
```
```python
dge_plot.available_status
['confirmados', 'negativos', 'sospechosos', 'muertos']
```
To plot a national map just use:
```python
dge_plot.plot_map(status='confirmados')
```
<img src=https://raw.githubusercontent.com/FedericoGarza/covidmx/dev/.github/images/confirmados-nacional.png width=400>
If you want to include municipalities use:
```python
dge_plot.plot_map(status='confirmados', add_municipalities=True)
```
<img src=https://raw.githubusercontent.com/FedericoGarza/covidmx/dev/.github/images/confirmados-nacional-muns.png width=400>
You can pass a particular state filling the `state` argument with a valid name included in the `available_states` attribute:
```python
dge_plot.plot_map(status='confirmados', state='CIUDAD DE MÉXICO', add_municipalities=True)
```
|`state='CIUDAD DE MÉXICO'`| `state='JALISCO'`| `state='MORELOS'`| `state='MÉXICO'`|
|:------------------------:|:----------------:|:----------------:|:---------------:|
|<img src=https://raw.githubusercontent.com/FedericoGarza/covidmx/dev/.github/images/confirmados-CIUDAD%20DE%20M%C3%89XICO-muns.png width="220">| <img src=https://raw.githubusercontent.com/FedericoGarza/covidmx/dev/.github/images/confirmados-JALISCO-muns.png width="220"> | <img src=https://raw.githubusercontent.com/FedericoGarza/covidmx/dev/.github/images/confirmados-MORELOS-muns.png width="220">| <img src=https://raw.githubusercontent.com/FedericoGarza/covidmx/dev/.github/images/confirmados-MÉXICO-muns.png width="220">|
Finally you can plot another interest variable (according to `available_status` attribute):
```python
dge_plot.plot_map(status='sospechosos', add_municipalities=True)
```
<img src=https://raw.githubusercontent.com/FedericoGarza/covidmx/dev/.github/images/sospechosos-nacional.png width=400>
You can save your maps using `save_file_name`:
```python
dge_plot.plot_map(status='sospechosos', add_municipalities=True, save_file_name='sospechosos-nacional.png')
```
## Serendipia
Serendipia [publishes daily information](https://serendipia.digital/2020/03/datos-abiertos-sobre-casos-de-coronavirus-covid-19-en-mexico/) of the mexican *Secretaría de Salud* about covid in open format (.csv). This api downloads this data easily, making it useful for task automation.
```python
from covidmx import CovidMX
latest_published_data = CovidMX(source='Serendipia').get_data()
```
Then `CovidMX` instances a `Serendipia` class, searches the latest published data for both confirmed and suspects individuals and finally clean the data. Nevertheless, a more specific search can be conducted (see docs for details).
```python
raw_data = CovidMX(source='Serendipia', clean=False).get_data()
confirmed = CovidMX(source='Serendipia', kind="confirmed").get_data()
suspects = CovidMX(source='Serendipia',kind="suspects").get_data()
particular_published_date = CovidMX(source='Serendipia', date='2020-04-10', date_format='%Y-%m-%d').get_data()
```
# Cite as
- Federico Garza Ramírez (2020). *covidmx: Python API to get information about COVID-19 in México*. Python package version 0.3.1. https://github.com/FedericoGarza/covidmx.
# Acknowledgments
- [Max Mergenthaler](https://github.com/mergenthaler)
- [Mario Jimenez](https://github.com/isccarrasco)
# Release information
## 0.3.1 (Current version)
- 2020-06-01
- Updated new urls from serendipia source. (Thanks to [Mario Jimenez](https://github.com/isccarrasco).)
## 0.3.0
- 2020-04-26.
- Includes a plot module at state and municipality leveles.
- Includes a better handling of encodings. (Thanks to [Mario Jimenez](https://github.com/isccarrasco).)
## 0.2.5
- 2020-04-20. The [*Dirección General de Epidemiología*](https://www.gob.mx/salud/documentos/datos-abiertos-152127):
- Added an id column.
- Released historical information.
- Now the API can handle this changes.
## 0.2.4
- 2020-04-16. The [*Dirección General de Epidemiología*](https://www.gob.mx/salud/documentos/datos-abiertos-152127) source renamed two columns:
- `HABLA_LENGUA_INDI` -> `HABLA_LENGUA_INDIG` (column name and description are now homologated)
- `OTRA_CON` -> `OTRA_COM`
- Now the API can handle this change.
## 0.2.3
- Now works with `python3.5+`.
- Using `clean=True` returns encoded data instead of decoded data without cleaning columns (as works in `0.2.0` and `0.2.1`).
## 0.2.1
- Minor changes to README.
## 0.2.0
- Added new source: [*Dirección General de Epidemiología*](https://www.gob.mx/salud/documentos/datos-abiertos-152127). Default source.
- Only works with `python3.7+`.
## 0.1.1
- Minor changes to README.
## 0.1.0
First realease.
- Only one source, [Serendipia](https://serendipia.digital/2020/03/datos-abiertos-sobre-casos-de-coronavirus-covid-19-en-mexico/). Default source.
نیازمندی
| مقدار | نام |
|---|---|
| >=6.0.0 | more-itertools |
| >=0.25.2 | pandas |
| >=1.1.1 | Unidecode |
| >=2.21.0 | requests |
| >=1.2.0 | xlrd |
| >=0.0.3 | mapsmx |
| >=3.0.3 | matplotlib |
| >=2.2.0 | mapclassify |
| >=1.1.0 | descartes |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.5 | Python |
نحوه نصب
نصب پکیج whl covidmx-0.3.1:
pip install covidmx-0.3.1.whl
نصب پکیج tar.gz covidmx-0.3.1:
pip install covidmx-0.3.1.tar.gz