Skip to main content

Get PH COVID data in only two lines of code!

Project description

phcovid

Build Status License: MIT Code style: black

A Python library that allows extraction of pre-processed data for COVID-19 in the Philippines. The goal of the library is to make data accessible so that we do more with analyses and less on cleaning.

Get PH COVID data in only two lines of code!

Using phcovid is as simple as importing it and calling get_cases!

from phcovid import get_cases
df = get_cases()
print(get_cases().iloc[:5, :5])

#  case_no  age     sex nationality    residence
#0     PH1   38  Female     Chinese         None
#1     PH2   44    Male     Chinese         None
#2     PH3   60  Female     Chinese         None
#3     PH4   48    Male    Filipino  Taguig City
#4     PH5   62    Male    Filipino        Rizal

Using the library

The package is installable through Python pip with the assumption that you're using Python 3.

pip install phcovid

Cases

The get_cases function will take data stated from the sources that this library is integrated with.

from phcovid import get_cases
df = get_cases()

The base of the data will come from the DOH dataset. But with the increasing number of cases, some columns from the base dataset is incomplete. To remedy this, columns are completed from a crowdsourced dataset from the Data Science Philippines curated COVID-19 dataset or DSPH GSheet Dataset. Below is the breakdown of the columns and where they're coming from.

Column Source
case_no DOH
travel_history DOH
latitude DOH
longitude DOH
epi_link DOH
date DOH
case_no_num DOH
contacts DOH
num_contacts DOH
contacts_num DOH
age DSPH GSheet
sex DSPH GSheet
nationality DSPH GSheet
residence DSPH GSheet
symptoms DSPH GSheet
confirmation_date DSPH GSheet
facility DSPH GSheet
status DSPH GSheet
announcement_date DSPH GSheet
final_status_date DSPH GSheet

Case Network

With the cases available, a get_case_network function is created to see how the pandemic is spreading amongst the cases.

from phcovid import get_cases, get_case_network
df = get_cases()

# takes in the cases dataframe as input
case_network = get_case_network(df)
print(case_network)

# 	network_no	network_cases	network_num_cases
#0	0	        [1025]	        1
#1	1	        [1030]	        1
#2	2	        [1034]	        1
#3	3	        [1041]	        1
#4	4	        [1042]	        1

Case Plot

from phcovid import get_cases, get_case_plot
df = get_cases()

# takes in the cases dataframe
get_case_plot(df)

By default, the plot will be created from the announcement_date column. This can be changed through date_col parameter.

get_case_plot(df, date_col="new_col_to_plot")

Lastly, a start_date can also be set (it used all data by default). This date will be in the format MM-DD-YY.

get_case_plot(df, start_date="03-02-20")

An example similar to image below should be the result.

Case Plot from March 2 to March 23

Contributing

Getting Started

All tests are done on Python 3 and may not work as expected on Python 2. As such, it is highly recommended that you have Python 3 installed.

Make sure to install all libraries for development in your local.

pip install -r requirements.dev.txt

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

phcovid-0.0.2.10-py3-none-any.whl (10.3 kB view details)

Uploaded Python 3

File details

Details for the file phcovid-0.0.2.10-py3-none-any.whl.

File metadata

  • Download URL: phcovid-0.0.2.10-py3-none-any.whl
  • Upload date:
  • Size: 10.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.7.1

File hashes

Hashes for phcovid-0.0.2.10-py3-none-any.whl
Algorithm Hash digest
SHA256 ebe16ab179b7e2bec834203cc6d5eb005c9e9fa95bd281a0bfcd31bbccf7fde0
MD5 e309d28806db0f5ff77f5b0dbb894a1d
BLAKE2b-256 7d9585fb3c96d4031fb42e5f6700c87562126878ebc6337827b3da24697f9dbe

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page