phcovid

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.

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.

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