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EasyDataPy

EasyDataPy aKa EDpy for short, is a unofficial Python library/package to read in data from EasyData platform of the State Bank of Pakistan

Details about EasyData Database of the State Bank of Pakistan

EasyData platform of the State Bank of Pakistan is the largest repository of Macroeconomic time-series. It has more than 2 million observations covering more than 13,000 time-series related to economy of Pakistan.

About the Library/Package

This package is intended to identify a session with EasyData API key, obtain information about a particular series of interest, and download a series of interest to Python for further analysis. Although, I could have performed basic time-series in Python such as:

  1. Unit-Root tests
  2. Seasonality tests
  3. Cointegration tests and Cointegrated vector autoregressive model
  4. Autoregressive and Vector Autoregressive models
  5. Forecasting using Machine Learning and Dynamic Factor models (Rolling and Fixed Window Forecast)
  6. In and Out-of-Sample Forecasts

But this package is not intended to conduct these analysis but I am programming another one, which will be able to perform all of these operations. Stay Tuned!

How to install and use

Inside the Python you just need to type "pip install EasyDataPy"

How to use the functions inside this library/package

Verifying EasyData API Key

EasyData_key_setup("C10D3D29160CE5693F56AA9846ABB2C423D8B123") <- type in/paste your EasyData API Key!

Finding if the EasyData API Key has been verified

session_has_key()

Getting the entered key for further use

get_Easydata_key()

Downloads Weighted-average Overnight Repo Rate series as a Pandas dataframe

data_frame = download_series("TS_GP_IR_REPOMR_D.ORR",Easydata_key, "2015-05-25" ,"2023-12-20", "csv")

Tranforming output of download_series function, that is object called data_frame into a usable time-series

build_time_series(data_frame)

Plot Time-Series Graph for the downloaded time-series

plot_time_series(data_frame)

To download a dataset containing multiple time-series

We present an example that downloads three time-series from Easydata database. It is assumed that a researcher is

expected to know the sample period and variables needed for the study. Just remove the #(hash) below:

series_ids = ["TS_GP_BOP_BPM6SUM_M.P00010", "TS_GP_RL_LSM1516_M.LSM000160000", "TS_GP_PT_CPI_M.P00011516"]

start_date = "2016-07-31"

end_date = "2023-11-30"

The data has to be saved in an object, we call that object combined_dataframe below:

combined_dataframe = download_dataset(series_ids, Easydata_key, start_date, end_date)

combined_dataframe

Metadata

Release files for EasyDataPy 1.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for EasyDataPy 1.4
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Built distribution (wheel)

Table of built distributions (wheels) for EasyDataPy 1.4
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EasyDataPy-1.4-py3-none-any.whl Python 3 none any Details

Total release size: 10.9 kB

Release files / easydatapy-1.4.tar.gz

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