| Name | EasyDataPy JSON |
| Version |
1.4
JSON |
| download |
| home_page | None |
| Summary | EasyDataPy through EasyData API key of State Bank of Pakistan helps to obtain information on and download a series of interest in Python for further analysis |
| upload_time | 2024-04-23 15:39:03 |
| maintainer | None |
| docs_url | None |
| author | Dr. Syed Ateeb Akhter Shah |
| requires_python | None |
| license | None |
| keywords |
easydata
easydatapy
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# 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
Raw data
{
"_id": null,
"home_page": null,
"name": "EasyDataPy",
"maintainer": null,
"docs_url": null,
"requires_python": null,
"maintainer_email": null,
"keywords": "EasyData, EasyDataPy",
"author": "Dr. Syed Ateeb Akhter Shah",
"author_email": "syed.ateeb@wmich.edu",
"download_url": "https://files.pythonhosted.org/packages/20/80/ed0d75e77b8796624be0c7808dcc8025a734e23ae211f7bcb3a79959b85a/easydatapy-1.4.tar.gz",
"platform": null,
"description": "# EasyDataPy\n\nEasyDataPy aKa EDpy for short, is a unofficial Python library/package to read in data from EasyData platform of the State Bank of Pakistan\n\n# Details about EasyData Database of the State Bank of Pakistan\n\nEasyData 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.\n\n# About the Library/Package\n\nThis 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:\n\n1. Unit-Root tests\n2. Seasonality tests\n3. Cointegration tests and Cointegrated vector autoregressive model\n4. Autoregressive and Vector Autoregressive models\n5. Forecasting using Machine Learning and Dynamic Factor models (Rolling and Fixed Window Forecast)\n6. In and Out-of-Sample Forecasts\n\nBut 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!\n\n# How to install and use\n\nInside the Python you just need to type \"pip install EasyDataPy\"\n\n# How to use the functions inside this library/package\n\n## Verifying EasyData API Key\n\nEasyData_key_setup(\"C10D3D29160CE5693F56AA9846ABB2C423D8B123\") <- type in/paste your EasyData API Key!\n\n## Finding if the EasyData API Key has been verified\n\nsession_has_key()\n\n## Getting the entered key for further use\n\nget_Easydata_key()\n\n## Downloads Weighted-average Overnight Repo Rate series as a Pandas dataframe \n\ndata_frame = download_series(\"TS_GP_IR_REPOMR_D.ORR\",Easydata_key, \"2015-05-25\" ,\"2023-12-20\", \"csv\")\n\n## Tranforming output of download_series function, that is object called data_frame into a usable time-series\n\nbuild_time_series(data_frame)\n\n## Plot Time-Series Graph for the downloaded time-series\n\nplot_time_series(data_frame)\n\n## To download a dataset containing multiple time-series\n\n# We present an example that downloads three time-series from Easydata database. It is assumed that a researcher is\n# expected to know the sample period and variables needed for the study. Just remove the #(hash) below:\n\n# series_ids = [\"TS_GP_BOP_BPM6SUM_M.P00010\", \"TS_GP_RL_LSM1516_M.LSM000160000\", \"TS_GP_PT_CPI_M.P00011516\"]\n# start_date = \"2016-07-31\"\n# end_date = \"2023-11-30\"\n\n# The data has to be saved in an object, we call that object combined_dataframe below:\n\n# combined_dataframe = download_dataset(series_ids, Easydata_key, start_date, end_date)\n\n# combined_dataframe\n",
"bugtrack_url": null,
"license": null,
"summary": "EasyDataPy through EasyData API key of State Bank of Pakistan helps to obtain information on and download a series of interest in Python for further analysis",
"version": "1.4",
"project_urls": null,
"split_keywords": [
"easydata",
" easydatapy"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "0586aa28787282901b59a4bfb1083c0efed75f87da191a06ddbaae0fe453f1db",
"md5": "effea594e32040b6905f9a2fe57945ba",
"sha256": "03a764db4d2bad9fa7e9475f43fd05bfb0ccd81e2d72fcdf42f2bb4af796d6a5"
},
"downloads": -1,
"filename": "EasyDataPy-1.4-py3-none-any.whl",
"has_sig": false,
"md5_digest": "effea594e32040b6905f9a2fe57945ba",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 5721,
"upload_time": "2024-04-23T15:39:02",
"upload_time_iso_8601": "2024-04-23T15:39:02.450977Z",
"url": "https://files.pythonhosted.org/packages/05/86/aa28787282901b59a4bfb1083c0efed75f87da191a06ddbaae0fe453f1db/EasyDataPy-1.4-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "2080ed0d75e77b8796624be0c7808dcc8025a734e23ae211f7bcb3a79959b85a",
"md5": "c35845a0631759452c5f228de5c58366",
"sha256": "1e68088c621cafd4ce04ad75e8431fcc0356b0a88df7e38acd10e1f081b80e42"
},
"downloads": -1,
"filename": "easydatapy-1.4.tar.gz",
"has_sig": false,
"md5_digest": "c35845a0631759452c5f228de5c58366",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 5178,
"upload_time": "2024-04-23T15:39:03",
"upload_time_iso_8601": "2024-04-23T15:39:03.792078Z",
"url": "https://files.pythonhosted.org/packages/20/80/ed0d75e77b8796624be0c7808dcc8025a734e23ae211f7bcb3a79959b85a/easydatapy-1.4.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-04-23 15:39:03",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "easydatapy"
}
