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cso-ireland-data-0.0.3
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مشاهده بیشتر
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مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
Download CSO Ireland datasets and data catalogue as Pandas dataframes.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | cso-ireland-data-0.0.3 |
| نام | cso-ireland-data |
| نسخه کتابخانه | 0.0.3 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | - |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | - |
| آدرس اینترنتی | https://pypi.org/project/cso-ireland-data/ |
| مجوز | BSD 3-Clause License |
# CSO Ireland Data
==============================
Easily download data from the CSO PxStat API as Pandas datasets.
Uses [requests-cache](https://github.com/requests-cache/requests-cache) for super fast access to cached requests and easy persistence with multiple storage backends.
## Installation
To install, just use pip:
```bash
pip install cso-ireland-data
```
## Usage
### Getting started
First, set up a `CSODataSession`.
* By default, this is really simple.
```python
from cso_ireland_data import CSODataSession
cso = CSODataSession()
```
* If you want to add caching, no problem! All the functionality of [the `requests-cache` package](https://github.com/requests-cache/requests-cache) is available through `cached_session_params`.
```python
from datetime import timedelta
from cso_ireland_data import CSODataSession
cso = CSODataSession(
cached_session_params={
"use_cache_dir": True, # Save files in the default user cache dir
"cache_control": True, # Use Cache-Control response headers for expiration, if available
"expire_after": timedelta(days=1), # Otherwise expire responses after one day
}
)
```
* Stuck behind a corporate firewall that causes SSL certificate issues? Also no problem! All the functionality of [the `requests` `get()` method](https://requests.readthedocs.io/en/latest/user/quickstart/) is available through `request_params`.
```python
from cso_ireland+data import CSODataSession
# Tell requests.get() it's ok not to verify SSL certificates when getting data.
# !!! Only do this if you're absolutely sure it's what you need !!!
cso = CSODataSession(request_params={"verify": False})
```
### Getting the data catalogue
To get a catalogue (Table of Contents) of all the datasets that are available through the API, use `get_toc()`.
NB Requests for the ToC sometimes time out on the CSO API. IF this happens, try again!
```python
cso.get_toc()
```
| table_id | table_name | last_updated | copyright | exceptional | frequency | earliest | latest | variables |
|:-----------|:-----------------------------------------------------|:--------------------------|:-----------------------------------|:--------------|:------------|-----------:|---------:|:-------------------------------------------------------------------|
| A0101 | 1996 Population and Percentage Change 1991 and 1996 | 2020-05-01 11:00:00+00:00 | Central Statistics Office, Ireland | False | CensusYear | 1996 | 1996 | ['Province County or City'] |
| A0102 | Population at Each Census Since 1841 | 2020-05-01 11:00:00+00:00 | Central Statistics Office, Ireland | False | CensusYear | 1841 | 1996 | ['Province or County', 'Sex'] |
| A0103 | Population | 2020-05-01 11:00:00+00:00 | Central Statistics Office, Ireland | False | CensusYear | 1996 | 1996 | ['Province County or City', 'Sex', 'Aggregate Town or Rural Area'] |
| A0104 | Population | 2020-06-03 11:00:00+00:00 | Central Statistics Office, Ireland | False | CensusYear | 1996 | 1996 | ['Sex', 'Regional Authority'] |
| A0105 | 1996 Population and Percentage Change 1996 and 2002 | 2021-07-19 11:00:00+00:00 | Central Statistics Office, Ireland | False | CensusYear | 1996 | 1996 | ['Towns by Electoral Division'] |
### Getting a table using its ID code
To get the whole contents of a particular table hosted on the Statbank API, use `get_table()`.
You just need to know the ID code of the table, which you can look up using `get_toc()`.
```python
wpm29 = cso.get_table("WPM29")
wpm29.head()
```
| | Wholesale Price Index (Excl VAT) for Energy Products |
|:--------------------------|-------------------------------------------------------:|
| ('Autodiesel', '2015M01') | 96.7 |
| ('Autodiesel', '2015M02') | 102 |
| ('Autodiesel', '2015M03') | 103 |
| ('Autodiesel', '2015M04') | 102.9 |
| ('Autodiesel', '2015M05') | 104.6 |
### Getting some common tables quickly
The `CSODataSession` class includes some useful methods to get data from commonly accessed tables quickly.
#### Monthly Consumer Price Index (CPI)
By default, the `monthly_cpi()` method returns a single column corresponding to the 'All items' headline CPI in the source table.
Also by default, this index is re-normalized to the most recent month - you can toggle this by setting `normalize_to_most_recent` to `False`.
```python
simple_cpi = cso.monthly_cpi()
simple_cpi.tail()
```
| Month | All items |
|:--------------------|------------:|
| 2022-04-01 00:00:00 | 0.9725 |
| 2022-05-01 00:00:00 | 0.981 |
| 2022-06-01 00:00:00 | 0.9937 |
| 2022-07-01 00:00:00 | 0.9986 |
| 2022-08-01 00:00:00 | 1 |
It's also possible to pass a list of commodity groups:
```python
commmodity_group_cpi = cso.monthly_cpi(
commodity_groups=[
"All items",
"Alcoholic beverages and tobacco",
"Health",
"Recreation and culture",
]
)
commodity_group_cpi.tail()
```
| Month | All items | Alcoholic beverages and tobacco | Health | Recreation and culture |
|:--------------------|------------:|----------------------------------:|---------:|-------------------------:|
| 2022-04-01 00:00:00 | 0.9725 | 0.9738 | 0.9828 | 0.9945 |
| 2022-05-01 00:00:00 | 0.981 | 0.9937 | 0.9851 | 0.9954 |
| 2022-06-01 00:00:00 | 0.9937 | 0.9958 | 0.9874 | 0.9973 |
| 2022-07-01 00:00:00 | 0.9986 | 0.9969 | 0.9874 | 0.9991 |
| 2022-08-01 00:00:00 | 1 | 1 | 1 | 1 |1 | 1 |
#### Live Register
Use the `live_register()` method to get Live Register numbers (optionally broken down by Age Group and Sex) by month. This is a long data series, starting in April 1967 and still continuing every month, so it may be convenient to specify a `start` and/or `end` date for the data returned.
The Live Register data series is based on a monthly point-in-time count of people who have active Jobseeker claims with the Department of Social Protection (DSP), and these counts are extracted from DSP's administrative computer systems on a particular day every month.
Because of this, `live_register()` returns three possibly useful dates for each month:
1. 'Month' is the index of the data frame. It's just the last day of each calendar month.
2. 'reference_date' is the date of the point-in-time count of people with active Jobseeker claims. It's the last Friday of each month before May 2015, and the last Thursday of the month from then on.
3. 'extract_date' is the date on which the source administrative data was actually extracted - it's always the Sunday after the reporting_date.
```python
live_register = cso.live_register(start=datetime(2010, 1, 1))
```
| | Month | Age Group | Sex | Persons on the Live Register | Persons on the Live Register (Seasonally Adjusted) | reference_date | extract_date |
|----:|:--------------------|:------------|:-----------|-------------------------------:|-----------------------------------------------------:|:--------------------|:--------------------|
| 516 | 2010-04-30 00:00:00 | All ages | Both sexes | 432657 | 440800 | 2010-04-30 00:00:00 | 2010-05-02 00:00:00 |
| 517 | 2010-08-31 00:00:00 | All ages | Both sexes | 466923 | 444000 | 2010-08-27 00:00:00 | 2010-08-29 00:00:00 |
| 518 | 2010-12-31 00:00:00 | All ages | Both sexes | 437079 | 446000 | 2010-12-31 00:00:00 | 2011-01-02 00:00:00 |
| 519 | 2010-02-28 00:00:00 | All ages | Both sexes | 436956 | 439000 | 2010-02-26 00:00:00 | 2010-02-28 00:00:00 |
| 520 | 2010-01-31 00:00:00 | All ages | Both sexes | 436936 | 439400 | 2010-01-29 00:00:00 | 2010-01-31 00:00:00 |
#### Life Tables
The `life_table()` method by default returns a complete life table for the most recent source data vintage.
```python
life_table = cso.life_table()
life_table.head()
```
| | Ix | dx | px | qx | Lx | Tx | e0x |
|:--------------|-----:|-----:|---------:|---------:|-----:|-----:|------:|
| ('Male', 101) | 851 | 616 | 0.724494 | 0.275506 | 543 | 1544 | 1.82 |
| ('Male', 102) | 616 | 440 | 0.714258 | 0.285742 | 396 | 1002 | 1.63 |
| ('Male', 103) | 440 | 307 | 0.69799 | 0.30201 | 287 | 605 | 1.38 |
| ('Male', 104) | 307 | 221 | 0.71911 | 0.28089 | 197 | 319 | 1.04 |
| ('Male', 105) | 221 | 198 | 0.896101 | 0.103899 | 122 | 122 | 0.55 |
نیازمندی
| مقدار | نام |
|---|---|
| - | requests-cache |
| - | numpy |
| - | pandas |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl cso-ireland-data-0.0.3:
pip install cso-ireland-data-0.0.3.whl
نصب پکیج tar.gz cso-ireland-data-0.0.3:
pip install cso-ireland-data-0.0.3.tar.gz