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An example of using the ABS API to look at unemployment data
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"id": "c3e0b430-1d3f-4fcd-9d26-243adca0d9e1", | |
"metadata": {}, | |
"source": [ | |
"# Fetching Unemployment data from the ABS\n", | |
"\n", | |
"Here's an example of fetching data from the ABS using their API and [requests](https://pypi.org/project/requests/), and turning it into observations. You can [learn more about the API here](https://akst.substack.com/p/so-you-want-to-use-the-abs-stats) (full disclosure I wrote this)." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"id": "3afcd6ab-fd61-41a3-a935-0dc5b88aab73", | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import requests\n", | |
"\n", | |
"def parse_observations(resp) -> list[tuple[int, dict[str, str]]]:\n", | |
" data, meta = resp['data']['dataSets'], resp['data']['structures']\n", | |
" dims: List[List[Tuple[str, List[str]]]] = [[ \n", | |
" (dimension['id'], [v['name'] for v in dimension['values']])\n", | |
" for dimension in structure['dimensions']['observation']\n", | |
" ] for structure in meta]\n", | |
" return [\n", | |
" (count, {\n", | |
" d_id: d_values[v_idx]\n", | |
" for d_idx, v_idx in enumerate(map(int, o_dims.split(':')))\n", | |
" for d_id, d_values in [dims[dataset['structure']][d_idx]]\n", | |
" })\n", | |
" for dataset in data\n", | |
" for o_dims, observations in dataset['observations'].items()\n", | |
" for count in observations\n", | |
" ]\n", | |
"\n", | |
"response = requests.get(\n", | |
" 'https://data.api.abs.gov.au/rest/data/ABS,LF_AGES,1.0.0/M6+M3.2+3.1564.20.AUS.M',\n", | |
" headers={ \"Accept\": \"application/vnd.sdmx.data+json\" },\n", | |
" params={ \"startPeriod\": \"2009-12\", \"dimensionAtObservation\": \"AllDimensions\" },\n", | |
")\n", | |
"\n", | |
"observations = parse_observations(response.json())" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "9982372e-79dd-471c-a32c-ca38340518f3", | |
"metadata": {}, | |
"source": [ | |
"## Create a dataframe\n", | |
"\n", | |
"With [Pandas](https://pandas.pydata.org):\n", | |
"\n", | |
"1. Create a dataframe\n", | |
"2. Process the date column\n", | |
"3. Perform a pivot table\n", | |
"4. Update the columns\n", | |
"5. Calculate an unemployment rate" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"id": "1d5cb151-05e1-47e7-9508-ed3e8a3b2893", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div>\n", | |
"<style scoped>\n", | |
" .dataframe tbody tr th:only-of-type {\n", | |
" vertical-align: middle;\n", | |
" }\n", | |
"\n", | |
" .dataframe tbody tr th {\n", | |
" vertical-align: top;\n", | |
" }\n", | |
"\n", | |
" .dataframe thead th {\n", | |
" text-align: right;\n", | |
" }\n", | |
"</style>\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th>MEASURE</th>\n", | |
" <th>Period</th>\n", | |
" <th>Sex</th>\n", | |
" <th>Employed</th>\n", | |
" <th>Unemployed</th>\n", | |
" <th>Unemployment Rate</th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>0</th>\n", | |
" <td>2009-12-01</td>\n", | |
" <td>Females</td>\n", | |
" <td>4850.821658</td>\n", | |
" <td>281.306222</td>\n", | |
" <td>5.799146</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>1</th>\n", | |
" <td>2009-12-01</td>\n", | |
" <td>Persons</td>\n", | |
" <td>10580.052546</td>\n", | |
" <td>632.681051</td>\n", | |
" <td>5.979942</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2</th>\n", | |
" <td>2010-01-01</td>\n", | |
" <td>Females</td>\n", | |
" <td>4864.335878</td>\n", | |
" <td>278.067287</td>\n", | |
" <td>5.716449</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3</th>\n", | |
" <td>2010-01-01</td>\n", | |
" <td>Persons</td>\n", | |
" <td>10631.352791</td>\n", | |
" <td>609.106376</td>\n", | |
" <td>5.729340</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>4</th>\n", | |
" <td>2010-02-01</td>\n", | |
" <td>Females</td>\n", | |
" <td>4851.432409</td>\n", | |
" <td>275.078970</td>\n", | |
" <td>5.670057</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>...</th>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>359</th>\n", | |
" <td>2024-11-01</td>\n", | |
" <td>Persons</td>\n", | |
" <td>13770.005808</td>\n", | |
" <td>575.597990</td>\n", | |
" <td>4.180085</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>360</th>\n", | |
" <td>2024-12-01</td>\n", | |
" <td>Females</td>\n", | |
" <td>6647.284270</td>\n", | |
" <td>269.478596</td>\n", | |
" <td>4.053965</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>361</th>\n", | |
" <td>2024-12-01</td>\n", | |
" <td>Persons</td>\n", | |
" <td>13838.792005</td>\n", | |
" <td>591.242095</td>\n", | |
" <td>4.272353</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>362</th>\n", | |
" <td>2025-01-01</td>\n", | |
" <td>Females</td>\n", | |
" <td>6688.446334</td>\n", | |
" <td>291.413976</td>\n", | |
" <td>4.356976</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>363</th>\n", | |
" <td>2025-01-01</td>\n", | |
" <td>Persons</td>\n", | |
" <td>13899.201315</td>\n", | |
" <td>600.479388</td>\n", | |
" <td>4.320244</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"<p>364 rows × 5 columns</p>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
"MEASURE Period Sex Employed Unemployed Unemployment Rate\n", | |
"0 2009-12-01 Females 4850.821658 281.306222 5.799146\n", | |
"1 2009-12-01 Persons 10580.052546 632.681051 5.979942\n", | |
"2 2010-01-01 Females 4864.335878 278.067287 5.716449\n", | |
"3 2010-01-01 Persons 10631.352791 609.106376 5.729340\n", | |
"4 2010-02-01 Females 4851.432409 275.078970 5.670057\n", | |
".. ... ... ... ... ...\n", | |
"359 2024-11-01 Persons 13770.005808 575.597990 4.180085\n", | |
"360 2024-12-01 Females 6647.284270 269.478596 4.053965\n", | |
"361 2024-12-01 Persons 13838.792005 591.242095 4.272353\n", | |
"362 2025-01-01 Females 6688.446334 291.413976 4.356976\n", | |
"363 2025-01-01 Persons 13899.201315 600.479388 4.320244\n", | |
"\n", | |
"[364 rows x 5 columns]" | |
] | |
}, | |
"execution_count": 2, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"import pandas as pd\n", | |
"\n", | |
"\n", | |
"df = pd.DataFrame.from_records([{\"AMOUNT\": v, **o } for v, o in observations])\n", | |
"df['TIME_PERIOD'] = pd.to_datetime(df['TIME_PERIOD'], format='%Y-%m')\n", | |
"df = df.drop(columns=['FREQ', 'REGION', 'TSEST', 'AGE'])\n", | |
"df = df.pivot_table(index=['TIME_PERIOD', 'SEX'], columns='MEASURE', values='AMOUNT', aggfunc='sum').reset_index()\n", | |
"df = df.rename(columns={ \n", | |
" 'Employed persons': 'Employed',\n", | |
" 'Unemployed persons': 'Unemployed',\n", | |
" 'SEX': 'Sex',\n", | |
" 'TIME_PERIOD': 'Period',\n", | |
"})\n", | |
"df['Unemployment Rate'] = (df['Unemployed'] / df['Employed']) * 100.0\n", | |
"df\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "4ed74a11-25bb-4586-83e0-8614aeb74da9", | |
"metadata": {}, | |
"source": [ | |
"## Lets make a Graph\n", | |
"\n", | |
"Lets now create a graph using [matplotlib](https://matplotlib.org). " | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"id": "95e30a1f-885f-4353-b40c-e5278fcaf3f8", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
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", | |
"text/plain": [ | |
"<Figure size 1000x700 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"import matplotlib.pyplot as plt\n", | |
"import matplotlib.dates as mdates\n", | |
"\n", | |
"plt.rcParams['font.family'] = 'serif'\n", | |
"\n", | |
"fig, ax = plt.subplots(1, 1, figsize=(10, 7))\n", | |
"\n", | |
"df_f = df[df['Sex'] == 'Females']\n", | |
"df_a = df[df['Sex'] == 'Persons']\n", | |
"ax.plot(df_f['Period'], df_f['Unemployment Rate'], label='Female', color='red')\n", | |
"ax.plot(df_a['Period'], df_a['Unemployment Rate'], label='All', color='black')\n", | |
"\n", | |
"ax.set_title(\"\\nUnemployement Rate\\n\", fontsize=20)\n", | |
"ax.set_xlabel(\"\\nTime Period\\n\")\n", | |
"ax.set_ylabel(\"\\nUnemployment (%)\\n\")\n", | |
"ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))\n", | |
"ax.xaxis.set_major_locator(mdates.YearLocator())\n", | |
"ax.tick_params(axis='x', rotation=45, labelsize=9, labelfontfamily='monospace')\n", | |
"plt.legend(prop={ 'family': 'monospace' })\n", | |
"plt.show()" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3 (ipykernel)", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.12.5" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 5 | |
} |
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