{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Summary of all harvested series\n", "\n", "This notebook displays summary information from 23 series in the National Archives of Australia relating to the administration of the White Australia Policy.\n", "\n", "Item level metadata for all of these series has been harvested from RecordSearch, the National Archive's online database, and saved as CSV-formatted files.\n", "\n", "Just click on one of the series numbers in the table below for more detailed information, some simple visualisations, and a link to the CSV file." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "from IPython.core.display import display, HTML\n", "import series_details" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "series_list = ['B13', 'B6003', 'BP343/15', 'D2860', 'D5036', 'D596', 'E752', 'J2481', 'J2482', 'J2483', 'J3115', 'K1145', 'P437', 'P526', 'PP4/2', 'PP6/1', 'SP11/26', 'SP11/6', 'SP115/1', 'SP115/10', 'SP42/1', 'SP726/1', 'ST84/1']" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "df = series_details.make_df_all(series_list)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "" ], "text/vnd.plotly.v1+html": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "

Aggregated totals

" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
Total items88,580
Access status
Open74,732 (84.37%)
OWE83 (0.09%)
NYE13,759 (15.53%)
Closed6 (0.01%)
Number of items digitised21,762 (24.57%)
Number of pages digitised173,120
Date of earliest content1800
Date of latest content2005
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "series_details.display_summary_all(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Summary by series" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
seriestotal_itemsdate_fromdate_toOpenOWENYECloseddigitised_filesdigitised_pages% open% digitised
0B1320,1941800200519,786840003545,04397.98%1.75%
1B6003319041959300000100.00%0.00%
2BP343/152,571191619552,5660508517699.81%3.31%
3D28601190219570100000.00%0.00%
4D5036119061935100000100.00%0.00%
5D59611,395187119712,983318,38101853,03126.18%1.62%
6E752722190519417190307179,31099.58%99.31%
7J2481858189719038580008582,031100.00%100.00%
8J2482799190219127990007983,153100.00%99.87%
9J248314,4381903195614,43602014,43679,21099.99%99.99%
10J3115161189919281610001611,344100.00%100.00%
11K11454,816190019554,791025017587499.48%3.63%
12P4374,958190119404,94510211844299.74%0.36%
13P52621909191810100050.00%0.00%
14PP4/261319031947610030281,51299.51%4.57%
15PP6/16,010190619781,863334,10952456,46131.00%4.08%
16SP11/26271902190227000584100.00%18.52%
17SP11/6191190219471010900132352.88%0.52%
18SP115/11,787188419431,7870009285100.00%0.50%
19SP115/10618841888600000100.00%0.00%
20SP42/116,2561881196015,525073103,25345,86295.50%20.01%
21SP726/1619021959600000100.00%0.00%
22ST84/12,765185519752,75807043413,97999.75%15.70%
" ], "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "series_details.display_series_all(df)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 2 }