{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "series = 'A9626'" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/vnd.plotly.v1+html": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/vnd.plotly.v1+html": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import os\n", "import pandas as pd\n", "import series_details\n", "import plotly.offline as py\n", "py.init_notebook_mode()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(os.path.join('data', '{}.csv'.format(series.replace('/', '-'))), parse_dates=['start_date', 'end_date'])" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "

National Archives of Australia: Series A9626

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Photographic material (including photocopies of photographs) created by ASIO

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Total items1,075
Access status
Open792 (73.67%)
Open with exception277 (25.77%)
Not yet examined6 (0.56%)
Number of items digitised570 (53.02%)
Number of pages digitised9,370
Date of earliest content1919
Date of latest content1998
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "series_details.display_summary(series, df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Content preview" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": false }, "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", "
identifierseriescontrol_symboltitlecontents_datesstart_dateend_dateaccess_statuslocationdigitised_statusdigitised_pages
01188387A96261ASIO surveillance photograph of James Frederick Hill [former Department of External Affairs diplomat]circa1950 - circa1950NaTNaTOpenCanberraFalse0
11188390A96262ASIO surveillance photograph of James Frederick Hill [former Department of External Affairs diplomat]circa1950 - circa1950NaTNaTOpenCanberraFalse0
21188393A96263ASIO surveillance photograph of James Frederick Hill [former Department of External Affairs diplomat]circa1950 - circa1950NaTNaTOpenCanberraTrue1
31188395A96264ASIO surveillance photograph of James Frederick Hill [former Department of External Affairs diplomat]circa1950 - circa1950NaTNaTOpenCanberraFalse0
41188399A96265ASIO photograph of John Wear Burton [former Secretary of Department of External Affairs]circa1950 - circa1950NaTNaTOpenCanberraFalse0
" ], "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Change the number_of_rows value to see more\n", "number_of_rows = 5\n", "\n", "# Display dataframe \n", "df[:number_of_rows].style.set_properties(['title'], **{'text-align': 'left'}).set_table_styles([dict(selector=\"th\", props=[(\"text-align\", \"center\")]),\n", " dict(selector='.row_heading, .blank', props=[('display', 'none')])])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot content dates" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "data": [ { "name": "Digitised", "type": "bar", "x": [ 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998 ], "y": [ 48, 48, 48, 50, 49, 49, 49, 50, 49, 49, 49, 49, 49, 52, 60, 55, 64, 69, 75, 82, 101, 103, 109, 111, 112, 168, 172, 180, 188, 196, 211, 213, 217, 224, 227, 230, 208, 96, 59, 59, 48, 47, 49, 39, 31, 19, 19, 12, 7, 9, 6, 7, 6, 6, 6, 6, 6, 6, 6, 6, 6, 1, 1 ] }, { "name": "Not digitised", "type": "bar", "x": [ 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997 ], "y": [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4, 4, 5, 7, 7, 15, 17, 29, 35, 44, 59, 77, 79, 86, 94, 102, 109, 113, 118, 127, 139, 138, 126, 138, 140, 145, 134, 129, 89, 84, 74, 68, 62, 57, 53, 36, 29, 25, 9, 5, 4, 2, 2, 2, 3, 1, 1, 1, 1, 1, 1, 1, 1 ] } ], "layout": { "barmode": "stack", "title": "Content dates", "xaxis": { "title": "Year" }, "yaxis": { "title": "Number of items" } } }, "text/html": [ "
" ], "text/vnd.plotly.v1+html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = series_details.plot_dates(df)\n", "py.iplot(fig, filename='series-dates-bar')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## View word frequencies" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# Combine all of the file titles into a single string\n", "title_text = a = df['title'].str.lower().str.cat(sep=' ')" ] }, { "cell_type": "code", "execution_count": 8, "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", "
wordcount
0asio246
1surveillance243
2photograph237
174robinson161
198aka100
11john91
3james70
30william67
173albert56
175eva51
101march43
440number41
187george39
80may33
178max31
82sydney30
146demonstration29
208robert28
121david28
179ernest28
162photographs28
131doreen28
81day26
195nee25
153canberra23
" ], "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "series_details.display_word_counts(title_text)" ] }, { "cell_type": "code", "execution_count": 9, "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", "
ngramcount
0asio surveillance237
1surveillance photograph228
2photograph of208
3robinson asio119
4albert robinson51
5eva robinson50
6of eva48
7of albert48
8william robinson29
9photograph james28
10james william28
11ernest robinson25
12max ernest25
13of max25
14may day24
15day march23
16at the15
17scan of13
18resolution scan13
19high resolution13
20of page13
21doreen burrow12
22of doreen12
23burrow at12
24zangalis george11
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Change ngram_count for larger ngrams (trigrams etc)\n", "ngram_count = 2\n", "series_details.display_top_ngrams(title_text, ngram_count)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "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 }