{"id":4583,"date":"2015-05-11T16:15:57","date_gmt":"2015-05-11T13:15:57","guid":{"rendered":"http:\/\/www.webcodegeeks.com\/?p=4583"},"modified":"2015-05-11T03:43:22","modified_gmt":"2015-05-11T00:43:22","slug":"python-selecting-certain-indexes-array","status":"publish","type":"post","link":"https:\/\/www.webcodegeeks.com\/python\/python-selecting-certain-indexes-array\/","title":{"rendered":"Python: Selecting certain indexes in an array"},"content":{"rendered":"<p>A couple of days ago I was scrapping the <a href=\"http:\/\/en.wikipedia.org\/wiki\/List_of_United_Kingdom_Parliament_constituencies\">UK parliament constituencies<\/a> from Wikipedia in preparation for the <a href=\"http:\/\/www.meetup.com\/graphdb-london\/events\/221364888\/\">Graph Connect hackathon<\/a> and had got to the point where I had an array with one entry per column in the table.<\/p>\n<p><a href=\"http:\/\/www.webcodegeeks.com\/wp-content\/uploads\/2015\/05\/2015-05-05_22-22-57.png\"><img decoding=\"async\" class=\"aligncenter wp-image-4646\" src=\"http:\/\/www.webcodegeeks.com\/wp-content\/uploads\/2015\/05\/2015-05-05_22-22-57.png\" alt=\"2015-05-05_22-22-57\" width=\"860\" height=\"273\" srcset=\"https:\/\/www.webcodegeeks.com\/wp-content\/uploads\/2015\/05\/2015-05-05_22-22-57.png 946w, https:\/\/www.webcodegeeks.com\/wp-content\/uploads\/2015\/05\/2015-05-05_22-22-57-300x95.png 300w\" sizes=\"(max-width: 860px) 100vw, 860px\" \/><\/a><\/p>\n<pre class=\" brush:py\">import requests\r\n\u00a0\r\nfrom bs4 import BeautifulSoup\r\nfrom soupselect import select\r\n\u00a0\r\npage = open(\"constituencies.html\", 'r')\r\nsoup = BeautifulSoup(page.read())\r\n\u00a0\r\nfor row in select(soup, \"table.wikitable tr\"):\r\n    if select(row, \"th\"):\r\n        print [cell.text for cell in select(row, \"th\")]\r\n\u00a0\r\n    if select(row, \"td\"):\r\n        print [cell.text for cell in select(row, \"td\")]<\/pre>\n<pre class=\" brush:bash\">$ python blog.py\r\n[u'Constituency', u'Electorate (2000)', u'Electorate (2010)', u'Largest Local Authority', u'Country of the UK']\r\n[u'Aldershot', u'66,499', u'71,908', u'Hampshire', u'England']\r\n[u'Aldridge-Brownhills', u'58,695', u'59,506', u'West Midlands', u'England']\r\n[u'Altrincham and Sale West', u'69,605', u'72,008', u'Greater Manchester', u'England']\r\n[u'Amber Valley', u'66,406', u'69,538', u'Derbyshire', u'England']\r\n[u'Arundel and South Downs', u'71,203', u'76,697', u'West Sussex', u'England']\r\n[u'Ashfield', u'74,674', u'77,049', u'Nottinghamshire', u'England']\r\n[u'Ashford', u'72,501', u'81,947', u'Kent', u'England']\r\n[u'Ashton-under-Lyne', u'67,334', u'68,553', u'Greater Manchester', u'England']\r\n[u'Aylesbury', u'72,023', u'78,750', u'Buckinghamshire', u'England']\r\n...<\/pre>\n<p>I wanted to get rid of the 2nd and 3rd columns (containing the electorates) from the array since those aren\u2019t interesting to me as I have another source where I\u2019ve got that data from.<\/p>\n<p>I was struggling to do this but <a href=\"http:\/\/stackoverflow.com\/questions\/3179106\/python-select-subset-from-list-based-on-index-set\">two<\/a> <a href=\"http:\/\/stackoverflow.com\/questions\/522563\/accessing-the-index-in-python-for-loops\">different<\/a> Stack Overflow questions came to the rescue with suggestions to use enumerate to get the index of each column and then add to the list comprehension to filter appropriately.<\/p>\n<p>First we\u2019ll look at the filtering on a simple example. Imagine we have a list of 5 people:<\/p>\n<pre class=\" brush:py\">people = [\"mark\", \"michael\", \"brian\", \"alistair\", \"jim\"]<\/pre>\n<p>And we only want to keep the 1st, 4th and 5th people. We therefore only want to keep the values that exist in index positions 0,3 and 4 which we can do like this:<\/p>\n<pre class=\" brush:py\">&gt;&gt;&gt; [x[1] for x in enumerate(people) if x[0] in [0,3,4]]\r\n['mark', 'alistair', 'jim']<\/pre>\n<p>Now let\u2019s apply the same approach to our constituencies data set:<\/p>\n<pre class=\" brush:py\">import requests\r\n\u00a0\r\nfrom bs4 import BeautifulSoup\r\nfrom soupselect import select\r\n\u00a0\r\npage = open(\"constituencies.html\", 'r')\r\nsoup = BeautifulSoup(page.read())\r\n\u00a0\r\nfor row in select(soup, \"table.wikitable tr\"):\r\n    if select(row, \"th\"):\r\n        print [entry[1].text for entry in enumerate(select(row, \"th\")) if entry[0] in [0,3,4]]\r\n\u00a0\r\n    if select(row, \"td\"):\r\n        print [entry[1].text for entry in enumerate(select(row, \"td\")) if entry[0] in [0,3,4]]<\/pre>\n<pre class=\" brush:bash\">$ python blog.py\r\n[u'Constituency', u'Largest Local Authority', u'Country of the UK']\r\n[u'Aldershot', u'Hampshire', u'England']\r\n[u'Aldridge-Brownhills', u'West Midlands', u'England']\r\n[u'Altrincham and Sale West', u'Greater Manchester', u'England']\r\n[u'Amber Valley', u'Derbyshire', u'England']\r\n[u'Arundel and South Downs', u'West Sussex', u'England']\r\n[u'Ashfield', u'Nottinghamshire', u'England']\r\n[u'Ashford', u'Kent', u'England']\r\n[u'Ashton-under-Lyne', u'Greater Manchester', u'England']\r\n[u'Aylesbury', u'Buckinghamshire', u'England']<\/pre>\n<div class=\"attribution\">\n<table>\n<tbody>\n<tr>\n<td><span class=\"reference\">Reference: <\/span><\/td>\n<td><a href=\"http:\/\/www.markhneedham.com\/blog\/2015\/05\/05\/python-selecting-certain-indexes-in-an-array\/\">Python: Selecting certain indexes in an array<\/a> from our <a href=\"http:\/\/www.webcodegeeks.com\/wcg\/\">WCG partner<\/a> Mark Needham at the <a href=\"http:\/\/www.markhneedham.com\/blog\/\">Mark Needham Blog<\/a> blog.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>A couple of days ago I was scrapping the UK parliament constituencies from Wikipedia in preparation for the Graph Connect hackathon and had got to the point where I had an array with one entry per column in the table. import requests \u00a0 from bs4 import BeautifulSoup from soupselect import select \u00a0 page = open(&#8220;constituencies.html&#8221;, &hellip;<\/p>\n","protected":false},"author":48,"featured_media":1651,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[53],"tags":[],"class_list":["post-4583","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.5 - 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