Jul-12-2019, 04:34 AM
(Jul-11-2019, 06:50 AM)perfringo Wrote: Is having table as pandas dataframe is ok?
>>> df = pd.read_html('http://stats.espncricinfo.com/ci/engine/player/348144.htmlclass=3;template=results;type=batting;view=innings') >>> df[3] Runs Mins BF ... Ground Start Date Unnamed: 13 0 15* 13 11 ... Manchester 7 Sep 2016 T20I # 566 1 55* 49 37 ... Dubai (DSC) 23 Sep 2016 T20I # 568 2 19 28 18 ... Dubai (DSC) 24 Sep 2016 T20I # 569 3 27* 42 24 ... Abu Dhabi 27 Sep 2016 T20I # 570 4 29 - 30 ... Bridgetown 26 Mar 2017 T20I # 602 5 27 - 28 ... Port of Spain 30 Mar 2017 T20I # 603 6 43 - 38 ... Port of Spain 1 Apr 2017 T20I # 604 7 38 - 36 ... Port of Spain 2 Apr 2017 T20I # 605 8 86 - 52 ... Lahore 12 Sep 2017 T20I # 619 9 45 - 38 ... Lahore 13 Sep 2017 T20I # 620 10 48 - 31 ... Lahore 15 Sep 2017 T20I # 621 11 1 - 8 ... Abu Dhabi 26 Oct 2017 T20I # 625 12 1 - 2 ... Abu Dhabi 27 Oct 2017 T20I # 627 13 34* - 31 ... Lahore 29 Oct 2017 T20I # 629 14 41 68 41 ... Wellington 22 Jan 2018 T20I # 639 15 50* 45 29 ... Auckland 25 Jan 2018 T20I # 640 16 18 - 17 ... Mount Maunganui 28 Jan 2018 T20I # 641 17 17 - 13 ... Karachi 1 Apr 2018 T20I # 663 18 97* - 58 ... Karachi 2 Apr 2018 T20I # 664 19 51 - 40 ... Karachi 3 Apr 2018 T20I # 665 20 68* - 55 ... Abu Dhabi 24 Oct 2018 T20I # 701 21 45 - 44 ... Dubai (DSC) 26 Oct 2018 T20I # 702 22 50 - 40 ... Dubai (DSC) 28 Oct 2018 T20I # 704 23 7 - 9 ... Abu Dhabi 31 Oct 2018 T20I # 705 24 40 - 41 ... Dubai (DSC) 2 Nov 2018 T20I # 706 25 79 66 58 ... Dubai (DSC) 4 Nov 2018 T20I # 708 26 38 55 27 ... Cape Town 1 Feb 2019 T20I # 732 27 90 78 58 ... Johannesburg 3 Feb 2019 T20I # 734 28 23 10 11 ... Centurion 6 Feb 2019 T20I # 736 29 65 - 42 ... Cardiff 5 May 2019 T20I # 772 [30 rows x 14 columns]
Do I have to restructure my code from scratch? Is there no way I can use my existing code to get the columns that I might need?
Thanks