Jan-06-2020, 06:06 PM
Hi there,
I have a Python Code, which runs fine, but I want the Correct complete Date shown, in the Date Column, in each Row of the DataFrame Output.
Due to the layout of the Schedule Table, at that particular URL, only the day is shown in the Date Column, in each Row displayed.
Here is the Code :-
For example for the Venue Ripley the date would show as, 02/05/2004
For Blackpool it would show as 16/05/2004
And that pattern, supplied for every Row, in the Output DataFrame ?
Sorry in the Output I posted, the layout is incorrect. If you run the Code, in Jupyter Notebook, you will see,
what I was trying to post.
Any help would be appreciated
Regards
Eddie Winch
I have a Python Code, which runs fine, but I want the Correct complete Date shown, in the Date Column, in each Row of the DataFrame Output.
Due to the layout of the Schedule Table, at that particular URL, only the day is shown in the Date Column, in each Row displayed.
Here is the Code :-
import pandas as pd import requests from bs4 import BeautifulSoup res = requests.get("http://web.archive.org/web/20041020000138/http://www.raf.mod.uk/bbmf/displaydates.html") soup = BeautifulSoup(res.content,'lxml') table = soup.find_all('table', align="CENTER")[0] df = pd.read_html(str(table)) df = df[0] df = df.rename(columns=df.iloc[0]) df = df.iloc[2:] df.head(15) pd.options.display.max_rows = 1000 display = df[(df['Location'].str.contains('[a-zA-Z]')) & (df['Lancaster'].str.contains('X')) & (df['Spitfire'].str.contains('X', na=True)) & (df['Dakota'].str.contains('X', na=True))] display #display.drop('Dakota', axis=1, inplace=True) display.dropna(subset=['Spitfire', 'Hurricane'], how='all')And this is the Output :-
Output:Date Location Lancaster Spitfire Hurricane Dakota
21 14 Digby X X X NaN
22 15 Harlaxton X X X NaN
23 15 Coleraine X X X NaN
30 16 New Leake X X X X
31 16 Blackpool X X X NaN
32 16 Elvington X X X NaN
46 30 Conington X X X NaN
47 30 Enfield X X X NaN
48 30 Southend X X X NaN
51 31 Southend X X X NaN
53 31 Sharnbrook X X X NaN
54 31 Peterborough X X X NaN
62 5 Portsmouth X X x 2 NaN NaN
63 5 Sandown (IoW) X X x 2 NaN NaN
64 5 Yarmouth Harbour (IoW) X X x 2 NaN NaN
68 6 Newhaven Fort X X x 2 NaN NaN
71 6 Westerham X X x 2 NaN NaN
72 6 Arromanche X X x 2 NaN NaN
75 7 Normandy X X x 2 NaN X
79 12 Digby X X NaN NaN
80 12 Bracebridge Heath X X NaN NaN
81 12 Newark X X x 2 X X
82 12 Castle Donington X X NaN NaN
87 13 Barrow in Furness X X X NaN
88 13 Cosford X X X X
89 13 Loughborough X X X NaN
91 13 Little Bytham X X NaN NaN
128 26 Woodston X X X NaN
129 26 Barrowden X X X NaN
130 26 Skillington X X X NaN
131 26 East Bridgeford X X X NaN
132 26 Waddington X X X X
139 27 Waddington X X X X
151 3 Tattershall X X NaN NaN
162 3 Branston X X X NaN
163 3 Ripley Castle X X X NaN
175 4 Spilsby X X NaN NaN
185 10 East Fortune X X X NaN
186 10 Thirsk X X X NaN
203 14 Culdrose X X X NaN
204 14 Shrivenham X X X NaN
208 17 Old Brampton X X X NaN
209 17 Glenridding X X X NaN
210 17 Carlisle X X X NaN
219 23 Llandiloes X X X X
220 23 Benson X NaN X NaN
221 24 Farnborough X X X NaN
222 24 North Coates X X X NaN
223 24 Scunthorpe X X X NaN
224 24 Breighton X X X NaN
225 24 Sunderland X X X NaN
226 25 Sunderland X X X NaN
227 25 York X X X NaN
228 25 Breighton X X X NaN
229 25 Luddington X X X NaN
230 25 North Coates X X X NaN
231 25 Sutton on Sea X X X NaN
235 29 Lowestoft X X X NaN
236 30 Lowestoft X X X NaN
240 31 Lincoln Showground X X X NaN
241 31 Kielder Forest X X X NaN
242 31 Windermere X X X NaN
244 1 Windermere X X X NaN
245 1 Cudworth X X X NaN
246 1 Doncaster X X X NaN
247 1 Lincoln Showground X X X NaN
250 13 Eastbourne X X X NaN
251 14 Eastbourne X X X NaN
258 15 Eastbourne X X X NaN
260 15 Barnack X X X NaN
271 21 Shepway X X X NaN
274 22 Falaise X X NaN NaN
277 27 Dartmouth X X X NaN
278 28 Henstridge X X X NaN
279 28 Shoreham X X X NaN
280 28 Kent Showground X X X NaN
281 29 Shoreham X X X NaN
285 29 Little Gransden X X X NaN
289 30 Aylsham X X X NaN
291 30 Grimsthorpe X NaN X NaN
303 4 Duxford X X X NaN
304 4 Goodwood X X X NaN
305 4 Fareham X X X NaN
306 5 Goodwood X X X NaN
308 5 Duxford X X X NaN
315 9 Guernsey X X X X
316 9 Jersey X X X X
319 11 Southport X X X NaN
320 11 Morecambe X X X NaN
321 11 Leuchars X X X NaN
325 12 Morecambe X X X NaN
326 12 Southport X X X NaN
350 18 Yeovilton X X X NaN
351 18 Little Casterton X X X NaN
364 25 Lichfield X X NaN NaN
If you type, and go to the Url, you will see where the Month Is displayed. What should I type, so that all the full Dates are shown, in the Date Column ?For example for the Venue Ripley the date would show as, 02/05/2004
For Blackpool it would show as 16/05/2004
And that pattern, supplied for every Row, in the Output DataFrame ?
Sorry in the Output I posted, the layout is incorrect. If you run the Code, in Jupyter Notebook, you will see,
what I was trying to post.
Any help would be appreciated
Regards
Eddie Winch