def get_lineup_info(teampg_url, n_combo):
'''
For a team, gets lineup-by-lineup statistics for each individual combination of n_combo (a value in
(2,5)) players
Given:
teampg_url, a string giving the url of the Basketball-Reference page for a team for a given season
n_combo, an integer specifying the level of lineup combination (2, 3, 4, or 5 players)
Return:
df, a dataframe of the team's statistics for each possible n_combo lineup of players
'''
# Parse the team/season's lineup page
main_url = teampg_url + '/lineups'
soup = get_soup(main_url)
# Find the table with all n_combo man lineups
tbl_string = 'lineups_' + str(n_combo) + '-man_'
tbl = soup.find('table', {'id': tbl_string})
# Create dictionary whose keys are the lineup combination and values are all the statistics from the
# table, then convert to a dataframe
d = {}
rows = [row for row in tbl.find_all('tr')]
for row in rows[:-1]:
items = row.find_all('td')
try:
comb = items[0].text
d[comb] = [j.text.strip() for j in items[1:]]
except:
continue
df = pd.DataFrame.from_dict(d, orient='index')
df.columns = [k.text for k in rows[1].find_all('th')][2:]
return df
def get_season_teams(season):
'''
Returns the Basketball-Reference page urls for each team that played during a specified season
Given:
season, the (int) end year of a given NBA regular season
Return:
d, a dictionary of each team and the url of the team page for the given season
'''
# Parse the season page
year = season.split('-')[1]
szn_url = 'https://www.basketball-reference.com/leagues/NBA_' + year + '.html'
soup = get_soup(szn_url)
# Find a table listing all teams
tbl = soup.find('table', {'id': 'team-stats-per_game'})
# Fill dictionary of all team names (keys) and team pages (values) for the season
d = {}
rows = [row for row in tbl.find_all('tr')]
for row in rows[:-1]:
items = row.find_all('td')
try:
team = items[0].text.replace('*', '')
d[team] = row.find('a').get('href')
except:
continue
return d
from bokeh.models import Div
extract_contents = lambda row: [x.text.replace('\n', '') for x in row]
URL = 'https://www.mohfw.gov.in/'
SHORT_HEADERS = [
'SNo', 'State', 'Indian-Confirmed(Including Foreign Confirmed)', 'Cured',
'Death'
]
response = requests.get(URL).content
soup = BeautifulSoup(response, 'html.parser')
updatedon = soup.find('div', class_="status-update").find('h2').text
header = extract_contents(soup.tr.find_all('th'))
stats = []
all_rows = soup.find_all('tr')
for row in all_rows:
stat = extract_contents(row.find_all('td'))
if stat:
if len(stat) == 4:
# last row
stat = ['', *stat]
stats.append(stat)
elif len(stat) == 5:
stats.append(stat)
stats[-1][0] = len(stats)
stats[-1][1] = "Total Cases"
objects = []
for row in stats:
objects.append(row[1])
y_pos = np.arange(len(objects))
performance = []
for row in stats[:len(stats) - 1]: