def makegraph(self, outfile, masterkey="stats", key="occurences"):
"""
Generate a graph.
@param outfile: path to file to write to
@type outfile: L{str}
@param masterkey: category key of get_pairing_data()'s result to use.
@type masterkey: L{str}
@param key: key for value to use
@type key: L{str}
"""
# prepare data
data = self.get_pairing_data()
pairingstats = data[masterkey]
# purge all entries were value of key <= 0
to_purge = set()
for pairing in pairingstats.keys():
v = pairingstats[pairing][key]
if v <= 0:
to_purge.add(pairing)
for p in to_purge:
del pairingstats[p]
names = list(
sorted(
set([name for pairing in data[masterkey]
for name in pairing])))
n_names = len(names)
matrix = [[0] * n_names for i in range(n_names)]
for pairing in pairingstats.keys():
v = pairingstats[pairing][key]
name_1, name_2 = pairing
i, j = names.index(name_1), names.index(name_2)
matrix[i][j] = v
matrix[j][i] = v
c = Chord(
matrix,
names,
width=1600,
margin=200,
padding=0.02,
wrap_labels=False,
font_size="12px",
noun="FanFics",
allow_download=True,
#title="Ships (by {})".format(key),
credit=False,
)
c.to_html(filename=outfile)
def plot_diagrams(self, matrices, names, l_labels):
for i, (matrix, name) in enumerate(zip(matrices, names)):
colors = (get_colors(gray=name, color=l_labels))
diagram = Chord(
matrix,
name,
colors=colors, #"d3.schemeSet1",
opacity=0.9,
padding=0.01,
width=self.width,
font_size="10px",
font_size_large="10px",
label_color="#454545",
wrap_labels=self.wrap,
credit=False,
margin=self.margin,
)
diagram.show()
diagram.to_html(f'{self.filename}_{i}.html')
def generate_chord(team_id, season_id, season_progress, team_name):
team_passes = teamdashptpass.TeamDashPtPass(
team_id=team_id,
season=season_id,
season_type_all_star=season_progress,
per_mode_simple='PerGame')
# Print passes made
df_team_passes_made = team_passes.get_data_frames()[0]
#print(df_team_passes_made)
# Print passes received
df_team_passes_rec = team_passes.get_data_frames()[1]
#print(df_team_passes_rec)
player_ids = list(df_team_passes_made['PASS_TEAMMATE_PLAYER_ID'])
#print(player_ids)
# Create empty dataframes, one for passes made, another for passes received
team_pp_made = pd.DataFrame()
team_pp_rec = pd.DataFrame()
# Cycle through each pleayer id and extract passes made and passes received
for pid in player_ids:
player_pass = playerdashptpass.PlayerDashPtPass(
team_id=team_id,
player_id=pid,
season=season_id,
season_type_all_star=season_progress,
per_mode_simple='PerGame')
# Get DataFrames
player_pass_made = player_pass.get_data_frames()[0]
player_pass_rec = player_pass.get_data_frames()[1]
# Append
team_pp_made = pd.concat([team_pp_made, player_pass_made],
ignore_index=True,
axis=0,
sort=False)
team_pp_rec = pd.concat([team_pp_rec, player_pass_rec],
ignore_index=True,
axis=0,
sort=False)
# Sleep for 5 seconds before moving to the next player
time.sleep(0.5)
# Create merge keys
team_pp_made['key_pass_from_to'] = team_pp_made[
'PLAYER_NAME_LAST_FIRST'] + " : " + team_pp_made['PASS_TO']
team_pp_made['key_pass_to_from'] = team_pp_made[
'PASS_TO'] + " : " + team_pp_made['PLAYER_NAME_LAST_FIRST']
# Create a DataFrame based on key_pass_to_from
team_pp_made_to_from = team_pp_made.loc[:, ['key_pass_to_from', 'PASS']]
team_pp_made_to_from = team_pp_made_to_from.rename(
columns={'PASS': '******'})
#print(team_pp_made_to_from)
# Merge it back to the main DataFrame
team_pp_comb = pd.merge(team_pp_made,
team_pp_made_to_from,
how='left',
left_on='key_pass_from_to',
right_on='key_pass_to_from')
team_pp_comb['Total Passes'] = team_pp_comb['PASS'] + team_pp_comb[
'pass_to_from_cnt']
#print(team_pp_comb)
# Take a copy of DF
df = team_pp_comb.copy()
# Keep only required fields
df = df.loc[:, ['PLAYER_NAME_LAST_FIRST', 'PASS_TO', 'Total Passes']]
# Create crosstab (note, we replace NaN with 0's)
df_tab = pd.crosstab(df['PLAYER_NAME_LAST_FIRST'],
df['PASS_TO'],
aggfunc='sum',
values=df['Total Passes']).fillna(0)
# Print resulting DataFrame
#print(df_tab)
# Player Names
names = list(df_tab.columns)
#names
# Passing data (change from df to list of lists)
matrix = df_tab.values.tolist()
#matrix
# Create our diagram
diagram = Chord(matrix,
names,
font_size_large='10px',
wrap_labels=False,
margin=100,
width=800)
# Save it into HTML file
team_name = team_name.replace(' ', '')
season_progress = season_progress.replace(' ', '')
diagram.to_html(team_name + season_id + season_progress + 'Chord.html')
popupmsg_success()
