Spaces:
Sleeping
Sleeping
James McCool
commited on
Commit
·
572db67
1
Parent(s):
d4b7286
Remove redundant print statements in seed frame initialization functions
Browse filesCleaned up unnecessary `st.write("converting names")` debug statements across DraftKings and FanDuel seed frame initialization methods, improving code clarity without changing core functionality.
app.py
CHANGED
|
@@ -66,7 +66,6 @@ def init_DK_seed_frames(load_size):
|
|
| 66 |
raw_display = pd.DataFrame(list(cursor))
|
| 67 |
raw_display = raw_display[['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
|
| 68 |
dict_columns = ['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX']
|
| 69 |
-
st.write("converting names")
|
| 70 |
for col in dict_columns:
|
| 71 |
raw_display[col] = raw_display[col].map(names_dict)
|
| 72 |
DK_seed = raw_display.to_numpy()
|
|
@@ -87,7 +86,6 @@ def init_DK_secondary_seed_frames(load_size):
|
|
| 87 |
raw_display = pd.DataFrame(list(cursor))
|
| 88 |
raw_display = raw_display[['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
|
| 89 |
dict_columns = ['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX']
|
| 90 |
-
st.write("converting names")
|
| 91 |
for col in dict_columns:
|
| 92 |
raw_display[col] = raw_display[col].map(names_dict)
|
| 93 |
DK_seed = raw_display.to_numpy()
|
|
@@ -108,7 +106,6 @@ def init_FD_seed_frames(load_size):
|
|
| 108 |
raw_display = pd.DataFrame(list(cursor))
|
| 109 |
raw_display = raw_display[['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
|
| 110 |
dict_columns = ['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1']
|
| 111 |
-
st.write("converting names")
|
| 112 |
for col in dict_columns:
|
| 113 |
raw_display[col] = raw_display[col].map(names_dict)
|
| 114 |
FD_seed = raw_display.to_numpy()
|
|
@@ -129,7 +126,6 @@ def init_FD_secondary_seed_frames(load_size):
|
|
| 129 |
raw_display = pd.DataFrame(list(cursor))
|
| 130 |
raw_display = raw_display[['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
|
| 131 |
dict_columns = ['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1']
|
| 132 |
-
st.write("converting names")
|
| 133 |
for col in dict_columns:
|
| 134 |
raw_display[col] = raw_display[col].map(names_dict)
|
| 135 |
FD_seed = raw_display.to_numpy()
|
|
|
|
| 66 |
raw_display = pd.DataFrame(list(cursor))
|
| 67 |
raw_display = raw_display[['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
|
| 68 |
dict_columns = ['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX']
|
|
|
|
| 69 |
for col in dict_columns:
|
| 70 |
raw_display[col] = raw_display[col].map(names_dict)
|
| 71 |
DK_seed = raw_display.to_numpy()
|
|
|
|
| 86 |
raw_display = pd.DataFrame(list(cursor))
|
| 87 |
raw_display = raw_display[['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
|
| 88 |
dict_columns = ['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX']
|
|
|
|
| 89 |
for col in dict_columns:
|
| 90 |
raw_display[col] = raw_display[col].map(names_dict)
|
| 91 |
DK_seed = raw_display.to_numpy()
|
|
|
|
| 106 |
raw_display = pd.DataFrame(list(cursor))
|
| 107 |
raw_display = raw_display[['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
|
| 108 |
dict_columns = ['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1']
|
|
|
|
| 109 |
for col in dict_columns:
|
| 110 |
raw_display[col] = raw_display[col].map(names_dict)
|
| 111 |
FD_seed = raw_display.to_numpy()
|
|
|
|
| 126 |
raw_display = pd.DataFrame(list(cursor))
|
| 127 |
raw_display = raw_display[['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
|
| 128 |
dict_columns = ['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1']
|
|
|
|
| 129 |
for col in dict_columns:
|
| 130 |
raw_display[col] = raw_display[col].map(names_dict)
|
| 131 |
FD_seed = raw_display.to_numpy()
|