Spaces:
Running
Running
James McCool
commited on
Commit
·
9c5865c
1
Parent(s):
de14f93
Add dropna() to seed frame initialization functions
Browse filesImplemented dropna() in the seed frame initialization functions for DraftKings and FanDuel to remove any rows with missing values, ensuring cleaner data output for further processing.
app.py
CHANGED
@@ -68,6 +68,8 @@ def init_DK_seed_frames(load_size):
|
|
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()
|
72 |
|
73 |
return DK_seed
|
@@ -88,6 +90,8 @@ def init_DK_secondary_seed_frames(load_size):
|
|
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()
|
92 |
|
93 |
return DK_seed
|
@@ -108,6 +112,8 @@ def init_FD_seed_frames(load_size):
|
|
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()
|
112 |
|
113 |
return FD_seed
|
@@ -128,6 +134,8 @@ def init_FD_secondary_seed_frames(load_size):
|
|
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()
|
132 |
|
133 |
return FD_seed
|
|
|
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 |
+
|
72 |
+
raw_display = raw_display.dropna()
|
73 |
DK_seed = raw_display.to_numpy()
|
74 |
|
75 |
return DK_seed
|
|
|
90 |
dict_columns = ['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX']
|
91 |
for col in dict_columns:
|
92 |
raw_display[col] = raw_display[col].map(names_dict)
|
93 |
+
|
94 |
+
raw_display = raw_display.dropna()
|
95 |
DK_seed = raw_display.to_numpy()
|
96 |
|
97 |
return DK_seed
|
|
|
112 |
dict_columns = ['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1']
|
113 |
for col in dict_columns:
|
114 |
raw_display[col] = raw_display[col].map(names_dict)
|
115 |
+
|
116 |
+
raw_display = raw_display.dropna()
|
117 |
FD_seed = raw_display.to_numpy()
|
118 |
|
119 |
return FD_seed
|
|
|
134 |
dict_columns = ['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1']
|
135 |
for col in dict_columns:
|
136 |
raw_display[col] = raw_display[col].map(names_dict)
|
137 |
+
|
138 |
+
raw_display = raw_display.dropna()
|
139 |
FD_seed = raw_display.to_numpy()
|
140 |
|
141 |
return FD_seed
|