James McCool
commited on
Commit
·
2ab6242
1
Parent(s):
31e306d
getting NFL ready and set
Browse files- app.py +4 -4
- global_func/load_contest_file.py +9 -3
app.py
CHANGED
@@ -250,7 +250,7 @@ if selected_tab == 'Data Load':
|
|
250 |
sport_options, date_options = st.columns(2)
|
251 |
parse_type = 'Manual'
|
252 |
with sport_options:
|
253 |
-
sport_init = st.selectbox("Select Sport", ['MLB', 'MMA', 'GOLF', 'NBA', 'NHL', 'CFB', 'WNBA', 'NAS'], key='sport_init')
|
254 |
type_init = st.selectbox("Select Game Type", ['Classic', 'Showdown'], key='type_init')
|
255 |
try:
|
256 |
contest_names, curr_info = grab_contest_names(db, sport_init, type_init)
|
@@ -718,14 +718,14 @@ if selected_tab == 'Contest Analysis':
|
|
718 |
with col1:
|
719 |
pos_var = st.selectbox("Which position(s) would you like to view?", ['All', 'Specific'], key='pos_var')
|
720 |
with col2:
|
721 |
-
if st.session_state['sport_select'] == '
|
|
|
|
|
722 |
pos_select = st.multiselect("Select your position(s)", ['P', 'C', '1B', '2B', '3B', 'SS', 'OF'], key='pos_select')
|
723 |
elif st.session_state['sport_select'] == 'NBA':
|
724 |
pos_select = st.multiselect("Select your position(s)", ['PG', 'SG', 'SF', 'PF', 'C'], key='pos_select')
|
725 |
elif st.session_state['sport_select'] == 'WNBA':
|
726 |
pos_select = st.multiselect("Select your position(s)", ['PG', 'SG', 'SF', 'PF'], key='pos_select')
|
727 |
-
elif st.session_state['sport_select'] == 'NFL':
|
728 |
-
pos_select = st.multiselect("Select your position(s)", ['QB', 'RB', 'WR', 'TE', 'DST'], key='pos_select')
|
729 |
elif st.session_state['sport_select'] == 'NHL':
|
730 |
pos_select = st.multiselect("Select your position(s)", ['W', 'C', 'D', 'G'], key='pos_select')
|
731 |
elif st.session_state['sport_select'] == 'MMA':
|
|
|
250 |
sport_options, date_options = st.columns(2)
|
251 |
parse_type = 'Manual'
|
252 |
with sport_options:
|
253 |
+
sport_init = st.selectbox("Select Sport", ['NFL', 'MLB', 'MMA', 'GOLF', 'NBA', 'NHL', 'CFB', 'WNBA', 'NAS'], key='sport_init')
|
254 |
type_init = st.selectbox("Select Game Type", ['Classic', 'Showdown'], key='type_init')
|
255 |
try:
|
256 |
contest_names, curr_info = grab_contest_names(db, sport_init, type_init)
|
|
|
718 |
with col1:
|
719 |
pos_var = st.selectbox("Which position(s) would you like to view?", ['All', 'Specific'], key='pos_var')
|
720 |
with col2:
|
721 |
+
if st.session_state['sport_select'] == 'NFL':
|
722 |
+
pos_select = st.multiselect("Select your position(s)", ['QB', 'RB', 'WR', 'TE', 'DST'], key='pos_select')
|
723 |
+
elif st.session_state['sport_select'] == 'MLB':
|
724 |
pos_select = st.multiselect("Select your position(s)", ['P', 'C', '1B', '2B', '3B', 'SS', 'OF'], key='pos_select')
|
725 |
elif st.session_state['sport_select'] == 'NBA':
|
726 |
pos_select = st.multiselect("Select your position(s)", ['PG', 'SG', 'SF', 'PF', 'C'], key='pos_select')
|
727 |
elif st.session_state['sport_select'] == 'WNBA':
|
728 |
pos_select = st.multiselect("Select your position(s)", ['PG', 'SG', 'SF', 'PF'], key='pos_select')
|
|
|
|
|
729 |
elif st.session_state['sport_select'] == 'NHL':
|
730 |
pos_select = st.multiselect("Select your position(s)", ['W', 'C', 'D', 'G'], key='pos_select')
|
731 |
elif st.session_state['sport_select'] == 'MMA':
|
global_func/load_contest_file.py
CHANGED
@@ -109,7 +109,9 @@ def load_contest_file(upload, type, helper = None, sport = None, portfolio = Non
|
|
109 |
# Create the cleaned dataframe with just the essential columns
|
110 |
cleaned_df = df[['BaseName', 'Lineup']]
|
111 |
if type == 'Classic':
|
112 |
-
if sport == '
|
|
|
|
|
113 |
cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' P ', ' C ', '1B ', ' 2B ', ' 3B ', ' SS ', ' OF '], value=',', regex=True)
|
114 |
elif sport == 'MMA':
|
115 |
cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' P ', ' C ', '1B ', ' 2B ', ' 3B ', ' SS ', ' OF ', ' F ', 'F '], value=',', regex=True)
|
@@ -123,7 +125,9 @@ def load_contest_file(upload, type, helper = None, sport = None, portfolio = Non
|
|
123 |
cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' QB ', 'QB ', ' RB ', 'RB ', 'WR ', 'WR ', ' S-FLEX ', 'S-FLEX ', ' FLEX ', 'FLEX '], value=',', regex=True)
|
124 |
print(sport)
|
125 |
check_lineups = cleaned_df.copy()
|
126 |
-
if sport == '
|
|
|
|
|
127 |
cleaned_df[['Remove', '1B', '2B', '3B', 'C', 'OF1', 'OF2', 'OF3', 'P1', 'P2', 'SS']] = cleaned_df['Lineup'].str.split(',', expand=True)
|
128 |
elif sport == 'MMA':
|
129 |
cleaned_df[['Remove', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']] = cleaned_df['Lineup'].str.split(',', expand=True)
|
@@ -138,7 +142,9 @@ def load_contest_file(upload, type, helper = None, sport = None, portfolio = Non
|
|
138 |
cleaned_df = cleaned_df.drop(columns=['Lineup', 'Remove'])
|
139 |
entry_counts = cleaned_df['BaseName'].value_counts()
|
140 |
cleaned_df['EntryCount'] = cleaned_df['BaseName'].map(entry_counts)
|
141 |
-
if sport == '
|
|
|
|
|
142 |
cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'P1', 'P2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']]
|
143 |
elif sport == 'MMA':
|
144 |
cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']]
|
|
|
109 |
# Create the cleaned dataframe with just the essential columns
|
110 |
cleaned_df = df[['BaseName', 'Lineup']]
|
111 |
if type == 'Classic':
|
112 |
+
if sport == 'NFL':
|
113 |
+
cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' QB ', 'QB ', ' RB ', 'RB ', ' WR ', 'WR ', ' TE ', 'TE ', ' DST ', 'DST ', ' FLEX ', 'FLEX '], value=',', regex=True)
|
114 |
+
elif sport == 'MLB':
|
115 |
cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' P ', ' C ', '1B ', ' 2B ', ' 3B ', ' SS ', ' OF '], value=',', regex=True)
|
116 |
elif sport == 'MMA':
|
117 |
cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' P ', ' C ', '1B ', ' 2B ', ' 3B ', ' SS ', ' OF ', ' F ', 'F '], value=',', regex=True)
|
|
|
125 |
cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' QB ', 'QB ', ' RB ', 'RB ', 'WR ', 'WR ', ' S-FLEX ', 'S-FLEX ', ' FLEX ', 'FLEX '], value=',', regex=True)
|
126 |
print(sport)
|
127 |
check_lineups = cleaned_df.copy()
|
128 |
+
if sport == 'NFL':
|
129 |
+
cleaned_df[['Remove', 'DST', 'FLEX', 'QB', 'RB1', 'RB2', 'TE', 'WR1', 'WR2', 'WR3']] = cleaned_df['Lineup'].str.split(',', expand=True)
|
130 |
+
elif sport == 'MLB':
|
131 |
cleaned_df[['Remove', '1B', '2B', '3B', 'C', 'OF1', 'OF2', 'OF3', 'P1', 'P2', 'SS']] = cleaned_df['Lineup'].str.split(',', expand=True)
|
132 |
elif sport == 'MMA':
|
133 |
cleaned_df[['Remove', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']] = cleaned_df['Lineup'].str.split(',', expand=True)
|
|
|
142 |
cleaned_df = cleaned_df.drop(columns=['Lineup', 'Remove'])
|
143 |
entry_counts = cleaned_df['BaseName'].value_counts()
|
144 |
cleaned_df['EntryCount'] = cleaned_df['BaseName'].map(entry_counts)
|
145 |
+
if sport == 'NFL':
|
146 |
+
cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']]
|
147 |
+
elif sport == 'MLB':
|
148 |
cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'P1', 'P2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']]
|
149 |
elif sport == 'MMA':
|
150 |
cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']]
|