Rename streamlit_app.py to app.py
Browse files- streamlit_app.py → app.py +39 -3
streamlit_app.py → app.py
RENAMED
@@ -71,8 +71,36 @@ def load_fd_player_projections():
|
|
71 |
|
72 |
return raw_display
|
73 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
74 |
dk_roo_raw = load_dk_player_projections()
|
|
|
75 |
fd_roo_raw = load_fd_player_projections()
|
|
|
76 |
|
77 |
@st.cache_data
|
78 |
def convert_df_to_csv(df):
|
@@ -104,16 +132,24 @@ with tab2:
|
|
104 |
if st.button("Load/Reset Data", key='reset2'):
|
105 |
st.cache_data.clear()
|
106 |
dk_roo_raw = load_dk_player_projections()
|
|
|
107 |
fd_roo_raw = load_fd_player_projections()
|
108 |
-
|
|
|
109 |
site_var2 = st.radio("What table would you like to display?", ('Draftkings', 'Fanduel'), key='site_var2')
|
110 |
if slate_var2 == 'User':
|
111 |
raw_baselines = proj_dataframe
|
112 |
elif slate_var2 != 'User':
|
113 |
if site_var2 == 'Draftkings':
|
114 |
-
|
|
|
|
|
|
|
115 |
elif site_var2 == 'Fanduel':
|
116 |
-
|
|
|
|
|
|
|
117 |
|
118 |
with col2:
|
119 |
hold_container = st.empty()
|
|
|
71 |
|
72 |
return raw_display
|
73 |
|
74 |
+
@st.cache_resource(ttl=600)
|
75 |
+
def load_dk_player_projections_2():
|
76 |
+
sh = gc.open_by_url(all_dk_player_projections)
|
77 |
+
worksheet = sh.worksheet('SD_Projections_2')
|
78 |
+
load_display = pd.DataFrame(worksheet.get_all_records())
|
79 |
+
load_display.replace('', np.nan, inplace=True)
|
80 |
+
raw_display = load_display.dropna(subset=['PPR'])
|
81 |
+
raw_display.rename(columns={"name": "Player", "PPR": "Median"}, inplace = True)
|
82 |
+
raw_display = raw_display[['Player', 'Salary', 'Position', 'Team', 'Opp', 'Median', 'Own', 'rush_yards', 'rec']]
|
83 |
+
raw_display = raw_display.loc[raw_display['Median'] > 0]
|
84 |
+
|
85 |
+
return raw_display
|
86 |
+
|
87 |
+
@st.cache_resource(ttl=600)
|
88 |
+
def load_fd_player_projections_2():
|
89 |
+
sh = gc.open_by_url(all_dk_player_projections)
|
90 |
+
worksheet = sh.worksheet('FD_SD_Projections_2')
|
91 |
+
load_display = pd.DataFrame(worksheet.get_all_records())
|
92 |
+
load_display.replace('', np.nan, inplace=True)
|
93 |
+
raw_display = load_display.dropna(subset=['Half_PPR'])
|
94 |
+
raw_display.rename(columns={"name": "Player", "Half_PPR": "Median"}, inplace = True)
|
95 |
+
raw_display = raw_display[['Player', 'Salary', 'Position', 'Team', 'Opp', 'Median', 'Own', 'rush_yards', 'rec']]
|
96 |
+
raw_display = raw_display.loc[raw_display['Median'] > 0]
|
97 |
+
|
98 |
+
return raw_display
|
99 |
+
|
100 |
dk_roo_raw = load_dk_player_projections()
|
101 |
+
dk_roo_raw_2 = load_dk_player_projections_2()
|
102 |
fd_roo_raw = load_fd_player_projections()
|
103 |
+
fd_roo_raw_2 = load_fd_player_projections_2()
|
104 |
|
105 |
@st.cache_data
|
106 |
def convert_df_to_csv(df):
|
|
|
132 |
if st.button("Load/Reset Data", key='reset2'):
|
133 |
st.cache_data.clear()
|
134 |
dk_roo_raw = load_dk_player_projections()
|
135 |
+
dk_roo_raw_2 = load_dk_player_projections_2()
|
136 |
fd_roo_raw = load_fd_player_projections()
|
137 |
+
fd_roo_raw_2 = load_fd_player_projections_2()
|
138 |
+
slate_var2 = st.radio("Which data are you loading?", ('Paydirt (Main)', 'Paydirt (Secondary)', 'User'), key='slate_var2')
|
139 |
site_var2 = st.radio("What table would you like to display?", ('Draftkings', 'Fanduel'), key='site_var2')
|
140 |
if slate_var2 == 'User':
|
141 |
raw_baselines = proj_dataframe
|
142 |
elif slate_var2 != 'User':
|
143 |
if site_var2 == 'Draftkings':
|
144 |
+
if slate_var2 == 'Paydirt (Main)':
|
145 |
+
raw_baselines = dk_roo_raw
|
146 |
+
elif slate_var2 == 'Paydirt (Secondary)':
|
147 |
+
raw_baselines = dk_roo_raw_2
|
148 |
elif site_var2 == 'Fanduel':
|
149 |
+
if slate_var2 == 'Paydirt (Main)':
|
150 |
+
raw_baselines = fd_roo_raw
|
151 |
+
elif slate_var2 == 'Paydirt (Secondary)':
|
152 |
+
raw_baselines = fd_roo_raw_2
|
153 |
|
154 |
with col2:
|
155 |
hold_container = st.empty()
|