Spaces:
Running
Running
James McCool
commited on
Commit
·
95a7eab
1
Parent(s):
532dd1b
removed dtype prints
Browse files
app.py
CHANGED
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@@ -190,7 +190,6 @@ with tab1:
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salary_file[x] = salary_file['Salary']
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salary_file=salary_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
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salary_file.astype('int').dtypes
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salary_file = salary_file.div(1000)
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@@ -198,7 +197,6 @@ with tab1:
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overall_file[x] = np.random.normal(overall_file['Median'],overall_file['STD'])
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overall_file=overall_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
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overall_file.astype('int').dtypes
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players_only = hold_file[['Player']]
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raw_lineups_file = players_only
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@@ -209,7 +207,6 @@ with tab1:
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players_only[x] = raw_lineups_file[x].rank(ascending=False)
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players_only=players_only.drop(['Player'], axis=1)
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players_only.astype('int').dtypes
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salary_2x_check = (overall_file - (salary_file*2))
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salary_3x_check = (overall_file - (salary_file*3))
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@@ -278,7 +275,6 @@ with tab1:
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salary_file[x] = salary_file['Salary']
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salary_file=salary_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
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salary_file.astype('int').dtypes
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salary_file = salary_file.div(1000)
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@@ -286,7 +282,6 @@ with tab1:
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overall_file[x] = np.random.normal(overall_file['Median'],overall_file['STD'])
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overall_file=overall_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
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overall_file.astype('int').dtypes
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players_only = hold_file[['Player']]
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raw_lineups_file = players_only
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@@ -297,7 +292,6 @@ with tab1:
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players_only[x] = raw_lineups_file[x].rank(ascending=False)
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players_only=players_only.drop(['Player'], axis=1)
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players_only.astype('int').dtypes
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salary_2x_check = (overall_file - (salary_file*2))
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salary_3x_check = (overall_file - (salary_file*3))
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salary_file[x] = salary_file['Salary']
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salary_file=salary_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
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salary_file = salary_file.div(1000)
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overall_file[x] = np.random.normal(overall_file['Median'],overall_file['STD'])
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overall_file=overall_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
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players_only = hold_file[['Player']]
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raw_lineups_file = players_only
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players_only[x] = raw_lineups_file[x].rank(ascending=False)
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players_only=players_only.drop(['Player'], axis=1)
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salary_2x_check = (overall_file - (salary_file*2))
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salary_3x_check = (overall_file - (salary_file*3))
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salary_file[x] = salary_file['Salary']
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salary_file=salary_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
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salary_file = salary_file.div(1000)
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overall_file[x] = np.random.normal(overall_file['Median'],overall_file['STD'])
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overall_file=overall_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
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players_only = hold_file[['Player']]
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raw_lineups_file = players_only
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players_only[x] = raw_lineups_file[x].rank(ascending=False)
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players_only=players_only.drop(['Player'], axis=1)
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salary_2x_check = (overall_file - (salary_file*2))
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salary_3x_check = (overall_file - (salary_file*3))
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