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Update app.py
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app.py
CHANGED
@@ -715,9 +715,32 @@ pitcher_test_df = pitcher_test_df.set_index('pitcher_id')
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batter_dict = batter_test_df['batter'].to_dict()
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pitcher_dict = pitcher_test_df['pitcher'].to_dict()
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level_dict = {'MLB':'MLB','AAA':'AAA','AA':'AA','A+':'A+','A':'A'}
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level_dict_pitch = {'MLB':'MLB','AAA':'AAA','AA':'AA','A+':'A+','A':'A'}
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plot_dict_small_all = {
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'k':'k_percent',
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'bb':'bb_percent',
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@@ -739,31 +762,11 @@ plot_dict_small_all = {
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'chase_percent':'chase_percent',
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'chase_contact':'chase_contact',}
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plot_dict_small_all_input = {
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'k_percent':'k_percent',
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'bb_percent':'bb_percent',
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'bb_minus_k_percent':'bb_minus_k_percent',
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'csw_percent':'csw_percent',
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'woba_percent':'woba_percent',
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'launch_speed':'launch_speed',
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'launch_speed_90':'launch_speed_90',
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'hard_hit_percent':'hard_hit_percent',
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'sweet_spot_percent':'sweet_spot_percent',
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'launch_angle':'launch_angle',
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'zone_percent':'zone_percent',
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'barrel_percent':'barrel_percent',
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'swing_percent':'swing_percent',
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'whiff_rate':'whiff_rate',
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'swstr_rate':'swstr_rate',
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'zone_swing_percent':'zone_swing_percent',
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'zone_contact_percent':'zone_contact_percent',
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'chase_percent':'chase_percent',
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'chase_contact':'chase_contact',}
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plot_dict_small_this_one = {
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'k_percent':'K%',
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'bb_percent':'BB%',
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'bb_minus_k_percent':'BB
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'csw_percent':'CSW%',
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'woba_percent':'wOBA',
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'launch_speed':'Exit Velocity',
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@@ -780,16 +783,50 @@ plot_dict_small_this_one = {
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'zone_contact_percent':'Z-Contact%',
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'chase_percent':'O-Swing%',
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'chase_contact':'O-Contact%',}
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plot_dict_small_this_format = {
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'k_percent':'{:,.1%}',
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'bb_percent':'{:,.1%}',
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@@ -832,50 +869,31 @@ plot_dict_small_this_format_diff = {
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'chase_percent':'{0:+.1%}',
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'chase_contact':'{0:+.1%}',}
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plot_dict_small = {
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'k':'K%',
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'bb':'BB%',
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'bb_minus_k':'BB-K%',
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'csw':'CSW%',
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'woba':'wOBA',
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'launch_speed':'Exit Velocity',
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'launch_speed_90':'90th Percentile Exit Velocity',
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'hard_hit':'HardHit%',
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'sweet_spot':'SweetSpot%',
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'launch_angle':'Launch Angle',
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'zone_percent':'Zone%',
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'barrel':'Barrel%',
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'swing_percent':'Swing%',
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'whiff_rate':'Whiff%',
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'swstr_rate':'SwStr%',
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'zone_swing':'Z-Swing%',
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'zone_contact':'Z-Contact%',
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'chase_percent':'O-Swing%',
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'chase_contact':'O-Contact%',}
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'
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'bb':'BB%',
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'bb_minus_k':'K-BB%',
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'csw':'CSW%',
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'woba':'wOBA',
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'launch_speed':'Exit Velocity',
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'launch_speed_90':'90th Percentile Exit Velocity',
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'hard_hit':'HardHit%',
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'sweet_spot':'SweetSpot%',
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'launch_angle':'Launch Angle',
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'zone_percent':'Zone%',
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'barrel':'Barrel%',
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'swing_percent':'Swing%',
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'whiff_rate':'Whiff%',
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'sw_str':'SwStr%',
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'zone_swing':'Z-Swing%',
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'zone_contact':'Z-Contact%',
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'chase_percent':'O-Swing%',
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'chase_contact':'O-Contact%',}
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team_list = ['All'] + sorted(list(exit_velo_df_codes_summ_batter.parent_org_abb.unique()))
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sort_list = ['Season Stat','Timeframe Stat','Difference']
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@@ -906,11 +924,11 @@ app_ui = ui.page_fluid(ui.layout_sidebar(
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ui.input_select("level_id", "Select Level",level_dict,width=1,multiple=True,selected='MLB',selectize=True),
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ui.input_select("team_id", "Select Team",team_list,width=1,size=1,multiple=True,selected='All',selectize=True),
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ui.input_select("sort_id", "Sort By",sort_list,width=1,size=1,selected='Timeframe Stat'),
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ui.
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ui.panel_main(ui.tags.h2("Batter Season Average vs Timeframe Average"),
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ui.output_text("txt"),
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ui.output_table("result")),
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))
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@@ -1051,14 +1069,10 @@ def server(input, output, session):
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print(plot_dict_small_all_input[input.stat_id()])
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exit_velo_df_codes_summ_time['Difference'] = exit_velo_df_codes_summ_time[input.stat_id()+'_time'] - exit_velo_df_codes_summ_time[input.stat_id()]
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# format_column
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format_column = plot_dict_small_this_format[input.stat_id()]
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format_column_diff = plot_dict_small_this_format_diff[input.stat_id()]
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if input.sort_id() == 'Difference':
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@@ -1098,14 +1112,67 @@ def server(input, output, session):
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# })
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exit_velo_df_codes_summ_time[plot_dict_small_this_one[input.stat_id()]] = exit_velo_df_codes_summ_time[plot_dict_small_this_one[input.stat_id()]].map(format_column.format)
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exit_velo_df_codes_summ_time[plot_dict_small_this_one[input.stat_id()]+' Since'] = exit_velo_df_codes_summ_time[plot_dict_small_this_one[input.stat_id()]+' Since'].map(format_column.format)
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exit_velo_df_codes_summ_time['Difference'] = exit_velo_df_codes_summ_time['Difference'].map(format_column_diff.format)
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return exit_velo_df_codes_summ_time[['Rank','Batter ID','Batter','Team','Level','PA',plot_dict_small_this_one[input.stat_id()],
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'PA Since',plot_dict_small_this_one[input.stat_id()]+' Since',
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'Difference']]
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# @output
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# @render.plot(alt="A histogram")
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# def plot_pitch():
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batter_dict = batter_test_df['batter'].to_dict()
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pitcher_dict = pitcher_test_df['pitcher'].to_dict()
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plot_dict_small_all_input = {
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'k_percent':'k_percent',
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'bb_percent':'bb_percent',
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'bb_minus_k_percent':'bb_minus_k_percent',
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'csw_percent':'csw_percent',
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'woba_percent':'woba_percent',
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'launch_speed':'launch_speed',
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'launch_speed_90':'launch_speed_90',
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'hard_hit_percent':'hard_hit_percent',
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'sweet_spot_percent':'sweet_spot_percent',
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'launch_angle':'launch_angle',
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'zone_percent':'zone_percent',
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'barrel_percent':'barrel_percent',
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'swing_percent':'swing_percent',
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'whiff_rate':'whiff_rate',
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'swstr_rate':'swstr_rate',
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'zone_swing_percent':'zone_swing_percent',
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'zone_contact_percent':'zone_contact_percent',
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'chase_percent':'chase_percent',
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'chase_contact':'chase_contact',}
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level_dict = {'MLB':'MLB','AAA':'AAA','AA':'AA','A+':'A+','A':'A'}
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level_dict_pitch = {'MLB':'MLB','AAA':'AAA','AA':'AA','A+':'A+','A':'A'}
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plot_dict_small_all = {
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'k':'k_percent',
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'bb':'bb_percent',
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'chase_percent':'chase_percent',
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'chase_contact':'chase_contact',}
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plot_dict_small_this_one = {
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'k_percent':'K%',
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'bb_percent':'BB%',
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'bb_minus_k_percent':'BB%-K%',
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'csw_percent':'CSW%',
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'woba_percent':'wOBA',
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'launch_speed':'Exit Velocity',
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'zone_contact_percent':'Z-Contact%',
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'chase_percent':'O-Swing%',
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'chase_contact':'O-Contact%',}
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plot_dict_small = {
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'k':'K%',
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'bb':'BB%',
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'bb_minus_k':'BB%-K%',
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'csw':'CSW%',
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'woba':'wOBA',
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'launch_speed':'Exit Velocity',
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'launch_speed_90':'90th Percentile Exit Velocity',
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'hard_hit':'HardHit%',
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'sweet_spot':'SweetSpot%',
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'launch_angle':'Launch Angle',
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'zone_percent':'Zone%',
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'barrel':'Barrel%',
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'swing_percent':'Swing%',
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'whiff_percent':'Whiff%',
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'sw_str':'SwStr%',
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'zone_swing':'Z-Swing%',
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'zone_contact':'Z-Contact%',
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'chase_percent':'O-Swing%',
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'chase_contact':'O-Contact%',}
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plot_dict_small_pitch = {
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'k':'K%',
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'bb':'BB%',
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'bb_minus_k':'BB%-K%',
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'csw':'CSW%',
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'woba':'wOBA',
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'launch_speed':'Exit Velocity',
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'launch_speed_90':'90th Percentile Exit Velocity',
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'hard_hit':'HardHit%',
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'sweet_spot':'SweetSpot%',
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'launch_angle':'Launch Angle',
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'zone_percent':'Zone%',
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'barrel':'Barrel%',
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'swing_percent':'Swing%',
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'whiff_percent':'Whiff%',
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'sw_str':'SwStr%',
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'zone_swing':'Z-Swing%',
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'zone_contact':'Z-Contact%',
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'chase_percent':'O-Swing%',
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'chase_contact':'O-Contact%',}
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plot_dict_small_this_format = {
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'k_percent':'{:,.1%}',
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'bb_percent':'{:,.1%}',
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'chase_percent':'{0:+.1%}',
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'chase_contact':'{0:+.1%}',}
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plot_dict_small_this_format_sorted = {
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'k_percent':False,
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'bb_percent':True,
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'bb_minus_k_percent':True,
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'csw_percent':False,
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'woba_percent':True,
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'launch_speed':True,
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'launch_speed_90':True,
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'hard_hit_percent':True,
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'sweet_spot_percent':True,
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'launch_angle':True,
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'zone_percent':False,
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'barrel_percent':True,
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'swing_percent':True,
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'whiff_rate':False,
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'swstr_rate':False,
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'zone_swing_percent':False,
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'zone_contact_percent':True,
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'chase_percent':False,
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'chase_contact':True,}
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team_list = ['All'] + sorted(list(exit_velo_df_codes_summ_batter.parent_org_abb.unique()))
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sort_list = ['Season Stat','Timeframe Stat','Difference']
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team_list = ['All'] + sorted(list(exit_velo_df_codes_summ_batter.parent_org_abb.unique()))
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sort_list = ['Season Stat','Timeframe Stat','Difference']
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ui.input_select("level_id", "Select Level",level_dict,width=1,multiple=True,selected='MLB',selectize=True),
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ui.input_select("team_id", "Select Team",team_list,width=1,size=1,multiple=True,selected='All',selectize=True),
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ui.input_select("sort_id", "Sort By",sort_list,width=1,size=1,selected='Timeframe Stat'),
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ui.input_numeric("n", "Minimum PA", value=50),
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ui.input_numeric("n_top", "Show top 'n'", value=0),
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ui.input_switch("sort_order", "Ascending?"),),
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ui.panel_main(ui.tags.h2("Batter Season Average vs Timeframe Average"),
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ui.tags.h6("Created By: @TJStats, Data: MLB"),
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ui.output_text("txt"),
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ui.output_table("result")),
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))
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print(plot_dict_small_all_input[input.stat_id()])
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exit_velo_df_codes_summ_time['Difference'] = exit_velo_df_codes_summ_time[input.stat_id()+'_time'] - exit_velo_df_codes_summ_time[input.stat_id()]
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# print(format_column)
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format_column = plot_dict_small_this_format[input.stat_id()]
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format_column_diff = plot_dict_small_this_format_diff[input.stat_id()]
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print('Difference',format_column)
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if input.sort_id() == 'Difference':
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# })
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# exit_velo_df_codes_summ_time[plot_dict_small_this_one[input.stat_id()]] = exit_velo_df_codes_summ_time[plot_dict_small_this_one[input.stat_id()]].map(format_column.format)
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# exit_velo_df_codes_summ_time[plot_dict_small_this_one[input.stat_id()]+' Since'] = exit_velo_df_codes_summ_time[plot_dict_small_this_one[input.stat_id()]+' Since'].map(format_column.format)
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# exit_velo_df_codes_summ_time['Difference'] = exit_velo_df_codes_summ_time['Difference'].map(format_column_diff.format)
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exit_velo_df_codes_summ_time_style_setting = exit_velo_df_codes_summ_time[['Rank','Batter ID','Batter','Team','Level','PA',plot_dict_small_this_one[input.stat_id()],
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'PA Since',plot_dict_small_this_one[input.stat_id()]+' Since',
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'Difference']]
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df_min_max = exit_velo_df_codes_summ_time_style_setting.copy()
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1124 |
+
if int(input.n_top()) > 0:
|
1125 |
+
exit_velo_df_codes_summ_time_style_setting = exit_velo_df_codes_summ_time_style_setting.head(int(input.n_top()))
|
1126 |
+
|
1127 |
+
# exit_velo_df_codes_summ_time_style = exit_velo_df_codes_summ_time[['Rank','Pitcher ID','Pitcher','Team','Level','PA',plot_dict_small_this_one[input.stat_id()],
|
1128 |
+
# 'PA Since',plot_dict_small_this_one[input.stat_id()]+' Since',
|
1129 |
+
# 'Difference']]
|
1130 |
+
|
1131 |
+
#exit_velo_df_codes_summ_time_style = exit_velo_df_codes_summ_time.copy()
|
1132 |
+
|
1133 |
+
exit_velo_df_codes_summ_time_style_set = exit_velo_df_codes_summ_time_style_setting.style.set_properties(**{'border': '1 px'},overwrite=False).set_table_styles([{
|
1134 |
+
'selector': 'caption',
|
1135 |
+
'props': [
|
1136 |
+
('color', ''),
|
1137 |
+
('fontname', 'Century Gothic'),
|
1138 |
+
('font-size', '16px'),
|
1139 |
+
('font-style', 'italic'),
|
1140 |
+
('font-weight', ''),
|
1141 |
+
('text-align', 'centre'),
|
1142 |
+
]
|
1143 |
+
|
1144 |
+
},{'selector' :'th', 'props':[('text-align', 'center'),('Height','24px'),('border', '1 px black solid !important')]},{'selector' :'td', 'props':[('text-align', 'center'),('font-size', '16px')]}],overwrite=False).set_table_styles(
|
1145 |
+
[{'selector': 'tr', 'props': [('line-height', '1px')]}],overwrite=False).set_properties(
|
1146 |
+
**{'Height': '28px'},**{'text-align': 'center'},overwrite=False).hide_index().format(
|
1147 |
+
{
|
1148 |
+
plot_dict_small_this_one[input.stat_id()]: format_column,
|
1149 |
+
plot_dict_small_this_one[input.stat_id()]+' Since': format_column,
|
1150 |
+
"Difference":format_column_diff,
|
1151 |
+
})
|
1152 |
+
|
1153 |
+
if plot_dict_small_this_format_sorted[input.stat_id()]:
|
1154 |
+
cmap_sum = matplotlib.colors.LinearSegmentedColormap.from_list("", ["#4285f4","#FFFFFF","#F0E442"])
|
1155 |
+
|
1156 |
+
else:
|
1157 |
+
cmap_sum = matplotlib.colors.LinearSegmentedColormap.from_list("", ["#F0E442","#FFFFFF","#4285f4"])
|
1158 |
+
|
1159 |
+
|
1160 |
+
exit_velo_df_codes_summ_time_style_set = exit_velo_df_codes_summ_time_style_set.background_gradient(cmap=cmap_sum,subset = ((list(exit_velo_df_codes_summ_time_style_set.index[:]),exit_velo_df_codes_summ_time_style_set.columns[-1])),vmin=df_min_max[df_min_max.columns[-1]].min(),vmax=df_min_max[df_min_max.columns[-1]].max())
|
1161 |
+
exit_velo_df_codes_summ_time_style_set = exit_velo_df_codes_summ_time_style_set.background_gradient(cmap=cmap_sum,subset = ((list(exit_velo_df_codes_summ_time_style_set.index[:]),exit_velo_df_codes_summ_time_style_set.columns[-2])),vmin=df_min_max[df_min_max.columns[-2]].min(),vmax=df_min_max[df_min_max.columns[-2]].max())
|
1162 |
+
exit_velo_df_codes_summ_time_style_set = exit_velo_df_codes_summ_time_style_set.background_gradient(cmap=cmap_sum,subset = ((list(exit_velo_df_codes_summ_time_style_set.index[:]),exit_velo_df_codes_summ_time_style_set.columns[-4])),vmin=df_min_max[df_min_max.columns[-4]].min(),vmax=df_min_max[df_min_max.columns[-4]].max())
|
1163 |
+
|
1164 |
+
exit_velo_df_codes_summ_time_style_set = exit_velo_df_codes_summ_time_style_set.set_properties(
|
1165 |
+
**{'border': '1px black solid !important'},subset = ((list(exit_velo_df_codes_summ_time_style_set.index[:-1]),exit_velo_df_codes_summ_time_style_set.columns[:]))).set_properties(
|
1166 |
+
#**{'font-weight': 'bold'},subset = ((list(exit_velo_df_codes_summ_time_style.index[:]),exit_velo_df_codes_summ_time_style.columns[:4]))).set_properties(
|
1167 |
+
**{'min-width':'100px'},subset = ((list(exit_velo_df_codes_summ_time_style_set.index[:-1]),exit_velo_df_codes_summ_time_style_set.columns[1])),overwrite=False).set_properties(
|
1168 |
+
**{'min-width':'150px'},subset = ((list(exit_velo_df_codes_summ_time_style_set.index[:-1]),exit_velo_df_codes_summ_time_style_set.columns[2])),overwrite=False).set_properties(
|
1169 |
+
**{'min-width':'85px'},subset = ((list(exit_velo_df_codes_summ_time_style_set.index[:-1]),exit_velo_df_codes_summ_time_style_set.columns[3:])),overwrite=False).set_properties(
|
1170 |
+
**{'border': '1px black solid !important'},subset = ((list(exit_velo_df_codes_summ_time_style_set.index[:]),exit_velo_df_codes_summ_time_style_set.columns[:])))
|
1171 |
+
|
1172 |
+
|
1173 |
+
|
1174 |
+
return exit_velo_df_codes_summ_time_style_set
|
1175 |
+
|
1176 |
# @output
|
1177 |
# @render.plot(alt="A histogram")
|
1178 |
# def plot_pitch():
|