TJStatsApps/2025_decision_value
0
1from shiny import App, Inputs, Outputs, Session, reactive, render, req, ui2import datasets3from datasets import load_dataset4import pandas as pd5import numpy as np6import matplotlib.pyplot as plt7import seaborn as sns8import numpy as np9from scipy.stats import gaussian_kde10import matplotlib11from matplotlib.ticker import MaxNLocator12from matplotlib.gridspec import GridSpec13from scipy.stats import zscore14import math15import matplotlib16from adjustText import adjust_text17import matplotlib.ticker as mtick18from shinywidgets import output_widget, render_widget19import pandas as pd20from configure import base_url21import shinyswatch22import inflect23from matplotlib.pyplot import text24 25 26exit_velo_df_codes_summ = pd.read_csv('summary_pitcher.csv',index_col=[0]).reset_index(drop=True)27exit_velo_df_codes_summ_non_level = pd.read_csv('summary_pitcher_level.csv',index_col=[0]).reset_index(drop=True)28 29exit_velo_df_codes_summ_non_level['levels'] = exit_velo_df_codes_summ_non_level.levels.str.split(', ')30 31exit_velo_df_codes_summ_non_level = exit_velo_df_codes_summ_non_level.rename(columns={'levels':'level'})32 33print(exit_velo_df_codes_summ.bb_minus_k_percent)34exit_velo_df_codes_summ.bb_minus_k_percent = -1*exit_velo_df_codes_summ.bb_minus_k_percent35exit_velo_df_codes_summ.bb_over_k_percent = exit_velo_df_codes_summ.k_percent/exit_velo_df_codes_summ.bb_percent36 37exit_velo_df_codes_summ_non_level.bb_minus_k_percent = -1*exit_velo_df_codes_summ_non_level.bb_minus_k_percent38exit_velo_df_codes_summ_non_level.bb_over_k_percent = exit_velo_df_codes_summ_non_level.k_percent/exit_velo_df_codes_summ_non_level.bb_percent39 40pitcher_dict_stat = { 'sweet_spot_percent':{'x_axis':'SweetSpot%','title':'SweetSpot%','flip_p':False,'decimal_format':'percent_1','percent_adjust':100},41 'max_launch_speed':{'x_axis':'Max Exit Velocity','title':'Max Exit Velocity','flip_p':False,'decimal_format':'string_0','percent_adjust':1},42 'launch_speed_90':{'x_axis':'90th Percentile EV','title':'90th Percentile EV','flip_p':False,'decimal_format':'string_0','percent_adjust':1},43 'launch_speed':{'x_axis':'Exit Velocity','title':'Exit Velocity','flip_p':False,'decimal_format':'string_0','percent_adjust':1},44 'launch_angle':{'x_axis':'Launch Angle','title':'Launch Angle','flip_p':False,'decimal_format':'string_0','percent_adjust':100},45 'avg':{'x_axis':'AVG','title':'AVG','flip_p':False,'decimal_format':'string_3','percent_adjust':100},46 'obp':{'x_axis':'OBP','title':'OBP','flip_p':False,'decimal_format':'string_3','percent_adjust':100},47 'slg':{'x_axis':'SLG','title':'SLG','flip_p':False,'decimal_format':'string_3','percent_adjust':100},48 'ops':{'x_axis':'OPS','title':'OPS','flip_p':False,'decimal_format':'string_3','percent_adjust':100},49 'k_percent':{'x_axis':'K%','title':'K%','flip_p':True,'decimal_format':'percent_1','percent_adjust':100},50 'bb_percent':{'x_axis':'BB%','title':'BB%','flip_p':False,'decimal_format':'percent_1','percent_adjust':100},51 'bb_over_k_percent':{'x_axis':'K/BB','title':'K/BB','flip_p':True,'decimal_format':'string_1','percent_adjust':100},52 'bb_minus_k_percent':{'x_axis':'K%-BB%','title':'K%-BB%','flip_p':True,'decimal_format':'percent_1','percent_adjust':100},53 'csw_percent':{'x_axis':'CSW%','title':'CSW%','flip_p':True,'decimal_format':'percent_1','percent_adjust':100},54 'woba_percent':{'x_axis':'wOBA','title':'wOBA','flip_p':False,'decimal_format':'string_3','percent_adjust':100},55 'hard_hit_percent':{'x_axis':'HardHit%','title':'HardHit%','flip_p':False,'decimal_format':'percent_1','percent_adjust':100},56 'barrel_percent':{'x_axis':'Barrel%','title':'Barrel%','flip_p':False,'decimal_format':'percent_1','percent_adjust':100},57 'zone_contact_percent':{'x_axis':'Z-Contact%','title':'Z-Contact%','flip_p':False,'decimal_format':'percent_1','percent_adjust':100},58 'zone_swing_percent':{'x_axis':'Z-Swing%','title':'Z-Swing%','flip_p':False,'decimal_format':'percent_1','percent_adjust':100},59 'zone_percent':{'x_axis':'Zone%','title':'Zone%','flip_p':False,'decimal_format':'percent_1','percent_adjust':100},60 'chase_percent':{'x_axis':'O-Swing%','title':'O-Swing%','flip_p':True,'decimal_format':'percent_1','percent_adjust':100},61 'chase_contact':{'x_axis':'O-Contact%','title':'O-Contact%','flip_p':True,'decimal_format':'percent_1','percent_adjust':100},62 'swing_percent':{'x_axis':'Swing%','title':'Swing%','flip_p':False,'decimal_format':'percent_1','percent_adjust':100},63 'whiff_rate':{'x_axis':'Whiff%','title':'Whiff%','flip_p':True,'decimal_format':'percent_1','percent_adjust':100},64 'swstr_rate':{'x_axis':'SwStr%','title':'SwStr%','flip_p':True,'decimal_format':'percent_1','percent_adjust':100},65 }66 67pitcher_dict_stat_small = { 'sweet_spot_percent':'SweetSpot%',68 'max_launch_speed':'Max Exit Velocity',69 'launch_speed_90':'90th Percentile EV',70 'launch_speed':'Exit Velocity',71 'launch_angle':'Launch Angle',72 'avg':'AVG',73 'obp':'OBP',74 'slg':'SLG',75 'ops':'OPS',76 'k_percent':'K%',77 'bb_percent':'BB%',78 'bb_over_k_percent':'K/BB',79 'bb_minus_k_percent':'K%-BB%',80 'csw_percent':'CSW%',81 'woba_percent':'wOBA',82 'hard_hit_percent':'HardHit%',83 'barrel_percent':'Barrel%',84 'zone_contact_percent':'Z-Contact%',85 'zone_swing_percent':'Z-Swing%',86 'zone_percent':'Zone%',87 'chase_percent':'O-Swing%',88 'chase_contact':'O-Contact%',89 'swing_percent':'Swing%',90 'whiff_rate':'Whiff%',91 'swstr_rate':'SwStr%',92 }93 94 95colour_palette = ['#FFB000','#648FFF','#785EF0',96 '#DC267F','#FE6100','#3D1EB2','#894D80','#16AA02','#B5592B','#A3C1ED']97 98level_dict = {'MLB':'MLB','AAA':'AAA','AA':'AA','A+':'A+','A':'A','ROK':'ROK'}99 100batter_test_df = exit_velo_df_codes_summ.sort_values(by='pitcher').drop_duplicates(subset='pitcher_id').reset_index(drop=True)[['pitcher_id','pitcher']]#['pitcher'].to_dict()101batter_test_df = batter_test_df.set_index('pitcher_id')102 103 104def decimal_format_assign(x):105 if x['decimal_format'] == 'percent_1':106 return mtick.PercentFormatter(1,decimals=1)107 if x['decimal_format'] == 'string_3':108 return mtick.FormatStrFormatter('%.3f')109 if x['decimal_format'] == 'string_0':110 return mtick.FormatStrFormatter('%.0f')111 if x['decimal_format'] == 'string_1':112 return mtick.FormatStrFormatter('%.1f')113 114 115#test_df = test_df[test_df.pitcher == 'Chris Bassitt'].append(test_df[test_df.pitcher != 'Chris Bassitt'])116 117pitcher_dict = batter_test_df['pitcher'].to_dict()118 119exit_velo_df_codes_summ.position = exit_velo_df_codes_summ.position.replace(['TWP'],['P'])120 121exit_velo_df_codes_summ_non_level.position = exit_velo_df_codes_summ_non_level.position.replace(['TWP'],['P'])122 123 124position_list = ['All'] + list(exit_velo_df_codes_summ.position.unique())125team_list = ['All'] + sorted(list(exit_velo_df_codes_summ.parent_org_abb.unique()))126 127 128 129def server(input,output,session):130 131 132 @output133 @render.plot(alt="A histogram")134 @reactive.event(input.go, ignore_none=False)135 def plot():136 sns.set_theme(style="whitegrid", palette="pastel")137 138 139 print(input.level_id())140 print(input.n())141 print('we made it here')142 143 #data_df = exit_velo_df_codes_summ.copy()144 145 146 if input.group_level():147 data_df = exit_velo_df_codes_summ_non_level.copy()148 149 turth_list = []150 #turth_list_2 = []151 for x in range(0,len(data_df.level)):152 turth_list_2 = []153 for y in range(0,len(data_df.level[x])):154 #print(level_list[x][y])155 turth_list_2.append(data_df.level[x][y] in input.level_id())156 turth_list.append(turth_list_2)157 158 final_check_list = [True if True in x else False for x in turth_list]159 160 161 data_df = data_df[(data_df.pa >= input.n())&(data_df.age <= input.n_age())&(final_check_list)]162 163 else:164 data_df = exit_velo_df_codes_summ.copy()165 166 data_df = data_df[(data_df.pa >= input.n())&(data_df.age <= input.n_age())&(data_df.level.isin(input.level_id()))]167 print(data_df)168 if 'All' in input.team_id():169 print('nice')#data_df = data_df[(data_df.pa >= input.n())&(data_df.age <= input.n_age())].reset_index(drop=True)170 171 else:172 data_df = data_df[(data_df.parent_org_abb.isin(input.team_id()))].reset_index(drop=True)173 174 if 'All' in input.position_id():175 print('nice')#data_df = data_df[(data_df.level.isin(input.level_id()))&(data_df.pa >= input.n())&(data_df.age <= input.n_age())].reset_index(drop=True)176 177 else:178 data_df = data_df[(data_df.position.isin(input.position_id()))].reset_index(drop=True)179 180 181 182 183 184 185 data_df = data_df.sort_values(by='level').reset_index(drop=True)186 print(pitcher_dict_stat[input.stat_x()]['flip_p'])187 188 189 190 x_flip = pitcher_dict_stat[input.stat_x()]['flip_p']191 y_flip = pitcher_dict_stat[input.stat_y()]['flip_p']192 cbr_flip = pitcher_dict_stat[input.stat_z()]['flip_p']193 194 195 196 data_df[input.stat_x()+'_percent'] = data_df[input.stat_x()].rank(pct=True,ascending=abs(x_flip-1))197 198 data_df[input.stat_y()+'_percent'] = data_df[input.stat_y()].rank(pct=True,ascending=abs(y_flip-1))199 200 data_df[input.stat_z()+'_percent'] = data_df[input.stat_z()].rank(pct=True,ascending=abs(cbr_flip-1))201 202 203 204 fig, ax = plt.subplots(1, 1, figsize=(9, 9))205 206 #data_df['bb_over_obp'] = data_df['bb']/data_df['k']207 208 #data_df[input.stat_z()]= data_df[input.stat_z()].fillna(-100000)209 210 211 if not cbr_flip:212 cmap_hue = matplotlib.colors.LinearSegmentedColormap.from_list("", [colour_palette[0],colour_palette[3],colour_palette[1]])213 norm = plt.Normalize(data_df[input.stat_z()].min(), data_df[input.stat_z()].max())214 215 else:216 cmap_hue = matplotlib.colors.LinearSegmentedColormap.from_list("", [colour_palette[1],colour_palette[3],colour_palette[0]])217 norm = plt.Normalize(data_df[input.stat_z()].min(), data_df[input.stat_z()].max())218 219 sm = plt.cm.ScalarMappable(cmap=cmap_hue, norm=norm)220 print('we made it here')221 222 # sns.regplot(x = stat_x, y = stat_y, data=data_df, color = colour_palette[6],ax=ax,scatter=False,223 # line_kws=dict(alpha=0.3,linewidth=2,zorder=1))224 # scatter_plot = sns.scatterplot(x = stat_x, y = stat_y, data=data_df, color = colour_palette[0],ax=ax,hue=stat_z,palette=cmap_hue)225 226 227 228 # r, p = sp.stats.pearsonr(data_df[input.stat_x()], data_df[input.stat_y()])229 # ax = plt.gca()230 # # ax.text(.25, 0.3, 'r={:.2f}, p={:.2g}'.format(r, p),231 # # transform=ax.transAxes, fontsize=12)232 233 # ax.annotate('R²={:.2f}'.format(r, p), ( math.ceil(data_df[input.stat_x()].max()*pitcher_dict_stat[input.stat_x()]['percent_adjust']/5)*5/pitcher_dict_stat[input.stat_x()]['percent_adjust']*(1-pitcher_dict_stat[input.stat_x()]['flip_p']), 234 # math.floor(data_df[input.stat_y()].min()*pitcher_dict_stat[input.stat_y()]['percent_adjust']/5)*5/pitcher_dict_stat[input.stat_y()]['percent_adjust']*(1-pitcher_dict_stat[input.stat_y()]['flip_p'])), 235 # fontsize=18,fontname='Century Gothic',ha='right')236 237 if input.group_level():238 scatter = sns.scatterplot(x = input.stat_x(), y = input.stat_y(), data=data_df, color = '#b3b3b3')239 #ax.get_legend().remove()240 scatter = sns.scatterplot(x = input.stat_x(), y = input.stat_y(), data=data_df, color = colour_palette[0],ax=ax,hue=input.stat_z(),palette=cmap_hue)241 else:242 scatter = sns.scatterplot(x = input.stat_x(), y = input.stat_y(), data=data_df, color = '#b3b3b3',style='level') 243 #ax.get_legend().remove()244 scatter = sns.scatterplot(x = input.stat_x(), y = input.stat_y(), data=data_df, color = colour_palette[0],ax=ax,hue=input.stat_z(),palette=cmap_hue,style='level')245 246 247 sns.set_theme(style="whitegrid", palette="pastel")248 249 fig.set_facecolor('#F0F0F0')250 ax.set_facecolor('white')251 252 print('we made it here!')253 # for i in range(0,len(pitch_group_unique)):254 # data_df = elly_zone_df[elly_zone_df.pitch_group==pitch_group_unique[i]]255 # len_df.append(len(data_df))256 # sns.lineplot(x=range(1,len(data_df)+1),y=data_df.swings.rolling(window=rolling_window_input).sum()/data_df.pitches.rolling(window=rolling_window_input).sum(),color=colour_palette[i],linewidth=3,ax=ax,257 # label=f'{pitch_group_unique[i]} (Season Average {float(data_df.swings.sum()/data_df.pitches.sum()):.1%})',zorder=i+10)258 # ax.hlines(xmin=0,xmax=len(elly_zone_df),y=data_df.swings.sum()/data_df.pitches.sum(),color=colour_palette[i],linewidth=3,linestyle='-.',alpha=0.4,zorder=i)259 260 ts=[]261 xs=[]262 ys=[]263 labels=[]264 265 print(input.player_id())266 if input.names():267 for i in range(len(data_df)):268 if (data_df[input.stat_x()+'_percent'][i] < input.n_percent_bot_x() or data_df[input.stat_x()+'_percent'][i] > 1 - input.n_percent_top_x() ) \269 or (data_df[input.stat_y()+'_percent'][i] < input.n_percent_bot_y() or data_df[input.stat_y()+'_percent'][i] > 1 -input.n_percent_top_y()) \270 or (data_df[input.stat_z()+'_percent'][i] < input.n_percent_bot_z() or data_df[input.stat_z()+'_percent'][i] > 1 -input.n_percent_top_z() )\271 or (str(data_df.pitcher_id[i]) in (input.player_id())):272 ts.append(ax.text(data_df[input.stat_x()][i], data_df[input.stat_y()][i], data_df.pitcher[i],fontsize=8))273 274 275 # ax.annotate(data_df.pitcher[i], xy=((data_df[input.stat_x()][i])+0.025/pitcher_dict_stat[input.stat_x()]['percent_adjust'], data_df[input.stat_y()][i]+0.01/pitcher_dict_stat[input.stat_x()]['percent_adjust']), xytext=(-20,20), 276 # textcoords='offset points', ha='center', va='bottom',fontsize=7,277 # bbox=dict(boxstyle='round,pad=0', fc=colour_palette[6], alpha=0.0),278 # arrowprops=dict(arrowstyle='->', connectionstyle="angle,angleA=-90,angleB=-10,rad=5", 279 # color=colour_palette[4]))280 281 # print('CONDITION CHEK')282 # print(data_df[input.stat_x()][i])283 # #if data_df['pitcher'][i] != 'Jo Adell':284 # #ax.annotate(data_df.pitcher[i], ((data_df[input.stat_x()][i])+0.025/pitcher_dict_stat[input.stat_x()]['percent_adjust'], data_df[input.stat_y()][i]+0.01/pitcher_dict_stat[input.stat_x()]['percent_adjust']),fontsize=8)285 # #ts.append(data_df[input.stat_x()][i], data_df[input.stat_y()][i], data_df.pitcher[i],fontsize=8))286 # xs.append(data_df[input.stat_x()][i])287 # ys.append(data_df[input.stat_y()][i])288 # labels.append(data_df.pitcher[i])289 290 # # adjust_text(ts, force_points=0.2, force_text=0.2,291 # # expand_points=(1, 1), expand_text=(1, 1),292 # # arrowprops=dict(arrowstyle="-", color='black', lw=0))293 # #print(xs)294 # if len(xs)>0: 295 # repel_labels(ax=ax, x = xs,y = ys, labels = labels, k=0.0025)296 297 ax.hlines(xmin=math.floor((data_df[input.stat_x()].min()*pitcher_dict_stat[input.stat_x()]['percent_adjust']-0.01)/5)*5/pitcher_dict_stat[input.stat_x()]['percent_adjust'],298 xmax= math.ceil((data_df[input.stat_x()].max()*pitcher_dict_stat[input.stat_x()]['percent_adjust']+0.01)/5)*5/pitcher_dict_stat[input.stat_x()]['percent_adjust'],299 y=data_df[input.stat_y()].mean(),color='gray',linewidth=3,linestyle='dotted',alpha=0.4)300 301 print('we made it here')302 ax.vlines(ymin=(math.floor(data_df[input.stat_y()].min()*pitcher_dict_stat[input.stat_y()]['percent_adjust']-0.01)/5)*5/pitcher_dict_stat[input.stat_y()]['percent_adjust'],303 ymax= (math.ceil(data_df[input.stat_y()].max()*pitcher_dict_stat[input.stat_y()]['percent_adjust']+0.01)/5)*5/pitcher_dict_stat[input.stat_y()]['percent_adjust'],304 x=data_df[input.stat_x()].mean(),color='gray',linewidth=3,linestyle='dotted',alpha=0.4)305 306 ax.set_xlim((math.floor(data_df[input.stat_x()].min()*pitcher_dict_stat[input.stat_x()]['percent_adjust']-0.01)/5)*5/pitcher_dict_stat[input.stat_x()]['percent_adjust'],307 (math.ceil(data_df[input.stat_x()].max()*pitcher_dict_stat[input.stat_x()]['percent_adjust']+0.01)/5)*5/pitcher_dict_stat[input.stat_x()]['percent_adjust'])308 309 ax.set_ylim((math.floor(data_df[input.stat_y()].min()*pitcher_dict_stat[input.stat_y()]['percent_adjust']-0.01)/5)*5/pitcher_dict_stat[input.stat_y()]['percent_adjust'],310 (math.ceil(data_df[input.stat_y()].max()*pitcher_dict_stat[input.stat_y()]['percent_adjust']+0.01)/5)*5/pitcher_dict_stat[input.stat_y()]['percent_adjust'])311 312 title_level = str([x .strip("\'")for x in input.level_id()]).strip('[').strip(']').replace("'",'')313 314 if title_level == 'AAA, AA, A+, A':315 title_level='MiLB'316 317 318 if input.n_age() >= 50:319 title_spot = f'{title_level} Pitcher {pitcher_dict_stat[input.stat_y()]["title"]} vs {pitcher_dict_stat[input.stat_x()]["title"]} (min. {input.n()} PA)'320 321 else:322 title_spot = f'{title_level} Pitcher {pitcher_dict_stat[input.stat_y()]["title"]} vs {pitcher_dict_stat[input.stat_x()]["title"]} (min. {input.n()} PA, Max Age {input.n_age()})'323 324 #title_level = input.level_id()[0]325 #title_spot = f'{title_level} pitcher {pitcher_dict_stat[input.stat_y()]["title"]} vs {pitcher_dict_stat[input.stat_x()]["title"]} (min. {input.n()} PA)'326 327 ax.set_title(title_spot, fontsize=24/(len(title_spot)*0.03),fontname='Century Gothic')328 # #vals = ax.get_yticks()329 ax.set_xlabel(pitcher_dict_stat[input.stat_x()]['x_axis'], fontsize=16,fontname='Century Gothic')330 ax.set_ylabel(pitcher_dict_stat[input.stat_y()]['x_axis'], fontsize=16,fontname='Century Gothic')331 332 333 if input.group_level():334 ax.get_legend().remove()335 336 if not input.group_level():337 if len(input.level_id()) > 1:338 h,l = scatter.get_legend_handles_labels()339 l[-(len(input.level_id())+1)] = 'Level'340 ax.legend(h[-(len(input.level_id())+1):],l[-(len(input.level_id())+1):], borderaxespad=0.1,loc=0)341 342 else:343 ax.get_legend().remove()344 345 346 347 #plt.show(g)348 # ax.figure.colorbar(sm, ax=ax)349 350 cbar = ax.figure.colorbar(sm, ax=ax,format=decimal_format_assign(x=pitcher_dict_stat[input.stat_z()]),orientation='vertical',aspect=30)351 cbar.set_label(pitcher_dict_stat[input.stat_z()]['x_axis'])352 #fig.axes[0].invert_yaxis()353 print('we made it here5')354 fig.subplots_adjust(wspace=.02, hspace=.02)355 # ax.xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))356 #ax.set_yticks([0,0.1,0.2,0.3,0.4,0.5])357 # fig.colorbar(plot_dist, ax=ax)358 # fig.colorbar(plot_dist)359 360 if not pitcher_dict_stat[input.stat_x()]['flip_p']:361 fig.axes[0].invert_xaxis()362 363 if not pitcher_dict_stat[input.stat_y()]['flip_p']:364 fig.axes[0].invert_yaxis()365 366 367 # ax.xaxis.set_major_formatter(mtick.PercentFormatter(1,decimals=0))368 # ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))369 370 371 372 373 374 print('we made it here6')375 376 ax.xaxis.set_major_formatter(decimal_format_assign(x=pitcher_dict_stat[input.stat_x()]))377 ax.yaxis.set_major_formatter(decimal_format_assign(x=pitcher_dict_stat[input.stat_y()]))378 379 380 print('we made it here7')381 # ax.text(0.5, 0.5, '/u/tomstoms', transform=ax.transAxes,382 # fontsize=60, color='gray', alpha=0.075,383 # ha='center', va='center', rotation=45)384 adjust_text(ts,385 arrowprops=dict(arrowstyle="-", color=colour_palette[4], lw=1),ax=ax)386 387 #ax.legend(fontsize='16')388 fig.text(x=0.03,y=0.02,s='By: @TJStats',fontname='Century Gothic')389 fig.text(x=1-0.03,y=0.02,s='Data: MLB',ha='right',fontname='Century Gothic')390 fig.tight_layout()391 392 393pitcher_scatter = App(ui.page_fluid(394 ui.tags.base(href=base_url), 395 ui.tags.div(396 {"style": "width:90%;margin: 0 auto;max-width: 1600px;"},397 ui.tags.style(398 """399 h4 {400 margin-top: 1em;font-size:35px;401 }402 h2{403 font-size:25px;404 }405 """406 ),407 shinyswatch.theme.simplex(),408 ui.tags.h4("TJStats"),409 ui.tags.i("Baseball Analytics and Visualizations"),410 ui.markdown("""<a href='https://www.patreon.com/tj_stats'>Support me on Patreon for Access to 2024 Apps</a><sup>1</sup>"""),411 ui.navset_tab(412 ui.nav_control(413 ui.a(414 "Home",415 href="home/"416 ),417 ),418 ui.nav_menu(419 "Batter Charts",420 ui.nav_control(421 ui.a(422 "Batting Rolling",423 href="rolling_batter/"424 ),425 ui.a(426 "Spray & Damage",427 href="spray/"428 ),429 ui.a(430 "Decision Value",431 href="decision_value/"432 ),433 # ui.a(434 # "Damage Model",435 # href="damage_model/"436 # ),437 ui.a(438 "Batter Scatter",439 href="batter_scatter/"440 ),441 # ui.a(442 # "EV vs LA Plot",443 # href="ev_angle/"444 # ),445 ui.a(446 "Statcast Compare",447 href="statcast_compare/"448 )449 ),450 ),451 ui.nav_menu(452 "Pitcher Charts",453 ui.nav_control(454 ui.a(455 "Pitcher Rolling",456 href="rolling_pitcher/"457 ),458 ui.a(459 "Pitcher Summary",460 href="pitching_summary_graphic_new/"461 ),462 ui.a(463 "Pitcher Scatter",464 href="pitcher_scatter/"465 )466 ),467 )),ui.row(468 ui.layout_sidebar(469 470 471 472 ui.panel_sidebar(473 #ui.input_select("id", "Select Batter",batter_dict,selected=675911,width=1,size=1),474 ui.row(475 ui.column(4,ui.input_select("level_id", "Select Level",level_dict,width=1,size=1,multiple=True,selected='MLB',selectize=True),),476 ui.column(4,ui.input_select("team_id", "Select Team",team_list,width=1,size=1,multiple=True,selected='All',selectize=True),),477 ui.column(4,ui.input_select("position_id", "Select Position",position_list,width=1,size=1,selected='All',multiple=True,selectize=True))),478 ui.row(479 ui.column(6,ui.input_numeric("n", "Minimum PA", value=100)),480 ui.column(6,ui.input_numeric("n_age", "Maximum Age", value=50))),481 ui.row(482 ui.column(4,ui.input_select("stat_x", "X-Axis",pitcher_dict_stat_small,selected='k_percent',width=1,size=1)),483 ui.column(4,ui.input_select("stat_y", "Y-Axis",pitcher_dict_stat_small,selected='bb_percent',width=1,size=1)),484 ui.column(4,ui.input_select("stat_z", "Colour-Bar Axis",pitcher_dict_stat_small,selected='bb_minus_k_percent',width=1,size=1))),485 486 ui.row(487 ui.column(6,ui.input_numeric("n_percent_top_x", "Top 'n' Percentile X-Labels", value=0.01)),488 ui.column(6,ui.input_numeric("n_percent_bot_x", "Bottom 'n' Percentile X-Labels", value=0.01))),489 ui.row(490 ui.column(6,ui.input_numeric("n_percent_top_y", "Top 'n' Percentile Y-Labels", value=0.01)),491 ui.column(6,ui.input_numeric("n_percent_bot_y", "Bottom 'n' Percentile Y-Labels", value=0.01))),492 ui.row(493 ui.column(6,ui.input_numeric("n_percent_top_z", "Top 'n' Percentile Z-Labels", value=0.01)),494 ui.column(6,ui.input_numeric("n_percent_bot_z", "Bottom 'n' Percentile Z-Labels", value=0.01))),495 496 ui.input_select("player_id", "Label Player",pitcher_dict,width=1,size=1,multiple=True,selectize=True),497 ui.row(498 ui.input_switch("names", "Toggle Names"),499 ui.input_switch("group_level", "Group Levels")),500 ui.input_action_button("go", "Generate",class_="btn-primary"),501 ),502 503 504 ui.panel_main(505 ui.output_plot("plot",height = "1000px",width="1000px")506 ,507 ),508 )),)),server)