-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathipl2020.py
510 lines (377 loc) · 25.3 KB
/
ipl2020.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
# -----------------------------------------------------------
# (C) Dheeraj Chaudhary
# -----------------------------------------------------------
import streamlit as st
import pandas as pd
import numpy as np
from sodapy import Socrata
import pydeck as pdk
import plotly.express as px
import requests
# from IPython.display import Image
with open("style.css") as f:
st.markdown('<style>{}</style>'.format(f.read()), unsafe_allow_html=True)
@st.cache(persist=True)
def giphy_path():
path = "https://media.giphy.com/media/rS9tqucvXWwuY/giphy.gif"
return path
path = giphy_path()
points_table_data_url = 'https://www.iplt20.com/points-table/2020'
html = requests.get(points_table_data_url).content
df_list_points_table = pd.read_html(html)
df_points_table = df_list_points_table[-1]
# print(df)
# df = pd.DataFrame(df)
st.markdown("<h1 style='text-align: center; color: #9C021B;'><strong>🏏 <u>IPL 2020 Dashboard</u> 🏏</strong></h1>", unsafe_allow_html=True)
st.markdown("_________________________________________________________________________________")
# st.markdown("<h4 style='text-align: center; color: #9C021B;'><hr></h4>", unsafe_allow_html=True)
st.markdown("<h4 style='text-align: center; color: #E07811;'>You can check latest Status of IPL 2020 along with stats of top Players</h4>", unsafe_allow_html=True)
# st.markdown("You can check latest Status of **IPL 2020** along with stats of top Players 🏏")
st.markdown(" ")
# st.markdown(" ")
@st.cache(persist=True)
def load_data_point_table():
data = pd.DataFrame(df_points_table)
data.rename(columns={'Unnamed: 0': 'Position', 'Pld': 'Match Played', 'Pts': 'Points', 'Form':'Status of Past Matches'}, inplace=True)
data = data.replace(np.nan, 'Not Played yet')
return data
data_point_table = load_data_point_table()
# st.header("Points Table of IPL 2020")
st.markdown("<h2 style='text-align: center; color: blue;'><strong><u>Points Table of IPL 2020</u></strong></h2>", unsafe_allow_html=True)
st.write(data_point_table)
st.markdown("_________________________________________________________________________________")
# Batting & Bowling stats of all team
batting_stats_data_url = 'https://www.iplt20.com/stats/2020/most-runs'
# most_run_data_url = 'https://www.iplt20.com/stats/2020/most-runs'
html = requests.get(batting_stats_data_url).content
df_list_batting_stat = pd.read_html(html)
df_batting_stat = df_list_batting_stat[-1]
# print(df)
# st.markdown(" ")
# st.markdown(" ")
# st.header("Check Top Performers of Ongoing IPL Season")
st.markdown("<h2 style='text-align: center; color: green;'><strong><u>Check Top Performers of Ongoing IPL Season</u></strong></h2>", unsafe_allow_html=True)
select_bat_bowl = st.selectbox('Which stats you want to check?', ['--Select--', 'Batting stats', 'Bowling stats'])
if select_bat_bowl == 'Batting stats':
@st.cache(persist=True)
def load_data_batting_table():
data = pd.DataFrame(df_batting_stat)
data.rename(columns={'POS':'Position.', 'PLAYER': 'Player', 'Mat': 'Matches','Inns': 'Innings', 'NO':'Not Outs','HS': 'Highest Score',
'Avg': 'Average', 'BF': 'Ball Faced', 'SR': 'Strike Rate' }, inplace=True)
# data = data.replace(np.nan, 'Not Played yet')
return data
data_batting_stats = load_data_batting_table()
if st.checkbox("Show Top 20 Batsman List (in terms of Total Runs Scored)", False):
# st.header("Batting Stats of top Players")
st.markdown("<h3 style='text-align: center; color: #4BC401;'><strong>Batting Stats of top Players</strong></h3>", unsafe_allow_html=True)
st.write(data_batting_stats.head(20))
st.markdown("_________________________________________________________________________________")
# st.subheader("Check Top 3 Best Batsman in Selective categories")
st.markdown("<h3 style='text-align: center; color: orangered;'><strong>Check Top 3 Best Batsman in Selective categories</strong></h3>", unsafe_allow_html=True)
select_category = st.selectbox('Choose the Performance category', ['--Select--', 'Top Run Scorer', 'Highest Strike Rate', 'Best Average'])
if select_category == 'Top Run Scorer':
df_bat_total_score = data_batting_stats.sort_values(by=['Runs'], ascending=False).head(3)
x = np.arange(1, 4)
df_bat_total_score['Position'] = x
data_batting_stats_new = df_bat_total_score[['Position', 'Player', 'Runs']].head(3)
fig = px.bar(data_batting_stats_new, x='Player', y='Runs',text='Runs', hover_data=['Position','Player', 'Runs'], color='Player')
fig.update_traces(texttemplate='%{text:.s}', textposition='inside')
fig.update_layout(uniformtext_minsize=12, uniformtext_mode='hide')
fig.update_layout(xaxis_title="Batsman",
yaxis_title="Total Runs Scored",
legend_title="Players",
font=dict(
family="Arial",
size=16,
color="RebeccaPurple"
))
fig.update_layout(title={'text': "Top 3 Most run scorer Batsman",
'y':0.95,
'x':0.43,
'xanchor': 'center',
'yanchor': 'top'})
st.write(fig)
st.markdown("_________________________________________________________________________________")
elif select_category == 'Highest Strike Rate':
df_bat_sr = data_batting_stats.sort_values(by=['Strike Rate'], ascending=False).head(3)
x = np.arange(1, 4)
df_bat_sr['Position'] = x
data_batting_stats_sr = df_bat_sr[['Position', 'Player', 'Strike Rate']].head(3)
fig2 = px.bar(data_batting_stats_sr, x='Player', y='Strike Rate',text='Strike Rate', hover_data=['Position','Player', 'Strike Rate'], color='Player')
fig2.update_traces(texttemplate='%{text:.4s}', textposition='inside')
fig2.update_layout(uniformtext_minsize=12, uniformtext_mode='hide')
fig2.update_layout(xaxis_title="Batsman",
yaxis_title="Strike Rate",
legend_title="Players",
font=dict(
family="Arial",
size=16,
color="RebeccaPurple"
))
fig2.update_layout(title={'text': "Top 3 Batsman with Highest Strike Rate)",
'y':0.95,
'x':0.43,
'xanchor': 'center',
'yanchor': 'top'})
st.write(fig2)
st.markdown("🤔💡 * **Batting Strike rate** is measure of runs per ball. It is calculated in **%** *")
st.markdown("_________________________________________________________________________________")
elif select_category == 'Best Average':
best_avg_data_url = 'https://www.iplt20.com/stats/2020/best-batting-average'
# most_run_data_url = 'https://www.iplt20.com/stats/2020/most-runs'
html = requests.get(best_avg_data_url).content
df_list_avg = pd.read_html(html)
df_batting_stat_best_avg = df_list_avg[-1]
@st.cache(persist=True)
def load_data_batting_table():
data = pd.DataFrame(df_batting_stat_best_avg)
data.rename(columns={'PLAYER':'Player', 'Avg': 'Average'}, inplace=True)
# data = data.replace(np.nan, 'Not Played yet')
return data
data_best_avg_stats = load_data_batting_table()
df_bat_bestavg = data_best_avg_stats.sort_values(by=['Average'], ascending=False).head(3)
x = np.arange(1, 4)
df_bat_bestavg['Position'] = x
data_batting_stats_bestavg = df_bat_bestavg[['Position', 'Player', 'Average']].head(3)
fig2 = px.bar(data_batting_stats_bestavg, x='Player', y='Average',text='Average', hover_data=['Position','Player', 'Average'], color='Player')
fig2.update_traces(texttemplate='%{text:.4s}', textposition='inside')
fig2.update_layout(uniformtext_minsize=12, uniformtext_mode='hide')
fig2.update_layout(xaxis_title="Batsman",
yaxis_title="Best Average",
legend_title="Players",
font=dict(
family="Arial",
size=16,
color="RebeccaPurple"
))
fig2.update_layout(title={'text': "Top 3 Batsman with Best Average",
'y':0.95,
'x':0.42,
'xanchor': 'center',
'yanchor': 'top'})
st.write(fig2)
st.markdown("🤔💡 * **Batting average** is the **total number of runs** a batsman have scored divided by the **number of times** they have been out*")
st.markdown("_________________________________________________________________________________")
##############################################################################################################################
##################### Bowling
bowling_stats_data_url = 'https://www.iplt20.com/stats/2020/most-wickets'
# most_run_data_url = 'https://www.iplt20.com/stats/2020/most-runs'
html = requests.get(bowling_stats_data_url).content
df_list_bowling_stat = pd.read_html(html)
df_bowling_stat = df_list_bowling_stat[-1]
if select_bat_bowl == 'Bowling stats':
@st.cache(persist=True)
def load_data_bowling_table():
data = pd.DataFrame(df_bowling_stat)
data.rename(columns={'POS':'Position.', 'PLAYER': 'Player', 'Mat': 'Matches','Inns': 'Innings', 'Ov':'Overs','Wkts': 'Wickets taken',
'BBI': 'Best Bowling in a Inns', 'Avg': 'Average', 'Econ': 'Economy Rate', 'SR': 'Strike Rate' }, inplace=True)
# data = data.replace(np.nan, 'Not Played yet')
return data
data_bowling_stats = load_data_bowling_table()
if st.checkbox("Show Top 20 Bowlers List (in terms of Total number of wickets taken)", False):
# st.header("Bowling Stats of top Players")
st.markdown("<h3 style='text-align: center; color: #4BC401;'><strong>Bowling Stats of top Players</strong></h3>", unsafe_allow_html=True)
st.write(data_bowling_stats.head(20))
st.markdown("_________________________________________________________________________________")
# st.subheader("Check Top 3 Best Bowlers in Selective categories")
st.markdown("<h3 style='text-align: center; color: purple;'><strong>Check Top 3 Best Bowlers in Selective categories</strong></h3>", unsafe_allow_html=True)
select_category = st.selectbox('Choose the Performance category', ['--Select--', 'Top Wicket Taker', 'Best Economy Rate', 'Best Bowling Average'])
######################################### !st category
if select_category == 'Top Wicket Taker':
df_bowl_top_wicket = data_bowling_stats.sort_values(by=['Wickets taken'], ascending=False).head(3)
x = np.arange(1, 4)
df_bowl_top_wicket['Position'] = x
data_bowl_stats_top_wkt = df_bowl_top_wicket[['Position', 'Player', 'Wickets taken']].head(3)
fig = px.bar(data_bowl_stats_top_wkt, x='Player', y='Wickets taken',text='Wickets taken', hover_data=['Position','Player', 'Wickets taken'], color='Player')
fig.update_traces(texttemplate='%{text:.s}', textposition='inside')
fig.update_layout(uniformtext_minsize=12, uniformtext_mode='hide')
fig.update_layout(xaxis_title="Bowlers",
yaxis_title="Wickets taken so far",
legend_title="Players",
font=dict(
family="Arial",
size=16,
color="RebeccaPurple"
))
fig.update_layout(title={'text': "Top 3 Most Wicket taker",
'y':0.95,
'x':0.42,
'xanchor': 'center',
'yanchor': 'top'})
st.write(fig)
st.markdown("_________________________________________________________________________________")
elif select_category == 'Best Economy Rate':
df_bowl_best_er = data_bowling_stats.sort_values(by=['Economy Rate'], ascending=True).head(3)
x = np.arange(1, 4)
df_bowl_best_er['Position'] = x
data_bowl_stats_best_er = df_bowl_best_er[['Position', 'Player', 'Economy Rate']].head(3)
fig = px.bar(data_bowl_stats_best_er, x='Player', y='Economy Rate', text='Economy Rate', hover_data=['Position','Player', 'Economy Rate'], color='Player')
fig.update_traces(texttemplate='%{text:.4s}', textposition='inside')
fig.update_layout(uniformtext_minsize=12, uniformtext_mode='hide')
fig.update_layout(xaxis_title="Bowlers",
yaxis_title="Economy Rate",
legend_title="Players",
font=dict(
family="Arial",
size=16,
color="RebeccaPurple"
))
fig.update_layout(title={'text': "Top 3 Bowlers with Best Economy rate",
'y':0.95,
'x':0.40,
'xanchor': 'center',
'yanchor': 'top'})
st.write(fig)
st.markdown("🤔💡 * **Economy rate** is the number of runs a bowler have conceded per over bowled. The **lower** the economy rate is, the **better** the bowler is performing.*")
st.markdown("_________________________________________________________________________________")
elif select_category == 'Best Bowling Average':
data_bowling_stats = data_bowling_stats[data_bowling_stats.Average != '-']
df_bowl_best_avg = data_bowling_stats.sort_values(by=['Average'], ascending=True).head(3)
x = np.arange(1, 4)
df_bowl_best_avg['Position'] = x
data_bowl_stats_best_avg = df_bowl_best_avg[['Position', 'Player', 'Average']].head(3)
fig = px.bar(data_bowl_stats_best_avg, x='Player', y='Average',text='Average', hover_data=['Position','Player', 'Average'], color='Player', width=750)
fig.update_traces(texttemplate='%{text:.4s}', textposition='inside')
fig.update_layout(uniformtext_minsize=12, uniformtext_mode='hide')
fig.update_layout(xaxis_title="Bowlers",
yaxis_title="Average",
legend_title="Players",
font=dict(
family="Arial",
size=16,
color="RebeccaPurple"
))
fig.update_layout(title={'text': "Top 3 Bowlers with Best Bowling Average",
'y':0.95,
'x':0.40,
'xanchor': 'center',
'yanchor': 'top'})
st.write(fig)
st.markdown("🤔💡 * **Bowling average** is the number of runs a bowler have conceded per wicket taken. The **lower** the bowling average is, the **better** the bowler is performing*")
st.markdown("_________________________________________________________________________________")
#########################################################################################################################################
#########################################################################################################################################
# st.sidebar.title("Schedule of IPL 2020")
st.sidebar.markdown("<h1 style='text-align: center; color: #F34600;'><u><strong>Schedule of IPL 2020</strong></u></h1>", unsafe_allow_html=True)
# st.sidebar.markdown("You can check the scheduled matches of IPL 2020, along with various other details like timing, Venue etc.")
st.sidebar.markdown("<h4 style='text-align: center; '>You can check all the scheduled matches of IPL 2020, along with various other details like timing, Venue etc.</h4>", unsafe_allow_html=True)
st.sidebar.markdown("_________________________________________________________________________________")
# st.sidebar.markdown(" ")
# st.sidebar.markdown(" ")
# st.sidebar.subheader("Want to check all scheduled Matches?")
st.sidebar.markdown("<h2 style='text-align: center; color: #BD08D3;'><strong>Want to check all scheduled Matches?</strong></h2>", unsafe_allow_html=True)
if st.sidebar.checkbox("Show IPL 2020 scheduled matches", False):
st.markdown(" ")
# st.markdown(" ")
# st.header("IPL 2020 Scheduled Matches")
st.markdown("<h2 style='text-align: center; color: #BD08D3;'><strong><u>All Scheduled matches of IPL 2020</u></strong></h2>", unsafe_allow_html=True)
# st.header("Bowling Stats of top Players")
all_match = st.slider("Adjust the slider if you want to check more Scheduled Matches?", 20, 60)
st.markdown("<h4 style='text-align: center;'><i>You can view in fullscreen for better visibility of Schedule</i></h4>", unsafe_allow_html=True)
# st.markdown("You can expand the view for better visibility of Time table")
image = pd.read_csv('ipl_schedule.csv')
# st.image(image, use_column_width=True)
imag= image[['Match No', 'Match Center', 'Date', 'Day', 'Time India (IST)', 'Venuue']]
# imag = imag.style.hide_index()
# imag.set_index('column', inplace=True)
st.write(image.head(all_match))
st.markdown("_________________________________________________________________________________")
# st.table(imag.assign(hack='').set_index('hack').head(all_match))
# st.sidebar.markdown(" ")
# st.sidebar.markdown(" ")
# st.sidebar.subheader("Want to check scheduled Matches of your favourite team?")
st.sidebar.markdown("_________________________________________________________________________________")
st.sidebar.markdown("<h2 style='text-align: center; color: #5A2553;'><strong>Want to check scheduled Matches of your favourite team?</strong></h2>", unsafe_allow_html=True)
favourite_team = st.sidebar.selectbox("Which's your favourite team?", ['--Select--', 'Chennai Super Kings (CSK)', 'Mumbai Indians (MI)', 'Royal Challengers Benglore (RCB)', 'Sunrisers Hyderabad (SRH)', 'Delhi Capitals (DC)', 'Kings Eleven Punjab (KXIP)', 'Rajasthan Royals (RR)', 'Kolkata knight Riders (KKR)'])
if favourite_team == 'Chennai Super Kings (CSK)':
# @st.cache(persist=True)
csk = pd.read_csv('csk_schedule.csv')
# st.image(image, use_column_width=True)
csk= csk[['Match No', 'Match Center', 'Date', 'Day', 'Time India (IST)', 'Venuue']]
# imag = imag.style.hide_index()
# imag.set_index('column', inplace=True)
# st.write(csk)
st.markdown(" ")
# st.markdown(" ")
# st.header("Chennai Super Kings full Schedule of Matches")
st.markdown("<h2 style='text-align: center; color: #DBB000;'><strong><u>Chennai Super Kings full Schedule of Matches</strong></h2>", unsafe_allow_html=True)
st.table(csk.assign(hack='').set_index('hack'))
# st.markdown("_________________________*****___________________________")
st.markdown("<h2 style='text-align: center; color: #DBB000;'><strong><u>_____________________*****_____________________</strong></h2>", unsafe_allow_html=True)
#
elif favourite_team == 'Mumbai Indians (MI)':
mi = pd.read_csv('mi_schedule.csv')
mi= mi[['Match No', 'Match Center', 'Date', 'Day', 'Time India (IST)', 'Venuue']]
st.markdown(" ")
# st.markdown(" ")
# st.header("Mumbai Indians full Schedule of Matches")
st.markdown("<h2 style='text-align: center; color: #006EC9;'><strong><u>Mumbai Indians full Schedule of Matches</u></strong></h2>", unsafe_allow_html=True)
st.table(mi.assign(hack='').set_index('hack'))
st.markdown("<h2 style='text-align: center; color: #006EC9;'><strong><u>_____________________*****_____________________</strong></h2>", unsafe_allow_html=True)
elif favourite_team == 'Royal Challengers Benglore (RCB)':
rcb = pd.read_csv('rcb_schedule.csv')
rcb= rcb[['Match No', 'Match Center', 'Date', 'Day', 'Time India (IST)', 'Venuue']]
st.markdown(" ")
# st.markdown(" ")
# st.header("Royal Challengers Benglore full Schedule of Matches")
st.markdown("<h2 style='text-align: center; color: #F30922;'><strong><u>Royal Challengers Benglore full Schedule of Matches</u></strong></h2>", unsafe_allow_html=True)
st.table(rcb.assign(hack='').set_index('hack'))
st.markdown("<h2 style='text-align: center; color: #F30922;'><strong><u>_____________________*****_____________________</strong></h2>", unsafe_allow_html=True)
elif favourite_team == 'Sunrisers Hyderabad (SRH)':
srh = pd.read_csv('srh_schedule.csv')
srh= srh[['Match No', 'Match Center', 'Date', 'Day', 'Time India (IST)', 'Venuue']]
st.markdown(" ")
# st.markdown(" ")
# st.header("Sunrisers Hyderabad full Schedule of Matches")
st.markdown("<h2 style='text-align: center; color: #F32C09;'><strong><u>Sunrisers Hyderabad full Schedule of Matches</u></strong></h2>", unsafe_allow_html=True)
st.table(srh.assign(hack='').set_index('hack'))
st.markdown("<h2 style='text-align: center; color: #F32C09;'><strong><u>_____________________*****_____________________</strong></h2>", unsafe_allow_html=True)
elif favourite_team == 'Delhi Capitals (DC)':
dc = pd.read_csv('dc_schedule.csv')
dc= dc[['Match No', 'Match Center', 'Date', 'Day', 'Time India (IST)', 'Venuue']]
st.markdown(" ")
# st.markdown(" ")
# st.header("Delhi Capitals full Schedule of Matches")
st.markdown("<h2 style='text-align: center; color: #4403E3;'><strong><u>Delhi Capitals full Schedule of Matches</u></strong></h2>", unsafe_allow_html=True)
st.table(dc.assign(hack='').set_index('hack'))
st.markdown("<h2 style='text-align: center; color: #4403E3;'><strong><u>_____________________*****_____________________</strong></h2>", unsafe_allow_html=True)
elif favourite_team == 'Kings Eleven Punjab (KXIP)':
punjab = pd.read_csv('punjab_schedule.csv')
punjab= punjab[['Match No', 'Match Center', 'Date', 'Day', 'Time India (IST)', 'Venuue']]
st.markdown(" ")
# st.markdown(" ")
# st.header("RKings Eleven Punjab full Schedule of Matches")
st.markdown("<h2 style='text-align: center; color: #E10000;'><strong><u>Kings Eleven Punjab full Schedule of Matches</u></strong></h2>", unsafe_allow_html=True)
st.table(punjab.assign(hack='').set_index('hack'))
st.markdown("<h2 style='text-align: center; color: #E10000;'><strong><u>_____________________*****_____________________</strong></h2>", unsafe_allow_html=True)
elif favourite_team == 'Rajasthan Royals (RR)':
rr = pd.read_csv('rajasthan_schedule.csv')
rr= rr[['Match No', 'Match Center', 'Date', 'Day', 'Time India (IST)', 'Venuue']]
st.markdown(" ")
# st.markdown(" ")
# st.header("Rajasthan Royals full Schedule of Matches")
st.markdown("<h2 style='text-align: center; color: #F519AC;'><strong><u>Rajasthan Royals full Schedule of Matches</u></strong></h2>", unsafe_allow_html=True)
st.table(rr.assign(hack='').set_index('hack'))
st.markdown("<h2 style='text-align: center; color: #F519AC;'><strong><u>_____________________*****_____________________</strong></h2>", unsafe_allow_html=True)
elif favourite_team == 'Kolkata knight Riders (KKR)':
kkr = pd.read_csv('kkr_schedule.csv')
kkr= kkr[['Match No', 'Match Center', 'Date', 'Day', 'Time India (IST)', 'Venuue']]
st.markdown(" ")
# st.markdown(" ")
# st.header("Kolkata knight Riders full Schedule of Matches")
st.markdown("<h2 style='text-align: center; color: #3328B3;'><strong><u>Kolkata knight Riders full Schedule of Matches</u></strong></h2>", unsafe_allow_html=True)
st.table(kkr.assign(hack='').set_index('hack'))
st.markdown("<h2 style='text-align: center; color: #3328B3;'><strong><u>_____________________*****_____________________</strong></h2>", unsafe_allow_html=True)
# with open("/home/dheeraj/my_projects/my_project_env/practice/IPL2020_Dashnoard/style.css") as f:
# st.markdown('<style>{}</style>'.format(f.read()), unsafe_allow_html=True)
#
# path = "https://media.giphy.com/media/rS9tqucvXWwuY/giphy.gif"
st.markdown(" ")
st.image(path, width = 300)
# st.write("bye world")
# bye = '/home/dheeraj/my_projects/my_project_env/practice/IPL2020_Dashnoard/bye.png'
# st.image(bye, width=150)
# st.markdown("<img src='/home/dheeraj/my_projects/my_project_env/practice/IPL2020_Dashnoard/bye.png' >", unsafe_allow_html=True)
# <iframe src="https://giphy.com/embed/rS9tqucvXWwuY" width="480" height="271" frameBorder="0" class="giphy-embed" allowFullScreen></iframe><p><a href="https://giphy.com/stickers/bye-rS9tqucvXWwuY">via GIPHY</a></p>
# <img src="/home/dheeraj/my_projects/my_project_env/practice/IPL2020_Dashnoard/bye.png" alt="Italian Trulli">
# st.markdown("")