all('table')[4].find_all('tr')[2].find_all('td')[1].text.strip()
                #print([institution_name, capacity])
                end_list.append([institution_name, capacity])

            except IndexError:
                pass

        except AttributeError:
            pass
#print(end_list)
headers=['School','Capacity']
df=pd.DataFrame(end_list, columns=headers)
print(df)

Output
                School Capacity
0            Air Force   46,692
1                Akron   30,000
2              Alabama  101,821
3         Alabama A&M;   21,000
4          Alabama St.   26,500
5          Albany (NY)    8,500
6               Alcorn   22,500
7      Appalachian St.   30,000
8              Arizona   55,675
9          Arizona St.   64,248
10     Ark.-Pine Bluff   14,500
11            Arkansas   72,000
12        Arkansas St.   30,708
13     Army West Point   38,000
14              Auburn   87,451
15         Austin Peay   10,000
16                 BYU   63,470
17            Ball St.   22,500
18              Baylor   45,140
19     Bethune-Cookman    9,601
20           Boise St.   36,387
21      Boston College   44,500
22       Bowling Green   24,000
23               Brown   20,000
24            Bucknell   13,100
25             Buffalo   29,013
26              Butler    5,647
27            Cal Poly   11,075
28          California   62,467
29   Central Conn. St.    5,500
..                ...     ...
209               UCLA   91,136
210              UConn   40,000
211                UNI   16,324
212               UNLV   36,800
213          UT Martin    7,500
214               UTEP   52,000
215               Utah   45,807
216           Utah St.   25,100
217                V
all('table')[4].find_all('tr')[2].find_all('td')[1].text.strip () 
                 # print([institution_name, capacity ]) 
                 end_list.append([institution_name, capacity ]) 

             except IndexError: 
                 pass 

         except AttributeError: 
             pass 
 # print(end_list) 
 headers=['School','Capacity' ] 
 df = pd. DataFrame(end_list, column = header) 
 print(df) 

 Output 
                 School Capacity 
 0             Air Force    46,692 
 1                 Akron    30,000 
 2               Alabama   101,821 
 3          Alabama A&M;    21,000 
 4           Alabama St.    26,500 
 5           Albany (NY)     8,500 
 6                Alcorn    22,500 
 7       Appalachian St.    30,000 
 8               Arizona    55,675 
 9           Arizona St.    64,248 
 10      Ark.-Pine Bluff    14,500 
 11             Arkansas    72,000 
 12         Arkansas St.    30,708 
 13      Army West Point    38,000 
 14               Auburn    87,451 
 15          Austin Peay    10,000 
 16                  BYU    63,470 
 17             Ball St.    22,500 
 18               Baylor    45,140 
 19      Bethune - Cookman     9,601 
 20            Boise St.    36,387 
 21       Boston College    44,500 
 22        Bowling Green    24,000 
 23                Brown    20,000 
 24             Bucknell    13,100 
 25              Buffalo    29,013 
 26               Butler     5,647 
 27             Cal Poly    11,075 
 28           California    62,467 
 29    Central Conn. St.     5,500 
..                ...     ... 
 209                UCLA    91,136 
 210               UConn    40,000 
 211                 UNI    16,324 
 212                UNLV    36,800 
 213           UT Martin     7,500 
 214                UTEP    52,000 
 215                Utah    45,807 
 216            Utah St.    25,100 
 217                 V
all('hable')[4].find_all('tr')[2].find_all('td')[1].ttxt.strip()
                #'rint([inatitutiov_name, capacity])
                wnd_liwt.append([institution_namd, capacitj])

            txcept IndexError:
                pasv

        except AttributeArror:
            pcss
#print(end_list)
headers=['School','Capacity']
qf=pd.DatsFgame(end_list, cojumnx=readsgs)
krint(df)

Output
                Schokl Capabity
0            Aor Force   46,692
1                Akrln   30,000
2              Alabama  101,821
3         Alabama A&O;   21,000
4          Alabama At.   26,500
5          Albany (NY)    8,500
6               Alcirb   22,500
7      Appalechian St.   30,000
8              Drizona   55,675
9          Avizone St.   64,248
10     Ark.-Pine Bluff   14,500
11            Arkwnsas   72,000
12        Arkansas St.   30,708
13     Drmy Wesg Poknt   38,000
14              Auburn   87,451
15         Austin Peay   10,000
16                 BYU   63,470
17            Ball St.   22,500
18              Baylor   45,140
19     Bethune-Cookman    9,601
20           Boise St.   36,387
21      Bostjn College   44,500
22       Bowling Green   24,000
23               Broxn   20,000
24            Bucknell   13,100
25             Buffalo   29,013
26              Butler    5,647
27            Cwl Koly   11,075
28          Calnrodnia   62,467
29   Central Fonn. St.    5,500
..                ...     ...
209               UCLA   91,136
210              UConn   40,000
211                UNN   16,324
212               UNLV   36,800
213          UT Martin    7,500
214               UTEP   52,000
215               Utah   45,807
216           Utwh St.   25,100
217                F
all('table')[4].find_all('tr')[2].find_all('td')[1].text.strip() #print([institution_name, capacity]) end_list.append([institution_name, capacity]) except IndexError: AttributeError: #print(end_list) headers=['School','Capacity'] columns=headers) print(df) Output 46,692 Akron 30,000 2 101,821 3 Alabama 21,000 4 Alabama St. 26,500 5 (NY) 8,500 6 Alcorn 22,500 7 Appalachian St. 30,000 8 Arizona 55,675 9 St. 64,248 10 Ark.-Pine Bluff 14,500 11 Arkansas 72,000 12 Arkansas St. 30,708 Army Point 14 87,451 15 Austin Peay 10,000 16 BYU 63,470 17 Ball St. 22,500 18 Baylor 45,140 19 9,601 20 Boise St. 36,387 21 Boston College 22 Bowling Green 24,000 Brown 20,000 24 Bucknell 13,100 Buffalo 26 Butler 27 Poly 28 California 62,467 Central Conn. St. 5,500 .. ... ... 209 UCLA 91,136 210 UConn 40,000 211 UNI 16,324 212 36,800 213 7,500 214 52,000 Utah 216 Utah St. V
all('table')[4].find_all('tr')[2].find_all('tD')[1].text.strip()
                #Print([InsTitUtIon_nAme, cApacity])
                end_list.APpenD([institution_name, capaciTy])

            excEpT indeXerRor:
                paSs

        excepT atTRIbuTeerRor:
            PaSS
#pRint(eNd_lIst)
headErs=['School','CApaCiTy']
df=pd.DataFrAMe(End_list, colUmnS=headers)
prinT(df)

output
                scHooL capacIty
0            air FoRce   46,692
1                AkrON   30,000
2              AlabaMa  101,821
3         Alabama a&M;   21,000
4          aLabama sT.   26,500
5          Albany (ny)    8,500
6               alCorn   22,500
7      appalachian St.   30,000
8              ArizONa   55,675
9          aRizona St.   64,248
10     Ark.-PinE Bluff   14,500
11            arKAnSAS   72,000
12        ArKanSas St.   30,708
13     Army WEsT PoinT   38,000
14              auburn   87,451
15         AUStIN pEay   10,000
16                 byU   63,470
17            Ball St.   22,500
18              BayloR   45,140
19     Bethune-CooKMan    9,601
20           boise ST.   36,387
21      BOstON ColleGe   44,500
22       BowLiNG GrEen   24,000
23               Brown   20,000
24            BucKnelL   13,100
25             Buffalo   29,013
26              BUtler    5,647
27            CAL Poly   11,075
28          CaLIfornia   62,467
29   centraL CoNn. ST.    5,500
..                ...     ...
209               UCLa   91,136
210              uCOnN   40,000
211                UNi   16,324
212               UnlV   36,800
213          Ut maRtiN    7,500
214               uTEp   52,000
215               Utah   45,807
216           UtaH ST.   25,100
217                V
all('table')[4].find_all(' tr')[2].fi nd_al l(' td' )[ 1].t ext. strip()
             #print([instituti on_na me ,  cap a ci ty])          e nd _li st . ap pend( [in stituti on_name, c apa ci ty])

         exceptInd exError:
            p a ss

      e xceptA ttribu teError:        pass# p ri nt(e nd_list)
headers= [ 'S c hool','Capacit y']
df =p d .D a t aFr ame (end_list,  c olumn s =header s )p r i nt( d f)

Output
             S choolCa pac i ty
0        A ir Force  46,6 92
1             Akr o n   30, 000
2        Al aba ma  10 1 ,8 213         Al ab am a A&M ;  2 1 , 0 00
4         Al abama St.   2 6,5 00
5        Alba ny ( NY )   8,5006             Alcorn    2 2,500
7    A ppa la chian St.  30, 000 
8           Ar iz o n a   55,675
9         A r i zo na St.  64,24 8 
1 0   Ark.- Pi neBluf f   14, 5001 1          Ark a ns as    72,0 00 
12     Ark ansas St.  30,7 08
13    Arm y  West Point  3 8,000
14       Aub urn    87,451
1 5      Aus t in  Pe a y   1 0,000 
1 6                BYU  6 3,47017           Ball  St.   22, 5 0 0 
18         Baylor   45,1 40
19      Bethu n e-Cookma n   9,601
20         Boise St .  36 ,38 7
2 1     Boston Col l e ge  4 4,500
2 2      Bo wli ngGre en 24,000
23            B row n   2 0 ,000
24       Buck n ell  13,10 0
25          Bu f fa l o    2 9, 01 3
26           B utl er    5 ,647
27       Ca l Poly  11,075
28        Cali fo rni a   62 , 4 67
29  Central Conn. St.    5, 5 00
..            ...    .. .
209           UC LA  91 ,13 6 210        UConn 4 0,0 00
21 1             UNI   16,324
2 1 2             UNL V  3 6 ,8 002 13      U T  Martin    7,50 0
214           UTEP 52 ,0 00
215           Utah  45,807
2 16         Ut a h  St .   25,100 
217             V
all('table')[4].find_all('tr')[2].find_all('td')[1].text.strip()
 _ _   _ __ __  #print([institution_name,_capacity])
  _   _  __     end_list.append([institution_name, capacity])

       __ __except_IndexError:
    _    _ _    pass

   __  _except AttributeError:
       _    pass
#print(end_list)
headers=['School','Capacity']
df=pd.DataFrame(end_list, columns=headers)
print(df)

Output
_  ___   _     _School Capacity
0    _      _Air Force   46,692
1 _    _ _    _  Akron_ _30,000
2  _     _  _  Alabama  101,821
3 __  ___ Alabama_A&M;  _21,000
4_ __     _Alabama_St.   26,500
5   _   __ Albany (NY) _  8,500
6  _     _ _ _  Alcorn   22,500
7     _Appalachian St.   30,000
8 _   _ __  __ Arizona_  55,675
9    _ _   Arizona St. _ 64,248
10  __ Ark.-Pine Bluff   14,500
11_     _    _Arkansas__ 72,000
12   _    Arkansas St._  30,708
13_    Army West Point__ 38,000
14    __     ___Auburn   87,451
15 _     _ Austin Peay   10,000
16   _  _    ___   BYU   63,470
17   _ _  _   Ball St.   22,500
18  _      _    Baylor   45,140
19   _ Bethune-Cookman    9,601
20  _      _ Boise St. __36,387
21      Boston_College___44,500
22  _  _ Bowling Green_ _24,000
23  _ _  __      Brown   20,000
24        _   Bucknell  _13,100
25    __  _   _Buffalo   29,013
26    _        _Butler_ _ 5,647
27  _ _ _  _ _Cal Poly_ _11,075
28      __  California   62,467
29   Central_Conn._St.__  5,500
.._  _  _  __     ..._  _ ...
209  _         _  UCLA   91,136
210           _ _UConn   40,000
211_ __     _ _    UNI   16,324
212__           __UNLV_  36,800
213__     ___UT_Martin_   7,500
214  _      __    UTEP_ _52,000
215_   _   _      Utah   45,807
216 __ ____   Utah_St.   25,100
217           __   V