import pandas as pd
import os.path
import requests
from bs4 import BeautifulSoup
def getStandardBatting(league, year):
csvfile = league + '_' + str(year) + '-standard-batting.csv'
if os.path.isfile(csvfile):
dd = pd.read_csv(csvfile)
else:
r = requests.get("https://www.baseball-reference.com/leagues/"+league+"/"+str(year)+"-standard-batting.shtml")
soup = BeautifulSoup(r.content, "html.parser") # try lxml
div = soup.find('div', id='all_players_standard_batting')
bdiv = bytearray(str(div.contents),'utf-8')
soup2 = BeautifulSoup(bdiv, "html.parser")
tbody = soup2.find('tbody')
rows = tbody.find_all('tr')
columns = ['Name','Age','Tm','G','PA','AB','R','H','2B','3B','HR','RBI','SB','CS','BB','SO',
'BA','OBP','SLG','OPS','OPS+','TB','GDP','HBP','SH','SF','IBB','Pos Summary']
dd = pd.DataFrame(columns = columns)
irow = 0
for row in rows:
cols = row.find_all('td')
if (len(cols) >= 28):
dd.loc[irow] = [
cols[0].text.strip(),
cols[1].text.strip(),
cols[2].text.strip(),
cols[3].text.strip(),
cols[4].text.strip(),
cols[5].text.strip(),
cols[6].text.strip(),
cols[7].text.strip(),
cols[8].text.strip(),
cols[9].text.strip(),
cols[10].text.strip(),
cols[11].text.strip(),
cols[12].text.strip(),
cols[13].text.strip(),
cols[14].text.strip(),
cols[15].text.strip(),
cols[16].text.strip(),
cols[17].text.strip(),
cols[18].text.strip(),
cols[19].text.strip(),
cols[20].text.strip(),
cols[21].text.strip(),
cols[22].text.strip(),
cols[23].text.strip(),
cols[24].text.strip(),
cols[25].text.strip(),
cols[26].text.strip(),
cols[27].text.strip()
]
irow = irow+1
dd.index += 1
dd.to_csv(csvfile)
return dd
nl17 = getStandardBatting('NL', 2017)
al17 = getStandardBatting('AL', 2017)
print(nl17)
print(al17)
print(nl17.iloc[0,:])
print(al17.iloc[0,:])
Unnamed: 0 Name Age Tm G PA AB R H 2B \
0 1 Cristhian Adames# 25.0 COL 12 14 13 1 0 0
1 2 Austin Adams 26.0 WSN 6 0 0 0 0 0
2 3 Lane Adams 27.0 ATL 85 122 109 19 30 4
3 4 Matt Adams* 28.0 TOT 131 367 339 46 93 22
4 5 Matt Adams* 28.0 STL 31 53 48 4 14 2
5 6 Matt Adams* 28.0 ATL 100 314 291 42 79 20
6 7 Tim Adleman 29.0 CIN 27 32 29 0 3 1
7 8 Jesus Aguilar 27.0 MIL 133 311 279 40 74 15
8 9 Nick Ahmed 27.0 ARI 53 178 167 24 42 8
9 10 Matt Albers* 34.0 WSN 59 0 0 0 0 0
10 11 Ozzie Albies# 20.0 ATL 57 244 217 34 62 9
11 12 Arismendy Alcantara# 25.0 CIN 70 108 105 13 18 3
12 13 Sandy Alcantara 21.0 STL 8 0 0 0 0 0
13 14 Jorge Alfaro 24.0 PHI 29 114 107 12 34 6
14 15 Albert Almora 23.0 CHC 132 323 299 39 89 18
15 16 Aaron Altherr 26.0 PHI 107 412 372 58 101 24
16 17 Henderson Alvarez 27.0 PHI 3 6 6 0 0 0
17 18 Alexi Amarista* 28.0 COL 96 176 168 22 40 10
18 19 Brett Anderson* 29.0 CHC 6 8 7 0 1 0
19 20 Brian Anderson 24.0 MIA 25 95 84 11 22 7
20 21 Chase Anderson 29.0 MIL 24 55 52 1 7 1
21 22 Drew Anderson 23.0 PHI 1 0 0 0 0 0
22 23 Tyler Anderson* 27.0 COL 17 33 26 1 1 0
23 24 Norichika Aoki* 35.0 NYM 27 116 102 16 29 7
24 25 Victor Arano 22.0 PHI 10 0 0 0 0 0
25 26 Orlando Arcia 22.0 MIL 153 548 506 56 140 17
26 27 Nolan Arenado 26.0 COL 159 680 606 100 187 43
27 28 Jake Arrieta 31.0 CHC 29 64 61 2 8 0
28 29 Bronson Arroyo 40.0 CIN 15 29 26 0 4 0
29 30 Christian Arroyo 22.0 SFG 34 135 125 9 24 5
.. ... ... ... ... ... ... ... ... ... ..
717 718 Zack Wheeler* 27.0 NYM 17 29 27 1 2 1
718 719 Matt Wieters# 31.0 WSN 123 465 422 43 95 20
719 720 Tom Wilhelmsen 33.0 ARI 27 1 1 0 0 0
720 721 Adam Wilk* 29.0 NYM 1 1 1 0 0 0
721 722 Aaron Wilkerson 28.0 MIL 3 4 4 0 0 0
722 723 Nick Williams* 23.0 PHI 83 343 313 45 90 14
723 724 Taylor Williams# 25.0 MIL 5 0 0 0 0 0
724 725 Trevor Williams 25.0 PIT 30 47 41 1 2 0
725 726 Mac Williamson 26.0 SFG 28 73 68 8 16 2
726 727 Justin Wilson* 29.0 CHC 22 0 0 0 0 0
727 728 Jesse Winker* 23.0 CIN 47 137 121 21 36 7
728 729 Dan Winkler 27.0 ATL 16 0 0 0 0 0
729 730 Matt Wisler 24.0 ATL 20 3 2 0 0 0
730 731 Nick Wittgren 26.0 MIA 34 4 4 0 0 0
731 732 Asher Wojciechowski 28.0 CIN 23 14 14 0 1 0
732 733 Tony Wolters* 25.0 COL 83 266 229 30 55 8
733 734 Kolten Wong* 26.0 STL 108 411 354 55 101 27
734 735 Alex Wood 26.0 LAD 27 58 52 1 3 0
735 736 Blake Wood 31.0 CIN 52 1 1 0 0 0
736 737 Travis Wood 30.0 SDP 11 17 17 3 4 0
737 738 Brandon Woodruff* 24.0 MIL 7 12 10 2 2 0
738 739 Vance Worley 29.0 MIA 25 27 22 0 4 0
739 740 Kirby Yates* 30.0 SDP 55 0 0 0 0 0
740 741 Christian Yelich* 25.0 MIA 156 695 602 100 170 36
741 742 Mark Zagunis 24.0 CHC 7 18 14 0 0 0
742 743 Rob Zastryzny 25.0 CHC 4 3 3 0 1 0
743 744 Brad Ziegler 37.0 MIA 51 0 0 0 0 0
744 745 Ryan Zimmerman 32.0 WSN 144 576 524 90 159 33
745 746 Ben Zobrist# 36.0 CHC 128 496 435 58 101 20
746 747 LgAvg per 600 PA NaN NaN 230 600 534 72 136 27
... SLG OPS OPS+ TB GDP HBP SH SF IBB Pos Summary
0 ... 0.000 0.071 -80.0 0 0 0 0 0 0 /346
1 ... NaN NaN NaN 0 0 0 0 0 0 /1
2 ... 0.468 0.807 108.0 51 3 1 1 1 0 78/9
3 ... 0.522 0.841 115.0 177 5 1 0 4 5 37/D
4 ... 0.396 0.735 95.0 19 0 0 0 1 0 /73D
5 ... 0.543 0.858 118.0 158 5 1 0 3 5 37
6 ... 0.138 0.241 -37.0 4 0 0 3 0 0 1
7 ... 0.505 0.837 114.0 141 8 4 0 3 1 3/D5
8 ... 0.419 0.717 78.0 70 6 1 0 0 3 6
9 ... NaN NaN NaN 0 0 0 0 0 0 1
10 ... 0.456 0.810 110.0 99 3 3 1 2 0 4
11 ... 0.248 0.435 13.0 26 2 0 1 0 0 4/89657
12 ... NaN NaN NaN 0 0 0 0 0 0 /1
13 ... 0.514 0.874 129.0 55 2 4 0 0 1 2/3
14 ... 0.445 0.782 101.0 133 8 0 3 2 1 8/79
15 ... 0.516 0.856 124.0 192 12 7 0 1 2 798
16 ... 0.000 0.000 -100.0 0 0 0 0 0 0 /1
17 ... 0.351 0.620 52.0 59 5 0 1 0 0 46/8975
18 ... 0.143 0.393 7.0 1 0 0 0 0 0 /1
19 ... 0.369 0.706 92.0 31 1 0 0 1 0 5
20 ... 0.154 0.288 -25.0 8 1 0 3 0 0 1
21 ... NaN NaN NaN 0 0 0 0 0 0 /1
22 ... 0.038 0.113 -71.0 1 1 0 6 0 0 1
23 ... 0.373 0.743 99.0 38 1 1 0 0 0 9/78
24 ... NaN NaN NaN 0 0 0 0 0 0 1
25 ... 0.407 0.731 89.0 206 10 1 2 3 9 *6
26 ... 0.586 0.959 132.0 355 21 4 1 6 9 *5
27 ... 0.213 0.358 -9.0 13 0 0 2 0 0 1
28 ... 0.154 0.308 -19.0 4 0 0 3 0 0 1
29 ... 0.304 0.548 45.0 38 4 1 0 1 1 56/4
.. ... ... ... ... ... ... ... .. .. ... ...
717 ... 0.111 0.218 -42.0 3 0 0 1 0 0 1
718 ... 0.344 0.632 64.0 145 14 1 0 4 4 *2
719 ... 0.000 0.000 -100.0 0 0 0 0 0 0 1
720 ... 0.000 0.000 -100.0 0 0 0 0 0 0 /1
721 ... 0.000 0.000 -100.0 0 0 0 0 0 0 /1
722 ... 0.473 0.811 113.0 148 8 6 0 4 0 987/D
723 ... NaN NaN NaN 0 0 0 0 0 0 /1
724 ... 0.049 0.142 -61.0 2 1 0 4 0 0 1
725 ... 0.397 0.685 79.0 27 2 0 0 0 1 9/7D
726 ... NaN NaN NaN 0 0 0 0 0 0 1
727 ... 0.529 0.904 133.0 64 2 0 1 0 0 9/D7
728 ... NaN NaN NaN 0 0 0 0 0 0 1
729 ... 0.000 0.000 -100.0 0 0 0 1 0 0 1
730 ... 0.000 0.000 -100.0 0 0 0 0 0 0 1
731 ... 0.071 0.143 -62.0 1 0 0 0 0 0 1
732 ... 0.284 0.625 58.0 65 9 2 2 0 9 2/45
733 ... 0.412 0.788 110.0 146 4 12 1 3 11 4
734 ... 0.058 0.150 -59.0 3 1 0 4 0 0 1
735 ... 0.000 0.000 -100.0 0 0 0 0 0 0 1
736 ... 0.588 0.824 111.0 10 0 0 0 0 0 1
737 ... 0.200 0.473 27.0 2 0 0 1 0 0 /1
738 ... 0.182 0.364 -1.0 4 1 0 5 0 0 1
739 ... NaN NaN NaN 0 0 0 0 0 0 1
740 ... 0.439 0.807 118.0 264 13 6 0 6 4 *8
741 ... 0.000 0.222 -34.0 0 0 0 0 0 0 /9
742 ... 0.333 0.667 75.0 1 0 0 0 0 0 /1
743 ... NaN NaN NaN 0 0 0 0 0 0 1
744 ... 0.573 0.930 136.0 300 16 3 0 5 1 *3/D
745 ... 0.375 0.693 79.0 163 13 2 2 3 2 479/36
746 ... 0.423 0.748 NaN 226 12 6 4 4 4 NaN
[747 rows x 29 columns]
Unnamed: 0 Name Age Tm G PA AB R H 2B \
0 1 Fernando Abad* 31.0 BOS 4 0 0 0 0 0
1 2 Jose Abreu 30.0 CHW 156 675 621 95 189 43
2 3 Jim Adduci* 32.0 DET 29 93 83 14 20 6
3 4 Ehire Adrianza# 27.0 MIN 70 186 162 30 43 9
4 5 Andrew Albers 31.0 SEA 1 3 1 0 1 0
5 6 Al Alburquerque 31.0 TOT 1 0 0 0 0 0
6 7 Al Alburquerque 31.0 KCR 1 0 0 0 0 0
7 8 Scott Alexander* 27.0 KCR 4 3 3 0 0 0
8 9 Anthony Alford 22.0 TOR 4 8 8 0 1 1
9 10 Cody Allen 28.0 CLE 5 0 0 0 0 0
10 11 Greg Allen# 24.0 CLE 25 39 35 7 8 1
11 12 Abraham Almonte# 28.0 CLE 69 195 172 26 40 8
12 13 Yonder Alonso* 30.0 TOT 142 521 451 72 120 22
13 14 Yonder Alonso* 30.0 OAK 100 371 319 52 85 17
14 15 Yonder Alonso* 30.0 SEA 42 150 132 20 35 5
15 16 Dan Altavilla 24.0 SEA 5 0 0 0 0 0
16 17 Jose Altuve 27.0 HOU 153 662 590 112 204 39
17 18 Jose Alvarez* 28.0 LAA 5 0 0 0 0 0
18 19 Pedro Alvarez* 30.0 BAL 14 34 32 4 10 1
19 20 Tim Anderson 24.0 CHW 146 606 587 72 151 26
20 21 Elvis Andrus 28.0 TEX 158 689 643 100 191 44
21 22 Miguel Andujar 22.0 NYY 5 8 7 0 4 2
22 23 Norichika Aoki* 35.0 TOT 82 258 234 32 64 13
23 24 Norichika Aoki* 35.0 HOU 70 224 202 28 55 12
24 25 Norichika Aoki* 35.0 TOR 12 34 32 4 9 1
25 26 Jayson Aquino* 24.0 BAL 1 2 2 0 0 0
26 27 Chris Archer 28.0 TBR 3 8 8 1 2 0
27 28 Shawn Armstrong 26.0 CLE 3 0 0 0 0 0
28 29 Cody Asche* 27.0 CHW 19 62 57 5 6 1
29 30 Alec Asher 25.0 BAL 2 1 1 0 0 0
.. ... ... ... ... ... ... ... ... ... ..
610 611 Justin Verlander 34.0 DET 2 6 6 0 1 0
611 612 Nick Vincent 30.0 SEA 6 0 0 0 0 0
612 613 Daniel Vogelbach* 24.0 SEA 16 31 28 0 6 1
613 614 Stephen Vogt* 32.0 OAK 54 174 157 12 34 8
614 615 Tyler Wade* 22.0 NYY 30 63 58 7 9 4
615 616 Adam Warren 29.0 NYY 4 0 0 0 0 0
616 617 David Washington* 26.0 BAL 3 6 6 0 0 0
617 618 Rickie Weeks 34.0 TBR 37 112 97 13 21 6
618 619 Joey Wendle* 27.0 OAK 8 14 13 3 4 1
619 620 Tyler White 26.0 HOU 22 67 61 7 17 6
620 621 Chase Whitley 28.0 TBR 4 0 0 0 0 0
621 622 Mason Williams* 25.0 NYY 5 17 16 3 4 0
622 623 Alex Wilson 30.0 DET 6 0 0 0 0 0
623 624 Justin Wilson* 29.0 DET 2 0 0 0 0 0
624 625 Tyler Wilson 27.0 BAL 2 0 0 0 0 0
625 626 Alex Wimmers* 28.0 MIN 1 0 0 0 0 0
626 627 Travis Wood 30.0 KCR 3 1 1 0 0 0
627 628 Brandon Workman 28.0 BOS 1 0 0 0 0 0
628 629 Mike Wright 27.0 BAL 2 0 0 0 0 0
629 630 Jimmy Yacabonis 25.0 BAL 2 2 2 0 0 0
630 631 Gabriel Ynoa 24.0 BAL 1 1 1 0 0 0
631 632 Michael Ynoa 25.0 CHW 1 0 0 0 0 0
632 633 Chris Young 38.0 KCR 2 0 0 0 0 0
633 634 Chris Young 33.0 BOS 90 276 243 30 57 12
634 635 Eric Young# 32.0 LAA 47 125 110 24 29 5
635 636 Bradley Zimmer* 24.0 CLE 101 332 299 41 72 15
636 637 Jordan Zimmermann 31.0 DET 3 6 6 0 1 0
637 638 Mike Zunino 26.0 SEA 124 435 387 52 97 25
638 639 Tony Zych 26.0 SEA 4 0 0 0 0 0
639 640 LgAvg per 600 PA NaN NaN 166 600 538 74 137 27
... SLG OPS OPS+ TB GDP HBP SH SF IBB Pos Summary
0 ... NaN NaN NaN 0 0 0 0 0 0 1
1 ... 0.552 0.906 141.0 343 21 15 0 4 6 *3D
2 ... 0.398 0.720 90.0 33 1 0 0 0 0 9/D
3 ... 0.383 0.707 89.0 62 0 1 1 6 1 67/453D
4 ... 1.000 2.000 448.0 1 0 0 2 0 0 /1
5 ... NaN NaN NaN 0 0 0 0 0 0 1
6 ... NaN NaN NaN 0 0 0 0 0 0 1
7 ... 0.000 0.000 -100.0 0 0 0 0 0 0 1
8 ... 0.250 0.375 -5.0 2 0 0 0 0 0 /79
9 ... NaN NaN NaN 0 0 0 0 0 0 1
10 ... 0.343 0.625 63.0 12 0 1 0 1 0 8/7
11 ... 0.366 0.681 78.0 63 2 1 1 1 0 97/8D
12 ... 0.501 0.866 133.0 226 9 2 0 0 6 *3/D
13 ... 0.527 0.896 141.0 168 6 2 0 0 6 3/D
14 ... 0.439 0.793 114.0 58 3 0 0 0 0 3
15 ... NaN NaN NaN 0 0 0 0 0 0 1
16 ... 0.547 0.957 164.0 323 19 9 1 4 3 *4/D
17 ... NaN NaN NaN 0 0 0 0 0 0 1
18 ... 0.438 0.790 112.0 14 0 0 0 0 0 /D3
19 ... 0.402 0.679 81.0 236 13 3 2 1 0 *6
20 ... 0.471 0.808 108.0 303 18 3 1 4 0 *6/D
21 ... 0.857 1.482 286.0 6 0 0 0 0 0 /5D
22 ... 0.402 0.721 98.0 94 11 2 1 5 1 79/8D1
23 ... 0.371 0.694 93.0 75 11 2 1 4 1 79/D1
24 ... 0.594 0.888 124.0 19 0 0 0 1 0 /978
25 ... 0.000 0.000 -100.0 0 0 0 0 0 0 /1
26 ... 0.250 0.500 39.0 2 1 0 0 0 0 1
27 ... NaN NaN NaN 0 0 0 0 0 0 1
28 ... 0.175 0.353 -3.0 10 1 2 0 0 1 D/357
29 ... 0.000 0.000 -100.0 0 0 0 0 0 0 1
.. ... ... ... ... ... ... ... .. .. ... ...
610 ... 0.167 0.333 -11.0 1 0 0 0 0 0 1
611 ... NaN NaN NaN 0 0 0 0 0 0 1
612 ... 0.250 0.540 50.0 7 2 0 0 0 0 /3D
613 ... 0.357 0.644 75.0 56 1 0 0 1 1 2/D7
614 ... 0.224 0.446 19.0 13 2 0 0 0 0 4/679D
615 ... NaN NaN NaN 0 0 0 0 0 0 1
616 ... 0.000 0.000 -100.0 0 0 0 0 0 0 /9D
617 ... 0.340 0.662 84.0 33 0 3 0 0 0 D3
618 ... 0.615 0.973 159.0 8 0 0 0 0 1 /4
619 ... 0.525 0.853 132.0 32 0 1 0 1 0 3/471
620 ... NaN NaN NaN 0 0 0 0 0 0 1
621 ... 0.250 0.544 46.0 4 0 0 0 0 0 /89
622 ... NaN NaN NaN 0 0 0 0 0 0 1
623 ... NaN NaN NaN 0 0 0 0 0 0 1
624 ... NaN NaN NaN 0 0 0 0 0 0 /1
625 ... NaN NaN NaN 0 0 0 0 0 0 /1
626 ... 0.000 0.000 -100.0 0 1 0 0 0 0 1
627 ... NaN NaN NaN 0 0 0 0 0 0 1
628 ... NaN NaN NaN 0 0 0 0 0 0 1
629 ... 0.000 0.000 -100.0 0 0 0 0 0 0 1
630 ... 0.000 0.000 -100.0 0 0 0 0 0 0 /1
631 ... NaN NaN NaN 0 0 0 0 0 0 1
632 ... NaN NaN NaN 0 0 0 0 0 0 1
633 ... 0.387 0.709 84.0 94 4 2 0 1 0 7D/9
634 ... 0.418 0.754 103.0 46 0 7 3 0 0 78/D9
635 ... 0.385 0.692 80.0 115 5 4 0 3 1 8
636 ... 0.167 0.333 -11.0 1 0 0 0 0 0 1
637 ... 0.509 0.840 123.0 197 8 8 0 1 0 *2/D
638 ... NaN NaN NaN 0 0 0 0 0 0 1
639 ... 0.428 0.752 NaN 230 13 6 2 4 2 NaN
[640 rows x 29 columns]
Unnamed: 0 1
Name Cristhian Adames#
Age 25
Tm COL
G 12
PA 14
AB 13
R 1
H 0
2B 0
3B 0
HR 0
RBI 0
SB 0
CS 0
BB 1
SO 6
BA 0
OBP 0.071
SLG 0
OPS 0.071
OPS+ -80
TB 0
GDP 0
HBP 0
SH 0
SF 0
IBB 0
Pos Summary /346
Name: 0, dtype: object
Unnamed: 0 1
Name Fernando Abad*
Age 31
Tm BOS
G 4
PA 0
AB 0
R 0
H 0
2B 0
3B 0
HR 0
RBI 0
SB 0
CS 0
BB 0
SO 0
BA NaN
OBP NaN
SLG NaN
OPS NaN
OPS+ NaN
TB 0
GDP 0
HBP 0
SH 0
SF 0
IBB 0
Pos Summary 1
Name: 0, dtype: object
import pandas as pd
import os.path
import requests
from bs4 import BeautifulSoup
def getStarterPitching(league, year):
csvfile = league + '_' + str(year) + '-starter-pitching.csv'
if os.path.isfile(csvfile):
dd = pd.read_csv(csvfile)
else:
r = requests.get("https://www.baseball-reference.com/leagues/"+league+"/"+str(year)+"-starter-pitching.shtml")
soup = BeautifulSoup(r.content, "html.parser") # try lxml
div = soup.find('div', id='all_players_starter_pitching')
bdiv = bytearray(str(div.contents),'utf-8')
soup2 = BeautifulSoup(bdiv, "html.parser")
tbody = soup2.find('tbody')
rows = tbody.find_all('tr')
columns = ['Name','Age','Tm','IP','G','GS','Wgs','Lgs','ND','Wchp','Ltuf','Wtm','Ltm','tmW-L%','Wist','Lsv',
'CG','SHO','QS','QS%','GmScA','Best','Wrst','BQR','BQS','sDR','IDR','RS/GS','RS/IP','IP/GS',
'Pit/GS','<80','80-99','100-119','≥120','Max']
dd = pd.DataFrame(columns = columns)
irow = 0
for row in rows:
cols = row.find_all('td')
if (len(cols) >= 28):
dd.loc[irow] = [
cols[0].text.strip(),
cols[1].text.strip(),
cols[2].text.strip(),
cols[3].text.strip(),
cols[4].text.strip(),
cols[5].text.strip(),
cols[6].text.strip(),
cols[7].text.strip(),
cols[8].text.strip(),
cols[9].text.strip(),
cols[10].text.strip(),
cols[11].text.strip(),
cols[12].text.strip(),
cols[13].text.strip(),
cols[14].text.strip(),
cols[15].text.strip(),
cols[16].text.strip(),
cols[17].text.strip(),
cols[18].text.strip(),
cols[19].text.strip(),
cols[20].text.strip(),
cols[21].text.strip(),
cols[22].text.strip(),
cols[23].text.strip(),
cols[24].text.strip(),
cols[25].text.strip(),
cols[26].text.strip(),
cols[27].text.strip(),
cols[28].text.strip(),
cols[29].text.strip(),
cols[30].text.strip(),
cols[31].text.strip(),
cols[32].text.strip(),
cols[33].text.strip(),
cols[34].text.strip(),
cols[35].text.strip()
]
irow = irow+1
dd.index += 1
dd.to_csv(csvfile)
return dd
nl17 = getStarterPitching('NL', 2017)
al17 = getStarterPitching('AL', 2017)
print(nl17)
print(al17)
print(nl17.iloc[0,:])
print(al17.iloc[0,:])
Unnamed: 0 Name Age Tm IP G GS Wgs Lgs ND \
0 1 Tim Adleman 29 CIN 122.1 30 20 5 9 6
1 2 Henderson Alvarez 27 PHI 14.2 3 3 0 1 2
2 3 Brett Anderson* 29 CHC 22.0 6 6 2 2 2
3 4 Chase Anderson 29 MIL 141.1 25 25 12 4 9
4 5 Tyler Anderson* 27 COL 86.0 17 15 5 6 4
5 6 Jake Arrieta 31 CHC 168.1 30 30 14 10 6
6 7 Bronson Arroyo 40 CIN 71.0 14 14 3 6 5
7 8 Homer Bailey 31 CIN 91.0 18 18 6 9 3
8 9 Anthony Banda* 23 ARI 25.2 8 4 1 3 0
9 10 Chad Bettis 28 COL 46.1 9 9 2 4 3
10 11 Ty Blach* 26 SFG 163.2 34 24 8 12 4
11 12 Aaron Blair 25 ATL 3.0 1 1 0 1 0
12 13 Michael Blazek 28 MIL 8.2 5 1 0 1 0
13 14 Lisalverto Bonilla 27 CIN 36.2 10 4 0 3 1
14 15 Steven Brault* 25 PIT 34.2 11 4 1 0 3
15 16 Clay Buchholz 32 PHI 7.1 2 2 0 1 1
16 17 Madison Bumgarner* 27 SFG 111.0 17 17 4 9 4
17 18 Eddie Butler 26 CHC 54.2 13 11 4 3 4
18 19 Trevor Cahill 29 SDP 61.0 11 11 4 3 4
19 20 Matt Cain 32 SFG 124.1 27 23 3 11 9
20 21 Luis Castillo 24 CIN 89.1 15 15 3 7 5
21 22 Jhoulys Chacin 29 SDP 180.1 32 32 13 10 9
22 23 Tyler Chatwood 27 COL 147.2 33 25 8 14 3
23 24 Wei-Yin Chen* 31 MIA 33.0 9 5 2 1 2
24 25 A.J. Cole 25 WSN 52.0 11 8 3 5 0
25 26 Gerrit Cole 26 PIT 203.0 33 33 12 12 9
26 27 Bartolo Colon 44 ATL 63.0 13 13 2 8 3
27 28 Adam Conley* 27 MIA 102.2 22 20 7 7 6
28 29 Patrick Corbin* 27 ARI 189.2 33 32 14 13 5
29 30 Jarred Cosart 27 SDP 24.0 7 6 0 2 4
.. ... ... ... ... ... .. .. ... ... ..
131 132 Dan Straily 28 MIA 181.2 33 33 10 9 14
132 133 Stephen Strasburg 28 WSN 175.1 28 28 15 4 9
133 134 Chris Stratton 26 SFG 58.2 13 10 4 3 3
134 135 Ross Stripling 27 LAD 74.1 49 2 0 0 2
135 136 Brent Suter* 27 MIL 81.2 22 14 3 2 9
136 137 Noah Syndergaard 24 NYM 30.1 7 7 1 2 4
137 138 Jameson Taillon 25 PIT 133.2 25 25 8 7 10
138 139 Julio Teheran 26 ATL 188.1 32 32 11 13 8
139 140 Jake Thompson 23 PHI 46.1 11 8 3 2 3
140 141 Jen-Ho Tseng 22 CHC 6.0 2 1 0 0 1
141 142 Jacob Turner 26 WSN 39.0 18 2 0 1 1
142 143 Jose Urena 25 MIA 169.2 34 28 14 7 7
143 144 Julio Urias* 20 LAD 23.1 5 5 0 2 3
144 145 Vince Velasquez 25 PHI 72.0 15 15 2 7 6
145 146 Edinson Volquez 33 MIA 92.1 17 17 4 8 5
146 147 Michael Wacha 25 STL 165.2 30 30 12 9 9
147 148 Adam Wainwright 35 STL 123.1 24 23 12 5 6
148 149 Taijuan Walker 24 ARI 157.1 28 28 9 9 10
149 150 Jered Weaver 34 SDP 42.1 9 9 0 5 4
150 151 Luke Weaver 23 STL 60.1 13 10 7 2 1
151 152 Zack Wheeler 27 NYM 86.1 17 17 3 7 7
152 153 Adam Wilk* 29 NYM 3.2 1 1 0 1 0
153 154 Aaron Wilkerson 28 MIL 10.1 3 2 1 0 1
154 155 Trevor Williams 25 PIT 150.1 31 25 6 8 11
155 156 Matt Wisler 24 ATL 32.1 20 1 0 1 0
156 157 Asher Wojciechowski 28 CIN 62.1 25 8 2 3 3
157 158 Alex Wood* 26 LAD 152.1 27 25 15 3 7
158 159 Travis Wood* 30 SDP 52.1 11 11 3 4 4
159 160 Brandon Woodruff 24 MIL 43.0 8 8 2 3 3
160 161 Vance Worley 29 MIA 71.2 24 12 2 5 5
... IDR RS/GS RS/IP IP/GS Pit/GS <80 80-99 100-119 ≥120 Max
0 ... 8 5.1 4.8 5.3 90 3 13 4 0 110
1 ... 3 2.8 4.3 4.9 87 0 3 0 0 89
2 ... 4 6.0 7.3 3.7 68 3 2 1 0 100
3 ... 11 4.7 4.5 5.7 90 3 16 6 0 114
4 ... 5 5.8 5.3 5.4 88 4 8 3 0 103
5 ... 16 5.2 5.2 5.6 91 3 21 6 0 111
6 ... 6 5.4 4.4 5.1 83 3 11 0 0 95
7 ... 8 4.8 5.0 5.1 88 6 7 5 0 117
8 ... 3 3.8 1.9 4.9 84 1 3 0 0 92
9 ... 4 3.3 3.6 5.1 82 2 7 0 0 95
10 ... 10 4.1 4.5 6.2 96 2 12 10 0 112
11 ... 1 3.0 3.0 3.0 75 1 0 0 0 75
12 ... 0 2.0 0.0 2.3 61 1 0 0 0 61
13 ... 2 3.3 2.1 5.2 88 1 2 1 0 105
14 ... 3 7.3 7.6 4.5 79 2 2 0 0 92
15 ... 1 4.0 6.4 3.7 69 2 0 0 0 77
16 ... 10 2.8 2.6 6.5 98 0 10 7 0 114
17 ... 6 3.9 3.5 4.7 80 6 5 0 0 94
18 ... 6 4.8 4.0 5.5 94 0 8 3 0 111
19 ... 12 4.0 2.7 5.2 85 7 14 2 0 112
20 ... 5 4.3 3.6 6.0 99 0 7 8 0 113
21 ... 20 3.7 2.7 5.6 92 3 20 9 0 108
22 ... 9 4.2 3.9 5.5 91 4 13 8 0 114
23 ... 3 4.5 6.3 5.4 84 1 3 1 0 100
24 ... 6 3.1 2.6 5.5 100 0 3 5 0 109
25 ... 17 4.2 3.8 6.2 100 2 11 20 0 115
26 ... 7 5.1 3.7 4.8 84 3 9 1 0 101
27 ... 9 5.4 5.5 5.0 85 5 9 6 0 111
28 ... 16 5.4 4.6 5.8 95 5 14 13 0 113
29 ... 4 3.6 1.5 3.9 77 4 2 0 0 96
.. ... ... ... ... ... ... ... ... ... ... ...
131 ... 15 5.3 4.7 5.5 93 5 21 7 0 113
132 ... 17 4.8 4.3 6.3 98 2 10 16 0 119
133 ... 9 4.2 3.7 5.1 91 1 4 5 0 110
134 ... 0 3.0 1.8 2.5 36 2 0 0 0 49
135 ... 7 4.5 4.5 5.0 77 7 6 1 0 100
136 ... 6 3.6 3.8 4.3 65 3 2 2 0 114
137 ... 14 3.8 3.5 5.3 93 3 14 8 0 116
138 ... 17 4.5 4.5 5.9 96 3 16 13 0 112
139 ... 6 6.6 5.8 5.2 89 1 6 1 0 103
140 ... 1 15.8 9.0 3.0 70 1 0 0 0 70
141 ... 1 2.5 3.0 5.7 87 0 2 0 0 89
142 ... 11 5.5 4.6 5.5 95 3 14 11 0 107
143 ... 4 4.1 2.6 4.7 82 2 3 0 0 95
144 ... 9 4.0 2.7 4.8 84 4 6 5 0 108
145 ... 7 3.8 4.2 5.4 89 2 13 2 0 111
146 ... 16 4.4 4.4 5.5 90 4 20 6 0 119
147 ... 12 5.8 5.6 5.3 92 3 11 9 0 109
148 ... 17 4.7 4.2 5.6 98 1 15 12 0 117
149 ... 4 2.2 1.5 4.7 75 4 5 0 0 89
150 ... 6 5.8 7.5 5.5 96 1 5 4 0 111
151 ... 12 4.0 3.5 5.1 92 2 9 6 0 108
152 ... 1 0.0 0.0 3.7 80 0 1 0 0 80
153 ... 1 5.0 5.4 4.7 63 1 1 0 0 86
154 ... 11 4.3 3.2 5.5 89 6 16 3 0 114
155 ... 1 1.0 0.0 6.0 94 0 1 0 0 94
156 ... 3 4.3 3.4 4.4 81 3 4 1 0 100
157 ... 20 5.9 5.5 5.9 88 4 20 1 0 100
158 ... 6 4.4 3.6 4.8 88 2 5 4 0 107
159 ... 5 3.0 3.7 5.4 90 1 6 1 0 105
160 ... 4 5.4 5.6 4.4 74 8 4 0 0 92
[161 rows x 37 columns]
Unnamed: 0 Name Age Tm IP G GS Wgs Lgs ND \
0 1 Andrew Albers* 31 SEA 41.0 9 6 4 1 1
1 2 Raul Alcantara 24 OAK 24.0 8 4 1 2 1
2 3 Brett Anderson* 29 TOR 33.1 7 7 2 2 3
3 4 Matt Andriese 27 TBR 86.0 18 17 5 5 7
4 5 Jayson Aquino* 24 BAL 13.1 4 2 1 1 0
5 6 Chris Archer 28 TBR 201.0 34 34 10 12 12
6 7 Alec Asher 25 BAL 60.0 24 6 1 4 1
7 8 Trevor Bauer 26 CLE 176.1 32 31 17 9 5
8 9 Chad Bell* 28 DET 62.1 28 4 0 2 2
9 10 Christian Bergman 29 SEA 54.0 13 8 4 4 0
10 11 Jose Berrios 23 MIN 145.2 26 25 13 8 4
11 12 Joe Biagini 27 TOR 119.2 44 18 2 12 4
12 13 Austin Bibens-Dirkx 32 TEX 69.1 24 6 2 1 3
13 14 Paul Blackburn 23 OAK 58.2 10 10 3 1 6
14 15 Mike Bolsinger 29 TOR 41.1 11 5 0 2 3
15 16 Matthew Boyd* 26 DET 135.0 26 25 6 11 8
16 17 Parker Bridwell 25 LAA 121.0 21 20 10 3 7
17 18 Dylan Bundy 24 BAL 169.2 28 28 13 9 6
18 19 Trevor Cahill 29 KCR 23.0 10 3 0 0 3
19 20 Carlos Carrasco 30 CLE 200.0 32 32 18 6 8
20 21 Andrew Cashner 30 TEX 166.2 28 28 11 11 6
21 22 Miguel Castro 22 BAL 66.1 39 1 0 1 0
22 23 Luis Cessa 25 NYY 36.0 10 5 0 3 2
23 24 Jesse Chavez 33 LAA 138.0 38 21 5 9 7
24 25 Alex Claudio* 25 TEX 82.2 70 1 0 0 1
25 26 Mike Clevinger 26 CLE 121.2 27 21 11 4 6
26 27 Alex Cobb 29 TBR 179.1 29 29 12 10 7
27 28 Bartolo Colon 44 MIN 80.0 15 15 5 6 4
28 29 Jharel Cotton 25 OAK 129.0 24 24 9 10 5
29 30 Dylan Covey 25 CHW 70.0 18 12 0 7 5
.. ... ... ... ... ... .. .. ... ... ..
161 162 Matt Strahm* 25 KCR 34.2 24 3 1 2 0
162 163 Marcus Stroman 26 TOR 201.0 33 33 13 9 11
163 164 Masahiro Tanaka 28 NYY 178.1 30 30 13 12 5
164 165 Nick Tepesch 28 TOT 15.2 4 4 1 2 1
165 166 Nick Tepesch 28 MIN 1.2 1 1 0 1 0
166 167 Nick Tepesch 28 TOR 14.0 3 3 1 1 1
167 168 Chris Tillman 29 BAL 93.0 24 19 1 7 11
168 169 Josh Tomlin 32 CLE 141.0 26 26 10 9 7
169 170 Andrew Triggs 28 OAK 65.1 12 12 5 6 1
170 171 Nik Turley* 27 MIN 17.2 10 3 0 2 1
171 172 Cesar Valdez 32 TOT 30.2 11 4 1 1 2
172 173 Cesar Valdez 32 OAK 9.1 4 1 0 0 1
173 174 Cesar Valdez 32 TOR 21.1 7 3 1 1 1
174 175 Jason Vargas* 34 KCR 179.2 32 32 18 11 3
175 176 Hector Velazquez 28 BOS 24.2 8 3 0 1 2
176 177 Drew VerHagen 26 DET 34.1 24 2 0 1 1
177 178 Justin Verlander 34 TOT 206.0 33 33 15 8 10
178 179 Justin Verlander 34 DET 172.0 28 28 10 8 10
179 180 Justin Verlander 34 HOU 34.0 5 5 5 0 0
180 181 Chris Volstad 30 CHW 19.1 6 2 0 2 0
181 182 Ryan Weber 26 SEA 3.2 1 1 0 0 1
182 183 Robert Whalen 23 SEA 7.1 2 1 0 1 0
183 184 Adam Wilk* 29 MIN 10.1 3 1 0 1 0
184 185 Tyler Wilson 27 BAL 15.1 9 1 1 0 0
185 186 Travis Wood* 30 KCR 41.2 28 3 0 1 2
186 187 Daniel Wright 26 LAA 19.2 5 2 0 1 1
187 188 Steven Wright 32 BOS 24.0 5 5 1 3 1
188 189 Gabriel Ynoa 24 BAL 34.2 9 4 1 3 0
189 190 Chris Young 38 KCR 30.0 14 2 0 0 2
190 191 Jordan Zimmermann 31 DET 160.0 29 29 8 13 8
... QS QS% GmScA Best Wrst BQR BQS sDR IDR RS/GS
0 ... 2 33% 50.3 70 25 7 5 0 5 6.0
1 ... 0 0% 44.0 66 15 2 0 0 3 4.4
2 ... 2 29% 46.1 64 7 5 1 0 4 3.3
3 ... 6 35% 48.9 73 13 10 3 0 10 4.2
4 ... 1 50% 51.0 51 51 0 0 0 2 2.1
5 ... 20 59% 54.5 83 17 17 4 0 16 4.6
6 ... 3 50% 43.7 67 20 20 5 1 3 2.0
7 ... 15 48% 52.4 69 18 21 4 2 16 5.0
8 ... 0 0% 33.5 48 21 29 13 0 2 5.0
9 ... 3 38% 43.9 81 -8 8 2 0 2 4.8
10 ... 12 48% 53.4 85 22 19 7 0 11 4.5
11 ... 5 28% 44.9 76 10 16 5 1 9 2.4
12 ... 2 33% 48.5 68 37 12 4 1 2 5.1
13 ... 5 50% 51.2 73 29 8 4 0 5 5.4
14 ... 0 0% 42.6 55 27 11 0 0 3 4.8
15 ... 10 40% 45.8 89 12 19 7 1 10 4.2
16 ... 13 65% 52.6 73 18 12 3 0 8 5.1
17 ... 19 68% 53.4 95 25 11 7 0 15 5.2
18 ... 0 0% 34.7 45 26 7 0 0 2 6.3
19 ... 19 59% 58.8 86 20 18 5 0 15 6.2
20 ... 18 64% 51.4 78 28 18 12 0 13 4.3
21 ... 0 0% 38.0 38 38 21 7 0 1 3.0
22 ... 0 0% 44.4 55 39 8 0 0 4 3.5
23 ... 7 33% 47.0 66 18 23 7 1 8 4.6
24 ... 0 0% 43.0 43 43 12 6 0 1 7.0
25 ... 11 52% 57.1 79 23 9 2 2 13 4.5
26 ... 15 52% 53.0 81 4 19 7 0 16 4.1
27 ... 6 40% 45.7 71 19 10 5 0 6 4.7
28 ... 6 25% 45.5 76 26 16 2 0 14 4.0
29 ... 1 8% 38.6 52 14 7 1 1 5 3.6
.. ... .. ... ... ... ... ... ... ... ... ...
161 ... 0 0% 40.7 61 28 14 5 0 2 4.3
162 ... 20 61% 54.0 76 21 22 5 0 13 5.3
163 ... 17 57% 51.9 88 11 17 5 0 22 5.8
164 ... 1 25% 39.7 57 29 7 3 0 2 2.8
165 ... 0 0% 29.0 29 29 1 1 0 1 1.0
166 ... 1 33% 43.3 57 30 6 2 0 1 3.5
167 ... 3 16% 36.2 63 2 20 10 1 11 4.4
168 ... 9 35% 47.8 74 10 20 5 0 15 5.2
169 ... 6 50% 48.1 76 11 7 1 0 8 4.2
170 ... 0 0% 22.3 34 13 8 3 0 2 3.0
171 ... 1 25% 35.8 61 17 7 4 1 1 8.4
172 ... 0 0% 42.0 42 42 0 0 0 1 10.1
173 ... 1 33% 33.7 61 17 7 4 1 0 7.8
174 ... 16 50% 50.7 78 16 11 2 0 16 4.5
175 ... 0 0% 46.0 58 27 0 0 1 1 2.7
176 ... 0 0% 35.5 52 19 8 2 0 1 3.5
177 ... 23 70% 57.8 88 7 20 7 0 15 4.9
178 ... 18 64% 55.0 83 7 20 7 0 13 4.9
179 ... 5 100% 73.6 88 62 0 0 0 2 5.4
180 ... 1 50% 42.5 52 33 0 0 0 0 2.0
181 ... 0 0% 51.0 51 51 0 0 0 1 2.0
182 ... 0 0% 32.0 32 32 0 0 0 1 0.0
183 ... 0 0% 19.0 19 19 2 0 0 1 3.0
184 ... 1 100% 49.0 49 49 3 1 0 1 8.0
185 ... 0 0% 34.3 44 22 11 5 0 2 5.0
186 ... 0 0% 52.0 62 42 2 2 0 2 1.0
187 ... 1 20% 34.0 49 7 4 2 0 2 4.1
188 ... 1 25% 47.5 69 35 3 1 0 3 2.6
189 ... 0 0% 29.0 31 27 2 0 0 1 7.2
190 ... 11 38% 42.3 71 16 14 4 0 16 4.9
[191 rows x 29 columns]
Unnamed: 0 1
Name Tim Adleman
Age 29
Tm CIN
IP 122.1
G 30
GS 20
Wgs 5
Lgs 9
ND 6
Wchp 2
Ltuf 1
Wtm 8
Ltm 12
tmW-L% 0.4
Wist 2
Lsv 1
CG 0
SHO 0
QS 7
QS% 35%
GmScA 46.8
Best 82
Wrst 25
BQR 9
BQS 5
sDR 0
IDR 8
RS/GS 5.1
RS/IP 4.8
IP/GS 5.3
Pit/GS 90
<80 3
80-99 13
100-119 4
≥120 0
Max 110
Name: 0, dtype: object
Unnamed: 0 1
Name Andrew Albers*
Age 31
Tm SEA
IP 41
G 9
GS 6
Wgs 4
Lgs 1
ND 1
Wchp 2
Ltuf 0
Wtm 5
Ltm 1
tmW-L% 0.833
Wist 0
Lsv 1
CG 0
SHO 0
QS 2
QS% 33%
GmScA 50.3
Best 70
Wrst 25
BQR 7
BQS 5
sDR 0
IDR 5
RS/GS 6
Name: 0, dtype: object