我有一个CSV文件，我正在使用pandas加载到一个表中。
Rank Player Nat Tot MtchWin-Loss Tie BrkWin-Loss \
0 1 Novak Djokovic SRB 5-0 0-0
1 2 Roger Federer SUI 1-1 0-1
2 3 Andy Murray GBR 0-0 0-0
3 4 Rafael Nadal ESP 11-3 2-1
4 5 Kei Nishikori JPN 5-0 0-0
5 6 Milos Raonic CAN 2-1 1-0
6 7 Tomas Berdych CZE 4-1 2-0
7 8 David Ferrer ESP 10-2 2-2
8 9 Stan Wawrinka SUI 1-1 0-0
9 10 Marin Cilic CRO 2-2 1-0
10 11 Grigor Dimitrov BUL 3-1 0-0
11 12 Feliciano Lopez ESP 5-3 4-1
12 13 Gilles Simon FRA 3-2 2-0
13 14 Jo-Wilfried Tsonga FRA 2-2 0-1
14 15 Gael Monfils FRA 6-2 5-0
15 16 Roberto Bautista Agut ESP 4-3 2-2
16 17 Kevin Anderson RSA 2-1 1-3
17 18 John Isner USA 2-2 2-2
18 19 Tommy Robredo ESP 6-5 0-2
19 20 Ernests Gulbis LAT 0-2 0-0
20 21 David Goffin BEL 1-1 0-0
21 22 Ivo Karlovic CRO 1-1 0-0
22 23 Pablo Cuevas URU 10-4 4-2
23 24 Martin Klizan SVK 10-5 3-1
24 25 Leonardo Mayer ARG 4-4 2-1
25 26 Philipp Kohlschreiber GER 3-2 3-2
26 27 Bernard Tomic AUS 1-1 1-1
27 28 Richard Gasquet FRA 0-0 0-0
28 29 Fabio Fognini ITA 8-5 3-2
29 30 Adrian Mannarino FRA 0-1 0-0
.. ... ... ... ... ...
170 171 Elias Ymer SWE 2-2 1-1
171 172 Renzo Olivo ARG 2-2 2-1
172 173 Tommy Haas GER 0-0 0-0
173 174 Nicolas Almagro ESP 8-5 3-2
174 175 Alex Bolt AUS 0-0 0-0
175 176 Mate Delic CRO 0-0 0-0
176 177 Liam Broady GBR 0-0 0-0
177 178 Maxime Authom BEL 0-0 0-0
178 179 Roberto Marcora ITA 0-0 0-0
179 180 Marius Copil ROU 0-1 0-0
180 181 Lukasz Kubot POL 0-0 0-0
181 182 Guilherme Clezar BRA 0-3 0-1
182 183 Ruben Ramirez Hidalgo ESP 0-0 0-0
183 184 Andrej Martin SVK 0-0 0-0
184 185 Andrea Arnaboldi ITA 0-0 0-0
185 186 Gerald Melzer AUT 1-1 2-1
186 187 Jan Hernych CZE 0-0 0-0
187 188 Julian Reister GER 0-0 0-0
188 189 Nicolas Jarry CHI 3-1 1-0
189 190 Mirza Basic BIH 0-0 0-0
190 191 Filippo Volandri ITA 0-0 0-0
191 192 Dennis Novikov USA 0-0 0-0
192 193 Denys Molchanov UKR 0-0 0-0
193 194 Jason Jung USA 0-0 0-0
194 195 Luke Saville AUS 0-0 0-0
195 196 Evgeny Donskoy RUS 0-1 0-1
196 197 Adrian Ungur ROU 0-0 0-0
197 198 Hans Podlipnik-Castillo CHI 1-0 0-0
198 199 Thomas Fabbiano ITA 0-1 0-0
199 200 Tim Puetz GER 0-0 0-0
Tot Aces Ace/ Mtch Avg Tot Dbl Flts DF/ Mtch Avg 1st Srv 1st Srv Won \
0 9 1.8 7 1.4 62% 74%
1 9 4.5 2 1.0 59% 68%
2 0 0.0 0 0.0 0% 0%
3 25 1.8 18 1.3 68% 69%
4 14 2.8 9 1.8 57% 75%
5 16 5.3 3 1.0 64% 78%
6 18 3.6 8 1.6 53% 81%
7 18 1.5 32 2.7 62% 66%
8 2 1.0 2 1.0 58% 64%
9 20 5.0 5 1.3 60% 72%
10 12 3.0 5 1.3 63% 74%
11 66 8.3 23 2.9 60% 74%
12 14 2.8 13 2.6 64% 63%
13 13 3.3 5 1.3 59% 70%
14 32 4.0 5 0.6 63% 69%
15 16 2.3 13 1.9 64% 73%
16 40 13.3 9 3.0 65% 74%
17 49 12.3 6 1.5 68% 77%
18 41 3.7 20 1.8 66% 72%
19 9 4.5 15 7.5 52% 67%
20 9 4.5 7 3.5 51% 67%
21 23 11.5 4 2.0 71% 86%
22 78 6.5 22 1.8 56% 74%
23 49 3.1 54 3.4 59% 70%
24 41 6.8 13 2.2 64% 71%
25 10 1.7 5 0.8 65% 61%
26 11 3.7 2 0.7 70% 66%
27 0 0.0 0 0.0 0% 0%
28 41 2.9 35 2.5 57% 65%
29 0 0.0 2 2.0 64% 47%
.. ... ... ... ... ... ...
170 12 3.0 6 1.5 58% 65%
171 9 2.3 36 9.0 57% 71%
172 0 0.0 0 0.0 0% 0%
173 81 5.8 25 1.8 56% 75%
174 0 0.0 0 0.0 0% 0%
175 0 0.0 0 0.0 0% 0%
176 0 0.0 0 0.0 0% 0%
177 0 0.0 0 0.0 0% 0%
178 0 0.0 0 0.0 0% 0%
179 8 8.0 2 2.0 60% 78%
180 0 0.0 0 0.0 0% 0%
181 11 3.7 10 3.3 61% 64%
182 0 0.0 0 0.0 0% 0%
183 0 0.0 0 0.0 0% 0%
184 0 0.0 0 0.0 0% 0%
185 11 5.5 6 3.0 58% 75%
186 0 0.0 0 0.0 0% 0%
187 0 0.0 0 0.0 0% 0%
188 25 12.5 10 5.0 60% 72%
189 0 0.0 0 0.0 0% 0%
190 0 0.0 0 0.0 0% 0%
191 0 0.0 0 0.0 0% 0%
192 0 0.0 0 0.0 0% 0%
193 0 0.0 0 0.0 0% 0%
194 0 0.0 0 0.0 0% 0%
195 1 1.0 9 9.0 52% 70%
196 0 0.0 0 0.0 0% 0%
197 0 0.0 0 0.0 0% 0%
198 3 3.0 4 4.0 73% 61%
199 0 0.0 0 0.0 0% 0%
2nd Srv Won Srv Gam Won Brk Pts Won Brk Pts Svd Pts Won Ret Srv1st-2nd \
0 58% 88% 42% 68% 39%-57%
1 54% 84% 46% 67% 37%-49%
2 0% 0% 0% 0% 0%-0%
3 57% 82% 43% 57% 36%-58%
4 62% 92% 49% 80% 39%-62%
5 62% 90% 25% 50% 26%-46%
6 52% 82% 47% 68% 37%-49%
7 54% 78% 47% 61% 40%-56%
8 50% 59% 25% 46% 41%-47%
9 49% 74% 43% 58% 26%-43%
10 49% 85% 38% 79% 35%-48%
11 54% 82% 42% 65% 28%-50%
12 47% 68% 56% 63% 31%-56%
13 58% 87% 31% 78% 26%-45%
14 53% 82% 42% 68% 31%-51%
15 48% 80% 53% 62% 29%-53%
16 47% 83% 55% 68% 35%-47%
17 56% 91% 25% 75% 26%-39%
18 52% 82% 42% 65% 32%-48%
19 32% 50% 33% 50% 29%-39%
20 55% 76% 38% 69% 38%-52%
21 43% 88% 22% 25% 21%-45%
22 54% 82% 49% 63% 32%-47%
23 48% 76% 43% 63% 31%-49%
24 50% 81% 23% 65% 31%-57%
25 52% 67% 48% 51% 35%-54%
26 47% 73% 38% 58% 33%-52%
27 0% 0% 0% 0% 0%-0%
28 49% 67% 49% 61% 32%-54%
29 41% 29% 33% 50% 26%-38%
.. ... ... ... ... ...
170 50% 69% 38% 60% 30%-55%
171 51% 79% 27% 62% 29%-51%
172 0% 0% 0% 0% 0%-0%
173 55% 82% 32% 59% 32%-47%
174 0% 0% 0% 0% 0%-0%
175 0% 0% 0% 0% 0%-0%
176 0% 0% 0% 0% 0%-0%
177 0% 0% 0% 0% 0%-0%
178 0% 0% 0% 0% 0%-0%
179 56% 77% 43% 40% 36%-39%
180 0% 0% 0% 0% 0%-0%
181 44% 67% 39% 50% 24%-53%
182 0% 0% 0% 0% 0%-0%
183 0% 0% 0% 0% 0%-0%
184 0% 0% 0% 0% 0%-0%
185 43% 77% 14% 73% 21%-51%
186 0% 0% 0% 0% 0%-0%
187 0% 0% 0% 0% 0%-0%
188 62% 86% 38% 75% 25%-43%
189 0% 0% 0% 0% 0%-0%
190 0% 0% 0% 0% 0%-0%
191 0% 0% 0% 0% 0%-0%
192 0% 0% 0% 0% 0%-0%
193 0% 0% 0% 0% 0%-0%
194 0% 0% 0% 0% 0%-0%
195 52% 79% 18% 70% 28%-42%
196 0% 0% 0% 0% 0%-0%
197 0% 0% 0% 0% 0%-0%
198 39% 60% 17% 43% 22%-45%
199 0% 0% 0% 0% 0%-0%
Ret Gam Won
0 46%
1 33%
2 0%
3 38%
4 42%
5 12%
6 30%
7 42%
8 33%
9 15%
10 25%
11 20%
12 31%
13 13%
14 24%
15 26%
16 26%
17 8%
18 27%
19 16%
20 32%
21 8%
22 25%
23 25%
24 21%
25 36%
26 32%
27 0%
28 31%
29 13%
.. ...
170 23%
171 17%
172 0%
173 22%
174 0%
175 0%
176 0%
177 0%
178 0%
179 23%
180 0%
181 22%
182 0%
183 0%
184 0%
185 11%
186 0%
187 0%
188 11%
189 0%
190 0%
191 0%
192 0%
193 0%
194 0%
195 14%
196 0%
197 0%
198 11%
199 0%
我不确定为什么它会出现在不同的路线上，理想情况下我希望看到它一直横向移动，但这不是一个大问题。我想要做的是根据标准从细胞中获取某些数据。例如，我这样做是为了获得Novak Djokovic的第一个服务百分比：
firstServePecentage = df[["1st Srv"]][df['Player'] == 'Novak Djokovic']
返回：
1st Srv
0 62%
如您所见，这会获取列名和行名。我怎样才能得到62％的值，所以我可以将它转换为十进制，0.62，并且能够将它分配给我可用于计算的变量？
答案 0 :(得分：2)
如果你只想要值，那么返回的是一个系列：
firstServePecentage = df[df['Player'] == 'Novak Djokovic']['1st Srv']
firstServePecentage.values[0]