Format: application/octet-stream
1 {
2 "cells": [
3 {
4 "cell_type": "code",
5 "execution_count": 1,
6 "id": "0d675eea",
7 "metadata": {},
8 "outputs": [],
9 "source": [
10 "import pandas as pd"
11 ]
12 },
13 {
14 "cell_type": "code",
15 "execution_count": 2,
16 "id": "2ad4bc87",
17 "metadata": {},
18 "outputs": [],
19 "source": [
20 "df= pd.read_csv('question 3.csv')"
21 ]
22 },
23 {
24 "cell_type": "code",
25 "execution_count": 3,
26 "id": "ea5423e9",
27 "metadata": {},
28 "outputs": [
29 {
30 "name": "stdout",
31 "output_type": "stream",
32 "text": [
33 "<class 'pandas.core.frame.DataFrame'>\n",
34 "RangeIndex: 16 entries, 0 to 15\n",
35 "Data columns (total 35 columns):\n",
36 " # Column Non-Null Count Dtype \n",
37 "--- ------ -------------- ----- \n",
38 " 0 Team 16 non-null object \n",
39 " 1 Goals 16 non-null int64 \n",
40 " 2 Shots on target 16 non-null int64 \n",
41 " 3 Shots off target 16 non-null int64 \n",
42 " 4 Shooting Accuracy 16 non-null object \n",
43 " 5 % Goals-to-shots 16 non-null object \n",
44 " 6 Total shots (inc. Blocked) 16 non-null int64 \n",
45 " 7 Hit Woodwork 16 non-null int64 \n",
46 " 8 Penalty goals 16 non-null int64 \n",
47 " 9 Penalties not scored 16 non-null int64 \n",
48 " 10 Headed goals 16 non-null int64 \n",
49 " 11 Passes 16 non-null int64 \n",
50 " 12 Passes completed 16 non-null int64 \n",
51 " 13 Passing Accuracy 16 non-null object \n",
52 " 14 Touches 16 non-null int64 \n",
53 " 15 Crosses 16 non-null int64 \n",
54 " 16 Dribbles 16 non-null int64 \n",
55 " 17 Corners Taken 16 non-null int64 \n",
56 " 18 Tackles 16 non-null int64 \n",
57 " 19 Clearances 16 non-null int64 \n",
58 " 20 Interceptions 16 non-null int64 \n",
59 " 21 Clearances off line 15 non-null float64\n",
60 " 22 Clean Sheets 16 non-null int64 \n",
61 " 23 Blocks 16 non-null int64 \n",
62 " 24 Goals conceded 16 non-null int64 \n",
63 " 25 Saves made 16 non-null int64 \n",
64 " 26 Saves-to-shots ratio 16 non-null object \n",
65 " 27 Fouls Won 16 non-null int64 \n",
66 " 28 Fouls Conceded 16 non-null int64 \n",
67 " 29 Offsides 16 non-null int64 \n",
68 " 30 Yellow Cards 16 non-null int64 \n",
69 " 31 Red Cards 16 non-null int64 \n",
70 " 32 Subs on 16 non-null int64 \n",
71 " 33 Subs off 16 non-null int64 \n",
72 " 34 Players Used 16 non-null int64 \n",
73 "dtypes: float64(1), int64(29), object(5)\n",
74 "memory usage: 4.5+ KB\n"
75 ]
76 }
77 ],
78 "source": [
79 "df.info()"
80 ]
81 },
82 {
83 "cell_type": "code",
84 "execution_count": 4,
85 "id": "f0342c19",
86 "metadata": {},
87 "outputs": [
88 {
89 "data": {
90 "text/html": [
91 "<div>\n",
92 "<style scoped>\n",
93 " .dataframe tbody tr th:only-of-type {\n",
94 " vertical-align: middle;\n",
95 " }\n",
96 "\n",
97 " .dataframe tbody tr th {\n",
98 " vertical-align: top;\n",
99 " }\n",
100 "\n",
101 " .dataframe thead th {\n",
102 " text-align: right;\n",
103 " }\n",
104 "</style>\n",
105 "<table border=\"1\" class=\"dataframe\">\n",
106 " <thead>\n",
107 " <tr style=\"text-align: right;\">\n",
108 " <th></th>\n",
109 " <th>Team</th>\n",
110 " <th>Goals</th>\n",
111 " <th>Shots on target</th>\n",
112 " <th>Shots off target</th>\n",
113 " <th>Shooting Accuracy</th>\n",
114 " <th>% Goals-to-shots</th>\n",
115 " <th>Total shots (inc. Blocked)</th>\n",
116 " <th>Hit Woodwork</th>\n",
117 " <th>Penalty goals</th>\n",
118 " <th>Penalties not scored</th>\n",
119 " <th>...</th>\n",
120 " <th>Saves made</th>\n",
121 " <th>Saves-to-shots ratio</th>\n",
122 " <th>Fouls Won</th>\n",
123 " <th>Fouls Conceded</th>\n",
124 " <th>Offsides</th>\n",
125 " <th>Yellow Cards</th>\n",
126 " <th>Red Cards</th>\n",
127 " <th>Subs on</th>\n",
128 " <th>Subs off</th>\n",
129 " <th>Players Used</th>\n",
130 " </tr>\n",
131 " </thead>\n",
132 " <tbody>\n",
133 " <tr>\n",
134 " <th>0</th>\n",
135 " <td>Croatia</td>\n",
136 " <td>4</td>\n",
137 " <td>13</td>\n",
138 " <td>12</td>\n",
139 " <td>51.9%</td>\n",
140 " <td>16.0%</td>\n",
141 " <td>32</td>\n",
142 " <td>0</td>\n",
143 " <td>0</td>\n",
144 " <td>0</td>\n",
145 " <td>...</td>\n",
146 " <td>13</td>\n",
147 " <td>81.3%</td>\n",
148 " <td>41</td>\n",
149 " <td>62</td>\n",
150 " <td>2</td>\n",
151 " <td>9</td>\n",
152 " <td>0</td>\n",
153 " <td>9</td>\n",
154 " <td>9</td>\n",
155 " <td>16</td>\n",
156 " </tr>\n",
157 " <tr>\n",
158 " <th>1</th>\n",
159 " <td>Czech Republic</td>\n",
160 " <td>4</td>\n",
161 " <td>13</td>\n",
162 " <td>18</td>\n",
163 " <td>41.9%</td>\n",
164 " <td>12.9%</td>\n",
165 " <td>39</td>\n",
166 " <td>0</td>\n",
167 " <td>0</td>\n",
168 " <td>0</td>\n",
169 " <td>...</td>\n",
170 " <td>9</td>\n",
171 " <td>60.1%</td>\n",
172 " <td>53</td>\n",
173 " <td>73</td>\n",
174 " <td>8</td>\n",
175 " <td>7</td>\n",
176 " <td>0</td>\n",
177 " <td>11</td>\n",
178 " <td>11</td>\n",
179 " <td>19</td>\n",
180 " </tr>\n",
181 " <tr>\n",
182 " <th>2</th>\n",
183 " <td>Denmark</td>\n",
184 " <td>4</td>\n",
185 " <td>10</td>\n",
186 " <td>10</td>\n",
187 " <td>50.0%</td>\n",
188 " <td>20.0%</td>\n",
189 " <td>27</td>\n",
190 " <td>1</td>\n",
191 " <td>0</td>\n",
192 " <td>0</td>\n",
193 " <td>...</td>\n",
194 " <td>10</td>\n",
195 " <td>66.7%</td>\n",
196 " <td>25</td>\n",
197 " <td>38</td>\n",
198 " <td>8</td>\n",
199 " <td>4</td>\n",
200 " <td>0</td>\n",
201 " <td>7</td>\n",
202 " <td>7</td>\n",
203 " <td>15</td>\n",
204 " </tr>\n",
205 " <tr>\n",
206 " <th>3</th>\n",
207 " <td>England</td>\n",
208 " <td>5</td>\n",
209 " <td>11</td>\n",
210 " <td>18</td>\n",
211 " <td>50.0%</td>\n",
212 " <td>17.2%</td>\n",
213 " <td>40</td>\n",
214 " <td>0</td>\n",
215 " <td>0</td>\n",
216 " <td>0</td>\n",
217 " <td>...</td>\n",
218 " <td>22</td>\n",
219 " <td>88.1%</td>\n",
220 " <td>43</td>\n",
221 " <td>45</td>\n",
222 " <td>6</td>\n",
223 " <td>5</td>\n",
224 " <td>0</td>\n",
225 " <td>11</td>\n",
226 " <td>11</td>\n",
227 " <td>16</td>\n",
228 " </tr>\n",
229 " <tr>\n",
230 " <th>4</th>\n",
231 " <td>France</td>\n",
232 " <td>3</td>\n",
233 " <td>22</td>\n",
234 " <td>24</td>\n",
235 " <td>37.9%</td>\n",
236 " <td>6.5%</td>\n",
237 " <td>65</td>\n",
238 " <td>1</td>\n",
239 " <td>0</td>\n",
240 " <td>0</td>\n",
241 " <td>...</td>\n",
242 " <td>6</td>\n",
243 " <td>54.6%</td>\n",
244 " <td>36</td>\n",
245 " <td>51</td>\n",
246 " <td>5</td>\n",
247 " <td>6</td>\n",
248 " <td>0</td>\n",
249 " <td>11</td>\n",
250 " <td>11</td>\n",
251 " <td>19</td>\n",
252 " </tr>\n",
253 " </tbody>\n",
254 "</table>\n",
255 "<p>5 rows × 35 columns</p>\n",
256 "</div>"
257 ],
258 "text/plain": [
259 " Team Goals Shots on target Shots off target Shooting Accuracy \\\n",
260 "0 Croatia 4 13 12 51.9% \n",
261 "1 Czech Republic 4 13 18 41.9% \n",
262 "2 Denmark 4 10 10 50.0% \n",
263 "3 England 5 11 18 50.0% \n",
264 "4 France 3 22 24 37.9% \n",
265 "\n",
266 " % Goals-to-shots Total shots (inc. Blocked) Hit Woodwork Penalty goals \\\n",
267 "0 16.0% 32 0 0 \n",
268 "1 12.9% 39 0 0 \n",
269 "2 20.0% 27 1 0 \n",
270 "3 17.2% 40 0 0 \n",
271 "4 6.5% 65 1 0 \n",
272 "\n",
273 " Penalties not scored ... Saves made Saves-to-shots ratio Fouls Won \\\n",
274 "0 0 ... 13 81.3% 41 \n",
275 "1 0 ... 9 60.1% 53 \n",
276 "2 0 ... 10 66.7% 25 \n",
277 "3 0 ... 22 88.1% 43 \n",
278 "4 0 ... 6 54.6% 36 \n",
279 "\n",
280 " Fouls Conceded Offsides Yellow Cards Red Cards Subs on Subs off \\\n",
281 "0 62 2 9 0 9 9 \n",
282 "1 73 8 7 0 11 11 \n",
283 "2 38 8 4 0 7 7 \n",
284 "3 45 6 5 0 11 11 \n",
285 "4 51 5 6 0 11 11 \n",
286 "\n",
287 " Players Used \n",
288 "0 16 \n",
289 "1 19 \n",
290 "2 15 \n",
291 "3 16 \n",
292 "4 19 \n",
293 "\n",
294 "[5 rows x 35 columns]"
295 ]
296 },
297 "execution_count": 4,
298 "metadata": {},
299 "output_type": "execute_result"
300 }
301 ],
302 "source": [
303 "df.head()"
304 ]
305 },
306 {
307 "cell_type": "code",
308 "execution_count": 5,
309 "id": "4d59c089",
310 "metadata": {},
311 "outputs": [],
312 "source": [
313 "df=df.loc[:,['Team', \"Red Cards\", 'Yellow Cards']]"
314 ]
315 },
316 {
317 "cell_type": "code",
318 "execution_count": 6,
319 "id": "ebcac1e3",
320 "metadata": {},
321 "outputs": [
322 {
323 "data": {
324 "text/html": [
325 "<div>\n",
326 "<style scoped>\n",
327 " .dataframe tbody tr th:only-of-type {\n",
328 " vertical-align: middle;\n",
329 " }\n",
330 "\n",
331 " .dataframe tbody tr th {\n",
332 " vertical-align: top;\n",
333 " }\n",
334 "\n",
335 " .dataframe thead th {\n",
336 " text-align: right;\n",
337 " }\n",
338 "</style>\n",
339 "<table border=\"1\" class=\"dataframe\">\n",
340 " <thead>\n",
341 " <tr style=\"text-align: right;\">\n",
342 " <th></th>\n",
343 " <th>Team</th>\n",
344 " <th>Red Cards</th>\n",
345 " <th>Yellow Cards</th>\n",
346 " </tr>\n",
347 " </thead>\n",
348 " <tbody>\n",
349 " <tr>\n",
350 " <th>6</th>\n",
351 " <td>Greece</td>\n",
352 " <td>1</td>\n",
353 " <td>9</td>\n",
354 " </tr>\n",
355 " <tr>\n",
356 " <th>9</th>\n",
357 " <td>Poland</td>\n",
358 " <td>1</td>\n",
359 " <td>7</td>\n",
360 " </tr>\n",
361 " <tr>\n",
362 " <th>11</th>\n",
363 " <td>Republic of Ireland</td>\n",
364 " <td>1</td>\n",
365 " <td>6</td>\n",
366 " </tr>\n",
367 " <tr>\n",
368 " <th>7</th>\n",
369 " <td>Italy</td>\n",
370 " <td>0</td>\n",
371 " <td>16</td>\n",
372 " </tr>\n",
373 " <tr>\n",
374 " <th>10</th>\n",
375 " <td>Portugal</td>\n",
376 " <td>0</td>\n",
377 " <td>12</td>\n",
378 " </tr>\n",
379 " <tr>\n",
380 " <th>13</th>\n",
381 " <td>Spain</td>\n",
382 " <td>0</td>\n",
383 " <td>11</td>\n",
384 " </tr>\n",
385 " <tr>\n",
386 " <th>0</th>\n",
387 " <td>Croatia</td>\n",
388 " <td>0</td>\n",
389 " <td>9</td>\n",
390 " </tr>\n",
391 " <tr>\n",
392 " <th>1</th>\n",
393 " <td>Czech Republic</td>\n",
394 " <td>0</td>\n",
395 " <td>7</td>\n",
396 " </tr>\n",
397 " <tr>\n",
398 " <th>14</th>\n",
399 " <td>Sweden</td>\n",
400 " <td>0</td>\n",
401 " <td>7</td>\n",
402 " </tr>\n",
403 " <tr>\n",
404 " <th>4</th>\n",
405 " <td>France</td>\n",
406 " <td>0</td>\n",
407 " <td>6</td>\n",
408 " </tr>\n",
409 " <tr>\n",
410 " <th>12</th>\n",
411 " <td>Russia</td>\n",
412 " <td>0</td>\n",
413 " <td>6</td>\n",
414 " </tr>\n",
415 " <tr>\n",
416 " <th>3</th>\n",
417 " <td>England</td>\n",
418 " <td>0</td>\n",
419 " <td>5</td>\n",
420 " </tr>\n",
421 " <tr>\n",
422 " <th>8</th>\n",
423 " <td>Netherlands</td>\n",
424 " <td>0</td>\n",
425 " <td>5</td>\n",
426 " </tr>\n",
427 " <tr>\n",
428 " <th>15</th>\n",
429 " <td>Ukraine</td>\n",
430 " <td>0</td>\n",
431 " <td>5</td>\n",
432 " </tr>\n",
433 " <tr>\n",
434 " <th>2</th>\n",
435 " <td>Denmark</td>\n",
436 " <td>0</td>\n",
437 " <td>4</td>\n",
438 " </tr>\n",
439 " <tr>\n",
440 " <th>5</th>\n",
441 " <td>Germany</td>\n",
442 " <td>0</td>\n",
443 " <td>4</td>\n",
444 " </tr>\n",
445 " </tbody>\n",
446 "</table>\n",
447 "</div>"
448 ],
449 "text/plain": [
450 " Team Red Cards Yellow Cards\n",
451 "6 Greece 1 9\n",
452 "9 Poland 1 7\n",
453 "11 Republic of Ireland 1 6\n",
454 "7 Italy 0 16\n",
455 "10 Portugal 0 12\n",
456 "13 Spain 0 11\n",
457 "0 Croatia 0 9\n",
458 "1 Czech Republic 0 7\n",
459 "14 Sweden 0 7\n",
460 "4 France 0 6\n",
461 "12 Russia 0 6\n",
462 "3 England 0 5\n",
463 "8 Netherlands 0 5\n",
464 "15 Ukraine 0 5\n",
465 "2 Denmark 0 4\n",
466 "5 Germany 0 4"
467 ]
468 },
469 "execution_count": 6,
470 "metadata": {},
471 "output_type": "execute_result"
472 }
473 ],
474 "source": [
475 "df=df.sort_values(by=['Red Cards','Yellow Cards'], ascending=[False, False])\n",
476 "df"
477 ]
478 },
479 {
480 "cell_type": "code",
481 "execution_count": 7,
482 "id": "a6a32a56",
483 "metadata": {},
484 "outputs": [],
485 "source": [
486 "df.to_csv('answer3.csv')"
487 ]
488 },
489 {
490 "cell_type": "code",
491 "execution_count": null,
492 "id": "bb308577",
493 "metadata": {},
494 "outputs": [],
495 "source": []
496 }
497 ],
498 "metadata": {
499 "kernelspec": {
500 "display_name": "Python 3",
501 "language": "python",
502 "name": "python3"
503 },
504 "language_info": {
505 "codemirror_mode": {
506 "name": "ipython",
507 "version": 3
508 },
509 "file_extension": ".py",
510 "mimetype": "text/x-python",
511 "name": "python",
512 "nbconvert_exporter": "python",
513 "pygments_lexer": "ipython3",
514 "version": "3.8.8"
515 }
516 },
517 "nbformat": 4,
518 "nbformat_minor": 5
519 }
520