In [7]:
df['age'].plot(kind='hist', figsize=(10, 8))
Out[7]:
<Axes: ylabel='Frequency'>
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.read_csv('players_22.csv',dtype={25: str, 108: str})
we will see the first few rows of the dataframe using df.head(), if we want to check the last few rows then we will use df.tail(),
After that, we will check the names of columns using df.columns, check the datatype, and values in each column using df.info().
Lastly, to find the statistical features we use df.describe().
df.head()
| sofifa_id | player_url | short_name | long_name | player_positions | overall | potential | value_eur | wage_eur | age | ... | lcb | cb | rcb | rb | gk | player_face_url | club_logo_url | club_flag_url | nation_logo_url | nation_flag_url | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 158023 | https://sofifa.com/player/158023/lionel-messi/... | L. Messi | Lionel Andrés Messi Cuccittini | RW, ST, CF | 93 | 93 | 78000000.0 | 320000.0 | 34 | ... | 50+3 | 50+3 | 50+3 | 61+3 | 19+3 | https://cdn.sofifa.net/players/158/023/22_120.png | https://cdn.sofifa.net/teams/73/60.png | https://cdn.sofifa.net/flags/fr.png | https://cdn.sofifa.net/teams/1369/60.png | https://cdn.sofifa.net/flags/ar.png |
| 1 | 188545 | https://sofifa.com/player/188545/robert-lewand... | R. Lewandowski | Robert Lewandowski | ST | 92 | 92 | 119500000.0 | 270000.0 | 32 | ... | 60+3 | 60+3 | 60+3 | 61+3 | 19+3 | https://cdn.sofifa.net/players/188/545/22_120.png | https://cdn.sofifa.net/teams/21/60.png | https://cdn.sofifa.net/flags/de.png | https://cdn.sofifa.net/teams/1353/60.png | https://cdn.sofifa.net/flags/pl.png |
| 2 | 20801 | https://sofifa.com/player/20801/c-ronaldo-dos-... | Cristiano Ronaldo | Cristiano Ronaldo dos Santos Aveiro | ST, LW | 91 | 91 | 45000000.0 | 270000.0 | 36 | ... | 53+3 | 53+3 | 53+3 | 60+3 | 20+3 | https://cdn.sofifa.net/players/020/801/22_120.png | https://cdn.sofifa.net/teams/11/60.png | https://cdn.sofifa.net/flags/gb-eng.png | https://cdn.sofifa.net/teams/1354/60.png | https://cdn.sofifa.net/flags/pt.png |
| 3 | 190871 | https://sofifa.com/player/190871/neymar-da-sil... | Neymar Jr | Neymar da Silva Santos Júnior | LW, CAM | 91 | 91 | 129000000.0 | 270000.0 | 29 | ... | 50+3 | 50+3 | 50+3 | 62+3 | 20+3 | https://cdn.sofifa.net/players/190/871/22_120.png | https://cdn.sofifa.net/teams/73/60.png | https://cdn.sofifa.net/flags/fr.png | NaN | https://cdn.sofifa.net/flags/br.png |
| 4 | 192985 | https://sofifa.com/player/192985/kevin-de-bruy... | K. De Bruyne | Kevin De Bruyne | CM, CAM | 91 | 91 | 125500000.0 | 350000.0 | 30 | ... | 69+3 | 69+3 | 69+3 | 75+3 | 21+3 | https://cdn.sofifa.net/players/192/985/22_120.png | https://cdn.sofifa.net/teams/10/60.png | https://cdn.sofifa.net/flags/gb-eng.png | https://cdn.sofifa.net/teams/1325/60.png | https://cdn.sofifa.net/flags/be.png |
5 rows × 110 columns
df.columns
Index(['sofifa_id', 'player_url', 'short_name', 'long_name',
'player_positions', 'overall', 'potential', 'value_eur', 'wage_eur',
'age',
...
'lcb', 'cb', 'rcb', 'rb', 'gk', 'player_face_url', 'club_logo_url',
'club_flag_url', 'nation_logo_url', 'nation_flag_url'],
dtype='object', length=110)
df.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 19239 entries, 0 to 19238 Columns: 110 entries, sofifa_id to nation_flag_url dtypes: float64(16), int64(44), object(50) memory usage: 16.1+ MB
df.describe()
| sofifa_id | overall | potential | value_eur | wage_eur | age | height_cm | weight_kg | club_team_id | league_level | ... | mentality_composure | defending_marking_awareness | defending_standing_tackle | defending_sliding_tackle | goalkeeping_diving | goalkeeping_handling | goalkeeping_kicking | goalkeeping_positioning | goalkeeping_reflexes | goalkeeping_speed | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| count | 19239.000000 | 19239.000000 | 19239.000000 | 1.916500e+04 | 19178.000000 | 19239.000000 | 19239.000000 | 19239.000000 | 19178.000000 | 19178.000000 | ... | 19239.000000 | 19239.000000 | 19239.000000 | 19239.000000 | 19239.000000 | 19239.000000 | 19239.000000 | 19239.000000 | 19239.000000 | 2132.000000 |
| mean | 231468.086959 | 65.772182 | 71.079370 | 2.850452e+06 | 9017.989363 | 25.210822 | 181.299704 | 74.943032 | 50580.498123 | 1.354364 | ... | 57.929830 | 46.601746 | 48.045584 | 45.906700 | 16.406102 | 16.192474 | 16.055356 | 16.229274 | 16.491814 | 36.439962 |
| std | 27039.717497 | 6.880232 | 6.086213 | 7.613700e+06 | 19470.176724 | 4.748235 | 6.863179 | 7.069434 | 54401.868535 | 0.747865 | ... | 12.159326 | 20.200807 | 21.232718 | 20.755683 | 17.574028 | 16.839528 | 16.564554 | 17.059779 | 17.884833 | 10.751563 |
| min | 41.000000 | 47.000000 | 49.000000 | 9.000000e+03 | 500.000000 | 16.000000 | 155.000000 | 49.000000 | 1.000000 | 1.000000 | ... | 12.000000 | 4.000000 | 5.000000 | 5.000000 | 2.000000 | 2.000000 | 2.000000 | 2.000000 | 2.000000 | 15.000000 |
| 25% | 214413.500000 | 61.000000 | 67.000000 | 4.750000e+05 | 1000.000000 | 21.000000 | 176.000000 | 70.000000 | 479.000000 | 1.000000 | ... | 50.000000 | 29.000000 | 28.000000 | 25.000000 | 8.000000 | 8.000000 | 8.000000 | 8.000000 | 8.000000 | 27.000000 |
| 50% | 236543.000000 | 66.000000 | 71.000000 | 9.750000e+05 | 3000.000000 | 25.000000 | 181.000000 | 75.000000 | 1938.000000 | 1.000000 | ... | 59.000000 | 52.000000 | 56.000000 | 53.000000 | 11.000000 | 11.000000 | 11.000000 | 11.000000 | 11.000000 | 36.000000 |
| 75% | 253532.500000 | 70.000000 | 75.000000 | 2.000000e+06 | 8000.000000 | 29.000000 | 186.000000 | 80.000000 | 111139.000000 | 1.000000 | ... | 66.000000 | 63.000000 | 65.000000 | 63.000000 | 14.000000 | 14.000000 | 14.000000 | 14.000000 | 14.000000 | 45.000000 |
| max | 264640.000000 | 93.000000 | 95.000000 | 1.940000e+08 | 350000.000000 | 54.000000 | 206.000000 | 110.000000 | 115820.000000 | 5.000000 | ... | 96.000000 | 93.000000 | 93.000000 | 92.000000 | 91.000000 | 92.000000 | 93.000000 | 92.000000 | 90.000000 | 65.000000 |
8 rows × 60 columns
df['age'].plot(kind='hist', figsize=(10, 8))
<Axes: ylabel='Frequency'>
df['overall'].plot(kind='box', vert=False, figsize=(10, 5))
<Axes: >
sns.distplot(df['age']);
/tmp/ipykernel_148/1462740167.py:1: UserWarning: `distplot` is a deprecated function and will be removed in seaborn v0.14.0. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms). For a guide to updating your code to use the new functions, please see https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751 sns.distplot(df['age']);
df['international_reputation'].value_counts().plot(kind='pie', autopct='%1.1f%%', cmap='Set3', figsize=(10, 8))
<Axes: ylabel='count'>
df['nationality_name'].value_counts().head(10).plot(kind='pie', autopct='%1.1f%%', cmap='Set3', figsize=(10, 8))
<Axes: ylabel='count'>
df['work_rate'].value_counts().plot(kind='pie', autopct='%1.1f%%', cmap='Set3', figsize=(10, 8))
<Axes: ylabel='count'>
Below we will do some basic as well as advance filtering on our FIFA Players 22 dataset.
1. Select all the rows and the first 5 columns from the dataframe and store the result in the variable df_first_five_cols
df_first_five_cols = ...
2. Select Specific Columns in a Custom Order
df_order_cols = ...
3. Filter out 50 rows from the Colum number 3,6,4,1 into the variable fifty_rows
fifty_rows = ...
4. Select the all rows and the Columns ['short_name','age','player_positions', 'overall', 'value_eur'] from the dataframe and store your selection in the variable named_cols
named_cols= ...
5. Filter out the first 14 rows and the Columns ['short_name','age','player_positions', 'overall', 'value_eur'] from the dataframe and store the result in the variable named_cols_rows
named_cols_rows = ...
6. Find out how many players of overall rating greater than 90 exists in the dataset?
7. Find out how many players of value_eur of less than or equal to 20000 in the dataset?
8. Select the long_name and age of the players having the club_name='Manchester City' and store your selection in the variable name long_name_age
long_name_age = df[df['club_name']=='Manchester City'][['long_name','age']]
long_name_age
| long_name | age | |
|---|---|---|
| 4 | Kevin De Bruyne | 30 |
| 18 | Ederson Santana de Moraes | 27 |
| 27 | Raheem Sterling | 26 |
| 46 | Rúben dos Santos Gato Alves Dias | 24 |
| 58 | Riyad Mahrez | 30 |
| 62 | João Pedro Cavaco Cancelo | 27 |
| 63 | Aymeric Laporte | 27 |
| 65 | Bernardo Mota Veiga de Carvalho e Silva | 26 |
| 67 | Rodrigo Hernández Cascante | 25 |
| 78 | İlkay Gündoğan | 30 |
| 80 | Kyle Walker | 31 |
| 118 | Jack Grealish | 25 |
| 139 | Philip Foden | 21 |
| 140 | Fernando Luiz Rosa | 36 |
| 166 | John Stones | 27 |
| 191 | Gabriel Fernando de Jesus | 24 |
| 280 | Ferran Torres García | 21 |
| 477 | Oleksandr Zinchenko | 24 |
| 569 | Benjamin Mendy | 26 |
| 745 | Nathan Aké | 26 |
| 1075 | Zack Thomas Steffen | 26 |
| 7487 | Scott Carson | 35 |
| 9771 | Kayky da Silva Chagas | 18 |
| 11543 | Luke Bolton | 21 |
| 12055 | Cole Palmer | 19 |
| 12095 | Liam Delap | 18 |
| 12113 | Jayden Jezairo Braaf | 18 |
| 14275 | Luke Mbete | 17 |
| 14349 | Romeo Lavia | 17 |
| 14364 | Samuel Edozie | 18 |
| 15157 | James McAtee | 18 |
| 17084 | Iker Pozo La Rosa | 20 |
9. Filter out the players of Liverpool club and who are from Brazil and store them in the variable liverpool_brazil
Note: club_name & nationality_name are the column names
liverpool_brazil = df[(df['nationality_name'] == 'Brazil') & (df['club_name'] == 'Liverpool')]
liverpool_brazil
| sofifa_id | player_url | short_name | long_name | player_positions | overall | potential | value_eur | wage_eur | age | ... | lcb | cb | rcb | rb | gk | player_face_url | club_logo_url | club_flag_url | nation_logo_url | nation_flag_url | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 20 | 212831 | https://sofifa.com/player/212831/alisson-ramse... | Alisson | Alisson Ramsés Becker | GK | 89 | 90 | 82000000.0 | 190000.0 | 28 | ... | 31+3 | 31+3 | 31+3 | 30+3 | 87+3 | https://cdn.sofifa.net/players/212/831/22_120.png | https://cdn.sofifa.net/teams/9/60.png | https://cdn.sofifa.net/flags/gb-eng.png | NaN | https://cdn.sofifa.net/flags/br.png |
| 61 | 209499 | https://sofifa.com/player/209499/fabio-henriqu... | Fabinho | Fábio Henrique Tavares | CDM, CB | 86 | 88 | 73500000.0 | 165000.0 | 27 | ... | 84+3 | 84+3 | 84+3 | 82+3 | 18+3 | https://cdn.sofifa.net/players/209/499/22_120.png | https://cdn.sofifa.net/teams/9/60.png | https://cdn.sofifa.net/flags/gb-eng.png | NaN | https://cdn.sofifa.net/flags/br.png |
| 85 | 201942 | https://sofifa.com/player/201942/roberto-firmi... | Roberto Firmino | Roberto Firmino Barbosa de Oliveira | CF | 85 | 85 | 54000000.0 | 185000.0 | 29 | ... | 67+3 | 67+3 | 67+3 | 69+3 | 17+3 | https://cdn.sofifa.net/players/201/942/22_120.png | https://cdn.sofifa.net/teams/9/60.png | https://cdn.sofifa.net/flags/gb-eng.png | NaN | https://cdn.sofifa.net/flags/br.png |
| 17275 | 259430 | https://sofifa.com/player/259430/marcelo-pital... | Marcelo Pitaluga | Marcelo Pitaluga | GK | 57 | 78 | 475000.0 | 1000.0 | 18 | ... | 21+2 | 21+2 | 21+2 | 18+2 | 56+2 | https://cdn.sofifa.net/players/259/430/22_120.png | https://cdn.sofifa.net/teams/9/60.png | https://cdn.sofifa.net/flags/gb-eng.png | NaN | https://cdn.sofifa.net/flags/br.png |
4 rows × 110 columns
10. How many players are there who have either mentality_aggression > 91 or power_stamina < 80
Note: Using query method will be easy
len(df.query("mentality_aggression > 91 or power_stamina < 80"))
16919
11. Select all players from France who have either mentality_aggression > 91 or power_stamina < 80 and store the filtered data in the variable france_player
france_player = df.loc[(df['nationality_name'] == 'France') & ((df["mentality_aggression"] > 91) | (df["power_stamina"] < 80))]
france_player
| sofifa_id | player_url | short_name | long_name | player_positions | overall | potential | value_eur | wage_eur | age | ... | lcb | cb | rcb | rb | gk | player_face_url | club_logo_url | club_flag_url | nation_logo_url | nation_flag_url | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 10 | 215914 | https://sofifa.com/player/215914/ngolo-kante/2... | N. Kanté | N'Golo Kanté | CDM, CM | 90 | 90 | 100000000.0 | 230000.0 | 30 | ... | 84+3 | 84+3 | 84+3 | 85+3 | 20+3 | https://cdn.sofifa.net/players/215/914/22_120.png | https://cdn.sofifa.net/teams/5/60.png | https://cdn.sofifa.net/flags/gb-eng.png | https://cdn.sofifa.net/teams/1335/60.png | https://cdn.sofifa.net/flags/fr.png |
| 11 | 165153 | https://sofifa.com/player/165153/karim-benzema... | K. Benzema | Karim Benzema | CF, ST | 89 | 89 | 66000000.0 | 350000.0 | 33 | ... | 55+3 | 55+3 | 55+3 | 59+3 | 18+3 | https://cdn.sofifa.net/players/165/153/22_120.png | https://cdn.sofifa.net/teams/243/60.png | https://cdn.sofifa.net/flags/es.png | https://cdn.sofifa.net/teams/1335/60.png | https://cdn.sofifa.net/flags/fr.png |
| 31 | 167948 | https://sofifa.com/player/167948/hugo-lloris/2... | H. Lloris | Hugo Lloris | GK | 87 | 87 | 13500000.0 | 125000.0 | 34 | ... | 30+3 | 30+3 | 30+3 | 34+3 | 85+2 | https://cdn.sofifa.net/players/167/948/22_120.png | https://cdn.sofifa.net/teams/18/60.png | https://cdn.sofifa.net/flags/gb-eng.png | https://cdn.sofifa.net/teams/1335/60.png | https://cdn.sofifa.net/flags/fr.png |
| 37 | 195864 | https://sofifa.com/player/195864/paul-pogba/22... | P. Pogba | Paul Pogba | CM, LM | 87 | 87 | 79500000.0 | 220000.0 | 28 | ... | 72+3 | 72+3 | 72+3 | 72+3 | 13+3 | https://cdn.sofifa.net/players/195/864/22_120.png | https://cdn.sofifa.net/teams/11/60.png | https://cdn.sofifa.net/flags/gb-eng.png | https://cdn.sofifa.net/teams/1335/60.png | https://cdn.sofifa.net/flags/fr.png |
| 57 | 201535 | https://sofifa.com/player/201535/raphael-varan... | R. Varane | Raphaël Varane | CB | 86 | 88 | 68500000.0 | 180000.0 | 28 | ... | 85+3 | 85+3 | 85+3 | 80+3 | 18+3 | https://cdn.sofifa.net/players/201/535/22_120.png | https://cdn.sofifa.net/teams/11/60.png | https://cdn.sofifa.net/flags/gb-eng.png | https://cdn.sofifa.net/teams/1335/60.png | https://cdn.sofifa.net/flags/fr.png |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 18375 | 263276 | https://sofifa.com/player/263276/steven-goma/2... | S. Goma | Steven Goma | ST | 54 | 65 | 230000.0 | 750.0 | 19 | ... | 32+2 | 32+2 | 32+2 | 36+2 | 12+2 | https://cdn.sofifa.net/players/263/276/22_120.png | https://cdn.sofifa.net/teams/113391/60.png | https://cdn.sofifa.net/flags/ro.png | NaN | https://cdn.sofifa.net/flags/fr.png |
| 18381 | 263425 | https://sofifa.com/player/263425/adrien-delphi... | A. Delphis | Adrien Delphis | CM | 54 | 66 | 250000.0 | 500.0 | 18 | ... | 46+2 | 46+2 | 46+2 | 50+2 | 16+2 | https://cdn.sofifa.net/players/263/425/22_120.png | https://cdn.sofifa.net/teams/226/60.png | https://cdn.sofifa.net/flags/fr.png | NaN | https://cdn.sofifa.net/flags/fr.png |
| 18424 | 264501 | https://sofifa.com/player/264501/ilyes-hamache... | I. Hamache | Ilyes Hamache | RW | 54 | 69 | 250000.0 | 500.0 | 18 | ... | 27+2 | 27+2 | 27+2 | 34+2 | 10+2 | https://cdn.sofifa.net/players/264/501/22_120.png | https://cdn.sofifa.net/teams/110456/60.png | https://cdn.sofifa.net/flags/fr.png | NaN | https://cdn.sofifa.net/flags/fr.png |
| 18435 | 233645 | https://sofifa.com/player/233645/beni-nkololo/... | B. Nkololo | Béni Nkololo | CAM | 53 | 60 | 190000.0 | 500.0 | 24 | ... | 39+2 | 39+2 | 39+2 | 44+2 | 14+2 | https://cdn.sofifa.net/players/233/645/22_120.png | https://cdn.sofifa.net/teams/111396/60.png | https://cdn.sofifa.net/flags/au.png | NaN | https://cdn.sofifa.net/flags/fr.png |
| 18837 | 263712 | https://sofifa.com/player/263712/melvin-mastil... | M. Mastil | Melvin Mastil | GK | 52 | 62 | 160000.0 | 1000.0 | 21 | ... | 20+2 | 20+2 | 20+2 | 15+2 | 51+2 | https://cdn.sofifa.net/players/263/712/22_120.png | https://cdn.sofifa.net/teams/1862/60.png | https://cdn.sofifa.net/flags/ch.png | NaN | https://cdn.sofifa.net/flags/fr.png |
862 rows × 110 columns
12. How many players have Left foot as their preferred_foot, also print their short_name, and age. Store the result in the variable left_foot_players
left_foot_players = df[df['preferred_foot'] == 'Left']
left_foot_players
| sofifa_id | player_url | short_name | long_name | player_positions | overall | potential | value_eur | wage_eur | age | ... | lcb | cb | rcb | rb | gk | player_face_url | club_logo_url | club_flag_url | nation_logo_url | nation_flag_url | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 158023 | https://sofifa.com/player/158023/lionel-messi/... | L. Messi | Lionel Andrés Messi Cuccittini | RW, ST, CF | 93 | 93 | 78000000.0 | 320000.0 | 34 | ... | 50+3 | 50+3 | 50+3 | 61+3 | 19+3 | https://cdn.sofifa.net/players/158/023/22_120.png | https://cdn.sofifa.net/teams/73/60.png | https://cdn.sofifa.net/flags/fr.png | https://cdn.sofifa.net/teams/1369/60.png | https://cdn.sofifa.net/flags/ar.png |
| 12 | 192119 | https://sofifa.com/player/192119/thibaut-court... | T. Courtois | Thibaut Courtois | GK | 89 | 91 | 85500000.0 | 250000.0 | 29 | ... | 29+3 | 29+3 | 29+3 | 29+3 | 86+3 | https://cdn.sofifa.net/players/192/119/22_120.png | https://cdn.sofifa.net/teams/243/60.png | https://cdn.sofifa.net/flags/es.png | https://cdn.sofifa.net/teams/1325/60.png | https://cdn.sofifa.net/flags/be.png |
| 17 | 209331 | https://sofifa.com/player/209331/mohamed-salah... | M. Salah | Mohamed Salah Ghaly | RW | 89 | 89 | 101000000.0 | 270000.0 | 29 | ... | 58+3 | 58+3 | 58+3 | 67+3 | 22+3 | https://cdn.sofifa.net/players/209/331/22_120.png | https://cdn.sofifa.net/teams/9/60.png | https://cdn.sofifa.net/flags/gb-eng.png | NaN | https://cdn.sofifa.net/flags/eg.png |
| 18 | 210257 | https://sofifa.com/player/210257/ederson-santa... | Ederson | Ederson Santana de Moraes | GK | 89 | 91 | 94000000.0 | 200000.0 | 27 | ... | 35+3 | 35+3 | 35+3 | 36+3 | 87+3 | https://cdn.sofifa.net/players/210/257/22_120.png | https://cdn.sofifa.net/teams/10/60.png | https://cdn.sofifa.net/flags/gb-eng.png | NaN | https://cdn.sofifa.net/flags/br.png |
| 25 | 192505 | https://sofifa.com/player/192505/romelu-lukaku... | R. Lukaku | Romelu Lukaku Menama | ST | 88 | 88 | 93500000.0 | 260000.0 | 28 | ... | 57+3 | 57+3 | 57+3 | 58+3 | 19+3 | https://cdn.sofifa.net/players/192/505/22_120.png | https://cdn.sofifa.net/teams/5/60.png | https://cdn.sofifa.net/flags/gb-eng.png | https://cdn.sofifa.net/teams/1325/60.png | https://cdn.sofifa.net/flags/be.png |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 19198 | 261424 | https://sofifa.com/player/261424/nabin-rabha/2... | N. Rabha | Nabin Rabha | LB | 48 | 52 | 60000.0 | 500.0 | 24 | ... | 45+2 | 45+2 | 45+2 | 46+2 | 17+2 | https://cdn.sofifa.net/players/261/424/22_120.png | https://cdn.sofifa.net/teams/113040/60.png | https://cdn.sofifa.net/flags/in.png | NaN | https://cdn.sofifa.net/flags/in.png |
| 19202 | 261816 | https://sofifa.com/player/261816/joel-bradley-... | J. Bradley-Walsh | Joel Bradley-Walsh | CB | 48 | 61 | 110000.0 | 500.0 | 20 | ... | 48+2 | 48+2 | 48+2 | 42+2 | 13+2 | https://cdn.sofifa.net/players/261/816/22_120.png | https://cdn.sofifa.net/teams/111131/60.png | https://cdn.sofifa.net/flags/ie.png | NaN | https://cdn.sofifa.net/flags/ie.png |
| 19204 | 261887 | https://sofifa.com/player/261887/wenhao-jiang/... | Jiang Wenhao | Wenhao Jiang | CDM, LM, LB | 48 | 58 | 100000.0 | 2000.0 | 21 | ... | 47+2 | 47+2 | 47+2 | 48+2 | 15+2 | https://cdn.sofifa.net/players/261/887/22_120.png | https://cdn.sofifa.net/teams/111768/60.png | https://cdn.sofifa.net/flags/cn.png | NaN | https://cdn.sofifa.net/flags/cn.png |
| 19214 | 262034 | https://sofifa.com/player/262034/robbie-mahon/... | R. Mahon | Robbie Mahon | LW, LM | 48 | 60 | 110000.0 | 500.0 | 18 | ... | 28+2 | 28+2 | 28+2 | 34+2 | 14+2 | https://cdn.sofifa.net/players/262/034/22_120.png | https://cdn.sofifa.net/teams/305/60.png | https://cdn.sofifa.net/flags/ie.png | NaN | https://cdn.sofifa.net/flags/ie.png |
| 19219 | 264150 | https://sofifa.com/player/264150/ebuka-kwelele... | E. Kwelele | Ebuka Kwelele | ST | 48 | 62 | 110000.0 | 500.0 | 19 | ... | 30+2 | 30+2 | 30+2 | 36+2 | 14+2 | https://cdn.sofifa.net/players/264/150/22_120.png | https://cdn.sofifa.net/teams/837/60.png | https://cdn.sofifa.net/flags/ie.png | NaN | https://cdn.sofifa.net/flags/ie.png |
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