import pandas as pd
import numpy as np
from plotnine import *supp-1: FIFA23 자료의 시각화
plotnine
1. 강의영상
2. Imports
3. 예비학습..
A. dropna()
- 결측치가 하나라도 포함된 모든 행을 제거하는 방법
df = pd.DataFrame({
'A': [1,2,3,np.nan,5,6,7],
'B': [11,np.nan,33,np.nan,55,66,77],
'C': [111,222,333,np.nan,555,666,np.nan]})
df| A | B | C | |
|---|---|---|---|
| 0 | 1.0 | 11.0 | 111.0 |
| 1 | 2.0 | NaN | 222.0 |
| 2 | 3.0 | 33.0 | 333.0 |
| 3 | NaN | NaN | NaN |
| 4 | 5.0 | 55.0 | 555.0 |
| 5 | 6.0 | 66.0 | 666.0 |
| 6 | 7.0 | 77.0 | NaN |
df.dropna()| A | B | C | |
|---|---|---|---|
| 0 | 1.0 | 11.0 | 111.0 |
| 2 | 3.0 | 33.0 | 333.0 |
| 4 | 5.0 | 55.0 | 555.0 |
| 5 | 6.0 | 66.0 | 666.0 |
B. _
- 파이썬이 계산한 최근 결과는 _에 저장된다.
a = [1,2,3]
a + [4] [1, 2, 3, 4]_[1, 2, 3, 4]_ + [5] [1, 2, 3, 4, 5]_.pop()5_ + 164. FIFA23 시각화 – 문제
# DV2022-중간고사-4-(2)의 변형:
아래는 FIFA22의 자료를 불러오는 코드이다.
df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2021/master/_notebooks/2021-10-25-FIFA22_official_data.csv')
df.head()| ID | Name | Age | Photo | Nationality | Flag | Overall | Potential | Club | Club Logo | ... | SlidingTackle | GKDiving | GKHandling | GKKicking | GKPositioning | GKReflexes | Best Position | Best Overall Rating | Release Clause | DefensiveAwareness | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 212198 | Bruno Fernandes | 26 | https://cdn.sofifa.com/players/212/198/22_60.png | Portugal | https://cdn.sofifa.com/flags/pt.png | 88 | 89 | Manchester United | https://cdn.sofifa.com/teams/11/30.png | ... | 65.0 | 12.0 | 14.0 | 15.0 | 8.0 | 14.0 | CAM | 88.0 | €206.9M | 72.0 |
| 1 | 209658 | L. Goretzka | 26 | https://cdn.sofifa.com/players/209/658/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 87 | 88 | FC Bayern München | https://cdn.sofifa.com/teams/21/30.png | ... | 77.0 | 13.0 | 8.0 | 15.0 | 11.0 | 9.0 | CM | 87.0 | €160.4M | 74.0 |
| 2 | 176580 | L. Suárez | 34 | https://cdn.sofifa.com/players/176/580/22_60.png | Uruguay | https://cdn.sofifa.com/flags/uy.png | 88 | 88 | Atlético de Madrid | https://cdn.sofifa.com/teams/240/30.png | ... | 38.0 | 27.0 | 25.0 | 31.0 | 33.0 | 37.0 | ST | 88.0 | €91.2M | 42.0 |
| 3 | 192985 | K. De Bruyne | 30 | https://cdn.sofifa.com/players/192/985/22_60.png | Belgium | https://cdn.sofifa.com/flags/be.png | 91 | 91 | Manchester City | https://cdn.sofifa.com/teams/10/30.png | ... | 53.0 | 15.0 | 13.0 | 5.0 | 10.0 | 13.0 | CM | 91.0 | €232.2M | 68.0 |
| 4 | 224334 | M. Acuña | 29 | https://cdn.sofifa.com/players/224/334/22_60.png | Argentina | https://cdn.sofifa.com/flags/ar.png | 84 | 84 | Sevilla FC | https://cdn.sofifa.com/teams/481/30.png | ... | 82.0 | 8.0 | 14.0 | 13.0 | 13.0 | 14.0 | LB | 84.0 | €77.7M | 80.0 |
5 rows × 65 columns
포지션별로 선수들의 능력치(ShotPower,SlidingTackle)와 급여(Wage)를 시각화하고 싶다. 아래의 세부지침에 맞추어 포지션별 ShotPower와 SlidingTackle의 산점도를 그려라. – (30점)
df.Position0 <span class="pos pos18">CAM
1 <span class="pos pos11">LDM
2 <span class="pos pos24">RS
3 <span class="pos pos13">RCM
4 <span class="pos pos7">LB
...
16705 <span class="pos pos29">RES
16706 <span class="pos pos29">RES
16707 <span class="pos pos29">RES
16708 <span class="pos pos28">SUB
16709 <span class="pos pos28">SUB
Name: Position, Length: 16710, dtype: object세부지침
A. Column의 이름에서 공백을 제거하라.
B. 결측치가 50%이상인 컬럼을 찾고 이를 제거하라. 그 뒤에 .dropna()를 사용하여 결측치가 포함된 행을 제거하라.
C. position_dict를 이용하여 df.Position을 적절하게 변환하라. 변환된 값을 df.Position에 저장하라.
position_dict = {
'GOALKEEPER':{'GK'},
'DEFENDER':{'CB','RCB','LCB','RB','LB','RWB','LWB'},
'MIDFIELDER':{'CM','RCM','LCM','CDM','RDM','LDM','CAM','RAM','LAM','RM','LM'},
'FORWARD':{'ST','CF','RF','LF','RW','LW','RS','LS'},
'SUB':{'SUB'},
'RES':{'RES'}
}
position_dict{'GOALKEEPER': {'GK'},
'DEFENDER': {'CB', 'LB', 'LCB', 'LWB', 'RB', 'RCB', 'RWB'},
'MIDFIELDER': {'CAM',
'CDM',
'CM',
'LAM',
'LCM',
'LDM',
'LM',
'RAM',
'RCM',
'RDM',
'RM'},
'FORWARD': {'CF', 'LF', 'LS', 'LW', 'RF', 'RS', 'RW', 'ST'},
'SUB': {'SUB'},
'RES': {'RES'}}D. df.Wage를 적절하게 변환하라.
E. Position==“DEFENDER” or Position==“FORWARD”에 해당하는 관측치를 고른 뒤 x축에 ShotPower, y축에 SlidingTackle을 시각화하라. 이때 Position은 color로 구분하고 Wage는 size와 alpha로 구분하라.
— 시각화예시 —
#
5. FIFA23 시각화 – 풀이1
A. 열의 이름에서 공백제거
df.columns = df.columns.str.replace(' ','')B. 결측치제거
df = df.loc[:,df.isna().mean()<0.5] # 결측치가 50퍼 이상인 컬럼을 제거df = df.dropna()df| ID | Name | Age | Photo | Nationality | Flag | Overall | Potential | Club | Club Logo | ... | SlidingTackle | GKDiving | GKHandling | GKKicking | GKPositioning | GKReflexes | Best Position | Best Overall Rating | Release Clause | DefensiveAwareness | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 212198 | Bruno Fernandes | 26 | https://cdn.sofifa.com/players/212/198/22_60.png | Portugal | https://cdn.sofifa.com/flags/pt.png | 88 | 89 | Manchester United | https://cdn.sofifa.com/teams/11/30.png | ... | 65.0 | 12.0 | 14.0 | 15.0 | 8.0 | 14.0 | CAM | 88.0 | €206.9M | 72.0 |
| 1 | 209658 | L. Goretzka | 26 | https://cdn.sofifa.com/players/209/658/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 87 | 88 | FC Bayern München | https://cdn.sofifa.com/teams/21/30.png | ... | 77.0 | 13.0 | 8.0 | 15.0 | 11.0 | 9.0 | CM | 87.0 | €160.4M | 74.0 |
| 2 | 176580 | L. Suárez | 34 | https://cdn.sofifa.com/players/176/580/22_60.png | Uruguay | https://cdn.sofifa.com/flags/uy.png | 88 | 88 | Atlético de Madrid | https://cdn.sofifa.com/teams/240/30.png | ... | 38.0 | 27.0 | 25.0 | 31.0 | 33.0 | 37.0 | ST | 88.0 | €91.2M | 42.0 |
| 3 | 192985 | K. De Bruyne | 30 | https://cdn.sofifa.com/players/192/985/22_60.png | Belgium | https://cdn.sofifa.com/flags/be.png | 91 | 91 | Manchester City | https://cdn.sofifa.com/teams/10/30.png | ... | 53.0 | 15.0 | 13.0 | 5.0 | 10.0 | 13.0 | CM | 91.0 | €232.2M | 68.0 |
| 4 | 224334 | M. Acuña | 29 | https://cdn.sofifa.com/players/224/334/22_60.png | Argentina | https://cdn.sofifa.com/flags/ar.png | 84 | 84 | Sevilla FC | https://cdn.sofifa.com/teams/481/30.png | ... | 82.0 | 8.0 | 14.0 | 13.0 | 13.0 | 14.0 | LB | 84.0 | €77.7M | 80.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 16703 | 259718 | F. Gebhardt | 19 | https://cdn.sofifa.com/players/259/718/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 52 | 66 | FC Basel 1893 | https://cdn.sofifa.com/teams/896/30.png | ... | 10.0 | 53.0 | 45.0 | 47.0 | 52.0 | 57.0 | GK | 52.0 | €361K | 6.0 |
| 16704 | 251433 | B. Voll | 20 | https://cdn.sofifa.com/players/251/433/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 58 | 69 | F.C. Hansa Rostock | https://cdn.sofifa.com/teams/27/30.png | ... | 10.0 | 59.0 | 60.0 | 56.0 | 55.0 | 61.0 | GK | 58.0 | €656K | 5.0 |
| 16706 | 262846 | �. Dobre | 20 | https://cdn.sofifa.com/players/262/846/22_60.png | Romania | https://cdn.sofifa.com/flags/ro.png | 53 | 63 | FC Academica Clinceni | https://cdn.sofifa.com/teams/113391/30.png | ... | 12.0 | 57.0 | 52.0 | 53.0 | 48.0 | 58.0 | GK | 53.0 | €279K | 5.0 |
| 16707 | 241317 | 21 Xue Qinghao | 19 | https://cdn.sofifa.com/players/241/317/21_60.png | China PR | https://cdn.sofifa.com/flags/cn.png | 47 | 60 | Shanghai Shenhua FC | https://cdn.sofifa.com/teams/110955/30.png | ... | 9.0 | 49.0 | 48.0 | 45.0 | 38.0 | 52.0 | GK | 47.0 | €223K | 21.0 |
| 16708 | 259646 | A. Shaikh | 18 | https://cdn.sofifa.com/players/259/646/22_60.png | India | https://cdn.sofifa.com/flags/in.png | 47 | 67 | ATK Mohun Bagan FC | https://cdn.sofifa.com/teams/113146/30.png | ... | 13.0 | 49.0 | 41.0 | 39.0 | 45.0 | 49.0 | GK | 47.0 | €259K | 7.0 |
14398 rows × 63 columns
C. Position 칼럼의 변환
df['Position'] = df.Position.str.split(">").str[-1].apply(lambda x: [k for k,v in position_dict.items() if x in v][0])D. Wage 칼럼의 변환
df['Wage'] = df.Wage.str[1:].str.replace('K','000').astype(int)E. 시각화
fig = ggplot(df.query('Position=="DEFENDER" or Position=="FORWARD"'))
point = geom_point(aes(x='ShotPower',y='SlidingTackle',color='Position',size='Wage',alpha='Wage'),position='jitter')
fig + point
6. FIFA23 시각화 – 망하는 경우
df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2021/master/_notebooks/2021-10-25-FIFA22_official_data.csv')A. 열의 이름에서 공백제거
df.columns = df.columns.str.replace(' ','')B. 결측치제거
- 실수로 df.dropna()를 먼저 사용.
df = df.dropna()df| ID | Name | Age | Photo | Nationality | Flag | Overall | Potential | Club | ClubLogo | ... | SlidingTackle | GKDiving | GKHandling | GKKicking | GKPositioning | GKReflexes | BestPosition | BestOverallRating | ReleaseClause | DefensiveAwareness |
|---|
0 rows × 65 columns
- 이럴경우는 다시 처음부터 실행해야함.
df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2021/master/_notebooks/2021-10-25-FIFA22_official_data.csv')df.columns = df.columns.str.replace(' ','')df = df.loc[:,df.isna().mean()<0.5]df = df.dropna()C. Position 칼럼의 변환
- 실수로 아래와 같이 코드를 입력했다고 치자.
df['Position'] = df.Position.str.split('>').str[-1].apply(lambda x: [k for k,v in position_dict.items() if x in v])
df.Position0 [MIDFIELDER]
1 [MIDFIELDER]
2 [FORWARD]
3 [MIDFIELDER]
4 [DEFENDER]
...
16703 [RES]
16704 [RES]
16706 [RES]
16707 [RES]
16708 [SUB]
Name: Position, Length: 14398, dtype: object- 하지만 지금와서 고쳐보려고 해봤자 늦음..
df['Position'] = df.Position.str.split('>').str[-1].apply(lambda x: [k for k,v in position_dict.items() if x in v].pop())AttributeError: Can only use .str accessor with string values!- 다시 처음부터..
df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2021/master/_notebooks/2021-10-25-FIFA22_official_data.csv')
df.columns = df.columns.str.replace(' ','')
df = df.loc[:,df.isna().mean()<0.5]
df = df.dropna()
df['Position'] = df.Position.str.split('>').str[-1].apply(lambda x: [k for k,v in position_dict.items() if x in v].pop())
df| ID | Name | Age | Photo | Nationality | Flag | Overall | Potential | Club | ClubLogo | ... | SlidingTackle | GKDiving | GKHandling | GKKicking | GKPositioning | GKReflexes | BestPosition | BestOverallRating | ReleaseClause | DefensiveAwareness | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 212198 | Bruno Fernandes | 26 | https://cdn.sofifa.com/players/212/198/22_60.png | Portugal | https://cdn.sofifa.com/flags/pt.png | 88 | 89 | Manchester United | https://cdn.sofifa.com/teams/11/30.png | ... | 65.0 | 12.0 | 14.0 | 15.0 | 8.0 | 14.0 | CAM | 88.0 | €206.9M | 72.0 |
| 1 | 209658 | L. Goretzka | 26 | https://cdn.sofifa.com/players/209/658/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 87 | 88 | FC Bayern München | https://cdn.sofifa.com/teams/21/30.png | ... | 77.0 | 13.0 | 8.0 | 15.0 | 11.0 | 9.0 | CM | 87.0 | €160.4M | 74.0 |
| 2 | 176580 | L. Suárez | 34 | https://cdn.sofifa.com/players/176/580/22_60.png | Uruguay | https://cdn.sofifa.com/flags/uy.png | 88 | 88 | Atlético de Madrid | https://cdn.sofifa.com/teams/240/30.png | ... | 38.0 | 27.0 | 25.0 | 31.0 | 33.0 | 37.0 | ST | 88.0 | €91.2M | 42.0 |
| 3 | 192985 | K. De Bruyne | 30 | https://cdn.sofifa.com/players/192/985/22_60.png | Belgium | https://cdn.sofifa.com/flags/be.png | 91 | 91 | Manchester City | https://cdn.sofifa.com/teams/10/30.png | ... | 53.0 | 15.0 | 13.0 | 5.0 | 10.0 | 13.0 | CM | 91.0 | €232.2M | 68.0 |
| 4 | 224334 | M. Acuña | 29 | https://cdn.sofifa.com/players/224/334/22_60.png | Argentina | https://cdn.sofifa.com/flags/ar.png | 84 | 84 | Sevilla FC | https://cdn.sofifa.com/teams/481/30.png | ... | 82.0 | 8.0 | 14.0 | 13.0 | 13.0 | 14.0 | LB | 84.0 | €77.7M | 80.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 16703 | 259718 | F. Gebhardt | 19 | https://cdn.sofifa.com/players/259/718/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 52 | 66 | FC Basel 1893 | https://cdn.sofifa.com/teams/896/30.png | ... | 10.0 | 53.0 | 45.0 | 47.0 | 52.0 | 57.0 | GK | 52.0 | €361K | 6.0 |
| 16704 | 251433 | B. Voll | 20 | https://cdn.sofifa.com/players/251/433/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 58 | 69 | F.C. Hansa Rostock | https://cdn.sofifa.com/teams/27/30.png | ... | 10.0 | 59.0 | 60.0 | 56.0 | 55.0 | 61.0 | GK | 58.0 | €656K | 5.0 |
| 16706 | 262846 | �. Dobre | 20 | https://cdn.sofifa.com/players/262/846/22_60.png | Romania | https://cdn.sofifa.com/flags/ro.png | 53 | 63 | FC Academica Clinceni | https://cdn.sofifa.com/teams/113391/30.png | ... | 12.0 | 57.0 | 52.0 | 53.0 | 48.0 | 58.0 | GK | 53.0 | €279K | 5.0 |
| 16707 | 241317 | 21 Xue Qinghao | 19 | https://cdn.sofifa.com/players/241/317/21_60.png | China PR | https://cdn.sofifa.com/flags/cn.png | 47 | 60 | Shanghai Shenhua FC | https://cdn.sofifa.com/teams/110955/30.png | ... | 9.0 | 49.0 | 48.0 | 45.0 | 38.0 | 52.0 | GK | 47.0 | €223K | 21.0 |
| 16708 | 259646 | A. Shaikh | 18 | https://cdn.sofifa.com/players/259/646/22_60.png | India | https://cdn.sofifa.com/flags/in.png | 47 | 67 | ATK Mohun Bagan FC | https://cdn.sofifa.com/teams/113146/30.png | ... | 13.0 | 49.0 | 41.0 | 39.0 | 45.0 | 49.0 | GK | 47.0 | €259K | 7.0 |
14398 rows × 63 columns
- 요령1: 데이터를 불러오는 코드부터 시작해서 하나의 셀에 df를 처리하는 코드를 모두 몰아넣어서 처리하는게 유리함. (그래야 덜 당황해요 \(\star\star\star\star\star\))
- 요령2: 데이터프레임 자체를 변환시키는 코드를 가급적 작성하지 않음. (제가 좀 더 자주 쓰는 테크닉, 기술이 필요함)
7. FIFA23 시각화 – 풀이2
df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2021/master/_notebooks/2021-10-25-FIFA22_official_data.csv')A. 열의 이름에서 공백제거
df.set_axis(df.columns.str.replace(' ',''),axis=1)| ID | Name | Age | Photo | Nationality | Flag | Overall | Potential | Club | ClubLogo | ... | SlidingTackle | GKDiving | GKHandling | GKKicking | GKPositioning | GKReflexes | BestPosition | BestOverallRating | ReleaseClause | DefensiveAwareness | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 212198 | Bruno Fernandes | 26 | https://cdn.sofifa.com/players/212/198/22_60.png | Portugal | https://cdn.sofifa.com/flags/pt.png | 88 | 89 | Manchester United | https://cdn.sofifa.com/teams/11/30.png | ... | 65.0 | 12.0 | 14.0 | 15.0 | 8.0 | 14.0 | CAM | 88.0 | €206.9M | 72.0 |
| 1 | 209658 | L. Goretzka | 26 | https://cdn.sofifa.com/players/209/658/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 87 | 88 | FC Bayern München | https://cdn.sofifa.com/teams/21/30.png | ... | 77.0 | 13.0 | 8.0 | 15.0 | 11.0 | 9.0 | CM | 87.0 | €160.4M | 74.0 |
| 2 | 176580 | L. Suárez | 34 | https://cdn.sofifa.com/players/176/580/22_60.png | Uruguay | https://cdn.sofifa.com/flags/uy.png | 88 | 88 | Atlético de Madrid | https://cdn.sofifa.com/teams/240/30.png | ... | 38.0 | 27.0 | 25.0 | 31.0 | 33.0 | 37.0 | ST | 88.0 | €91.2M | 42.0 |
| 3 | 192985 | K. De Bruyne | 30 | https://cdn.sofifa.com/players/192/985/22_60.png | Belgium | https://cdn.sofifa.com/flags/be.png | 91 | 91 | Manchester City | https://cdn.sofifa.com/teams/10/30.png | ... | 53.0 | 15.0 | 13.0 | 5.0 | 10.0 | 13.0 | CM | 91.0 | €232.2M | 68.0 |
| 4 | 224334 | M. Acuña | 29 | https://cdn.sofifa.com/players/224/334/22_60.png | Argentina | https://cdn.sofifa.com/flags/ar.png | 84 | 84 | Sevilla FC | https://cdn.sofifa.com/teams/481/30.png | ... | 82.0 | 8.0 | 14.0 | 13.0 | 13.0 | 14.0 | LB | 84.0 | €77.7M | 80.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 16705 | 240558 | 18 L. Clayton | 17 | https://cdn.sofifa.com/players/240/558/18_60.png | England | https://cdn.sofifa.com/flags/gb-eng.png | 53 | 70 | Cheltenham Town | https://cdn.sofifa.com/teams/1936/30.png | ... | 12.0 | 55.0 | 54.0 | 52.0 | 50.0 | 59.0 | GK | 52.0 | €238K | NaN |
| 16706 | 262846 | �. Dobre | 20 | https://cdn.sofifa.com/players/262/846/22_60.png | Romania | https://cdn.sofifa.com/flags/ro.png | 53 | 63 | FC Academica Clinceni | https://cdn.sofifa.com/teams/113391/30.png | ... | 12.0 | 57.0 | 52.0 | 53.0 | 48.0 | 58.0 | GK | 53.0 | €279K | 5.0 |
| 16707 | 241317 | 21 Xue Qinghao | 19 | https://cdn.sofifa.com/players/241/317/21_60.png | China PR | https://cdn.sofifa.com/flags/cn.png | 47 | 60 | Shanghai Shenhua FC | https://cdn.sofifa.com/teams/110955/30.png | ... | 9.0 | 49.0 | 48.0 | 45.0 | 38.0 | 52.0 | GK | 47.0 | €223K | 21.0 |
| 16708 | 259646 | A. Shaikh | 18 | https://cdn.sofifa.com/players/259/646/22_60.png | India | https://cdn.sofifa.com/flags/in.png | 47 | 67 | ATK Mohun Bagan FC | https://cdn.sofifa.com/teams/113146/30.png | ... | 13.0 | 49.0 | 41.0 | 39.0 | 45.0 | 49.0 | GK | 47.0 | €259K | 7.0 |
| 16709 | 178453 | 07 A. Censori | 17 | https://cdn.sofifa.com/players/178/453/07_60.png | Italy | https://cdn.sofifa.com/flags/it.png | 28 | 38 | Arezzo | https://cdn.sofifa.com/teams/110907/30.png | ... | NaN | 7.0 | 1.0 | 36.0 | 6.0 | 9.0 | ST | 36.0 | NaN | NaN |
16710 rows × 65 columns
B. 결측치제거
_df = df.set_axis(df.columns.str.replace(' ',''),axis=1)
_df| ID | Name | Age | Photo | Nationality | Flag | Overall | Potential | Club | ClubLogo | ... | SlidingTackle | GKDiving | GKHandling | GKKicking | GKPositioning | GKReflexes | BestPosition | BestOverallRating | ReleaseClause | DefensiveAwareness | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 212198 | Bruno Fernandes | 26 | https://cdn.sofifa.com/players/212/198/22_60.png | Portugal | https://cdn.sofifa.com/flags/pt.png | 88 | 89 | Manchester United | https://cdn.sofifa.com/teams/11/30.png | ... | 65.0 | 12.0 | 14.0 | 15.0 | 8.0 | 14.0 | CAM | 88.0 | €206.9M | 72.0 |
| 1 | 209658 | L. Goretzka | 26 | https://cdn.sofifa.com/players/209/658/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 87 | 88 | FC Bayern München | https://cdn.sofifa.com/teams/21/30.png | ... | 77.0 | 13.0 | 8.0 | 15.0 | 11.0 | 9.0 | CM | 87.0 | €160.4M | 74.0 |
| 2 | 176580 | L. Suárez | 34 | https://cdn.sofifa.com/players/176/580/22_60.png | Uruguay | https://cdn.sofifa.com/flags/uy.png | 88 | 88 | Atlético de Madrid | https://cdn.sofifa.com/teams/240/30.png | ... | 38.0 | 27.0 | 25.0 | 31.0 | 33.0 | 37.0 | ST | 88.0 | €91.2M | 42.0 |
| 3 | 192985 | K. De Bruyne | 30 | https://cdn.sofifa.com/players/192/985/22_60.png | Belgium | https://cdn.sofifa.com/flags/be.png | 91 | 91 | Manchester City | https://cdn.sofifa.com/teams/10/30.png | ... | 53.0 | 15.0 | 13.0 | 5.0 | 10.0 | 13.0 | CM | 91.0 | €232.2M | 68.0 |
| 4 | 224334 | M. Acuña | 29 | https://cdn.sofifa.com/players/224/334/22_60.png | Argentina | https://cdn.sofifa.com/flags/ar.png | 84 | 84 | Sevilla FC | https://cdn.sofifa.com/teams/481/30.png | ... | 82.0 | 8.0 | 14.0 | 13.0 | 13.0 | 14.0 | LB | 84.0 | €77.7M | 80.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 16705 | 240558 | 18 L. Clayton | 17 | https://cdn.sofifa.com/players/240/558/18_60.png | England | https://cdn.sofifa.com/flags/gb-eng.png | 53 | 70 | Cheltenham Town | https://cdn.sofifa.com/teams/1936/30.png | ... | 12.0 | 55.0 | 54.0 | 52.0 | 50.0 | 59.0 | GK | 52.0 | €238K | NaN |
| 16706 | 262846 | �. Dobre | 20 | https://cdn.sofifa.com/players/262/846/22_60.png | Romania | https://cdn.sofifa.com/flags/ro.png | 53 | 63 | FC Academica Clinceni | https://cdn.sofifa.com/teams/113391/30.png | ... | 12.0 | 57.0 | 52.0 | 53.0 | 48.0 | 58.0 | GK | 53.0 | €279K | 5.0 |
| 16707 | 241317 | 21 Xue Qinghao | 19 | https://cdn.sofifa.com/players/241/317/21_60.png | China PR | https://cdn.sofifa.com/flags/cn.png | 47 | 60 | Shanghai Shenhua FC | https://cdn.sofifa.com/teams/110955/30.png | ... | 9.0 | 49.0 | 48.0 | 45.0 | 38.0 | 52.0 | GK | 47.0 | €223K | 21.0 |
| 16708 | 259646 | A. Shaikh | 18 | https://cdn.sofifa.com/players/259/646/22_60.png | India | https://cdn.sofifa.com/flags/in.png | 47 | 67 | ATK Mohun Bagan FC | https://cdn.sofifa.com/teams/113146/30.png | ... | 13.0 | 49.0 | 41.0 | 39.0 | 45.0 | 49.0 | GK | 47.0 | €259K | 7.0 |
| 16709 | 178453 | 07 A. Censori | 17 | https://cdn.sofifa.com/players/178/453/07_60.png | Italy | https://cdn.sofifa.com/flags/it.png | 28 | 38 | Arezzo | https://cdn.sofifa.com/teams/110907/30.png | ... | NaN | 7.0 | 1.0 | 36.0 | 6.0 | 9.0 | ST | 36.0 | NaN | NaN |
16710 rows × 65 columns
df.set_axis(df.columns.str.replace(' ',''),axis=1)\
.loc[:,lambda _df: _df.isna().mean()<0.5].dropna()| ID | Name | Age | Photo | Nationality | Flag | Overall | Potential | Club | ClubLogo | ... | SlidingTackle | GKDiving | GKHandling | GKKicking | GKPositioning | GKReflexes | BestPosition | BestOverallRating | ReleaseClause | DefensiveAwareness | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 212198 | Bruno Fernandes | 26 | https://cdn.sofifa.com/players/212/198/22_60.png | Portugal | https://cdn.sofifa.com/flags/pt.png | 88 | 89 | Manchester United | https://cdn.sofifa.com/teams/11/30.png | ... | 65.0 | 12.0 | 14.0 | 15.0 | 8.0 | 14.0 | CAM | 88.0 | €206.9M | 72.0 |
| 1 | 209658 | L. Goretzka | 26 | https://cdn.sofifa.com/players/209/658/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 87 | 88 | FC Bayern München | https://cdn.sofifa.com/teams/21/30.png | ... | 77.0 | 13.0 | 8.0 | 15.0 | 11.0 | 9.0 | CM | 87.0 | €160.4M | 74.0 |
| 2 | 176580 | L. Suárez | 34 | https://cdn.sofifa.com/players/176/580/22_60.png | Uruguay | https://cdn.sofifa.com/flags/uy.png | 88 | 88 | Atlético de Madrid | https://cdn.sofifa.com/teams/240/30.png | ... | 38.0 | 27.0 | 25.0 | 31.0 | 33.0 | 37.0 | ST | 88.0 | €91.2M | 42.0 |
| 3 | 192985 | K. De Bruyne | 30 | https://cdn.sofifa.com/players/192/985/22_60.png | Belgium | https://cdn.sofifa.com/flags/be.png | 91 | 91 | Manchester City | https://cdn.sofifa.com/teams/10/30.png | ... | 53.0 | 15.0 | 13.0 | 5.0 | 10.0 | 13.0 | CM | 91.0 | €232.2M | 68.0 |
| 4 | 224334 | M. Acuña | 29 | https://cdn.sofifa.com/players/224/334/22_60.png | Argentina | https://cdn.sofifa.com/flags/ar.png | 84 | 84 | Sevilla FC | https://cdn.sofifa.com/teams/481/30.png | ... | 82.0 | 8.0 | 14.0 | 13.0 | 13.0 | 14.0 | LB | 84.0 | €77.7M | 80.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 16703 | 259718 | F. Gebhardt | 19 | https://cdn.sofifa.com/players/259/718/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 52 | 66 | FC Basel 1893 | https://cdn.sofifa.com/teams/896/30.png | ... | 10.0 | 53.0 | 45.0 | 47.0 | 52.0 | 57.0 | GK | 52.0 | €361K | 6.0 |
| 16704 | 251433 | B. Voll | 20 | https://cdn.sofifa.com/players/251/433/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 58 | 69 | F.C. Hansa Rostock | https://cdn.sofifa.com/teams/27/30.png | ... | 10.0 | 59.0 | 60.0 | 56.0 | 55.0 | 61.0 | GK | 58.0 | €656K | 5.0 |
| 16706 | 262846 | �. Dobre | 20 | https://cdn.sofifa.com/players/262/846/22_60.png | Romania | https://cdn.sofifa.com/flags/ro.png | 53 | 63 | FC Academica Clinceni | https://cdn.sofifa.com/teams/113391/30.png | ... | 12.0 | 57.0 | 52.0 | 53.0 | 48.0 | 58.0 | GK | 53.0 | €279K | 5.0 |
| 16707 | 241317 | 21 Xue Qinghao | 19 | https://cdn.sofifa.com/players/241/317/21_60.png | China PR | https://cdn.sofifa.com/flags/cn.png | 47 | 60 | Shanghai Shenhua FC | https://cdn.sofifa.com/teams/110955/30.png | ... | 9.0 | 49.0 | 48.0 | 45.0 | 38.0 | 52.0 | GK | 47.0 | €223K | 21.0 |
| 16708 | 259646 | A. Shaikh | 18 | https://cdn.sofifa.com/players/259/646/22_60.png | India | https://cdn.sofifa.com/flags/in.png | 47 | 67 | ATK Mohun Bagan FC | https://cdn.sofifa.com/teams/113146/30.png | ... | 13.0 | 49.0 | 41.0 | 39.0 | 45.0 | 49.0 | GK | 47.0 | €259K | 7.0 |
14398 rows × 63 columns
C. Position 칼럼의 변환
df.set_axis(df.columns.str.replace(' ',''),axis=1)\
.loc[:,lambda _df: _df.isna().mean()<0.5].dropna()\
.assign(Position = lambda _df: _df.Position.str.split(">").str[-1].apply(lambda x: [k for k,v in position_dict.items() if x in v].pop()))| ID | Name | Age | Photo | Nationality | Flag | Overall | Potential | Club | ClubLogo | ... | SlidingTackle | GKDiving | GKHandling | GKKicking | GKPositioning | GKReflexes | BestPosition | BestOverallRating | ReleaseClause | DefensiveAwareness | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 212198 | Bruno Fernandes | 26 | https://cdn.sofifa.com/players/212/198/22_60.png | Portugal | https://cdn.sofifa.com/flags/pt.png | 88 | 89 | Manchester United | https://cdn.sofifa.com/teams/11/30.png | ... | 65.0 | 12.0 | 14.0 | 15.0 | 8.0 | 14.0 | CAM | 88.0 | €206.9M | 72.0 |
| 1 | 209658 | L. Goretzka | 26 | https://cdn.sofifa.com/players/209/658/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 87 | 88 | FC Bayern München | https://cdn.sofifa.com/teams/21/30.png | ... | 77.0 | 13.0 | 8.0 | 15.0 | 11.0 | 9.0 | CM | 87.0 | €160.4M | 74.0 |
| 2 | 176580 | L. Suárez | 34 | https://cdn.sofifa.com/players/176/580/22_60.png | Uruguay | https://cdn.sofifa.com/flags/uy.png | 88 | 88 | Atlético de Madrid | https://cdn.sofifa.com/teams/240/30.png | ... | 38.0 | 27.0 | 25.0 | 31.0 | 33.0 | 37.0 | ST | 88.0 | €91.2M | 42.0 |
| 3 | 192985 | K. De Bruyne | 30 | https://cdn.sofifa.com/players/192/985/22_60.png | Belgium | https://cdn.sofifa.com/flags/be.png | 91 | 91 | Manchester City | https://cdn.sofifa.com/teams/10/30.png | ... | 53.0 | 15.0 | 13.0 | 5.0 | 10.0 | 13.0 | CM | 91.0 | €232.2M | 68.0 |
| 4 | 224334 | M. Acuña | 29 | https://cdn.sofifa.com/players/224/334/22_60.png | Argentina | https://cdn.sofifa.com/flags/ar.png | 84 | 84 | Sevilla FC | https://cdn.sofifa.com/teams/481/30.png | ... | 82.0 | 8.0 | 14.0 | 13.0 | 13.0 | 14.0 | LB | 84.0 | €77.7M | 80.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 16703 | 259718 | F. Gebhardt | 19 | https://cdn.sofifa.com/players/259/718/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 52 | 66 | FC Basel 1893 | https://cdn.sofifa.com/teams/896/30.png | ... | 10.0 | 53.0 | 45.0 | 47.0 | 52.0 | 57.0 | GK | 52.0 | €361K | 6.0 |
| 16704 | 251433 | B. Voll | 20 | https://cdn.sofifa.com/players/251/433/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 58 | 69 | F.C. Hansa Rostock | https://cdn.sofifa.com/teams/27/30.png | ... | 10.0 | 59.0 | 60.0 | 56.0 | 55.0 | 61.0 | GK | 58.0 | €656K | 5.0 |
| 16706 | 262846 | �. Dobre | 20 | https://cdn.sofifa.com/players/262/846/22_60.png | Romania | https://cdn.sofifa.com/flags/ro.png | 53 | 63 | FC Academica Clinceni | https://cdn.sofifa.com/teams/113391/30.png | ... | 12.0 | 57.0 | 52.0 | 53.0 | 48.0 | 58.0 | GK | 53.0 | €279K | 5.0 |
| 16707 | 241317 | 21 Xue Qinghao | 19 | https://cdn.sofifa.com/players/241/317/21_60.png | China PR | https://cdn.sofifa.com/flags/cn.png | 47 | 60 | Shanghai Shenhua FC | https://cdn.sofifa.com/teams/110955/30.png | ... | 9.0 | 49.0 | 48.0 | 45.0 | 38.0 | 52.0 | GK | 47.0 | €223K | 21.0 |
| 16708 | 259646 | A. Shaikh | 18 | https://cdn.sofifa.com/players/259/646/22_60.png | India | https://cdn.sofifa.com/flags/in.png | 47 | 67 | ATK Mohun Bagan FC | https://cdn.sofifa.com/teams/113146/30.png | ... | 13.0 | 49.0 | 41.0 | 39.0 | 45.0 | 49.0 | GK | 47.0 | €259K | 7.0 |
14398 rows × 63 columns
D. Wage 칼럼의 변환
df.set_axis(df.columns.str.replace(' ',''),axis=1)\
.loc[:,lambda _df: _df.isna().mean()<0.5].dropna()\
.assign(Position = lambda _df: _df.Position.str.split(">").str[-1].apply(lambda x: [k for k,v in position_dict.items() if x in v].pop()))\
.assign(Wage = lambda _df: _df.Wage.str[1:].str.replace('K','000').astype(int))| ID | Name | Age | Photo | Nationality | Flag | Overall | Potential | Club | ClubLogo | ... | SlidingTackle | GKDiving | GKHandling | GKKicking | GKPositioning | GKReflexes | BestPosition | BestOverallRating | ReleaseClause | DefensiveAwareness | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 212198 | Bruno Fernandes | 26 | https://cdn.sofifa.com/players/212/198/22_60.png | Portugal | https://cdn.sofifa.com/flags/pt.png | 88 | 89 | Manchester United | https://cdn.sofifa.com/teams/11/30.png | ... | 65.0 | 12.0 | 14.0 | 15.0 | 8.0 | 14.0 | CAM | 88.0 | €206.9M | 72.0 |
| 1 | 209658 | L. Goretzka | 26 | https://cdn.sofifa.com/players/209/658/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 87 | 88 | FC Bayern München | https://cdn.sofifa.com/teams/21/30.png | ... | 77.0 | 13.0 | 8.0 | 15.0 | 11.0 | 9.0 | CM | 87.0 | €160.4M | 74.0 |
| 2 | 176580 | L. Suárez | 34 | https://cdn.sofifa.com/players/176/580/22_60.png | Uruguay | https://cdn.sofifa.com/flags/uy.png | 88 | 88 | Atlético de Madrid | https://cdn.sofifa.com/teams/240/30.png | ... | 38.0 | 27.0 | 25.0 | 31.0 | 33.0 | 37.0 | ST | 88.0 | €91.2M | 42.0 |
| 3 | 192985 | K. De Bruyne | 30 | https://cdn.sofifa.com/players/192/985/22_60.png | Belgium | https://cdn.sofifa.com/flags/be.png | 91 | 91 | Manchester City | https://cdn.sofifa.com/teams/10/30.png | ... | 53.0 | 15.0 | 13.0 | 5.0 | 10.0 | 13.0 | CM | 91.0 | €232.2M | 68.0 |
| 4 | 224334 | M. Acuña | 29 | https://cdn.sofifa.com/players/224/334/22_60.png | Argentina | https://cdn.sofifa.com/flags/ar.png | 84 | 84 | Sevilla FC | https://cdn.sofifa.com/teams/481/30.png | ... | 82.0 | 8.0 | 14.0 | 13.0 | 13.0 | 14.0 | LB | 84.0 | €77.7M | 80.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 16703 | 259718 | F. Gebhardt | 19 | https://cdn.sofifa.com/players/259/718/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 52 | 66 | FC Basel 1893 | https://cdn.sofifa.com/teams/896/30.png | ... | 10.0 | 53.0 | 45.0 | 47.0 | 52.0 | 57.0 | GK | 52.0 | €361K | 6.0 |
| 16704 | 251433 | B. Voll | 20 | https://cdn.sofifa.com/players/251/433/22_60.png | Germany | https://cdn.sofifa.com/flags/de.png | 58 | 69 | F.C. Hansa Rostock | https://cdn.sofifa.com/teams/27/30.png | ... | 10.0 | 59.0 | 60.0 | 56.0 | 55.0 | 61.0 | GK | 58.0 | €656K | 5.0 |
| 16706 | 262846 | �. Dobre | 20 | https://cdn.sofifa.com/players/262/846/22_60.png | Romania | https://cdn.sofifa.com/flags/ro.png | 53 | 63 | FC Academica Clinceni | https://cdn.sofifa.com/teams/113391/30.png | ... | 12.0 | 57.0 | 52.0 | 53.0 | 48.0 | 58.0 | GK | 53.0 | €279K | 5.0 |
| 16707 | 241317 | 21 Xue Qinghao | 19 | https://cdn.sofifa.com/players/241/317/21_60.png | China PR | https://cdn.sofifa.com/flags/cn.png | 47 | 60 | Shanghai Shenhua FC | https://cdn.sofifa.com/teams/110955/30.png | ... | 9.0 | 49.0 | 48.0 | 45.0 | 38.0 | 52.0 | GK | 47.0 | €223K | 21.0 |
| 16708 | 259646 | A. Shaikh | 18 | https://cdn.sofifa.com/players/259/646/22_60.png | India | https://cdn.sofifa.com/flags/in.png | 47 | 67 | ATK Mohun Bagan FC | https://cdn.sofifa.com/teams/113146/30.png | ... | 13.0 | 49.0 | 41.0 | 39.0 | 45.0 | 49.0 | GK | 47.0 | €259K | 7.0 |
14398 rows × 63 columns
E. 시각화
tidydata = df.set_axis(df.columns.str.replace(' ',''),axis=1)\
.loc[:,lambda _df: _df.isna().mean()<0.5].dropna()\
.assign(Position = lambda _df: _df.Position.str.split(">").str[-1].apply(lambda x: [k for k,v in position_dict.items() if x in v].pop()))\
.assign(Wage = lambda _df: _df.Wage.str[1:].str.replace('K','000').astype(int))fig = ggplot(tidydata.query('Position=="DEFENDER" or Position=="FORWARD"'))
point = geom_point(aes(x='ShotPower',y='SlidingTackle',color='Position',size='Wage',alpha='Wage'),position='jitter')
fig + point
8. 숙제
1.
df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2021/master/_notebooks/2021-10-25-FIFA22_official_data.csv')
s = df.Wage
s0 €250K
1 €140K
2 €135K
3 €350K
4 €45K
...
16705 €1K
16706 €550
16707 €700
16708 €500
16709 €0
Name: Wage, Length: 16710, dtype: object위의 자료형에서 “€250.5K”와 같이 소수점이 포함된 형태의 문자열이 있는지 조사하는 코드를 작성하라.
hint: 아래의 코드를 이용
"." in "€250.5K"True"." in "€250.25K"True"." in "€250K"False2.
아래와 같은 pd.Series가 있다고 하자.
df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2021/master/_notebooks/2021-10-25-FIFA22_official_data.csv').iloc[[0,1,16708,16709],:].reset_index()
s = df.Value
s0 €107.5M
1 €93M
2 €110K
3 €0
Name: Value, dtype: object아래와 같은 변환을 수행하라.
| 변환전 | 변환후 |
|---|---|
| ‘€107.5M’ | 107500000 |
| ‘€93M’ | 93000000 |
| ‘€110K’ | 110000 |
| ‘€0’ | 0 |
s.str[1:].str.replace('M','*1000000').str.replace('K','*1000')0 107.5*1000000
1 93*1000000
2 110*1000
3 0
Name: Value, dtype: objecteval('93*1000000')93000000hint 아래를 이용하면 쉬울껄요?
eval('100*100')10000