10wk-2: `pandas`, 반복문자투리, 변수의범위

Author

최규빈

Published

May 10, 2024

1. 강의영상

2. Imports

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
import itertools

3. `Pandas`

A. `numpy` 대비 장점?

- 장점1: 모든 자료형이 동일할 필요가 없다.

(문제) – 아래의 리스트에서 능력치가 90 보다 큰 선수들을 출력하라.

lst = [['Bruno Fernandes', 'Europe', 88],
       ['L. Goretzka', 'Europe', 87],
       ['L. Suárez', 'South America', 88],
       ['K. De Bruyne', 'Europe', 91],
       ['M. Acuña', 'South America', 84],
       ['J. Kimmich', 'Europe', 89]]

(풀이) – 아마 이렇게..

[[name,continent,x] for name, continent, x in lst if x>90]

[['K. De Bruyne', 'Europe', 91]]

(풀이) – 말린다면..

arr = np.array(lst)
arr

array([['Bruno Fernandes', 'Europe', '88'],
       ['L. Goretzka', 'Europe', '87'],
       ['L. Suárez', 'South America', '88'],
       ['K. De Bruyne', 'Europe', '91'],
       ['M. Acuña', 'South America', '84'],
       ['J. Kimmich', 'Europe', '89']], dtype='<U21')

arr[arr[:,2] > 90]

UFuncTypeError: ufunc 'greater' did not contain a loop with signature matching types (<class 'numpy.dtypes.StrDType'>, <class 'numpy.dtypes.Int64DType'>) -> <class 'numpy.dtypes.BoolDType'>

(풀이) – 판다스였다면

df = pd.DataFrame(lst)
df

	0	1	2
0	Bruno Fernandes	Europe	88
1	L. Goretzka	Europe	87
2	L. Suárez	South America	88
3	K. De Bruyne	Europe	91
4	M. Acuña	South America	84
5	J. Kimmich	Europe	89

df[df.iloc[:,2] > 90]

	0	1	2
3	K. De Bruyne	Europe	91

(분석)

arr[:,0],arr[:,1],arr[:,2] # 문자열,문자열,문자열 -> 각 col의 자료형이 반드시 같아야함

(array(['Bruno Fernandes', 'L. Goretzka', 'L. Suárez', 'K. De Bruyne',
        'M. Acuña', 'J. Kimmich'], dtype='<U21'),
 array(['Europe', 'Europe', 'South America', 'Europe', 'South America',
        'Europe'], dtype='<U21'),
 array(['88', '87', '88', '91', '84', '89'], dtype='<U21'))

df.iloc[:,0], df.iloc[:,1], df.iloc[:,2] # object,object,int -> 각 col의 자료형이 다를수도있음.

(0    Bruno Fernandes
 1        L. Goretzka
 2          L. Suárez
 3       K. De Bruyne
 4           M. Acuña
 5         J. Kimmich
 Name: 0, dtype: object,
 0           Europe
 1           Europe
 2    South America
 3           Europe
 4    South America
 5           Europe
 Name: 1, dtype: object,
 0    88
 1    87
 2    88
 3    91
 4    84
 5    89
 Name: 2, dtype: int64)

- 장점2: 인덱싱과 해싱을 동시에 할 수 있다. (순서형자료형과 맵핑형자료형의 장점을 동시에 가짐)

list의 장점 \(\to\) numpy 가 계승
dct의 장점 \(\to\) pandas 가 계승 + list/numpy의 장점 일부흡수

dct = {'att':[30,40,50],'mid':[50,60,70]}
df = pd.DataFrame(dct)
df

	att	mid
0	30	50
1	40	60
2	50	70

df['att'], dct['att'] # 해싱

(0    30
 1    40
 2    50
 Name: att, dtype: int64,
 [30, 40, 50])

df.iloc[[1],[0,1]] # 인덱싱

	att	mid
1	40	60

느낌: 판다스데이터프레임은 엑셀 그자체!

B. 선언방법

- 방법1: dictionary에서 만든다. (맵핑형자료에서 생성)

pd.DataFrame({'att':[30,40,50],'mid':[50,60,70]})

	att	mid
0	30	50
1	40	60
2	50	70

pd.DataFrame({'att':(30,40,50),'mid':(50,60,70)})

	att	mid
0	30	50
1	40	60
2	50	70

pd.DataFrame({'att':np.array([30,40,50]),'mid':np.array([50,60,70])})

	att	mid
0	30	50
1	40	60
2	50	70

- 방법2: ndarray 혹은 list 등에서 만든다. (보통 2차원의 중첩구조를 가지는 순서형자료에서 생성하는게 일반적임)

np.arange(2*3).reshape(2,3)

array([[0, 1, 2],
       [3, 4, 5]])

pd.DataFrame(np.arange(2*3).reshape(2,3))

	0	1	2
0	0	1	2
1	3	4	5

C. 자료형, len, shape, for문의 반복변수

df = pd.DataFrame({'att':[30,40,50],'mid':[5,45,90]})
df

	att	mid
0	30	5
1	40	45
2	50	90

- type

type(df)

pandas.core.frame.DataFrame

- len

len(df) # row의 갯수

- shape

df.shape

(3, 2)

- for문의 반복변수

for k in df:
    print(k) # 딕셔너리같죠

att
mid

for k in {'att':[30,40,50],'mid':[5,45,90]}: 
    print(k)

att
mid

참고: df는 진짜 딕셔너리 느낌 강해요

df.keys()

Index(['att', 'mid'], dtype='object')

for k,v in df.items():
    print(k)
    print(v)
    print('\n')

att
0    30
1    40
2    50
Name: att, dtype: int64


mid
0     5
1    45
2    90
Name: mid, dtype: int64

D. `pd.Series`

- 2차원 ndarray가 pd.DataFrame에 대응한다면 1차원 ndarray는 pd.Series에 대응한다.

s=pd.Series(np.random.randn(10))
s

0    0.252373
1   -1.075307
2   -0.368705
3    0.784600
4    0.549906
5   -0.479970
6   -1.991117
7   -0.407330
8   -0.131100
9    0.388155
dtype: float64

type(s)

pandas.core.series.Series

len(s)

s.shape

(10,)

for x in s: 
    print(x)

0.2523733143388311
-1.0753068117512616
-0.36870536789029595
0.7845995696103139
0.5499055415241653
-0.47997013360871355
-1.9911174129623606
-0.40733045301228693
-0.13110029817116495
0.38815521816133036

4. Pandas: 행과 열의 선택

- 두 가지 형태의 데이터프레임

dct = {'date': ['12/30','12/31','01/01','01/02','01/03'], 'X1': [65,95,65,55,80], 'X2': [55,100,90,80,30], 'X3': [50,50,60,75,30], 'X4': [40,80,30,80,100]}
df = pd.DataFrame(dct) 
df

	date	X1	X2	X3	X4
0	12/30	65	55	50	40
1	12/31	95	100	50	80
2	01/01	65	90	60	30
3	01/02	55	80	75	80
4	01/03	80	30	30	100

ts = pd.DataFrame({'X1': [65,95,65,55,80], 'X2': [55,100,90,80,30], 'X3': [50,50,60,75,30], 'X4': [40,80,30,80,100]}, index=['12/30','12/31','01/01','01/02','01/03']) 
ts

	X1	X2	X3	X4
12/30	65	55	50	40
12/31	95	100	50	80
01/01	65	90	60	30
01/02	55	80	75	80
01/03	80	30	30	100

A. 열의 선택

df

	date	X1	X2	X3	X4
0	12/30	65	55	50	40
1	12/31	95	100	50	80
2	01/01	65	90	60	30
3	01/02	55	80	75	80
4	01/03	80	30	30	100

- 방법1: df.? + col-name

# df.X1

- 방법2: df[?] + str, [str,str]

# df['X1'] # str 
# df[['X1']] # [str]
# df[['X1','X3']] # [str,str]

- 방법3: df.iloc[:,?] + int, int:int, [int,int], [bool,bool], range

# df.iloc[:,0] # int
# df.iloc[:,-2:] # int:int - 슬라이싱
# df.iloc[:,1::2] # int:int - 스트라이딩
# df.iloc[:,[0]] # [int]
# df.iloc[:,[0,1]] # [int,int]
# df.iloc[:,[True,True,False,False]] # bool의 list 
# df.iloc[:,range(2)] # range

- 방법4: df.loc[:,?] + str, ‘str:str’, [str,str], [bool,bool]

# df.loc[:,'X1'] # str
# df.loc[:,'X1':'X3'] # 'str':'str' -- 칼럼이름으로 슬라이싱 **
# df.loc[:,'X1'::2] # 'str':'str' -- 칼럼이름으로 스트라이딩 ** 
# df.loc[:,['X1']] # [str]
# df.loc[:,['X1','X4']] # [str,str]
# df.loc[:,[True,False,False,True]] # bool의 list

B. 행의 선택

- 방법1: df[] + int:int, str:str, [bool,bool], pd.Series([bool,bool]) – \((\star\star\star\star\star)\)

# df[:2] # int:int -- 슬라이싱 // df.iloc[:2,:], df.iloc[:2] 와 같음
# df[::2] # int:int -- 스트라이딩 
# ts['12/30':'01/02'] # str:str -- 슬라이싱
# ts['12/31'::2] # str:str -- 스트라이딩
# df[['12' in date for date in df.date]] # [bool,bool]
# df[df.X1 < 70] # pd.Series([bool,bool])

- 방법2: df.iloc[], df.iloc[,:] + int, int:int, [int,int], [bool,bool], range

# df.iloc[0] # int 
# df.iloc[-2:] # int:int -- 슬라이싱
# df.iloc[1::2] # int:int -- 스트라이딩
# df.iloc[[0]] # [int]
# df.iloc[[0,1]] # [int,int]
# df.iloc[['12' in date for date in df.date]] # [bool,bool]
# df.iloc[range(2)] # range

# df.iloc[0,:] # int 
# df.iloc[-2:,:] # int:int -- 슬라이싱
# df.iloc[1::2,:] # int:int -- 스트라이딩
# df.iloc[[0],:] # [int]
# df.iloc[[0,1],:] # [int,int]
# df.iloc[['12' in date for date in df.date],:] # [bool,bool]
# df.iloc[range(2),:] # range

- 방법3: df.loc[], df.loc[,:] + int, str, int:int, str:str, [int,int], [str,str], [bool,bool], pd.Series([bool,bool])

# df.loc[0] # int 
# ts.loc['12/30'] # str 
# df.loc[:2] # int:int 
# ts.loc[:'01/02'] # str:str 
# df.loc[[0,1]] # [int,int]
# ts.loc[['12/30','01/01']] # [str,str]
# df.loc[['12' in date for date in df.date]] # [bool,bool]
# df.loc[df.X1>70] # pd.Series([bool,bool])

C. 제 스타일

- 가장 안전한 코드

# df.loc[:,:]

- 상황1: 하나의 col을 뽑으려 할때 좋은 코드

# df.X1 # 최애 
# df['X1'] # 차애 
# df[['X1']] # 차애

- 상황2: row 슬라이싱을 할때 좋은 코드 \((\star\star\star)\)

# df[:5] # 최애 
# ts[:'01/02'] # 시계열인 경우

- 상황3: 조건에 맞는 row를 뽑을때 좋은 코드

# df[df.X1<60] # 최애
# df.loc[['12' in date for date in df.date]] # 차애

- 상황4: 하나의 row를 뽑으려 할때 좋은 코드

# df.iloc[0] # 최애 
# df.loc[0] # 차애

- 상황5: (row,col)을 뽑으려 할때 좋은 코드

# 최애: pd.Series를 뽑고 -> 인덱스로접근
# df.X1[0]
# df['X1'][0]

# 차애: iloc, loc 으로 한번에 뽑기
# df.iloc[0,0]
# df.loc[0,'X1']

위의 상황이외에는 df.loc[:,:]를 사용하는것이 유리하다

- 상황6: column 슬라이싱을 할때

# df.loc[:,'X1':'X3'] # 끝점포함

- 상황7: row + column 슬라이싱을 하는 가장 좋은 코드

# df.loc[::2,'X1':'X2']

- 상황8: 조건에 맞는 col을 뽑기에 가장 좋은 코드

# df.loc[:,[len(colname)>2 for colname in df.columns]]

- 상황9: 조건에 맞는 row, col을 뽑기에 가장 좋은 코드

# df.loc[df.X1>70,[len(colname)>2 for colname in df.columns]]

D. 제 스타일 X

- 제가 안쓰는 코드1

df[:1]

	date	X1	X2	X3	X4
0	12/30	65	55	50	40

이러면 내 입장에서는 마치 아래가 동작할 것 같잖아..

df[0]

KeyError: 0

- 제가 안쓰는 코드2: bool의 list를 사용할때 iloc은 가급적 쓰지마세요

df.iloc[list(df['X1']<80),:]

	date	X1	X2	X3	X4
0	12/30	65	55	50	40
2	01/01	65	90	60	30
3	01/02	55	80	75	80

이러면 마치 아래도 동작할 것 같잖아..

df.iloc[df['X1']<80,:]

NotImplementedError: iLocation based boolean indexing on an integer type is not available

E. 요약

- 알아두면 좋은 규칙

.iloc[] 와 .iloc[,:]는 완전히 동등하다.
.loc[] 와 .loc[,:]는 완전히 동등하다.
결과를 pd.Series 형태가 아닌 pd.DataFrame 형태로 얻고 싶다면 [[?]]를 사용하면 된다.

- 정리

type of indexer	`.`	`[]`	`.iloc`	`.loc`	내가 쓴다면?
int	X	X	O	\(\Delta\)	`df.iloc[3,:]`
int:int	X	O	O	\(\Delta\)	`df[3:5]`
[int,int]	X	X	O	\(\Delta\)	`df.iloc[idx,:]`
str	X	X	X	O	`ts.loc['time1',:]`
str:str	X	O	X	O	`ts.loc['time1':'time2',:]`
[str,str]	X	X	X	O	안할 듯
[bool,bool]	X	O	O	O	`df[filtered_idx]`
pd.Series([bool,bool])	X	O	X	O	`df[df.X1>20]`

type of indexer	`.`	`[]`	`.iloc`	`.loc`	내가 쓴다면?
int	X	X	O	X	`df.iloc[:,0]`
int:int	X	X	O	X	`df.iloc[:,0:2]`
[int,int]	X	X	O	X	`df.iloc[:,idx]`
str	O	O	X	O	`df.loc[:,'X1']`
str:str	X	X	X	O	`df.loc[:,'X1':'X4']`
[str,str]	X	O	X	O	`df.loc[:,colname_list]`
[bool,bool]	X	X	O	O	`df.loc[:,bool_list]`

5. Pandas: 기본기능

A. 열의 이름 변경

- 방법1: df.columns에 대입

df = pd.DataFrame(np.random.randn(3,2))
df.columns = ['A','B']
df

	A	B
0	0.037335	-0.540520
1	-0.019184	-0.711376
2	0.320825	-0.245878

- 방법2: df.set_axis()

df = pd.DataFrame(np.random.randn(3,2))
df.set_axis(['A','B'],axis=1)

	A	B
0	-0.252874	1.569584
1	-0.957351	-0.120713
2	1.400832	-0.916344

- 방법3: df.rename()

df = pd.DataFrame(np.random.randn(3,2))
df.rename({0:'AA',1:'BB'},axis=1)

	AA	BB
0	-1.793611	0.047263
1	-0.326602	0.054525
2	-1.117781	0.405474

B. 행의 이름 변경

- 방법1: df.index에 대입

df = pd.DataFrame(np.random.randn(3,2))
df

	0	1
0	-1.074150	0.030191
1	-2.527365	0.964030
2	0.305062	-0.858343

df.index = ['guebin','jiyoon','boram']
df

	0	1
guebin	-1.074150	0.030191
jiyoon	-2.527365	0.964030
boram	0.305062	-0.858343

- 방법2: df.set_axis()

df = pd.DataFrame(np.random.randn(3,2))
df.set_axis([11,22,33],axis=0)

	0	1
11	0.003062	0.005044
22	0.915182	0.303740
33	1.665422	-0.164989

- 방법3: df.rename()

df = pd.DataFrame(np.random.randn(3,2))
df.rename({1:'guebin'},axis=0)

	0	1
0	0.937158	0.504850
guebin	-0.891393	0.592022
2	1.386969	0.773002

- 방법4: 임의의 열을 행이름 으로 지정!

df = pd.DataFrame({'id':['2021-43052','2021-43052'], 'hour':[3,2], 'height':[176,172]})
df.set_index('id')

	hour	height
id
2021-43052	3	176
2021-43052	2	172

`#` A~B에 대한 연습문제

- 데이터 load

df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2022/master/posts/FIFA23_official_data.csv')
df.head()

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Kit Number	Best Overall Rating
0	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	Yes	<span class="pos pos28">SUB	Jul 1, 2018	NaN	2026	189cm	82kg	€157M	8.0	NaN
1	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	Yes	<span class="pos pos15">LCM	Jan 30, 2020	NaN	2026	179cm	69kg	€155M	8.0	NaN
2	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	No	<span class="pos pos7">LB	Sep 14, 2020	NaN	2024	172cm	69kg	€97.7M	19.0	NaN
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	Yes	<span class="pos pos13">RCM	Aug 30, 2015	NaN	2025	181cm	70kg	€198.9M	17.0	NaN
4	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	Yes	<span class="pos pos13">RCM	Sep 1, 2020	NaN	2026	172cm	68kg	€154.4M	23.0	NaN

5 rows × 29 columns

# 예제1: 열의 이름 출력하고, 열의 이름중 공백()이 있을 경우 언더바(_) 로 바꾸자.

컬럼출력

df.columns

Index(['ID', 'Name', 'Age', 'Photo', 'Nationality', 'Flag', 'Overall',
       'Potential', 'Club', 'Club Logo', 'Value', 'Wage', 'Special',
       'Preferred Foot', 'International Reputation', 'Weak Foot',
       'Skill Moves', 'Work Rate', 'Body Type', 'Real Face', 'Position',
       'Joined', 'Loaned From', 'Contract Valid Until', 'Height', 'Weight',
       'Release Clause', 'Kit Number', 'Best Overall Rating'],
      dtype='object')

df.columns에 직접대입

new_colnames = [l.replace(' ','_') for l in df.columns]

# df.columns = new_colnames
# df

set_axis() 이용

df.set_axis(new_colnames,axis=1)

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club_Logo	...	Real_Face	Position	Joined	Loaned_From	Contract_Valid_Until	Height	Weight	Release_Clause	Kit_Number	Best_Overall_Rating
0	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	Yes	<span class="pos pos28">SUB	Jul 1, 2018	NaN	2026	189cm	82kg	€157M	8.0	NaN
1	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	Yes	<span class="pos pos15">LCM	Jan 30, 2020	NaN	2026	179cm	69kg	€155M	8.0	NaN
2	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	No	<span class="pos pos7">LB	Sep 14, 2020	NaN	2024	172cm	69kg	€97.7M	19.0	NaN
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	Yes	<span class="pos pos13">RCM	Aug 30, 2015	NaN	2025	181cm	70kg	€198.9M	17.0	NaN
4	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	Yes	<span class="pos pos13">RCM	Sep 1, 2020	NaN	2026	172cm	68kg	€154.4M	23.0	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
17655	269526	Deng Xiongtao	19	https://cdn.sofifa.net/players/269/526/23_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	48	61	Meizhou Hakka	https://cdn.sofifa.net/teams/114628/30.png	...	No	<span class="pos pos29">RES	Apr 11, 2022	NaN	2027	190cm	78kg	€218K	35.0	NaN
17656	267946	22 Lim Jun Sub	17	https://cdn.sofifa.net/players/267/946/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	48	64	Jeju United FC	https://cdn.sofifa.net/teams/1478/30.png	...	No	<span class="pos pos29">RES	Jan 1, 2022	NaN	2026	195cm	84kg	€188K	21.0	NaN
17657	270567	A. Demir	25	https://cdn.sofifa.net/players/270/567/23_60.png	Turkey	https://cdn.sofifa.net/flags/tr.png	51	56	Ümraniyespor	https://cdn.sofifa.net/teams/113796/30.png	...	No	<span class="pos pos29">RES	Jun 6, 2021	NaN	2023	190cm	82kg	€142K	12.0	NaN
17658	256624	21 S. Czajor	18	https://cdn.sofifa.net/players/256/624/21_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	50	65	Fleetwood Town	https://cdn.sofifa.net/teams/112260/30.png	...	No	<span class="pos pos29">RES	Jan 1, 2020	NaN	2021	187cm	79kg	€214K	40.0	NaN
17659	256376	21 F. Jakobsson	20	https://cdn.sofifa.net/players/256/376/21_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	50	61	IFK Norrköping	https://cdn.sofifa.net/teams/702/30.png	...	No	<span class="pos pos29">RES	Jan 8, 2020	NaN	2021	186cm	78kg	€131K	30.0	NaN

17660 rows × 29 columns

rename() 이용

df.rename({l:l.replace(' ','_') for l in df.columns if ' ' in l},axis=1)

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club_Logo	...	Real_Face	Position	Joined	Loaned_From	Contract_Valid_Until	Height	Weight	Release_Clause	Kit_Number	Best_Overall_Rating
0	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	Yes	<span class="pos pos28">SUB	Jul 1, 2018	NaN	2026	189cm	82kg	€157M	8.0	NaN
1	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	Yes	<span class="pos pos15">LCM	Jan 30, 2020	NaN	2026	179cm	69kg	€155M	8.0	NaN
2	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	No	<span class="pos pos7">LB	Sep 14, 2020	NaN	2024	172cm	69kg	€97.7M	19.0	NaN
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	Yes	<span class="pos pos13">RCM	Aug 30, 2015	NaN	2025	181cm	70kg	€198.9M	17.0	NaN
4	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	Yes	<span class="pos pos13">RCM	Sep 1, 2020	NaN	2026	172cm	68kg	€154.4M	23.0	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
17655	269526	Deng Xiongtao	19	https://cdn.sofifa.net/players/269/526/23_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	48	61	Meizhou Hakka	https://cdn.sofifa.net/teams/114628/30.png	...	No	<span class="pos pos29">RES	Apr 11, 2022	NaN	2027	190cm	78kg	€218K	35.0	NaN
17656	267946	22 Lim Jun Sub	17	https://cdn.sofifa.net/players/267/946/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	48	64	Jeju United FC	https://cdn.sofifa.net/teams/1478/30.png	...	No	<span class="pos pos29">RES	Jan 1, 2022	NaN	2026	195cm	84kg	€188K	21.0	NaN
17657	270567	A. Demir	25	https://cdn.sofifa.net/players/270/567/23_60.png	Turkey	https://cdn.sofifa.net/flags/tr.png	51	56	Ümraniyespor	https://cdn.sofifa.net/teams/113796/30.png	...	No	<span class="pos pos29">RES	Jun 6, 2021	NaN	2023	190cm	82kg	€142K	12.0	NaN
17658	256624	21 S. Czajor	18	https://cdn.sofifa.net/players/256/624/21_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	50	65	Fleetwood Town	https://cdn.sofifa.net/teams/112260/30.png	...	No	<span class="pos pos29">RES	Jan 1, 2020	NaN	2021	187cm	79kg	€214K	40.0	NaN
17659	256376	21 F. Jakobsson	20	https://cdn.sofifa.net/players/256/376/21_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	50	61	IFK Norrköping	https://cdn.sofifa.net/teams/702/30.png	...	No	<span class="pos pos29">RES	Jan 8, 2020	NaN	2021	186cm	78kg	€131K	30.0	NaN

17660 rows × 29 columns

#

예제2: ID를 row-index로 지정하라.

직접지정

# df.index = df.ID
# df

set_axis()

df.set_axis(df.ID,axis=0)

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Kit Number	Best Overall Rating
ID
209658	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	Yes	<span class="pos pos28">SUB	Jul 1, 2018	NaN	2026	189cm	82kg	€157M	8.0	NaN
212198	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	Yes	<span class="pos pos15">LCM	Jan 30, 2020	NaN	2026	179cm	69kg	€155M	8.0	NaN
224334	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	No	<span class="pos pos7">LB	Sep 14, 2020	NaN	2024	172cm	69kg	€97.7M	19.0	NaN
192985	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	Yes	<span class="pos pos13">RCM	Aug 30, 2015	NaN	2025	181cm	70kg	€198.9M	17.0	NaN
224232	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	Yes	<span class="pos pos13">RCM	Sep 1, 2020	NaN	2026	172cm	68kg	€154.4M	23.0	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
269526	269526	Deng Xiongtao	19	https://cdn.sofifa.net/players/269/526/23_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	48	61	Meizhou Hakka	https://cdn.sofifa.net/teams/114628/30.png	...	No	<span class="pos pos29">RES	Apr 11, 2022	NaN	2027	190cm	78kg	€218K	35.0	NaN
267946	267946	22 Lim Jun Sub	17	https://cdn.sofifa.net/players/267/946/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	48	64	Jeju United FC	https://cdn.sofifa.net/teams/1478/30.png	...	No	<span class="pos pos29">RES	Jan 1, 2022	NaN	2026	195cm	84kg	€188K	21.0	NaN
270567	270567	A. Demir	25	https://cdn.sofifa.net/players/270/567/23_60.png	Turkey	https://cdn.sofifa.net/flags/tr.png	51	56	Ümraniyespor	https://cdn.sofifa.net/teams/113796/30.png	...	No	<span class="pos pos29">RES	Jun 6, 2021	NaN	2023	190cm	82kg	€142K	12.0	NaN
256624	256624	21 S. Czajor	18	https://cdn.sofifa.net/players/256/624/21_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	50	65	Fleetwood Town	https://cdn.sofifa.net/teams/112260/30.png	...	No	<span class="pos pos29">RES	Jan 1, 2020	NaN	2021	187cm	79kg	€214K	40.0	NaN
256376	256376	21 F. Jakobsson	20	https://cdn.sofifa.net/players/256/376/21_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	50	61	IFK Norrköping	https://cdn.sofifa.net/teams/702/30.png	...	No	<span class="pos pos29">RES	Jan 8, 2020	NaN	2021	186cm	78kg	€131K	30.0	NaN

17660 rows × 29 columns

rename()

df.rename({i:j for i,j in zip(df.index, df.ID)})

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Kit Number	Best Overall Rating
209658	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	Yes	<span class="pos pos28">SUB	Jul 1, 2018	NaN	2026	189cm	82kg	€157M	8.0	NaN
212198	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	Yes	<span class="pos pos15">LCM	Jan 30, 2020	NaN	2026	179cm	69kg	€155M	8.0	NaN
224334	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	No	<span class="pos pos7">LB	Sep 14, 2020	NaN	2024	172cm	69kg	€97.7M	19.0	NaN
192985	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	Yes	<span class="pos pos13">RCM	Aug 30, 2015	NaN	2025	181cm	70kg	€198.9M	17.0	NaN
224232	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	Yes	<span class="pos pos13">RCM	Sep 1, 2020	NaN	2026	172cm	68kg	€154.4M	23.0	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
269526	269526	Deng Xiongtao	19	https://cdn.sofifa.net/players/269/526/23_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	48	61	Meizhou Hakka	https://cdn.sofifa.net/teams/114628/30.png	...	No	<span class="pos pos29">RES	Apr 11, 2022	NaN	2027	190cm	78kg	€218K	35.0	NaN
267946	267946	22 Lim Jun Sub	17	https://cdn.sofifa.net/players/267/946/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	48	64	Jeju United FC	https://cdn.sofifa.net/teams/1478/30.png	...	No	<span class="pos pos29">RES	Jan 1, 2022	NaN	2026	195cm	84kg	€188K	21.0	NaN
270567	270567	A. Demir	25	https://cdn.sofifa.net/players/270/567/23_60.png	Turkey	https://cdn.sofifa.net/flags/tr.png	51	56	Ümraniyespor	https://cdn.sofifa.net/teams/113796/30.png	...	No	<span class="pos pos29">RES	Jun 6, 2021	NaN	2023	190cm	82kg	€142K	12.0	NaN
256624	256624	21 S. Czajor	18	https://cdn.sofifa.net/players/256/624/21_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	50	65	Fleetwood Town	https://cdn.sofifa.net/teams/112260/30.png	...	No	<span class="pos pos29">RES	Jan 1, 2020	NaN	2021	187cm	79kg	€214K	40.0	NaN
256376	256376	21 F. Jakobsson	20	https://cdn.sofifa.net/players/256/376/21_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	50	61	IFK Norrköping	https://cdn.sofifa.net/teams/702/30.png	...	No	<span class="pos pos29">RES	Jan 8, 2020	NaN	2021	186cm	78kg	€131K	30.0	NaN

17660 rows × 29 columns

set_index()

df.set_index('ID')

	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	Value	...	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Kit Number	Best Overall Rating
ID
209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	€91M	...	Yes	<span class="pos pos28">SUB	Jul 1, 2018	NaN	2026	189cm	82kg	€157M	8.0	NaN
212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	€78.5M	...	Yes	<span class="pos pos15">LCM	Jan 30, 2020	NaN	2026	179cm	69kg	€155M	8.0	NaN
224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	€46.5M	...	No	<span class="pos pos7">LB	Sep 14, 2020	NaN	2024	172cm	69kg	€97.7M	19.0	NaN
192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	€107.5M	...	Yes	<span class="pos pos13">RCM	Aug 30, 2015	NaN	2025	181cm	70kg	€198.9M	17.0	NaN
224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	€89.5M	...	Yes	<span class="pos pos13">RCM	Sep 1, 2020	NaN	2026	172cm	68kg	€154.4M	23.0	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
269526	Deng Xiongtao	19	https://cdn.sofifa.net/players/269/526/23_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	48	61	Meizhou Hakka	https://cdn.sofifa.net/teams/114628/30.png	€100K	...	No	<span class="pos pos29">RES	Apr 11, 2022	NaN	2027	190cm	78kg	€218K	35.0	NaN
267946	22 Lim Jun Sub	17	https://cdn.sofifa.net/players/267/946/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	48	64	Jeju United FC	https://cdn.sofifa.net/teams/1478/30.png	€100K	...	No	<span class="pos pos29">RES	Jan 1, 2022	NaN	2026	195cm	84kg	€188K	21.0	NaN
270567	A. Demir	25	https://cdn.sofifa.net/players/270/567/23_60.png	Turkey	https://cdn.sofifa.net/flags/tr.png	51	56	Ümraniyespor	https://cdn.sofifa.net/teams/113796/30.png	€70K	...	No	<span class="pos pos29">RES	Jun 6, 2021	NaN	2023	190cm	82kg	€142K	12.0	NaN
256624	21 S. Czajor	18	https://cdn.sofifa.net/players/256/624/21_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	50	65	Fleetwood Town	https://cdn.sofifa.net/teams/112260/30.png	€90K	...	No	<span class="pos pos29">RES	Jan 1, 2020	NaN	2021	187cm	79kg	€214K	40.0	NaN
256376	21 F. Jakobsson	20	https://cdn.sofifa.net/players/256/376/21_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	50	61	IFK Norrköping	https://cdn.sofifa.net/teams/702/30.png	€90K	...	No	<span class="pos pos29">RES	Jan 8, 2020	NaN	2021	186cm	78kg	€131K	30.0	NaN

17660 rows × 28 columns

#

C. `df.T`

- 데이터 load

df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2022/master/posts/FIFA23_official_data.csv')
df.head()

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Kit Number	Best Overall Rating
0	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	Yes	<span class="pos pos28">SUB	Jul 1, 2018	NaN	2026	189cm	82kg	€157M	8.0	NaN
1	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	Yes	<span class="pos pos15">LCM	Jan 30, 2020	NaN	2026	179cm	69kg	€155M	8.0	NaN
2	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	No	<span class="pos pos7">LB	Sep 14, 2020	NaN	2024	172cm	69kg	€97.7M	19.0	NaN
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	Yes	<span class="pos pos13">RCM	Aug 30, 2015	NaN	2025	181cm	70kg	€198.9M	17.0	NaN
4	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	Yes	<span class="pos pos13">RCM	Sep 1, 2020	NaN	2026	172cm	68kg	€154.4M	23.0	NaN

5 rows × 29 columns

- df.T를 이용하여 데이터를 살피면 편리함

df.T.iloc[:,:2]

	0	1
ID	209658	212198
Name	L. Goretzka	Bruno Fernandes
Age	27	27
Photo	https://cdn.sofifa.net/players/209/658/23_60.png	https://cdn.sofifa.net/players/212/198/23_60.png
Nationality	Germany	Portugal
Flag	https://cdn.sofifa.net/flags/de.png	https://cdn.sofifa.net/flags/pt.png
Overall	87	86
Potential	88	87
Club	FC Bayern München	Manchester United
Club Logo	https://cdn.sofifa.net/teams/21/30.png	https://cdn.sofifa.net/teams/11/30.png
Value	€91M	€78.5M
Wage	€115K	€190K
Special	2312	2305
Preferred Foot	Right	Right
International Reputation	4.0	3.0
Weak Foot	4.0	3.0
Skill Moves	3.0	4.0
Work Rate	High/ Medium	High/ High
Body Type	Unique	Unique
Real Face	Yes	Yes
Position	<span class="pos pos28">SUB	<span class="pos pos15">LCM
Joined	Jul 1, 2018	Jan 30, 2020
Loaned From	NaN	NaN
Contract Valid Until	2026	2026
Height	189cm	179cm
Weight	82kg	69kg
Release Clause	€157M	€155M
Kit Number	8.0	8.0
Best Overall Rating	NaN	NaN

- 출력옵션 조정

pd.options.display.max_rows = 12
display(df.T.iloc[:,:2])
pd.reset_option("display.max_rows")

	0	1
ID	209658	212198
Name	L. Goretzka	Bruno Fernandes
Age	27	27
Photo	https://cdn.sofifa.net/players/209/658/23_60.png	https://cdn.sofifa.net/players/212/198/23_60.png
Nationality	Germany	Portugal
...	...	...
Height	189cm	179cm
Weight	82kg	69kg
Release Clause	€157M	€155M
Kit Number	8.0	8.0
Best Overall Rating	NaN	NaN

29 rows × 2 columns

이 예제에서는 줄이는 옵션을 사용했지만 보통은 늘려서 사용함

D. `df.dtypes`, `s.dtype`, `df.select_dtypes()`

- df.dtypes

df.dtypes

ID                            int64
Name                         object
Age                           int64
Photo                        object
Nationality                  object
Flag                         object
Overall                       int64
Potential                     int64
Club                         object
Club Logo                    object
Value                        object
Wage                         object
Special                       int64
Preferred Foot               object
International Reputation    float64
Weak Foot                   float64
Skill Moves                 float64
Work Rate                    object
Body Type                    object
Real Face                    object
Position                     object
Joined                       object
Loaned From                  object
Contract Valid Until         object
Height                       object
Weight                       object
Release Clause               object
Kit Number                  float64
Best Overall Rating          object
dtype: object

- s.dtype

df.Name.dtype

dtype('O')

- ==를 이용한 자료형 체크

df.Name.dtype == object
df.Name.dtype == np.object_

True

df.Age.dtype == int
df.Age.dtype == np.int64

True

df['International Reputation'].dtype == float
df['International Reputation'].dtype == np.float64

True

# 예제1: df에서 int 자료형만 출력

- (풀이1)

df.loc[:,[l == int for l in df.dtypes]]
df.loc[:,[l == np.int64 for l in df.dtypes]]

	ID	Age	Overall	Potential	Special
0	209658	27	87	88	2312
1	212198	27	86	87	2305
2	224334	30	85	85	2303
3	192985	31	91	91	2303
4	224232	25	86	89	2296
...	...	...	...	...	...
17655	269526	19	48	61	762
17656	267946	17	48	64	761
17657	270567	25	51	56	759
17658	256624	18	50	65	758
17659	256376	20	50	61	749

17660 rows × 5 columns

- (풀이2)

df.select_dtypes(int)
df.select_dtypes(np.int64)
df.select_dtypes([int])
df.select_dtypes([np.int64])

	ID	Age	Overall	Potential	Special
0	209658	27	87	88	2312
1	212198	27	86	87	2305
2	224334	30	85	85	2303
3	192985	31	91	91	2303
4	224232	25	86	89	2296
...	...	...	...	...	...
17655	269526	19	48	61	762
17656	267946	17	48	64	761
17657	270567	25	51	56	759
17658	256624	18	50	65	758
17659	256376	20	50	61	749

17660 rows × 5 columns

#

# 예제2: df에서 int, float 자료형만 출력 – select_dtypes() 이용

df.select_dtypes([int,float])
df.select_dtypes([np.int64,np.float64])
df.select_dtypes('number')
df.select_dtypes(['number'])

	ID	Age	Overall	Potential	Special	International Reputation	Weak Foot	Skill Moves	Kit Number
0	209658	27	87	88	2312	4.0	4.0	3.0	8.0
1	212198	27	86	87	2305	3.0	3.0	4.0	8.0
2	224334	30	85	85	2303	2.0	3.0	3.0	19.0
3	192985	31	91	91	2303	4.0	5.0	4.0	17.0
4	224232	25	86	89	2296	3.0	3.0	3.0	23.0
...	...	...	...	...	...	...	...	...	...
17655	269526	19	48	61	762	1.0	3.0	1.0	35.0
17656	267946	17	48	64	761	1.0	2.0	1.0	21.0
17657	270567	25	51	56	759	1.0	2.0	1.0	12.0
17658	256624	18	50	65	758	1.0	2.0	1.0	40.0
17659	256376	20	50	61	749	1.0	2.0	1.0	30.0

17660 rows × 9 columns

#

# 예제3: df에서 object 자료형만 출력 – select_dtypes() 이용

df.select_dtypes(object)
df.select_dtypes([object])

	Name	Photo	Nationality	Flag	Club	Club Logo	Value	Wage	Preferred Foot	Work Rate	Body Type	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Best Overall Rating
0	L. Goretzka	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	€91M	€115K	Right	High/ Medium	Unique	Yes	<span class="pos pos28">SUB	Jul 1, 2018	NaN	2026	189cm	82kg	€157M	NaN
1	Bruno Fernandes	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	Manchester United	https://cdn.sofifa.net/teams/11/30.png	€78.5M	€190K	Right	High/ High	Unique	Yes	<span class="pos pos15">LCM	Jan 30, 2020	NaN	2026	179cm	69kg	€155M	NaN
2	M. Acuña	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	€46.5M	€46K	Left	High/ High	Stocky (170-185)	No	<span class="pos pos7">LB	Sep 14, 2020	NaN	2024	172cm	69kg	€97.7M	NaN
3	K. De Bruyne	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	Manchester City	https://cdn.sofifa.net/teams/10/30.png	€107.5M	€350K	Right	High/ High	Unique	Yes	<span class="pos pos13">RCM	Aug 30, 2015	NaN	2025	181cm	70kg	€198.9M	NaN
4	N. Barella	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	Inter	https://cdn.sofifa.net/teams/44/30.png	€89.5M	€110K	Right	High/ High	Normal (170-)	Yes	<span class="pos pos13">RCM	Sep 1, 2020	NaN	2026	172cm	68kg	€154.4M	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
17655	Deng Xiongtao	https://cdn.sofifa.net/players/269/526/23_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	Meizhou Hakka	https://cdn.sofifa.net/teams/114628/30.png	€100K	€500	Right	Medium/ Medium	Normal (185+)	No	<span class="pos pos29">RES	Apr 11, 2022	NaN	2027	190cm	78kg	€218K	NaN
17656	22 Lim Jun Sub	https://cdn.sofifa.net/players/267/946/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	Jeju United FC	https://cdn.sofifa.net/teams/1478/30.png	€100K	€500	Right	Medium/ Medium	Lean (185+)	No	<span class="pos pos29">RES	Jan 1, 2022	NaN	2026	195cm	84kg	€188K	NaN
17657	A. Demir	https://cdn.sofifa.net/players/270/567/23_60.png	Turkey	https://cdn.sofifa.net/flags/tr.png	Ümraniyespor	https://cdn.sofifa.net/teams/113796/30.png	€70K	€2K	Right	Medium/ Medium	Lean (185+)	No	<span class="pos pos29">RES	Jun 6, 2021	NaN	2023	190cm	82kg	€142K	NaN
17658	21 S. Czajor	https://cdn.sofifa.net/players/256/624/21_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	Fleetwood Town	https://cdn.sofifa.net/teams/112260/30.png	€90K	€500	Right	Medium/ Medium	Normal (185+)	No	<span class="pos pos29">RES	Jan 1, 2020	NaN	2021	187cm	79kg	€214K	NaN
17659	21 F. Jakobsson	https://cdn.sofifa.net/players/256/376/21_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	IFK Norrköping	https://cdn.sofifa.net/teams/702/30.png	€90K	€500	Left	Medium/ Medium	Normal (185+)	No	<span class="pos pos29">RES	Jan 8, 2020	NaN	2021	186cm	78kg	€131K	NaN

17660 rows × 20 columns

#

E. `df.sort_values()`

- 예시1: 나이가 어린 순서대로 정렬

df.sort_values(by='Age')

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Kit Number	Best Overall Rating
17636	263636	22 D. Oncescu	15	https://cdn.sofifa.net/players/263/636/22_60.png	Romania	https://cdn.sofifa.net/flags/ro.png	50	72	FC Dinamo 1948 Bucureşti	https://cdn.sofifa.net/teams/100757/30.png	...	No	<span class="pos pos29">RES	Jun 1, 2021	NaN	2025	190cm	77kg	€306K	34.0	NaN
13712	271072	E. Topcu	16	https://cdn.sofifa.net/players/271/072/23_60.png	Republic of Ireland	https://cdn.sofifa.net/flags/ie.png	48	58	Drogheda United	https://cdn.sofifa.net/teams/1572/30.png	...	No	<span class="pos pos29">RES	Jul 8, 2022	NaN	2022	183cm	65kg	€175K	20.0	NaN
13078	259442	22 R. van den Berg	16	https://cdn.sofifa.net/players/259/442/22_60.png	Netherlands	https://cdn.sofifa.net/flags/nl.png	60	81	PEC Zwolle	https://cdn.sofifa.net/teams/1914/30.png	...	No	<span class="pos pos29">RES	May 24, 2020	NaN	2024	190cm	73kg	€1.8M	33.0	NaN
11257	266205	22 Y. Koré	16	https://cdn.sofifa.net/players/266/205/22_60.png	France	https://cdn.sofifa.net/flags/fr.png	59	74	Paris FC	https://cdn.sofifa.net/teams/111817/30.png	...	No	<span class="pos pos29">RES	Aug 11, 2022	NaN	2025	187cm	75kg	€1.1M	34.0	NaN
11278	261873	21 H. Kumagai	16	https://cdn.sofifa.net/players/261/873/21_60.png	Japan	https://cdn.sofifa.net/flags/jp.png	52	70	Vegalta Sendai	https://cdn.sofifa.net/teams/112836/30.png	...	No	<span class="pos pos29">RES	Apr 16, 2021	NaN	2023	174cm	64kg	€375K	48.0	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
16311	254196	21 L. Fernández	42	https://cdn.sofifa.net/players/254/196/21_60.png	Colombia	https://cdn.sofifa.net/flags/co.png	61	61	Sociedad Deportiva Aucas	https://cdn.sofifa.net/teams/110987/30.png	...	No	<span class="pos pos28">SUB	Jan 29, 2018	NaN	2024	187cm	82kg	€75K	1.0	NaN
16036	216692	S. Torrico	42	https://cdn.sofifa.net/players/216/692/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	72	72	San Lorenzo de Almagro	https://cdn.sofifa.net/teams/1013/30.png	...	No	<span class="pos pos0">GK	Apr 25, 2013	NaN	2022	183cm	84kg	€375K	12.0	NaN
17257	645	17 D. Andersson	43	https://cdn.sofifa.net/players/000/645/17_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	57	57	Helsingborgs IF	https://cdn.sofifa.net/teams/432/30.png	...	No	<span class="pos pos28">SUB	Apr 21, 2016	NaN	2022	187cm	85kg	NaN	39.0	NaN
15375	1179	G. Buffon	44	https://cdn.sofifa.net/players/001/179/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	79	79	Parma	https://cdn.sofifa.net/teams/50/30.png	...	Yes	<span class="pos pos0">GK	Jul 1, 2021	NaN	2024	192cm	92kg	€3M	1.0	NaN
15272	254704	22 K. Miura	54	https://cdn.sofifa.net/players/254/704/22_60.png	Japan	https://cdn.sofifa.net/flags/jp.png	56	56	Yokohama FC	https://cdn.sofifa.net/teams/113197/30.png	...	No	<span class="pos pos29">RES	Jul 1, 2005	NaN	2022	177cm	72kg	NaN	11.0	NaN

17660 rows × 29 columns

- 예시2: 나이가 많은 순서대로 정렬

df.sort_values(by='Age',ascending=False)

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Kit Number	Best Overall Rating
15272	254704	22 K. Miura	54	https://cdn.sofifa.net/players/254/704/22_60.png	Japan	https://cdn.sofifa.net/flags/jp.png	56	56	Yokohama FC	https://cdn.sofifa.net/teams/113197/30.png	...	No	<span class="pos pos29">RES	Jul 1, 2005	NaN	2022	177cm	72kg	NaN	11.0	NaN
15375	1179	G. Buffon	44	https://cdn.sofifa.net/players/001/179/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	79	79	Parma	https://cdn.sofifa.net/teams/50/30.png	...	Yes	<span class="pos pos0">GK	Jul 1, 2021	NaN	2024	192cm	92kg	€3M	1.0	NaN
17257	645	17 D. Andersson	43	https://cdn.sofifa.net/players/000/645/17_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	57	57	Helsingborgs IF	https://cdn.sofifa.net/teams/432/30.png	...	No	<span class="pos pos28">SUB	Apr 21, 2016	NaN	2022	187cm	85kg	NaN	39.0	NaN
16036	216692	S. Torrico	42	https://cdn.sofifa.net/players/216/692/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	72	72	San Lorenzo de Almagro	https://cdn.sofifa.net/teams/1013/30.png	...	No	<span class="pos pos0">GK	Apr 25, 2013	NaN	2022	183cm	84kg	€375K	12.0	NaN
16311	254196	21 L. Fernández	42	https://cdn.sofifa.net/players/254/196/21_60.png	Colombia	https://cdn.sofifa.net/flags/co.png	61	61	Sociedad Deportiva Aucas	https://cdn.sofifa.net/teams/110987/30.png	...	No	<span class="pos pos28">SUB	Jan 29, 2018	NaN	2024	187cm	82kg	€75K	1.0	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
17360	261023	21 H. Broun	16	https://cdn.sofifa.net/players/261/023/21_60.png	Scotland	https://cdn.sofifa.net/flags/gb-sct.png	52	72	Kilmarnock	https://cdn.sofifa.net/teams/82/30.png	...	No	<span class="pos pos29">RES	Sep 17, 2020	NaN	2022	182cm	70kg	€523K	40.0	NaN
15536	263639	22 M. Pavel	16	https://cdn.sofifa.net/players/263/639/22_60.png	Romania	https://cdn.sofifa.net/flags/ro.png	51	69	FC Dinamo 1948 Bucureşti	https://cdn.sofifa.net/teams/100757/30.png	...	No	<span class="pos pos29">RES	Jul 1, 2021	NaN	2023	178cm	66kg	€277K	77.0	NaN
11398	256405	21 W. Essanoussi	16	https://cdn.sofifa.net/players/256/405/21_60.png	Netherlands	https://cdn.sofifa.net/flags/nl.png	59	75	VVV-Venlo	https://cdn.sofifa.net/teams/100651/30.png	...	No	<span class="pos pos29">RES	Jul 1, 2019	NaN	2022	178cm	70kg	€1.1M	24.0	NaN
15030	270594	T. Walczak	16	https://cdn.sofifa.net/players/270/594/23_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	54	68	Wisła Płock	https://cdn.sofifa.net/teams/1569/30.png	...	No	<span class="pos pos29">RES	Sep 7, 2021	NaN	2023	191cm	88kg	€494K	99.0	NaN
17636	263636	22 D. Oncescu	15	https://cdn.sofifa.net/players/263/636/22_60.png	Romania	https://cdn.sofifa.net/flags/ro.png	50	72	FC Dinamo 1948 Bucureşti	https://cdn.sofifa.net/teams/100757/30.png	...	No	<span class="pos pos29">RES	Jun 1, 2021	NaN	2025	190cm	77kg	€306K	34.0	NaN

17660 rows × 29 columns

- 예시3: 능력치가 좋은 순서대로 정렬

df.sort_values(by='Overall',ascending=False)

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Kit Number	Best Overall Rating
41	188545	R. Lewandowski	33	https://cdn.sofifa.net/players/188/545/23_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	91	91	FC Barcelona	https://cdn.sofifa.net/teams/241/30.png	...	Yes	<span class="pos pos25">ST	Jul 18, 2022	NaN	2025	185cm	81kg	€172.2M	9.0	NaN
124	165153	K. Benzema	34	https://cdn.sofifa.net/players/165/153/23_60.png	France	https://cdn.sofifa.net/flags/fr.png	91	91	Real Madrid CF	https://cdn.sofifa.net/teams/243/30.png	...	Yes	<span class="pos pos21">CF	Jul 9, 2009	NaN	2023	185cm	81kg	€131.2M	9.0	NaN
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	Yes	<span class="pos pos13">RCM	Aug 30, 2015	NaN	2025	181cm	70kg	€198.9M	17.0	NaN
56	158023	L. Messi	35	https://cdn.sofifa.net/players/158/023/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	91	91	Paris Saint-Germain	https://cdn.sofifa.net/teams/73/30.png	...	Yes	<span class="pos pos23">RW	Aug 10, 2021	NaN	2023	169cm	67kg	€99.9M	30.0	NaN
75	231747	K. Mbappé	23	https://cdn.sofifa.net/players/231/747/23_60.png	France	https://cdn.sofifa.net/flags/fr.png	91	95	Paris Saint-Germain	https://cdn.sofifa.net/teams/73/30.png	...	Yes	<span class="pos pos25">ST	Jul 1, 2018	NaN	2025	182cm	73kg	€366.7M	7.0	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
15513	266751	22 Jung Ho Yeon	20	https://cdn.sofifa.net/players/266/751/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	45	53	GwangJu FC	https://cdn.sofifa.net/teams/112258/30.png	...	No	<span class="pos pos29">RES	Jan 20, 2022	NaN	2026	180cm	73kg	€145K	23.0	NaN
16215	268279	22 J. Looschen	24	https://cdn.sofifa.net/players/268/279/22_60.png	Germany	https://cdn.sofifa.net/flags/de.png	44	47	SV Meppen	https://cdn.sofifa.net/teams/110597/30.png	...	No	<span class="pos pos29">RES	Mar 19, 2022	NaN	2026	178cm	78kg	€92K	42.0	NaN
16042	255283	20 Kim Yeong Geun	22	https://cdn.sofifa.net/players/255/283/20_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	44	49	Gyeongnam FC	https://cdn.sofifa.net/teams/111588/30.png	...	No	<span class="pos pos29">RES	Jan 9, 2020	NaN	2020	174cm	71kg	€53K	43.0	NaN
14634	269038	22 Zhang Wenxuan	16	https://cdn.sofifa.net/players/269/038/22_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	44	59	Guangzhou FC	https://cdn.sofifa.net/teams/111839/30.png	...	No	<span class="pos pos29">RES	May 1, 2022	NaN	2022	175cm	70kg	€239K	29.0	NaN
17618	168933	07 I. Paskov	33	https://cdn.sofifa.net/players/168/933/07_60.png	Bulgaria	https://cdn.sofifa.net/flags/bg.png	43	42	NaN	https://cdn.sofifa.net/flags/bg.png	...	NaN	<span class="pos pos28">SUB	NaN	NaN	NaN	184cm	79kg	NaN	24.0	NaN

17660 rows × 29 columns

F. `df.info()`

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 17660 entries, 0 to 17659
Data columns (total 29 columns):
 #   Column                    Non-Null Count  Dtype  
---  ------                    --------------  -----  
 0   ID                        17660 non-null  int64  
 1   Name                      17660 non-null  object 
 2   Age                       17660 non-null  int64  
 3   Photo                     17660 non-null  object 
 4   Nationality               17660 non-null  object 
 5   Flag                      17660 non-null  object 
 6   Overall                   17660 non-null  int64  
 7   Potential                 17660 non-null  int64  
 8   Club                      17449 non-null  object 
 9   Club Logo                 17660 non-null  object 
 10  Value                     17660 non-null  object 
 11  Wage                      17660 non-null  object 
 12  Special                   17660 non-null  int64  
 13  Preferred Foot            17660 non-null  object 
 14  International Reputation  17660 non-null  float64
 15  Weak Foot                 17660 non-null  float64
 16  Skill Moves               17660 non-null  float64
 17  Work Rate                 17660 non-null  object 
 18  Body Type                 17622 non-null  object 
 19  Real Face                 17622 non-null  object 
 20  Position                  17625 non-null  object 
 21  Joined                    16562 non-null  object 
 22  Loaned From               694 non-null    object 
 23  Contract Valid Until      17299 non-null  object 
 24  Height                    17660 non-null  object 
 25  Weight                    17660 non-null  object 
 26  Release Clause            16509 non-null  object 
 27  Kit Number                17625 non-null  float64
 28  Best Overall Rating       21 non-null     object 
dtypes: float64(4), int64(5), object(20)
memory usage: 3.9+ MB

6. Pandas: query

ts = pd.DataFrame(np.random.normal(size=(20,4)),columns=list('ABCD'),index=pd.date_range('20221226',periods=20)).assign(Sex=['M']*10+['F']*10)
ts

	A	B	C	D	Sex
2022-12-26	0.913373	1.273686	-1.031498	0.107483	M
2022-12-27	-0.231464	-2.486921	-2.037792	0.455930	M
2022-12-28	0.044797	0.013809	-0.780978	0.288263	M
2022-12-29	0.584282	1.763700	0.943253	0.153924	M
2022-12-30	0.210974	-0.691147	-0.484299	0.265967	M
2022-12-31	1.062767	-0.958027	-0.128911	-0.156103	M
2023-01-01	1.358383	0.972339	-0.888977	-1.260350	M
2023-01-02	-0.095874	-0.382660	0.846097	0.490706	M
2023-01-03	-0.918114	0.040202	-0.837528	0.290037	M
2023-01-04	-1.651541	1.264967	0.334392	-1.445567	M
2023-01-05	-0.164268	-0.424999	1.506550	-0.254232	F
2023-01-06	-0.949612	1.078584	0.079759	0.897018	F
2023-01-07	-0.795211	0.749976	1.882239	-0.847576	F
2023-01-08	-0.326690	-0.265898	0.398331	0.198163	F
2023-01-09	-0.770815	-0.143819	0.095757	-0.716950	F
2023-01-10	-0.519762	0.619891	0.317133	-0.728839	F
2023-01-11	1.033974	-0.098040	-1.367873	-0.777833	F
2023-01-12	0.351120	0.137920	-1.809062	0.470261	F
2023-01-13	-0.789317	-0.179441	0.615646	-0.110530	F
2023-01-14	0.183356	0.362680	0.318493	-1.005962	F

A. 기본 query

- 예시1: A>0 and B<0

#ts[(ts.A>0) & (ts.B<0)]
ts.query('A>0 and B<0')

	A	B	C	D	Sex
2022-12-30	0.210974	-0.691147	-0.484299	0.265967	M
2022-12-31	1.062767	-0.958027	-0.128911	-0.156103	M
2023-01-11	1.033974	-0.098040	-1.367873	-0.777833	F

- 예시2: A<B<C

ts.query('A<B<C')

	A	B	C	D	Sex
2023-01-07	-0.795211	0.749976	1.882239	-0.847576	F
2023-01-08	-0.326690	-0.265898	0.398331	0.198163	F
2023-01-09	-0.770815	-0.143819	0.095757	-0.716950	F
2023-01-13	-0.789317	-0.179441	0.615646	-0.110530	F

- 예시3: (A+B)/2 > 0

#ts[(ts.A + ts.B)/2 >0]
ts.query('(A+B)/2 >0')

	A	B	C	D	Sex
2022-12-26	0.913373	1.273686	-1.031498	0.107483	M
2022-12-28	0.044797	0.013809	-0.780978	0.288263	M
2022-12-29	0.584282	1.763700	0.943253	0.153924	M
2022-12-31	1.062767	-0.958027	-0.128911	-0.156103	M
2023-01-01	1.358383	0.972339	-0.888977	-1.260350	M
2023-01-06	-0.949612	1.078584	0.079759	0.897018	F
2023-01-10	-0.519762	0.619891	0.317133	-0.728839	F
2023-01-11	1.033974	-0.098040	-1.367873	-0.777833	F
2023-01-12	0.351120	0.137920	-1.809062	0.470261	F
2023-01-14	0.183356	0.362680	0.318493	-1.005962	F

- 예시4: (A+B)/2 > 0 and Sex=='M'

ts.query('(A+B)/2>0 and Sex=="M"')

	A	B	C	D	Sex
2022-12-26	0.913373	1.273686	-1.031498	0.107483	M
2022-12-28	0.044797	0.013809	-0.780978	0.288263	M
2022-12-29	0.584282	1.763700	0.943253	0.153924	M
2022-12-31	1.062767	-0.958027	-0.128911	-0.156103	M
2023-01-01	1.358383	0.972339	-0.888977	-1.260350	M

ts.query("(A+B)/2>0 and Sex=='F'")

	A	B	C	D	Sex
2023-01-06	-0.949612	1.078584	0.079759	0.897018	F
2023-01-10	-0.519762	0.619891	0.317133	-0.728839	F
2023-01-11	1.033974	-0.098040	-1.367873	-0.777833	F
2023-01-12	0.351120	0.137920	-1.809062	0.470261	F
2023-01-14	0.183356	0.362680	0.318493	-1.005962	F

B. 외부변수를 이용

- 예시: A > mean(A)

(풀이1)

ts[ts.A > -0.0734821041290727]
ts.query('A > A.mean()')

	A	B	C	D	Sex
2022-12-26	0.913373	1.273686	-1.031498	0.107483	M
2022-12-28	0.044797	0.013809	-0.780978	0.288263	M
2022-12-29	0.584282	1.763700	0.943253	0.153924	M
2022-12-30	0.210974	-0.691147	-0.484299	0.265967	M
2022-12-31	1.062767	-0.958027	-0.128911	-0.156103	M
2023-01-01	1.358383	0.972339	-0.888977	-1.260350	M
2023-01-11	1.033974	-0.098040	-1.367873	-0.777833	F
2023-01-12	0.351120	0.137920	-1.809062	0.470261	F
2023-01-14	0.183356	0.362680	0.318493	-1.005962	F

(풀이2)

m = ts.A.mean()
ts[ts.A>m]
ts.query('A > @m')

	A	B	C	D	Sex
2022-12-26	0.913373	1.273686	-1.031498	0.107483	M
2022-12-28	0.044797	0.013809	-0.780978	0.288263	M
2022-12-29	0.584282	1.763700	0.943253	0.153924	M
2022-12-30	0.210974	-0.691147	-0.484299	0.265967	M
2022-12-31	1.062767	-0.958027	-0.128911	-0.156103	M
2023-01-01	1.358383	0.972339	-0.888977	-1.260350	M
2023-01-11	1.033974	-0.098040	-1.367873	-0.777833	F
2023-01-12	0.351120	0.137920	-1.809062	0.470261	F
2023-01-14	0.183356	0.362680	0.318493	-1.005962	F

C. Index로 query

- 예시: (2022년 12월30일 보다 이전 날짜) \(\cup\) (2023년 1월10일)

ts.query('index < "2022-12-30" or index == "2023-01-10"')

/tmp/ipykernel_642677/2579726232.py:1: FutureWarning: The behavior of 'isin' with dtype=datetime64[ns] and castable values (e.g. strings) is deprecated. In a future version, these will not be considered matching by isin. Explicitly cast to the appropriate dtype before calling isin instead.
  ts.query('index < "2022-12-30" or index == "2023-01-10"')

	A	B	C	D	Sex
2022-12-26	0.913373	1.273686	-1.031498	0.107483	M
2022-12-27	-0.231464	-2.486921	-2.037792	0.455930	M
2022-12-28	0.044797	0.013809	-0.780978	0.288263	M
2022-12-29	0.584282	1.763700	0.943253	0.153924	M
2023-01-10	-0.519762	0.619891	0.317133	-0.728839	F

D. 열의 이름에 공백이 있을 경우

df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2022/master/posts/FIFA23_official_data.csv')
df.head()

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Kit Number	Best Overall Rating
0	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	Yes	<span class="pos pos28">SUB	Jul 1, 2018	NaN	2026	189cm	82kg	€157M	8.0	NaN
1	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	Yes	<span class="pos pos15">LCM	Jan 30, 2020	NaN	2026	179cm	69kg	€155M	8.0	NaN
2	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	No	<span class="pos pos7">LB	Sep 14, 2020	NaN	2024	172cm	69kg	€97.7M	19.0	NaN
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	Yes	<span class="pos pos13">RCM	Aug 30, 2015	NaN	2025	181cm	70kg	€198.9M	17.0	NaN
4	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	Yes	<span class="pos pos13">RCM	Sep 1, 2020	NaN	2026	172cm	68kg	€154.4M	23.0	NaN

5 rows × 29 columns

- 예시: Skill Moves > 4

df.query('`Skill Moves` > 4').head(5)

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Real Face	Position	Joined	Loaned From	Contract Valid Until	Height	Weight	Release Clause	Kit Number	Best Overall Rating
19	193082	J. Cuadrado	34	https://cdn.sofifa.net/players/193/082/23_60.png	Colombia	https://cdn.sofifa.net/flags/co.png	83	83	Juventus	https://cdn.sofifa.net/teams/45/30.png	...	Yes	<span class="pos pos3">RB	Jul 1, 2017	NaN	2023	179cm	72kg	€23M	11.0	NaN
27	189509	Thiago	31	https://cdn.sofifa.net/players/189/509/23_60.png	Spain	https://cdn.sofifa.net/flags/es.png	86	86	Liverpool	https://cdn.sofifa.net/teams/9/30.png	...	Yes	<span class="pos pos15">LCM	Sep 18, 2020	NaN	2024	174cm	70kg	€102.7M	6.0	NaN
44	232411	C. Nkunku	24	https://cdn.sofifa.net/players/232/411/23_60.png	France	https://cdn.sofifa.net/flags/fr.png	86	89	RB Leipzig	https://cdn.sofifa.net/teams/112172/30.png	...	Yes	<span class="pos pos28">SUB	NaN	NaN	NaN	175cm	73kg	€166.9M	12.0	NaN
62	233927	Lucas Paquetá	24	https://cdn.sofifa.net/players/233/927/23_60.png	Brazil	https://cdn.sofifa.net/flags/br.png	82	87	Olympique Lyonnais	https://cdn.sofifa.net/teams/66/30.png	...	Yes	<span class="pos pos15">LCM	Oct 1, 2020	NaN	2025	180cm	72kg	€90.9M	10.0	NaN
75	231747	K. Mbappé	23	https://cdn.sofifa.net/players/231/747/23_60.png	France	https://cdn.sofifa.net/flags/fr.png	91	95	Paris Saint-Germain	https://cdn.sofifa.net/teams/73/30.png	...	Yes	<span class="pos pos25">ST	Jul 1, 2018	NaN	2025	182cm	73kg	€366.7M	7.0	NaN

5 rows × 29 columns

7. Pandas: 할당

np.random.seed(43052)
att = np.random.choice(np.arange(10,21)*5,20)
rep = np.random.choice(np.arange(5,21)*5,20)
mid = np.random.choice(np.arange(0,21)*5,20)
fin = np.random.choice(np.arange(0,21)*5,20)
df = pd.DataFrame({'att':att,'rep':rep,'mid':mid,'fin':fin})
df

	att	rep	mid	fin
0	65	55	50	40
1	95	100	50	80
2	65	90	60	30
3	55	80	75	80
4	80	30	30	100
5	75	40	100	15
6	65	45	45	90
7	60	60	25	0
8	95	65	20	10
9	90	80	80	20
10	55	75	35	25
11	95	95	45	0
12	95	55	15	35
13	50	80	40	30
14	50	55	15	85
15	95	30	30	95
16	50	50	45	10
17	65	55	15	45
18	70	70	40	35
19	90	90	80	90

A. `df.assign()`

- 예시: total = att*0.1 + rep*0.2 + mid*0.35 + fin*0.35 를 계산하여 할당

df.assign(total = df.att*0.1 + df.rep*0.2 + df.mid*0.35 + df.fin*0.35)

	att	rep	mid	fin	total
0	65	55	50	40	49.00
1	95	100	50	80	75.00
2	65	90	60	30	56.00
3	55	80	75	80	75.75
4	80	30	30	100	59.50
5	75	40	100	15	55.75
6	65	45	45	90	62.75
7	60	60	25	0	26.75
8	95	65	20	10	33.00
9	90	80	80	20	60.00
10	55	75	35	25	41.50
11	95	95	45	0	44.25
12	95	55	15	35	38.00
13	50	80	40	30	45.50
14	50	55	15	85	51.00
15	95	30	30	95	59.25
16	50	50	45	10	34.25
17	65	55	15	45	38.50
18	70	70	40	35	47.25
19	90	90	80	90	86.50

Note: 이 방법은 df원본을 손상시키지 않음

B. `df.eval()`

- 예시: total = att*0.1 + rep*0.2 + mid*0.35 + fin*0.35 를 계산하여 할당

df.eval("total = att*0.1 + rep*0.2 + mid*0.35 + fin*0.35")

	att	rep	mid	fin	total
0	65	55	50	40	49.00
1	95	100	50	80	75.00
2	65	90	60	30	56.00
3	55	80	75	80	75.75
4	80	30	30	100	59.50
5	75	40	100	15	55.75
6	65	45	45	90	62.75
7	60	60	25	0	26.75
8	95	65	20	10	33.00
9	90	80	80	20	60.00
10	55	75	35	25	41.50
11	95	95	45	0	44.25
12	95	55	15	35	38.00
13	50	80	40	30	45.50
14	50	55	15	85	51.00
15	95	30	30	95	59.25
16	50	50	45	10	34.25
17	65	55	15	45	38.50
18	70	70	40	35	47.25
19	90	90	80	90	86.50

Note: 이 방법은 df원본을 손상시키지 않음

C. `df[colname] = xxx`

- 예시: total = att*0.1 + rep*0.2 + mid*0.35 + fin*0.35 를 계산하여 할당.

df['total'] = df.att*0.1 + df.rep*0.2 + df.mid*0.35 + df.fin*0.35
df

	att	rep	mid	fin	total
0	65	55	50	40	49.00
1	95	100	50	80	75.00
2	65	90	60	30	56.00
3	55	80	75	80	75.75
4	80	30	30	100	59.50
5	75	40	100	15	55.75
6	65	45	45	90	62.75
7	60	60	25	0	26.75
8	95	65	20	10	33.00
9	90	80	80	20	60.00
10	55	75	35	25	41.50
11	95	95	45	0	44.25
12	95	55	15	35	38.00
13	50	80	40	30	45.50
14	50	55	15	85	51.00
15	95	30	30	95	59.25
16	50	50	45	10	34.25
17	65	55	15	45	38.50
18	70	70	40	35	47.25
19	90	90	80	90	86.50

Note: 이 방법은 df를 영구적으로 변화시킴

8. Pandas: transform column

# 예시1 df.Height열 변환하기 + 변환된 열 할당하기

df = pd.read_csv('https://raw.githubusercontent.com/guebin/DV2022/master/posts/FIFA23_official_data.csv').drop(['Loaned From','Best Overall Rating'],axis=1).dropna().reset_index(drop=True)
df.head()

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Work Rate	Body Type	Real Face	Position	Joined	Contract Valid Until	Height	Weight	Release Clause	Kit Number
0	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	High/ Medium	Unique	Yes	<span class="pos pos28">SUB	Jul 1, 2018	2026	189cm	82kg	€157M	8.0
1	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	High/ High	Unique	Yes	<span class="pos pos15">LCM	Jan 30, 2020	2026	179cm	69kg	€155M	8.0
2	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	High/ High	Stocky (170-185)	No	<span class="pos pos7">LB	Sep 14, 2020	2024	172cm	69kg	€97.7M	19.0
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	High/ High	Unique	Yes	<span class="pos pos13">RCM	Aug 30, 2015	2025	181cm	70kg	€198.9M	17.0
4	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	High/ High	Normal (170-)	Yes	<span class="pos pos13">RCM	Sep 1, 2020	2026	172cm	68kg	€154.4M	23.0

5 rows × 27 columns

- (풀이1)

df.assign(Height = list(map(lambda x: int(x.replace('cm','')),df.Height)))

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Work Rate	Body Type	Real Face	Position	Joined	Contract Valid Until	Height	Weight	Release Clause	Kit Number
0	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	High/ Medium	Unique	Yes	<span class="pos pos28">SUB	Jul 1, 2018	2026	189	82kg	€157M	8.0
1	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	High/ High	Unique	Yes	<span class="pos pos15">LCM	Jan 30, 2020	2026	179	69kg	€155M	8.0
2	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	High/ High	Stocky (170-185)	No	<span class="pos pos7">LB	Sep 14, 2020	2024	172	69kg	€97.7M	19.0
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	High/ High	Unique	Yes	<span class="pos pos13">RCM	Aug 30, 2015	2025	181	70kg	€198.9M	17.0
4	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	High/ High	Normal (170-)	Yes	<span class="pos pos13">RCM	Sep 1, 2020	2026	172	68kg	€154.4M	23.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
16359	269526	Deng Xiongtao	19	https://cdn.sofifa.net/players/269/526/23_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	48	61	Meizhou Hakka	https://cdn.sofifa.net/teams/114628/30.png	...	Medium/ Medium	Normal (185+)	No	<span class="pos pos29">RES	Apr 11, 2022	2027	190	78kg	€218K	35.0
16360	267946	22 Lim Jun Sub	17	https://cdn.sofifa.net/players/267/946/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	48	64	Jeju United FC	https://cdn.sofifa.net/teams/1478/30.png	...	Medium/ Medium	Lean (185+)	No	<span class="pos pos29">RES	Jan 1, 2022	2026	195	84kg	€188K	21.0
16361	270567	A. Demir	25	https://cdn.sofifa.net/players/270/567/23_60.png	Turkey	https://cdn.sofifa.net/flags/tr.png	51	56	Ümraniyespor	https://cdn.sofifa.net/teams/113796/30.png	...	Medium/ Medium	Lean (185+)	No	<span class="pos pos29">RES	Jun 6, 2021	2023	190	82kg	€142K	12.0
16362	256624	21 S. Czajor	18	https://cdn.sofifa.net/players/256/624/21_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	50	65	Fleetwood Town	https://cdn.sofifa.net/teams/112260/30.png	...	Medium/ Medium	Normal (185+)	No	<span class="pos pos29">RES	Jan 1, 2020	2021	187	79kg	€214K	40.0
16363	256376	21 F. Jakobsson	20	https://cdn.sofifa.net/players/256/376/21_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	50	61	IFK Norrköping	https://cdn.sofifa.net/teams/702/30.png	...	Medium/ Medium	Normal (185+)	No	<span class="pos pos29">RES	Jan 8, 2020	2021	186	78kg	€131K	30.0

16364 rows × 27 columns

- (풀이2) – 컴프리헨션

df.assign(Height= [int(height.replace('cm','')) for height in df.Height])

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Work Rate	Body Type	Real Face	Position	Joined	Contract Valid Until	Height	Weight	Release Clause	Kit Number
0	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	High/ Medium	Unique	Yes	<span class="pos pos28">SUB	Jul 1, 2018	2026	189	82kg	€157M	8.0
1	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	High/ High	Unique	Yes	<span class="pos pos15">LCM	Jan 30, 2020	2026	179	69kg	€155M	8.0
2	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	High/ High	Stocky (170-185)	No	<span class="pos pos7">LB	Sep 14, 2020	2024	172	69kg	€97.7M	19.0
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	High/ High	Unique	Yes	<span class="pos pos13">RCM	Aug 30, 2015	2025	181	70kg	€198.9M	17.0
4	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	High/ High	Normal (170-)	Yes	<span class="pos pos13">RCM	Sep 1, 2020	2026	172	68kg	€154.4M	23.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
16359	269526	Deng Xiongtao	19	https://cdn.sofifa.net/players/269/526/23_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	48	61	Meizhou Hakka	https://cdn.sofifa.net/teams/114628/30.png	...	Medium/ Medium	Normal (185+)	No	<span class="pos pos29">RES	Apr 11, 2022	2027	190	78kg	€218K	35.0
16360	267946	22 Lim Jun Sub	17	https://cdn.sofifa.net/players/267/946/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	48	64	Jeju United FC	https://cdn.sofifa.net/teams/1478/30.png	...	Medium/ Medium	Lean (185+)	No	<span class="pos pos29">RES	Jan 1, 2022	2026	195	84kg	€188K	21.0
16361	270567	A. Demir	25	https://cdn.sofifa.net/players/270/567/23_60.png	Turkey	https://cdn.sofifa.net/flags/tr.png	51	56	Ümraniyespor	https://cdn.sofifa.net/teams/113796/30.png	...	Medium/ Medium	Lean (185+)	No	<span class="pos pos29">RES	Jun 6, 2021	2023	190	82kg	€142K	12.0
16362	256624	21 S. Czajor	18	https://cdn.sofifa.net/players/256/624/21_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	50	65	Fleetwood Town	https://cdn.sofifa.net/teams/112260/30.png	...	Medium/ Medium	Normal (185+)	No	<span class="pos pos29">RES	Jan 1, 2020	2021	187	79kg	€214K	40.0
16363	256376	21 F. Jakobsson	20	https://cdn.sofifa.net/players/256/376/21_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	50	61	IFK Norrköping	https://cdn.sofifa.net/teams/702/30.png	...	Medium/ Medium	Normal (185+)	No	<span class="pos pos29">RES	Jan 8, 2020	2021	186	78kg	€131K	30.0

16364 rows × 27 columns

#

# 예시2 df.Joined을 이용하여 선수들이 join한 연도를 알아내고 이를 새로운 열로 할당하라.

- (풀이1)

df.assign(JoinedYear = list(map(lambda x: int(x[-4:]), df.Joined)))

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Body Type	Real Face	Position	Joined	Contract Valid Until	Height	Weight	Release Clause	Kit Number	JoinedYear
0	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	Unique	Yes	<span class="pos pos28">SUB	Jul 1, 2018	2026	189cm	82kg	€157M	8.0	2018
1	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	Unique	Yes	<span class="pos pos15">LCM	Jan 30, 2020	2026	179cm	69kg	€155M	8.0	2020
2	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	Stocky (170-185)	No	<span class="pos pos7">LB	Sep 14, 2020	2024	172cm	69kg	€97.7M	19.0	2020
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	Unique	Yes	<span class="pos pos13">RCM	Aug 30, 2015	2025	181cm	70kg	€198.9M	17.0	2015
4	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	Normal (170-)	Yes	<span class="pos pos13">RCM	Sep 1, 2020	2026	172cm	68kg	€154.4M	23.0	2020
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
16359	269526	Deng Xiongtao	19	https://cdn.sofifa.net/players/269/526/23_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	48	61	Meizhou Hakka	https://cdn.sofifa.net/teams/114628/30.png	...	Normal (185+)	No	<span class="pos pos29">RES	Apr 11, 2022	2027	190cm	78kg	€218K	35.0	2022
16360	267946	22 Lim Jun Sub	17	https://cdn.sofifa.net/players/267/946/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	48	64	Jeju United FC	https://cdn.sofifa.net/teams/1478/30.png	...	Lean (185+)	No	<span class="pos pos29">RES	Jan 1, 2022	2026	195cm	84kg	€188K	21.0	2022
16361	270567	A. Demir	25	https://cdn.sofifa.net/players/270/567/23_60.png	Turkey	https://cdn.sofifa.net/flags/tr.png	51	56	Ümraniyespor	https://cdn.sofifa.net/teams/113796/30.png	...	Lean (185+)	No	<span class="pos pos29">RES	Jun 6, 2021	2023	190cm	82kg	€142K	12.0	2021
16362	256624	21 S. Czajor	18	https://cdn.sofifa.net/players/256/624/21_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	50	65	Fleetwood Town	https://cdn.sofifa.net/teams/112260/30.png	...	Normal (185+)	No	<span class="pos pos29">RES	Jan 1, 2020	2021	187cm	79kg	€214K	40.0	2020
16363	256376	21 F. Jakobsson	20	https://cdn.sofifa.net/players/256/376/21_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	50	61	IFK Norrköping	https://cdn.sofifa.net/teams/702/30.png	...	Normal (185+)	No	<span class="pos pos29">RES	Jan 8, 2020	2021	186cm	78kg	€131K	30.0	2020

16364 rows × 28 columns

- (풀이2)

df.assign(JoinedYear = [int(l[-4:]) for l in df.Joined])

	ID	Name	Age	Photo	Nationality	Flag	Overall	Potential	Club	Club Logo	...	Body Type	Real Face	Position	Joined	Contract Valid Until	Height	Weight	Release Clause	Kit Number	JoinedYear
0	209658	L. Goretzka	27	https://cdn.sofifa.net/players/209/658/23_60.png	Germany	https://cdn.sofifa.net/flags/de.png	87	88	FC Bayern München	https://cdn.sofifa.net/teams/21/30.png	...	Unique	Yes	<span class="pos pos28">SUB	Jul 1, 2018	2026	189cm	82kg	€157M	8.0	2018
1	212198	Bruno Fernandes	27	https://cdn.sofifa.net/players/212/198/23_60.png	Portugal	https://cdn.sofifa.net/flags/pt.png	86	87	Manchester United	https://cdn.sofifa.net/teams/11/30.png	...	Unique	Yes	<span class="pos pos15">LCM	Jan 30, 2020	2026	179cm	69kg	€155M	8.0	2020
2	224334	M. Acuña	30	https://cdn.sofifa.net/players/224/334/23_60.png	Argentina	https://cdn.sofifa.net/flags/ar.png	85	85	Sevilla FC	https://cdn.sofifa.net/teams/481/30.png	...	Stocky (170-185)	No	<span class="pos pos7">LB	Sep 14, 2020	2024	172cm	69kg	€97.7M	19.0	2020
3	192985	K. De Bruyne	31	https://cdn.sofifa.net/players/192/985/23_60.png	Belgium	https://cdn.sofifa.net/flags/be.png	91	91	Manchester City	https://cdn.sofifa.net/teams/10/30.png	...	Unique	Yes	<span class="pos pos13">RCM	Aug 30, 2015	2025	181cm	70kg	€198.9M	17.0	2015
4	224232	N. Barella	25	https://cdn.sofifa.net/players/224/232/23_60.png	Italy	https://cdn.sofifa.net/flags/it.png	86	89	Inter	https://cdn.sofifa.net/teams/44/30.png	...	Normal (170-)	Yes	<span class="pos pos13">RCM	Sep 1, 2020	2026	172cm	68kg	€154.4M	23.0	2020
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
16359	269526	Deng Xiongtao	19	https://cdn.sofifa.net/players/269/526/23_60.png	China PR	https://cdn.sofifa.net/flags/cn.png	48	61	Meizhou Hakka	https://cdn.sofifa.net/teams/114628/30.png	...	Normal (185+)	No	<span class="pos pos29">RES	Apr 11, 2022	2027	190cm	78kg	€218K	35.0	2022
16360	267946	22 Lim Jun Sub	17	https://cdn.sofifa.net/players/267/946/22_60.png	Korea Republic	https://cdn.sofifa.net/flags/kr.png	48	64	Jeju United FC	https://cdn.sofifa.net/teams/1478/30.png	...	Lean (185+)	No	<span class="pos pos29">RES	Jan 1, 2022	2026	195cm	84kg	€188K	21.0	2022
16361	270567	A. Demir	25	https://cdn.sofifa.net/players/270/567/23_60.png	Turkey	https://cdn.sofifa.net/flags/tr.png	51	56	Ümraniyespor	https://cdn.sofifa.net/teams/113796/30.png	...	Lean (185+)	No	<span class="pos pos29">RES	Jun 6, 2021	2023	190cm	82kg	€142K	12.0	2021
16362	256624	21 S. Czajor	18	https://cdn.sofifa.net/players/256/624/21_60.png	Poland	https://cdn.sofifa.net/flags/pl.png	50	65	Fleetwood Town	https://cdn.sofifa.net/teams/112260/30.png	...	Normal (185+)	No	<span class="pos pos29">RES	Jan 1, 2020	2021	187cm	79kg	€214K	40.0	2020
16363	256376	21 F. Jakobsson	20	https://cdn.sofifa.net/players/256/376/21_60.png	Sweden	https://cdn.sofifa.net/flags/se.png	50	61	IFK Norrköping	https://cdn.sofifa.net/teams/702/30.png	...	Normal (185+)	No	<span class="pos pos29">RES	Jan 8, 2020	2021	186cm	78kg	€131K	30.0	2020

16364 rows × 28 columns

9. 반복문 – 자투리

A. `zip`

- 예시1

x = [11,22,33]
y = [44,55,66]
for xi,yi in zip(x,y):
    print(xi,yi)

11 44
22 55
33 66

- 예시2

df = pd.DataFrame({'year':[2022,2023,2022,2022,2019],'month':[12,10,8,2,1],'day':[31,22,31,28,15]})
df

	year	month	day
0	2022	12	31
1	2023	10	22
2	2022	8	31
3	2022	2	28
4	2019	1	15

df.assign(ymd = [f"{y}-{m}-{d}" for y,m,d in zip(df.year, df.month, df.day)])

	year	month	day	ymd
0	2022	12	31	2022-12-31
1	2023	10	22	2023-10-22
2	2022	8	31	2022-8-31
3	2022	2	28	2022-2-28
4	2019	1	15	2019-1-15

B. `enumerate`

- 예시1

x = [11,22,33]
for i,xi in enumerate(x):
    print(i,xi)

0 11
1 22
2 33

- 예시2

lst = np.random.choice(['사과','딸기','배'],100,replace=True).tolist()
lst[:5]

['배', '사과', '사과', '딸기', '딸기']

dct = {l:i for i,l in enumerate(set(lst))}
dct

{'딸기': 0, '사과': 1, '배': 2}

[dct[l] for l in lst][:5]

[2, 1, 1, 0, 0]

10. 변수의 범위

- 모티브: 주피터노트북 하나를 키고 x에 100을 넣는다. 다른 주피터를 하나 키고 x를 치면 100이 나올까? –> “독립된 환경”이라는 개념

A. 함수

- 예시1: 함수내부 / 함수외부

x = None 
y = None

def f(x):
    y = x+1
    return y

f(1)

x,y

(None, None)

여기에서 x,y는 함수내부에서만 선언 및 계산되고 소멸한다. 즉 함수안에서 사용되는 코드는 마치 독립된 환경처럼 작동한다. 함수외부의 x,y는 함수내부의 x,y와 “기본적으로는” 상관이 없다.

- 예시2: 함수내부 / 함수외부

x = 1
y = None

def f(x):
    y = x+1
    return y

f(x)

x,y

(1, None)

여기에서 x는 함수외부에 선언되었고, 함수 외부에 선언된 x의 값이 함수 내부로 전달되었다. 전달된 값은 함수내부에서 x라는 이름으로 저장되었음.

- 예시3: 함수내부 / 함수외부

x = None 
y = None

def f(x):
    y = x+1
    return y

z = 1
f(z)

x,y

(None, None)

여기에서 z는 함수외부에 선언되었고, 함수 외부에 선언된 z의 값이 함수 내부로 전달되었음. 전달된 값은 함수내부에서 x라는 이름으로 저장되었음.

- 예시4: 함수내부 / 함수외부

x = 2
y = 3

def f(x):
    return x+y # 함수내부에서는 y를 정의한적이 없잖아? (뭘 x에 더하라는거야?) 혹시 함수 외부에 y가 정의되어있나? 찾아보니 y=3이있음. 이걸 가져다가 쓰자

f(10)

x,y

(2, 3)

여기에서 x=2,y=3는 함수외부에 선언되었음. 함수 내부에는 x=10 이 선언되었음. 함수내부에서 x+y를 계산하려고 했는데, y는 함수내부에 없음. 그런데 함수외부에는 y가 있네? 그럼 함수외부에 있는 y를 빌려옴!! (이건 엄청 위험한 코드임. 왜냐하면 y가 어디있는지 쉽게 찾을 수 없기 때문!)

사실 이 코드에서 y와 같은 역할을 하는 변수를 “전역변수”라고 하는데, y가 전역변수를 의미할때는 보통 대문자를 사용한다.

- 예시5: 전역변수를 사용하는 모범코드

PI = 3.141592

def f(r):
    return PI*(r**2)

def g(r): 
    return (4/3)*PI*(r**3)

f(2),g(2)

(12.566368, 33.510314666666666)

- 예시6: 전역변수와 지역변수가 충돌한다면?

x = 5
y = 5

def f(x):
    y = x+1 
    return x**y

f(2)

x,y

(5, 5)

이거 사실 예시1이랑 같은코드에요, 전역변수 개념이 너무 충격적이라서 갑자기 헷갈릴 뿐입니다.

B. for / 컴프리헨션

- 예시1: for문과 함께 사용된 \(i\)

i = None
lst = None

i, lst

(None, None)

lst = []
for i in range(5):
    lst.append(i)

i, lst

(4, [0, 1, 2, 3, 4])

- 예시2: 컴프리헨션과 사용된 \(i\)

i = None
lst = None

lst = [i for i in range(5)]

i, lst

(None, [0, 1, 2, 3, 4])

A1. 잔소리

A. 통계학과의 진로

- 코딩과 상관 X

시험을 통해 얻는 직업: 회계사, 공무원/공기업, …
본인이 선택하는 직업: 가업, 학원선생님, 전과 이후 새 직업 탐색, … ¹

¹ 사실상 졸업을 위해서 수강하는 학생들

- 코딩과 상관 O

당장 코딩실력이 필요할 경우 (= 코딩테스트를 준비해야 하는 경우): IT기업 (네이버, 카카오, …), 빅데이터분석기업(LG-CNS, 삼성SDS, …), 기타대기업(삼성전자, 하이닉스, SKT, KT, …),
당장 코딩실력이 필요하진 않지만 장기적으론 필요한 경우: 대학원진학, 금융권 (XX은행, XX증권, …), 병원(전북대병원등,…)

- 시험을 통해 얻는 직업 vs 일반사기업입사 (혹은 대학원)

사법고시공부 vs 좋은대학 느낌
할 수 있다면 시험준비해서 좋은기업가면 좋음.
그렇지 않다면 “공모전준비(캐글/데이콘경진대회경험등)”+“학점관리”+“영어공부”+“코딩테스트준비”+“학회활동”+“자격증대비” -> 대학원 or 취업

- 이 수업의 목적:

1. 통계학과 상위과목 수강을 위한 실력쌓기: 기계학습활용, 기계학습, 딥러닝, 데이터마이닝 등.. 파이썬을 활용하는 모든 과목들

2. 코딩 흡수력 향상: 남의 코드를 보고 흡수할 수 있느냐?

'A'.isupper()

True

'A'.islower()

False

3. 코딩테스트에 대한 대비 X (스트레스만 줄 것임)

B. 코딩테스트를 잘하면 좋은것

- 삼성 청년 SW 아카데미 https://www.ssafy.com/ksp/jsp/swp/apply/swpApplyProcess.jsp

전문화된 SW교육 제공
교육지원금 지급 (매월 100만원)
국내외 연구소 실습기회 부여
이 자체가 엄청난 스펙..

- 카카오 2024 채용연계형 겨울 인턴십 모집 https://www.kakaocorp.com/page/detail/10677

인턴십 이후 전환 인터뷰를 통해 최종 정규직 전환 대상자가 확정
전환 인터뷰에 통과하면 내년 3월부터 카카오 크루로 입사
단, 학업 등의 이유로 부득이하게 내년 3월 입사가 어려운 경우 2024년 9월 이내 가능한 일자로 별도 조율할 예정
학생들 입장에서는 유일한 입사기회 + 떨어져도 좋은 경험
최근에 이런 형태로 뽑는 기업들 많음

- 삼성 SW 역량테스트 https://swexpertacademy.com/main/capacityTest/main.do

입사시험임 (파이썬 지원)
지원: https://swexpertacademy.com/main/sst/intro.do
기출문제: https://swexpertacademy.com/main/code/problem/problemList.do

- 유용한사이트

백준: https://www.acmicpc.net/workbook/view/1152
프로그래머스: https://programmers.co.kr/

- 학생들의 노력

https://www.youtube.com/watch?v=saVwTNb1wzk
코딩테스트 탈락후기

C. 코딩테스트 잘보는 방법?

- 코딩테스트문제 = 구현문제 + 알고리즘문제

알고리즘문제는 따로 공부해야함. (풀이 패턴이 있음, 퀴즈5-1~2)
구현문제는 평소에 논리적 생각을 많이해야함 + 꼼꼼해야함 + 오류수정잘해야함(중간고사3)

- 언어특화문법을 잘 이해해야함

파이썬스러운 코딩 (퀴즈5-1, 퀴즈5-3)

- 사용가능한 패키지를 잘 확인할 것: numpy, pandas 활용가능 유무

- 계산 시간을 따질 것

1. 강의영상

2. Imports

3. Pandas

A. numpy 대비 장점?

B. 선언방법

C. 자료형, len, shape, for문의 반복변수

D. pd.Series

4. Pandas: 행과 열의 선택

A. 열의 선택

B. 행의 선택

C. 제 스타일

D. 제 스타일 X

E. 요약

5. Pandas: 기본기능

A. 열의 이름 변경

B. 행의 이름 변경

# A~B에 대한 연습문제

C. df.T

D. df.dtypes, s.dtype, df.select_dtypes()

E. df.sort_values()

F. df.info()

6. Pandas: query

A. 기본 query

B. 외부변수를 이용

C. Index로 query

D. 열의 이름에 공백이 있을 경우

7. Pandas: 할당

A. df.assign()

B. df.eval()

C. df[colname] = xxx

8. Pandas: transform column

9. 반복문 – 자투리

A. zip

B. enumerate

10. 변수의 범위

A. 함수

B. for / 컴프리헨션

A1. 잔소리

A. 통계학과의 진로

B. 코딩테스트를 잘하면 좋은것

C. 코딩테스트 잘보는 방법?

3. `Pandas`

A. `numpy` 대비 장점?

D. `pd.Series`

`#` A~B에 대한 연습문제

C. `df.T`

D. `df.dtypes`, `s.dtype`, `df.select_dtypes()`

E. `df.sort_values()`

F. `df.info()`

A. `df.assign()`

B. `df.eval()`

C. `df[colname] = xxx`

A. `zip`

B. `enumerate`