블로그로 배우는 시대는 끝이 나겠구나...

자격/경력 업뎃 하려고 한이음 들락 거리다 그 사이도 교육 분야는 시대가 정말 많이 변했구나 라는 것을 알게 되었다. 큰 틀은 프로그래머스, 엘리스 외 프로그래밍 시험 틀과 비슷한 것 같다. main branch가 있을 것 같은데 그 원류는 찾아봐야 겠다.

 

from datetime import datetime #날짜와 시간을 쉽게 조작할 수 있게 하는 클래스 제공

import pandas as pd

 

# csv 형태의 주식 데이터 파일을 불러오는 코드

df = pd.read_csv('stock.csv')

 

# 데이터프레임 출력(데이터프레임은 (헹 X 열)로 이루어진 표 형태의 특수한 데이터 타입)

print(df)

 

 

# --- 주식 데이터 살펴보기 --- #

 

print('\n주식 데이터의 형태를 출력')

print(df.shape)

 

print('\n주식 데이터의 정보를 출력')

print(df.info)

 

print('\n주식 데이터의 데이터 타입을 출력')

print(df.dtypes)

 

print('\n주식 데이터의 상단 5개 행을 출력')

print(df.head())

 

print('\n주식 데이터의 하단 5개 행을 출력')

print(df.tail())

 

print('\n주식 데이터의 모든 열을 출력')

print(df.columns)

 

print('\n주식 데이터의 요약 통계 자료 출력')

print(df.describe())

 

Date High Low Open Close Volume Adj Close 0 2020-03-02 55500 53600 54300 55000 30403412 55000 1 2020-03-03 56900 55100 56700 55400 30330295 55400 2 2020-03-04 57600 54600 54800 57400 24765728 57400 3 2020-03-05 58000 56700 57600 57800 21698990 57800 4 2020-03-06 57200 56200 56500 56500 18716656 56500 5 2020-03-09 56500 56500 56500 56500 0 56500 6 2020-03-10 54900 53700 53800 54600 32106554 54600 7 2020-03-11 54400 52000 54300 52100 45707281 52100 8 2020-03-12 52100 52100 52100 52100 0 52100 9 2020-03-13 51600 46850 47450 49950 59462933 49950 10 2020-03-16 50900 48800 50100 48900 33339821 48900 11 2020-03-17 49650 46700 46900 47300 51218151 47300 12 2020-03-18 48350 45600 47750 45600 40152623 45600 13 2020-03-19 46650 42300 46400 42950 56925513 42950 14 2020-03-20 45500 43550 44150 45400 49730008 45400 15 2020-03-23 43550 42400 42600 42500 41701626 42500 16 2020-03-24 46950 43050 43850 46950 49801908 46950 17 2020-03-25 49600 47150 48950 48650 52735922 48650 18 2020-03-26 49300 47700 49000 47800 42185129 47800 19 2020-03-27 49700 46850 49600 48300 39896178 48300 20 2020-03-30 48350 46550 47050 47850 26797395 47850 21 2020-03-31 48500 47150 48000 47750 30654261 47750 22 2020-04-01 47900 45800 47450 45800 27259532 45800 23 2020-04-02 46850 45350 46200 46800 21621076 46800 24 2020-04-03 47600 46550 47400 47000 22784682 47000 25 2020-04-06 48800 47250 47500 48700 23395726 48700 26 2020-04-07 50200 49000 49650 49600 31524034 49600 27 2020-04-08 49750 48600 49600 48600 25010314 48600 28 2020-04-09 49800 48700 49750 49100 22628058 49100 29 2020-04-10 49250 48650 48950 49250 17839111 49250 .. ... ... ... ... ... ... ... 75 2020-06-19 52900 51600 52600 52900 18157985 52900 76 2020-06-22 52600 51800 52000 52000 13801350 52000 77 2020-06-23 52800 51100 52500 51400 18086152 51400 78 2020-06-24 53900 51600 51900 52900 24519552 52900 79 2020-06-25 53000 51900 52100 51900 18541624 51900 80 2020-06-26 53900 52200 52800 53300 21575360 53300 81 2020-06-29 53200 52000 52500 52400 17776925 52400 82 2020-06-30 53900 52800 53900 52800 21157172 52800 83 2020-07-01 53600 52400 53400 52600 16706143 52600 84 2020-07-02 52900 52100 52100 52900 14142583 52900 85 2020-07-03 53600 52700 53000 53600 11887868 53600 86 2020-07-06 55000 53800 54000 55000 19856623 55000 87 2020-07-07 55900 53400 55800 53400 30760032 53400 88 2020-07-08 53900 52900 53600 53000 19664652 53000 89 2020-07-09 53600 52800 53200 52800 17054850 52800 90 2020-07-10 53200 52300 53100 52700 13714746 52700 91 2020-07-13 53800 53100 53300 53400 12240188 53400 92 2020-07-14 53800 53200 53700 53800 14269484 53800 93 2020-07-15 55000 54300 54400 54700 24051450 54700 94 2020-07-16 54800 53800 54800 53800 16779127 53800 95 2020-07-17 54700 54100 54200 54400 10096174 54400 96 2020-07-20 54800 54000 54800 54200 10507530 54200 97 2020-07-21 55400 54800 55200 55300 18297260 55300 98 2020-07-22 55500 54700 55300 54700 12885057 54700 99 2020-07-23 54700 53800 54700 54100 16214932 54100 100 2020-07-24 54400 53700 54000 54200 10994535 54200 101 2020-07-27 55700 54300 54300 55600 21054421 55600 102 2020-07-28 58800 56400 57000 58600 48431566 58600 103 2020-07-29 60400 58600 60300 59000 36476611 59000 104 2020-07-30 60100 59000 59700 59000 19285354 59000 [105 rows x 7 columns] 주식 데이터의 형태를 출력 (105, 7) 주식 데이터의 정보를 출력 <bound method DataFrame.info of Date High Low Open Close Volume Adj Close 0 2020-03-02 55500 53600 54300 55000 30403412 55000 1 2020-03-03 56900 55100 56700 55400 30330295 55400 2 2020-03-04 57600 54600 54800 57400 24765728 57400 3 2020-03-05 58000 56700 57600 57800 21698990 57800 4 2020-03-06 57200 56200 56500 56500 18716656 56500 5 2020-03-09 56500 56500 56500 56500 0 56500 6 2020-03-10 54900 53700 53800 54600 32106554 54600 7 2020-03-11 54400 52000 54300 52100 45707281 52100 8 2020-03-12 52100 52100 52100 52100 0 52100 9 2020-03-13 51600 46850 47450 49950 59462933 49950 10 2020-03-16 50900 48800 50100 48900 33339821 48900 11 2020-03-17 49650 46700 46900 47300 51218151 47300 12 2020-03-18 48350 45600 47750 45600 40152623 45600 13 2020-03-19 46650 42300 46400 42950 56925513 42950 14 2020-03-20 45500 43550 44150 45400 49730008 45400 15 2020-03-23 43550 42400 42600 42500 41701626 42500 16 2020-03-24 46950 43050 43850 46950 49801908 46950 17 2020-03-25 49600 47150 48950 48650 52735922 48650 18 2020-03-26 49300 47700 49000 47800 42185129 47800 19 2020-03-27 49700 46850 49600 48300 39896178 48300 20 2020-03-30 48350 46550 47050 47850 26797395 47850 21 2020-03-31 48500 47150 48000 47750 30654261 47750 22 2020-04-01 47900 45800 47450 45800 27259532 45800 23 2020-04-02 46850 45350 46200 46800 21621076 46800 24 2020-04-03 47600 46550 47400 47000 22784682 47000 25 2020-04-06 48800 47250 47500 48700 23395726 48700 26 2020-04-07 50200 49000 49650 49600 31524034 49600 27 2020-04-08 49750 48600 49600 48600 25010314 48600 28 2020-04-09 49800 48700 49750 49100 22628058 49100 29 2020-04-10 49250 48650 48950 49250 17839111 49250 .. ... ... ... ... ... ... ... 75 2020-06-19 52900 51600 52600 52900 18157985 52900 76 2020-06-22 52600 51800 52000 52000 13801350 52000 77 2020-06-23 52800 51100 52500 51400 18086152 51400 78 2020-06-24 53900 51600 51900 52900 24519552 52900 79 2020-06-25 53000 51900 52100 51900 18541624 51900 80 2020-06-26 53900 52200 52800 53300 21575360 53300 81 2020-06-29 53200 52000 52500 52400 17776925 52400 82 2020-06-30 53900 52800 53900 52800 21157172 52800 83 2020-07-01 53600 52400 53400 52600 16706143 52600 84 2020-07-02 52900 52100 52100 52900 14142583 52900 85 2020-07-03 53600 52700 53000 53600 11887868 53600 86 2020-07-06 55000 53800 54000 55000 19856623 55000 87 2020-07-07 55900 53400 55800 53400 30760032 53400 88 2020-07-08 53900 52900 53600 53000 19664652 53000 89 2020-07-09 53600 52800 53200 52800 17054850 52800 90 2020-07-10 53200 52300 53100 52700 13714746 52700 91 2020-07-13 53800 53100 53300 53400 12240188 53400 92 2020-07-14 53800 53200 53700 53800 14269484 53800 93 2020-07-15 55000 54300 54400 54700 24051450 54700 94 2020-07-16 54800 53800 54800 53800 16779127 53800 95 2020-07-17 54700 54100 54200 54400 10096174 54400 96 2020-07-20 54800 54000 54800 54200 10507530 54200 97 2020-07-21 55400 54800 55200 55300 18297260 55300 98 2020-07-22 55500 54700 55300 54700 12885057 54700 99 2020-07-23 54700 53800 54700 54100 16214932 54100 100 2020-07-24 54400 53700 54000 54200 10994535 54200 101 2020-07-27 55700 54300 54300 55600 21054421 55600 102 2020-07-28 58800 56400 57000 58600 48431566 58600 103 2020-07-29 60400 58600 60300 59000 36476611 59000 104 2020-07-30 60100 59000 59700 59000 19285354 59000 [105 rows x 7 columns]> 주식 데이터의 데이터 타입을 출력 Date object High int64 Low int64 Open int64 Close int64 Volume int64 Adj Close int64 dtype: object 주식 데이터의 상단 5개 행을 출력 Date High Low Open Close Volume Adj Close 0 2020-03-02 55500 53600 54300 55000 30403412 55000 1 2020-03-03 56900 55100 56700 55400 30330295 55400 2 2020-03-04 57600 54600 54800 57400 24765728 57400 3 2020-03-05 58000 56700 57600 57800 21698990 57800 4 2020-03-06 57200 56200 56500 56500 18716656 56500 주식 데이터의 하단 5개 행을 출력 Date High Low Open Close Volume Adj Close 100 2020-07-24 54400 53700 54000 54200 10994535 54200 101 2020-07-27 55700 54300 54300 55600 21054421 55600 102 2020-07-28 58800 56400 57000 58600 48431566 58600 103 2020-07-29 60400 58600 60300 59000 36476611 59000 104 2020-07-30 60100 59000 59700 59000 19285354 59000 주식 데이터의 모든 열을 출력 Index(['Date', 'High', 'Low', 'Open', 'Close', 'Volume', 'Adj Close'], dtype='object') 주식 데이터의 요약 통계 자료 출력 High Low ... Volume Adj Close count 105.000000 105.000000 ... 1.050000e+02 105.000000 mean 51996.190476 50637.619048 ... 2.390007e+07 51310.476190 std 3278.145108 3365.597879 ... 1.152018e+07 3331.829995 min 43550.000000 42300.000000 ... 0.000000e+00 42500.000000 25% 49350.000000 48500.000000 ... 1.621493e+07 48800.000000 50% 51600.000000 50300.000000 ... 2.105442e+07 51200.000000 75% 54700.000000 53200.000000 ... 2.759696e+07 53800.000000 max 60400.000000 59000.000000 ... 5.946293e+07 59000.000000 [8 rows x 6 columns]

코드 실행이 완료되었습니다.