Overview

Dataset statistics

Number of variables17
Number of observations10000
Missing cells1326
Missing cells (%)0.8%
Duplicate rows3
Duplicate rows (%)< 0.1%
Total size in memory1.4 MiB
Average record size in memory146.0 B

Variable types

Text8
Categorical8
Numeric1

Dataset

Description광주광역시 학원 및 교습소 현황으로 학원명, 주소, 전화번호, 교습과정, 교습과목, 교습기간 등의 항목을 제공합니다.
Author광주광역시교육청
URLhttps://www.data.go.kr/data/15095323/fileData.do

Alerts

Dataset has 3 (< 0.1%) duplicate rowsDuplicates
모의고사비 is highly overall correlated with 기숙사비High correlation
차량비 is highly overall correlated with 기숙사비High correlation
교습기간 is highly overall correlated with 기숙사비High correlation
재료비 is highly overall correlated with 기숙사비High correlation
기숙사비 is highly overall correlated with 강사수 and 7 other fieldsHigh correlation
교습과정 is highly overall correlated with 기숙사비High correlation
피복비 is highly overall correlated with 기숙사비High correlation
급식비 is highly overall correlated with 기숙사비High correlation
강사수 is highly overall correlated with 기숙사비High correlation
교습과정 is highly imbalanced (55.7%)Imbalance
교습기간 is highly imbalanced (86.1%)Imbalance
모의고사비 is highly imbalanced (99.8%)Imbalance
재료비 is highly imbalanced (99.4%)Imbalance
급식비 is highly imbalanced (99.7%)Imbalance
기숙사비 is highly imbalanced (99.9%)Imbalance
차량비 is highly imbalanced (98.7%)Imbalance
피복비 is highly imbalanced (94.8%)Imbalance
전화번호 has 1322 (13.2%) missing valuesMissing
강사수 has 683 (6.8%) zerosZeros

Reproduction

Analysis started2023-12-12 10:44:43.327742
Analysis finished2023-12-12 10:44:46.570889
Duration3.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

학원명
Text

Distinct2276
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T19:44:46.735340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length32
Mean length9.2777
Min length3

Characters and Unicode

Total characters92777
Distinct characters641
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique335 ?
Unique (%)3.4%

Sample

1st row에센피아노학원
2nd row숨쉬는수학학원
3rd row라온창의사고력학원
4th row(광산)브라이튼어학원
5th row미드미폴댄스학원
ValueCountFrequency (%)
광주서강컴퓨터학원 58
 
0.6%
페르마학원 55
 
0.5%
봉선지산한길어학원 55
 
0.5%
지산한길어학원 53
 
0.5%
스터디하우스앤카페(and 43
 
0.4%
그린컴퓨터아카데미광주학원 41
 
0.4%
눈높이러닝센터신암학원 39
 
0.4%
에듀윌행정고시학원 39
 
0.4%
눈높이러닝센터풍암학원 36
 
0.4%
씨엠에스학원 34
 
0.3%
Other values (2300) 9700
95.5%
2023-12-12T19:44:47.171729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 11498
 
12.4%
원 9744
 
10.5%
수 2645
 
2.9%
스 2162
 
2.3%
어 2129
 
2.3%
이 1943
 
2.1%
영 1735
 
1.9%
아 1234
 
1.3%
음 1214
 
1.3%
악 1212
 
1.3%
Other values (631) 57261
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 85255
91.9%
Uppercase Letter 2838
 
3.1%
Lowercase Letter 1732
 
1.9%
Close Punctuation 979
 
1.1%
Open Punctuation 979
 
1.1%
Decimal Number 432
 
0.5%
Other Punctuation 346
 
0.4%
Space Separator 158
 
0.2%
Dash Punctuation 32
 
< 0.1%
Math Symbol 26
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 11498
 
13.5%
원 9744
 
11.4%
수 2645
 
3.1%
스 2162
 
2.5%
어 2129
 
2.5%
이 1943
 
2.3%
영 1735
 
2.0%
아 1234
 
1.4%
음 1214
 
1.4%
악 1212
 
1.4%
Other values (555) 49739
58.3%
Uppercase Letter
ValueCountFrequency (%)
C 318
 
11.2%
S 301
 
10.6%
E 261
 
9.2%
M 260
 
9.2%
A 175
 
6.2%
T 158
 
5.6%
B 141
 
5.0%
K 137
 
4.8%
L 123
 
4.3%
P 116
 
4.1%
Other values (16) 848
29.9%
Lowercase Letter
ValueCountFrequency (%)
e 196
11.3%
a 192
11.1%
n 180
10.4%
c 117
 
6.8%
s 114
 
6.6%
o 110
 
6.4%
i 106
 
6.1%
h 98
 
5.7%
t 95
 
5.5%
l 84
 
4.8%
Other values (15) 440
25.4%
Decimal Number
ValueCountFrequency (%)
2 121
28.0%
1 73
16.9%
5 65
15.0%
3 52
12.0%
4 31
 
7.2%
8 31
 
7.2%
7 26
 
6.0%
0 20
 
4.6%
6 9
 
2.1%
9 4
 
0.9%
Other Punctuation
ValueCountFrequency (%)
& 123
35.5%
. 99
28.6%
· 86
24.9%
' 15
 
4.3%
: 9
 
2.6%
/ 7
 
2.0%
, 7
 
2.0%
Close Punctuation
ValueCountFrequency (%)
) 974
99.5%
] 5
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 974
99.5%
[ 5
 
0.5%
Math Symbol
ValueCountFrequency (%)
+ 19
73.1%
× 7
 
26.9%
Space Separator
ValueCountFrequency (%)
158
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 85234
91.9%
Latin 4570
 
4.9%
Common 2952
 
3.2%
Han 21
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 11498
 
13.5%
원 9744
 
11.4%
수 2645
 
3.1%
스 2162
 
2.5%
어 2129
 
2.5%
이 1943
 
2.3%
영 1735
 
2.0%
아 1234
 
1.4%
음 1214
 
1.4%
악 1212
 
1.4%
Other values (551) 49718
58.3%
Latin
ValueCountFrequency (%)
C 318
 
7.0%
S 301
 
6.6%
E 261
 
5.7%
M 260
 
5.7%
e 196
 
4.3%
a 192
 
4.2%
n 180
 
3.9%
A 175
 
3.8%
T 158
 
3.5%
B 141
 
3.1%
Other values (41) 2388
52.3%
Common
ValueCountFrequency (%)
) 974
33.0%
( 974
33.0%
158
 
5.4%
& 123
 
4.2%
2 121
 
4.1%
. 99
 
3.4%
· 86
 
2.9%
1 73
 
2.5%
5 65
 
2.2%
3 52
 
1.8%
Other values (15) 227
 
7.7%
Han
ValueCountFrequency (%)
數 11
52.4%
大 4
 
19.0%
本 3
 
14.3%
眞 3
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 85223
91.9%
ASCII 7417
 
8.0%
None 105
 
0.1%
CJK 21
 
< 0.1%
Compat Jamo 11
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 11498
 
13.5%
원 9744
 
11.4%
수 2645
 
3.1%
스 2162
 
2.5%
어 2129
 
2.5%
이 1943
 
2.3%
영 1735
 
2.0%
아 1234
 
1.4%
음 1214
 
1.4%
악 1212
 
1.4%
Other values (550) 49707
58.3%
ASCII
ValueCountFrequency (%)
) 974
 
13.1%
( 974
 
13.1%
C 318
 
4.3%
S 301
 
4.1%
E 261
 
3.5%
M 260
 
3.5%
e 196
 
2.6%
a 192
 
2.6%
n 180
 
2.4%
A 175
 
2.4%
Other values (63) 3586
48.3%
None
ValueCountFrequency (%)
· 86
81.9%
é 12
 
11.4%
× 7
 
6.7%
CJK
ValueCountFrequency (%)
數 11
52.4%
大 4
 
19.0%
本 3
 
14.3%
眞 3
 
14.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 11
100.0%

학원주소
Text

Distinct2217
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T19:44:47.504269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length64
Mean length35.7398
Min length22

Characters and Unicode

Total characters357398
Distinct characters405
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique317 ?
Unique (%)3.2%

Sample

1st row광주광역시 광산구 수등로 280 , 호반리젠시빌아파트1차@상가 203호 (신가동,신가1차 호반리젠시빌)
2nd row광주광역시 광산구 송도로 180-1 , 1층 (도산동)
3rd row광주광역시 남구 서문대로663번길 11 , 3층 (진월동)
4th row광주광역시 광산구 임방울대로 603 , 201호 (도천동)
5th row광주광역시 광산구 장신로 136 , 601호일부 (수완동)
ValueCountFrequency (%)
광주광역시 10000
 
13.2%
9993
 
13.2%
광산구 4096
 
5.4%
서구 3216
 
4.2%
남구 2688
 
3.5%
2층 1341
 
1.8%
3층 1311
 
1.7%
봉선동 1019
 
1.3%
수완동 874
 
1.2%
일부 766
 
1.0%
Other values (1934) 40522
53.4%
2023-12-12T19:44:48.013669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66114
 
18.5%
광 24409
 
6.8%
, 15227
 
4.3%
동 11685
 
3.3%
주 10613
 
3.0%
시 10342
 
2.9%
2 10334
 
2.9%
) 10265
 
2.9%
( 10265
 
2.9%
구 10145
 
2.8%
Other values (395) 177999
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 194501
54.4%
Space Separator 66114
 
18.5%
Decimal Number 58594
 
16.4%
Other Punctuation 15573
 
4.4%
Close Punctuation 10265
 
2.9%
Open Punctuation 10265
 
2.9%
Dash Punctuation 1358
 
0.4%
Uppercase Letter 516
 
0.1%
Lowercase Letter 206
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 24409
 
12.5%
동 11685
 
6.0%
주 10613
 
5.5%
시 10342
 
5.3%
구 10145
 
5.2%
역 10000
 
5.1%
로 9956
 
5.1%
층 6589
 
3.4%
호 6100
 
3.1%
산 5036
 
2.6%
Other values (346) 89626
46.1%
Uppercase Letter
ValueCountFrequency (%)
K 79
15.3%
B 62
12.0%
S 51
9.9%
A 48
9.3%
H 45
8.7%
L 28
 
5.4%
G 28
 
5.4%
E 26
 
5.0%
R 26
 
5.0%
X 26
 
5.0%
Other values (7) 97
18.8%
Lowercase Letter
ValueCountFrequency (%)
i 44
21.4%
a 33
16.0%
t 25
12.1%
g 22
10.7%
l 22
10.7%
y 19
9.2%
n 16
 
7.8%
d 11
 
5.3%
u 8
 
3.9%
e 3
 
1.5%
Decimal Number
ValueCountFrequency (%)
2 10334
17.6%
1 10112
17.3%
3 8024
13.7%
0 7915
13.5%
4 6410
10.9%
5 4542
7.8%
6 3855
 
6.6%
7 2860
 
4.9%
8 2289
 
3.9%
9 2253
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 15227
97.8%
@ 201
 
1.3%
. 99
 
0.6%
· 39
 
0.3%
& 4
 
< 0.1%
/ 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
66114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10265
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10265
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1358
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 194501
54.4%
Common 162175
45.4%
Latin 722
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 24409
 
12.5%
동 11685
 
6.0%
주 10613
 
5.5%
시 10342
 
5.3%
구 10145
 
5.2%
역 10000
 
5.1%
로 9956
 
5.1%
층 6589
 
3.4%
호 6100
 
3.1%
산 5036
 
2.6%
Other values (346) 89626
46.1%
Latin
ValueCountFrequency (%)
K 79
 
10.9%
B 62
 
8.6%
S 51
 
7.1%
A 48
 
6.6%
H 45
 
6.2%
i 44
 
6.1%
a 33
 
4.6%
L 28
 
3.9%
G 28
 
3.9%
E 26
 
3.6%
Other values (18) 278
38.5%
Common
ValueCountFrequency (%)
66114
40.8%
, 15227
 
9.4%
2 10334
 
6.4%
) 10265
 
6.3%
( 10265
 
6.3%
1 10112
 
6.2%
3 8024
 
4.9%
0 7915
 
4.9%
4 6410
 
4.0%
5 4542
 
2.8%
Other values (11) 12967
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 194501
54.4%
ASCII 162858
45.6%
None 39
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66114
40.6%
, 15227
 
9.3%
2 10334
 
6.3%
) 10265
 
6.3%
( 10265
 
6.3%
1 10112
 
6.2%
3 8024
 
4.9%
0 7915
 
4.9%
4 6410
 
3.9%
5 4542
 
2.8%
Other values (38) 13650
 
8.4%
Hangul
ValueCountFrequency (%)
광 24409
 
12.5%
동 11685
 
6.0%
주 10613
 
5.5%
시 10342
 
5.3%
구 10145
 
5.2%
역 10000
 
5.1%
로 9956
 
5.1%
층 6589
 
3.4%
호 6100
 
3.1%
산 5036
 
2.6%
Other values (346) 89626
46.1%
None
ValueCountFrequency (%)
· 39
100.0%

설립자-성명
Text

Distinct1991
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T19:44:48.356677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length3
Mean length4.0025
Min length2

Characters and Unicode

Total characters40025
Distinct characters361
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique274 ?
Unique (%)2.7%

Sample

1st row최진희
2nd row이형호
3rd row박유서
4th row박상준
5th row박상아
ValueCountFrequency (%)
주식회사 953
 
8.6%
대교 361
 
3.3%
웅진씽크빅 132
 
1.2%
고영경 108
 
1.0%
지산한길 102
 
0.9%
유한회사 73
 
0.7%
동화세상에듀코 59
 
0.5%
김미 58
 
0.5%
박미 55
 
0.5%
김천수 47
 
0.4%
Other values (1990) 9144
82.4%
2023-12-12T19:44:48.884964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 2131
 
5.3%
주 1647
 
4.1%
정 1396
 
3.5%
이 1390
 
3.5%
사 1117
 
2.8%
회 1109
 
2.8%
식 1098
 
2.7%
1092
 
2.7%
영 1074
 
2.7%
박 898
 
2.2%
Other values (351) 27073
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37826
94.5%
Space Separator 1092
 
2.7%
Uppercase Letter 365
 
0.9%
Lowercase Letter 253
 
0.6%
Open Punctuation 221
 
0.6%
Close Punctuation 221
 
0.6%
Other Punctuation 39
 
0.1%
Dash Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2131
 
5.6%
주 1647
 
4.4%
정 1396
 
3.7%
이 1390
 
3.7%
사 1117
 
3.0%
회 1109
 
2.9%
식 1098
 
2.9%
영 1074
 
2.8%
박 898
 
2.4%
경 770
 
2.0%
Other values (315) 25196
66.6%
Uppercase Letter
ValueCountFrequency (%)
L 43
11.8%
A 39
10.7%
C 37
10.1%
T 35
9.6%
I 29
 
7.9%
E 27
 
7.4%
R 21
 
5.8%
S 18
 
4.9%
M 16
 
4.4%
H 15
 
4.1%
Other values (9) 85
23.3%
Lowercase Letter
ValueCountFrequency (%)
o 39
15.4%
d 39
15.4%
t 38
15.0%
u 20
7.9%
n 20
7.9%
i 19
7.5%
h 19
7.5%
a 19
7.5%
c 19
7.5%
e 19
7.5%
Other values (2) 2
 
0.8%
Space Separator
ValueCountFrequency (%)
1092
100.0%
Open Punctuation
ValueCountFrequency (%)
( 221
100.0%
Close Punctuation
ValueCountFrequency (%)
) 221
100.0%
Other Punctuation
ValueCountFrequency (%)
. 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37826
94.5%
Common 1581
 
4.0%
Latin 618
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 2131
 
5.6%
주 1647
 
4.4%
정 1396
 
3.7%
이 1390
 
3.7%
사 1117
 
3.0%
회 1109
 
2.9%
식 1098
 
2.9%
영 1074
 
2.8%
박 898
 
2.4%
경 770
 
2.0%
Other values (315) 25196
66.6%
Latin
ValueCountFrequency (%)
L 43
 
7.0%
o 39
 
6.3%
A 39
 
6.3%
d 39
 
6.3%
t 38
 
6.1%
C 37
 
6.0%
T 35
 
5.7%
I 29
 
4.7%
E 27
 
4.4%
R 21
 
3.4%
Other values (21) 271
43.9%
Common
ValueCountFrequency (%)
1092
69.1%
( 221
 
14.0%
) 221
 
14.0%
. 39
 
2.5%
- 8
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37826
94.5%
ASCII 2199
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 2131
 
5.6%
주 1647
 
4.4%
정 1396
 
3.7%
이 1390
 
3.7%
사 1117
 
3.0%
회 1109
 
2.9%
식 1098
 
2.9%
영 1074
 
2.8%
박 898
 
2.4%
경 770
 
2.0%
Other values (315) 25196
66.6%
ASCII
ValueCountFrequency (%)
1092
49.7%
( 221
 
10.1%
) 221
 
10.1%
L 43
 
2.0%
o 39
 
1.8%
A 39
 
1.8%
. 39
 
1.8%
d 39
 
1.8%
t 38
 
1.7%
C 37
 
1.7%
Other values (26) 391
 
17.8%

전화번호
Text

MISSING 

Distinct1893
Distinct (%)21.8%
Missing1322
Missing (%)13.2%
Memory size156.2 KiB
2023-12-12T19:44:49.169878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.00726
Min length12

Characters and Unicode

Total characters104199
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique259 ?
Unique (%)3.0%

Sample

1st row062-961-4755
2nd row062-451-5391
3rd row062-975-2000
4th row062-383-0531
5th row062-941-0582
ValueCountFrequency (%)
062-719-1077 86
 
1.0%
062-514-5544 58
 
0.7%
062-375-1551 55
 
0.6%
062-382-7701 53
 
0.6%
062-710-2131 47
 
0.5%
062-682-0912 39
 
0.4%
062-453-0600 39
 
0.4%
062-682-0983 36
 
0.4%
062-675-6686 34
 
0.4%
062-971-0522 32
 
0.4%
Other values (1883) 8199
94.5%
2023-12-12T19:44:49.840915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17356
16.7%
0 15587
15.0%
6 15102
14.5%
2 14023
13.5%
5 8505
8.2%
9 7517
7.2%
7 6214
 
6.0%
3 6118
 
5.9%
1 5799
 
5.6%
4 4064
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 86843
83.3%
Dash Punctuation 17356
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15587
17.9%
6 15102
17.4%
2 14023
16.1%
5 8505
9.8%
9 7517
8.7%
7 6214
 
7.2%
3 6118
 
7.0%
1 5799
 
6.7%
4 4064
 
4.7%
8 3914
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 17356
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 104199
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 17356
16.7%
0 15587
15.0%
6 15102
14.5%
2 14023
13.5%
5 8505
8.2%
9 7517
7.2%
7 6214
 
6.0%
3 6118
 
5.9%
1 5799
 
5.6%
4 4064
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 104199
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17356
16.7%
0 15587
15.0%
6 15102
14.5%
2 14023
13.5%
5 8505
8.2%
9 7517
7.2%
7 6214
 
6.0%
3 6118
 
5.9%
1 5799
 
5.6%
4 4064
 
3.9%

교습과정
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct47
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
보습
5920 
음악
1145 
독서실(유아/초·중·고)
 
525
실용외국어(유아/초·중·고)
 
484
<NA>
 
419
Other values (42)
1507 

Length

Max length24
Median length2
Mean length4.0334
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row음악
2nd row보습
3rd row기타(소)
4th row실용외국어(유아/초·중·고)
5th row댄스

Common Values

ValueCountFrequency (%)
보습 5920
59.2%
음악 1145
 
11.5%
독서실(유아/초·중·고) 525
 
5.2%
실용외국어(유아/초·중·고) 484
 
4.8%
<NA> 419
 
4.2%
미술 324
 
3.2%
컴퓨터(정보처리,통신기기,인터넷,소프트웨어) 164
 
1.6%
이·미용 139
 
1.4%
실용음악(성악) 128
 
1.3%
무용 117
 
1.2%
Other values (37) 635
 
6.3%

Length

2023-12-12T19:44:50.014240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
보습 5920
59.2%
음악 1145
 
11.5%
독서실(유아/초·중·고 525
 
5.2%
실용외국어(유아/초·중·고 484
 
4.8%
na 419
 
4.2%
미술 324
 
3.2%
컴퓨터(정보처리,통신기기,인터넷,소프트웨어 164
 
1.6%
이·미용 139
 
1.4%
실용음악(성악 128
 
1.3%
무용 117
 
1.2%
Other values (37) 635
 
6.3%

교습과목(반)
Text

Distinct4319
Distinct (%)43.2%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T19:44:50.354560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length7.2623262
Min length2

Characters and Unicode

Total characters72616
Distinct characters553
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3416 ?
Unique (%)34.2%

Sample

1st row피아노(중급)
2nd row수학(초등1)
3rd row멘사(초등)
4th row생활영어I7 내국인
5th row초급
ValueCountFrequency (%)
수학(초등 251
 
2.3%
수학(중등 247
 
2.3%
영어(초등 202
 
1.9%
수학(고등 197
 
1.8%
영어(중등 196
 
1.8%
영어(고등 165
 
1.5%
중등수학 137
 
1.3%
초등수학 134
 
1.2%
고등수학 129
 
1.2%
피아노(초급 124
 
1.1%
Other values (4265) 9113
83.6%
2023-12-12T19:44:50.922361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
등 6275
 
8.6%
( 6210
 
8.6%
) 6196
 
8.5%
학 3373
 
4.6%
초 3062
 
4.2%
어 3048
 
4.2%
중 2791
 
3.8%
수 2778
 
3.8%
고 2444
 
3.4%
영 2396
 
3.3%
Other values (543) 34043
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52111
71.8%
Open Punctuation 6401
 
8.8%
Close Punctuation 6387
 
8.8%
Decimal Number 2702
 
3.7%
Uppercase Letter 2233
 
3.1%
Other Punctuation 1070
 
1.5%
Space Separator 896
 
1.2%
Lowercase Letter 310
 
0.4%
Dash Punctuation 237
 
0.3%
Letter Number 224
 
0.3%
Other values (3) 45
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 6275
 
12.0%
학 3373
 
6.5%
초 3062
 
5.9%
어 3048
 
5.8%
중 2791
 
5.4%
수 2778
 
5.3%
고 2444
 
4.7%
영 2396
 
4.6%
급 1502
 
2.9%
국 1302
 
2.5%
Other values (464) 23140
44.4%
Uppercase Letter
ValueCountFrequency (%)
A 658
29.5%
B 575
25.8%
C 284
12.7%
D 147
 
6.6%
S 61
 
2.7%
E 56
 
2.5%
T 48
 
2.1%
L 43
 
1.9%
N 42
 
1.9%
P 39
 
1.7%
Other values (15) 280
12.5%
Lowercase Letter
ValueCountFrequency (%)
a 38
12.3%
i 29
 
9.4%
e 27
 
8.7%
t 24
 
7.7%
s 24
 
7.7%
n 21
 
6.8%
c 21
 
6.8%
r 20
 
6.5%
o 19
 
6.1%
u 12
 
3.9%
Other values (11) 75
24.2%
Decimal Number
ValueCountFrequency (%)
1 1090
40.3%
2 638
23.6%
3 378
 
14.0%
4 211
 
7.8%
5 125
 
4.6%
0 107
 
4.0%
6 63
 
2.3%
7 39
 
1.4%
9 26
 
1.0%
8 25
 
0.9%
Letter Number
ValueCountFrequency (%)
Ⅱ 89
39.7%
Ⅲ 45
20.1%
Ⅳ 36
16.1%
Ⅴ 29
 
12.9%
Ⅰ 19
 
8.5%
Ⅵ 5
 
2.2%
ⅴ 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 936
87.5%
/ 62
 
5.8%
· 36
 
3.4%
. 25
 
2.3%
& 10
 
0.9%
: 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 6210
97.0%
[ 191
 
3.0%
Close Punctuation
ValueCountFrequency (%)
) 6196
97.0%
] 191
 
3.0%
Math Symbol
ValueCountFrequency (%)
+ 32
91.4%
~ 3
 
8.6%
Space Separator
ValueCountFrequency (%)
896
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 237
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52111
71.8%
Common 17738
 
24.4%
Latin 2767
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 6275
 
12.0%
학 3373
 
6.5%
초 3062
 
5.9%
어 3048
 
5.8%
중 2791
 
5.4%
수 2778
 
5.3%
고 2444
 
4.7%
영 2396
 
4.6%
급 1502
 
2.9%
국 1302
 
2.5%
Other values (464) 23140
44.4%
Latin
ValueCountFrequency (%)
A 658
23.8%
B 575
20.8%
C 284
 
10.3%
D 147
 
5.3%
Ⅱ 89
 
3.2%
S 61
 
2.2%
E 56
 
2.0%
T 48
 
1.7%
Ⅲ 45
 
1.6%
L 43
 
1.6%
Other values (43) 761
27.5%
Common
ValueCountFrequency (%)
( 6210
35.0%
) 6196
34.9%
1 1090
 
6.1%
, 936
 
5.3%
896
 
5.1%
2 638
 
3.6%
3 378
 
2.1%
- 237
 
1.3%
4 211
 
1.2%
[ 191
 
1.1%
Other values (16) 755
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52111
71.8%
ASCII 20245
 
27.9%
Number Forms 224
 
0.3%
None 36
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
등 6275
 
12.0%
학 3373
 
6.5%
초 3062
 
5.9%
어 3048
 
5.8%
중 2791
 
5.4%
수 2778
 
5.3%
고 2444
 
4.7%
영 2396
 
4.6%
급 1502
 
2.9%
국 1302
 
2.5%
Other values (464) 23140
44.4%
ASCII
ValueCountFrequency (%)
( 6210
30.7%
) 6196
30.6%
1 1090
 
5.4%
, 936
 
4.6%
896
 
4.4%
A 658
 
3.3%
2 638
 
3.2%
B 575
 
2.8%
3 378
 
1.9%
C 284
 
1.4%
Other values (61) 2384
 
11.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 89
39.7%
Ⅲ 45
20.1%
Ⅳ 36
16.1%
Ⅴ 29
 
12.9%
Ⅰ 19
 
8.5%
Ⅵ 5
 
2.2%
ⅴ 1
 
0.4%
None
ValueCountFrequency (%)
· 36
100.0%

정원
Text

Distinct142
Distinct (%)1.4%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T19:44:51.169904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.4821482
Min length1

Characters and Unicode

Total characters14820
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)0.5%

Sample

1st row10
2nd row120
3rd row100
4th row50
5th row0
ValueCountFrequency (%)
0 4812
48.1%
10 921
 
9.2%
20 651
 
6.5%
5 406
 
4.1%
30 311
 
3.1%
15 303
 
3.0%
100 209
 
2.1%
12 190
 
1.9%
40 173
 
1.7%
50 166
 
1.7%
Other values (132) 1857
 
18.6%
2023-12-12T19:44:51.687281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8173
55.1%
1 2193
 
14.8%
2 1364
 
9.2%
5 1224
 
8.3%
3 554
 
3.7%
4 384
 
2.6%
6 331
 
2.2%
8 287
 
1.9%
7 177
 
1.2%
9 132
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14819
> 99.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8173
55.2%
1 2193
 
14.8%
2 1364
 
9.2%
5 1224
 
8.3%
3 554
 
3.7%
4 384
 
2.6%
6 331
 
2.2%
8 287
 
1.9%
7 177
 
1.2%
9 132
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14820
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8173
55.1%
1 2193
 
14.8%
2 1364
 
9.2%
5 1224
 
8.3%
3 554
 
3.7%
4 384
 
2.6%
6 331
 
2.2%
8 287
 
1.9%
7 177
 
1.2%
9 132
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14820
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8173
55.1%
1 2193
 
14.8%
2 1364
 
9.2%
5 1224
 
8.3%
3 554
 
3.7%
4 384
 
2.6%
6 331
 
2.2%
8 287
 
1.9%
7 177
 
1.2%
9 132
 
0.9%

교습기간
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1개월 0일
9062 
0개월 1일
 
299
2개월 0일
 
138
0개월 0일
 
118
3개월 0일
 
101
Other values (41)
 
282

Length

Max length8
Median length6
Mean length6.0087
Min length6

Unique

Unique12 ?
Unique (%)0.1%

Sample

1st row1개월 0일
2nd row1개월 0일
3rd row1개월 0일
4th row1개월 0일
5th row1개월 0일

Common Values

ValueCountFrequency (%)
1개월 0일 9062
90.6%
0개월 1일 299
 
3.0%
2개월 0일 138
 
1.4%
0개월 0일 118
 
1.2%
3개월 0일 101
 
1.0%
1개월 7일 60
 
0.6%
4개월 0일 43
 
0.4%
1개월 5일 40
 
0.4%
6개월 0일 13
 
0.1%
5개월 0일 11
 
0.1%
Other values (36) 115
 
1.1%

Length

2023-12-12T19:44:51.844023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0일 9496
47.5%
1개월 9191
46.0%
0개월 473
 
2.4%
1일 300
 
1.5%
2개월 145
 
0.7%
3개월 110
 
0.5%
7일 69
 
0.3%
4개월 47
 
0.2%
5일 43
 
0.2%
15일 25
 
0.1%
Other values (24) 101
 
0.5%

총교습시간(분)
Text

Distinct275
Distinct (%)2.8%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T19:44:52.245519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.2009201
Min length1

Characters and Unicode

Total characters42005
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)0.9%

Sample

1st row1,200
2nd row1,200
3rd row1,080
4th row1,800
5th row240
ValueCountFrequency (%)
1,200 1368
 
13.7%
1,440 1099
 
11.0%
0 555
 
5.6%
1,800 427
 
4.3%
1,400 375
 
3.8%
720 359
 
3.6%
960 344
 
3.4%
1,600 273
 
2.7%
1,080 258
 
2.6%
1,000 250
 
2.5%
Other values (265) 4691
46.9%
2023-12-12T19:44:52.794757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15248
36.3%
, 6554
15.6%
1 5778
 
13.8%
4 4010
 
9.5%
2 3749
 
8.9%
8 2042
 
4.9%
6 1824
 
4.3%
3 1019
 
2.4%
9 632
 
1.5%
7 612
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35451
84.4%
Other Punctuation 6554
 
15.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15248
43.0%
1 5778
 
16.3%
4 4010
 
11.3%
2 3749
 
10.6%
8 2042
 
5.8%
6 1824
 
5.1%
3 1019
 
2.9%
9 632
 
1.8%
7 612
 
1.7%
5 537
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 6554
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42005
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15248
36.3%
, 6554
15.6%
1 5778
 
13.8%
4 4010
 
9.5%
2 3749
 
8.9%
8 2042
 
4.9%
6 1824
 
4.3%
3 1019
 
2.4%
9 632
 
1.5%
7 612
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42005
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15248
36.3%
, 6554
15.6%
1 5778
 
13.8%
4 4010
 
9.5%
2 3749
 
8.9%
8 2042
 
4.9%
6 1824
 
4.3%
3 1019
 
2.4%
9 632
 
1.5%
7 612
 
1.5%

교습비
Text

Distinct556
Distinct (%)5.6%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T19:44:53.205930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.8120812
Min length1

Characters and Unicode

Total characters68114
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)2.3%

Sample

1st row100,000
2nd row150,000
3rd row110,000
4th row305,000
5th row120,000
ValueCountFrequency (%)
150,000 967
 
9.7%
200,000 725
 
7.3%
180,000 541
 
5.4%
120,000 452
 
4.5%
250,000 436
 
4.4%
100,000 433
 
4.3%
130,000 331
 
3.3%
300,000 282
 
2.8%
140,000 274
 
2.7%
170,000 218
 
2.2%
Other values (546) 5340
53.4%
2023-12-12T19:44:53.819102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 39391
57.8%
, 10285
 
15.1%
1 5113
 
7.5%
2 3458
 
5.1%
5 2929
 
4.3%
3 1766
 
2.6%
4 1380
 
2.0%
8 1332
 
2.0%
6 1023
 
1.5%
7 849
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57829
84.9%
Other Punctuation 10285
 
15.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 39391
68.1%
1 5113
 
8.8%
2 3458
 
6.0%
5 2929
 
5.1%
3 1766
 
3.1%
4 1380
 
2.4%
8 1332
 
2.3%
6 1023
 
1.8%
7 849
 
1.5%
9 588
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 10285
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68114
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 39391
57.8%
, 10285
 
15.1%
1 5113
 
7.5%
2 3458
 
5.1%
5 2929
 
4.3%
3 1766
 
2.6%
4 1380
 
2.0%
8 1332
 
2.0%
6 1023
 
1.5%
7 849
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 39391
57.8%
, 10285
 
15.1%
1 5113
 
7.5%
2 3458
 
5.1%
5 2929
 
4.3%
3 1766
 
2.6%
4 1380
 
2.0%
8 1332
 
2.0%
6 1023
 
1.5%
7 849
 
1.2%

모의고사비
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9998 
<NA>
 
1
11
 
1

Length

Max length4
Median length1
Mean length1.0004
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9998
> 99.9%
<NA> 1
 
< 0.1%
11 1
 
< 0.1%

Length

2023-12-12T19:44:53.980365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:44:54.108123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9998
> 99.9%
na 1
 
< 0.1%
11 1
 
< 0.1%

재료비
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9986 
900,000
 
3
400,000
 
2
<NA>
 
1
1,750,000
 
1
Other values (7)
 
7

Length

Max length9
Median length1
Mean length1.0087
Min length1

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9986
99.9%
900,000 3
 
< 0.1%
400,000 2
 
< 0.1%
<NA> 1
 
< 0.1%
1,750,000 1
 
< 0.1%
137,440 1
 
< 0.1%
480,000 1
 
< 0.1%
2,230,000 1
 
< 0.1%
450,000 1
 
< 0.1%
200,000 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2023-12-12T19:44:54.239107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 9986
99.9%
900,000 3
 
< 0.1%
400,000 2
 
< 0.1%
na 1
 
< 0.1%
1,750,000 1
 
< 0.1%
137,440 1
 
< 0.1%
480,000 1
 
< 0.1%
2,230,000 1
 
< 0.1%
450,000 1
 
< 0.1%
200,000 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

급식비
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9996 
<NA>
 
1
60,000
 
1
75,000
 
1
66,700
 
1

Length

Max length6
Median length1
Mean length1.0018
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9996
> 99.9%
<NA> 1
 
< 0.1%
60,000 1
 
< 0.1%
75,000 1
 
< 0.1%
66,700 1
 
< 0.1%

Length

2023-12-12T19:44:54.405601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:44:54.545021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9996
> 99.9%
na 1
 
< 0.1%
60,000 1
 
< 0.1%
75,000 1
 
< 0.1%
66,700 1
 
< 0.1%

기숙사비
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9999 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0003
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9999
> 99.9%
<NA> 1
 
< 0.1%

Length

2023-12-12T19:44:54.673766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:44:54.783785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9999
> 99.9%
na 1
 
< 0.1%

차량비
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9966 
25,000
 
19
27,000
 
5
18,000
 
3
20,000
 
2
Other values (4)
 
5

Length

Max length6
Median length1
Mean length1.0168
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9966
99.7%
25,000 19
 
0.2%
27,000 5
 
0.1%
18,000 3
 
< 0.1%
20,000 2
 
< 0.1%
30,000 2
 
< 0.1%
<NA> 1
 
< 0.1%
26,000 1
 
< 0.1%
10,000 1
 
< 0.1%

Length

2023-12-12T19:44:54.924377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:44:55.079721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9966
99.7%
25,000 19
 
0.2%
27,000 5
 
< 0.1%
18,000 3
 
< 0.1%
20,000 2
 
< 0.1%
30,000 2
 
< 0.1%
na 1
 
< 0.1%
26,000 1
 
< 0.1%
10,000 1
 
< 0.1%

피복비
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9821 
<NA>
 
174
27,500
 
2
149,230
 
1
36,200
 
1

Length

Max length7
Median length1
Mean length1.0548
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9821
98.2%
<NA> 174
 
1.7%
27,500 2
 
< 0.1%
149,230 1
 
< 0.1%
36,200 1
 
< 0.1%
37,200 1
 
< 0.1%

Length

2023-12-12T19:44:55.256523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:44:55.402723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9821
98.2%
na 174
 
1.7%
27,500 2
 
< 0.1%
149,230 1
 
< 0.1%
36,200 1
 
< 0.1%
37,200 1
 
< 0.1%

강사수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8473
Minimum0
Maximum52
Zeros683
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:44:55.511714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q35
95-th percentile11
Maximum52
Range52
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.0763028
Coefficient of variation (CV)1.059523
Kurtosis24.122538
Mean3.8473
Median Absolute Deviation (MAD)2
Skewness3.4964285
Sum38473
Variance16.616244
MonotonicityNot monotonic
2023-12-12T19:44:55.671759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2 2189
21.9%
1 1964
19.6%
3 1353
13.5%
4 922
9.2%
5 856
 
8.6%
0 683
 
6.8%
6 500
 
5.0%
7 353
 
3.5%
8 296
 
3.0%
9 159
 
1.6%
Other values (16) 725
 
7.2%
ValueCountFrequency (%)
0 683
 
6.8%
1 1964
19.6%
2 2189
21.9%
3 1353
13.5%
4 922
9.2%
5 856
 
8.6%
6 500
 
5.0%
7 353
 
3.5%
8 296
 
3.0%
9 159
 
1.6%
ValueCountFrequency (%)
52 10
 
0.1%
32 3
 
< 0.1%
29 9
 
0.1%
24 12
 
0.1%
23 4
 
< 0.1%
22 12
 
0.1%
20 53
 
0.5%
18 5
 
0.1%
17 142
1.4%
16 61
0.6%

Interactions

2023-12-12T19:44:45.794304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:44:55.787159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교습과정교습기간모의고사비재료비급식비차량비피복비강사수
교습과정1.0000.8450.0000.1930.0000.1770.0000.540
교습기간0.8451.0000.0000.2730.0000.0000.1740.259
모의고사비0.0000.0001.0000.0000.0000.0000.0000.000
재료비0.1930.2730.0001.0000.0000.0000.0000.077
급식비0.0000.0000.0000.0001.0000.0000.0000.099
차량비0.1770.0000.0000.0000.0001.0000.0000.823
피복비0.0000.1740.0000.0000.0000.0001.0000.066
강사수0.5400.2590.0000.0770.0990.8230.0661.000
2023-12-12T19:44:55.931429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
모의고사비차량비교습기간재료비기숙사비교습과정피복비급식비
모의고사비1.0000.0000.0000.0001.0000.0000.0000.000
차량비0.0001.0000.0000.0001.0000.0680.0000.000
교습기간0.0000.0001.0000.0931.0000.2840.0800.000
재료비0.0000.0000.0931.0001.0000.0640.0000.000
기숙사비1.0001.0001.0001.0001.0001.0001.0001.000
교습과정0.0000.0680.2840.0641.0001.0000.0000.000
피복비0.0000.0000.0800.0001.0000.0001.0000.000
급식비0.0000.0000.0000.0001.0000.0000.0001.000
2023-12-12T19:44:56.094172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강사수교습과정교습기간모의고사비재료비급식비기숙사비차량비피복비
강사수1.0000.2370.1010.0000.0360.0451.0000.4100.040
교습과정0.2371.0000.2840.0000.0640.0001.0000.0680.000
교습기간0.1010.2841.0000.0000.0930.0001.0000.0000.080
모의고사비0.0000.0000.0001.0000.0000.0001.0000.0000.000
재료비0.0360.0640.0930.0001.0000.0001.0000.0000.000
급식비0.0450.0000.0000.0000.0001.0001.0000.0000.000
기숙사비1.0001.0001.0001.0001.0001.0001.0001.0001.000
차량비0.4100.0680.0000.0000.0000.0001.0001.0000.000
피복비0.0400.0000.0800.0000.0000.0001.0000.0001.000

Missing values

2023-12-12T19:44:45.937447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:44:46.154567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T19:44:46.402650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

학원명학원주소설립자-성명전화번호교습과정교습과목(반)정원교습기간총교습시간(분)교습비모의고사비재료비급식비기숙사비차량비피복비강사수
1037에센피아노학원광주광역시 광산구 수등로 280 , 호반리젠시빌아파트1차@상가 203호 (신가동,신가1차 호반리젠시빌)최진희062-961-4755음악피아노(중급)101개월 0일1,200100,0000000001
16130숨쉬는수학학원광주광역시 광산구 송도로 180-1 , 1층 (도산동)이형호<NA>보습수학(초등1)1201개월 0일1,200150,0000000002
12030라온창의사고력학원광주광역시 남구 서문대로663번길 11 , 3층 (진월동)박유서062-451-5391기타(소)멘사(초등)1001개월 0일1,080110,0000000001
9747(광산)브라이튼어학원광주광역시 광산구 임방울대로 603 , 201호 (도천동)박상준062-975-2000실용외국어(유아/초·중·고)생활영어I7 내국인501개월 0일1,800305,00000000032
10586미드미폴댄스학원광주광역시 광산구 장신로 136 , 601호일부 (수완동)박상아<NA>댄스초급01개월 0일240120,0000000001
7605금탑아카데미학원광주광역시 서구 화운로 173-1 , 3층 (화정동)박승진062-383-0531보습수학(초등)01개월 0일1,200100,0000000002
7053나영철영수학원광주광역시 광산구 소촌로 90-19 , 2층 (소촌동)나영철062-941-0582보습중등수학01개월 0일1,280160,0000000003
6618첨단시매쓰수학학원광주광역시 광산구 첨단중앙로 102 , 305호 (월계동)김정수062-971-3690보습수학(중등)01개월 0일1,440180,0000000003
14211아이비티영어학원광주광역시 광산구 임방울대로 142-10 , 5층 (운남동)김수진<NA>보습수학(고등)01개월 0일1,440230,0000000003
15583더포스학원광주광역시 남구 효천중앙로 62 , 502호 (임암동)백란희<NA>보습·논술수학(고등)01개월 0일1,440250,0000000005
학원명학원주소설립자-성명전화번호교습과정교습과목(반)정원교습기간총교습시간(분)교습비모의고사비재료비급식비기숙사비차량비피복비강사수
8877세움학원광주광역시 광산구 사암로340번길 31 , 201호일부 (월곡동)박철062-954-8873보습중등영어01개월 0일1,320180,0000000002
16505채움무용학원광주광역시 광산구 신창로 109 , 4층 (신창동)장혜원<NA>무용중급(B)반01개월 0일2,400300,0000000001
7785광주서강컴퓨터학원광주광역시 서구 하남대로710번길 6 , 4층일부 (동천동)김미062-514-5544컴퓨터(정보처리,통신기기,인터넷,소프트웨어)사무행정컴퓨터실무[L3]03개월 0일7,2001,440,0000000002
12420신의한수수학학원광주광역시 서구 치평로 76 , 406호 (치평동)신재호062-383-2502보습수학내신B(중등)01개월 0일1,200160,0000000000
17822커넥츠프랩수능관광주첨단점학원광주광역시 광산구 첨단중앙로116번길 10 , 4층 (월계동)나홍석062-971-7776보습종합(국영수)고등A601개월 0일3,360570,0000000002
15658그린컴퓨터아카데미광주학원광주광역시 서구 상무중앙로 44 , 501호일부 (치평동)김천수062-710-2131<NA>캐드 특강201개월 0일2,400400,00000000016
4995석사잉글리쉬무무학원광주광역시 광산구 풍영로330번길 34 , 신안실크밸리@상가 304,305호 (장덕동,수완신안실크밸리)차현옥062-953-0599보습영어(초등)1001개월 0일1,300155,0000000001
13930닥터필리스학원광주광역시 남구 진제길 16 , 2층 (진월동)김명화062-651-0922보습수학(초등)1801개월 0일1,800170,0000000002
4053이수진과학학원광주광역시 광산구 첨단중앙로106번길 23 , 3층 (월계동)이수진062-973-7239보습중등과학2001개월 0일1,440180,0000000003
11083독서실뿌리독서실광주광역시 남구 금당로 49 , 3층 (진월동)오해원062-672-7778독서실(유아/초·중·고)학생월권(1인실)01개월 0일0110,0000000000

Duplicate rows

Most frequently occurring

학원명학원주소설립자-성명전화번호교습과정교습과목(반)정원교습기간총교습시간(분)교습비모의고사비재료비급식비기숙사비차량비피복비강사수# duplicates
0선수학학원광주광역시 광산구 임방울대로332번길 29 , 3층일부 (수완동)김선화062-954-7575보습수학(중등)241개월 0일2,160300,00000000022
1지오캐드그래픽학원광주광역시 광산구 사암로 288-1 , 2층 (월곡동)임훈062-714-3111컴퓨터(정보처리,통신기기,인터넷,소프트웨어)전산응용기계제도(일반)101개월 15일5,400648,00000000042
2흑석건축전기학원광주광역시 광산구 풍영로101번안길 1-7 , 4층일부 (흑석동)김은경<NA><NA>실내건축(산업)기사 필기202개월 0일4,320800,00000000062