Overview

Dataset statistics

Number of variables22
Number of observations1139
Missing cells2475
Missing cells (%)9.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory205.9 KiB
Average record size in memory185.1 B

Variable types

Text5
Numeric9
Boolean4
DateTime2
Categorical2

Dataset

Description과천도시공사에서 운영하는 과천시민회관, 관문실내체육관 등에서 개설된 체육프로그램 강습반(강습반명, 강좌내용, 대상, 할인여부 등) 정보입니다.
Author과천도시공사
URLhttps://www.data.go.kr/data/15040288/fileData.do

Alerts

어린이강좌유무 has constant value ""Constant
사용유무 has constant value ""Constant
강습반관련연락처 is highly imbalanced (57.0%)Imbalance
성별구분 is highly imbalanced (87.5%)Imbalance
강습반특이사항 has 626 (55.0%) missing valuesMissing
강습반개설목적 has 226 (19.8%) missing valuesMissing
시작나이 has 280 (24.6%) missing valuesMissing
종료나이 has 280 (24.6%) missing valuesMissing
강좌상세정보 has 495 (43.5%) missing valuesMissing
강좌준비물 has 520 (45.7%) missing valuesMissing
강좌할인구분 has 48 (4.2%) missing valuesMissing
강습정원 is highly skewed (γ1 = 23.83263666)Skewed
강습정원 has 24 (2.1%) zerosZeros

Reproduction

Analysis started2023-12-12 13:46:10.828506
Analysis finished2023-12-12 13:46:11.774264
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

강습반명
Text

Distinct1131
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2023-12-12T22:46:12.009497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length26
Mean length17.071115
Min length3

Characters and Unicode

Total characters19444
Distinct characters342
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1124 ?
Unique (%)98.7%

Sample

1st row어머니09마스터1
2nd row저녁직장인21교정
3rd row방특 필라테스(초등생)
4th row수영(방특)2차14시 초급(자유형,배영)
5th row볼링방특14시(중고생)
ValueCountFrequency (%)
1:2 37
 
2.1%
입단상담 32
 
1.8%
1:1pt 21
 
1.2%
관문헬스 16
 
0.9%
수영 13
 
0.7%
주말 13
 
0.7%
골프일일입장(18:00~19:15 10
 
0.6%
골프일일입장(21:00~22:15 10
 
0.6%
수영일일입장(19:00~20:00 10
 
0.6%
골프일일입장(15:00~16:15 10
 
0.6%
Other values (1125) 1566
90.1%
2023-12-12T22:46:12.472393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1307
 
6.7%
) 1240
 
6.4%
( 1239
 
6.4%
0 1128
 
5.8%
600
 
3.1%
: 515
 
2.6%
2 506
 
2.6%
시 482
 
2.5%
일 391
 
2.0%
3 356
 
1.8%
Other values (332) 11680
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9938
51.1%
Decimal Number 4586
23.6%
Close Punctuation 1240
 
6.4%
Open Punctuation 1239
 
6.4%
Other Punctuation 890
 
4.6%
Space Separator 600
 
3.1%
Uppercase Letter 452
 
2.3%
Math Symbol 419
 
2.2%
Lowercase Letter 41
 
0.2%
Dash Punctuation 39
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 482
 
4.9%
일 391
 
3.9%
인 310
 
3.1%
스 277
 
2.8%
수 266
 
2.7%
장 259
 
2.6%
년 223
 
2.2%
정 212
 
2.1%
소 209
 
2.1%
초 200
 
2.0%
Other values (275) 7109
71.5%
Uppercase Letter
ValueCountFrequency (%)
P 118
26.1%
T 104
23.0%
A 79
17.5%
B 62
13.7%
E 19
 
4.2%
S 13
 
2.9%
M 9
 
2.0%
K 8
 
1.8%
N 7
 
1.5%
C 6
 
1.3%
Other values (10) 27
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
i 8
19.5%
g 5
12.2%
d 5
12.2%
r 4
9.8%
e 4
9.8%
x 4
9.8%
t 2
 
4.9%
s 2
 
4.9%
h 1
 
2.4%
l 1
 
2.4%
Other values (5) 5
12.2%
Decimal Number
ValueCountFrequency (%)
1 1307
28.5%
0 1128
24.6%
2 506
 
11.0%
3 356
 
7.8%
5 295
 
6.4%
8 289
 
6.3%
6 246
 
5.4%
4 165
 
3.6%
9 157
 
3.4%
7 137
 
3.0%
Other Punctuation
ValueCountFrequency (%)
: 515
57.9%
/ 236
26.5%
, 67
 
7.5%
. 63
 
7.1%
& 8
 
0.9%
% 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 331
79.0%
+ 88
 
21.0%
Close Punctuation
ValueCountFrequency (%)
) 1240
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1239
100.0%
Space Separator
ValueCountFrequency (%)
600
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9938
51.1%
Common 9013
46.4%
Latin 493
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 482
 
4.9%
일 391
 
3.9%
인 310
 
3.1%
스 277
 
2.8%
수 266
 
2.7%
장 259
 
2.6%
년 223
 
2.2%
정 212
 
2.1%
소 209
 
2.1%
초 200
 
2.0%
Other values (275) 7109
71.5%
Latin
ValueCountFrequency (%)
P 118
23.9%
T 104
21.1%
A 79
16.0%
B 62
12.6%
E 19
 
3.9%
S 13
 
2.6%
M 9
 
1.8%
i 8
 
1.6%
K 8
 
1.6%
N 7
 
1.4%
Other values (25) 66
13.4%
Common
ValueCountFrequency (%)
1 1307
14.5%
) 1240
13.8%
( 1239
13.7%
0 1128
12.5%
600
6.7%
: 515
 
5.7%
2 506
 
5.6%
3 356
 
3.9%
~ 331
 
3.7%
5 295
 
3.3%
Other values (12) 1496
16.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9938
51.1%
ASCII 9506
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1307
13.7%
) 1240
13.0%
( 1239
13.0%
0 1128
11.9%
600
 
6.3%
: 515
 
5.4%
2 506
 
5.3%
3 356
 
3.7%
~ 331
 
3.5%
5 295
 
3.1%
Other values (47) 1989
20.9%
Hangul
ValueCountFrequency (%)
시 482
 
4.9%
일 391
 
3.9%
인 310
 
3.1%
스 277
 
2.8%
수 266
 
2.7%
장 259
 
2.6%
년 223
 
2.2%
정 212
 
2.1%
소 209
 
2.1%
초 200
 
2.0%
Other values (275) 7109
71.5%

강습등급
Real number (ℝ)

Distinct13
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8630378
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T22:46:12.608115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile6.1
Maximum18
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.2510755
Coefficient of variation (CV)1.2082823
Kurtosis17.981729
Mean1.8630378
Median Absolute Deviation (MAD)0
Skewness3.7853908
Sum2122
Variance5.0673409
MonotonicityNot monotonic
2023-12-12T22:46:12.734517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 911
80.0%
7 39
 
3.4%
5 39
 
3.4%
4 39
 
3.4%
3 38
 
3.3%
2 30
 
2.6%
6 25
 
2.2%
13 6
 
0.5%
18 4
 
0.4%
16 3
 
0.3%
Other values (3) 5
 
0.4%
ValueCountFrequency (%)
1 911
80.0%
2 30
 
2.6%
3 38
 
3.3%
4 39
 
3.4%
5 39
 
3.4%
6 25
 
2.2%
7 39
 
3.4%
11 2
 
0.2%
13 6
 
0.5%
14 2
 
0.2%
ValueCountFrequency (%)
18 4
 
0.4%
16 3
 
0.3%
15 1
 
0.1%
14 2
 
0.2%
13 6
 
0.5%
11 2
 
0.2%
7 39
3.4%
6 25
2.2%
5 39
3.4%
4 39
3.4%

진도
Real number (ℝ)

Distinct28
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8200176
Minimum1
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T22:46:12.852638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile19
Maximum42
Range41
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.0436814
Coefficient of variation (CV)1.8438872
Kurtosis8.7937394
Mean3.8200176
Median Absolute Deviation (MAD)0
Skewness2.9081916
Sum4351
Variance49.613448
MonotonicityNot monotonic
2023-12-12T22:46:12.965560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 925
81.2%
13 31
 
2.7%
14 25
 
2.2%
7 21
 
1.8%
15 18
 
1.6%
10 18
 
1.6%
4 12
 
1.1%
19 10
 
0.9%
20 9
 
0.8%
32 7
 
0.6%
Other values (18) 63
 
5.5%
ValueCountFrequency (%)
1 925
81.2%
2 6
 
0.5%
3 1
 
0.1%
4 12
 
1.1%
7 21
 
1.8%
10 18
 
1.6%
12 7
 
0.6%
13 31
 
2.7%
14 25
 
2.2%
15 18
 
1.6%
ValueCountFrequency (%)
42 4
0.4%
38 5
0.4%
37 1
 
0.1%
34 1
 
0.1%
33 4
0.4%
32 7
0.6%
31 6
0.5%
27 1
 
0.1%
25 3
0.3%
24 3
0.3%

강습반유형
Real number (ℝ)

Distinct8
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5434592
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T22:46:13.069799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile6
Maximum8
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5788026
Coefficient of variation (CV)1.0228988
Kurtosis7.0596129
Mean1.5434592
Median Absolute Deviation (MAD)0
Skewness2.8813922
Sum1758
Variance2.4926175
MonotonicityNot monotonic
2023-12-12T22:46:13.170120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 998
87.6%
6 29
 
2.5%
7 25
 
2.2%
5 23
 
2.0%
4 21
 
1.8%
8 19
 
1.7%
3 12
 
1.1%
2 12
 
1.1%
ValueCountFrequency (%)
1 998
87.6%
2 12
 
1.1%
3 12
 
1.1%
4 21
 
1.8%
5 23
 
2.0%
6 29
 
2.5%
7 25
 
2.2%
8 19
 
1.7%
ValueCountFrequency (%)
8 19
 
1.7%
7 25
 
2.2%
6 29
 
2.5%
5 23
 
2.0%
4 21
 
1.8%
3 12
 
1.1%
2 12
 
1.1%
1 998
87.6%

강습요일
Real number (ℝ)

Distinct28
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42223.088
Minimum1
Maximum1234567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T22:46:13.305210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median135
Q312345
95-th percentile123456
Maximum1234567
Range1234566
Interquartile range (IQR)12339

Descriptive statistics

Standard deviation146848.43
Coefficient of variation (CV)3.4779179
Kurtosis54.634848
Mean42223.088
Median Absolute Deviation (MAD)130
Skewness7.103272
Sum48092097
Variance2.1564462 × 1010
MonotonicityNot monotonic
2023-12-12T22:46:13.471363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
123456 202
17.7%
12345 157
13.8%
24 142
12.5%
135 139
12.2%
6 138
12.1%
3 41
 
3.6%
2 38
 
3.3%
5 37
 
3.2%
4 37
 
3.2%
1 33
 
2.9%
Other values (18) 175
15.4%
ValueCountFrequency (%)
1 33
 
2.9%
2 38
 
3.3%
3 41
 
3.6%
4 37
 
3.2%
5 37
 
3.2%
6 138
12.1%
7 30
 
2.6%
12 10
 
0.9%
13 14
 
1.2%
14 3
 
0.3%
ValueCountFrequency (%)
1234567 15
 
1.3%
234567 11
 
1.0%
123456 202
17.7%
23456 1
 
0.1%
12345 157
13.8%
2345 25
 
2.2%
1245 2
 
0.2%
246 22
 
1.9%
235 6
 
0.5%
135 139
12.2%

강습시작시간
Real number (ℝ)

Distinct35
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1227.2344
Minimum0
Maximum2200
Zeros2
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T22:46:13.593600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile600
Q1900
median1100
Q31600
95-th percentile2030
Maximum2200
Range2200
Interquartile range (IQR)700

Descriptive statistics

Standard deviation479.59725
Coefficient of variation (CV)0.39079514
Kurtosis-1.0585823
Mean1227.2344
Median Absolute Deviation (MAD)400
Skewness0.25304984
Sum1397820
Variance230013.52
MonotonicityNot monotonic
2023-12-12T22:46:13.718758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
600 194
17.0%
900 114
 
10.0%
1000 84
 
7.4%
1100 75
 
6.6%
1900 65
 
5.7%
1600 64
 
5.6%
1500 61
 
5.4%
1400 56
 
4.9%
1300 47
 
4.1%
1200 45
 
4.0%
Other values (25) 334
29.3%
ValueCountFrequency (%)
0 2
 
0.2%
100 1
 
0.1%
500 2
 
0.2%
600 194
17.0%
630 3
 
0.3%
700 25
 
2.2%
730 10
 
0.9%
800 37
 
3.2%
900 114
10.0%
930 11
 
1.0%
ValueCountFrequency (%)
2200 10
 
0.9%
2100 42
3.7%
2030 16
 
1.4%
2000 32
2.8%
1930 2
 
0.2%
1900 65
5.7%
1830 3
 
0.3%
1800 44
3.9%
1700 37
3.2%
1630 13
 
1.1%

강습종료시간
Real number (ℝ)

Distinct79
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1568.4881
Minimum100
Maximum2359
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T22:46:13.877213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile715
Q11150
median1600
Q32000
95-th percentile2230
Maximum2359
Range2259
Interquartile range (IQR)850

Descriptive statistics

Standard deviation485.07558
Coefficient of variation (CV)0.30926315
Kurtosis-1.0329179
Mean1568.4881
Median Absolute Deviation (MAD)400
Skewness-0.22005385
Sum1786508
Variance235298.32
MonotonicityNot monotonic
2023-12-12T22:46:14.014436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2230 100
 
8.8%
1950 44
 
3.9%
1750 42
 
3.7%
650 41
 
3.6%
1650 40
 
3.5%
1800 38
 
3.3%
1550 38
 
3.3%
1150 37
 
3.2%
2200 37
 
3.2%
1250 36
 
3.2%
Other values (69) 686
60.2%
ValueCountFrequency (%)
100 1
 
0.1%
650 41
3.6%
700 11
 
1.0%
715 10
 
0.9%
750 21
1.8%
800 4
 
0.4%
810 3
 
0.3%
830 13
 
1.1%
850 16
 
1.4%
900 1
 
0.1%
ValueCountFrequency (%)
2359 2
 
0.2%
2320 4
 
0.4%
2300 16
 
1.4%
2250 6
 
0.5%
2230 100
8.8%
2215 10
 
0.9%
2200 37
 
3.2%
2150 31
 
2.7%
2130 15
 
1.3%
2120 3
 
0.3%

강습정원
Real number (ℝ)

SKEWED  ZEROS 

Distinct39
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1764.3529
Minimum0
Maximum990000
Zeros24
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T22:46:14.146222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q15
median10
Q325
95-th percentile100
Maximum990000
Range990000
Interquartile range (IQR)20

Descriptive statistics

Standard deviation41465.448
Coefficient of variation (CV)23.501788
Kurtosis566.9911
Mean1764.3529
Median Absolute Deviation (MAD)7
Skewness23.832637
Sum2009598
Variance1.7193834 × 109
MonotonicityNot monotonic
2023-12-12T22:46:14.291428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
5 193
16.9%
20 174
15.3%
10 168
14.7%
3 89
7.8%
50 76
 
6.7%
15 68
 
6.0%
40 43
 
3.8%
25 43
 
3.8%
30 43
 
3.8%
2 38
 
3.3%
Other values (29) 204
17.9%
ValueCountFrequency (%)
0 24
 
2.1%
1 17
 
1.5%
2 38
 
3.3%
3 89
7.8%
4 29
 
2.5%
5 193
16.9%
6 9
 
0.8%
7 1
 
0.1%
8 3
 
0.3%
10 168
14.7%
ValueCountFrequency (%)
990000 2
 
0.2%
1000 1
 
0.1%
400 1
 
0.1%
320 3
 
0.3%
300 12
1.1%
230 2
 
0.2%
200 9
0.8%
170 1
 
0.1%
150 3
 
0.3%
120 2
 
0.2%

강습반특이사항
Text

MISSING 

Distinct132
Distinct (%)25.7%
Missing626
Missing (%)55.0%
Memory size9.0 KiB
2023-12-12T22:46:14.530568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length526
Median length127
Mean length69.582846
Min length1

Characters and Unicode

Total characters35696
Distinct characters503
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)9.4%

Sample

1st row심폐지구력 및 스피드 운동, 영법교정, 턴, 운동량(1,200~1,500M)
2nd row영법교정 및 턴
3rd row초급,중급 볼링 이론 및 실기 수업
4th row심폐지구력 및 스피드 운동, 영법교정, 턴, 운동량(1,200~1,500M)
5th row개별 진도에 맞게 수업가능합니다.(초급, 중급등)
ValueCountFrequency (%)
427
 
5.4%
및 122
 
1.5%
수 104
 
1.3%
있는 97
 
1.2%
자유형 90
 
1.1%
발차기 88
 
1.1%
등 82
 
1.0%
배영 78
 
1.0%
연결동작 73
 
0.9%
있습니다 72
 
0.9%
Other values (803) 6745
84.5%
2023-12-12T22:46:14.924338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7518
 
21.1%
, 1346
 
3.8%
기 588
 
1.6%
. 485
 
1.4%
동 444
 
1.2%
다 416
 
1.2%
0 405
 
1.1%
스 392
 
1.1%
을 381
 
1.1%
수 358
 
1.0%
Other values (493) 23363
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22256
62.3%
Space Separator 7518
 
21.1%
Other Punctuation 2151
 
6.0%
Lowercase Letter 1362
 
3.8%
Decimal Number 1042
 
2.9%
Math Symbol 361
 
1.0%
Uppercase Letter 344
 
1.0%
Dash Punctuation 323
 
0.9%
Open Punctuation 156
 
0.4%
Close Punctuation 156
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 588
 
2.6%
동 444
 
2.0%
다 416
 
1.9%
스 392
 
1.8%
을 381
 
1.7%
수 358
 
1.6%
니 338
 
1.5%
영 320
 
1.4%
력 301
 
1.4%
로 292
 
1.3%
Other values (424) 18426
82.8%
Lowercase Letter
ValueCountFrequency (%)
r 144
10.6%
n 129
 
9.5%
e 128
 
9.4%
u 115
 
8.4%
o 112
 
8.2%
l 90
 
6.6%
a 85
 
6.2%
i 81
 
5.9%
h 74
 
5.4%
t 64
 
4.7%
Other values (12) 340
25.0%
Uppercase Letter
ValueCountFrequency (%)
C 66
19.2%
A 36
10.5%
P 32
9.3%
M 28
 
8.1%
U 20
 
5.8%
H 18
 
5.2%
F 17
 
4.9%
D 16
 
4.7%
R 16
 
4.7%
V 16
 
4.7%
Other values (9) 79
23.0%
Decimal Number
ValueCountFrequency (%)
0 405
38.9%
1 216
20.7%
2 145
 
13.9%
8 62
 
6.0%
3 60
 
5.8%
6 54
 
5.2%
7 43
 
4.1%
5 23
 
2.2%
4 20
 
1.9%
9 14
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 1346
62.6%
. 485
 
22.5%
: 202
 
9.4%
& 51
 
2.4%
* 21
 
1.0%
# 18
 
0.8%
; 16
 
0.7%
/ 8
 
0.4%
! 4
 
0.2%
Math Symbol
ValueCountFrequency (%)
> 240
66.5%
~ 118
32.7%
+ 3
 
0.8%
Other Symbol
ValueCountFrequency (%)
● 24
88.9%
ⓡ 3
 
11.1%
Space Separator
ValueCountFrequency (%)
7518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 323
100.0%
Open Punctuation
ValueCountFrequency (%)
( 156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22256
62.3%
Common 11734
32.9%
Latin 1706
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 588
 
2.6%
동 444
 
2.0%
다 416
 
1.9%
스 392
 
1.8%
을 381
 
1.7%
수 358
 
1.6%
니 338
 
1.5%
영 320
 
1.4%
력 301
 
1.4%
로 292
 
1.3%
Other values (424) 18426
82.8%
Latin
ValueCountFrequency (%)
r 144
 
8.4%
n 129
 
7.6%
e 128
 
7.5%
u 115
 
6.7%
o 112
 
6.6%
l 90
 
5.3%
a 85
 
5.0%
i 81
 
4.7%
h 74
 
4.3%
C 66
 
3.9%
Other values (31) 682
40.0%
Common
ValueCountFrequency (%)
7518
64.1%
, 1346
 
11.5%
. 485
 
4.1%
0 405
 
3.5%
- 323
 
2.8%
> 240
 
2.0%
1 216
 
1.8%
: 202
 
1.7%
( 156
 
1.3%
) 156
 
1.3%
Other values (18) 687
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22256
62.3%
ASCII 13413
37.6%
Geometric Shapes 24
 
0.1%
Enclosed Alphanum 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7518
56.1%
, 1346
 
10.0%
. 485
 
3.6%
0 405
 
3.0%
- 323
 
2.4%
> 240
 
1.8%
1 216
 
1.6%
: 202
 
1.5%
( 156
 
1.2%
) 156
 
1.2%
Other values (57) 2366
 
17.6%
Hangul
ValueCountFrequency (%)
기 588
 
2.6%
동 444
 
2.0%
다 416
 
1.9%
스 392
 
1.8%
을 381
 
1.7%
수 358
 
1.6%
니 338
 
1.5%
영 320
 
1.4%
력 301
 
1.4%
로 292
 
1.3%
Other values (424) 18426
82.8%
Geometric Shapes
ValueCountFrequency (%)
● 24
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓡ 3
100.0%

강습반개설목적
Text

MISSING 

Distinct81
Distinct (%)8.9%
Missing226
Missing (%)19.8%
Memory size9.0 KiB
2023-12-12T22:46:15.468196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length3.3340635
Min length2

Characters and Unicode

Total characters3044
Distinct characters73
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)4.9%

Sample

1st row성인
2nd row성인
3rd row초등생
4th row어린이
5th row중,고생
ValueCountFrequency (%)
성인 226
23.1%
청소년 186
19.0%
어린이 179
18.3%
실버 79
 
8.1%
7세 35
 
3.6%
노인 34
 
3.5%
유아 26
 
2.7%
통합 21
 
2.1%
수업 21
 
2.1%
초등생~성인 12
 
1.2%
Other values (78) 158
16.2%
2023-12-12T22:46:15.867546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 333
 
10.9%
성 284
 
9.3%
년 222
 
7.3%
소 217
 
7.1%
청 210
 
6.9%
이 197
 
6.5%
어 192
 
6.3%
린 192
 
6.3%
실 95
 
3.1%
버 95
 
3.1%
Other values (63) 1007
33.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2669
87.7%
Other Punctuation 107
 
3.5%
Decimal Number 98
 
3.2%
Space Separator 64
 
2.1%
Math Symbol 41
 
1.3%
Open Punctuation 29
 
1.0%
Close Punctuation 28
 
0.9%
Dash Punctuation 8
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 333
12.5%
성 284
10.6%
년 222
 
8.3%
소 217
 
8.1%
청 210
 
7.9%
이 197
 
7.4%
어 192
 
7.2%
린 192
 
7.2%
실 95
 
3.6%
버 95
 
3.6%
Other values (47) 632
23.7%
Decimal Number
ValueCountFrequency (%)
7 47
48.0%
6 16
 
16.3%
3 11
 
11.2%
1 7
 
7.1%
4 6
 
6.1%
8 4
 
4.1%
2 4
 
4.1%
0 3
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 81
75.7%
. 18
 
16.8%
/ 8
 
7.5%
Space Separator
ValueCountFrequency (%)
64
100.0%
Math Symbol
ValueCountFrequency (%)
~ 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2669
87.7%
Common 375
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 333
12.5%
성 284
10.6%
년 222
 
8.3%
소 217
 
8.1%
청 210
 
7.9%
이 197
 
7.4%
어 192
 
7.2%
린 192
 
7.2%
실 95
 
3.6%
버 95
 
3.6%
Other values (47) 632
23.7%
Common
ValueCountFrequency (%)
, 81
21.6%
64
17.1%
7 47
12.5%
~ 41
10.9%
( 29
 
7.7%
) 28
 
7.5%
. 18
 
4.8%
6 16
 
4.3%
3 11
 
2.9%
- 8
 
2.1%
Other values (6) 32
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2669
87.7%
ASCII 375
 
12.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 333
12.5%
성 284
10.6%
년 222
 
8.3%
소 217
 
8.1%
청 210
 
7.9%
이 197
 
7.4%
어 192
 
7.2%
린 192
 
7.2%
실 95
 
3.6%
버 95
 
3.6%
Other values (47) 632
23.7%
ASCII
ValueCountFrequency (%)
, 81
21.6%
64
17.1%
7 47
12.5%
~ 41
10.9%
( 29
 
7.7%
) 28
 
7.5%
. 18
 
4.8%
6 16
 
4.3%
3 11
 
2.9%
- 8
 
2.1%
Other values (6) 32
 
8.5%

시작나이
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)3.3%
Missing280
Missing (%)24.6%
Infinite0
Infinite (%)0.0%
Mean19.247963
Minimum0
Maximum69
Zeros7
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T22:46:15.995934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q16
median12
Q325
95-th percentile65
Maximum69
Range69
Interquartile range (IQR)19

Descriptive statistics

Standard deviation18.697263
Coefficient of variation (CV)0.97138917
Kurtosis1.6108231
Mean19.247963
Median Absolute Deviation (MAD)7
Skewness1.680114
Sum16534
Variance349.58763
MonotonicityNot monotonic
2023-12-12T22:46:16.163147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
12 190
16.7%
25 157
13.8%
6 110
 
9.7%
65 98
 
8.6%
5 95
 
8.3%
14 34
 
3.0%
13 28
 
2.5%
4 26
 
2.3%
7 15
 
1.3%
8 14
 
1.2%
Other values (18) 92
 
8.1%
(Missing) 280
24.6%
ValueCountFrequency (%)
0 7
 
0.6%
1 8
 
0.7%
2 2
 
0.2%
3 3
 
0.3%
4 26
 
2.3%
5 95
8.3%
6 110
9.7%
7 15
 
1.3%
8 14
 
1.2%
9 7
 
0.6%
ValueCountFrequency (%)
69 3
 
0.3%
66 1
 
0.1%
65 98
8.6%
64 2
 
0.2%
55 5
 
0.4%
25 157
13.8%
24 7
 
0.6%
23 1
 
0.1%
20 5
 
0.4%
19 13
 
1.1%

종료나이
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)4.1%
Missing280
Missing (%)24.6%
Infinite0
Infinite (%)0.0%
Mean46.342258
Minimum3
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T22:46:16.333432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile11.9
Q113
median24
Q364
95-th percentile100
Maximum1000
Range997
Interquartile range (IQR)51

Descriptive statistics

Standard deviation45.723954
Coefficient of variation (CV)0.98665786
Kurtosis219.49205
Mean46.342258
Median Absolute Deviation (MAD)17
Skewness10.706082
Sum39808
Variance2090.6799
MonotonicityNot monotonic
2023-12-12T22:46:16.457762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
64 181
15.9%
24 171
15.0%
100 109
 
9.6%
12 93
 
8.2%
13 83
 
7.3%
7 29
 
2.5%
80 22
 
1.9%
60 22
 
1.9%
14 19
 
1.7%
65 19
 
1.7%
Other values (25) 111
 
9.7%
(Missing) 280
24.6%
ValueCountFrequency (%)
3 1
 
0.1%
4 4
 
0.4%
5 2
 
0.2%
6 2
 
0.2%
7 29
 
2.5%
8 1
 
0.1%
9 2
 
0.2%
11 2
 
0.2%
12 93
8.2%
13 83
7.3%
ValueCountFrequency (%)
1000 1
 
0.1%
100 109
9.6%
99 6
 
0.5%
90 11
 
1.0%
85 14
 
1.2%
80 22
 
1.9%
75 4
 
0.4%
71 1
 
0.1%
70 13
 
1.1%
69 2
 
0.2%

어린이강좌유무
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
False
1139 
ValueCountFrequency (%)
False 1139
100.0%
2023-12-12T22:46:16.548097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

웹보임유무
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
True
695 
False
444 
ValueCountFrequency (%)
True 695
61.0%
False 444
39.0%
2023-12-12T22:46:16.631598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

사용유무
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
True
1139 
ValueCountFrequency (%)
True 1139
100.0%
2023-12-12T22:46:16.704517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

작성일
Date

Distinct380
Distinct (%)33.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
Minimum2006-06-14 00:00:00
Maximum2022-07-19 00:00:00
2023-12-12T22:46:16.810995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:46:16.966198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일
Date

Distinct35
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
Minimum2020-01-16 00:00:00
Maximum2022-08-01 00:00:00
2023-12-12T22:46:17.107104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:46:17.235815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

강좌상세정보
Text

MISSING 

Distinct127
Distinct (%)19.7%
Missing495
Missing (%)43.5%
Memory size9.0 KiB
2023-12-12T22:46:17.488032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length570
Median length273
Mean length123.00311
Min length2

Characters and Unicode

Total characters79214
Distinct characters672
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)5.9%

Sample

1st row자유형, 배영, 평영, 접영, 오리발 수영
2nd row자유형, 배영, 평영, 접영, 오리발 수영
3rd row필라테스는 1900년대 초 조셉 필라테스(독일, 1880-1967)에 의해 고안된 바디컨디셔닝 메소드로 통증을 유발시키지 않으면서 강한 운동을 할 수 있어 과도한 죄식생활과 컴퓨터 사용, 운동부족 등으로 나타날 수 있는 자세 불균형, 척추 측만증, 일자목 증후군, 비만 등을 해소시킬 수 있는 최고의 운동이라 하겠습니다. 또한 필라테스는 매트에서의 여러 가지 동작과 짐볼, 매직써클 등의 보조도구를 이용하는 다양한 동작으로 구성되어 있어 몸의 긴장 완화와 동시에 길고 매끈한 근육들의 생성, 유연성 향상, 몸의 균형을 증진시키고 복부의 깊은 근육들을 훈런하여 요통 개선과 예방에 효과적입니다.
4th row본 강습은 강습첫날 지도자와의 테스트를 통하여 진도 별 강습이 이루어집니다.
5th row자유형, 배영, 평영, 접영, 오리발 수영
ValueCountFrequency (%)
수 399
 
2.3%
및 204
 
1.2%
147
 
0.8%
있습니다 139
 
0.8%
있는 137
 
0.8%
있도록 122
 
0.7%
따라 121
 
0.7%
체력 117
 
0.7%
자유형 107
 
0.6%
있다 106
 
0.6%
Other values (1837) 16062
90.9%
2023-12-12T22:46:17.886896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17325
 
21.9%
이 1367
 
1.7%
는 1306
 
1.6%
을 1203
 
1.5%
다 1184
 
1.5%
의 1127
 
1.4%
, 1109
 
1.4%
에 1032
 
1.3%
. 1002
 
1.3%
로 964
 
1.2%
Other values (662) 51595
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55296
69.8%
Space Separator 17325
 
21.9%
Other Punctuation 2765
 
3.5%
Decimal Number 1898
 
2.4%
Lowercase Letter 712
 
0.9%
Close Punctuation 296
 
0.4%
Open Punctuation 296
 
0.4%
Dash Punctuation 257
 
0.3%
Uppercase Letter 147
 
0.2%
Math Symbol 102
 
0.1%
Other values (4) 120
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1367
 
2.5%
는 1306
 
2.4%
을 1203
 
2.2%
다 1184
 
2.1%
의 1127
 
2.0%
에 1032
 
1.9%
로 964
 
1.7%
가 885
 
1.6%
기 870
 
1.6%
하 815
 
1.5%
Other values (589) 44543
80.6%
Lowercase Letter
ValueCountFrequency (%)
l 101
14.2%
a 100
14.0%
e 98
13.8%
r 66
9.3%
b 54
 
7.6%
o 44
 
6.2%
t 36
 
5.1%
u 30
 
4.2%
i 25
 
3.5%
g 22
 
3.1%
Other values (13) 136
19.1%
Uppercase Letter
ValueCountFrequency (%)
P 28
19.0%
B 22
15.0%
T 20
13.6%
V 12
8.2%
S 11
 
7.5%
Z 9
 
6.1%
Y 9
 
6.1%
A 8
 
5.4%
E 8
 
5.4%
N 8
 
5.4%
Other values (4) 12
8.2%
Other Punctuation
ValueCountFrequency (%)
, 1109
40.1%
. 1002
36.2%
: 352
 
12.7%
※ 115
 
4.2%
/ 113
 
4.1%
* 20
 
0.7%
" 14
 
0.5%
' 13
 
0.5%
· 10
 
0.4%
＊ 9
 
0.3%
Other values (2) 8
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 644
33.9%
0 558
29.4%
2 217
 
11.4%
3 188
 
9.9%
9 94
 
5.0%
5 72
 
3.8%
6 58
 
3.1%
8 42
 
2.2%
7 21
 
1.1%
4 4
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 80
78.4%
> 9
 
8.8%
< 9
 
8.8%
→ 4
 
3.9%
Final Punctuation
ValueCountFrequency (%)
” 32
58.2%
’ 23
41.8%
Initial Punctuation
ValueCountFrequency (%)
“ 32
58.2%
‘ 23
41.8%
Space Separator
ValueCountFrequency (%)
17325
100.0%
Close Punctuation
ValueCountFrequency (%)
) 296
100.0%
Open Punctuation
ValueCountFrequency (%)
( 296
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 257
100.0%
Other Symbol
ValueCountFrequency (%)
ⓡ 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55241
69.7%
Common 23059
29.1%
Latin 859
 
1.1%
Han 55
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1367
 
2.5%
는 1306
 
2.4%
을 1203
 
2.2%
다 1184
 
2.1%
의 1127
 
2.0%
에 1032
 
1.9%
로 964
 
1.7%
가 885
 
1.6%
기 870
 
1.6%
하 815
 
1.5%
Other values (570) 44488
80.5%
Latin
ValueCountFrequency (%)
l 101
 
11.8%
a 100
 
11.6%
e 98
 
11.4%
r 66
 
7.7%
b 54
 
6.3%
o 44
 
5.1%
t 36
 
4.2%
u 30
 
3.5%
P 28
 
3.3%
i 25
 
2.9%
Other values (27) 277
32.2%
Common
ValueCountFrequency (%)
17325
75.1%
, 1109
 
4.8%
. 1002
 
4.3%
1 644
 
2.8%
0 558
 
2.4%
: 352
 
1.5%
) 296
 
1.3%
( 296
 
1.3%
- 257
 
1.1%
2 217
 
0.9%
Other values (26) 1003
 
4.3%
Han
ValueCountFrequency (%)
體 10
18.2%
一 6
10.9%
三 4
 
7.3%
道 4
 
7.3%
位 4
 
7.3%
健 4
 
7.3%
康 4
 
7.3%
禮 2
 
3.6%
節 2
 
3.6%
修 2
 
3.6%
Other values (9) 13
23.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55236
69.7%
ASCII 23664
29.9%
Punctuation 225
 
0.3%
CJK 55
 
0.1%
None 19
 
< 0.1%
Enclosed Alphanum 6
 
< 0.1%
Compat Jamo 5
 
< 0.1%
Arrows 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17325
73.2%
, 1109
 
4.7%
. 1002
 
4.2%
1 644
 
2.7%
0 558
 
2.4%
: 352
 
1.5%
) 296
 
1.3%
( 296
 
1.3%
- 257
 
1.1%
2 217
 
0.9%
Other values (54) 1608
 
6.8%
Hangul
ValueCountFrequency (%)
이 1367
 
2.5%
는 1306
 
2.4%
을 1203
 
2.2%
다 1184
 
2.1%
의 1127
 
2.0%
에 1032
 
1.9%
로 964
 
1.7%
가 885
 
1.6%
기 870
 
1.6%
하 815
 
1.5%
Other values (567) 44483
80.5%
Punctuation
ValueCountFrequency (%)
※ 115
51.1%
” 32
 
14.2%
“ 32
 
14.2%
‘ 23
 
10.2%
’ 23
 
10.2%
CJK
ValueCountFrequency (%)
體 10
18.2%
一 6
10.9%
三 4
 
7.3%
道 4
 
7.3%
位 4
 
7.3%
健 4
 
7.3%
康 4
 
7.3%
禮 2
 
3.6%
節 2
 
3.6%
修 2
 
3.6%
Other values (9) 13
23.6%
None
ValueCountFrequency (%)
· 10
52.6%
＊ 9
47.4%
Enclosed Alphanum
ValueCountFrequency (%)
ⓡ 6
100.0%
Arrows
ValueCountFrequency (%)
→ 4
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅊ 2
40.0%
ㅤ 2
40.0%
ㅏ 1
20.0%

강좌준비물
Text

MISSING 

Distinct88
Distinct (%)14.2%
Missing520
Missing (%)45.7%
Memory size9.0 KiB
2023-12-12T22:46:18.126328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length25
Mean length16.516963
Min length3

Characters and Unicode

Total characters10224
Distinct characters146
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)5.0%

Sample

1st row수영복, 수영모자, 물안경, 개인세면도구, 수건
2nd row수영복, 수영모자, 물안경, 개인세면도구, 수건
3rd row수영복, 수영모자, 물안경, 세면도구
4th row수영복, 수영모자, 물안경, 개인세면도구, 수건
5th row실내전용운동화,운동복,줄넘기줄
ValueCountFrequency (%)
수건 184
 
11.2%
수영복 147
 
9.0%
수영모자 147
 
9.0%
개인세면도구 146
 
8.9%
물안경 135
 
8.2%
운동복,실내전용운동화,수건 83
 
5.1%
운동복 72
 
4.4%
실내전용운동화 50
 
3.0%
스케이트,안전헬멧,장갑 36
 
2.2%
편한복장 32
 
2.0%
Other values (108) 609
37.1%
2023-12-12T22:46:18.480968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 1346
 
13.2%
1022
 
10.0%
수 633
 
6.2%
복 489
 
4.8%
동 466
 
4.6%
운 466
 
4.6%
영 325
 
3.2%
건 293
 
2.9%
화 253
 
2.5%
내 242
 
2.4%
Other values (136) 4689
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7793
76.2%
Other Punctuation 1352
 
13.2%
Space Separator 1022
 
10.0%
Open Punctuation 24
 
0.2%
Close Punctuation 24
 
0.2%
Modifier Symbol 6
 
0.1%
Decimal Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 633
 
8.1%
복 489
 
6.3%
동 466
 
6.0%
운 466
 
6.0%
영 325
 
4.2%
건 293
 
3.8%
화 253
 
3.2%
내 242
 
3.1%
실 242
 
3.1%
전 238
 
3.1%
Other values (129) 4146
53.2%
Other Punctuation
ValueCountFrequency (%)
, 1346
99.6%
. 6
 
0.4%
Space Separator
ValueCountFrequency (%)
1022
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 6
100.0%
Decimal Number
ValueCountFrequency (%)
2 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7793
76.2%
Common 2431
 
23.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 633
 
8.1%
복 489
 
6.3%
동 466
 
6.0%
운 466
 
6.0%
영 325
 
4.2%
건 293
 
3.8%
화 253
 
3.2%
내 242
 
3.1%
실 242
 
3.1%
전 238
 
3.1%
Other values (129) 4146
53.2%
Common
ValueCountFrequency (%)
, 1346
55.4%
1022
42.0%
( 24
 
1.0%
) 24
 
1.0%
^ 6
 
0.2%
. 6
 
0.2%
2 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7793
76.2%
ASCII 2431
 
23.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 1346
55.4%
1022
42.0%
( 24
 
1.0%
) 24
 
1.0%
^ 6
 
0.2%
. 6
 
0.2%
2 3
 
0.1%
Hangul
ValueCountFrequency (%)
수 633
 
8.1%
복 489
 
6.3%
동 466
 
6.0%
운 466
 
6.0%
영 325
 
4.2%
건 293
 
3.8%
화 253
 
3.2%
내 242
 
3.1%
실 242
 
3.1%
전 238
 
3.1%
Other values (129) 4146
53.2%

강습반관련연락처
Categorical

IMBALANCE 

Distinct29
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
498 
02-500-1112
459 
02-509-7700
 
25
02-500-1430
 
25
02-500-1320
 
22
Other values (24)
110 

Length

Max length17
Median length11
Mean length7.95259
Min length2

Unique

Unique9 ?
Unique (%)0.8%

Sample

1st row02-500-1112
2nd row02)500-1112
3rd row02-500-1112
4th row02-500-1112
5th row02-500-1370

Common Values

ValueCountFrequency (%)
<NA> 498
43.7%
02-500-1112 459
40.3%
02-509-7700 25
 
2.2%
02-500-1430 25
 
2.2%
02-500-1320 22
 
1.9%
02)500-1112 22
 
1.9%
02)504-7300 22
 
1.9%
02-500-1113 11
 
1.0%
02-500-1370 11
 
1.0%
02-500-1213 7
 
0.6%
Other values (19) 37
 
3.2%

Length

2023-12-12T22:46:18.616514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 498
43.7%
02-500-1112 459
40.3%
02-509-7700 25
 
2.2%
02-500-1430 25
 
2.2%
02-500-1320 22
 
1.9%
02)500-1112 22
 
1.9%
02)504-7300 22
 
1.9%
02-500-1113 11
 
1.0%
02-500-1370 11
 
1.0%
02-500-1213 7
 
0.6%
Other values (19) 37
 
3.2%

강좌할인구분
Boolean

MISSING 

Distinct2
Distinct (%)0.2%
Missing48
Missing (%)4.2%
Memory size2.4 KiB
True
761 
False
330 
(Missing)
 
48
ValueCountFrequency (%)
True 761
66.8%
False 330
29.0%
(Missing) 48
 
4.2%
2023-12-12T22:46:18.731871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

성별구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
A
1106 
F
 
31
M
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowF
2nd rowA
3rd rowA
4th rowA
5th rowA

Common Values

ValueCountFrequency (%)
A 1106
97.1%
F 31
 
2.7%
M 2
 
0.2%

Length

2023-12-12T22:46:18.809488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:46:18.889552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 1106
97.1%
f 31
 
2.7%
m 2
 
0.2%

Sample

강습반명강습등급진도강습반유형강습요일강습시작시간강습종료시간강습정원강습반특이사항강습반개설목적시작나이종료나이어린이강좌유무웹보임유무사용유무작성일수정일강좌상세정보강좌준비물강습반관련연락처강좌할인구분성별구분
0어머니09마스터171581234590095040심폐지구력 및 스피드 운동, 영법교정, 턴, 운동량(1,200~1,500M)성인1464NYY2009-06-242022-07-09자유형, 배영, 평영, 접영, 오리발 수영수영복, 수영모자, 물안경, 개인세면도구, 수건02-500-1112YF
1저녁직장인21교정5136123452100215035영법교정 및 턴성인2564NYY2009-06-262022-07-09자유형, 배영, 평영, 접영, 오리발 수영수영복, 수영모자, 물안경, 개인세면도구, 수건02)500-1112YA
2방특 필라테스(초등생)1112480085010<NA>초등생612NNY2009-07-042022-07-09필라테스는 1900년대 초 조셉 필라테스(독일, 1880-1967)에 의해 고안된 바디컨디셔닝 메소드로 통증을 유발시키지 않으면서 강한 운동을 할 수 있어 과도한 죄식생활과 컴퓨터 사용, 운동부족 등으로 나타날 수 있는 자세 불균형, 척추 측만증, 일자목 증후군, 비만 등을 해소시킬 수 있는 최고의 운동이라 하겠습니다. 또한 필라테스는 매트에서의 여러 가지 동작과 짐볼, 매직써클 등의 보조도구를 이용하는 다양한 동작으로 구성되어 있어 몸의 긴장 완화와 동시에 길고 매끈한 근육들의 생성, 유연성 향상, 몸의 균형을 증진시키고 복부의 깊은 근육들을 훈런하여 요통 개선과 예방에 효과적입니다.<NA>02-500-1112YA
3수영(방특)2차14시 초급(자유형,배영)111123451400145025<NA>어린이612NYY2009-07-042022-07-04본 강습은 강습첫날 지도자와의 테스트를 통하여 진도 별 강습이 이루어집니다.수영복, 수영모자, 물안경, 세면도구02-500-1112YA
4볼링방특14시(중고생)111123451400145015초급,중급 볼링 이론 및 실기 수업중,고생1219NYY2009-07-062022-07-04<NA><NA>02-500-1370YA
5새벽직장인07시마스터(청소년)71581234570075010심폐지구력 및 스피드 운동, 영법교정, 턴, 운동량(1,200~1,500M)청소년1224NYY2009-07-062022-07-09자유형, 배영, 평영, 접영, 오리발 수영수영복, 수영모자, 물안경, 개인세면도구, 수건02-500-1112YA
6줄넘기&학교체육16:30(중등생)1115163017503<NA>중등생1215NYY2009-07-062022-07-09간단한 도구인 줄넘기를 가지고 시간과 장소에 구애받지 않고 누구나 쉽고 안전하게 할 수 있는 운동으로 적당한 점프력과 스트레칭은 관절과 근육이 늘어나고 줄어들기를 반복하여 궁극적으로 성장판을 자극하게 되어 성장기 어린이, 청소년들의 성장을 촉진시키는데 도움이 되고 심장기능 강화에 탁월한 효과가 있다. 또한 스포츠 경기를 응용한 게임활동, 육상활동, 신체표현 활동, 기초체력활동, 전통놀이 등으로 구성된 학교체육은 신체의 바른 성장과 발달 뿐 아니라 아이의 건강하고 활기찬 학교생활에도 일조할 것으로 기대된다.실내전용운동화,운동복,줄넘기줄02-500-1112YA
7성인/기초3(박재갑)16191241900194515개별 진도에 맞게 수업가능합니다.(초급, 중급등)성인2565NYY2009-07-102022-07-11직장인반스케이트,안전헬멧,장갑<NA>YA
8새벽직장인06시 상급(청소년)4105123456006505접영 발차기, 접영 팔돌리기, 접영 연결동작청소년1224NYY2009-07-132022-07-09자유형/배영/평영 숙달, 접영 익히기수영복, 수영모자, 물안경, 개인세면도구, 수건02-500-1112YA
9새벽직장인06연수1(청소년)6147123456006505<NA>청소년1224NNY2009-07-132022-07-27강습 주4회(월,화,목,금)자유수영 주1회(수요일)수요일 자유수영은 강습시간에만 이용가능매주목요일 오리발수업수영복,물안경,개인샤워도구,수건02-500-1112YA
강습반명강습등급진도강습반유형강습요일강습시작시간강습종료시간강습정원강습반특이사항강습반개설목적시작나이종료나이어린이강좌유무웹보임유무사용유무작성일수정일강좌상세정보강좌준비물강습반관련연락처강좌할인구분성별구분
1129배드민턴(원포인트레슨)1113140015005<NA>성인<NA><NA>NYY2022-07-182022-07-20<NA><NA><NA>NA
1130테니스 개인강습(월,목)11114800180020<NA>누구나080NYY2013-02-282020-01-16<NA><NA><NA>NA
1131테니스 야간반(월,수,금)1111352000220010<NA>누구나585NYY2014-03-042021-12-03<NA><NA>02-500-1425NA
1132테니스 개인강습 주1회(수)11136002000100<NA>누구나770NYY2019-04-032020-01-16<NA><NA>02-500-1425NA
1133테니스 개인강습(월,화,목,금)1111245600200030스트레칭단계별 학습 지도 기초 - 스윙, 포핸드 스트로크, 백핸드 중급 - 서브 앤 발리 상급 - 게임지도주부,직장인,학생585NYY2008-10-102020-09-29테니스는 유산소 운동으로 심폐력 증진, 민첩성, 근력강화에 탁월한 운동이며 눈과 손의 협응력 및 정신 단련에도 도움을 주는 운동이다테니스 라켓, 전용운동화02-500-1425~6NA
1134테니스 오전 단체강습(월,목)111141000110010스트레칭단계별 학습 지도 기초 - 스윙, 포핸드 스트로크, 백핸드 중급 - 서브 앤 발리 상급 - 게임지도주부,직장인,학생585NYY2008-10-102020-01-16테니스는 유산소 운동으로 심폐력 증진, 민첩성, 근력강화에 탁월한 운동이며 눈과 손의 협응력 및 정신 단련에도 도움을 주는 운동이다테니스 라켓, 전용운동화02-500-1425~6NA
1135테니스 오후 단체강습(월,목)111141600170010스트레칭단계별 학습 지도 기초 - 스윙, 포핸드 스트로크, 백핸드 중급 - 서브 앤 발리 상급 - 게임지도주부,직장인,학생585NYY2008-10-102020-01-16테니스는 유산소 운동으로 심폐력 증진, 민첩성, 근력강화에 탁월한 운동이며 눈과 손의 협응력 및 정신 단련에도 도움을 주는 운동이다테니스 라켓, 전용운동화02-500-1425~6NA
1136테니스 오전 단체강습(화,금)111251000110010스트레칭단계별 학습 지도 기초 - 스윙, 포핸드 스트로크, 백핸드 중급 - 서브 앤 발리 상급 - 게임지도주부,직장인,학생585NYY2008-10-102020-01-16테니스는 유산소 운동으로 심폐력 증진, 민첩성, 근력강화에 탁월한 운동이며 눈과 손의 협응력 및 정신 단련에도 도움을 주는 운동이다테니스 라켓, 전용운동화02-500-1425~6NA
1137테니스 오후 단체강습(화,금)111251600170010스트레칭단계별 학습 지도 기초 - 스윙, 포핸드 스트로크, 백핸드 중급 - 서브 앤 발리 상급 - 게임지도주부,직장인,학생585NYY2008-10-102020-01-16테니스는 유산소 운동으로 심폐력 증진, 민첩성, 근력강화에 탁월한 운동이며 눈과 손의 협응력 및 정신 단련에도 도움을 주는 운동이다테니스 라켓, 전용운동화02-500-1425~6NA
1138테니스 개인강습(화,금)11125800180020<NA>누구나080NYY2020-01-152020-02-18<NA><NA><NA>NA