Overview

Dataset statistics

Number of variables34
Number of observations100
Missing cells415
Missing cells (%)12.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.0 KiB
Average record size in memory286.3 B

Variable types

Text16
Numeric11
Categorical5
Boolean2

Alerts

aprvl_at has constant value ""Constant
acmd_nmpr_co is highly imbalanced (91.9%)Imbalance
ldgs_psncpa_co is highly imbalanced (89.8%)Imbalance
fond_de is highly imbalanced (89.8%)Imbalance
use_at is highly imbalanced (71.4%)Imbalance
rspnsblty_dept_nm has 78 (78.0%) missing valuesMissing
main_fclty_cn has 92 (92.0%) missing valuesMissing
main_progrm_cn has 93 (93.0%) missing valuesMissing
hmpg_url has 7 (7.0%) missing valuesMissing
signgu_cd has 2 (2.0%) missing valuesMissing
signgu_nm has 2 (2.0%) missing valuesMissing
buld_nm has 19 (19.0%) missing valuesMissing
intrcn_cn has 21 (21.0%) missing valuesMissing
oper_instt_nm has 98 (98.0%) missing valuesMissing
esntl_id has unique valuesUnique
trng_act_fclty_seq_no has unique valuesUnique
fclty_nm has unique valuesUnique
tel_no has unique valuesUnique
area_detail_addr has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:08:57.984509
Analysis finished2023-12-10 10:09:00.213139
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

esntl_id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:09:00.482722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowKCCBSPO20N000000001
2nd rowKCCBSPO20N000000336
3rd rowKCCBSPO20N000000003
4th rowKCCBSPO20N000000004
5th rowKCCBSPO20N000000005
ValueCountFrequency (%)
kccbspo20n000000001 1
 
1.0%
kccbspo20n000000063 1
 
1.0%
kccbspo20n000000074 1
 
1.0%
kccbspo20n000000073 1
 
1.0%
kccbspo20n000000072 1
 
1.0%
kccbspo20n000000071 1
 
1.0%
kccbspo20n000000070 1
 
1.0%
kccbspo20n000000069 1
 
1.0%
kccbspo20n000000068 1
 
1.0%
kccbspo20n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:09:01.105384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 814
42.8%
C 200
 
10.5%
2 118
 
6.2%
K 100
 
5.3%
O 100
 
5.3%
N 100
 
5.3%
P 100
 
5.3%
S 100
 
5.3%
B 100
 
5.3%
3 25
 
1.3%
Other values (7) 143
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
57.9%
Uppercase Letter 800
42.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 814
74.0%
2 118
 
10.7%
3 25
 
2.3%
1 21
 
1.9%
6 21
 
1.9%
7 21
 
1.9%
4 20
 
1.8%
5 20
 
1.8%
9 20
 
1.8%
8 20
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
C 200
25.0%
K 100
12.5%
O 100
12.5%
N 100
12.5%
P 100
12.5%
S 100
12.5%
B 100
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
57.9%
Latin 800
42.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 814
74.0%
2 118
 
10.7%
3 25
 
2.3%
1 21
 
1.9%
6 21
 
1.9%
7 21
 
1.9%
4 20
 
1.8%
5 20
 
1.8%
9 20
 
1.8%
8 20
 
1.8%
Latin
ValueCountFrequency (%)
C 200
25.0%
K 100
12.5%
O 100
12.5%
N 100
12.5%
P 100
12.5%
S 100
12.5%
B 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 814
42.8%
C 200
 
10.5%
2 118
 
6.2%
K 100
 
5.3%
O 100
 
5.3%
N 100
 
5.3%
P 100
 
5.3%
S 100
 
5.3%
B 100
 
5.3%
3 25
 
1.3%
Other values (7) 143
 
7.5%

trng_act_fclty_seq_no
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean421.07
Minimum5
Maximum4924
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:01.363483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile27.7
Q1143
median272.5
Q3406.75
95-th percentile632.1
Maximum4924
Range4919
Interquartile range (IQR)263.75

Descriptive statistics

Standard deviation788.83778
Coefficient of variation (CV)1.8734124
Kurtosis26.933355
Mean421.07
Median Absolute Deviation (MAD)133
Skewness5.1852696
Sum42107
Variance622265.04
MonotonicityNot monotonic
2023-12-10T19:09:01.608724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1
 
1.0%
341 1
 
1.0%
398 1
 
1.0%
393 1
 
1.0%
376 1
 
1.0%
373 1
 
1.0%
372 1
 
1.0%
364 1
 
1.0%
362 1
 
1.0%
361 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
5 1
1.0%
11 1
1.0%
13 1
1.0%
14 1
1.0%
22 1
1.0%
28 1
1.0%
56 1
1.0%
58 1
1.0%
60 1
1.0%
66 1
1.0%
ValueCountFrequency (%)
4924 1
1.0%
4742 1
1.0%
4661 1
1.0%
638 1
1.0%
634 1
1.0%
632 1
1.0%
618 1
1.0%
615 1
1.0%
609 1
1.0%
607 1
1.0%

fclty_seq_no
Real number (ℝ)

Distinct99
Distinct (%)100.0%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean375.58586
Minimum5
Maximum4742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:01.904183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile27.4
Q1142
median269
Q3404.5
95-th percentile619.4
Maximum4742
Range4737
Interquartile range (IQR)262.5

Descriptive statistics

Standard deviation647.7831
Coefficient of variation (CV)1.7247271
Kurtosis40.096711
Mean375.58586
Median Absolute Deviation (MAD)131
Skewness6.1783872
Sum37183
Variance419622.94
MonotonicityNot monotonic
2023-12-10T19:09:02.157054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1
 
1.0%
341 1
 
1.0%
398 1
 
1.0%
393 1
 
1.0%
376 1
 
1.0%
373 1
 
1.0%
372 1
 
1.0%
364 1
 
1.0%
362 1
 
1.0%
361 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
5 1
1.0%
11 1
1.0%
13 1
1.0%
14 1
1.0%
22 1
1.0%
28 1
1.0%
56 1
1.0%
58 1
1.0%
60 1
1.0%
66 1
1.0%
ValueCountFrequency (%)
4742 1
1.0%
4661 1
1.0%
638 1
1.0%
634 1
1.0%
632 1
1.0%
618 1
1.0%
615 1
1.0%
609 1
1.0%
607 1
1.0%
561 1
1.0%

ty_cd
Real number (ℝ)

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49222.21
Minimum44003
Maximum50005
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:02.368580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44003
5-th percentile44003
Q150001
median50001
Q350003
95-th percentile50003
Maximum50005
Range6002
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1904.3302
Coefficient of variation (CV)0.038688433
Kurtosis3.6036134
Mean49222.21
Median Absolute Deviation (MAD)2
Skewness-2.2915612
Sum4922221
Variance3626473.5
MonotonicityNot monotonic
2023-12-10T19:09:02.558510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
50001 41
41.0%
50003 38
38.0%
44003 11
 
11.0%
48004 4
 
4.0%
50002 3
 
3.0%
48003 2
 
2.0%
50005 1
 
1.0%
ValueCountFrequency (%)
44003 11
 
11.0%
48003 2
 
2.0%
48004 4
 
4.0%
50001 41
41.0%
50002 3
 
3.0%
50003 38
38.0%
50005 1
 
1.0%
ValueCountFrequency (%)
50005 1
 
1.0%
50003 38
38.0%
50002 3
 
3.0%
50001 41
41.0%
48004 4
 
4.0%
48003 2
 
2.0%
44003 11
 
11.0%

ty_nm
Categorical

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
수련관
41 
문화의집
38 
진흥센터
11 
종교기관
 
4
수련원
 
3
Other values (2)
 
3

Length

Max length5
Median length4
Mean length3.58
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row문화의집
2nd row문화의집
3rd row수련원
4th row수련원
5th row수련관

Common Values

ValueCountFrequency (%)
수련관 41
41.0%
문화의집 38
38.0%
진흥센터 11
 
11.0%
종교기관 4
 
4.0%
수련원 3
 
3.0%
비영리법인 2
 
2.0%
특화시설 1
 
1.0%

Length

2023-12-10T19:09:02.823493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:03.071351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수련관 41
41.0%
문화의집 38
38.0%
진흥센터 11
 
11.0%
종교기관 4
 
4.0%
수련원 3
 
3.0%
비영리법인 2
 
2.0%
특화시설 1
 
1.0%

rspnsblty_dept_nm
Text

MISSING 

Distinct17
Distinct (%)77.3%
Missing78
Missing (%)78.0%
Memory size932.0 B
2023-12-10T19:09:03.479306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.9545455
Min length2

Characters and Unicode

Total characters109
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)68.2%

Sample

1st row활동운영부
2nd row복지팀
3rd row청소년사업팀
4th row청소년사업팀
5th row청소년사업팀
ValueCountFrequency (%)
청소년사업팀 4
18.2%
청소년활동팀 3
13.6%
청소년활동지원팀 1
 
4.5%
당동청소년팀 1
 
4.5%
rcy본부 1
 
4.5%
지도부 1
 
4.5%
문화사업팀 1
 
4.5%
수련팀 1
 
4.5%
참여활동팀 1
 
4.5%
활동운영부 1
 
4.5%
Other values (7) 7
31.8%
2023-12-10T19:09:04.114799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
13.8%
9
 
8.3%
9
 
8.3%
9
 
8.3%
9
 
8.3%
8
 
7.3%
6
 
5.5%
6
 
5.5%
4
 
3.7%
3
 
2.8%
Other values (26) 31
28.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 106
97.2%
Uppercase Letter 3
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15
14.2%
9
 
8.5%
9
 
8.5%
9
 
8.5%
9
 
8.5%
8
 
7.5%
6
 
5.7%
6
 
5.7%
4
 
3.8%
3
 
2.8%
Other values (23) 28
26.4%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
R 1
33.3%
Y 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 106
97.2%
Latin 3
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
15
14.2%
9
 
8.5%
9
 
8.5%
9
 
8.5%
9
 
8.5%
8
 
7.5%
6
 
5.7%
6
 
5.7%
4
 
3.8%
3
 
2.8%
Other values (23) 28
26.4%
Latin
ValueCountFrequency (%)
C 1
33.3%
R 1
33.3%
Y 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 106
97.2%
ASCII 3
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
15
14.2%
9
 
8.5%
9
 
8.5%
9
 
8.5%
9
 
8.5%
8
 
7.5%
6
 
5.7%
6
 
5.7%
4
 
3.8%
3
 
2.8%
Other values (23) 28
26.4%
ASCII
ValueCountFrequency (%)
C 1
33.3%
R 1
33.3%
Y 1
33.3%

main_fclty_cn
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing92
Missing (%)92.0%
Memory size932.0 B
2023-12-10T19:09:04.379994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length479
Median length98.5
Mean length130.75
Min length17

Characters and Unicode

Total characters1046
Distinct characters203
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st rowㅇ시설규모 : 1,329.26㎡ ㅇ지하1층 -다목적홀 : 공연 및 영화관람, 프로젠테이션- 좌석 100석, 프로젝터 -소회의실 : 회의 및 수업 등 -포켓볼실 : 포켓볼 이용, 포켓볼 1대 -동아리실 : 동아리 회의 시 활용 ㅇ지상1층 -멀티인터넷실 : PC이용 및 컴퓨터 수업, PC 16대, DVD 및 오디오 시설 -열린자료실 : DVD 및 비디오 시청 -정보서비스실 : 도서열람 교양도서 외 약 5,000여권 -사무실/안내데스크 : 안내 및 사무업무 ㅇ지상 2층 -다용도활동실 : 댄스 수업 및 동아리 댄스연습,전면거울 및 강화마루 -문화창작실 : 좌식이 요구되는 수업 및 안부연습, 전면거울 -음악활동실 : 밴드 및 노래연습, 바이올린 등 악기연주 수업 반주기기, 드럼, 키보드, 싱어엠프, 기타엠프 100W금 3개 -탁구장 : 탁구이용, 탁구대 1대 -사랑방 : 회의, 청소년 개인 및 집단상담 등
2nd row체육관, 샤워실, 공연장, 녹음스튜디오, 영상편집실, 작은도서관, 촬영스튜디오, 방과후아카데미, 헬스장, 동아리실, 컨텐츠아카데미실, 상담실, 이야기나눔방, 청소년운영위원회실, 청소년문화놀이터(탁구장, 포켓볼장, DVD룸), 쿠킹실, 밴드실, 춤터 등
3rd row공연장(250석),체육관(농구코트규모),댄스연습실(2실),음악연습실,어울마당,책방,당구장,프로그램실,성문화체험관,특별활동실,프로그램실,동아리방
4th row댄스스튜디오, 강의실, 헬스장, 수영장, 소극장, 세미나실 등등
5th row1. 동아리 이용시실 - 음악연습실, 공연연습실, 다목적홀, 유스카페 2. 청소년희망디자인공간 - 열린도서실, 사이버공간, 노래연습실 3. 청소년자치공간 4. 다목적무대 5. 작품전기공간 등
ValueCountFrequency (%)
17
 
8.9%
11
 
5.8%
6
 
3.2%
수업 5
 
2.6%
동아리 3
 
1.6%
회의 3
 
1.6%
공연연습실 3
 
1.6%
노래연습실 2
 
1.1%
음악연습실 2
 
1.1%
dvd 2
 
1.1%
Other values (130) 136
71.6%
2023-12-10T19:09:04.865517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
223
 
21.3%
, 73
 
7.0%
40
 
3.8%
21
 
2.0%
: 19
 
1.8%
0 18
 
1.7%
- 17
 
1.6%
14
 
1.3%
1 14
 
1.3%
13
 
1.2%
Other values (193) 594
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 628
60.0%
Space Separator 223
 
21.3%
Other Punctuation 99
 
9.5%
Decimal Number 51
 
4.9%
Dash Punctuation 17
 
1.6%
Uppercase Letter 14
 
1.3%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%
Math Symbol 3
 
0.3%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
40
 
6.4%
21
 
3.3%
14
 
2.2%
13
 
2.1%
12
 
1.9%
12
 
1.9%
12
 
1.9%
11
 
1.8%
11
 
1.8%
10
 
1.6%
Other values (170) 472
75.2%
Decimal Number
ValueCountFrequency (%)
0 18
35.3%
1 14
27.5%
2 8
15.7%
5 3
 
5.9%
3 3
 
5.9%
9 2
 
3.9%
6 2
 
3.9%
4 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
D 6
42.9%
V 3
21.4%
P 2
 
14.3%
C 2
 
14.3%
W 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 73
73.7%
: 19
 
19.2%
. 6
 
6.1%
/ 1
 
1.0%
Space Separator
ValueCountFrequency (%)
223
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 628
60.0%
Common 404
38.6%
Latin 14
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
40
 
6.4%
21
 
3.3%
14
 
2.2%
13
 
2.1%
12
 
1.9%
12
 
1.9%
12
 
1.9%
11
 
1.8%
11
 
1.8%
10
 
1.6%
Other values (170) 472
75.2%
Common
ValueCountFrequency (%)
223
55.2%
, 73
 
18.1%
: 19
 
4.7%
0 18
 
4.5%
- 17
 
4.2%
1 14
 
3.5%
2 8
 
2.0%
. 6
 
1.5%
) 5
 
1.2%
( 5
 
1.2%
Other values (8) 16
 
4.0%
Latin
ValueCountFrequency (%)
D 6
42.9%
V 3
21.4%
P 2
 
14.3%
C 2
 
14.3%
W 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 624
59.7%
ASCII 417
39.9%
Compat Jamo 4
 
0.4%
CJK Compat 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
223
53.5%
, 73
 
17.5%
: 19
 
4.6%
0 18
 
4.3%
- 17
 
4.1%
1 14
 
3.4%
2 8
 
1.9%
D 6
 
1.4%
. 6
 
1.4%
) 5
 
1.2%
Other values (12) 28
 
6.7%
Hangul
ValueCountFrequency (%)
40
 
6.4%
21
 
3.4%
14
 
2.2%
13
 
2.1%
12
 
1.9%
12
 
1.9%
12
 
1.9%
11
 
1.8%
11
 
1.8%
10
 
1.6%
Other values (169) 468
75.0%
Compat Jamo
ValueCountFrequency (%)
4
100.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%

main_progrm_cn
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing93
Missing (%)93.0%
Memory size932.0 B
2023-12-10T19:09:05.220491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length681
Median length143
Mean length211.42857
Min length33

Characters and Unicode

Total characters1480
Distinct characters250
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

Unique7 ?
Unique (%)100.0%

Sample

1st row-청소년수련활동인증프로그램 운영 -청소년운영위원회 운영 -국제청소년성취포상제 운영 -청소년자기도전포상제 운영 -다양한 체험활동 프로그램 운영 (아낌없이주는 도솔, 우리동네최고, 도솔을 위한 청소년 워크숍, 항공모형 기체험교실 등) -자원봉사프로그램 운영
2nd row미디어 특화사업은 청소년들이 다양한 미디어활동을 통해 소통할 수 있는 축제의 장을 마련하고, 미디어지원을 통해 청소년들의 긍정적 미디어 매체로 활용하도록 장려하는 사업으로 청소년들이 직접 미디어기획, 촬영, 제작 등의 활동을 할 수 있는 인적, 시설 인프라가 구축되어 있습니다. 또한 매년 청소년의 달에 청소년들을 위한 다양한 체험거리 및 볼거리로 건전하고 즐거운 축제의 장을 마련하고 있으ㅡ며, 대인관계 및 가정환경, 학습환경의 변화에 따른 올바른 예방적, 교육적 접을 통해 청소년들의 학교 적응력을 향상시키기 위한 학교연계상담 사업을 진행하고 있으며, 각종 청소년과 관련한 사업을 진행하고 있습니다.
3rd row청소년동아리활동,청소년문화페스티벌,청소년자원봉사,청소년방과후아카데미,영유아프로그램,유아프로그램,초등특강,청소년특강등
4th row청소년활동 프로그램, 교육문화강좌, 체육(수영,헬스)프로그램
5th row1. 청소년자치활동 - 청소년운영위원회 - 청소년기자단 - 청소년동아리 - 청소년희망디자인공간 - 청소년참여예산 2. 문화교육활동 - 동네프로젝트 - 문화아카데미 3. 연대교류활동 - 학생회지원사업 - 자원봉사활동 - 청소년학술제 4. 외부공모사업 등
ValueCountFrequency (%)
14
 
7.6%
운영 6
 
3.3%
청소년운영위원회 4
 
2.2%
통해 3
 
1.6%
3
 
1.6%
다양한 3
 
1.6%
위한 3
 
1.6%
청소년들의 2
 
1.1%
마련하고 2
 
1.1%
장을 2
 
1.1%
Other values (130) 142
77.2%
2023-12-10T19:09:05.872684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
437
29.5%
41
 
2.8%
40
 
2.7%
- 39
 
2.6%
39
 
2.6%
, 28
 
1.9%
. 25
 
1.7%
23
 
1.6%
) 15
 
1.0%
( 15
 
1.0%
Other values (240) 778
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 804
54.3%
Space Separator 437
29.5%
Other Punctuation 59
 
4.0%
Decimal Number 42
 
2.8%
Dash Punctuation 39
 
2.6%
Lowercase Letter 38
 
2.6%
Uppercase Letter 21
 
1.4%
Close Punctuation 15
 
1.0%
Open Punctuation 15
 
1.0%
Other Symbol 7
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
41
 
5.1%
40
 
5.0%
39
 
4.9%
23
 
2.9%
14
 
1.7%
14
 
1.7%
14
 
1.7%
13
 
1.6%
12
 
1.5%
12
 
1.5%
Other values (192) 582
72.4%
Uppercase Letter
ValueCountFrequency (%)
C 3
14.3%
I 2
 
9.5%
Y 2
 
9.5%
D 1
 
4.8%
G 1
 
4.8%
N 1
 
4.8%
K 1
 
4.8%
L 1
 
4.8%
A 1
 
4.8%
W 1
 
4.8%
Other values (7) 7
33.3%
Lowercase Letter
ValueCountFrequency (%)
n 8
21.1%
o 6
15.8%
i 5
13.2%
a 3
 
7.9%
t 3
 
7.9%
c 3
 
7.9%
e 2
 
5.3%
d 2
 
5.3%
m 2
 
5.3%
r 2
 
5.3%
Other values (2) 2
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 13
31.0%
2 8
19.0%
4 5
 
11.9%
3 4
 
9.5%
9 3
 
7.1%
6 3
 
7.1%
8 3
 
7.1%
5 2
 
4.8%
7 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 28
47.5%
. 25
42.4%
' 5
 
8.5%
/ 1
 
1.7%
Space Separator
ValueCountFrequency (%)
437
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Other Symbol
ValueCountFrequency (%)
7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 804
54.3%
Common 617
41.7%
Latin 59
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
41
 
5.1%
40
 
5.0%
39
 
4.9%
23
 
2.9%
14
 
1.7%
14
 
1.7%
14
 
1.7%
13
 
1.6%
12
 
1.5%
12
 
1.5%
Other values (192) 582
72.4%
Latin
ValueCountFrequency (%)
n 8
 
13.6%
o 6
 
10.2%
i 5
 
8.5%
a 3
 
5.1%
t 3
 
5.1%
c 3
 
5.1%
C 3
 
5.1%
e 2
 
3.4%
d 2
 
3.4%
I 2
 
3.4%
Other values (19) 22
37.3%
Common
ValueCountFrequency (%)
437
70.8%
- 39
 
6.3%
, 28
 
4.5%
. 25
 
4.1%
) 15
 
2.4%
( 15
 
2.4%
1 13
 
2.1%
2 8
 
1.3%
7
 
1.1%
4 5
 
0.8%
Other values (9) 25
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 803
54.3%
ASCII 669
45.2%
Geometric Shapes 7
 
0.5%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
437
65.3%
- 39
 
5.8%
, 28
 
4.2%
. 25
 
3.7%
) 15
 
2.2%
( 15
 
2.2%
1 13
 
1.9%
2 8
 
1.2%
n 8
 
1.2%
o 6
 
0.9%
Other values (37) 75
 
11.2%
Hangul
ValueCountFrequency (%)
41
 
5.1%
40
 
5.0%
39
 
4.9%
23
 
2.9%
14
 
1.7%
14
 
1.7%
14
 
1.7%
13
 
1.6%
12
 
1.5%
12
 
1.5%
Other values (191) 581
72.4%
Geometric Shapes
ValueCountFrequency (%)
7
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

acmd_nmpr_co
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
99 
200
 
1

Length

Max length4
Median length4
Mean length3.99
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 99
99.0%
200 1
 
1.0%

Length

2023-12-10T19:09:06.164751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:06.350811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 99
99.0%
200 1
 
1.0%

ldgs_psncpa_co
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
98 
0
 
1
100
 
1

Length

Max length4
Median length4
Mean length3.96
Min length1

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 98
98.0%
0 1
 
1.0%
100 1
 
1.0%

Length

2023-12-10T19:09:06.535787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:06.724414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
98.0%
0 1
 
1.0%
100 1
 
1.0%

fclty_nm
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:09:07.105595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length10.25
Min length6

Characters and Unicode

Total characters1025
Distinct characters143
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row대구광역시청소년문화의집
2nd row포천청소년문화의집
3rd row국립중앙청소년수련원
4th row국립평창청소년수련원
5th row서울중구청소년수련관
ValueCountFrequency (%)
대구광역시청소년문화의집 1
 
0.9%
완산청소년문화의집 1
 
0.9%
전라북도청소년활동진흥센터 1
 
0.9%
부산광역시청소년활동진흥센터 1
 
0.9%
무주청소년수련관 1
 
0.9%
서울시립문래청소년센터 1
 
0.9%
서귀포시청소년수련관 1
 
0.9%
당동청소년문화의집 1
 
0.9%
보령시청소년문화의집 1
 
0.9%
남목청소년문화의집 1
 
0.9%
Other values (99) 99
90.8%
2023-12-10T19:09:07.814826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93
 
9.1%
93
 
9.1%
92
 
9.0%
44
 
4.3%
43
 
4.2%
38
 
3.7%
37
 
3.6%
36
 
3.5%
35
 
3.4%
33
 
3.2%
Other values (133) 481
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1001
97.7%
Uppercase Letter 11
 
1.1%
Space Separator 9
 
0.9%
Decimal Number 2
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
93
 
9.3%
93
 
9.3%
92
 
9.2%
44
 
4.4%
43
 
4.3%
38
 
3.8%
37
 
3.7%
36
 
3.6%
35
 
3.5%
33
 
3.3%
Other values (122) 457
45.7%
Uppercase Letter
ValueCountFrequency (%)
Y 3
27.3%
C 3
27.3%
A 2
18.2%
W 1
 
9.1%
R 1
 
9.1%
M 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1001
97.7%
Common 13
 
1.3%
Latin 11
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
93
 
9.3%
93
 
9.3%
92
 
9.2%
44
 
4.4%
43
 
4.3%
38
 
3.8%
37
 
3.7%
36
 
3.6%
35
 
3.5%
33
 
3.3%
Other values (122) 457
45.7%
Latin
ValueCountFrequency (%)
Y 3
27.3%
C 3
27.3%
A 2
18.2%
W 1
 
9.1%
R 1
 
9.1%
M 1
 
9.1%
Common
ValueCountFrequency (%)
9
69.2%
) 1
 
7.7%
( 1
 
7.7%
2 1
 
7.7%
1 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1001
97.7%
ASCII 24
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
93
 
9.3%
93
 
9.3%
92
 
9.2%
44
 
4.4%
43
 
4.3%
38
 
3.8%
37
 
3.7%
36
 
3.6%
35
 
3.5%
33
 
3.3%
Other values (122) 457
45.7%
ASCII
ValueCountFrequency (%)
9
37.5%
Y 3
 
12.5%
C 3
 
12.5%
A 2
 
8.3%
W 1
 
4.2%
R 1
 
4.2%
M 1
 
4.2%
) 1
 
4.2%
( 1
 
4.2%
2 1
 
4.2%

tel_no
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:09:08.276071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.89
Min length10

Characters and Unicode

Total characters1189
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

Unique100 ?
Unique (%)100.0%

Sample

1st row053-661-1318
2nd row031-538-3382
3rd row041-620-7700
4th row033-330-0800
5th row02-2250-0500
ValueCountFrequency (%)
053-661-1318 1
 
1.0%
063-226-5193 1
 
1.0%
051-852-3461 1
 
1.0%
063-324-4242 1
 
1.0%
02-2167-0100 1
 
1.0%
064-760-6461 1
 
1.0%
031-390-1470 1
 
1.0%
041-936-2097 1
 
1.0%
052-234-5838 1
 
1.0%
055-711-1355 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:09:09.397918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 196
16.5%
0 188
15.8%
2 127
10.7%
3 124
10.4%
1 107
9.0%
4 100
8.4%
5 97
8.2%
6 78
 
6.6%
7 76
 
6.4%
8 52
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 993
83.5%
Dash Punctuation 196
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 188
18.9%
2 127
12.8%
3 124
12.5%
1 107
10.8%
4 100
10.1%
5 97
9.8%
6 78
7.9%
7 76
7.7%
8 52
 
5.2%
9 44
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1189
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 196
16.5%
0 188
15.8%
2 127
10.7%
3 124
10.4%
1 107
9.0%
4 100
8.4%
5 97
8.2%
6 78
 
6.6%
7 76
 
6.4%
8 52
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1189
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 196
16.5%
0 188
15.8%
2 127
10.7%
3 124
10.4%
1 107
9.0%
4 100
8.4%
5 97
8.2%
6 78
 
6.6%
7 76
 
6.4%
8 52
 
4.4%

hmpg_url
Text

MISSING 

Distinct93
Distinct (%)100.0%
Missing7
Missing (%)7.0%
Memory size932.0 B
2023-12-10T19:09:09.890023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length33
Mean length23.655914
Min length15

Characters and Unicode

Total characters2200
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)100.0%

Sample

1st rowhttp://dg1318.net
2nd rowhttp://youth.pocheon.go.kr/poycc
3rd rowhttp://nyc.kywa.or.kr
4th rowhttps://pnyc.kywa.or.kr
5th rowhttp://j-youth.org
ValueCountFrequency (%)
http://www.sokchosiseol.or.kr 1
 
1.1%
http://cafe.naver.com/dop6220 1
 
1.1%
http://www.youngi.or.kr 1
 
1.1%
http://mullaeyouth.or.kr 1
 
1.1%
http://www.seogwipo.go.kr/youth/index.htm 1
 
1.1%
http://www.ddyouth.or.kr 1
 
1.1%
http://www.dongmuya.or.kr 1
 
1.1%
http://nammok.or.kr 1
 
1.1%
http://gnyouth.net 1
 
1.1%
http://blog.naver.com/astacteen 1
 
1.1%
Other values (83) 83
89.2%
2023-12-10T19:09:10.717521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 251
 
11.4%
. 219
 
10.0%
/ 208
 
9.5%
o 162
 
7.4%
h 141
 
6.4%
r 139
 
6.3%
w 138
 
6.3%
p 106
 
4.8%
: 95
 
4.3%
k 79
 
3.6%
Other values (30) 662
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1592
72.4%
Other Punctuation 522
 
23.7%
Decimal Number 84
 
3.8%
Dash Punctuation 1
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 251
15.8%
o 162
10.2%
h 141
 
8.9%
r 139
 
8.7%
w 138
 
8.7%
p 106
 
6.7%
k 79
 
5.0%
y 78
 
4.9%
u 64
 
4.0%
n 58
 
3.6%
Other values (15) 376
23.6%
Decimal Number
ValueCountFrequency (%)
1 26
31.0%
0 16
19.0%
3 13
15.5%
8 12
14.3%
2 5
 
6.0%
7 5
 
6.0%
4 3
 
3.6%
9 2
 
2.4%
6 1
 
1.2%
5 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 219
42.0%
/ 208
39.8%
: 95
18.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1592
72.4%
Common 608
 
27.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 251
15.8%
o 162
10.2%
h 141
 
8.9%
r 139
 
8.7%
w 138
 
8.7%
p 106
 
6.7%
k 79
 
5.0%
y 78
 
4.9%
u 64
 
4.0%
n 58
 
3.6%
Other values (15) 376
23.6%
Common
ValueCountFrequency (%)
. 219
36.0%
/ 208
34.2%
: 95
15.6%
1 26
 
4.3%
0 16
 
2.6%
3 13
 
2.1%
8 12
 
2.0%
2 5
 
0.8%
7 5
 
0.8%
4 3
 
0.5%
Other values (5) 6
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 251
 
11.4%
. 219
 
10.0%
/ 208
 
9.5%
o 162
 
7.4%
h 141
 
6.4%
r 139
 
6.3%
w 138
 
6.3%
p 106
 
4.8%
: 95
 
4.3%
k 79
 
3.6%
Other values (30) 662
30.1%

ctprvn_cd
Real number (ℝ)

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20007.7
Minimum20001
Maximum20016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:10.994453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001
5-th percentile20001
Q120003
median20008
Q320011.25
95-th percentile20016
Maximum20016
Range15
Interquartile range (IQR)8.25

Descriptive statistics

Standard deviation4.979757
Coefficient of variation (CV)0.00024889203
Kurtosis-1.088651
Mean20007.7
Median Absolute Deviation (MAD)4
Skewness0.17713345
Sum2000770
Variance24.79798
MonotonicityNot monotonic
2023-12-10T19:09:11.216934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
20001 19
19.0%
20008 18
18.0%
20016 9
9.0%
20015 7
 
7.0%
20009 6
 
6.0%
20004 6
 
6.0%
20012 5
 
5.0%
20006 5
 
5.0%
20007 5
 
5.0%
20011 4
 
4.0%
Other values (6) 16
16.0%
ValueCountFrequency (%)
20001 19
19.0%
20002 4
 
4.0%
20003 3
 
3.0%
20004 6
 
6.0%
20005 2
 
2.0%
20006 5
 
5.0%
20007 5
 
5.0%
20008 18
18.0%
20009 6
 
6.0%
20010 3
 
3.0%
ValueCountFrequency (%)
20016 9
9.0%
20015 7
 
7.0%
20014 2
 
2.0%
20013 2
 
2.0%
20012 5
 
5.0%
20011 4
 
4.0%
20010 3
 
3.0%
20009 6
 
6.0%
20008 18
18.0%
20007 5
 
5.0%

ctprvn_nm
Categorical

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
19 
경기도
18 
제주특별자치도
경상남도
강원도
Other values (11)
41 

Length

Max length7
Median length5
Mean length4.47
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시
2nd row경기도
3rd row충청남도
4th row강원도
5th row서울특별시

Common Values

ValueCountFrequency (%)
서울특별시 19
19.0%
경기도 18
18.0%
제주특별자치도 9
9.0%
경상남도 7
 
7.0%
강원도 6
 
6.0%
인천광역시 6
 
6.0%
대전광역시 5
 
5.0%
울산광역시 5
 
5.0%
전라북도 5
 
5.0%
충청남도 4
 
4.0%
Other values (6) 16
16.0%

Length

2023-12-10T19:09:11.484045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 19
19.0%
경기도 18
18.0%
제주특별자치도 9
9.0%
경상남도 7
 
7.0%
강원도 6
 
6.0%
인천광역시 6
 
6.0%
대전광역시 5
 
5.0%
울산광역시 5
 
5.0%
전라북도 5
 
5.0%
충청남도 4
 
4.0%
Other values (6) 16
16.0%

signgu_cd
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)75.5%
Missing2
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean27706
Minimum21001
Maximum36002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:11.709706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21001
5-th percentile21010.55
Q123005.25
median28020
Q331011.25
95-th percentile36001
Maximum36002
Range15001
Interquartile range (IQR)8006

Descriptive statistics

Standard deviation4996.0918
Coefficient of variation (CV)0.18032527
Kurtosis-1.0864581
Mean27706
Median Absolute Deviation (MAD)4012.5
Skewness0.17857073
Sum2715188
Variance24960934
MonotonicityNot monotonic
2023-12-10T19:09:12.169009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36001 5
 
5.0%
36002 4
 
4.0%
35014 3
 
3.0%
28020 3
 
3.0%
26005 3
 
3.0%
24008 2
 
2.0%
21019 2
 
2.0%
21006 2
 
2.0%
27004 2
 
2.0%
32013 2
 
2.0%
Other values (64) 70
70.0%
ValueCountFrequency (%)
21001 1
1.0%
21005 1
1.0%
21006 2
2.0%
21008 1
1.0%
21011 2
2.0%
21012 1
1.0%
21013 1
1.0%
21017 2
2.0%
21019 2
2.0%
21020 2
2.0%
ValueCountFrequency (%)
36002 4
4.0%
36001 5
5.0%
35019 1
 
1.0%
35014 3
3.0%
35009 1
 
1.0%
35004 1
 
1.0%
35003 1
 
1.0%
34011 1
 
1.0%
34007 1
 
1.0%
33018 1
 
1.0%

signgu_nm
Text

MISSING 

Distinct65
Distinct (%)66.3%
Missing2
Missing (%)2.0%
Memory size932.0 B
2023-12-10T19:09:12.613936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.5612245
Min length2

Characters and Unicode

Total characters349
Distinct characters80
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)50.0%

Sample

1st row남구
2nd row포천시
3rd row천안시
4th row평창군
5th row중구
ValueCountFrequency (%)
중구 6
 
5.3%
동구 5
 
4.4%
서귀포시 5
 
4.4%
서구 5
 
4.4%
제주시 4
 
3.5%
성남시 3
 
2.7%
분당구 3
 
2.7%
창원시 3
 
2.7%
마산합포구 3
 
2.7%
전주시 3
 
2.7%
Other values (62) 73
64.6%
2023-12-10T19:09:13.318050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
60
 
17.2%
46
 
13.2%
15
 
4.3%
13
 
3.7%
13
 
3.7%
12
 
3.4%
11
 
3.2%
10
 
2.9%
9
 
2.6%
9
 
2.6%
Other values (70) 151
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 334
95.7%
Space Separator 15
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
60
18.0%
46
 
13.8%
13
 
3.9%
13
 
3.9%
12
 
3.6%
11
 
3.3%
10
 
3.0%
9
 
2.7%
9
 
2.7%
9
 
2.7%
Other values (69) 142
42.5%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 334
95.7%
Common 15
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
60
18.0%
46
 
13.8%
13
 
3.9%
13
 
3.9%
12
 
3.6%
11
 
3.3%
10
 
3.0%
9
 
2.7%
9
 
2.7%
9
 
2.7%
Other values (69) 142
42.5%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 334
95.7%
ASCII 15
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
60
18.0%
46
 
13.8%
13
 
3.9%
13
 
3.9%
12
 
3.6%
11
 
3.3%
10
 
3.0%
9
 
2.7%
9
 
2.7%
9
 
2.7%
Other values (69) 142
42.5%
ASCII
ValueCountFrequency (%)
15
100.0%

zip_no
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39555.07
Minimum2764
Maximum76024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:13.550542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2764
5-th percentile9923.3
Q120747.25
median41069
Q357180
95-th percentile69790
Maximum76024
Range73260
Interquartile range (IQR)36432.75

Descriptive statistics

Standard deviation20342.932
Coefficient of variation (CV)0.51429392
Kurtosis-1.1932762
Mean39555.07
Median Absolute Deviation (MAD)19026.5
Skewness-0.078365565
Sum3955507
Variance4.1383488 × 108
MonotonicityNot monotonic
2023-12-10T19:09:13.833138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69780 2
 
2.0%
42001 1
 
1.0%
60183 1
 
1.0%
56880 1
 
1.0%
15083 1
 
1.0%
63558 1
 
1.0%
15839 1
 
1.0%
35501 1
 
1.0%
68280 1
 
1.0%
51138 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
2764 1
1.0%
4422 1
1.0%
4750 1
1.0%
6650 1
1.0%
7991 1
1.0%
10025 1
1.0%
10045 1
1.0%
11141 1
1.0%
13001 1
1.0%
13123 1
1.0%
ValueCountFrequency (%)
76024 1
1.0%
70581 1
1.0%
70481 1
1.0%
69993 1
1.0%
69980 1
1.0%
69780 2
2.0%
69082 1
1.0%
69080 1
1.0%
68280 1
1.0%
68130 1
1.0%
Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:09:14.438574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length15.92
Min length9

Characters and Unicode

Total characters1592
Distinct characters173
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

Unique98 ?
Unique (%)98.0%

Sample

1st row대구 남구 대명2동
2nd row경기도 포천시 왕방로 169 (신읍동)
3rd row충남 천안시 목천읍 교촌리
4th row강원 평창군 용평면
5th row서울 중구 신당3동
ValueCountFrequency (%)
서울 13
 
3.3%
경기 12
 
3.0%
제주 6
 
1.5%
서울특별시 6
 
1.5%
경기도 6
 
1.5%
중구 6
 
1.5%
서구 5
 
1.3%
동구 5
 
1.3%
경남 5
 
1.3%
서귀포시 4
 
1.0%
Other values (269) 326
82.7%
2023-12-10T19:09:15.487478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
294
 
18.5%
102
 
6.4%
69
 
4.3%
62
 
3.9%
37
 
2.3%
32
 
2.0%
1 31
 
1.9%
30
 
1.9%
30
 
1.9%
29
 
1.8%
Other values (163) 876
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1098
69.0%
Space Separator 294
 
18.5%
Decimal Number 140
 
8.8%
Close Punctuation 28
 
1.8%
Open Punctuation 28
 
1.8%
Dash Punctuation 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
102
 
9.3%
69
 
6.3%
62
 
5.6%
37
 
3.4%
32
 
2.9%
30
 
2.7%
30
 
2.7%
29
 
2.6%
28
 
2.6%
26
 
2.4%
Other values (148) 653
59.5%
Decimal Number
ValueCountFrequency (%)
1 31
22.1%
2 22
15.7%
3 18
12.9%
5 14
10.0%
4 14
10.0%
9 12
 
8.6%
0 10
 
7.1%
6 8
 
5.7%
7 6
 
4.3%
8 5
 
3.6%
Space Separator
ValueCountFrequency (%)
294
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1098
69.0%
Common 494
31.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
102
 
9.3%
69
 
6.3%
62
 
5.6%
37
 
3.4%
32
 
2.9%
30
 
2.7%
30
 
2.7%
29
 
2.6%
28
 
2.6%
26
 
2.4%
Other values (148) 653
59.5%
Common
ValueCountFrequency (%)
294
59.5%
1 31
 
6.3%
) 28
 
5.7%
( 28
 
5.7%
2 22
 
4.5%
3 18
 
3.6%
5 14
 
2.8%
4 14
 
2.8%
9 12
 
2.4%
0 10
 
2.0%
Other values (5) 23
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1098
69.0%
ASCII 494
31.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
294
59.5%
1 31
 
6.3%
) 28
 
5.7%
( 28
 
5.7%
2 22
 
4.5%
3 18
 
3.6%
5 14
 
2.8%
4 14
 
2.8%
9 12
 
2.4%
0 10
 
2.0%
Other values (5) 23
 
4.7%
Hangul
ValueCountFrequency (%)
102
 
9.3%
69
 
6.3%
62
 
5.6%
37
 
3.4%
32
 
2.9%
30
 
2.7%
30
 
2.7%
29
 
2.6%
28
 
2.6%
26
 
2.4%
Other values (148) 653
59.5%

area_detail_addr
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:09:16.339417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length22
Mean length11.43
Min length2

Characters and Unicode

Total characters1143
Distinct characters143
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row1822-2
2nd row포천청소년문화의집
3rd row246-1
4th row새터마을길 108 국립평창청소년수련원
5th row844-5 서울중구청소년수련관
ValueCountFrequency (%)
3층 8
 
4.7%
2층 4
 
2.4%
서울특별시립 2
 
1.2%
1층 2
 
1.2%
4-190 1
 
0.6%
마산ywca 1
 
0.6%
포천청소년문화의집 1
 
0.6%
161-7 1
 
0.6%
완산청소년문화의집 1
 
0.6%
420-8번지 1
 
0.6%
Other values (147) 147
87.0%
2023-12-10T19:09:17.315794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70
 
6.1%
1 64
 
5.6%
57
 
5.0%
55
 
4.8%
55
 
4.8%
- 47
 
4.1%
2 40
 
3.5%
4 38
 
3.3%
33
 
2.9%
33
 
2.9%
Other values (133) 651
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 723
63.3%
Decimal Number 284
 
24.8%
Space Separator 70
 
6.1%
Dash Punctuation 47
 
4.1%
Uppercase Letter 9
 
0.8%
Open Punctuation 5
 
0.4%
Close Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
57
 
7.9%
55
 
7.6%
55
 
7.6%
33
 
4.6%
33
 
4.6%
29
 
4.0%
27
 
3.7%
26
 
3.6%
26
 
3.6%
24
 
3.3%
Other values (111) 358
49.5%
Decimal Number
ValueCountFrequency (%)
1 64
22.5%
2 40
14.1%
4 38
13.4%
3 27
9.5%
6 27
9.5%
5 20
 
7.0%
0 19
 
6.7%
9 17
 
6.0%
8 16
 
5.6%
7 16
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
S 2
22.2%
A 1
11.1%
W 1
11.1%
C 1
11.1%
J 1
11.1%
K 1
11.1%
Y 1
11.1%
O 1
11.1%
Space Separator
ValueCountFrequency (%)
70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 723
63.3%
Common 411
36.0%
Latin 9
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
57
 
7.9%
55
 
7.6%
55
 
7.6%
33
 
4.6%
33
 
4.6%
29
 
4.0%
27
 
3.7%
26
 
3.6%
26
 
3.6%
24
 
3.3%
Other values (111) 358
49.5%
Common
ValueCountFrequency (%)
70
17.0%
1 64
15.6%
- 47
11.4%
2 40
9.7%
4 38
9.2%
3 27
 
6.6%
6 27
 
6.6%
5 20
 
4.9%
0 19
 
4.6%
9 17
 
4.1%
Other values (4) 42
10.2%
Latin
ValueCountFrequency (%)
S 2
22.2%
A 1
11.1%
W 1
11.1%
C 1
11.1%
J 1
11.1%
K 1
11.1%
Y 1
11.1%
O 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 723
63.3%
ASCII 420
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70
16.7%
1 64
15.2%
- 47
11.2%
2 40
9.5%
4 38
9.0%
3 27
 
6.4%
6 27
 
6.4%
5 20
 
4.8%
0 19
 
4.5%
9 17
 
4.0%
Other values (12) 51
12.1%
Hangul
ValueCountFrequency (%)
57
 
7.9%
55
 
7.6%
55
 
7.6%
33
 
4.6%
33
 
4.6%
29
 
4.0%
27
 
3.7%
26
 
3.6%
26
 
3.6%
24
 
3.3%
Other values (111) 358
49.5%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:09:17.929180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length24.68
Min length19

Characters and Unicode

Total characters2468
Distinct characters192
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

Unique96 ?
Unique (%)96.0%

Sample

1st row대구광역시 남구 명덕로34길 16 (대명동)
2nd row경기도 포천시 왕방로 169 (신읍동)
3rd row충청남도 천안시 동남구 목천읍 서리4길 48
4th row강원도 평창군 용평면 새터마을길 108
5th row서울특별시 중구 동호로5길 19 (신당동)
ValueCountFrequency (%)
서울특별시 19
 
3.7%
경기도 18
 
3.5%
제주특별자치도 9
 
1.7%
경상남도 7
 
1.4%
인천광역시 6
 
1.2%
중구 6
 
1.2%
강원도 6
 
1.2%
울산광역시 5
 
1.0%
대전광역시 5
 
1.0%
전라북도 5
 
1.0%
Other values (358) 431
83.4%
2023-12-10T19:09:18.896937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
417
 
16.9%
109
 
4.4%
91
 
3.7%
87
 
3.5%
) 85
 
3.4%
( 85
 
3.4%
1 77
 
3.1%
72
 
2.9%
67
 
2.7%
52
 
2.1%
Other values (182) 1326
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1505
61.0%
Space Separator 417
 
16.9%
Decimal Number 360
 
14.6%
Close Punctuation 85
 
3.4%
Open Punctuation 85
 
3.4%
Dash Punctuation 14
 
0.6%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
109
 
7.2%
91
 
6.0%
87
 
5.8%
72
 
4.8%
67
 
4.5%
52
 
3.5%
40
 
2.7%
35
 
2.3%
31
 
2.1%
30
 
2.0%
Other values (166) 891
59.2%
Decimal Number
ValueCountFrequency (%)
1 77
21.4%
2 50
13.9%
4 46
12.8%
3 43
11.9%
6 30
 
8.3%
5 27
 
7.5%
7 23
 
6.4%
9 22
 
6.1%
0 21
 
5.8%
8 21
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
417
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1505
61.0%
Common 963
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
109
 
7.2%
91
 
6.0%
87
 
5.8%
72
 
4.8%
67
 
4.5%
52
 
3.5%
40
 
2.7%
35
 
2.3%
31
 
2.1%
30
 
2.0%
Other values (166) 891
59.2%
Common
ValueCountFrequency (%)
417
43.3%
) 85
 
8.8%
( 85
 
8.8%
1 77
 
8.0%
2 50
 
5.2%
4 46
 
4.8%
3 43
 
4.5%
6 30
 
3.1%
5 27
 
2.8%
7 23
 
2.4%
Other values (6) 80
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1505
61.0%
ASCII 963
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
417
43.3%
) 85
 
8.8%
( 85
 
8.8%
1 77
 
8.0%
2 50
 
5.2%
4 46
 
4.8%
3 43
 
4.5%
6 30
 
3.1%
5 27
 
2.8%
7 23
 
2.4%
Other values (6) 80
 
8.3%
Hangul
ValueCountFrequency (%)
109
 
7.2%
91
 
6.0%
87
 
5.8%
72
 
4.8%
67
 
4.5%
52
 
3.5%
40
 
2.7%
35
 
2.3%
31
 
2.1%
30
 
2.0%
Other values (166) 891
59.2%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:09:19.290303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length27.27
Min length9

Characters and Unicode

Total characters2727
Distinct characters208
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)96.0%

Sample

1st row대구광역시 남구 대명동 1822-2
2nd row경기도 포천시 신읍동 139-13
3rd row충청남도 천안시 동남구 목천읍 교촌리 232-4 국립중앙청소년수련원
4th row강원도 평창군 용평면 백옥포리 251 국립평창청소년수련원
5th row서울특별시 중구 신당동 844-5 중구청소년센터
ValueCountFrequency (%)
서울특별시 19
 
3.6%
경기도 18
 
3.4%
제주특별자치도 9
 
1.7%
청소년수련관 7
 
1.3%
경상남도 7
 
1.3%
강원도 6
 
1.1%
중구 6
 
1.1%
청소년문화의집 6
 
1.1%
대전광역시 5
 
0.9%
전라북도 5
 
0.9%
Other values (369) 446
83.5%
2023-12-10T19:09:19.945800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
434
 
15.9%
111
 
4.1%
104
 
3.8%
1 84
 
3.1%
78
 
2.9%
72
 
2.6%
68
 
2.5%
- 66
 
2.4%
59
 
2.2%
57
 
2.1%
Other values (198) 1594
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1831
67.1%
Space Separator 434
 
15.9%
Decimal Number 380
 
13.9%
Dash Punctuation 66
 
2.4%
Uppercase Letter 8
 
0.3%
Other Punctuation 7
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
111
 
6.1%
104
 
5.7%
78
 
4.3%
72
 
3.9%
68
 
3.7%
59
 
3.2%
57
 
3.1%
44
 
2.4%
41
 
2.2%
36
 
2.0%
Other values (179) 1161
63.4%
Decimal Number
ValueCountFrequency (%)
1 84
22.1%
2 53
13.9%
4 44
11.6%
6 41
10.8%
3 36
9.5%
5 27
 
7.1%
0 25
 
6.6%
7 25
 
6.6%
9 23
 
6.1%
8 22
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
A 2
25.0%
C 2
25.0%
Y 2
25.0%
W 1
12.5%
M 1
12.5%
Space Separator
ValueCountFrequency (%)
434
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1831
67.1%
Common 888
32.6%
Latin 8
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
111
 
6.1%
104
 
5.7%
78
 
4.3%
72
 
3.9%
68
 
3.7%
59
 
3.2%
57
 
3.1%
44
 
2.4%
41
 
2.2%
36
 
2.0%
Other values (179) 1161
63.4%
Common
ValueCountFrequency (%)
434
48.9%
1 84
 
9.5%
- 66
 
7.4%
2 53
 
6.0%
4 44
 
5.0%
6 41
 
4.6%
3 36
 
4.1%
5 27
 
3.0%
0 25
 
2.8%
7 25
 
2.8%
Other values (4) 53
 
6.0%
Latin
ValueCountFrequency (%)
A 2
25.0%
C 2
25.0%
Y 2
25.0%
W 1
12.5%
M 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1831
67.1%
ASCII 896
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
434
48.4%
1 84
 
9.4%
- 66
 
7.4%
2 53
 
5.9%
4 44
 
4.9%
6 41
 
4.6%
3 36
 
4.0%
5 27
 
3.0%
0 25
 
2.8%
7 25
 
2.8%
Other values (9) 61
 
6.8%
Hangul
ValueCountFrequency (%)
111
 
6.1%
104
 
5.7%
78
 
4.3%
72
 
3.9%
68
 
3.7%
59
 
3.2%
57
 
3.1%
44
 
2.4%
41
 
2.2%
36
 
2.0%
Other values (179) 1161
63.4%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:09:20.425919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length59
Mean length46.07
Min length30

Characters and Unicode

Total characters4607
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)96.0%

Sample

1st row16, Myeongdeok-ro 34-gil, Nam-gu, Daegu
2nd row169, Wangbang-ro, Pocheon-si, Gyeonggi-do
3rd row48, Seori 4-gil, Mokcheon-eup, Dongnam-gu, Cheonan-si, Chungcheongnam-do
4th row108, Saeteomaeul-gil, Yongpyeong-myeon, Pyeongchang-gun, Gangwon-do
5th row19, Dongho-ro 5-gil, Jung-gu, Seoul
ValueCountFrequency (%)
seoul 19
 
4.0%
gyeonggi-do 18
 
3.8%
jeju-do 9
 
1.9%
gyeongsangnam-do 7
 
1.5%
gangwon-do 6
 
1.3%
jung-gu 6
 
1.3%
incheon 6
 
1.3%
seogwipo-si 5
 
1.0%
jeollabuk-do 5
 
1.0%
dong-gu 5
 
1.0%
Other values (319) 393
82.0%
2023-12-10T19:09:21.261995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 429
 
9.3%
n 400
 
8.7%
379
 
8.2%
g 370
 
8.0%
- 335
 
7.3%
, 331
 
7.2%
e 276
 
6.0%
u 229
 
5.0%
a 227
 
4.9%
i 146
 
3.2%
Other values (42) 1485
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2878
62.5%
Space Separator 379
 
8.2%
Decimal Number 353
 
7.7%
Dash Punctuation 335
 
7.3%
Other Punctuation 332
 
7.2%
Uppercase Letter 330
 
7.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 429
14.9%
n 400
13.9%
g 370
12.9%
e 276
9.6%
u 229
8.0%
a 227
7.9%
i 146
 
5.1%
s 104
 
3.6%
l 103
 
3.6%
r 96
 
3.3%
Other values (11) 498
17.3%
Uppercase Letter
ValueCountFrequency (%)
G 66
20.0%
S 60
18.2%
J 45
13.6%
D 39
11.8%
B 19
 
5.8%
M 16
 
4.8%
C 16
 
4.8%
Y 15
 
4.5%
N 12
 
3.6%
H 9
 
2.7%
Other values (7) 33
10.0%
Decimal Number
ValueCountFrequency (%)
1 76
21.5%
2 47
13.3%
4 45
12.7%
3 41
11.6%
6 30
 
8.5%
5 27
 
7.6%
7 23
 
6.5%
9 22
 
6.2%
8 21
 
5.9%
0 21
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 331
99.7%
. 1
 
0.3%
Space Separator
ValueCountFrequency (%)
379
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 335
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3208
69.6%
Common 1399
30.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 429
13.4%
n 400
12.5%
g 370
11.5%
e 276
 
8.6%
u 229
 
7.1%
a 227
 
7.1%
i 146
 
4.6%
s 104
 
3.2%
l 103
 
3.2%
r 96
 
3.0%
Other values (28) 828
25.8%
Common
ValueCountFrequency (%)
379
27.1%
- 335
23.9%
, 331
23.7%
1 76
 
5.4%
2 47
 
3.4%
4 45
 
3.2%
3 41
 
2.9%
6 30
 
2.1%
5 27
 
1.9%
7 23
 
1.6%
Other values (4) 65
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4607
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 429
 
9.3%
n 400
 
8.7%
379
 
8.2%
g 370
 
8.0%
- 335
 
7.3%
, 331
 
7.2%
e 276
 
6.0%
u 229
 
5.0%
a 227
 
4.9%
i 146
 
3.2%
Other values (42) 1485
32.2%

adstrd_cd
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4468023 × 109
Minimum1.1140142 × 109
Maximum5.0130253 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:21.541091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1140142 × 109
5-th percentile1.1258605 × 109
Q12.7282613 × 109
median4.1180608 × 109
Q34.4810467 × 109
95-th percentile5.0111136 × 109
Maximum5.0130253 × 109
Range3.8990111 × 109
Interquartile range (IQR)1.7527854 × 109

Descriptive statistics

Standard deviation1.3320808 × 109
Coefficient of variation (CV)0.38646857
Kurtosis-0.8813666
Mean3.4468023 × 109
Median Absolute Deviation (MAD)8.929526 × 108
Skewness-0.68305681
Sum3.4468023 × 1011
Variance1.7744392 × 1018
MonotonicityNot monotonic
2023-12-10T19:09:21.921484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4380025026 2
 
2.0%
5013011600 2
 
2.0%
2820010100 2
 
2.0%
2824510800 2
 
2.0%
2720010300 1
 
1.0%
4150010100 1
 
1.0%
4573025022 1
 
1.0%
1156012100 1
 
1.0%
4141010100 1
 
1.0%
4418010100 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
1114014200 1
1.0%
1114016200 1
1.0%
1117012900 1
1.0%
1120010700 1
1.0%
1123010700 1
1.0%
1126010500 1
1.0%
1129013800 1
1.0%
1130510300 1
1.0%
1132010700 1
1.0%
1147010200 1
1.0%
ValueCountFrequency (%)
5013025321 1
1.0%
5013025022 1
1.0%
5013011600 2
2.0%
5013010200 1
1.0%
5011013800 1
1.0%
5011012900 1
1.0%
5011010700 1
1.0%
5011010400 1
1.0%
4882025027 1
1.0%
4833010300 1
1.0%

buld_nm
Text

MISSING 

Distinct76
Distinct (%)93.8%
Missing19
Missing (%)19.0%
Memory size932.0 B
2023-12-10T19:09:22.294366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length9.3703704
Min length3

Characters and Unicode

Total characters759
Distinct characters159
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)88.9%

Sample

1st row국립중앙청소년수련원
2nd row국립평창청소년수련원
3rd row중구청소년센터
4th row성남시분당서현청소년수련관
5th row신월청소년문화쎈타
ValueCountFrequency (%)
청소년수련관 7
 
6.5%
청소년문화의집 6
 
5.6%
계양구 2
 
1.9%
단양 2
 
1.9%
청소년 2
 
1.9%
남원청소년문화회관 1
 
0.9%
경남대표도서관 1
 
0.9%
스타디움 1
 
0.9%
1
 
0.9%
안산 1
 
0.9%
Other values (84) 84
77.8%
2023-12-10T19:09:22.945011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
7.8%
59
 
7.8%
56
 
7.4%
36
 
4.7%
34
 
4.5%
30
 
4.0%
27
 
3.6%
24
 
3.2%
21
 
2.8%
17
 
2.2%
Other values (149) 396
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 710
93.5%
Space Separator 27
 
3.6%
Uppercase Letter 8
 
1.1%
Other Punctuation 7
 
0.9%
Decimal Number 6
 
0.8%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
59
 
8.3%
59
 
8.3%
56
 
7.9%
36
 
5.1%
34
 
4.8%
30
 
4.2%
24
 
3.4%
21
 
3.0%
17
 
2.4%
17
 
2.4%
Other values (139) 357
50.3%
Uppercase Letter
ValueCountFrequency (%)
Y 2
25.0%
C 2
25.0%
A 2
25.0%
W 1
12.5%
M 1
12.5%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 3
50.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 710
93.5%
Common 41
 
5.4%
Latin 8
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
59
 
8.3%
59
 
8.3%
56
 
7.9%
36
 
5.1%
34
 
4.8%
30
 
4.2%
24
 
3.4%
21
 
3.0%
17
 
2.4%
17
 
2.4%
Other values (139) 357
50.3%
Common
ValueCountFrequency (%)
27
65.9%
, 7
 
17.1%
2 3
 
7.3%
1 3
 
7.3%
~ 1
 
2.4%
Latin
ValueCountFrequency (%)
Y 2
25.0%
C 2
25.0%
A 2
25.0%
W 1
12.5%
M 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 710
93.5%
ASCII 49
 
6.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
59
 
8.3%
59
 
8.3%
56
 
7.9%
36
 
5.1%
34
 
4.8%
30
 
4.2%
24
 
3.4%
21
 
3.0%
17
 
2.4%
17
 
2.4%
Other values (139) 357
50.3%
ASCII
ValueCountFrequency (%)
27
55.1%
, 7
 
14.3%
2 3
 
6.1%
1 3
 
6.1%
Y 2
 
4.1%
C 2
 
4.1%
A 2
 
4.1%
W 1
 
2.0%
~ 1
 
2.0%
M 1
 
2.0%

buld_manage_cd
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4468023 × 1024
Minimum1.1140142 × 1024
Maximum5.0130253 × 1024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:23.215618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1140142 × 1024
5-th percentile1.1258605 × 1024
Q12.7282613 × 1024
median4.1180608 × 1024
Q34.4810467 × 1024
95-th percentile5.0111136 × 1024
Maximum5.0130253 × 1024
Range3.8990111 × 1024
Interquartile range (IQR)1.7527854 × 1024

Descriptive statistics

Standard deviation1.3320808 × 1024
Coefficient of variation (CV)0.38646857
Kurtosis-0.8813666
Mean3.4468023 × 1024
Median Absolute Deviation (MAD)8.929526 × 1023
Skewness-0.68305681
Sum3.4468023 × 1026
Variance1.7744392 × 1048
MonotonicityNot monotonic
2023-12-10T19:09:23.476069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.82451080010214e+24 2
 
2.0%
4.38002502610636e+24 2
 
2.0%
4.1500101001042e+24 1
 
1.0%
2.61701010011144e+24 1
 
1.0%
4.57302502211094e+24 1
 
1.0%
1.15601210010073e+24 1
 
1.0%
5.0130116001148e+24 1
 
1.0%
4.14101010010729e+24 1
 
1.0%
4.4180101001012703e+24 1
 
1.0%
3.11701080010449e+24 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
1.11401420010002e+24 1
1.0%
1.11401620010844e+24 1
1.0%
1.11701290010301e+24 1
1.0%
1.12001070010007e+24 1
1.0%
1.12301070010011e+24 1
1.0%
1.12601050010241e+24 1
1.0%
1.12901380010135e+24 1
1.0%
1.1305103001053504e+24 1
1.0%
1.13201070010001e+24 1
1.0%
1.14701020010918e+24 1
1.0%
ValueCountFrequency (%)
5.013025321115e+24 1
1.0%
5.01302502211268e+24 1
1.0%
5.01301160014417e+24 1
1.0%
5.0130116001148e+24 1
1.0%
5.01301020010162e+24 1
1.0%
5.01101380010872e+24 1
1.0%
5.01101290010057e+24 1
1.0%
5.01101070010538e+24 1
1.0%
5.01101040011022e+24 1
1.0%
4.88202502710377e+24 1
1.0%

fclty_la
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.75518
Minimum35.574416
Maximum129.42516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:23.727020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.574416
5-th percentile126.47616
Q1126.87578
median127.09741
Q3128.22248
95-th percentile129.0715
Maximum129.42516
Range93.850744
Interquartile range (IQR)1.3466947

Descriptive statistics

Standard deviation15.576952
Coefficient of variation (CV)0.12486016
Kurtosis29.714096
Mean124.75518
Median Absolute Deviation (MAD)0.3432505
Skewness-5.5686558
Sum12475.518
Variance242.64142
MonotonicityNot monotonic
2023-12-10T19:09:23.948975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7420466 2
 
2.0%
128.3712834 2
 
2.0%
127.4407157 1
 
1.0%
129.0442921 1
 
1.0%
127.663447 1
 
1.0%
126.8941305 1
 
1.0%
126.4981426 1
 
1.0%
126.946177 1
 
1.0%
126.6001011 1
 
1.0%
129.4251597 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
35.5744155 1
1.0%
37.2181894 1
1.0%
37.4889409 1
1.0%
126.2477254 1
1.0%
126.4470726 1
1.0%
126.4776857 1
1.0%
126.4981426 1
1.0%
126.5141483 1
1.0%
126.5274792 1
1.0%
126.5326663 1
1.0%
ValueCountFrequency (%)
129.4251597 1
1.0%
129.4173704 1
1.0%
129.3012084 1
1.0%
129.2907148 1
1.0%
129.0951501 1
1.0%
129.0702544 1
1.0%
129.0450669 1
1.0%
129.0442921 1
1.0%
129.0372196 1
1.0%
129.0324818 1
1.0%

fclty_lo
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.128292
Minimum33.227892
Maximum129.30976
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:24.194388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.227892
5-th percentile33.46996
Q135.525462
median37.107387
Q337.495374
95-th percentile37.912205
Maximum129.30976
Range96.081866
Interquartile range (IQR)1.9699125

Descriptive statistics

Standard deviation15.706748
Coefficient of variation (CV)0.40141666
Kurtosis29.447682
Mean39.128292
Median Absolute Deviation (MAD)0.6975272
Skewness5.5311418
Sum3912.8292
Variance246.70194
MonotonicityNot monotonic
2023-12-10T19:09:24.426392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.550148 2
 
2.0%
36.9826526 2
 
2.0%
37.2835385 1
 
1.0%
35.1245221 1
 
1.0%
36.001649 1
 
1.0%
37.5188833 1
 
1.0%
33.2607167 1
 
1.0%
37.3582837 1
 
1.0%
36.3505525 1
 
1.0%
35.541318 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
33.2278921 1
1.0%
33.2355383 1
1.0%
33.2371902 1
1.0%
33.2607167 1
1.0%
33.2809399 1
1.0%
33.4799079 1
1.0%
33.4929278 1
1.0%
33.4936435 1
1.0%
33.5137858 1
1.0%
34.6751755 1
1.0%
ValueCountFrequency (%)
129.3097584 1
1.0%
127.0393854 1
1.0%
126.6411206 1
1.0%
38.2169492 1
1.0%
38.192892 1
1.0%
37.8974319 1
1.0%
37.8567056 1
1.0%
37.6580477 1
1.0%
37.6412288 1
1.0%
37.6174549 1
1.0%

intrcn_cn
Text

MISSING 

Distinct79
Distinct (%)100.0%
Missing21
Missing (%)21.0%
Memory size932.0 B
2023-12-10T19:09:24.857572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length650
Median length119
Mean length106.56962
Min length1

Characters and Unicode

Total characters8419
Distinct characters471
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)100.0%

Sample

1st row. 청소년과 같은 눈높이에서 눈빛만으로도 통할 수 있는 소중한 친구. 대구광역시 청소년문화의집입니다. 대구광역시 청소년문화의집은 2011년부터 (재)대구청소년재단에서 수탁 운영되고 있습니다.
2nd row- 일상생활 속에 문화공간을 제공함으로써 청소년들의 문화적 욕구를 충족시키고 올바른 여가활동 및 정서함양 등 건전한 청소년을 육성하고자 포천시에서 설립. - 청소년이 즐거운 ‘소통하는 행복 꿈 놀이터!’로 마을 청소년들의 발걸음이 끊임없이 이어지도록 열정과 전문성, 진정성을 담아내어 미래의 꿈과 희망을 키우는 청소년문화의집 운영. 2017.4.24. 준공 2017.5.20. 개관
3rd row자연과 함께하는 최고의 체험중심터전! 국립평창청소년수련원!
4th row서울의 중심 중구 지역 신당동 소재 청소년이 중심이 되는 수련관입니다
5th row성남시 출연기관 성남시청소년육성재단 산하 기관 2003년도 개관 후 다양한 청소년 활동을 운영하고 있으며 2009년도 청소년수련관 종합평가 최우수기관 선정 2010년도 푸른성장 대상 수상
ValueCountFrequency (%)
청소년 33
 
1.9%
29
 
1.7%
다양한 29
 
1.7%
24
 
1.4%
있는 22
 
1.3%
있습니다 19
 
1.1%
위한 19
 
1.1%
청소년의 16
 
0.9%
청소년들의 14
 
0.8%
13
 
0.8%
Other values (1091) 1492
87.3%
2023-12-10T19:09:25.810236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1659
 
19.7%
236
 
2.8%
235
 
2.8%
220
 
2.6%
152
 
1.8%
128
 
1.5%
121
 
1.4%
115
 
1.4%
. 113
 
1.3%
, 112
 
1.3%
Other values (461) 5328
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6181
73.4%
Space Separator 1659
 
19.7%
Other Punctuation 276
 
3.3%
Decimal Number 198
 
2.4%
Lowercase Letter 26
 
0.3%
Uppercase Letter 24
 
0.3%
Close Punctuation 16
 
0.2%
Open Punctuation 15
 
0.2%
Dash Punctuation 9
 
0.1%
Math Symbol 5
 
0.1%
Other values (2) 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
236
 
3.8%
235
 
3.8%
220
 
3.6%
152
 
2.5%
128
 
2.1%
121
 
2.0%
115
 
1.9%
108
 
1.7%
105
 
1.7%
103
 
1.7%
Other values (404) 4658
75.4%
Lowercase Letter
ValueCountFrequency (%)
e 4
15.4%
n 3
11.5%
o 3
11.5%
h 2
 
7.7%
g 2
 
7.7%
u 2
 
7.7%
a 2
 
7.7%
t 1
 
3.8%
s 1
 
3.8%
p 1
 
3.8%
Other values (5) 5
19.2%
Uppercase Letter
ValueCountFrequency (%)
C 4
16.7%
A 3
12.5%
Y 3
12.5%
M 3
12.5%
N 3
12.5%
B 2
8.3%
O 2
8.3%
D 1
 
4.2%
S 1
 
4.2%
U 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 44
22.2%
0 42
21.2%
2 38
19.2%
9 15
 
7.6%
6 11
 
5.6%
5 10
 
5.1%
4 10
 
5.1%
7 10
 
5.1%
8 9
 
4.5%
3 9
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 113
40.9%
, 112
40.6%
' 14
 
5.1%
! 14
 
5.1%
· 12
 
4.3%
" 4
 
1.4%
3
 
1.1%
/ 3
 
1.1%
: 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 15
93.8%
1
 
6.2%
Open Punctuation
ValueCountFrequency (%)
( 14
93.3%
1
 
6.7%
Math Symbol
ValueCountFrequency (%)
~ 4
80.0%
+ 1
 
20.0%
Final Punctuation
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Initial Punctuation
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Space Separator
ValueCountFrequency (%)
1659
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6181
73.4%
Common 2188
 
26.0%
Latin 50
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
236
 
3.8%
235
 
3.8%
220
 
3.6%
152
 
2.5%
128
 
2.1%
121
 
2.0%
115
 
1.9%
108
 
1.7%
105
 
1.7%
103
 
1.7%
Other values (404) 4658
75.4%
Common
ValueCountFrequency (%)
1659
75.8%
. 113
 
5.2%
, 112
 
5.1%
1 44
 
2.0%
0 42
 
1.9%
2 38
 
1.7%
) 15
 
0.7%
9 15
 
0.7%
( 14
 
0.6%
' 14
 
0.6%
Other values (21) 122
 
5.6%
Latin
ValueCountFrequency (%)
e 4
 
8.0%
C 4
 
8.0%
A 3
 
6.0%
Y 3
 
6.0%
M 3
 
6.0%
n 3
 
6.0%
o 3
 
6.0%
N 3
 
6.0%
B 2
 
4.0%
h 2
 
4.0%
Other values (16) 20
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6181
73.4%
ASCII 2211
 
26.3%
None 17
 
0.2%
Punctuation 10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1659
75.0%
. 113
 
5.1%
, 112
 
5.1%
1 44
 
2.0%
0 42
 
1.9%
2 38
 
1.7%
) 15
 
0.7%
9 15
 
0.7%
( 14
 
0.6%
' 14
 
0.6%
Other values (39) 145
 
6.6%
Hangul
ValueCountFrequency (%)
236
 
3.8%
235
 
3.8%
220
 
3.6%
152
 
2.5%
128
 
2.1%
121
 
2.0%
115
 
1.9%
108
 
1.7%
105
 
1.7%
103
 
1.7%
Other values (404) 4658
75.4%
None
ValueCountFrequency (%)
· 12
70.6%
3
 
17.6%
1
 
5.9%
1
 
5.9%
Punctuation
ValueCountFrequency (%)
4
40.0%
4
40.0%
1
 
10.0%
1
 
10.0%

oper_instt_nm
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing98
Missing (%)98.0%
Memory size932.0 B
2023-12-10T19:09:26.046039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3.5
Mean length3.5
Min length3

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row화성시
2nd row철원군청
ValueCountFrequency (%)
화성시 1
50.0%
철원군청 1
50.0%
2023-12-10T19:09:26.529547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

fond_de
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
98 
20031118
 
1
20060608
 
1

Length

Max length8
Median length4
Mean length4.08
Min length4

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 98
98.0%
20031118 1
 
1.0%
20060608 1
 
1.0%

Length

2023-12-10T19:09:26.812009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:27.011116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
98.0%
20031118 1
 
1.0%
20060608 1
 
1.0%

use_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
95 
False
 
5
ValueCountFrequency (%)
True 95
95.0%
False 5
 
5.0%
2023-12-10T19:09:27.163467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

aprvl_at
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing1
Missing (%)1.0%
Memory size332.0 B
True
99 
(Missing)
 
1
ValueCountFrequency (%)
True 99
99.0%
(Missing) 1
 
1.0%
2023-12-10T19:09:27.287741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

aprvl_dt
Real number (ℝ)

Distinct99
Distinct (%)100.0%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean2.0159355 × 1013
Minimum2.008062 × 1013
Maximum2.0170822 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:27.480583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.008062 × 1013
5-th percentile2.0131092 × 1013
Q12.0160366 × 1013
median2.0160708 × 1013
Q32.0170316 × 1013
95-th percentile2.0170721 × 1013
Maximum2.0170822 × 1013
Range9.0202021 × 1010
Interquartile range (IQR)9.9504746 × 109

Descriptive statistics

Standard deviation1.4875666 × 1010
Coefficient of variation (CV)0.00073790388
Kurtosis11.551118
Mean2.0159355 × 1013
Median Absolute Deviation (MAD)9.583029 × 109
Skewness-2.9355427
Sum1.9957761 × 1015
Variance2.2128545 × 1020
MonotonicityNot monotonic
2023-12-10T19:09:27.855080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160704170714 1
 
1.0%
20170207182538 1
 
1.0%
20170629135546 1
 
1.0%
20170627172258 1
 
1.0%
20160629154913 1
 
1.0%
20160414152658 1
 
1.0%
20170316093059 1
 
1.0%
20160408103132 1
 
1.0%
20160704170743 1
 
1.0%
20161207100313 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
20080620142429 1
1.0%
20090602100713 1
1.0%
20120802140353 1
1.0%
20130820111415 1
1.0%
20130907115810 1
1.0%
20131112172404 1
1.0%
20140527114912 1
1.0%
20140618133056 1
1.0%
20141215134116 1
1.0%
20141222104628 1
1.0%
ValueCountFrequency (%)
20170822163105 1
1.0%
20170810151553 1
1.0%
20170808112035 1
1.0%
20170801155237 1
1.0%
20170724160953 1
1.0%
20170720174036 1
1.0%
20170718161850 1
1.0%
20170704153708 1
1.0%
20170703152633 1
1.0%
20170630135304 1
1.0%

Sample

esntl_idtrng_act_fclty_seq_nofclty_seq_noty_cdty_nmrspnsblty_dept_nmmain_fclty_cnmain_progrm_cnacmd_nmpr_coldgs_psncpa_cofclty_nmtel_nohmpg_urlctprvn_cdctprvn_nmsigngu_cdsigngu_nmzip_noarea_addrarea_detail_addrfclty_road_nm_addrlnm_addraddr_eng_nmadstrd_cdbuld_nmbuld_manage_cdfclty_lafclty_lointrcn_cnoper_instt_nmfond_deuse_ataprvl_ataprvl_dt
0KCCBSPO20N0000000015550003문화의집<NA><NA><NA><NA><NA>대구광역시청소년문화의집053-661-1318http://dg1318.net20003대구광역시23005남구70581대구 남구 대명2동1822-2대구광역시 남구 명덕로34길 16 (대명동)대구광역시 남구 대명동 1822-216, Myeongdeok-ro 34-gil, Nam-gu, Daegu2720010300<NA>2720010300118220002017427128.58712535.855874. 청소년과 같은 눈높이에서 눈빛만으로도 통할 수 있는 소중한 친구. 대구광역시 청소년문화의집입니다. 대구광역시 청소년문화의집은 2011년부터 (재)대구청소년재단에서 수탁 운영되고 있습니다.<NA><NA>YY20160704170714
1KCCBSPO20N0000003364661466150003문화의집<NA><NA><NA><NA><NA>포천청소년문화의집031-538-3382http://youth.pocheon.go.kr/poycc20008경기도28047포천시11141경기도 포천시 왕방로 169 (신읍동)포천청소년문화의집경기도 포천시 왕방로 169 (신읍동)경기도 포천시 신읍동 139-13169, Wangbang-ro, Pocheon-si, Gyeonggi-do4165010100<NA>4165010100101390013033575127.19593837.897432- 일상생활 속에 문화공간을 제공함으로써 청소년들의 문화적 욕구를 충족시키고 올바른 여가활동 및 정서함양 등 건전한 청소년을 육성하고자 포천시에서 설립. - 청소년이 즐거운 ‘소통하는 행복 꿈 놀이터!’로 마을 청소년들의 발걸음이 끊임없이 이어지도록 열정과 전문성, 진정성을 담아내어 미래의 꿈과 희망을 키우는 청소년문화의집 운영. 2017.4.24. 준공 2017.5.20. 개관<NA><NA>YY20170630135304
2KCCBSPO20N000000003111150002수련원<NA><NA><NA><NA><NA>국립중앙청소년수련원041-620-7700http://nyc.kywa.or.kr20011충청남도31013천안시33084충남 천안시 목천읍 교촌리246-1충청남도 천안시 동남구 목천읍 서리4길 48충청남도 천안시 동남구 목천읍 교촌리 232-4 국립중앙청소년수련원48, Seori 4-gil, Mokcheon-eup, Dongnam-gu, Cheonan-si, Chungcheongnam-do4413125023국립중앙청소년수련원4413125021100850000036873127.22679936.791495<NA><NA><NA>YY20170703152633
3KCCBSPO20N000000004131350002수련원활동운영부<NA><NA><NA><NA>국립평창청소년수련원033-330-0800https://pnyc.kywa.or.kr20009강원도29015평창군23293강원 평창군 용평면새터마을길 108 국립평창청소년수련원강원도 평창군 용평면 새터마을길 108강원도 평창군 용평면 백옥포리 251 국립평창청소년수련원108, Saeteomaeul-gil, Yongpyeong-myeon, Pyeongchang-gun, Gangwon-do4276035026국립평창청소년수련원4276035026102510001031923128.39816237.583068자연과 함께하는 최고의 체험중심터전! 국립평창청소년수련원!<NA><NA>YY20151125142028
4KCCBSPO20N000000005141450001수련관<NA><NA><NA><NA><NA>서울중구청소년수련관02-2250-0500http://j-youth.org20001서울특별시21011중구10045서울 중구 신당3동844-5 서울중구청소년수련관서울특별시 중구 동호로5길 19 (신당동)서울특별시 중구 신당동 844-5 중구청소년센터19, Dongho-ro 5-gil, Jung-gu, Seoul1114016200중구청소년센터1114016200108440005007430127.01253937.551869서울의 중심 중구 지역 신당동 소재 청소년이 중심이 되는 수련관입니다<NA><NA>YY20160427141047
5KCCBSPO20N000000006222250001수련관<NA><NA><NA><NA><NA>분당서현청소년수련관031-729-9400http://www.uth.or.kr20008경기도28020성남시 분당구46382경기 성남시 분당구 서현동312-5 서현청소년수련관경기도 성남시 분당구 불정로386번길 38 (서현동)경기도 성남시 분당구 서현동 312-5 성남시분당서현청소년수련관38, Buljeong-ro 386beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do4113510500성남시분당서현청소년수련관4113510500103120005058117127.13992537.372275성남시 출연기관 성남시청소년육성재단 산하 기관 2003년도 개관 후 다양한 청소년 활동을 운영하고 있으며 2009년도 청소년수련관 종합평가 최우수기관 선정 2010년도 푸른성장 대상 수상<NA><NA>YY20150506150822
6KCCBSPO20N000000007282850003문화의집<NA><NA><NA><NA><NA>신월청소년문화센터02-2604-7485http://swyouth.or.kr/20001서울특별시21017양천구15882서울 양천구 신월3동150-3서울특별시 양천구 가로공원로 86 (신월동)서울특별시 양천구 신월동 150-3 신월청소년문화쎈타86, Garogongwon-ro, Yangcheon-gu, Seoul1147010300신월청소년문화쎈타1147010300101500003012728126.82541637.535182살레시오 수녀회의 기본정신인 돈보스코 성인의 예방교육을 바탕으로 청소년들에게 다양한 문화적 체험기회를 제공하고 자치활동을 위한 터전을 마련해주며 학교에서 가르쳐 주지 않는 세상이야기를 배울 수 있도록 하는 청소년들을 위한 전용공간입니다.<NA><NA>YY20160427141338
7KCCBSPO20N0000003374742474244003진흥센터<NA><NA><NA><NA><NA>(재)푸른나무 청예단070-7165-1071http://www.jikim.net20001서울특별시21020서초구6650서울특별시 서초구 서초대로46길 88 (서초동)3층 SOS지원단서울특별시 서초구 서초대로46길 88 (서초동)서울특별시 서초구 서초동 1566-2 청예단빌딩88, Seocho-daero 46-gil, Seocho-gu, Seoul1165010800청예단빌딩1165010800115660002020562127.01285737.489862(재)푸른나무 청예단은 1995년 6월 학교폭력의 피해로 16살의 꽃다운 나이에 죽음을 선택한 외아들을 그리고, 그 아버지(명예이사장 김종기)가 다시는 이 땅에 자신과 같이 불행한 아버지가 없기를 소망하는 마음으로 학교폭력 상담전화(1588-9128), 상담치료, 분쟁조정, 장학지원, 교육, 캠페인 등 학교폭력 예방과 치료를 위한 다양한 활동을 하고 있는 UN경제사회이사회에서 특별지위를 부여받은 청소년 비영리공익법인(NGO)입니다.<NA><NA>YY20170801155237
8KCCBSPO20N000000009565650003문화의집<NA><NA><NA><NA><NA>고성군청소년문화의집055-670-2919http://youth.goseong.go.kr20015경상남도35003고성군63880경남 고성군 고성읍 교사리377경상남도 고성군 고성읍 교사4길 13경상남도 고성군 고성읍 교사리 37713, Gyosa 4-gil, Goseong-eup, Goseong-gun, Gyeongsangnam-do4882025027<NA>4882025027103770000013013128.3096434.978427<NA><NA><NA>YY20160629110554
9KCCBSPO20N000000010585844003진흥센터<NA><NA><NA><NA><NA>인천YMCA032-431-8161http://www.icymca.or.kr20004인천광역시<NA><NA>40583인천 남동구 구월1동1131-12인천광역시 남동구 구월남로 118 (구월동)인천광역시 남동구 구월동 1131-12 인천YMCA118, Guwollam-ro, Namdong-gu, Incheon2820010100인천YMCA2820010100111310012000863126.70247637.452967<NA><NA><NA>YY20080620142429
esntl_idtrng_act_fclty_seq_nofclty_seq_noty_cdty_nmrspnsblty_dept_nmmain_fclty_cnmain_progrm_cnacmd_nmpr_coldgs_psncpa_cofclty_nmtel_nohmpg_urlctprvn_cdctprvn_nmsigngu_cdsigngu_nmzip_noarea_addrarea_detail_addrfclty_road_nm_addrlnm_addraddr_eng_nmadstrd_cdbuld_nmbuld_manage_cdfclty_lafclty_lointrcn_cnoper_instt_nmfond_deuse_ataprvl_ataprvl_dt
90KCCBSPO20N00000009155455450001수련관<NA><NA><NA><NA><NA>장흥청소년수련관061-863-0250<NA>20013전라남도33018장흥군52980전남 장흥군 장흥읍 건산리1구761-2 장흥청소년수련관전라남도 장흥군 장흥읍 흥성로 37-23전라남도 장흥군 장흥읍 건산리 761-2 장흥군청소년수련관37-23, Heungseong-ro, Jangheung-eup, Jangheung-gun, Jeollanam-do4680025037장흥군청소년수련관4680025037107610002006616126.90661234.675176장흥청소년수련관<NA><NA>YY20170510172028
91KCCBSPO20N00000009255655644003진흥센터RCY본부<NA><NA><NA><NA>대한적십자사 RCY울산본부052-243-7921http://www.redcross.or.kr/ulsan20007울산광역시27005중구68130울산 중구 성안동405-7울산광역시 중구 성안8길 71 (성안동)울산 중구 성안동71, Seongan 8-gil, Jung-gu, Ulsan3111010900대한적십자사 울산지사311101090010405000700000135.574416129.309758대한적십자사 울산광역시지사<NA><NA>YY20140527114912
92KCCBSPO20N00000009356156150001수련관<NA><NA><NA><NA><NA>대구광역시달서구청소년수련관053-639-7101http://dsyc.or.kr20003대구광역시23006달서구70481대구 달서구 상인3동1593-6번지대구광역시 달서구 상화로 420 (상인동)대구광역시 달서구 상인동 1593-6 청소년수련관420, Sanghwa-ro, Dalseo-gu, Daegu2729011500청소년수련관2729011500115930006001317128.5595335.807216달서구청소년수련관<NA><NA>YY20170822163105
93KCCBSPO20N00000009460760750001수련관활동사업부<NA><NA><NA><NA>안양시만안청소년수련관0314704700http://manan.ayf.or.kr20008경기도28035안양시 만안구14091경기도 안양시 만안구 냉천로31번길 33 (안양동)안양시청소년수련관경기도 안양시 만안구 냉천로31번길 33 (안양동)경기도 안양시 만안구 안양동 462-5 만안청소년수련관33, Naengcheon-ro 31beon-gil, Manan-gu, Anyang-si, Gyeonggi-do4117110100만안청소년수련관4117110100104620005013954126.92641637.383298<NA><NA><NA>YY20161213100813
94KCCBSPO20N00000009560960950001수련관<NA>-청소년수련관, 도서관, 체육관<NA><NA>100철원종합문화복지센터033-455-9192http://ccwc.cwg.go.kr20009강원도29012철원군24005강원도 철원군 철원읍 금학로330번길 12철원종합문화복지센터강원도 철원군 철원읍 금학로330번길 12강원도 철원군 철원읍 화지리 693 철원종합문화복지센터12, Geumhak-ro 330beon-gil, Cheorwon-eup, Cheorwon-gun, Gangwon-do4278025021철원종합문화복지센터4278025021106930000018132127.21400738.216949철원군 청소년수련관으로서 지역의 청소년들에게 다양한 활동, 체험 프로그램을 제공하고있습니다. 2006. 5. 준공 2007. 4. 개관(수탁 : 춘천YMCA) 2007. 6. 청소년 수련시설 등록(철원군) 2008. 5. 평생교육원 등록 2009. 1~ 2012.11.30 춘천YMCA 수탁 2012.12.1~ 철원군 직영운영철원군청20060608YY20170425141054
95KCCBSPO20N00000009661561550005특화시설<NA><NA><NA><NA><NA>서울시립청소년문화교류센터02-755-1024<NA>20001서울특별시21011중구10025서울 중구 예장동산 4-5 2층서울특별시 중구 퇴계로26가길 6 (예장동)서울특별시 중구 예장동 산4-56, Toegye-ro 26ga-gil, Jung-gu, Seoul1114014200<NA>1114014200100020001018246126.99125337.559075<NA><NA><NA>YY20151014161925
96KCCBSPO20N00000009761861850001수련관<NA><NA><NA><NA><NA>서울시립성북청소년센터02-3292-1318http://sbyouth.or.kr20001서울특별시21023성북구2764서울특별시 성북구 한천로95길 7 (장위동)서울특별시립 성북청소년수련관서울특별시 성북구 한천로 660-9 (장위동)서울특별시 성북구 장위동 135-2 성북청소년수련관660-9, Hancheon-ro, Seongbuk-gu, Seoul1129013800성북청소년수련관1129013800101350002008527127.0559437.617455청소년들을 위한 교육·상담·문화·예능·수련활동과 비행예방 및 교정 사업 등을 실시하며 아울러 청소년 보호의 기능을 수행해 21세기 주역이될 우리 청소년들에게 꿈과 사랑을 심어주고 민주 시민의식을 함양한 세계화 시대에 걸맞는 창의적인 청소년을 육성<NA><NA>YY20170428103118
97KCCBSPO20N00000009863263250003문화의집<NA><NA><NA><NA><NA>도계청소년장학센터033-541-0605http://dgyouth.samcheok.go.kr20009강원도29004삼척시25947강원도 삼척시 도계읍 도계로 2543층강원도 삼척시 도계읍 도계로 254강원도 삼척시 도계읍 전두리 49-5 도계청소년장학센터254, Dogye-ro, Dogye-eup, Samcheok-si, Gangwon-do4223025033도계청소년장학센터4223025030104210003000001129.04506737.232122도계청소년장학센터는 삼척시에서 직영으로 운영하는 청소년수련시설로써, 미래지향적인 건전한 청소년육성을 위한 자기계발, 체험활동, 문화활동, 봉사활동, 동아리활동을 통하여 역량을 강화하고 다양하고 특색있는 프로그램운영으로 청소년들이 자유롭게 이용할 수 있는 꿈과 희망이 가득한 학습 정보 문화의 공간입니다.<NA><NA>YY20170310190426
98KCCBSPO20N00000009963463450003문화의집<NA><NA><NA><NA><NA>문경시청소년문화의집054-550-6655<NA>20014경상북도34007문경시36950경상북도 문경시 신흥로 11 (모전동)문경시청소년문화의집경상북도 문경시 신흥로 11 (모전동)경상북도 문경시 모전동 77-1311, Sinheung-ro, Mungyeong-si, Gyeongsangbuk-do4728011000<NA>4728011000100770013026163128.19342536.586389내일의 주역인 청소년들이 밝고 아름다운 내일의 알찬 꿈을 키우며 자유롭게 이용할 수 있는 만남과 휴식의 공간을 제공하고 다양한 청소년 문화 활동과 변화하는 사회의 각종정보를 활용할 수 있도록 도내 최고의 시설과 공간을 확보한 생활권내의 청소년 전용 문화공간입니다.<NA><NA>YY20160406142835
99KCCBSPO20N00000010063863850003문화의집<NA><NA><NA><NA><NA>광주광역시 화정청소년문화의집062-375-1324http://gjyc.or.kr20005광주광역시25005서구61985광주광역시 서구 화정로179번길 63 (화정동)1층 화정청소년문화의집광주광역시 서구 화정로179번길 63 (화정동)광주광역시 서구 화정동 316-99 광주광역시청소년문화의집63, Hwajeong-ro 179beon-gil, Seo-gu, Gwangju2914011900광주광역시청소년문화의집2914011900103160011022696126.87589635.15067'청소년문화발전소' 광주광역시청소년문화의집은 청소년문화활동 활성화와 창의적체험활동, 학교밖청소년을 위한 다양한 프로그램을 운영하고 있습니다.<NA><NA>YY20150715115055