Overview

Dataset statistics

Number of variables19
Number of observations100
Missing cells468
Missing cells (%)24.6%
Duplicate rows16
Duplicate rows (%)16.0%
Total size in memory15.3 KiB
Average record size in memory156.3 B

Variable types

Categorical13
Numeric1
Text5

Alerts

dgnss_result_cn has constant value ""Constant
Dataset has 16 (16.0%) duplicate rowsDuplicates
area_nm is highly overall correlated with act_nm and 9 other fieldsHigh correlation
act_nm is highly overall correlated with actpd_begin_ymd and 12 other fieldsHigh correlation
instt_nm is highly overall correlated with actpd_begin_ymd and 12 other fieldsHigh correlation
confm_ymd is highly overall correlated with actpd_begin_ymd and 8 other fieldsHigh correlation
sttus is highly overall correlated with actpd_begin_ymd and 11 other fieldsHigh correlation
insrnc_occrrnc_at is highly overall correlated with actpd_begin_ymd and 9 other fieldsHigh correlation
instt_ty is highly overall correlated with actpd_begin_ymd and 9 other fieldsHigh correlation
act_time is highly overall correlated with actpd_begin_ymd and 12 other fieldsHigh correlation
actpd_begin_ymd is highly overall correlated with act_nm and 11 other fieldsHigh correlation
act_ty is highly overall correlated with actpd_begin_ymd and 10 other fieldsHigh correlation
partcpt_nmpr is highly overall correlated with actpd_begin_ymd and 12 other fieldsHigh correlation
actpd_end_ymd is highly overall correlated with actpd_begin_ymd and 11 other fieldsHigh correlation
insrnc_sbscrb_at is highly overall correlated with actpd_begin_ymd and 12 other fieldsHigh correlation
presentn_ymd is highly overall correlated with actpd_begin_ymd and 8 other fieldsHigh correlation
insrnc_occrrnc_at is highly imbalanced (89.8%)Imbalance
schul_nm has 86 (86.0%) missing valuesMissing
schul_area_nm has 87 (87.0%) missing valuesMissing
nsrnc_cn has 98 (98.0%) missing valuesMissing
nsrnc_process_cn has 98 (98.0%) missing valuesMissing
dgnss_result_cn has 99 (99.0%) missing valuesMissing

Reproduction

Analysis started2023-12-10 10:17:36.880248
Analysis finished2023-12-10 10:17:39.911243
Duration3.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

area_nm
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충청북도
26 
경기도
17 
전라남도
14 
강원도
14 
충청남도
11 
Other values (6)
18 

Length

Max length7
Median length4
Mean length3.9
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청북도
2nd row경기도
3rd row경기도
4th row경기도
5th row경기도

Common Values

ValueCountFrequency (%)
충청북도 26
26.0%
경기도 17
17.0%
전라남도 14
14.0%
강원도 14
14.0%
충청남도 11
11.0%
서울특별시 5
 
5.0%
제주특별자치도 4
 
4.0%
경상북도 3
 
3.0%
경상남도 2
 
2.0%
대구광역시 2
 
2.0%

Length

2023-12-10T19:17:40.025784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충청북도 26
26.0%
경기도 17
17.0%
전라남도 14
14.0%
강원도 14
14.0%
충청남도 11
11.0%
서울특별시 5
 
5.0%
제주특별자치도 4
 
4.0%
경상북도 3
 
3.0%
경상남도 2
 
2.0%
대구광역시 2
 
2.0%

act_nm
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
띵가띵가 나무소리
13 
창의력을 디자인하다!
10 
영광군청소년오케스트라
8 
Fly with Me
7 
뚝딱뚝딱 로봇창의활동(초급)
7 
Other values (25)
55 

Length

Max length25
Median length21
Mean length11.7
Min length4

Unique

Unique10 ?
Unique (%)10.0%

Sample

1st row띵가띵가 나무소리
2nd row내 꿈은 세계 요리사!
3rd row내 꿈은 세계 요리사!
4th row내 꿈은 세계 요리사!
5th row내 꿈은 세계 요리사!

Common Values

ValueCountFrequency (%)
띵가띵가 나무소리 13
 
13.0%
창의력을 디자인하다! 10
 
10.0%
영광군청소년오케스트라 8
 
8.0%
Fly with Me 7
 
7.0%
뚝딱뚝딱 로봇창의활동(초급) 7
 
7.0%
스페셜코더 5
 
5.0%
내 꿈은 세계 요리사! 4
 
4.0%
Hands On 미래기술 4
 
4.0%
우리문화를 품다 4
 
4.0%
나만의 "꼼지락" 프로젝트 3
 
3.0%
Other values (20) 35
35.0%

Length

2023-12-10T19:17:40.236330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
띵가띵가 13
 
5.2%
13
 
5.2%
나무소리 13
 
5.2%
창의력을 10
 
4.0%
디자인하다 10
 
4.0%
영광군청소년오케스트라 8
 
3.2%
fly 7
 
2.8%
with 7
 
2.8%
me 7
 
2.8%
뚝딱뚝딱 7
 
2.8%
Other values (68) 157
62.3%

instt_nm
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
금왕청소년문화의집
23 
영광군청소년문화센터
8 
보령시청소년문화의집
7 
임계청소년문화의집
7 
철원종합문화복지센터
7 
Other values (21)
48 

Length

Max length21
Median length12
Mean length10.24
Min length1

Unique

Unique9 ?
Unique (%)9.0%

Sample

1st row금왕청소년문화의집
2nd row의정부시청소년문화의집
3rd row의정부시청소년문화의집
4th row의정부시청소년문화의집
5th row의정부시청소년문화의집

Common Values

ValueCountFrequency (%)
금왕청소년문화의집 23
23.0%
영광군청소년문화센터 8
 
8.0%
보령시청소년문화의집 7
 
7.0%
임계청소년문화의집 7
 
7.0%
철원종합문화복지센터 7
 
7.0%
국립청소년우주센터 5
 
5.0%
김포시청소년육성재단(사우청소년문화의집) 5
 
5.0%
의정부시청소년문화의집 4
 
4.0%
신월청소년문화센터 4
 
4.0%
아산시청소년교육문화센터 3
 
3.0%
Other values (16) 27
27.0%

Length

2023-12-10T19:17:40.442106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
금왕청소년문화의집 23
22.3%
영광군청소년문화센터 8
 
7.8%
보령시청소년문화의집 7
 
6.8%
임계청소년문화의집 7
 
6.8%
철원종합문화복지센터 7
 
6.8%
국립청소년우주센터 5
 
4.9%
김포시청소년육성재단(사우청소년문화의집 5
 
4.9%
의정부시청소년문화의집 4
 
3.9%
신월청소년문화센터 4
 
3.9%
아산시청소년교육문화센터 3
 
2.9%
Other values (19) 30
29.1%

instt_ty
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
문화의집
67 
수련관
16 
수련원
9 
청소년단체
 
3
개인사업
 
1
Other values (4)
 
4

Length

Max length20
Median length4
Mean length3.95
Min length3

Unique

Unique5 ?
Unique (%)5.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화의집 67
67.0%
수련관 16
 
16.0%
수련원 9
 
9.0%
청소년단체 3
 
3.0%
개인사업 1
 
1.0%
비영리법인 1
 
1.0%
종교기관 1
 
1.0%
영리법인 1
 
1.0%
세상을 사랑하자)-초등학교/1박2일- 1
 
1.0%

Length

2023-12-10T19:17:40.664417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:40.874422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화의집 67
66.3%
수련관 16
 
15.8%
수련원 9
 
8.9%
청소년단체 3
 
3.0%
개인사업 1
 
1.0%
비영리법인 1
 
1.0%
종교기관 1
 
1.0%
영리법인 1
 
1.0%
세상을 1
 
1.0%
사랑하자)-초등학교/1박2일 1
 
1.0%

act_ty
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
기본형-회기
70 
기본형-당일
15 
숙박형
 
6
기본형-당일(식사포함)
 
4
학교단체형
 
4

Length

Max length12
Median length6
Mean length6.04
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row기본형-회기
2nd row기본형-회기
3rd row기본형-회기
4th row기본형-회기
5th row기본형-회기

Common Values

ValueCountFrequency (%)
기본형-회기 70
70.0%
기본형-당일 15
 
15.0%
숙박형 6
 
6.0%
기본형-당일(식사포함) 4
 
4.0%
학교단체형 4
 
4.0%
성이시돌젊음의집 1
 
1.0%

Length

2023-12-10T19:17:41.070375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:41.209773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기본형-회기 70
70.0%
기본형-당일 15
 
15.0%
숙박형 6
 
6.0%
기본형-당일(식사포함 4
 
4.0%
학교단체형 4
 
4.0%
성이시돌젊음의집 1
 
1.0%

partcpt_nmpr
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
11
14 
7
10 
20
9 
35
8 
4
8 
Other values (22)
51 

Length

Max length3
Median length2
Mean length1.78
Min length1

Unique

Unique13 ?
Unique (%)13.0%

Sample

1st row11
2nd row12
3rd row12
4th row12
5th row12

Common Values

ValueCountFrequency (%)
11 14
14.0%
7 10
10.0%
20 9
 
9.0%
35 8
 
8.0%
4 8
 
8.0%
2 7
 
7.0%
10 6
 
6.0%
15 6
 
6.0%
13 5
 
5.0%
6 4
 
4.0%
Other values (17) 23
23.0%

Length

2023-12-10T19:17:41.385263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11 14
14.0%
7 10
10.0%
20 9
 
9.0%
35 8
 
8.0%
4 8
 
8.0%
2 7
 
7.0%
10 6
 
6.0%
15 6
 
6.0%
13 5
 
5.0%
6 4
 
4.0%
Other values (17) 23
23.0%

sttus
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
승인
69 
제출
14 
보완완료
13 
보완요청
 
3
숙박형
 
1

Length

Max length4
Median length2
Mean length2.33
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row보완완료
2nd row제출
3rd row제출
4th row제출
5th row제출

Common Values

ValueCountFrequency (%)
승인 69
69.0%
제출 14
 
14.0%
보완완료 13
 
13.0%
보완요청 3
 
3.0%
숙박형 1
 
1.0%

Length

2023-12-10T19:17:41.589310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:41.751750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
승인 69
69.0%
제출 14
 
14.0%
보완완료 13
 
13.0%
보완요청 3
 
3.0%
숙박형 1
 
1.0%

actpd_begin_ymd
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19989062
Minimum83
Maximum20191127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:17:41.974085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum83
5-th percentile20190309
Q120190920
median20191102
Q320191116
95-th percentile20191125
Maximum20191127
Range20191044
Interquartile range (IQR)196

Descriptive statistics

Standard deviation2019088.8
Coefficient of variation (CV)0.10100968
Kurtosis99.999997
Mean19989062
Median Absolute Deviation (MAD)24
Skewness-9.9999998
Sum1.9989062 × 109
Variance4.0767195 × 1012
MonotonicityNot monotonic
2023-12-10T19:17:42.449638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20190830 13
13.0%
20191102 10
10.0%
20190920 10
10.0%
20190309 8
 
8.0%
20191116 8
 
8.0%
20191109 8
 
8.0%
20190928 7
 
7.0%
20191001 7
 
7.0%
20191120 4
 
4.0%
20191107 4
 
4.0%
Other values (10) 21
21.0%
ValueCountFrequency (%)
83 1
 
1.0%
20190309 8
8.0%
20190830 13
13.0%
20190920 10
10.0%
20190928 7
7.0%
20191001 7
7.0%
20191102 10
10.0%
20191107 4
 
4.0%
20191109 8
8.0%
20191110 3
 
3.0%
ValueCountFrequency (%)
20191127 4
4.0%
20191125 3
 
3.0%
20191123 2
 
2.0%
20191122 2
 
2.0%
20191121 2
 
2.0%
20191120 4
4.0%
20191119 2
 
2.0%
20191116 8
8.0%
20191115 1
 
1.0%
20191113 1
 
1.0%

actpd_end_ymd
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191123
27 
20191116
17 
20191122
15 
20191119
13 
20191115
7 
Other values (7)
21 

Length

Max length8
Median length8
Mean length7.94
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row20191119
2nd row20191123
3rd row20191123
4th row20191123
5th row20191123

Common Values

ValueCountFrequency (%)
20191123 27
27.0%
20191116 17
17.0%
20191122 15
15.0%
20191119 13
13.0%
20191115 7
 
7.0%
20191128 6
 
6.0%
20191127 4
 
4.0%
20191124 4
 
4.0%
20191126 3
 
3.0%
20191120 2
 
2.0%
Other values (2) 2
 
2.0%

Length

2023-12-10T19:17:42.629961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20191123 27
27.0%
20191116 17
17.0%
20191122 15
15.0%
20191119 13
13.0%
20191115 7
 
7.0%
20191128 6
 
6.0%
20191127 4
 
4.0%
20191124 4
 
4.0%
20191126 3
 
3.0%
20191120 2
 
2.0%
Other values (2) 2
 
2.0%

act_time
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
18시간
17 
16시간
15 
24시간
13 
8시간
11 
6시간
9 
Other values (11)
35 

Length

Max length8
Median length4
Mean length3.86
Min length3

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row24시간
2nd row8.3시간
3rd row8.3시간
4th row8.3시간
5th row8.3시간

Common Values

ValueCountFrequency (%)
18시간 17
17.0%
16시간 15
15.0%
24시간 13
13.0%
8시간 11
11.0%
6시간 9
9.0%
10시간 8
8.0%
3시간 6
 
6.0%
7.5시간 5
 
5.0%
8.3시간 4
 
4.0%
7시간 3
 
3.0%
Other values (6) 9
9.0%

Length

2023-12-10T19:17:42.802451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
18시간 17
17.0%
16시간 15
15.0%
24시간 13
13.0%
8시간 11
11.0%
6시간 9
9.0%
10시간 8
8.0%
3시간 6
 
6.0%
7.5시간 5
 
5.0%
8.3시간 4
 
4.0%
7시간 3
 
3.0%
Other values (6) 9
9.0%

schul_nm
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing86
Missing (%)86.0%
Memory size932.0 B
2023-12-10T19:17:43.062888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length8
Mean length6.5
Min length3

Characters and Unicode

Total characters91
Distinct characters44
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

Unique14 ?
Unique (%)100.0%

Sample

1st row천안부대초등학교
2nd row염산중학교
3rd row도제원초등학교
4th row마장중학교
5th row서울체육고
ValueCountFrequency (%)
천안부대초등학교 1
 
7.1%
염산중학교 1
 
7.1%
도제원초등학교 1
 
7.1%
마장중학교 1
 
7.1%
서울체육고 1
 
7.1%
자은초등학교 1
 
7.1%
충북대학교사범대학부설고등학교 1
 
7.1%
가야초등학교 1
 
7.1%
목포영화중학교 1
 
7.1%
20191120 1
 
7.1%
Other values (4) 4
28.6%
2023-12-10T19:17:43.561689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 13
 
14.3%
교 12
 
13.2%
등 7
 
7.7%
초 6
 
6.6%
중 5
 
5.5%
1 3
 
3.3%
대 3
 
3.3%
2 2
 
2.2%
고 2
 
2.2%
원 2
 
2.2%
Other values (34) 36
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83
91.2%
Decimal Number 8
 
8.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 13
15.7%
교 12
 
14.5%
등 7
 
8.4%
초 6
 
7.2%
중 5
 
6.0%
대 3
 
3.6%
고 2
 
2.4%
원 2
 
2.4%
부 2
 
2.4%
목 1
 
1.2%
Other values (30) 30
36.1%
Decimal Number
ValueCountFrequency (%)
1 3
37.5%
2 2
25.0%
0 2
25.0%
9 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83
91.2%
Common 8
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 13
15.7%
교 12
 
14.5%
등 7
 
8.4%
초 6
 
7.2%
중 5
 
6.0%
대 3
 
3.6%
고 2
 
2.4%
원 2
 
2.4%
부 2
 
2.4%
목 1
 
1.2%
Other values (30) 30
36.1%
Common
ValueCountFrequency (%)
1 3
37.5%
2 2
25.0%
0 2
25.0%
9 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83
91.2%
ASCII 8
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 13
15.7%
교 12
 
14.5%
등 7
 
8.4%
초 6
 
7.2%
중 5
 
6.0%
대 3
 
3.6%
고 2
 
2.4%
원 2
 
2.4%
부 2
 
2.4%
목 1
 
1.2%
Other values (30) 30
36.1%
ASCII
ValueCountFrequency (%)
1 3
37.5%
2 2
25.0%
0 2
25.0%
9 1
 
12.5%

schul_area_nm
Text

MISSING 

Distinct8
Distinct (%)61.5%
Missing87
Missing (%)87.0%
Memory size932.0 B
2023-12-10T19:17:43.799272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0769231
Min length3

Characters and Unicode

Total characters53
Distinct characters20
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

Unique4 ?
Unique (%)30.8%

Sample

1st row충청남도
2nd row전라남도
3rd row경기도
4th row서울특별시
5th row경상남도
ValueCountFrequency (%)
경상남도 3
23.1%
전라남도 2
15.4%
충청북도 2
15.4%
광주광역시 2
15.4%
충청남도 1
 
7.7%
경기도 1
 
7.7%
서울특별시 1
 
7.7%
8시간 1
 
7.7%
2023-12-10T19:17:44.240341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 9
17.0%
남 6
11.3%
경 4
 
7.5%
광 4
 
7.5%
시 4
 
7.5%
충 3
 
5.7%
청 3
 
5.7%
상 3
 
5.7%
역 2
 
3.8%
주 2
 
3.8%
Other values (10) 13
24.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52
98.1%
Decimal Number 1
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 9
17.3%
남 6
11.5%
경 4
 
7.7%
광 4
 
7.7%
시 4
 
7.7%
충 3
 
5.8%
청 3
 
5.8%
상 3
 
5.8%
역 2
 
3.8%
주 2
 
3.8%
Other values (9) 12
23.1%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52
98.1%
Common 1
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 9
17.3%
남 6
11.5%
경 4
 
7.7%
광 4
 
7.7%
시 4
 
7.7%
충 3
 
5.8%
청 3
 
5.8%
상 3
 
5.8%
역 2
 
3.8%
주 2
 
3.8%
Other values (9) 12
23.1%
Common
ValueCountFrequency (%)
8 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52
98.1%
ASCII 1
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 9
17.3%
남 6
11.5%
경 4
 
7.7%
광 4
 
7.7%
시 4
 
7.7%
충 3
 
5.8%
청 3
 
5.8%
상 3
 
5.8%
역 2
 
3.8%
주 2
 
3.8%
Other values (9) 12
23.1%
ASCII
ValueCountFrequency (%)
8 1
100.0%

insrnc_sbscrb_at
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
N
51 
Y
48 
대정초등학교
 
1

Length

Max length6
Median length1
Mean length1.05
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 51
51.0%
Y 48
48.0%
대정초등학교 1
 
1.0%

Length

2023-12-10T19:17:44.460726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:44.634898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 51
51.0%
y 48
48.0%
대정초등학교 1
 
1.0%

insrnc_occrrnc_at
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
N
98 
Y
 
1
제주특별자치도
 
1

Length

Max length7
Median length1
Mean length1.06
Min length1

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 98
98.0%
Y 1
 
1.0%
제주특별자치도 1
 
1.0%

Length

2023-12-10T19:17:44.806393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:44.983056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 98
98.0%
y 1
 
1.0%
제주특별자치도 1
 
1.0%

nsrnc_cn
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing98
Missing (%)98.0%
Memory size932.0 B
2023-12-10T19:17:45.095474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length1.5
Mean length1.5
Min length1

Characters and Unicode

Total characters3
Distinct characters3
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

Unique2 ?
Unique (%)100.0%

Sample

1st row기타
2nd rowY
ValueCountFrequency (%)
기타 1
50.0%
y 1
50.0%
2023-12-10T19:17:45.399565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1
33.3%
타 1
33.3%
Y 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
66.7%
Uppercase Letter 1
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
66.7%
Latin 1
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%
Latin
ValueCountFrequency (%)
Y 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
66.7%
ASCII 1
33.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%
ASCII
ValueCountFrequency (%)
Y 1
100.0%

nsrnc_process_cn
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing98
Missing (%)98.0%
Memory size932.0 B
2023-12-10T19:17:45.541915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3
Min length1

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
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 row병원 이송
2nd rowN
ValueCountFrequency (%)
병원 1
33.3%
이송 1
33.3%
n 1
33.3%
2023-12-10T19:17:45.929363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
병 1
16.7%
원 1
16.7%
1
16.7%
이 1
16.7%
송 1
16.7%
N 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
66.7%
Space Separator 1
 
16.7%
Uppercase Letter 1
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
병 1
25.0%
원 1
25.0%
이 1
25.0%
송 1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
66.7%
Common 1
 
16.7%
Latin 1
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
병 1
25.0%
원 1
25.0%
이 1
25.0%
송 1
25.0%
Common
ValueCountFrequency (%)
1
100.0%
Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
66.7%
ASCII 2
33.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
병 1
25.0%
원 1
25.0%
이 1
25.0%
송 1
25.0%
ASCII
ValueCountFrequency (%)
1
50.0%
N 1
50.0%

dgnss_result_cn
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing99
Missing (%)99.0%
Memory size932.0 B
2023-12-10T19:17:46.120989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row전치 3주 미만
ValueCountFrequency (%)
전치 1
33.3%
3주 1
33.3%
미만 1
33.3%
2023-12-10T19:17:46.485215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
25.0%
전 1
12.5%
치 1
12.5%
3 1
12.5%
주 1
12.5%
미 1
12.5%
만 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
62.5%
Space Separator 2
 
25.0%
Decimal Number 1
 
12.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 1
20.0%
치 1
20.0%
주 1
20.0%
미 1
20.0%
만 1
20.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
62.5%
Common 3
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 1
20.0%
치 1
20.0%
주 1
20.0%
미 1
20.0%
만 1
20.0%
Common
ValueCountFrequency (%)
2
66.7%
3 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
62.5%
ASCII 3
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
66.7%
3 1
33.3%
Hangul
ValueCountFrequency (%)
전 1
20.0%
치 1
20.0%
주 1
20.0%
미 1
20.0%
만 1
20.0%

presentn_ymd
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191129
38 
20191127
26 
20191126
22 
20191128
13 
<NA>
 
1

Length

Max length8
Median length8
Mean length7.96
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row20191129
2nd row20191129
3rd row20191129
4th row20191129
5th row20191129

Common Values

ValueCountFrequency (%)
20191129 38
38.0%
20191127 26
26.0%
20191126 22
22.0%
20191128 13
 
13.0%
<NA> 1
 
1.0%

Length

2023-12-10T19:17:46.668772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:46.839801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20191129 38
38.0%
20191127 26
26.0%
20191126 22
22.0%
20191128 13
 
13.0%
na 1
 
1.0%

confm_ymd
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
31 
20191127
22 
20191126
20 
20191129
18 
20191128
9 

Length

Max length8
Median length8
Mean length6.76
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 31
31.0%
20191127 22
22.0%
20191126 20
20.0%
20191129 18
18.0%
20191128 9
 
9.0%

Length

2023-12-10T19:17:47.028876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:47.198598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
31.0%
20191127 22
22.0%
20191126 20
20.0%
20191129 18
18.0%
20191128 9
 
9.0%

Interactions

2023-12-10T19:17:38.832345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:17:47.334528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
area_nmact_nminstt_nminstt_tyact_typartcpt_nmprsttusactpd_begin_ymdactpd_end_ymdact_timeschul_nmschul_area_nminsrnc_sbscrb_atinsrnc_occrrnc_atnsrnc_cnnsrnc_process_cnpresentn_ymdconfm_ymd
area_nm1.0001.0001.0000.7560.7980.9680.7950.4150.8810.9191.0001.0000.7540.3220.0000.0000.9000.862
act_nm1.0001.0001.0001.0001.0000.9931.0001.0000.9881.0001.0000.9681.0001.0000.0000.0000.9971.000
instt_nm1.0001.0001.0001.0001.0000.9840.9621.0000.9640.9921.0000.9600.9911.0000.0000.0000.9930.985
instt_ty0.7561.0001.0001.0000.9320.9670.7191.0000.8360.9441.0000.8430.9520.9410.0000.0000.7980.638
act_ty0.7981.0001.0000.9321.0000.9760.7121.0000.9310.9461.0000.9930.9690.9660.0000.0000.3290.312
partcpt_nmpr0.9680.9930.9840.9670.9761.0000.9631.0000.9750.9791.0001.0000.9971.0000.0000.0000.9500.995
sttus0.7951.0000.9620.7190.7120.9631.0001.0000.9310.9681.0001.0000.8090.7080.0000.0000.797NaN
actpd_begin_ymd0.4151.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.000NaNNaN
actpd_end_ymd0.8810.9880.9640.8360.9310.9750.9311.0001.0000.9401.0000.5780.9770.9200.0000.0000.7380.685
act_time0.9191.0000.9920.9440.9460.9790.9681.0000.9401.0001.0000.8100.9571.0000.0000.0000.8410.909
schul_nm1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0001.0001.000
schul_area_nm1.0000.9680.9600.8430.9931.0001.0001.0000.5780.8101.0001.0001.0001.0000.0000.0000.7460.191
insrnc_sbscrb_at0.7541.0000.9910.9520.9690.9970.8091.0000.9770.9571.0001.0001.0000.9410.0000.0000.9270.835
insrnc_occrrnc_at0.3221.0001.0000.9410.9661.0000.7081.0000.9201.0001.0001.0000.9411.0000.0000.0000.0000.000
nsrnc_cn0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.000NaNNaN
nsrnc_process_cn0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000NaNNaN
presentn_ymd0.9000.9970.9930.7980.3290.9500.797NaN0.7380.8411.0000.7460.9270.000NaNNaN1.0000.980
confm_ymd0.8621.0000.9850.6380.3120.995NaNNaN0.6850.9091.0000.1910.8350.000NaNNaN0.9801.000
2023-12-10T19:17:47.553139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
area_nmact_nmact_tyinstt_nmconfm_ymdsttuspresentn_ymdactpd_end_ymdinsrnc_occrrnc_atinsrnc_sbscrb_atinstt_typartcpt_nmpract_time
area_nm1.0000.8870.5570.9120.6820.5770.7660.6080.1880.5850.4670.7300.660
act_nm0.8871.0000.8630.9730.8150.8580.8500.7840.8490.8490.8770.8490.913
act_ty0.5570.8631.0000.8870.2560.5750.2720.6180.7630.7710.7590.7670.782
instt_nm0.9120.9730.8871.0000.8190.7490.8630.7150.8730.8530.9020.7740.862
confm_ymd0.6820.8150.2560.8191.0001.0000.8070.4960.0000.6200.3170.7590.593
sttus0.5770.8580.5750.7491.0001.0000.4370.8140.6870.8230.5100.7520.846
presentn_ymd0.7660.8500.2720.8630.8070.4371.0000.5300.0000.7480.4540.7250.620
actpd_end_ymd0.6080.7840.6180.7150.4960.8140.5301.0000.6530.7810.5430.7510.692
insrnc_occrrnc_at0.1880.8490.7630.8730.0000.6870.0000.6531.0000.7030.6930.8680.931
insrnc_sbscrb_at0.5850.8490.7710.8530.6200.8230.7480.7810.7031.0000.7170.8130.850
instt_ty0.4670.8770.7590.9020.3170.5100.4540.5430.6930.7171.0000.6560.755
partcpt_nmpr0.7300.8490.7670.7740.7590.7520.7250.7510.8680.8130.6561.0000.759
act_time0.6600.9130.7820.8620.5930.8460.6200.6920.9310.8500.7550.7591.000
2023-12-10T19:17:47.784122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
actpd_begin_ymdarea_nmact_nminstt_nminstt_tyact_typartcpt_nmprsttusactpd_end_ymdact_timeinsrnc_sbscrb_atinsrnc_occrrnc_atpresentn_ymdconfm_ymd
actpd_begin_ymd1.0000.3780.8450.8690.9640.9790.8630.9850.9480.9260.9950.9951.0001.000
area_nm0.3781.0000.8870.9120.4670.5570.7300.5770.6080.6600.5850.1880.7660.682
act_nm0.8450.8871.0000.9730.8770.8630.8490.8580.7840.9130.8490.8490.8500.815
instt_nm0.8690.9120.9731.0000.9020.8870.7740.7490.7150.8620.8530.8730.8630.819
instt_ty0.9640.4670.8770.9021.0000.7590.6560.5100.5430.7550.7170.6930.4540.317
act_ty0.9790.5570.8630.8870.7591.0000.7670.5750.6180.7820.7710.7630.2720.256
partcpt_nmpr0.8630.7300.8490.7740.6560.7671.0000.7520.7510.7590.8130.8680.7250.759
sttus0.9850.5770.8580.7490.5100.5750.7521.0000.8140.8460.8230.6870.4371.000
actpd_end_ymd0.9480.6080.7840.7150.5430.6180.7510.8141.0000.6920.7810.6530.5300.496
act_time0.9260.6600.9130.8620.7550.7820.7590.8460.6921.0000.8500.9310.6200.593
insrnc_sbscrb_at0.9950.5850.8490.8530.7170.7710.8130.8230.7810.8501.0000.7030.7480.620
insrnc_occrrnc_at0.9950.1880.8490.8730.6930.7630.8680.6870.6530.9310.7031.0000.0000.000
presentn_ymd1.0000.7660.8500.8630.4540.2720.7250.4370.5300.6200.7480.0001.0000.807
confm_ymd1.0000.6820.8150.8190.3170.2560.7591.0000.4960.5930.6200.0000.8071.000

Missing values

2023-12-10T19:17:39.071846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:17:39.502189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-10T19:17:39.769556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

area_nmact_nminstt_nminstt_tyact_typartcpt_nmprsttusactpd_begin_ymdactpd_end_ymdact_timeschul_nmschul_area_nminsrnc_sbscrb_atinsrnc_occrrnc_atnsrnc_cnnsrnc_process_cndgnss_result_cnpresentn_ymdconfm_ymd
0충청북도띵가띵가 나무소리금왕청소년문화의집문화의집기본형-회기11보완완료201908302019111924시간<NA><NA>NN<NA><NA><NA>20191129<NA>
1경기도내 꿈은 세계 요리사!의정부시청소년문화의집문화의집기본형-회기12제출20191102201911238.3시간<NA><NA>NN<NA><NA><NA>20191129<NA>
2경기도내 꿈은 세계 요리사!의정부시청소년문화의집문화의집기본형-회기12제출20191102201911238.3시간<NA><NA>NN<NA><NA><NA>20191129<NA>
3경기도내 꿈은 세계 요리사!의정부시청소년문화의집문화의집기본형-회기12제출20191102201911238.3시간<NA><NA>NN<NA><NA><NA>20191129<NA>
4경기도내 꿈은 세계 요리사!의정부시청소년문화의집문화의집기본형-회기12제출20191102201911238.3시간<NA><NA>NN<NA><NA><NA>20191129<NA>
5충청남도우리 가족 행복 프로젝트보령시청소년문화의집문화의집기본형-회기10승인20191102201911166시간<NA><NA>YN<NA><NA><NA>2019112920191129
6충청남도우리 가족 행복 프로젝트보령시청소년문화의집문화의집기본형-회기10승인20191102201911166시간<NA><NA>YN<NA><NA><NA>2019112920191129
7충청남도유관순과 함께 떠나는 VR역사탐방대천안시태조산청소년수련관수련관기본형-당일20보완요청20191127201911273시간천안부대초등학교충청남도NN<NA><NA><NA>20191129<NA>
8충청남도우리문화를 품다보령시청소년문화의집문화의집기본형-회기6승인20191107201911288시간<NA><NA>NN<NA><NA><NA>2019112920191129
9충청남도우리문화를 품다보령시청소년문화의집문화의집기본형-회기6승인20191107201911288시간<NA><NA>NN<NA><NA><NA>2019112920191129
area_nmact_nminstt_nminstt_tyact_typartcpt_nmprsttusactpd_begin_ymdactpd_end_ymdact_timeschul_nmschul_area_nminsrnc_sbscrb_atinsrnc_occrrnc_atnsrnc_cnnsrnc_process_cndgnss_result_cnpresentn_ymdconfm_ymd
90강원도Fly with Me임계청소년문화의집문화의집기본형-회기2승인201910012019111518시간<NA><NA>YN<NA><NA><NA>2019112620191126
91강원도뚝딱뚝딱 로봇창의활동(초급)철원종합문화복지센터수련관기본형-당일4승인201909282019112316시간<NA><NA>YN<NA><NA><NA>2019112620191126
92강원도Fly with Me임계청소년문화의집문화의집기본형-회기2승인201910012019111518시간<NA><NA>YN<NA><NA><NA>2019112620191126
93대구광역시골드헌터달성군청소년센터수련관기본형-당일(식사포함)20보완요청20191120201911205시간<NA><NA>NN<NA><NA><NA>20191126<NA>
94강원도Fly with Me임계청소년문화의집문화의집기본형-회기2승인201910012019111518시간<NA><NA>YN<NA><NA><NA>2019112620191126
95강원도뚝딱뚝딱 로봇창의활동(초급)철원종합문화복지센터수련관기본형-당일4승인201909282019112316시간<NA><NA>YN<NA><NA><NA>2019112620191126
96강원도Fly with Me임계청소년문화의집문화의집기본형-회기2승인201910012019111518시간<NA><NA>YN<NA><NA><NA>2019112620191126
97강원도뚝딱뚝딱 로봇창의활동(초급)철원종합문화복지센터수련관기본형-당일4승인201909282019112316시간<NA><NA>YN<NA><NA><NA>2019112620191126
98강원도뚝딱뚝딱 로봇창의활동(초급)철원종합문화복지센터수련관기본형-당일4승인201909282019112316시간<NA><NA>YN<NA><NA><NA>2019112620191126
99광주광역시초등 인성수련 우린멋쟁이광주광역시청소년수련원수련원학교단체형260승인201911212019112210시간조봉초등학교광주광역시YN<NA><NA><NA>2019112620191126

Duplicate rows

Most frequently occurring

area_nmact_nminstt_nminstt_tyact_typartcpt_nmprsttusactpd_begin_ymdactpd_end_ymdact_timeschul_nmschul_area_nminsrnc_sbscrb_atinsrnc_occrrnc_atnsrnc_cnnsrnc_process_cndgnss_result_cnpresentn_ymdconfm_ymd# duplicates
14충청북도띵가띵가 나무소리금왕청소년문화의집문화의집기본형-회기11보완완료201908302019111924시간<NA><NA>NN<NA><NA><NA>20191129<NA>13
15충청북도창의력을 디자인하다!금왕청소년문화의집문화의집기본형-회기7제출201909202019112218시간<NA><NA>NN<NA><NA><NA>20191129<NA>10
9전라남도영광군청소년오케스트라영광군청소년문화센터문화의집기본형-회기35승인201903092019111616시간<NA><NA>YN<NA><NA><NA>20191127201911278
0강원도Fly with Me임계청소년문화의집문화의집기본형-회기2승인201910012019111518시간<NA><NA>YN<NA><NA><NA>20191126201911267
1강원도뚝딱뚝딱 로봇창의활동(초급)철원종합문화복지센터수련관기본형-당일4승인201909282019112316시간<NA><NA>YN<NA><NA><NA>20191126201911267
3경기도스페셜코더김포시청소년육성재단(사우청소년문화의집)문화의집기본형-회기13승인201911092019112310시간<NA><NA>YN<NA><NA><NA>20191127201911275
2경기도내 꿈은 세계 요리사!의정부시청소년문화의집문화의집기본형-회기12제출20191102201911238.3시간<NA><NA>NN<NA><NA><NA>20191129<NA>4
13충청남도우리문화를 품다보령시청소년문화의집문화의집기본형-회기6승인20191107201911288시간<NA><NA>NN<NA><NA><NA>20191129201911294
4경기도창의로봇교실김포시청소년육성재단(통진청소년문화의집)문화의집기본형-회기20승인20191116201911236시간<NA><NA>NN<NA><NA><NA>20191127201911273
5경기도향기팩토리양촌청소년문화의집문화의집기본형-당일20승인20191116201911237.5시간<NA><NA>YN<NA><NA><NA>20191127201911273