Overview

Dataset statistics

Number of variables8
Number of observations144
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory66.9 B

Variable types

Numeric1
Text2
Categorical4
Boolean1

Dataset

Description제주특별자치도 민속자연사박물관 홈페이지 내 기증유물 현황입니다. 링크: http://www.jeju.go.kr/museum/relicinfo/donate/2020.htm
URLhttps://www.data.go.kr/data/15119812/fileData.do

Alerts

기증년도 has constant value ""Constant
썸네일유무 has constant value ""Constant
데이터기준일자 has constant value ""Constant
작가명 is highly overall correlated with 수정High correlation
수정 is highly overall correlated with 일련번호 and 1 other fieldsHigh correlation
일련번호 is highly overall correlated with 수정High correlation
일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:51:14.372042
Analysis finished2023-12-11 23:51:14.965201
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2293.4375
Minimum2221
Maximum2379
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T08:51:15.056582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2221
5-th percentile2228.15
Q12256.75
median2292.5
Q32328.25
95-th percentile2371.85
Maximum2379
Range158
Interquartile range (IQR)71.5

Descriptive statistics

Standard deviation43.367307
Coefficient of variation (CV)0.018909304
Kurtosis-1.0072129
Mean2293.4375
Median Absolute Deviation (MAD)36
Skewness0.13319264
Sum330255
Variance1880.7233
MonotonicityStrictly decreasing
2023-12-12T08:51:15.215009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2379 1
 
0.7%
2291 1
 
0.7%
2271 1
 
0.7%
2270 1
 
0.7%
2269 1
 
0.7%
2268 1
 
0.7%
2267 1
 
0.7%
2266 1
 
0.7%
2265 1
 
0.7%
2264 1
 
0.7%
Other values (134) 134
93.1%
ValueCountFrequency (%)
2221 1
0.7%
2222 1
0.7%
2223 1
0.7%
2224 1
0.7%
2225 1
0.7%
2226 1
0.7%
2227 1
0.7%
2228 1
0.7%
2229 1
0.7%
2230 1
0.7%
ValueCountFrequency (%)
2379 1
0.7%
2378 1
0.7%
2377 1
0.7%
2376 1
0.7%
2375 1
0.7%
2374 1
0.7%
2373 1
0.7%
2372 1
0.7%
2371 1
0.7%
2355 1
0.7%

관리번호
Text

Distinct142
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T08:51:15.533996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length7.3055556
Min length5

Characters and Unicode

Total characters1052
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

Unique140 ?
Unique (%)97.2%

Sample

1st row12485
2nd row12484
3rd row12483
4th row12482
5th row12481
ValueCountFrequency (%)
12428 2
 
1.4%
jnp004748 2
 
1.4%
jnp004745 1
 
0.7%
jfi001507 1
 
0.7%
12431 1
 
0.7%
12432 1
 
0.7%
12433 1
 
0.7%
12434 1
 
0.7%
12435 1
 
0.7%
12436 1
 
0.7%
Other values (132) 132
91.7%
2023-12-12T08:51:16.037292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 202
19.2%
4 168
16.0%
1 94
8.9%
7 92
8.7%
2 87
8.3%
j 83
7.9%
n 80
 
7.6%
p 80
 
7.6%
8 46
 
4.4%
3 34
 
3.2%
Other values (7) 86
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 803
76.3%
Lowercase Letter 249
 
23.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 202
25.2%
4 168
20.9%
1 94
11.7%
7 92
11.5%
2 87
10.8%
8 46
 
5.7%
3 34
 
4.2%
9 30
 
3.7%
5 27
 
3.4%
6 23
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
j 83
33.3%
n 80
32.1%
p 80
32.1%
o 2
 
0.8%
f 2
 
0.8%
r 1
 
0.4%
i 1
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 803
76.3%
Latin 249
 
23.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 202
25.2%
4 168
20.9%
1 94
11.7%
7 92
11.5%
2 87
10.8%
8 46
 
5.7%
3 34
 
4.2%
9 30
 
3.7%
5 27
 
3.4%
6 23
 
2.9%
Latin
ValueCountFrequency (%)
j 83
33.3%
n 80
32.1%
p 80
32.1%
o 2
 
0.8%
f 2
 
0.8%
r 1
 
0.4%
i 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1052
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 202
19.2%
4 168
16.0%
1 94
8.9%
7 92
8.7%
2 87
8.3%
j 83
7.9%
n 80
 
7.6%
p 80
 
7.6%
8 46
 
4.4%
3 34
 
3.2%
Other values (7) 86
8.2%

이름
Text

Distinct85
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T08:51:16.414820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.6041667
Min length1

Characters and Unicode

Total characters519
Distinct characters170
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)22.9%

Sample

1st row신칼(명두.멩두)
2nd row산판
3rd row요령
4th row주머니
5th row각반
ValueCountFrequency (%)
치마 5
 
3.5%
설쇠채 4
 
2.8%
요령 3
 
2.1%
바디 3
 
2.1%
사위질빵 2
 
1.4%
저고리 2
 
1.4%
개도둑놈의갈고리 2
 
1.4%
가막살나무 2
 
1.4%
솔박 2
 
1.4%
기름새 2
 
1.4%
Other values (75) 117
81.2%
2023-12-12T08:51:16.939185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 22
 
4.2%
고 17
 
3.3%
사 14
 
2.7%
개 12
 
2.3%
가 10
 
1.9%
쇠 10
 
1.9%
풀 10
 
1.9%
바 10
 
1.9%
치 8
 
1.5%
채 8
 
1.5%
Other values (160) 398
76.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 507
97.7%
Open Punctuation 4
 
0.8%
Close Punctuation 4
 
0.8%
Other Punctuation 3
 
0.6%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 22
 
4.3%
고 17
 
3.4%
사 14
 
2.8%
개 12
 
2.4%
가 10
 
2.0%
쇠 10
 
2.0%
풀 10
 
2.0%
바 10
 
2.0%
치 8
 
1.6%
채 8
 
1.6%
Other values (156) 386
76.1%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 505
97.3%
Common 12
 
2.3%
Han 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 22
 
4.4%
고 17
 
3.4%
사 14
 
2.8%
개 12
 
2.4%
가 10
 
2.0%
쇠 10
 
2.0%
풀 10
 
2.0%
바 10
 
2.0%
치 8
 
1.6%
채 8
 
1.6%
Other values (154) 384
76.0%
Common
ValueCountFrequency (%)
( 4
33.3%
) 4
33.3%
. 3
25.0%
8 1
 
8.3%
Han
ValueCountFrequency (%)
祭 1
50.0%
服 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 505
97.3%
ASCII 12
 
2.3%
CJK 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 22
 
4.4%
고 17
 
3.4%
사 14
 
2.8%
개 12
 
2.4%
가 10
 
2.0%
쇠 10
 
2.0%
풀 10
 
2.0%
바 10
 
2.0%
치 8
 
1.6%
채 8
 
1.6%
Other values (154) 384
76.0%
ASCII
ValueCountFrequency (%)
( 4
33.3%
) 4
33.3%
. 3
25.0%
8 1
 
8.3%
CJK
ValueCountFrequency (%)
祭 1
50.0%
服 1
50.0%

작가명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
문명옥
80 
조금해
30 
조정삼
 
8
강순옥
 
4
강화수
 
3
Other values (14)
19 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique11 ?
Unique (%)7.6%

Sample

1st row강순옥
2nd row강순옥
3rd row강순옥
4th row강순옥
5th row강화수

Common Values

ValueCountFrequency (%)
문명옥 80
55.6%
조금해 30
 
20.8%
조정삼 8
 
5.6%
강순옥 4
 
2.8%
강화수 3
 
2.1%
오성수 3
 
2.1%
이좌성 3
 
2.1%
김익수 2
 
1.4%
이중보 1
 
0.7%
고영숙 1
 
0.7%
Other values (9) 9
 
6.2%

Length

2023-12-12T08:51:17.096439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
문명옥 80
55.6%
조금해 30
 
20.8%
조정삼 8
 
5.6%
강순옥 4
 
2.8%
강화수 3
 
2.1%
오성수 3
 
2.1%
이좌성 3
 
2.1%
김익수 2
 
1.4%
양영환 1
 
0.7%
양동림 1
 
0.7%
Other values (9) 9
 
6.2%

기증년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2020
144 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 144
100.0%

Length

2023-12-12T08:51:17.243426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:51:17.347081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 144
100.0%

수정
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2020-07-07
83 
2020-07-06
52 
2021-01-06
9 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01-06
2nd row2021-01-06
3rd row2021-01-06
4th row2021-01-06
5th row2021-01-06

Common Values

ValueCountFrequency (%)
2020-07-07 83
57.6%
2020-07-06 52
36.1%
2021-01-06 9
 
6.2%

Length

2023-12-12T08:51:17.473966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:51:17.605283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-07-07 83
57.6%
2020-07-06 52
36.1%
2021-01-06 9
 
6.2%

썸네일유무
Boolean

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size276.0 B
True
144 
ValueCountFrequency (%)
True 144
100.0%
2023-12-12T08:51:17.721735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-08-21
144 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-21
2nd row2023-08-21
3rd row2023-08-21
4th row2023-08-21
5th row2023-08-21

Common Values

ValueCountFrequency (%)
2023-08-21 144
100.0%

Length

2023-12-12T08:51:17.856934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:51:17.993131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-21 144
100.0%

Interactions

2023-12-12T08:51:14.687443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:51:18.052603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호이름작가명수정
일련번호1.0000.9900.8330.969
이름0.9901.0000.9970.983
작가명0.8330.9971.0001.000
수정0.9690.9831.0001.000
2023-12-12T08:51:18.162569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
작가명수정
작가명1.0000.942
수정0.9421.000
2023-12-12T08:51:18.280820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호작가명수정
일련번호1.0000.4870.950
작가명0.4871.0000.942
수정0.9500.9421.000

Missing values

2023-12-12T08:51:14.816282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:51:14.922314image/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.

Sample

일련번호관리번호이름작가명기증년도수정썸네일유무데이터기준일자
0237912485신칼(명두.멩두)강순옥20202021-01-06Y2023-08-21
1237812484산판강순옥20202021-01-06Y2023-08-21
2237712483요령강순옥20202021-01-06Y2023-08-21
3237612482주머니강순옥20202021-01-06Y2023-08-21
4237512481각반강화수20202021-01-06Y2023-08-21
5237412480두건강화수20202021-01-06Y2023-08-21
6237312479제복(祭服)강화수20202021-01-06Y2023-08-21
7237212473자물쇠오영숙20202021-01-06Y2023-08-21
8237112472바느질자양동림20202021-01-06Y2023-08-21
92355jnp004748줄사초문명옥20202020-07-07Y2023-08-21
일련번호관리번호이름작가명기증년도수정썸네일유무데이터기준일자
134223012404대양채조금해20202020-07-06Y2023-08-21
135222912403대양채조금해20202020-07-06Y2023-08-21
136222812402징조금해20202020-07-06Y2023-08-21
137222712401징조금해20202020-07-06Y2023-08-21
138222612400장구조금해20202020-07-06Y2023-08-21
139222512399회화이승현20202020-07-06Y2023-08-21
140222412398서답마께고영숙20202020-07-06Y2023-08-21
141222312397솔박고금란20202020-07-06Y2023-08-21
142222212396대당중흥송김익수20202020-07-06Y2023-08-21
143222112395소치간찰김익수20202020-07-06Y2023-08-21