Overview

Dataset statistics

Number of variables6
Number of observations30
Missing cells26
Missing cells (%)14.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory52.4 B

Variable types

Unsupported1
Text5

Alerts

Unnamed: 1 has 26 (86.7%) missing valuesMissing
Unnamed: 3 has unique valuesUnique
Unnamed: 4 has unique valuesUnique
박물관 현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:26:19.935855
Analysis finished2024-03-14 02:26:20.529337
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

박물관 현황
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size372.0 B

Unnamed: 1
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing26
Missing (%)86.7%
Memory size372.0 B
2024-03-14T11:26:20.615213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters8
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

Unique4 ?
Unique (%)100.0%

Sample

1st row구분
2nd row공립
3rd row사립
4th row대학
ValueCountFrequency (%)
구분 1
25.0%
공립 1
25.0%
사립 1
25.0%
대학 1
25.0%
2024-03-14T11:26:20.828513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
립 2
25.0%
구 1
12.5%
분 1
12.5%
공 1
12.5%
사 1
12.5%
대 1
12.5%
학 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
립 2
25.0%
구 1
12.5%
분 1
12.5%
공 1
12.5%
사 1
12.5%
대 1
12.5%
학 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
립 2
25.0%
구 1
12.5%
분 1
12.5%
공 1
12.5%
사 1
12.5%
대 1
12.5%
학 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
립 2
25.0%
구 1
12.5%
분 1
12.5%
공 1
12.5%
사 1
12.5%
대 1
12.5%
학 1
12.5%

Unnamed: 2
Text

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-14T11:26:21.002023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.0666667
Min length3

Characters and Unicode

Total characters242
Distinct characters17
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)76.7%

Sample

1st row등록일
2nd row‘90.10.26
3rd row‘96.11.22
4th row‘02.10.15
5th row‘06.3.20
ValueCountFrequency (%)
13.1.3 3
 
9.4%
12.2.8 2
 
6.2%
‘00.12.30 2
 
6.2%
‘03.2.27 1
 
3.1%
‘02.10.15 1
 
3.1%
‘96.11.22 1
 
3.1%
‘00.11.20 1
 
3.1%
‘01.9.27 1
 
3.1%
‘13.8.29 1
 
3.1%
‘13.5.14 1
 
3.1%
Other values (18) 18
56.2%
2024-03-14T11:26:21.277280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 58
24.0%
1 40
16.5%
0 28
11.6%
2 25
10.3%
‘ 23
 
9.5%
3 15
 
6.2%
9 9
 
3.7%
6 8
 
3.3%
8 7
 
2.9%
' 6
 
2.5%
Other values (7) 23
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148
61.2%
Other Punctuation 64
26.4%
Initial Punctuation 23
 
9.5%
Space Separator 4
 
1.7%
Other Letter 3
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 40
27.0%
0 28
18.9%
2 25
16.9%
3 15
 
10.1%
9 9
 
6.1%
6 8
 
5.4%
8 7
 
4.7%
7 6
 
4.1%
5 6
 
4.1%
4 4
 
2.7%
Other Letter
ValueCountFrequency (%)
등 1
33.3%
록 1
33.3%
일 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 58
90.6%
' 6
 
9.4%
Initial Punctuation
ValueCountFrequency (%)
‘ 23
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 239
98.8%
Hangul 3
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 58
24.3%
1 40
16.7%
0 28
11.7%
2 25
10.5%
‘ 23
 
9.6%
3 15
 
6.3%
9 9
 
3.8%
6 8
 
3.3%
8 7
 
2.9%
' 6
 
2.5%
Other values (4) 20
 
8.4%
Hangul
ValueCountFrequency (%)
등 1
33.3%
록 1
33.3%
일 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216
89.3%
Punctuation 23
 
9.5%
Hangul 3
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 58
26.9%
1 40
18.5%
0 28
13.0%
2 25
11.6%
3 15
 
6.9%
9 9
 
4.2%
6 8
 
3.7%
8 7
 
3.2%
' 6
 
2.8%
7 6
 
2.8%
Other values (3) 14
 
6.5%
Punctuation
ValueCountFrequency (%)
‘ 23
100.0%
Hangul
ValueCountFrequency (%)
등 1
33.3%
록 1
33.3%
일 1
33.3%

Unnamed: 3
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-14T11:26:21.458293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length10
Mean length7.9666667
Min length4

Characters and Unicode

Total characters239
Distinct characters91
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row박물관명
2nd row국립전주박물관
3rd row미륵사지유물전시관
4th row전주역사박물관
5th row익산보석박물관
ValueCountFrequency (%)
박물관명 1
 
3.2%
익산 1
 
3.2%
군산대학교박물관 1
 
3.2%
전주대학교박물관 1
 
3.2%
전북대학교박물관 1
 
3.2%
완주책박물관 1
 
3.2%
연안이씨종중문적(보물651호)박물관 1
 
3.2%
카메라영상박물관 1
 
3.2%
예수병원의학박물관 1
 
3.2%
전주한지박물관 1
 
3.2%
Other values (21) 21
67.7%
2024-03-14T11:26:21.963082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 30
 
12.6%
물 29
 
12.1%
박 27
 
11.3%
전 10
 
4.2%
학 6
 
2.5%
주 6
 
2.5%
사 6
 
2.5%
산 5
 
2.1%
원 5
 
2.1%
교 5
 
2.1%
Other values (81) 110
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 233
97.5%
Decimal Number 3
 
1.3%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 30
 
12.9%
물 29
 
12.4%
박 27
 
11.6%
전 10
 
4.3%
학 6
 
2.6%
주 6
 
2.6%
사 6
 
2.6%
산 5
 
2.1%
원 5
 
2.1%
교 5
 
2.1%
Other values (75) 104
44.6%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
5 1
33.3%
6 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 233
97.5%
Common 6
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 30
 
12.9%
물 29
 
12.4%
박 27
 
11.6%
전 10
 
4.3%
학 6
 
2.6%
주 6
 
2.6%
사 6
 
2.6%
산 5
 
2.1%
원 5
 
2.1%
교 5
 
2.1%
Other values (75) 104
44.6%
Common
ValueCountFrequency (%)
( 1
16.7%
) 1
16.7%
1 1
16.7%
5 1
16.7%
6 1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 233
97.5%
ASCII 6
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 30
 
12.9%
물 29
 
12.4%
박 27
 
11.6%
전 10
 
4.3%
학 6
 
2.6%
주 6
 
2.6%
사 6
 
2.6%
산 5
 
2.1%
원 5
 
2.1%
교 5
 
2.1%
Other values (75) 104
44.6%
ASCII
ValueCountFrequency (%)
( 1
16.7%
) 1
16.7%
1 1
16.7%
5 1
16.7%
6 1
16.7%
1
16.7%

Unnamed: 4
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-14T11:26:22.182253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length14.666667
Min length3

Characters and Unicode

Total characters440
Distinct characters92
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row주 소
2nd row전주시 완산구 효자동
3rd row익산시 금마면 미륵사지로 362
4th row전주시 완산구 쑥고개로 251
5th row익산시 왕궁면 호반로 8
ValueCountFrequency (%)
전주시 8
 
7.0%
익산시 7
 
6.1%
완산구 6
 
5.2%
순창군 2
 
1.7%
왕궁면 2
 
1.7%
완주군 2
 
1.7%
부안군 2
 
1.7%
익산대로 2
 
1.7%
군산시 2
 
1.7%
정읍시 2
 
1.7%
Other values (78) 80
69.6%
2024-03-14T11:26:22.539237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
19.5%
시 21
 
4.8%
산 19
 
4.3%
로 19
 
4.3%
1 16
 
3.6%
4 15
 
3.4%
7 12
 
2.7%
면 11
 
2.5%
주 11
 
2.5%
군 10
 
2.3%
Other values (82) 220
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 266
60.5%
Space Separator 86
 
19.5%
Decimal Number 83
 
18.9%
Dash Punctuation 5
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 21
 
7.9%
산 19
 
7.1%
로 19
 
7.1%
면 11
 
4.1%
주 11
 
4.1%
군 10
 
3.8%
익 9
 
3.4%
전 9
 
3.4%
완 8
 
3.0%
구 8
 
3.0%
Other values (70) 141
53.0%
Decimal Number
ValueCountFrequency (%)
1 16
19.3%
4 15
18.1%
7 12
14.5%
2 8
9.6%
0 7
8.4%
3 7
8.4%
5 5
 
6.0%
6 5
 
6.0%
8 4
 
4.8%
9 4
 
4.8%
Space Separator
ValueCountFrequency (%)
86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 266
60.5%
Common 174
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 21
 
7.9%
산 19
 
7.1%
로 19
 
7.1%
면 11
 
4.1%
주 11
 
4.1%
군 10
 
3.8%
익 9
 
3.4%
전 9
 
3.4%
완 8
 
3.0%
구 8
 
3.0%
Other values (70) 141
53.0%
Common
ValueCountFrequency (%)
86
49.4%
1 16
 
9.2%
4 15
 
8.6%
7 12
 
6.9%
2 8
 
4.6%
0 7
 
4.0%
3 7
 
4.0%
- 5
 
2.9%
5 5
 
2.9%
6 5
 
2.9%
Other values (2) 8
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 266
60.5%
ASCII 174
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
49.4%
1 16
 
9.2%
4 15
 
8.6%
7 12
 
6.9%
2 8
 
4.6%
0 7
 
4.0%
3 7
 
4.0%
- 5
 
2.9%
5 5
 
2.9%
6 5
 
2.9%
Other values (2) 8
 
4.6%
Hangul
ValueCountFrequency (%)
시 21
 
7.9%
산 19
 
7.1%
로 19
 
7.1%
면 11
 
4.1%
주 11
 
4.1%
군 10
 
3.8%
익 9
 
3.4%
전 9
 
3.4%
완 8
 
3.0%
구 8
 
3.0%
Other values (70) 141
53.0%

Unnamed: 5
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-14T11:26:22.807264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length7.3
Min length1

Characters and Unicode

Total characters219
Distinct characters14
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

Unique27 ?
Unique (%)90.0%

Sample

1st row연락처
2nd row223-5651
3rd row836-7804
4th row281-2306
5th row850-4981
ValueCountFrequency (%)
3
 
10.0%
연락처 1
 
3.3%
223-5651 1
 
3.3%
469-4191 1
 
3.3%
220-2158 1
 
3.3%
270-3488 1
 
3.3%
070-8915-8132 1
 
3.3%
852-7277 1
 
3.3%
563-6600 1
 
3.3%
230-8828 1
 
3.3%
Other values (18) 18
60.0%
2024-03-14T11:26:23.065042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 30
13.7%
2 28
12.8%
8 26
11.9%
0 25
11.4%
5 21
9.6%
3 17
7.8%
6 17
7.8%
4 14
6.4%
1 14
6.4%
7 12
 
5.5%
Other values (4) 15
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 186
84.9%
Dash Punctuation 30
 
13.7%
Other Letter 3
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 28
15.1%
8 26
14.0%
0 25
13.4%
5 21
11.3%
3 17
9.1%
6 17
9.1%
4 14
7.5%
1 14
7.5%
7 12
6.5%
9 12
6.5%
Other Letter
ValueCountFrequency (%)
연 1
33.3%
락 1
33.3%
처 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216
98.6%
Hangul 3
 
1.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 30
13.9%
2 28
13.0%
8 26
12.0%
0 25
11.6%
5 21
9.7%
3 17
7.9%
6 17
7.9%
4 14
6.5%
1 14
6.5%
7 12
 
5.6%
Hangul
ValueCountFrequency (%)
연 1
33.3%
락 1
33.3%
처 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216
98.6%
Hangul 3
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 30
13.9%
2 28
13.0%
8 26
12.0%
0 25
11.6%
5 21
9.7%
3 17
7.9%
6 17
7.9%
4 14
6.5%
1 14
6.5%
7 12
 
5.6%
Hangul
ValueCountFrequency (%)
연 1
33.3%
락 1
33.3%
처 1
33.3%

Correlations

2024-03-14T11:26:23.152366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
Unnamed: 11.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.0001.000
Unnamed: 51.0001.0001.0001.0001.000

Missing values

2024-03-14T11:26:20.319047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:26:20.492817image/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

박물관 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
0연번구분등록일박물관명주 소연락처
11공립‘90.10.26국립전주박물관전주시 완산구 효자동223-5651
22<NA>‘96.11.22미륵사지유물전시관익산시 금마면 미륵사지로 362836-7804
33<NA>‘02.10.15전주역사박물관전주시 완산구 쑥고개로 251281-2306
44<NA>‘06.3.20익산보석박물관익산시 왕궁면 호반로 8850-4981
55<NA>‘06.11. 1남원향토박물관전북 남원시 양림길 14-9620-6792
66<NA>‘06.12.15벽골제농경문화박물관김제시 부량면 벽골제로 442540-3225
77<NA>‘05.4.28고창판소리박물관고창군 고창읍 읍내리 동리로 100560-2761
88<NA>‘08.08.19전주전통술박물관전주시 완산구 최명희길 74287-6305
99<NA>‘08.2.15왕궁리유적전시관익산시 왕궁면 궁성로 670859-4632
박물관 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
2020<NA>‘06. 9.14원숭이자연사박물관부안군 상서면 부안로 1783584-0708
2121<NA>‘07.7.31전주한지박물관전주시 덕진구 팔복로 59210-8216
2222<NA>‘09.7.30예수병원의학박물관전주시 완산구 서원로 68230-8828
2323<NA>‘09.12.16카메라영상박물관완주군 소양면 신교응암길 14563-6600
2424<NA>‘13.5.14연안이씨종중문적(보물651호)박물관익산시 삼기면 기산리 332-1번지852-7277
2525<NA>‘13.8.29완주책박물관완주군 삼례읍 후정리 247-1070-8915-8132
2626대학‘01.9.27전북대학교박물관전주시 덕진구 백제대로 567270-3488
2727<NA>‘00.11.20전주대학교박물관전주시 완산구 백마길 45220-2158
2828<NA>‘00.12.30군산대학교박물관군산시 대학로 1170469-4191
2929<NA>‘00.12.30원광대학교박물관익산시 신동 익산대로 460850-5483