Overview

Dataset statistics

Number of variables4
Number of observations852
Missing cells323
Missing cells (%)9.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.6 KiB
Average record size in memory33.2 B

Variable types

Numeric1
Text3

Dataset

Description부산광역시 부산도서관통합웹서비스플랫폼의 한국정부기관부호 정보로, 레코드키, 부호명, 참조명, 색인부호명 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15119890/fileData.do

Alerts

참조명 has 323 (37.9%) missing valuesMissing
레코드키 has unique valuesUnique
부호명 has unique valuesUnique
색인부호명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:14:28.111417
Analysis finished2023-12-12 05:14:28.801175
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

레코드키
Real number (ℝ)

UNIQUE 

Distinct852
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean426.5
Minimum1
Maximum852
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-12-12T14:14:28.888255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile43.55
Q1213.75
median426.5
Q3639.25
95-th percentile809.45
Maximum852
Range851
Interquartile range (IQR)425.5

Descriptive statistics

Standard deviation246.09551
Coefficient of variation (CV)0.57701175
Kurtosis-1.2
Mean426.5
Median Absolute Deviation (MAD)213
Skewness0
Sum363378
Variance60563
MonotonicityNot monotonic
2023-12-12T14:14:29.077140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
565 1
 
0.1%
641 1
 
0.1%
643 1
 
0.1%
644 1
 
0.1%
645 1
 
0.1%
646 1
 
0.1%
647 1
 
0.1%
648 1
 
0.1%
649 1
 
0.1%
650 1
 
0.1%
Other values (842) 842
98.8%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
852 1
0.1%
851 1
0.1%
850 1
0.1%
849 1
0.1%
848 1
0.1%
847 1
0.1%
846 1
0.1%
845 1
0.1%
844 1
0.1%
843 1
0.1%

부호명
Text

UNIQUE 

Distinct852
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2023-12-12T14:14:29.454086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length7.1279343
Min length2

Characters and Unicode

Total characters6073
Distinct characters238
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique852 ?
Unique (%)100.0%

Sample

1st row문화재관리국 지구관리사무소
2nd row서울민사지방법원
3rd row서울구치소
4th row서울과학관
5th row서울고등법원
ValueCountFrequency (%)
조달청 14
 
1.5%
철도청 12
 
1.3%
문화재관리국 9
 
1.0%
교육청 8
 
0.9%
특허청 4
 
0.4%
과학기술처 3
 
0.3%
내무부 2
 
0.2%
건설교통부 2
 
0.2%
제주도 2
 
0.2%
행정자치부 2
 
0.2%
Other values (830) 850
93.6%
2023-12-12T14:14:29.939179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 296
 
4.9%
청 261
 
4.3%
원 227
 
3.7%
지 208
 
3.4%
관 195
 
3.2%
방 182
 
3.0%
사 169
 
2.8%
국 168
 
2.8%
무 149
 
2.5%
산 119
 
2.0%
Other values (228) 4099
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5938
97.8%
Space Separator 109
 
1.8%
Decimal Number 12
 
0.2%
Other Punctuation 6
 
0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 296
 
5.0%
청 261
 
4.4%
원 227
 
3.8%
지 208
 
3.5%
관 195
 
3.3%
방 182
 
3.1%
사 169
 
2.8%
국 168
 
2.8%
무 149
 
2.5%
산 119
 
2.0%
Other values (215) 3964
66.8%
Decimal Number
ValueCountFrequency (%)
1 5
41.7%
2 3
25.0%
9 2
 
16.7%
5 1
 
8.3%
4 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 2
66.7%
[ 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 2
66.7%
] 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
I 1
50.0%
Space Separator
ValueCountFrequency (%)
109
100.0%
Other Punctuation
ValueCountFrequency (%)
· 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5938
97.8%
Common 133
 
2.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 296
 
5.0%
청 261
 
4.4%
원 227
 
3.8%
지 208
 
3.5%
관 195
 
3.3%
방 182
 
3.1%
사 169
 
2.8%
국 168
 
2.8%
무 149
 
2.5%
산 119
 
2.0%
Other values (215) 3964
66.8%
Common
ValueCountFrequency (%)
109
82.0%
· 6
 
4.5%
1 5
 
3.8%
2 3
 
2.3%
9 2
 
1.5%
( 2
 
1.5%
) 2
 
1.5%
5 1
 
0.8%
4 1
 
0.8%
] 1
 
0.8%
Latin
ValueCountFrequency (%)
A 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5938
97.8%
ASCII 129
 
2.1%
None 6
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 296
 
5.0%
청 261
 
4.4%
원 227
 
3.8%
지 208
 
3.5%
관 195
 
3.3%
방 182
 
3.1%
사 169
 
2.8%
국 168
 
2.8%
무 149
 
2.5%
산 119
 
2.0%
Other values (215) 3964
66.8%
ASCII
ValueCountFrequency (%)
109
84.5%
1 5
 
3.9%
2 3
 
2.3%
9 2
 
1.6%
( 2
 
1.6%
) 2
 
1.6%
5 1
 
0.8%
4 1
 
0.8%
A 1
 
0.8%
] 1
 
0.8%
Other values (2) 2
 
1.6%
None
ValueCountFrequency (%)
· 6
100.0%

참조명
Text

MISSING 

Distinct142
Distinct (%)26.8%
Missing323
Missing (%)37.9%
Memory size6.8 KiB
2023-12-12T14:14:30.390115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length11.750473
Min length8

Characters and Unicode

Total characters6216
Distinct characters189
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)14.7%

Sample

1st row지방법원 [VH]
2nd row구치소 [FJ]
3rd row국립중앙과학관 [CC]
4th row지방고등법원 [VG]
5th row지방고등검찰청 [FD]
ValueCountFrequency (%)
지방세관 31
 
2.7%
ek 31
 
2.7%
교도소 30
 
2.6%
및 30
 
2.6%
소년교도소 30
 
2.6%
fk 30
 
2.6%
문화재관리국 23
 
2.0%
시·도선거관리위원회 15
 
1.3%
zc 15
 
1.3%
wa 15
 
1.3%
Other values (265) 917
78.6%
2023-12-12T14:14:30.961114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
651
 
10.5%
[ 528
 
8.5%
] 528
 
8.5%
소 258
 
4.2%
지 221
 
3.6%
방 204
 
3.3%
청 179
 
2.9%
관 179
 
2.9%
F 116
 
1.9%
리 101
 
1.6%
Other values (179) 3251
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3427
55.1%
Uppercase Letter 1056
 
17.0%
Space Separator 651
 
10.5%
Open Punctuation 531
 
8.5%
Close Punctuation 531
 
8.5%
Other Punctuation 18
 
0.3%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 258
 
7.5%
지 221
 
6.4%
방 204
 
6.0%
청 179
 
5.2%
관 179
 
5.2%
리 101
 
2.9%
무 98
 
2.9%
도 94
 
2.7%
사 94
 
2.7%
국 91
 
2.7%
Other values (145) 1908
55.7%
Uppercase Letter
ValueCountFrequency (%)
F 116
 
11.0%
K 98
 
9.3%
M 83
 
7.9%
C 80
 
7.6%
O 65
 
6.2%
L 58
 
5.5%
J 54
 
5.1%
E 51
 
4.8%
B 46
 
4.4%
A 45
 
4.3%
Other values (15) 360
34.1%
Open Punctuation
ValueCountFrequency (%)
[ 528
99.4%
( 3
 
0.6%
Close Punctuation
ValueCountFrequency (%)
] 528
99.4%
) 3
 
0.6%
Other Punctuation
ValueCountFrequency (%)
· 15
83.3%
, 3
 
16.7%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
651
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3427
55.1%
Common 1733
27.9%
Latin 1056
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 258
 
7.5%
지 221
 
6.4%
방 204
 
6.0%
청 179
 
5.2%
관 179
 
5.2%
리 101
 
2.9%
무 98
 
2.9%
도 94
 
2.7%
사 94
 
2.7%
국 91
 
2.7%
Other values (145) 1908
55.7%
Latin
ValueCountFrequency (%)
F 116
 
11.0%
K 98
 
9.3%
M 83
 
7.9%
C 80
 
7.6%
O 65
 
6.2%
L 58
 
5.5%
J 54
 
5.1%
E 51
 
4.8%
B 46
 
4.4%
A 45
 
4.3%
Other values (15) 360
34.1%
Common
ValueCountFrequency (%)
651
37.6%
[ 528
30.5%
] 528
30.5%
· 15
 
0.9%
) 3
 
0.2%
, 3
 
0.2%
( 3
 
0.2%
5 1
 
0.1%
1 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3427
55.1%
ASCII 2774
44.6%
None 15
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
651
23.5%
[ 528
19.0%
] 528
19.0%
F 116
 
4.2%
K 98
 
3.5%
M 83
 
3.0%
C 80
 
2.9%
O 65
 
2.3%
L 58
 
2.1%
J 54
 
1.9%
Other values (23) 513
18.5%
Hangul
ValueCountFrequency (%)
소 258
 
7.5%
지 221
 
6.4%
방 204
 
6.0%
청 179
 
5.2%
관 179
 
5.2%
리 101
 
2.9%
무 98
 
2.9%
도 94
 
2.7%
사 94
 
2.7%
국 91
 
2.7%
Other values (145) 1908
55.7%
None
ValueCountFrequency (%)
· 15
100.0%

색인부호명
Text

UNIQUE 

Distinct852
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2023-12-12T14:14:31.256889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length6.9929577
Min length2

Characters and Unicode

Total characters5958
Distinct characters233
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique852 ?
Unique (%)100.0%

Sample

1st row문화재관리국지구관리사무소
2nd row서울민사지방법원
3rd row서울구치소
4th row서울과학관
5th row서울고등법원
ValueCountFrequency (%)
문화재관리국지구관리사무소 1
 
0.1%
농업유전공학연구소 1
 
0.1%
수출자유지역관리소 1
 
0.1%
국립농산물검사소 1
 
0.1%
국립동물검역소 1
 
0.1%
국립종축원 1
 
0.1%
종자관리소 1
 
0.1%
국립식물검역소 1
 
0.1%
국제특허연수원 1
 
0.1%
특허청항고심판소 1
 
0.1%
Other values (842) 842
98.8%
2023-12-12T14:14:31.721313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 296
 
5.0%
청 261
 
4.4%
원 227
 
3.8%
지 208
 
3.5%
관 195
 
3.3%
방 182
 
3.1%
사 169
 
2.8%
국 168
 
2.8%
무 149
 
2.5%
산 119
 
2.0%
Other values (223) 3984
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5938
99.7%
Decimal Number 12
 
0.2%
Other Punctuation 6
 
0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 296
 
5.0%
청 261
 
4.4%
원 227
 
3.8%
지 208
 
3.5%
관 195
 
3.3%
방 182
 
3.1%
사 169
 
2.8%
국 168
 
2.8%
무 149
 
2.5%
산 119
 
2.0%
Other values (215) 3964
66.8%
Decimal Number
ValueCountFrequency (%)
1 5
41.7%
2 3
25.0%
9 2
 
16.7%
4 1
 
8.3%
5 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
I 1
50.0%
Other Punctuation
ValueCountFrequency (%)
· 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5938
99.7%
Common 18
 
0.3%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 296
 
5.0%
청 261
 
4.4%
원 227
 
3.8%
지 208
 
3.5%
관 195
 
3.3%
방 182
 
3.1%
사 169
 
2.8%
국 168
 
2.8%
무 149
 
2.5%
산 119
 
2.0%
Other values (215) 3964
66.8%
Common
ValueCountFrequency (%)
· 6
33.3%
1 5
27.8%
2 3
16.7%
9 2
 
11.1%
4 1
 
5.6%
5 1
 
5.6%
Latin
ValueCountFrequency (%)
A 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5938
99.7%
ASCII 14
 
0.2%
None 6
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 296
 
5.0%
청 261
 
4.4%
원 227
 
3.8%
지 208
 
3.5%
관 195
 
3.3%
방 182
 
3.1%
사 169
 
2.8%
국 168
 
2.8%
무 149
 
2.5%
산 119
 
2.0%
Other values (215) 3964
66.8%
None
ValueCountFrequency (%)
· 6
100.0%
ASCII
ValueCountFrequency (%)
1 5
35.7%
2 3
21.4%
9 2
 
14.3%
A 1
 
7.1%
4 1
 
7.1%
5 1
 
7.1%
I 1
 
7.1%

Interactions

2023-12-12T14:14:28.487438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T14:14:28.640487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:14:28.760122image/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

레코드키부호명참조명색인부호명
0565문화재관리국 지구관리사무소<NA>문화재관리국지구관리사무소
1234서울민사지방법원지방법원 [VH]서울민사지방법원
2235서울구치소구치소 [FJ]서울구치소
3236서울과학관국립중앙과학관 [CC]서울과학관
4237서울고등법원지방고등법원 [VG]서울고등법원
5238서울고등검찰청지방고등검찰청 [FD]서울고등검찰청
6239서부지방산림관리청지방산림관리청 [IN]서부지방산림관리청
7240서부광산보안사무소광산보안사무소 [KB]서부광산보안사무소
8241상공자원부통상산업부 [JA]상공자원부
9242상공부상공자원부 [JA]상공부
레코드키부호명참조명색인부호명
84299제주해양경찰서해양경찰서 [QI]제주해양경찰서
843100제주항건설사무소건설사무소 [MH]제주항건설사무소
844101제주통계사무소지방통계사무소 [CK]제주통계사무소
845102제주출입국관리사무소출입국관리사무소 [FL]제주출입국관리사무소
846103제주체신청체신청 [NB]제주체신청
847104제주지방해양수산청지방해양수산청 [MJ]제주지방해양수산청
848105제주지방중소기업청지방중소기업청 [SD]제주지방중소기업청
849106제주지방병무청지방병무청 [GC]제주지방병무청
850107제주지방법원지방법원 [VH]제주지방법원
851108제주지방기상청지방기상청 [CU]제주지방기상청