Overview

Dataset statistics

Number of variables7
Number of observations755
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory42.2 KiB
Average record size in memory57.2 B

Variable types

Text6
Numeric1

Dataset

Description인천광역시 서구의 개인정보파일 보유현황에 관한 데이터로, 개인정보파일의 명칭, 부서명, 개인정보파일의 운영근거, 개인정보파일의 운영 목적 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15105067/fileData.do

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 07:30:24.204524
Analysis finished2023-12-12 07:30:25.454881
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct541
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-12T16:30:25.582099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length22
Mean length10.117881
Min length2

Characters and Unicode

Total characters7639
Distinct characters328
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique449 ?
Unique (%)59.5%

Sample

1st row국민기초생활수급자 관리 파일
2nd row등록장애인 관리 파일
3rd row아동급식지원 대상자 관리 파일
4th row자생단체원 관리 파일
5th row주민자치센터강사 관리 파일
ValueCountFrequency (%)
관리 91
 
7.2%
명부 61
 
4.8%
파일 46
 
3.6%
명단 41
 
3.2%
장애인 21
 
1.7%
관리파일 17
 
1.3%
대상자 15
 
1.2%
15
 
1.2%
지원 11
 
0.9%
등록 11
 
0.9%
Other values (611) 943
74.1%
2023-12-12T16:30:25.955552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
517
 
6.8%
404
 
5.3%
385
 
5.0%
228
 
3.0%
207
 
2.7%
188
 
2.5%
187
 
2.4%
185
 
2.4%
178
 
2.3%
177
 
2.3%
Other values (318) 4983
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6970
91.2%
Space Separator 517
 
6.8%
Open Punctuation 47
 
0.6%
Close Punctuation 47
 
0.6%
Other Punctuation 21
 
0.3%
Dash Punctuation 14
 
0.2%
Uppercase Letter 10
 
0.1%
Decimal Number 8
 
0.1%
Connector Punctuation 4
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
404
 
5.8%
385
 
5.5%
228
 
3.3%
207
 
3.0%
188
 
2.7%
187
 
2.7%
185
 
2.7%
178
 
2.6%
177
 
2.5%
126
 
1.8%
Other values (297) 4705
67.5%
Decimal Number
ValueCountFrequency (%)
3 3
37.5%
5 1
 
12.5%
2 1
 
12.5%
6 1
 
12.5%
1 1
 
12.5%
4 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
K 2
20.0%
I 2
20.0%
A 2
20.0%
S 2
20.0%
P 1
10.0%
C 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 11
52.4%
/ 9
42.9%
. 1
 
4.8%
Space Separator
ValueCountFrequency (%)
517
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6970
91.2%
Common 658
 
8.6%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
404
 
5.8%
385
 
5.5%
228
 
3.3%
207
 
3.0%
188
 
2.7%
187
 
2.7%
185
 
2.7%
178
 
2.6%
177
 
2.5%
126
 
1.8%
Other values (297) 4705
67.5%
Common
ValueCountFrequency (%)
517
78.6%
( 47
 
7.1%
) 47
 
7.1%
- 14
 
2.1%
, 11
 
1.7%
/ 9
 
1.4%
_ 4
 
0.6%
3 3
 
0.5%
5 1
 
0.2%
2 1
 
0.2%
Other values (4) 4
 
0.6%
Latin
ValueCountFrequency (%)
K 2
18.2%
I 2
18.2%
A 2
18.2%
S 2
18.2%
e 1
9.1%
P 1
9.1%
C 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6970
91.2%
ASCII 669
 
8.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
517
77.3%
( 47
 
7.0%
) 47
 
7.0%
- 14
 
2.1%
, 11
 
1.6%
/ 9
 
1.3%
_ 4
 
0.6%
3 3
 
0.4%
K 2
 
0.3%
I 2
 
0.3%
Other values (11) 13
 
1.9%
Hangul
ValueCountFrequency (%)
404
 
5.8%
385
 
5.5%
228
 
3.3%
207
 
3.0%
188
 
2.7%
187
 
2.7%
185
 
2.7%
178
 
2.6%
177
 
2.5%
126
 
1.8%
Other values (297) 4705
67.5%
Distinct62
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-12T16:30:26.182814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4.5496689
Min length3

Characters and Unicode

Total characters3435
Distinct characters121
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

Unique6 ?
Unique (%)0.8%

Sample

1st row가정1동
2nd row가정1동
3rd row가정1동
4th row가정1동
5th row가정1동
ValueCountFrequency (%)
석남1동 42
 
5.6%
석남2동 35
 
4.6%
오류왕길동 33
 
4.4%
검단출장소 29
 
3.8%
석남3동 28
 
3.7%
원당동 24
 
3.2%
건강증진과 24
 
3.2%
가좌2동 24
 
3.2%
세무1과 21
 
2.8%
경제정책과 21
 
2.8%
Other values (52) 474
62.8%
2023-12-12T16:30:26.528173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
414
 
12.1%
313
 
9.1%
110
 
3.2%
105
 
3.1%
105
 
3.1%
1 101
 
2.9%
2 99
 
2.9%
94
 
2.7%
73
 
2.1%
64
 
1.9%
Other values (111) 1957
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3167
92.2%
Decimal Number 268
 
7.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
414
 
13.1%
313
 
9.9%
110
 
3.5%
105
 
3.3%
105
 
3.3%
94
 
3.0%
73
 
2.3%
64
 
2.0%
63
 
2.0%
56
 
1.8%
Other values (107) 1770
55.9%
Decimal Number
ValueCountFrequency (%)
1 101
37.7%
2 99
36.9%
3 60
22.4%
4 8
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3167
92.2%
Common 268
 
7.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
414
 
13.1%
313
 
9.9%
110
 
3.5%
105
 
3.3%
105
 
3.3%
94
 
3.0%
73
 
2.3%
64
 
2.0%
63
 
2.0%
56
 
1.8%
Other values (107) 1770
55.9%
Common
ValueCountFrequency (%)
1 101
37.7%
2 99
36.9%
3 60
22.4%
4 8
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3167
92.2%
ASCII 268
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
414
 
13.1%
313
 
9.9%
110
 
3.5%
105
 
3.3%
105
 
3.3%
94
 
3.0%
73
 
2.3%
64
 
2.0%
63
 
2.0%
56
 
1.8%
Other values (107) 1770
55.9%
ASCII
ValueCountFrequency (%)
1 101
37.7%
2 99
36.9%
3 60
22.4%
4 8
 
3.0%
Distinct449
Distinct (%)59.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-12T16:30:26.710305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length56
Mean length15.174834
Min length3

Characters and Unicode

Total characters11457
Distinct characters287
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique355 ?
Unique (%)47.0%

Sample

1st row국민기초생활보장법
2nd row장애인복지법
3rd row아동복지법
4th row업무상 필요에 의거 관리
5th row인천광역시서구 주민자치회 및 주민자치센터 설치·운영에 관한 조례, 동법 시행규칙
ValueCountFrequency (%)
90
 
5.2%
관한 65
 
3.8%
인천광역시 47
 
2.7%
서구 43
 
2.5%
장애인복지법 37
 
2.2%
조례 37
 
2.2%
주민등록법 34
 
2.0%
법률 33
 
1.9%
시행령 29
 
1.7%
민방위기본법 27
 
1.6%
Other values (633) 1278
74.3%
2023-12-12T16:30:27.076843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
965
 
8.4%
694
 
6.1%
573
 
5.0%
447
 
3.9%
291
 
2.5%
234
 
2.0%
219
 
1.9%
191
 
1.7%
1 190
 
1.7%
188
 
1.6%
Other values (277) 7465
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9304
81.2%
Space Separator 965
 
8.4%
Decimal Number 834
 
7.3%
Other Punctuation 141
 
1.2%
Close Punctuation 96
 
0.8%
Open Punctuation 96
 
0.8%
Math Symbol 19
 
0.2%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
694
 
7.5%
573
 
6.2%
447
 
4.8%
291
 
3.1%
234
 
2.5%
219
 
2.4%
191
 
2.1%
188
 
2.0%
174
 
1.9%
171
 
1.8%
Other values (255) 6122
65.8%
Decimal Number
ValueCountFrequency (%)
1 190
22.8%
3 140
16.8%
2 129
15.5%
4 87
10.4%
5 61
 
7.3%
6 58
 
7.0%
9 53
 
6.4%
8 46
 
5.5%
7 44
 
5.3%
0 26
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 115
81.6%
· 10
 
7.1%
. 6
 
4.3%
: 5
 
3.5%
" 4
 
2.8%
/ 1
 
0.7%
Math Symbol
ValueCountFrequency (%)
~ 15
78.9%
+ 4
 
21.1%
Space Separator
ValueCountFrequency (%)
965
100.0%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9304
81.2%
Common 2153
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
694
 
7.5%
573
 
6.2%
447
 
4.8%
291
 
3.1%
234
 
2.5%
219
 
2.4%
191
 
2.1%
188
 
2.0%
174
 
1.9%
171
 
1.8%
Other values (255) 6122
65.8%
Common
ValueCountFrequency (%)
965
44.8%
1 190
 
8.8%
3 140
 
6.5%
2 129
 
6.0%
, 115
 
5.3%
) 96
 
4.5%
( 96
 
4.5%
4 87
 
4.0%
5 61
 
2.8%
6 58
 
2.7%
Other values (12) 216
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9304
81.2%
ASCII 2143
 
18.7%
None 10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
965
45.0%
1 190
 
8.9%
3 140
 
6.5%
2 129
 
6.0%
, 115
 
5.4%
) 96
 
4.5%
( 96
 
4.5%
4 87
 
4.1%
5 61
 
2.8%
6 58
 
2.7%
Other values (11) 206
 
9.6%
Hangul
ValueCountFrequency (%)
694
 
7.5%
573
 
6.2%
447
 
4.8%
291
 
3.1%
234
 
2.5%
219
 
2.4%
191
 
2.1%
188
 
2.0%
174
 
1.9%
171
 
1.8%
Other values (255) 6122
65.8%
None
ValueCountFrequency (%)
· 10
100.0%
Distinct559
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-12T16:30:27.310884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length52
Mean length15.150993
Min length2

Characters and Unicode

Total characters11439
Distinct characters350
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

Unique475 ?
Unique (%)62.9%

Sample

1st row국민기초생활수급자 지원을 위한 대상자 관리
2nd row장애인 지원을 위한 대상자 관리
3rd row아동급식지원을 위한 대상자 관리
4th row자생단체원의 신상정보 관리
5th row주민자치센터 강사의 신상정보 관리
ValueCountFrequency (%)
관리 322
 
12.3%
152
 
5.8%
지원 70
 
2.7%
위한 63
 
2.4%
대상자 60
 
2.3%
31
 
1.2%
장애인 30
 
1.1%
신상정보 30
 
1.1%
등록 25
 
1.0%
지원을 21
 
0.8%
Other values (898) 1821
69.4%
2023-12-12T16:30:27.791698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1870
 
16.3%
628
 
5.5%
598
 
5.2%
323
 
2.8%
310
 
2.7%
289
 
2.5%
225
 
2.0%
210
 
1.8%
206
 
1.8%
167
 
1.5%
Other values (340) 6613
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9387
82.1%
Space Separator 1870
 
16.3%
Other Punctuation 110
 
1.0%
Close Punctuation 31
 
0.3%
Open Punctuation 31
 
0.3%
Uppercase Letter 5
 
< 0.1%
Decimal Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
628
 
6.7%
598
 
6.4%
323
 
3.4%
310
 
3.3%
289
 
3.1%
225
 
2.4%
210
 
2.2%
206
 
2.2%
167
 
1.8%
159
 
1.7%
Other values (325) 6272
66.8%
Other Punctuation
ValueCountFrequency (%)
, 100
90.9%
. 7
 
6.4%
· 2
 
1.8%
/ 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
C 2
40.0%
E 1
20.0%
P 1
20.0%
O 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
1 1
20.0%
7 1
20.0%
3 1
20.0%
Space Separator
ValueCountFrequency (%)
1870
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9387
82.1%
Common 2047
 
17.9%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
628
 
6.7%
598
 
6.4%
323
 
3.4%
310
 
3.3%
289
 
3.1%
225
 
2.4%
210
 
2.2%
206
 
2.2%
167
 
1.8%
159
 
1.7%
Other values (325) 6272
66.8%
Common
ValueCountFrequency (%)
1870
91.4%
, 100
 
4.9%
) 31
 
1.5%
( 31
 
1.5%
. 7
 
0.3%
· 2
 
0.1%
2 2
 
0.1%
1 1
 
< 0.1%
7 1
 
< 0.1%
3 1
 
< 0.1%
Latin
ValueCountFrequency (%)
C 2
40.0%
E 1
20.0%
P 1
20.0%
O 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9387
82.1%
ASCII 2050
 
17.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1870
91.2%
, 100
 
4.9%
) 31
 
1.5%
( 31
 
1.5%
. 7
 
0.3%
C 2
 
0.1%
2 2
 
0.1%
1 1
 
< 0.1%
7 1
 
< 0.1%
3 1
 
< 0.1%
Other values (4) 4
 
0.2%
Hangul
ValueCountFrequency (%)
628
 
6.7%
598
 
6.4%
323
 
3.4%
310
 
3.3%
289
 
3.1%
225
 
2.4%
210
 
2.2%
206
 
2.2%
167
 
1.8%
159
 
1.7%
Other values (325) 6272
66.8%
None
ValueCountFrequency (%)
· 2
100.0%
Distinct516
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45335.797
Minimum1
Maximum3950284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T16:30:27.976946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q152
median391
Q32319
95-th percentile62804.2
Maximum3950284
Range3950283
Interquartile range (IQR)2267

Descriptive statistics

Standard deviation286413.33
Coefficient of variation (CV)6.3175976
Kurtosis95.560301
Mean45335.797
Median Absolute Deviation (MAD)379
Skewness9.1789319
Sum34228527
Variance8.2032593 × 1010
MonotonicityNot monotonic
2023-12-12T16:30:28.111129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 9
 
1.2%
2 9
 
1.2%
10 8
 
1.1%
12 8
 
1.1%
8 7
 
0.9%
20 7
 
0.9%
34 6
 
0.8%
50 6
 
0.8%
1 6
 
0.8%
7 6
 
0.8%
Other values (506) 683
90.5%
ValueCountFrequency (%)
1 6
0.8%
2 9
1.2%
3 5
0.7%
4 2
 
0.3%
5 3
 
0.4%
6 2
 
0.3%
7 6
0.8%
8 7
0.9%
9 4
0.5%
10 8
1.1%
ValueCountFrequency (%)
3950284 1
0.1%
3481834 1
0.1%
2412533 1
0.1%
2265459 1
0.1%
2231221 1
0.1%
2006958 1
0.1%
1832420 1
0.1%
1789710 1
0.1%
1620751 1
0.1%
1379389 1
0.1%
Distinct55
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-12T16:30:28.291715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length30
Mean length15.845033
Min length4

Characters and Unicode

Total characters11963
Distinct characters141
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)3.6%

Sample

1st row개인정보처리시스템 (사회보장정보시스템)
2nd row개인정보처리시스템 (사회보장정보시스템)
3rd row종이문서
4th row업무용 PC
5th row업무용 PC , 종이문서
ValueCountFrequency (%)
개인정보처리시스템 482
30.4%
업무용 226
14.3%
pc 226
14.3%
사회보장정보시스템 161
 
10.2%
새올행정시스템 107
 
6.8%
종이문서 102
 
6.4%
주민등록시스템 62
 
3.9%
55
 
3.5%
표준지방세정보시스템 32
 
2.0%
건축행정시스템 16
 
1.0%
Other values (46) 116
 
7.3%
2023-12-12T16:30:28.627493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
952
 
8.0%
950
 
7.9%
950
 
7.9%
916
 
7.7%
852
 
7.1%
830
 
6.9%
) 511
 
4.3%
( 511
 
4.3%
510
 
4.3%
487
 
4.1%
Other values (131) 4494
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9494
79.4%
Space Separator 830
 
6.9%
Uppercase Letter 554
 
4.6%
Close Punctuation 511
 
4.3%
Open Punctuation 511
 
4.3%
Other Punctuation 55
 
0.5%
Lowercase Letter 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
952
 
10.0%
950
 
10.0%
950
 
10.0%
916
 
9.6%
852
 
9.0%
510
 
5.4%
487
 
5.1%
483
 
5.1%
482
 
5.1%
232
 
2.4%
Other values (111) 2680
28.2%
Uppercase Letter
ValueCountFrequency (%)
P 236
42.6%
C 226
40.8%
S 25
 
4.5%
R 12
 
2.2%
T 12
 
2.2%
I 12
 
2.2%
H 11
 
2.0%
M 11
 
2.0%
A 4
 
0.7%
K 3
 
0.5%
Other values (2) 2
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
830
100.0%
Close Punctuation
ValueCountFrequency (%)
) 511
100.0%
Open Punctuation
ValueCountFrequency (%)
( 511
100.0%
Other Punctuation
ValueCountFrequency (%)
, 55
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9494
79.4%
Common 1911
 
16.0%
Latin 558
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
952
 
10.0%
950
 
10.0%
950
 
10.0%
916
 
9.6%
852
 
9.0%
510
 
5.4%
487
 
5.1%
483
 
5.1%
482
 
5.1%
232
 
2.4%
Other values (111) 2680
28.2%
Latin
ValueCountFrequency (%)
P 236
42.3%
C 226
40.5%
S 25
 
4.5%
R 12
 
2.2%
T 12
 
2.2%
I 12
 
2.2%
H 11
 
2.0%
M 11
 
2.0%
e 4
 
0.7%
A 4
 
0.7%
Other values (3) 5
 
0.9%
Common
ValueCountFrequency (%)
830
43.4%
) 511
26.7%
( 511
26.7%
, 55
 
2.9%
- 2
 
0.1%
2 1
 
0.1%
4 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9494
79.4%
ASCII 2469
 
20.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
952
 
10.0%
950
 
10.0%
950
 
10.0%
916
 
9.6%
852
 
9.0%
510
 
5.4%
487
 
5.1%
483
 
5.1%
482
 
5.1%
232
 
2.4%
Other values (111) 2680
28.2%
ASCII
ValueCountFrequency (%)
830
33.6%
) 511
20.7%
( 511
20.7%
P 236
 
9.6%
C 226
 
9.2%
, 55
 
2.2%
S 25
 
1.0%
R 12
 
0.5%
T 12
 
0.5%
I 12
 
0.5%
Other values (10) 39
 
1.6%
Distinct71
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-12T16:30:28.913727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length2
Mean length5.1562914
Min length2

Characters and Unicode

Total characters3893
Distinct characters151
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)6.1%

Sample

1st row기타 (중지사유발생전까지 보유) (년)
2nd row5년
3rd row3년
4th row기타 (탈퇴시까지) (년)
5th row5년
ValueCountFrequency (%)
5년 241
20.1%
영구 169
14.1%
기타 126
10.5%
100
 
8.4%
3년 75
 
6.3%
10년 74
 
6.2%
준영구 52
 
4.3%
1년 24
 
2.0%
기간 20
 
1.7%
2년 14
 
1.2%
Other values (112) 302
25.2%
2023-12-12T16:30:29.489513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
537
13.8%
442
 
11.4%
( 254
 
6.5%
) 254
 
6.5%
5 241
 
6.2%
231
 
5.9%
222
 
5.7%
180
 
4.6%
126
 
3.2%
99
 
2.5%
Other values (141) 1307
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2423
62.2%
Decimal Number 519
 
13.3%
Space Separator 442
 
11.4%
Open Punctuation 254
 
6.5%
Close Punctuation 254
 
6.5%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
537
22.2%
231
 
9.5%
222
 
9.2%
180
 
7.4%
126
 
5.2%
99
 
4.1%
91
 
3.8%
77
 
3.2%
53
 
2.2%
43
 
1.8%
Other values (132) 764
31.5%
Decimal Number
ValueCountFrequency (%)
5 241
46.4%
1 98
18.9%
3 84
 
16.2%
0 82
 
15.8%
2 14
 
2.7%
Space Separator
ValueCountFrequency (%)
442
100.0%
Open Punctuation
ValueCountFrequency (%)
( 254
100.0%
Close Punctuation
ValueCountFrequency (%)
) 254
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2423
62.2%
Common 1470
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
537
22.2%
231
 
9.5%
222
 
9.2%
180
 
7.4%
126
 
5.2%
99
 
4.1%
91
 
3.8%
77
 
3.2%
53
 
2.2%
43
 
1.8%
Other values (132) 764
31.5%
Common
ValueCountFrequency (%)
442
30.1%
( 254
17.3%
) 254
17.3%
5 241
16.4%
1 98
 
6.7%
3 84
 
5.7%
0 82
 
5.6%
2 14
 
1.0%
, 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2423
62.2%
ASCII 1470
37.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
537
22.2%
231
 
9.5%
222
 
9.2%
180
 
7.4%
126
 
5.2%
99
 
4.1%
91
 
3.8%
77
 
3.2%
53
 
2.2%
43
 
1.8%
Other values (132) 764
31.5%
ASCII
ValueCountFrequency (%)
442
30.1%
( 254
17.3%
) 254
17.3%
5 241
16.4%
1 98
 
6.7%
3 84
 
5.7%
0 82
 
5.6%
2 14
 
1.0%
, 1
 
0.1%

Interactions

2023-12-12T16:30:25.108429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:30:29.621683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부서명개인정보파일로 보유하고 있는 개인정보의 정보주체 수(건)개인정보의 처리방법개인정보의 보유기간
부서명1.0000.4350.9480.884
개인정보파일로 보유하고 있는 개인정보의 정보주체 수(건)0.4351.0000.0000.000
개인정보의 처리방법0.9480.0001.0000.000
개인정보의 보유기간0.8840.0000.0001.000

Missing values

2023-12-12T16:30:25.271420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:30:25.406343image/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

개인정보파일의 명칭부서명개인정보파일의 운영 근거개인정보파일의 운영 목적개인정보파일로 보유하고 있는 개인정보의 정보주체 수(건)개인정보의 처리방법개인정보의 보유기간
0국민기초생활수급자 관리 파일가정1동국민기초생활보장법국민기초생활수급자 지원을 위한 대상자 관리1387개인정보처리시스템 (사회보장정보시스템)기타 (중지사유발생전까지 보유) (년)
1등록장애인 관리 파일가정1동장애인복지법장애인 지원을 위한 대상자 관리1540개인정보처리시스템 (사회보장정보시스템)5년
2아동급식지원 대상자 관리 파일가정1동아동복지법아동급식지원을 위한 대상자 관리105종이문서3년
3자생단체원 관리 파일가정1동업무상 필요에 의거 관리자생단체원의 신상정보 관리150업무용 PC기타 (탈퇴시까지) (년)
4주민자치센터강사 관리 파일가정1동인천광역시서구 주민자치회 및 주민자치센터 설치·운영에 관한 조례, 동법 시행규칙주민자치센터 강사의 신상정보 관리11업무용 PC , 종이문서5년
5주민자치회 위원 관리 파일가정1동인천광역시 서구 주민자치회 및 주민자치센터 설치·운영에 관한 조례, 동법 시행규칙주민자치회 위원의 자격 및 신상정보 관리43업무용 PC , 종이문서기타 (해촉시까지) (년)
6통반장관리 파일가정1동인천광역시서구통반설치조레통반장의 신상정보 관리42업무용 PC기타 (해촉시까지) (년)
7국민기초생활수급자 관리 파일가정2동국민기초생활보장법국민기초생활수급자 지원을 위한 대상자 관리241개인정보처리시스템 (사회보장정보시스템)5년
8등록장애인 관리 파일가정2동장애인복지법장애 지원을 위한 대상자 관리339개인정보처리시스템 (사회보장정보시스템)5년
9민방위교육 교육 관리 파일가정2동민방위기본법민방위대원 교육을 위한 자원 관리411개인정보처리시스템 (새올행정시스템)기타 (자원해제시까지) (년)
개인정보파일의 명칭부서명개인정보파일의 운영 근거개인정보파일의 운영 목적개인정보파일로 보유하고 있는 개인정보의 정보주체 수(건)개인정보의 처리방법개인정보의 보유기간
745소음진동배출시설관리환경관리과소음진동규제법소음진동배출시설관리586업무용 PC영구
746수렵면허환경관리과야생생물보호및관리에관한법률수렵면허(신규,갱신,변경,취소)관리34업무용 PC준영구
747시설물분 환경개선부담금환경관리과환경개선비용부담법제9조환경개선비용부담법 시행령 제29조(고유식별정보의 처리)시설물분 환경개선부담금 부과징수91643개인정보처리시스템 (새올행정시스템)영구
748악취배출시설관리환경관리과악취방지법악취배출시설관리1303업무용 PC영구
749유해야생동물 포획 허가환경관리과야생생물보호및관리에관한법률유해야생동물 포획 허가34업무용 PC5년
750자동차분 환경개선부담금환경관리과환경개선비용부담법 제9조환경개선부담금시행령 제29조(고유식별정보의 처리)자동차분 환경개선부담금 부과징수1789710개인정보처리시스템 (새올행정시스템)영구
751토양오염관리시설관리환경관리과토양환경보전법토양오염관리시설관리143업무용 PC영구
752토양오염실태조사환경관리과토양환경보전법토양오염실태조사 대상선정18업무용 PC영구
753폐수배출시설관리환경관리과물환경보전법폐수배출시설관리1116업무용 PC영구
754휘발성유기화합물질배출시설관리환경관리과대기환경보전법휘발성유기화합물질배출시설관리157업무용 PC영구

Duplicate rows

Most frequently occurring

개인정보파일의 명칭부서명개인정보파일의 운영 근거개인정보파일의 운영 목적개인정보파일로 보유하고 있는 개인정보의 정보주체 수(건)개인정보의 처리방법개인정보의 보유기간# duplicates
0장애인생활안정지원장애인복지과장애인복지법장애인복지대상자 신상정보관리6418개인정보처리시스템 (사회보장정보시스템)5년2