Overview

Dataset statistics

Number of variables6
Number of observations3508
Missing cells24
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory168.0 KiB
Average record size in memory49.0 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description전국 읍면동 하부행정기관(행정복지센터)에 관한 데이터로 자치단체별 목록, 우편번호, 주소로 구성되어 있습니다.
Author행정안전부
URLhttps://www.data.go.kr/data/15059715/fileData.do

Alerts

연번 is highly overall correlated with 시도High correlation
시도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-16 04:16:17.507664
Analysis finished2024-03-16 04:16:18.771362
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3508
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1754.5
Minimum1
Maximum3508
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.0 KiB
2024-03-16T13:16:18.918421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile176.35
Q1877.75
median1754.5
Q32631.25
95-th percentile3332.65
Maximum3508
Range3507
Interquartile range (IQR)1753.5

Descriptive statistics

Standard deviation1012.8167
Coefficient of variation (CV)0.577268
Kurtosis-1.2
Mean1754.5
Median Absolute Deviation (MAD)877
Skewness0
Sum6154786
Variance1025797.7
MonotonicityStrictly increasing
2024-03-16T13:16:19.181983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2345 1
 
< 0.1%
2334 1
 
< 0.1%
2335 1
 
< 0.1%
2336 1
 
< 0.1%
2337 1
 
< 0.1%
2338 1
 
< 0.1%
2339 1
 
< 0.1%
2340 1
 
< 0.1%
2341 1
 
< 0.1%
Other values (3498) 3498
99.7%
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 (%)
3508 1
< 0.1%
3507 1
< 0.1%
3506 1
< 0.1%
3505 1
< 0.1%
3504 1
< 0.1%
3503 1
< 0.1%
3502 1
< 0.1%
3501 1
< 0.1%
3500 1
< 0.1%
3499 1
< 0.1%

시도
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
경기
555 
서울
426 
경북
330 
경남
305 
전남
297 
Other values (13)
1595 

Length

Max length3
Median length2
Mean length2.0065564
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기 555
15.8%
서울 426
12.1%
경북 330
9.4%
경남 305
8.7%
전남 297
8.5%
전북 243
6.9%
충남 208
 
5.9%
부산 206
 
5.9%
강원 187
 
5.3%
인천 155
 
4.4%
Other values (8) 596
17.0%

Length

2024-03-16T13:16:19.557653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 555
15.8%
서울 426
12.1%
경북 330
9.4%
경남 305
8.7%
전남 297
8.5%
전북 243
6.9%
충남 208
 
5.9%
부산 206
 
5.9%
강원 187
 
5.3%
인천 155
 
4.4%
Other values (7) 596
17.0%

시군구
Text

Distinct223
Distinct (%)6.4%
Missing24
Missing (%)0.7%
Memory size27.5 KiB
2024-03-16T13:16:20.232954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.2890356
Min length2

Characters and Unicode

Total characters11459
Distinct characters141
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row종로구
2nd row종로구
3rd row종로구
4th row종로구
5th row종로구
ValueCountFrequency (%)
서구 94
 
2.5%
북구 87
 
2.3%
동구 83
 
2.2%
남구 75
 
2.0%
중구 62
 
1.6%
창원시 55
 
1.5%
성남시 50
 
1.3%
수원시 44
 
1.2%
청주시 43
 
1.1%
고양시 39
 
1.0%
Other values (218) 3147
83.3%
2024-03-16T13:16:20.994849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 1564
 
13.6%
구 1459
 
12.7%
군 869
 
7.6%
주 395
 
3.4%
349
 
3.0%
산 317
 
2.8%
천 312
 
2.7%
성 292
 
2.5%
양 263
 
2.3%
동 258
 
2.3%
Other values (131) 5381
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11110
97.0%
Space Separator 349
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1564
 
14.1%
구 1459
 
13.1%
군 869
 
7.8%
주 395
 
3.6%
산 317
 
2.9%
천 312
 
2.8%
성 292
 
2.6%
양 263
 
2.4%
동 258
 
2.3%
남 244
 
2.2%
Other values (130) 5137
46.2%
Space Separator
ValueCountFrequency (%)
349
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11110
97.0%
Common 349
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1564
 
14.1%
구 1459
 
13.1%
군 869
 
7.8%
주 395
 
3.6%
산 317
 
2.9%
천 312
 
2.8%
성 292
 
2.6%
양 263
 
2.4%
동 258
 
2.3%
남 244
 
2.2%
Other values (130) 5137
46.2%
Common
ValueCountFrequency (%)
349
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11110
97.0%
ASCII 349
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 1564
 
14.1%
구 1459
 
13.1%
군 869
 
7.8%
주 395
 
3.6%
산 317
 
2.9%
천 312
 
2.8%
성 292
 
2.6%
양 263
 
2.4%
동 258
 
2.3%
남 244
 
2.2%
Other values (130) 5137
46.2%
ASCII
ValueCountFrequency (%)
349
100.0%

읍면동
Text

Distinct3323
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
2024-03-16T13:16:21.475684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length8.5701254
Min length5

Characters and Unicode

Total characters30064
Distinct characters350
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3195 ?
Unique (%)91.1%

Sample

1st row청운효자동주민센터
2nd row사직동주민센터
3rd row삼청동주민센터
4th row부암동주민센터
5th row평창동주민센터
ValueCountFrequency (%)
행정복지센터 164
 
4.4%
주민센터 30
 
0.8%
중앙동행정복지센터 20
 
0.5%
중앙동주민센터 9
 
0.2%
남면행정복지센터 9
 
0.2%
서면행정복지센터 7
 
0.2%
삼산면사무소 4
 
0.1%
송정동행정복지센터 4
 
0.1%
성산면사무소 4
 
0.1%
북면사무소 4
 
0.1%
Other values (3295) 3447
93.1%
2024-03-16T13:16:22.293965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
센 2856
 
9.5%
터 2855
 
9.5%
동 2242
 
7.5%
정 2233
 
7.4%
지 2168
 
7.2%
복 2133
 
7.1%
행 2125
 
7.1%
면 1177
 
3.9%
주 800
 
2.7%
민 752
 
2.5%
Other values (340) 10723
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28463
94.7%
Decimal Number 1082
 
3.6%
Space Separator 507
 
1.7%
Other Punctuation 8
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
센 2856
 
10.0%
터 2855
 
10.0%
동 2242
 
7.9%
정 2233
 
7.8%
지 2168
 
7.6%
복 2133
 
7.5%
행 2125
 
7.5%
면 1177
 
4.1%
주 800
 
2.8%
민 752
 
2.6%
Other values (325) 9122
32.0%
Decimal Number
ValueCountFrequency (%)
1 383
35.4%
2 377
34.8%
3 165
15.2%
4 78
 
7.2%
5 34
 
3.1%
6 21
 
1.9%
7 11
 
1.0%
8 7
 
0.6%
9 4
 
0.4%
0 2
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
· 4
50.0%
Space Separator
ValueCountFrequency (%)
507
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28463
94.7%
Common 1601
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
센 2856
 
10.0%
터 2855
 
10.0%
동 2242
 
7.9%
정 2233
 
7.8%
지 2168
 
7.6%
복 2133
 
7.5%
행 2125
 
7.5%
면 1177
 
4.1%
주 800
 
2.8%
민 752
 
2.6%
Other values (325) 9122
32.0%
Common
ValueCountFrequency (%)
507
31.7%
1 383
23.9%
2 377
23.5%
3 165
 
10.3%
4 78
 
4.9%
5 34
 
2.1%
6 21
 
1.3%
7 11
 
0.7%
8 7
 
0.4%
. 4
 
0.2%
Other values (5) 14
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28456
94.7%
ASCII 1597
 
5.3%
Compat Jamo 7
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
센 2856
 
10.0%
터 2855
 
10.0%
동 2242
 
7.9%
정 2233
 
7.8%
지 2168
 
7.6%
복 2133
 
7.5%
행 2125
 
7.5%
면 1177
 
4.1%
주 800
 
2.8%
민 752
 
2.6%
Other values (324) 9115
32.0%
ASCII
ValueCountFrequency (%)
507
31.7%
1 383
24.0%
2 377
23.6%
3 165
 
10.3%
4 78
 
4.9%
5 34
 
2.1%
6 21
 
1.3%
7 11
 
0.7%
8 7
 
0.4%
. 4
 
0.3%
Other values (4) 10
 
0.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 7
100.0%
None
ValueCountFrequency (%)
· 4
100.0%

우편번호
Text

Distinct3488
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
2024-03-16T13:16:22.854413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.881699
Min length4

Characters and Unicode

Total characters17125
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3468 ?
Unique (%)98.9%

Sample

1st row3047
2nd row3027
3rd row3049
4th row3022
5th row3009
ValueCountFrequency (%)
10894 2
 
0.1%
14201 2
 
0.1%
31163 2
 
0.1%
51670 2
 
0.1%
10509 2
 
0.1%
39504 2
 
0.1%
41946 2
 
0.1%
57902 2
 
0.1%
30150 2
 
0.1%
54018 2
 
0.1%
Other values (3478) 3488
99.4%
2024-03-16T13:16:23.763605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2262
13.2%
5 2219
13.0%
2 2114
12.3%
3 1992
11.6%
4 1939
11.3%
0 1536
9.0%
6 1520
8.9%
7 1319
7.7%
8 1138
6.6%
9 1075
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17114
99.9%
Other Punctuation 11
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2262
13.2%
5 2219
13.0%
2 2114
12.4%
3 1992
11.6%
4 1939
11.3%
0 1536
9.0%
6 1520
8.9%
7 1319
7.7%
8 1138
6.6%
9 1075
6.3%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17125
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2262
13.2%
5 2219
13.0%
2 2114
12.3%
3 1992
11.6%
4 1939
11.3%
0 1536
9.0%
6 1520
8.9%
7 1319
7.7%
8 1138
6.6%
9 1075
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17125
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2262
13.2%
5 2219
13.0%
2 2114
12.3%
3 1992
11.6%
4 1939
11.3%
0 1536
9.0%
6 1520
8.9%
7 1319
7.7%
8 1138
6.6%
9 1075
6.3%

주 소
Text

Distinct3503
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
2024-03-16T13:16:24.433522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length35
Mean length19.474059
Min length11

Characters and Unicode

Total characters68315
Distinct characters472
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

Unique3498 ?
Unique (%)99.7%

Sample

1st row서울특별시 종로구 자하문로 92
2nd row서울특별시 종로구 사직로9길 1
3rd row서울특별시 종로구 삼청로 107
4th row서울특별시 종로구 창의문로 145
5th row서울특별시 종로구 평창문화로 65
ValueCountFrequency (%)
경기도 550
 
3.5%
서울특별시 417
 
2.6%
경상북도 315
 
2.0%
경상남도 305
 
1.9%
전라남도 297
 
1.9%
전라북도 240
 
1.5%
충청남도 208
 
1.3%
부산광역시 206
 
1.3%
강원도 187
 
1.2%
인천광역시 154
 
1.0%
Other values (5743) 13006
81.9%
2024-03-16T13:16:25.323412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12790
 
18.7%
로 2877
 
4.2%
시 2804
 
4.1%
도 2486
 
3.6%
1 2269
 
3.3%
구 1844
 
2.7%
길 1547
 
2.3%
2 1475
 
2.2%
경 1299
 
1.9%
남 1286
 
1.9%
Other values (462) 37638
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44108
64.6%
Space Separator 12796
 
18.7%
Decimal Number 10934
 
16.0%
Dash Punctuation 343
 
0.5%
Close Punctuation 50
 
0.1%
Open Punctuation 50
 
0.1%
Other Punctuation 31
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 2877
 
6.5%
시 2804
 
6.4%
도 2486
 
5.6%
구 1844
 
4.2%
길 1547
 
3.5%
경 1299
 
2.9%
남 1286
 
2.9%
면 1187
 
2.7%
산 1019
 
2.3%
광 992
 
2.2%
Other values (443) 26767
60.7%
Decimal Number
ValueCountFrequency (%)
1 2269
20.8%
2 1475
13.5%
3 1262
11.5%
5 1036
9.5%
4 1009
9.2%
7 873
 
8.0%
6 826
 
7.6%
0 742
 
6.8%
8 722
 
6.6%
9 720
 
6.6%
Other Punctuation
ValueCountFrequency (%)
, 25
80.6%
. 4
 
12.9%
' 2
 
6.5%
Space Separator
ValueCountFrequency (%)
12790
> 99.9%
　 6
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 343
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44108
64.6%
Common 24207
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 2877
 
6.5%
시 2804
 
6.4%
도 2486
 
5.6%
구 1844
 
4.2%
길 1547
 
3.5%
경 1299
 
2.9%
남 1286
 
2.9%
면 1187
 
2.7%
산 1019
 
2.3%
광 992
 
2.2%
Other values (443) 26767
60.7%
Common
ValueCountFrequency (%)
12790
52.8%
1 2269
 
9.4%
2 1475
 
6.1%
3 1262
 
5.2%
5 1036
 
4.3%
4 1009
 
4.2%
7 873
 
3.6%
6 826
 
3.4%
0 742
 
3.1%
8 722
 
3.0%
Other values (9) 1203
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44108
64.6%
ASCII 24201
35.4%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12790
52.8%
1 2269
 
9.4%
2 1475
 
6.1%
3 1262
 
5.2%
5 1036
 
4.3%
4 1009
 
4.2%
7 873
 
3.6%
6 826
 
3.4%
0 742
 
3.1%
8 722
 
3.0%
Other values (8) 1197
 
4.9%
Hangul
ValueCountFrequency (%)
로 2877
 
6.5%
시 2804
 
6.4%
도 2486
 
5.6%
구 1844
 
4.2%
길 1547
 
3.5%
경 1299
 
2.9%
남 1286
 
2.9%
면 1187
 
2.7%
산 1019
 
2.3%
광 992
 
2.2%
Other values (443) 26767
60.7%
None
ValueCountFrequency (%)
　 6
100.0%

Interactions

2024-03-16T13:16:18.343061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:16:25.511616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시도
연번1.0000.976
시도0.9761.000
2024-03-16T13:16:25.684673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시도
연번1.0000.879
시도0.8791.000

Missing values

2024-03-16T13:16:18.518767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:16:18.698089image/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

연번시도시군구읍면동우편번호주 소
01서울종로구청운효자동주민센터3047서울특별시 종로구 자하문로 92
12서울종로구사직동주민센터3027서울특별시 종로구 사직로9길 1
23서울종로구삼청동주민센터3049서울특별시 종로구 삼청로 107
34서울종로구부암동주민센터3022서울특별시 종로구 창의문로 145
45서울종로구평창동주민센터3009서울특별시 종로구 평창문화로 65
56서울종로구무악동주민센터3030서울특별시 종로구 통일로14길 36
67서울종로구교남동주민센터3166서울특별시 종로구 송월길 154
78서울종로구가회동주민센터3055서울특별시 종로구 북촌로 35
89서울종로구종로1234가동주민센터3140서울특별시 종로구 종로17길 8
910서울종로구종로56가동주민센터3126서울특별시 종로구 종로35가길 19
연번시도시군구읍면동우편번호주 소
34983499제주서귀포시중앙동주민센터63590제주특별자치도 서귀포시 동문동로 27
34993500제주서귀포시천지동주민센터63592제주특별자치도 서귀포시 중정로47번길 3
35003501제주서귀포시효돈동주민센터63606제주특별자치도 서귀포시 효돈로152번길 7
35013502제주서귀포시영천동주민센터63603제주특별자치도 서귀포시 토평로 15
35023503제주서귀포시동홍동주민센터63588제주특별자치도 서귀포시 동홍로 104
35033504제주서귀포시서홍동주민센터63584제주특별자치도 서귀포시 중앙로 125
35043505제주서귀포시대륜동주민센터63572제주특별자치도 서귀포시 일주동로 9185
35053506제주서귀포시대천동주민센터63561제주특별자치도 서귀포시 도순로 44
35063507제주서귀포시중문동주민센터63540제주특별자치도 서귀포시 1100로 30
35073508제주서귀포시예래동주민센터63537제주특별자치도 서귀포시 예래로 82