Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells10
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory132.0 B

Variable types

Numeric3
Text8
Categorical3
Boolean1

Dataset

Description성범죄자 신상정보 공개고지를 위한 아동청소년보호기관정보(우편고지발송기관고유번호, 아동청소년보호기관명, 시도, 주소지시군구, 읍면동정보, 행정동명, 우편번호, 기관주소, 상세건물명, 기관대표자, 기관구분값, 주소지지도X좌표, 주소지지도Y좌표, 완료여부, 기관코드, 교육기관일련번호, 교육기관시도교육기관시군구, 교육기관읍면동)
Author여성가족부
URLhttps://www.data.go.kr/data/15059846/fileData.do

Alerts

완료여부 has constant value ""Constant
시도 is highly overall correlated with 주소지지도X좌표 and 2 other fieldsHigh correlation
교육기관시도 is highly overall correlated with 주소지지도X좌표 and 2 other fieldsHigh correlation
일련번호 is highly overall correlated with 기관구분값High correlation
주소지지도X좌표 is highly overall correlated with 시도 and 1 other fieldsHigh correlation
주소지지도Y좌표 is highly overall correlated with 시도 and 1 other fieldsHigh correlation
기관구분값 is highly overall correlated with 일련번호High correlation
시도 is highly imbalanced (62.7%)Imbalance
기관구분값 is highly imbalanced (74.9%)Imbalance
교육기관시도 is highly imbalanced (62.7%)Imbalance
일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:30:01.120377
Analysis finished2023-12-12 19:30:05.857832
Duration4.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2947548.6
Minimum2662046
Maximum2999452
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:30:05.966229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2662046
5-th percentile2715020.3
Q12953223.8
median2968742
Q32984116.5
95-th percentile2996483.1
Maximum2999452
Range337406
Interquartile range (IQR)30892.75

Descriptive statistics

Standard deviation77990.365
Coefficient of variation (CV)0.026459399
Kurtosis5.8774845
Mean2947548.6
Median Absolute Deviation (MAD)15462.5
Skewness-2.7059525
Sum2.9475486 × 1010
Variance6.082497 × 109
MonotonicityNot monotonic
2023-12-13T04:30:06.210152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2662098 1
 
< 0.1%
2944255 1
 
< 0.1%
2973426 1
 
< 0.1%
2716514 1
 
< 0.1%
2662962 1
 
< 0.1%
2955164 1
 
< 0.1%
2954386 1
 
< 0.1%
2983745 1
 
< 0.1%
2662658 1
 
< 0.1%
2960762 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2662046 1
< 0.1%
2662061 1
< 0.1%
2662062 1
< 0.1%
2662066 1
< 0.1%
2662072 1
< 0.1%
2662073 1
< 0.1%
2662078 1
< 0.1%
2662080 1
< 0.1%
2662081 1
< 0.1%
2662083 1
< 0.1%
ValueCountFrequency (%)
2999452 1
< 0.1%
2999431 1
< 0.1%
2999418 1
< 0.1%
2999408 1
< 0.1%
2999407 1
< 0.1%
2999396 1
< 0.1%
2999394 1
< 0.1%
2999391 1
< 0.1%
2999387 1
< 0.1%
2999386 1
< 0.1%

아동청소년보호기관명
Text

Distinct7518
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T04:30:06.627996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length3
Mean length3.7251
Min length2

Characters and Unicode

Total characters37251
Distinct characters539
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6343 ?
Unique (%)63.4%

Sample

1st row소망지역아동센터
2nd row송명애
3rd row이현영
4th row김수련
5th row변지영
ValueCountFrequency (%)
김민정 23
 
0.2%
김지은 16
 
0.2%
김은희 16
 
0.2%
김미선 15
 
0.1%
김현주 15
 
0.1%
김수진 15
 
0.1%
김혜진 14
 
0.1%
이미경 13
 
0.1%
이지영 13
 
0.1%
김수정 13
 
0.1%
Other values (7677) 10060
98.5%
2023-12-13T04:30:07.260708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 1900
 
5.1%
이 1505
 
4.0%
정 1405
 
3.8%
지 1305
 
3.5%
영 1112
 
3.0%
아 958
 
2.6%
희 912
 
2.4%
미 872
 
2.3%
동 858
 
2.3%
경 821
 
2.2%
Other values (529) 25603
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35394
95.0%
Uppercase Letter 1420
 
3.8%
Space Separator 213
 
0.6%
Lowercase Letter 168
 
0.5%
Decimal Number 20
 
0.1%
Open Punctuation 16
 
< 0.1%
Close Punctuation 16
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Other Symbol 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 1900
 
5.4%
이 1505
 
4.3%
정 1405
 
4.0%
지 1305
 
3.7%
영 1112
 
3.1%
아 958
 
2.7%
희 912
 
2.6%
미 872
 
2.5%
동 858
 
2.4%
경 821
 
2.3%
Other values (472) 23746
67.1%
Uppercase Letter
ValueCountFrequency (%)
A 156
 
11.0%
N 142
 
10.0%
E 133
 
9.4%
I 107
 
7.5%
O 91
 
6.4%
R 80
 
5.6%
H 79
 
5.6%
L 76
 
5.4%
S 60
 
4.2%
U 59
 
4.2%
Other values (16) 437
30.8%
Lowercase Letter
ValueCountFrequency (%)
e 23
13.7%
a 21
12.5%
n 16
 
9.5%
o 12
 
7.1%
l 12
 
7.1%
r 11
 
6.5%
i 10
 
6.0%
m 8
 
4.8%
y 7
 
4.2%
h 6
 
3.6%
Other values (12) 42
25.0%
Decimal Number
ValueCountFrequency (%)
1 10
50.0%
8 5
25.0%
3 5
25.0%
Space Separator
ValueCountFrequency (%)
213
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
! 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35394
95.0%
Latin 1588
 
4.3%
Common 268
 
0.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 1900
 
5.4%
이 1505
 
4.3%
정 1405
 
4.0%
지 1305
 
3.7%
영 1112
 
3.1%
아 958
 
2.7%
희 912
 
2.6%
미 872
 
2.5%
동 858
 
2.4%
경 821
 
2.3%
Other values (472) 23746
67.1%
Latin
ValueCountFrequency (%)
A 156
 
9.8%
N 142
 
8.9%
E 133
 
8.4%
I 107
 
6.7%
O 91
 
5.7%
R 80
 
5.0%
H 79
 
5.0%
L 76
 
4.8%
S 60
 
3.8%
U 59
 
3.7%
Other values (38) 605
38.1%
Common
ValueCountFrequency (%)
213
79.5%
( 16
 
6.0%
) 16
 
6.0%
1 10
 
3.7%
8 5
 
1.9%
3 5
 
1.9%
- 2
 
0.7%
! 1
 
0.4%
Han
ValueCountFrequency (%)
聖 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35393
95.0%
ASCII 1856
 
5.0%
CJK 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 1900
 
5.4%
이 1505
 
4.3%
정 1405
 
4.0%
지 1305
 
3.7%
영 1112
 
3.1%
아 958
 
2.7%
희 912
 
2.6%
미 872
 
2.5%
동 858
 
2.4%
경 821
 
2.3%
Other values (471) 23745
67.1%
ASCII
ValueCountFrequency (%)
213
 
11.5%
A 156
 
8.4%
N 142
 
7.7%
E 133
 
7.2%
I 107
 
5.8%
O 91
 
4.9%
R 80
 
4.3%
H 79
 
4.3%
L 76
 
4.1%
S 60
 
3.2%
Other values (46) 719
38.7%
CJK
ValueCountFrequency (%)
聖 1
100.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

시도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
7393 
경상남도
1103 
강원특별자치도
 
603
경상북도
 
271
서울특별시
 
128
Other values (12)
 
502

Length

Max length7
Median length3
Mean length3.4861
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도
2nd row경상남도
3rd row경기도
4th row경상남도
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 7393
73.9%
경상남도 1103
 
11.0%
강원특별자치도 603
 
6.0%
경상북도 271
 
2.7%
서울특별시 128
 
1.3%
전라남도 91
 
0.9%
충청남도 68
 
0.7%
광주광역시 59
 
0.6%
전라북도 57
 
0.6%
부산광역시 43
 
0.4%
Other values (7) 184
 
1.8%

Length

2023-12-13T04:30:07.482068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 7393
73.9%
경상남도 1103
 
11.0%
강원특별자치도 603
 
6.0%
경상북도 271
 
2.7%
서울특별시 128
 
1.3%
전라남도 91
 
0.9%
충청남도 68
 
0.7%
광주광역시 59
 
0.6%
전라북도 57
 
0.6%
부산광역시 43
 
0.4%
Other values (7) 184
 
1.8%

주소지시군구
Text

Distinct217
Distinct (%)2.2%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T04:30:07.926077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length4.4785914
Min length2

Characters and Unicode

Total characters44768
Distinct characters139
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

Unique17 ?
Unique (%)0.2%

Sample

1st row광주시
2nd row창원시 성산구
3rd row시흥시
4th row김해시
5th row군포시
ValueCountFrequency (%)
수원시 795
 
5.9%
고양시 638
 
4.7%
용인시 595
 
4.4%
화성시 514
 
3.8%
김포시 471
 
3.5%
부천시 444
 
3.3%
남양주시 397
 
3.0%
창원시 393
 
2.9%
시흥시 361
 
2.7%
성남시 347
 
2.6%
Other values (216) 8499
63.2%
2023-12-13T04:30:08.495168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 9626
21.5%
구 3909
 
8.7%
3458
 
7.7%
양 1959
 
4.4%
원 1608
 
3.6%
주 1412
 
3.2%
산 1157
 
2.6%
성 1109
 
2.5%
수 1079
 
2.4%
남 1034
 
2.3%
Other values (129) 18417
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41310
92.3%
Space Separator 3458
 
7.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9626
23.3%
구 3909
 
9.5%
양 1959
 
4.7%
원 1608
 
3.9%
주 1412
 
3.4%
산 1157
 
2.8%
성 1109
 
2.7%
수 1079
 
2.6%
남 1034
 
2.5%
천 959
 
2.3%
Other values (128) 17458
42.3%
Space Separator
ValueCountFrequency (%)
3458
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41310
92.3%
Common 3458
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9626
23.3%
구 3909
 
9.5%
양 1959
 
4.7%
원 1608
 
3.9%
주 1412
 
3.4%
산 1157
 
2.8%
성 1109
 
2.7%
수 1079
 
2.6%
남 1034
 
2.5%
천 959
 
2.3%
Other values (128) 17458
42.3%
Common
ValueCountFrequency (%)
3458
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41310
92.3%
ASCII 3458
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 9626
23.3%
구 3909
 
9.5%
양 1959
 
4.7%
원 1608
 
3.9%
주 1412
 
3.4%
산 1157
 
2.8%
성 1109
 
2.7%
수 1079
 
2.6%
남 1034
 
2.5%
천 959
 
2.3%
Other values (128) 17458
42.3%
ASCII
ValueCountFrequency (%)
3458
100.0%

읍면동정보
Text

Distinct1510
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T04:30:08.850684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.5071
Min length2

Characters and Unicode

Total characters35071
Distinct characters296
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

Unique728 ?
Unique (%)7.3%

Sample

1st row고산동
2nd row남양동
3rd row목감동
4th row진영읍 진영리
5th row산본동
ValueCountFrequency (%)
장기동 133
 
1.2%
중동 125
 
1.1%
영통동 122
 
1.1%
정자동 104
 
0.9%
정왕동 87
 
0.8%
매탄동 77
 
0.7%
상동 77
 
0.7%
목동동 70
 
0.6%
다산동 69
 
0.6%
권선동 67
 
0.6%
Other values (1610) 10436
91.8%
2023-12-13T04:30:09.338789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 8826
25.2%
리 1394
 
4.0%
1367
 
3.9%
읍 1182
 
3.4%
산 698
 
2.0%
정 636
 
1.8%
면 565
 
1.6%
곡 542
 
1.5%
양 524
 
1.5%
신 454
 
1.3%
Other values (286) 18883
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33669
96.0%
Space Separator 1367
 
3.9%
Decimal Number 35
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 8826
26.2%
리 1394
 
4.1%
읍 1182
 
3.5%
산 698
 
2.1%
정 636
 
1.9%
면 565
 
1.7%
곡 542
 
1.6%
양 524
 
1.6%
신 454
 
1.3%
장 405
 
1.2%
Other values (280) 18443
54.8%
Decimal Number
ValueCountFrequency (%)
1 15
42.9%
2 15
42.9%
4 2
 
5.7%
3 2
 
5.7%
7 1
 
2.9%
Space Separator
ValueCountFrequency (%)
1367
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33669
96.0%
Common 1402
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 8826
26.2%
리 1394
 
4.1%
읍 1182
 
3.5%
산 698
 
2.1%
정 636
 
1.9%
면 565
 
1.7%
곡 542
 
1.6%
양 524
 
1.6%
신 454
 
1.3%
장 405
 
1.2%
Other values (280) 18443
54.8%
Common
ValueCountFrequency (%)
1367
97.5%
1 15
 
1.1%
2 15
 
1.1%
4 2
 
0.1%
3 2
 
0.1%
7 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33669
96.0%
ASCII 1402
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 8826
26.2%
리 1394
 
4.1%
읍 1182
 
3.5%
산 698
 
2.1%
정 636
 
1.9%
면 565
 
1.7%
곡 542
 
1.6%
양 524
 
1.6%
신 454
 
1.3%
장 405
 
1.2%
Other values (280) 18443
54.8%
ASCII
ValueCountFrequency (%)
1367
97.5%
1 15
 
1.1%
2 15
 
1.1%
4 2
 
0.1%
3 2
 
0.1%
7 1
 
0.1%

행정동명
Text

Distinct1298
Distinct (%)13.0%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T04:30:09.737221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.39984
Min length2

Characters and Unicode

Total characters33995
Distinct characters282
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

Unique535 ?
Unique (%)5.4%

Sample

1st row오포1동
2nd row가음정동
3rd row목감동
4th row진영읍
5th row산본2동
ValueCountFrequency (%)
중앙동 112
 
1.1%
신중동 83
 
0.8%
장기본동 79
 
0.8%
운정2동 70
 
0.7%
범안동 70
 
0.7%
물금읍 67
 
0.7%
장유3동 66
 
0.7%
상동 66
 
0.7%
김포본동 63
 
0.6%
풍무동 62
 
0.6%
Other values (1288) 9261
92.6%
2023-12-13T04:30:10.283085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 8851
26.0%
2 1444
 
4.2%
1 1192
 
3.5%
읍 1130
 
3.3%
3 680
 
2.0%
정 673
 
2.0%
산 595
 
1.8%
면 562
 
1.7%
장 495
 
1.5%
양 487
 
1.4%
Other values (272) 17886
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30260
89.0%
Decimal Number 3729
 
11.0%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 8851
29.2%
읍 1130
 
3.7%
정 673
 
2.2%
산 595
 
2.0%
면 562
 
1.9%
장 495
 
1.6%
양 487
 
1.6%
신 481
 
1.6%
탄 430
 
1.4%
천 419
 
1.4%
Other values (262) 16137
53.3%
Decimal Number
ValueCountFrequency (%)
2 1444
38.7%
1 1192
32.0%
3 680
18.2%
4 225
 
6.0%
5 64
 
1.7%
6 46
 
1.2%
9 34
 
0.9%
7 28
 
0.8%
8 16
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30260
89.0%
Common 3735
 
11.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 8851
29.2%
읍 1130
 
3.7%
정 673
 
2.2%
산 595
 
2.0%
면 562
 
1.9%
장 495
 
1.6%
양 487
 
1.6%
신 481
 
1.6%
탄 430
 
1.4%
천 419
 
1.4%
Other values (262) 16137
53.3%
Common
ValueCountFrequency (%)
2 1444
38.7%
1 1192
31.9%
3 680
18.2%
4 225
 
6.0%
5 64
 
1.7%
6 46
 
1.2%
9 34
 
0.9%
7 28
 
0.7%
8 16
 
0.4%
. 6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30260
89.0%
ASCII 3735
 
11.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 8851
29.2%
읍 1130
 
3.7%
정 673
 
2.2%
산 595
 
2.0%
면 562
 
1.9%
장 495
 
1.6%
양 487
 
1.6%
신 481
 
1.6%
탄 430
 
1.4%
천 419
 
1.4%
Other values (262) 16137
53.3%
ASCII
ValueCountFrequency (%)
2 1444
38.7%
1 1192
31.9%
3 680
18.2%
4 225
 
6.0%
5 64
 
1.7%
6 46
 
1.2%
9 34
 
0.9%
7 28
 
0.7%
8 16
 
0.4%
. 6
 
0.2%

우편번호
Text

Distinct4242
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T04:30:10.731506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9872
Min length4

Characters and Unicode

Total characters49872
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

Unique2350 ?
Unique (%)23.5%

Sample

1st row12790
2nd row51484
3rd row14984
4th row50862
5th row15815
ValueCountFrequency (%)
15002 30
 
0.3%
15011 27
 
0.3%
10073 23
 
0.2%
10077 23
 
0.2%
10891 23
 
0.2%
16295 22
 
0.2%
18477 21
 
0.2%
18429 21
 
0.2%
10893 21
 
0.2%
10130 19
 
0.2%
Other values (4231) 9769
97.7%
2023-12-13T04:30:11.379936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11772
23.6%
0 5094
10.2%
5 5014
10.1%
2 4664
 
9.4%
4 4509
 
9.0%
6 4225
 
8.5%
3 4183
 
8.4%
8 3727
 
7.5%
7 3592
 
7.2%
9 3088
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49868
> 99.9%
Space Separator 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11772
23.6%
0 5094
10.2%
5 5014
10.1%
2 4664
 
9.4%
4 4509
 
9.0%
6 4225
 
8.5%
3 4183
 
8.4%
8 3727
 
7.5%
7 3592
 
7.2%
9 3088
 
6.2%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49872
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11772
23.6%
0 5094
10.2%
5 5014
10.1%
2 4664
 
9.4%
4 4509
 
9.0%
6 4225
 
8.5%
3 4183
 
8.4%
8 3727
 
7.5%
7 3592
 
7.2%
9 3088
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11772
23.6%
0 5094
10.2%
5 5014
10.1%
2 4664
 
9.4%
4 4509
 
9.0%
6 4225
 
8.5%
3 4183
 
8.4%
8 3727
 
7.5%
7 3592
 
7.2%
9 3088
 
6.2%

기관주소
Text

Distinct9963
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T04:30:11.870980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length60
Mean length39.1748
Min length14

Characters and Unicode

Total characters391748
Distinct characters663
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9926 ?
Unique (%)99.3%

Sample

1st row경기도 광주시 고산길39번길 45 (고산동)
2nd row경상남도 창원시 성산구 대암로 22 106동 307호 (남양동 우성아파트)
3rd row경기도 시흥시 동서로 1076 대명아파트 306 (목감동)
4th row경상남도 김해시 진영읍 장등로 55 111동 807호 (진영읍 중흥에스클래스1단지아파트)
5th row경기도 군포시 금산로 91 래미안하이어스 107동 2902호
ValueCountFrequency (%)
경기도 7393
 
9.6%
경상남도 1103
 
1.4%
수원시 795
 
1.0%
고양시 638
 
0.8%
강원특별자치도 603
 
0.8%
용인시 595
 
0.8%
화성시 514
 
0.7%
김포시 471
 
0.6%
부천시 444
 
0.6%
남양주시 397
 
0.5%
Other values (15026) 63727
83.1%
2023-12-13T04:30:12.587980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70316
 
17.9%
1 20005
 
5.1%
0 16767
 
4.3%
동 16697
 
4.3%
2 12257
 
3.1%
시 10825
 
2.8%
도 10315
 
2.6%
경 9084
 
2.3%
3 8742
 
2.2%
로 8704
 
2.2%
Other values (653) 208036
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 215452
55.0%
Decimal Number 85992
 
22.0%
Space Separator 70316
 
17.9%
Open Punctuation 8105
 
2.1%
Close Punctuation 8018
 
2.0%
Dash Punctuation 2570
 
0.7%
Uppercase Letter 866
 
0.2%
Lowercase Letter 268
 
0.1%
Other Punctuation 147
 
< 0.1%
Letter Number 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 16697
 
7.7%
시 10825
 
5.0%
도 10315
 
4.8%
경 9084
 
4.2%
로 8704
 
4.0%
호 8288
 
3.8%
기 7928
 
3.7%
구 4318
 
2.0%
파 4300
 
2.0%
아 4185
 
1.9%
Other values (584) 130808
60.7%
Uppercase Letter
ValueCountFrequency (%)
A 124
14.3%
B 97
11.2%
S 81
 
9.4%
C 78
 
9.0%
L 70
 
8.1%
K 69
 
8.0%
I 43
 
5.0%
P 34
 
3.9%
T 33
 
3.8%
G 32
 
3.7%
Other values (15) 205
23.7%
Lowercase Letter
ValueCountFrequency (%)
e 153
57.1%
a 19
 
7.1%
t 18
 
6.7%
h 15
 
5.6%
r 11
 
4.1%
l 9
 
3.4%
n 8
 
3.0%
p 6
 
2.2%
s 6
 
2.2%
c 5
 
1.9%
Other values (8) 18
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 20005
23.3%
0 16767
19.5%
2 12257
14.3%
3 8742
10.2%
4 6654
 
7.7%
5 5834
 
6.8%
6 4795
 
5.6%
7 4133
 
4.8%
8 3532
 
4.1%
9 3273
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 91
61.9%
· 20
 
13.6%
@ 12
 
8.2%
/ 12
 
8.2%
: 5
 
3.4%
& 5
 
3.4%
' 2
 
1.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
50.0%
Ⅳ 3
25.0%
Ⅰ 2
 
16.7%
Ⅲ 1
 
8.3%
Space Separator
ValueCountFrequency (%)
70316
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8018
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2570
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 215447
55.0%
Common 175150
44.7%
Latin 1146
 
0.3%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 16697
 
7.7%
시 10825
 
5.0%
도 10315
 
4.8%
경 9084
 
4.2%
로 8704
 
4.0%
호 8288
 
3.8%
기 7928
 
3.7%
구 4318
 
2.0%
파 4300
 
2.0%
아 4185
 
1.9%
Other values (581) 130803
60.7%
Latin
ValueCountFrequency (%)
e 153
13.4%
A 124
 
10.8%
B 97
 
8.5%
S 81
 
7.1%
C 78
 
6.8%
L 70
 
6.1%
K 69
 
6.0%
I 43
 
3.8%
P 34
 
3.0%
T 33
 
2.9%
Other values (37) 364
31.8%
Common
ValueCountFrequency (%)
70316
40.1%
1 20005
 
11.4%
0 16767
 
9.6%
2 12257
 
7.0%
3 8742
 
5.0%
( 8105
 
4.6%
) 8018
 
4.6%
4 6654
 
3.8%
5 5834
 
3.3%
6 4795
 
2.7%
Other values (12) 13657
 
7.8%
Han
ValueCountFrequency (%)
家 2
40.0%
林 2
40.0%
騁 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 215446
55.0%
ASCII 176264
45.0%
None 20
 
< 0.1%
Number Forms 12
 
< 0.1%
CJK 5
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70316
39.9%
1 20005
 
11.3%
0 16767
 
9.5%
2 12257
 
7.0%
3 8742
 
5.0%
( 8105
 
4.6%
) 8018
 
4.5%
4 6654
 
3.8%
5 5834
 
3.3%
6 4795
 
2.7%
Other values (54) 14771
 
8.4%
Hangul
ValueCountFrequency (%)
동 16697
 
7.7%
시 10825
 
5.0%
도 10315
 
4.8%
경 9084
 
4.2%
로 8704
 
4.0%
호 8288
 
3.8%
기 7928
 
3.7%
구 4318
 
2.0%
파 4300
 
2.0%
아 4185
 
1.9%
Other values (580) 130802
60.7%
None
ValueCountFrequency (%)
· 20
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
50.0%
Ⅳ 3
25.0%
Ⅰ 2
 
16.7%
Ⅲ 1
 
8.3%
CJK
ValueCountFrequency (%)
家 2
40.0%
林 2
40.0%
騁 1
20.0%
Compat Jamo
ValueCountFrequency (%)
ㄷ 1
100.0%

기관구분값
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
19
9103 
9
 
726
10
 
167
11
 
4

Length

Max length2
Median length2
Mean length1.9274
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row19
3rd row19
4th row19
5th row19

Common Values

ValueCountFrequency (%)
19 9103
91.0%
9 726
 
7.3%
10 167
 
1.7%
11 4
 
< 0.1%

Length

2023-12-13T04:30:12.758050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:30:12.886826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
19 9103
91.0%
9 726
 
7.3%
10 167
 
1.7%
11 4
 
< 0.1%

주소지지도X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct6577
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean573214.52
Minimum309415
Maximum1065351
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:30:13.031693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum309415
5-th percentile437591
Q1467893
median516175
Q3562972.5
95-th percentile935005.45
Maximum1065351
Range755936
Interquartile range (IQR)95079.5

Descriptive statistics

Standard deviation161902.92
Coefficient of variation (CV)0.28244735
Kurtosis1.0667045
Mean573214.52
Median Absolute Deviation (MAD)48132
Skewness1.5277355
Sum5.7321452 × 109
Variance2.6212557 × 1010
MonotonicityNot monotonic
2023-12-13T04:30:13.211015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
501045 22
 
0.2%
508765 18
 
0.2%
428757 17
 
0.2%
441632 15
 
0.1%
462038 14
 
0.1%
534485 14
 
0.1%
855868 13
 
0.1%
441965 13
 
0.1%
885090 12
 
0.1%
515447 12
 
0.1%
Other values (6567) 9850
98.5%
ValueCountFrequency (%)
309415 1
< 0.1%
314105 1
< 0.1%
318323 1
< 0.1%
326966 1
< 0.1%
326975 1
< 0.1%
331610 1
< 0.1%
335303 1
< 0.1%
338541 1
< 0.1%
342573 1
< 0.1%
343037 1
< 0.1%
ValueCountFrequency (%)
1065351 1
< 0.1%
1059344 1
< 0.1%
1054532 1
< 0.1%
1051057 1
< 0.1%
1049768 1
< 0.1%
1049580 1
< 0.1%
1048884 1
< 0.1%
1044695 1
< 0.1%
1044593 1
< 0.1%
1044556 1
< 0.1%

주소지지도Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct6615
Distinct (%)66.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean996526.12
Minimum-76378
Maximum1377076
Zeros0
Zeros (%)0.0%
Negative21
Negative (%)0.2%
Memory size166.0 KiB
2023-12-13T04:30:13.374682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-76378
5-th percentile467896
Q11022789
median1071333
Q31144636.2
95-th percentile1199302.8
Maximum1377076
Range1453454
Interquartile range (IQR)121847.25

Descriptive statistics

Standard deviation236117.83
Coefficient of variation (CV)0.23694094
Kurtosis1.7022766
Mean996526.12
Median Absolute Deviation (MAD)66306
Skewness-1.6636248
Sum9.9652612 × 109
Variance5.575163 × 1010
MonotonicityNot monotonic
2023-12-13T04:30:13.561278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1057523 22
 
0.2%
1045096 18
 
0.2%
1149061 17
 
0.2%
1173490 15
 
0.1%
1142093 14
 
0.1%
1050503 14
 
0.1%
469076 13
 
0.1%
1171612 13
 
0.1%
1137639 12
 
0.1%
1110413 12
 
0.1%
Other values (6605) 9850
98.5%
ValueCountFrequency (%)
-76378 1
< 0.1%
-71184 1
< 0.1%
-69859 1
< 0.1%
-68725 1
< 0.1%
-67222 1
< 0.1%
-66865 1
< 0.1%
-66510 1
< 0.1%
-64352 1
< 0.1%
-63995 1
< 0.1%
-46993 1
< 0.1%
ValueCountFrequency (%)
1377076 1
< 0.1%
1376145 1
< 0.1%
1360565 1
< 0.1%
1358565 1
< 0.1%
1357531 1
< 0.1%
1338963 1
< 0.1%
1325771 1
< 0.1%
1325261 1
< 0.1%
1324593 1
< 0.1%
1323758 1
< 0.1%

완료여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
10000 
ValueCountFrequency (%)
True 10000
100.0%
2023-12-13T04:30:13.705116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

교육기관시도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
7393 
경상남도
1103 
강원특별자치도
 
603
경상북도
 
271
서울특별시
 
128
Other values (12)
 
502

Length

Max length7
Median length3
Mean length3.4861
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도
2nd row경상남도
3rd row경기도
4th row경상남도
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 7393
73.9%
경상남도 1103
 
11.0%
강원특별자치도 603
 
6.0%
경상북도 271
 
2.7%
서울특별시 128
 
1.3%
전라남도 91
 
0.9%
충청남도 68
 
0.7%
광주광역시 59
 
0.6%
전라북도 57
 
0.6%
부산광역시 43
 
0.4%
Other values (7) 184
 
1.8%

Length

2023-12-13T04:30:13.849090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 7393
73.9%
경상남도 1103
 
11.0%
강원특별자치도 603
 
6.0%
경상북도 271
 
2.7%
서울특별시 128
 
1.3%
전라남도 91
 
0.9%
충청남도 68
 
0.7%
광주광역시 59
 
0.6%
전라북도 57
 
0.6%
부산광역시 43
 
0.4%
Other values (7) 184
 
1.8%

교육기관시군구
Text

Distinct217
Distinct (%)2.2%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T04:30:14.230974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length4.4785914
Min length2

Characters and Unicode

Total characters44768
Distinct characters139
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

Unique17 ?
Unique (%)0.2%

Sample

1st row광주시
2nd row창원시 성산구
3rd row시흥시
4th row김해시
5th row군포시
ValueCountFrequency (%)
수원시 795
 
5.9%
고양시 638
 
4.7%
용인시 595
 
4.4%
화성시 514
 
3.8%
김포시 471
 
3.5%
부천시 444
 
3.3%
남양주시 397
 
3.0%
창원시 393
 
2.9%
시흥시 361
 
2.7%
성남시 347
 
2.6%
Other values (216) 8499
63.2%
2023-12-13T04:30:14.722977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 9626
21.5%
구 3909
 
8.7%
3458
 
7.7%
양 1959
 
4.4%
원 1608
 
3.6%
주 1412
 
3.2%
산 1157
 
2.6%
성 1109
 
2.5%
수 1079
 
2.4%
남 1034
 
2.3%
Other values (129) 18417
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41310
92.3%
Space Separator 3458
 
7.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9626
23.3%
구 3909
 
9.5%
양 1959
 
4.7%
원 1608
 
3.9%
주 1412
 
3.4%
산 1157
 
2.8%
성 1109
 
2.7%
수 1079
 
2.6%
남 1034
 
2.5%
천 959
 
2.3%
Other values (128) 17458
42.3%
Space Separator
ValueCountFrequency (%)
3458
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41310
92.3%
Common 3458
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9626
23.3%
구 3909
 
9.5%
양 1959
 
4.7%
원 1608
 
3.9%
주 1412
 
3.4%
산 1157
 
2.8%
성 1109
 
2.7%
수 1079
 
2.6%
남 1034
 
2.5%
천 959
 
2.3%
Other values (128) 17458
42.3%
Common
ValueCountFrequency (%)
3458
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41310
92.3%
ASCII 3458
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 9626
23.3%
구 3909
 
9.5%
양 1959
 
4.7%
원 1608
 
3.9%
주 1412
 
3.4%
산 1157
 
2.8%
성 1109
 
2.7%
수 1079
 
2.6%
남 1034
 
2.5%
천 959
 
2.3%
Other values (128) 17458
42.3%
ASCII
ValueCountFrequency (%)
3458
100.0%

교육기관읍면동
Text

Distinct1298
Distinct (%)13.0%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T04:30:15.031033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.39984
Min length2

Characters and Unicode

Total characters33995
Distinct characters282
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

Unique535 ?
Unique (%)5.4%

Sample

1st row오포1동
2nd row가음정동
3rd row목감동
4th row진영읍
5th row산본2동
ValueCountFrequency (%)
중앙동 112
 
1.1%
신중동 83
 
0.8%
장기본동 79
 
0.8%
운정2동 70
 
0.7%
범안동 70
 
0.7%
물금읍 67
 
0.7%
장유3동 66
 
0.7%
상동 66
 
0.7%
김포본동 63
 
0.6%
풍무동 62
 
0.6%
Other values (1288) 9261
92.6%
2023-12-13T04:30:15.535247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 8851
26.0%
2 1444
 
4.2%
1 1192
 
3.5%
읍 1130
 
3.3%
3 680
 
2.0%
정 673
 
2.0%
산 595
 
1.8%
면 562
 
1.7%
장 495
 
1.5%
양 487
 
1.4%
Other values (272) 17886
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30260
89.0%
Decimal Number 3729
 
11.0%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 8851
29.2%
읍 1130
 
3.7%
정 673
 
2.2%
산 595
 
2.0%
면 562
 
1.9%
장 495
 
1.6%
양 487
 
1.6%
신 481
 
1.6%
탄 430
 
1.4%
천 419
 
1.4%
Other values (262) 16137
53.3%
Decimal Number
ValueCountFrequency (%)
2 1444
38.7%
1 1192
32.0%
3 680
18.2%
4 225
 
6.0%
5 64
 
1.7%
6 46
 
1.2%
9 34
 
0.9%
7 28
 
0.8%
8 16
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30260
89.0%
Common 3735
 
11.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 8851
29.2%
읍 1130
 
3.7%
정 673
 
2.2%
산 595
 
2.0%
면 562
 
1.9%
장 495
 
1.6%
양 487
 
1.6%
신 481
 
1.6%
탄 430
 
1.4%
천 419
 
1.4%
Other values (262) 16137
53.3%
Common
ValueCountFrequency (%)
2 1444
38.7%
1 1192
31.9%
3 680
18.2%
4 225
 
6.0%
5 64
 
1.7%
6 46
 
1.2%
9 34
 
0.9%
7 28
 
0.7%
8 16
 
0.4%
. 6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30260
89.0%
ASCII 3735
 
11.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 8851
29.2%
읍 1130
 
3.7%
정 673
 
2.2%
산 595
 
2.0%
면 562
 
1.9%
장 495
 
1.6%
양 487
 
1.6%
신 481
 
1.6%
탄 430
 
1.4%
천 419
 
1.4%
Other values (262) 16137
53.3%
ASCII
ValueCountFrequency (%)
2 1444
38.7%
1 1192
31.9%
3 680
18.2%
4 225
 
6.0%
5 64
 
1.7%
6 46
 
1.2%
9 34
 
0.9%
7 28
 
0.7%
8 16
 
0.4%
. 6
 
0.2%

Interactions

2023-12-13T04:30:04.739821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:03.500068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:04.242182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:04.899664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:03.662181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:04.396737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:05.047542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:03.853204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:04.581996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:30:15.644773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호시도기관구분값주소지지도X좌표주소지지도Y좌표교육기관시도
일련번호1.0000.6910.7840.3600.4940.691
시도0.6911.0000.6980.8320.9021.000
기관구분값0.7840.6981.0000.2640.4660.698
주소지지도X좌표0.3600.8320.2641.0000.8530.832
주소지지도Y좌표0.4940.9020.4660.8531.0000.902
교육기관시도0.6911.0000.6980.8320.9021.000
2023-12-13T04:30:15.762163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도교육기관시도기관구분값
시도1.0001.0000.470
교육기관시도1.0001.0000.470
기관구분값0.4700.4701.000
2023-12-13T04:30:15.883402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호주소지지도X좌표주소지지도Y좌표시도기관구분값교육기관시도
일련번호1.0000.1230.0420.4130.6280.413
주소지지도X좌표0.1231.000-0.4270.5160.1630.516
주소지지도Y좌표0.042-0.4271.0000.6500.2960.650
시도0.4130.5160.6501.0000.4701.000
기관구분값0.6280.1630.2960.4701.0000.470
교육기관시도0.4130.5160.6501.0000.4701.000

Missing values

2023-12-13T04:30:05.281852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:30:05.553360image/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.
2023-12-13T04:30:05.745364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

일련번호아동청소년보호기관명시도주소지시군구읍면동정보행정동명우편번호기관주소기관구분값주소지지도X좌표주소지지도Y좌표완료여부교육기관시도교육기관시군구교육기관읍면동
532662098소망지역아동센터경기도광주시고산동오포1동12790경기도 광주시 고산길39번길 45 (고산동)95497371075628Y경기도광주시오포1동
545922992458송명애경상남도창원시 성산구남양동가음정동51484경상남도 창원시 성산구 대암로 22 106동 307호 (남양동 우성아파트)19886814480288Y경상남도창원시 성산구가음정동
399792977845이현영경기도시흥시목감동목감동14984경기도 시흥시 동서로 1076 대명아파트 306 (목감동)194690631079286Y경기도시흥시목감동
577682995634김수련경상남도김해시진영읍 진영리진영읍50862경상남도 김해시 진영읍 장등로 55 111동 807호 (진영읍 중흥에스클래스1단지아파트)19894450507311Y경상남도김해시진영읍
198682957734변지영경기도군포시산본동산본2동15815경기도 군포시 금산로 91 래미안하이어스 107동 2902호194860171075012Y경기도군포시산본2동
30322715208울림사회적협동조합꾸러기지역아동센터서울특별시강북구미아동송중동1163서울특별시 강북구 도봉로28나길 7 1층 3층 (미아동)95070251144736Y서울특별시강북구송중동
519442989810오춘혜경기도파주시문산읍 문산리문산읍10820경기도 파주시 방촌로 1648 104동 1403호(파주문산신원아침도시아파트)194515121211460Y경기도파주시문산읍
155752953440김은숙경기도성남시 분당구분당동분당동13581경기도 성남시 분당구 수내로 201 404동 401호 (분당동 샛별마을)195287321075616Y경기도성남시 분당구분당동
189602956826안혜란경기도광명시하안동하안2동14245경기도 광명시 안현로 15 103동 801호(하안동 하안주공1단지아파트)194718341101385Y경기도광명시하안2동
568072994673최양정경상남도통영시용남면 동달리용남면53030경상남도 통영시 용남면 대곡길 12 206동 1301호 (용남면 통영청구하이츠아파트)19829373382611Y경상남도통영시용남면
일련번호아동청소년보호기관명시도주소지시군구읍면동정보행정동명우편번호기관주소기관구분값주소지지도X좌표주소지지도Y좌표완료여부교육기관시도교육기관시군구교육기관읍면동
247112962577김선희경기도부천시옥길동범안동14790경기도 부천시 범안로 220 106동 1204호 (옥길동 옥길호반베르디움)194581711101167Y경기도부천시범안동
468372984703한선경경기도고양시 일산서구일산동일산1동10351경기도 고양시 일산서구 고양대로 633 108동 805호(일산동 동양아파트)194486421162886Y경기도고양시 일산서구일산1동
91112946968오현주경기도수원시 영통구하동광교2동16514경기도 수원시 영통구 센트럴파크로 6 102동 2304호 (하동 힐스테이트 광교)195143861052074Y경기도수원시 영통구광교2동
298292967695권미영경기도화성시청계동동탄4동18477경기도 화성시 동탄대로시범길 20 1419동 3003호 (청계동 동탄역 시범한화 꿈에그린 프레스티지)195221261027022Y경기도화성시동탄4동
140062951870김은지경기도수원시 권선구권선동권선1동16568경기도 수원시 권선구 세권로207번길 16 101동 101호 (권선동 금성아파트)195061471043458Y경기도수원시 권선구권선1동
495212987387한송이경기도남양주시호평동호평동12141경기도 남양주시 천마산로25 101동 205호(호평동)195541751157113Y경기도남양주시호평동
397142977580이미숙경기도김포시감정동김포본동10102경기도 김포시 감정동 676 한국아파트 106동 603호194337761146340Y경기도김포시김포본동
330472970913한문광경기도시흥시하상동연성동14977경기도 시흥시 상직길 9 태평아파트 101동 102호(하상동)194585921080707Y경기도시흥시연성동
67252944582이윤정강원특별자치도춘천시퇴계동퇴계동24420강원특별자치도 춘천시 지석로 64 604동 706호 (퇴계동 퇴계(6)주공아파트)196634251209163Y강원특별자치도춘천시퇴계동
609422998808이경화경상북도포항시 남구동해면 도구리동해면37926경상북도 포항시 남구 동해면 연오로15번길 20 B동 103호 (동해면 리빙타운)191051057698337Y경상북도포항시 남구동해면