Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells28
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory888.7 KiB
Average record size in memory91.0 B

Variable types

Categorical3
Text4
Numeric3

Alerts

시설구분명 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 21:30:57.999552
Analysis finished2023-12-10 21:31:00.947638
Duration2.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
1101 
화성시
734 
용인시
706 
남양주시
657 
성남시
646 
Other values (26)
6156 

Length

Max length4
Median length3
Mean length3.1191
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부천시
2nd row용인시
3rd row성남시
4th row의정부시
5th row고양시

Common Values

ValueCountFrequency (%)
수원시 1101
 
11.0%
화성시 734
 
7.3%
용인시 706
 
7.1%
남양주시 657
 
6.6%
성남시 646
 
6.5%
고양시 569
 
5.7%
부천시 476
 
4.8%
시흥시 468
 
4.7%
파주시 443
 
4.4%
의정부시 423
 
4.2%
Other values (21) 3777
37.8%

Length

2023-12-11T06:31:01.006139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 1101
 
11.0%
화성시 734
 
7.3%
용인시 706
 
7.1%
남양주시 657
 
6.6%
성남시 646
 
6.5%
고양시 569
 
5.7%
부천시 476
 
4.8%
시흥시 468
 
4.7%
파주시 443
 
4.4%
의정부시 423
 
4.2%
Other values (21) 3777
37.8%

시설구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
어린이집
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 10000
100.0%

Length

2023-12-11T06:31:01.104577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:31:01.181489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 10000
100.0%

공사립구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가정
5258 
민간
3238 
국공립
1025 
직장
 
261
법인·단체
 
95
Other values (3)
 
123

Length

Max length6
Median length2
Mean length2.1546
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가정 5258
52.6%
민간 3238
32.4%
국공립 1025
 
10.2%
직장 261
 
2.6%
법인·단체 95
 
0.9%
협동 63
 
0.6%
사회복지법인 58
 
0.6%
부모협동 2
 
< 0.1%

Length

2023-12-11T06:31:01.277393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:31:01.380003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가정 5258
52.6%
민간 3238
32.4%
국공립 1025
 
10.2%
직장 261
 
2.6%
법인·단체 95
 
0.9%
협동 63
 
0.6%
사회복지법인 58
 
0.6%
부모협동 2
 
< 0.1%

시설명
Text

Distinct6693
Distinct (%)66.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:31:01.578830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length7.658
Min length1

Characters and Unicode

Total characters76580
Distinct characters730
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5614 ?
Unique (%)56.1%

Sample

1st row참조은어린이집
2nd row에벤에셀어린이집
3rd row빛나는어린이집
4th row아이뜰어린이집
5th row햇살가득어린이집
ValueCountFrequency (%)
어린이집 247
 
2.4%
아이숲어린이집 19
 
0.2%
다솜어린이집 19
 
0.2%
아이사랑어린이집 18
 
0.2%
아이뜰어린이집 17
 
0.2%
새싹어린이집 17
 
0.2%
해맑은어린이집 17
 
0.2%
꿈나무어린이집 17
 
0.2%
사과나무어린이집 16
 
0.2%
동화나라어린이집 16
 
0.2%
Other values (6708) 9969
96.1%
2023-12-11T06:31:02.060373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 11038
 
14.4%
린 9719
 
12.7%
어 9606
 
12.5%
집 9554
 
12.5%
아 1487
 
1.9%
시 785
 
1.0%
리 764
 
1.0%
사 721
 
0.9%
립 682
 
0.9%
나 668
 
0.9%
Other values (720) 31556
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75507
98.6%
Space Separator 372
 
0.5%
Uppercase Letter 279
 
0.4%
Lowercase Letter 186
 
0.2%
Decimal Number 180
 
0.2%
Dash Punctuation 15
 
< 0.1%
Close Punctuation 14
 
< 0.1%
Open Punctuation 14
 
< 0.1%
Other Punctuation 11
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 11038
 
14.6%
린 9719
 
12.9%
어 9606
 
12.7%
집 9554
 
12.7%
아 1487
 
2.0%
시 785
 
1.0%
리 764
 
1.0%
사 721
 
1.0%
립 682
 
0.9%
나 668
 
0.9%
Other values (654) 30483
40.4%
Uppercase Letter
ValueCountFrequency (%)
S 41
14.7%
K 37
13.3%
C 25
 
9.0%
I 24
 
8.6%
A 21
 
7.5%
B 20
 
7.2%
E 15
 
5.4%
L 11
 
3.9%
T 11
 
3.9%
G 9
 
3.2%
Other values (16) 65
23.3%
Lowercase Letter
ValueCountFrequency (%)
i 44
23.7%
e 28
15.1%
s 18
9.7%
k 14
 
7.5%
d 9
 
4.8%
n 9
 
4.8%
l 8
 
4.3%
a 7
 
3.8%
c 7
 
3.8%
m 7
 
3.8%
Other values (10) 35
18.8%
Decimal Number
ValueCountFrequency (%)
2 64
35.6%
1 39
21.7%
3 29
16.1%
5 12
 
6.7%
4 11
 
6.1%
7 8
 
4.4%
6 7
 
3.9%
9 6
 
3.3%
0 4
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 4
36.4%
! 3
27.3%
& 2
18.2%
? 1
 
9.1%
＆ 1
 
9.1%
Other Symbol
ValueCountFrequency (%)
♥ 1
50.0%
★ 1
50.0%
Space Separator
ValueCountFrequency (%)
372
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75505
98.6%
Common 608
 
0.8%
Latin 465
 
0.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 11038
 
14.6%
린 9719
 
12.9%
어 9606
 
12.7%
집 9554
 
12.7%
아 1487
 
2.0%
시 785
 
1.0%
리 764
 
1.0%
사 721
 
1.0%
립 682
 
0.9%
나 668
 
0.9%
Other values (653) 30481
40.4%
Latin
ValueCountFrequency (%)
i 44
 
9.5%
S 41
 
8.8%
K 37
 
8.0%
e 28
 
6.0%
C 25
 
5.4%
I 24
 
5.2%
A 21
 
4.5%
B 20
 
4.3%
s 18
 
3.9%
E 15
 
3.2%
Other values (36) 192
41.3%
Common
ValueCountFrequency (%)
372
61.2%
2 64
 
10.5%
1 39
 
6.4%
3 29
 
4.8%
- 15
 
2.5%
) 14
 
2.3%
( 14
 
2.3%
5 12
 
2.0%
4 11
 
1.8%
7 8
 
1.3%
Other values (10) 30
 
4.9%
Han
ValueCountFrequency (%)
愛 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75505
98.6%
ASCII 1070
 
1.4%
CJK 2
 
< 0.1%
Misc Symbols 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 11038
 
14.6%
린 9719
 
12.9%
어 9606
 
12.7%
집 9554
 
12.7%
아 1487
 
2.0%
시 785
 
1.0%
리 764
 
1.0%
사 721
 
1.0%
립 682
 
0.9%
나 668
 
0.9%
Other values (653) 30481
40.4%
ASCII
ValueCountFrequency (%)
372
34.8%
2 64
 
6.0%
i 44
 
4.1%
S 41
 
3.8%
1 39
 
3.6%
K 37
 
3.5%
3 29
 
2.7%
e 28
 
2.6%
C 25
 
2.3%
I 24
 
2.2%
Other values (53) 367
34.3%
CJK
ValueCountFrequency (%)
愛 2
100.0%
Misc Symbols
ValueCountFrequency (%)
♥ 1
50.0%
★ 1
50.0%
None
ValueCountFrequency (%)
＆ 1
100.0%

전화번호
Text

Distinct9978
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:31:02.284954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.0498
Min length11

Characters and Unicode

Total characters120498
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

Unique9964 ?
Unique (%)99.6%

Sample

1st row032-321-5496
2nd row031-263-8044
3rd row070-8193-3215
4th row031-878-3144
5th row031-976-7911
ValueCountFrequency (%)
000-0000-0000 6
 
0.1%
031-0000-0000 6
 
0.1%
031-948-2385 2
 
< 0.1%
031-511-0951 2
 
< 0.1%
031-000-0000 2
 
< 0.1%
031-865-7738 2
 
< 0.1%
031-273-9999 2
 
< 0.1%
031-847-8159 2
 
< 0.1%
031-944-6607 2
 
< 0.1%
031-838-1241 2
 
< 0.1%
Other values (9968) 9972
99.7%
2023-12-11T06:31:02.636760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 20000
16.6%
0 17295
14.4%
3 17235
14.3%
1 15415
12.8%
2 8737
7.3%
7 8061
6.7%
5 7470
 
6.2%
8 6824
 
5.7%
9 6624
 
5.5%
6 6584
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100498
83.4%
Dash Punctuation 20000
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17295
17.2%
3 17235
17.1%
1 15415
15.3%
2 8737
8.7%
7 8061
8.0%
5 7470
7.4%
8 6824
 
6.8%
9 6624
 
6.6%
6 6584
 
6.6%
4 6253
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120498
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 20000
16.6%
0 17295
14.4%
3 17235
14.3%
1 15415
12.8%
2 8737
7.3%
7 8061
6.7%
5 7470
 
6.2%
8 6824
 
5.7%
9 6624
 
5.5%
6 6584
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 20000
16.6%
0 17295
14.4%
3 17235
14.3%
1 15415
12.8%
2 8737
7.3%
7 8061
6.7%
5 7470
 
6.2%
8 6824
 
5.7%
9 6624
 
5.5%
6 6584
 
5.5%

소재지지번주소
Text

Distinct9970
Distinct (%)99.8%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2023-12-11T06:31:02.940161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length47
Mean length33.620735
Min length11

Characters and Unicode

Total characters335972
Distinct characters602
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9949 ?
Unique (%)99.6%

Sample

1st row경기도 부천시 상동 393번지 한아름아파트 1529동 101호
2nd row경기도 용인시 수지구 성복동 726번지 성동마을엘지빌리지3차아파트 302동 103호
3rd row경기도 성남시 중원구 상대원동 279-1번지 선경아파트 102동 101호
4th row경기도 의정부시 호원동 308-139번지 회룡역풍림아이원아파트 204동 103호
5th row경기도 고양시 일산서구 일산동 1670번지 산들마을5단지아파트 506동 101호
ValueCountFrequency (%)
경기도 10002
 
15.3%
101호 1280
 
2.0%
102호 1140
 
1.7%
수원시 1101
 
1.7%
103호 928
 
1.4%
104호 815
 
1.2%
관리동 804
 
1.2%
화성시 735
 
1.1%
용인시 706
 
1.1%
남양주시 655
 
1.0%
Other values (11004) 47378
72.3%
2023-12-11T06:31:03.377175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55551
 
16.5%
1 19518
 
5.8%
동 16081
 
4.8%
지 12974
 
3.9%
0 11885
 
3.5%
시 11127
 
3.3%
도 10608
 
3.2%
기 10483
 
3.1%
경 10163
 
3.0%
번 9976
 
3.0%
Other values (592) 167606
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 204109
60.8%
Decimal Number 70856
 
21.1%
Space Separator 55551
 
16.5%
Dash Punctuation 4139
 
1.2%
Uppercase Letter 807
 
0.2%
Other Punctuation 229
 
0.1%
Lowercase Letter 154
 
< 0.1%
Close Punctuation 52
 
< 0.1%
Open Punctuation 51
 
< 0.1%
Math Symbol 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 16081
 
7.9%
지 12974
 
6.4%
시 11127
 
5.5%
도 10608
 
5.2%
기 10483
 
5.1%
경 10163
 
5.0%
번 9976
 
4.9%
호 5648
 
2.8%
파 4999
 
2.4%
아 4944
 
2.4%
Other values (532) 107106
52.5%
Uppercase Letter
ValueCountFrequency (%)
L 97
12.0%
S 83
10.3%
E 81
10.0%
K 76
9.4%
C 73
9.0%
H 63
 
7.8%
A 57
 
7.1%
G 44
 
5.5%
B 29
 
3.6%
D 25
 
3.1%
Other values (14) 179
22.2%
Lowercase Letter
ValueCountFrequency (%)
e 102
66.2%
s 19
 
12.3%
k 6
 
3.9%
c 6
 
3.9%
h 5
 
3.2%
l 4
 
2.6%
t 3
 
1.9%
i 2
 
1.3%
p 2
 
1.3%
a 2
 
1.3%
Other values (3) 3
 
1.9%
Decimal Number
ValueCountFrequency (%)
1 19518
27.5%
0 11885
16.8%
2 7814
11.0%
3 5963
 
8.4%
4 5098
 
7.2%
5 5037
 
7.1%
6 4543
 
6.4%
7 3960
 
5.6%
8 3770
 
5.3%
9 3268
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 126
55.0%
. 92
40.2%
/ 5
 
2.2%
? 4
 
1.7%
& 2
 
0.9%
Math Symbol
ValueCountFrequency (%)
~ 20
90.9%
> 1
 
4.5%
< 1
 
4.5%
Space Separator
ValueCountFrequency (%)
55551
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 204108
60.8%
Common 130902
39.0%
Latin 961
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 16081
 
7.9%
지 12974
 
6.4%
시 11127
 
5.5%
도 10608
 
5.2%
기 10483
 
5.1%
경 10163
 
5.0%
번 9976
 
4.9%
호 5648
 
2.8%
파 4999
 
2.4%
아 4944
 
2.4%
Other values (531) 107105
52.5%
Latin
ValueCountFrequency (%)
e 102
 
10.6%
L 97
 
10.1%
S 83
 
8.6%
E 81
 
8.4%
K 76
 
7.9%
C 73
 
7.6%
H 63
 
6.6%
A 57
 
5.9%
G 44
 
4.6%
B 29
 
3.0%
Other values (27) 256
26.6%
Common
ValueCountFrequency (%)
55551
42.4%
1 19518
 
14.9%
0 11885
 
9.1%
2 7814
 
6.0%
3 5963
 
4.6%
4 5098
 
3.9%
5 5037
 
3.8%
6 4543
 
3.5%
- 4139
 
3.2%
7 3960
 
3.0%
Other values (13) 7394
 
5.6%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 204107
60.8%
ASCII 131863
39.2%
Compat Jamo 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55551
42.1%
1 19518
 
14.8%
0 11885
 
9.0%
2 7814
 
5.9%
3 5963
 
4.5%
4 5098
 
3.9%
5 5037
 
3.8%
6 4543
 
3.4%
- 4139
 
3.1%
7 3960
 
3.0%
Other values (50) 8355
 
6.3%
Hangul
ValueCountFrequency (%)
동 16081
 
7.9%
지 12974
 
6.4%
시 11127
 
5.5%
도 10608
 
5.2%
기 10483
 
5.1%
경 10163
 
5.0%
번 9976
 
4.9%
호 5648
 
2.8%
파 4999
 
2.4%
아 4944
 
2.4%
Other values (530) 107104
52.5%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%
CJK
ValueCountFrequency (%)
內 1
100.0%

소재지도로명주소
Text

Distinct9982
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:31:03.666082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length49
Mean length36.0525
Min length13

Characters and Unicode

Total characters360525
Distinct characters638
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9965 ?
Unique (%)99.7%

Sample

1st row경기도 부천시 부흥로 100 1529동 101호(상동, 한아름아파트)
2nd row경기도 용인시 수지구 성복2로 126 302동 103호(성복동, 성동마을엘지빌리지3차아파트)
3rd row경기도 성남시 중원구 금상로 134 102동 101호(상대원동, 선경아파트)
4th row경기도 의정부시 외미로 64 204동 103호(호원동, 회룡역풍림아이원아파트)
5th row경기도 고양시 일산서구 일중로 30 506동 101호(일산동, 산들마을5단지아파트)
ValueCountFrequency (%)
경기도 10014
 
14.8%
수원시 1101
 
1.6%
관리동 889
 
1.3%
화성시 737
 
1.1%
용인시 706
 
1.0%
남양주시 657
 
1.0%
성남시 649
 
1.0%
고양시 570
 
0.8%
부천시 476
 
0.7%
시흥시 472
 
0.7%
Other values (13469) 51432
76.0%
2023-12-11T06:31:04.112717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
57836
 
16.0%
1 20083
 
5.6%
동 14610
 
4.1%
0 11753
 
3.3%
시 11175
 
3.1%
도 10665
 
3.0%
기 10569
 
2.9%
경 10472
 
2.9%
로 9514
 
2.6%
2 9020
 
2.5%
Other values (628) 194828
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 210676
58.4%
Decimal Number 70403
 
19.5%
Space Separator 57836
 
16.0%
Open Punctuation 6900
 
1.9%
Close Punctuation 6899
 
1.9%
Other Punctuation 4779
 
1.3%
Dash Punctuation 2203
 
0.6%
Uppercase Letter 675
 
0.2%
Lowercase Letter 130
 
< 0.1%
Math Symbol 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 14610
 
6.9%
시 11175
 
5.3%
도 10665
 
5.1%
기 10569
 
5.0%
경 10472
 
5.0%
로 9514
 
4.5%
호 5444
 
2.6%
파 4763
 
2.3%
아 4708
 
2.2%
트 4370
 
2.1%
Other values (570) 124386
59.0%
Uppercase Letter
ValueCountFrequency (%)
L 79
11.7%
S 75
11.1%
E 74
11.0%
K 72
10.7%
A 68
10.1%
H 53
7.9%
C 53
7.9%
G 42
 
6.2%
B 21
 
3.1%
P 18
 
2.7%
Other values (14) 120
17.8%
Lowercase Letter
ValueCountFrequency (%)
e 80
61.5%
s 18
 
13.8%
k 6
 
4.6%
c 6
 
4.6%
a 5
 
3.8%
l 4
 
3.1%
t 3
 
2.3%
h 3
 
2.3%
i 2
 
1.5%
y 1
 
0.8%
Other values (2) 2
 
1.5%
Decimal Number
ValueCountFrequency (%)
1 20083
28.5%
0 11753
16.7%
2 9020
12.8%
3 6520
 
9.3%
4 5081
 
7.2%
5 4712
 
6.7%
6 4034
 
5.7%
7 3511
 
5.0%
8 2945
 
4.2%
9 2744
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 4672
97.8%
. 90
 
1.9%
/ 12
 
0.3%
? 5
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 20
90.9%
< 1
 
4.5%
> 1
 
4.5%
Space Separator
ValueCountFrequency (%)
57836
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6900
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6899
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2203
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 210675
58.4%
Common 149044
41.3%
Latin 805
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 14610
 
6.9%
시 11175
 
5.3%
도 10665
 
5.1%
기 10569
 
5.0%
경 10472
 
5.0%
로 9514
 
4.5%
호 5444
 
2.6%
파 4763
 
2.3%
아 4708
 
2.2%
트 4370
 
2.1%
Other values (569) 124385
59.0%
Latin
ValueCountFrequency (%)
e 80
9.9%
L 79
9.8%
S 75
 
9.3%
E 74
 
9.2%
K 72
 
8.9%
A 68
 
8.4%
H 53
 
6.6%
C 53
 
6.6%
G 42
 
5.2%
B 21
 
2.6%
Other values (26) 188
23.4%
Common
ValueCountFrequency (%)
57836
38.8%
1 20083
 
13.5%
0 11753
 
7.9%
2 9020
 
6.1%
( 6900
 
4.6%
) 6899
 
4.6%
3 6520
 
4.4%
4 5081
 
3.4%
5 4712
 
3.2%
, 4672
 
3.1%
Other values (12) 15568
 
10.4%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 210674
58.4%
ASCII 149849
41.6%
CJK 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
57836
38.6%
1 20083
 
13.4%
0 11753
 
7.8%
2 9020
 
6.0%
( 6900
 
4.6%
) 6899
 
4.6%
3 6520
 
4.4%
4 5081
 
3.4%
5 4712
 
3.1%
, 4672
 
3.1%
Other values (48) 16373
 
10.9%
Hangul
ValueCountFrequency (%)
동 14610
 
6.9%
시 11175
 
5.3%
도 10665
 
5.1%
기 10569
 
5.0%
경 10472
 
5.0%
로 9514
 
4.5%
호 5444
 
2.6%
파 4763
 
2.3%
아 4708
 
2.2%
트 4370
 
2.1%
Other values (568) 124384
59.0%
CJK
ValueCountFrequency (%)
內 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct3282
Distinct (%)32.8%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean14378.509
Minimum10005
Maximum18632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:31:04.246922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10005
5-th percentile10301
Q112047
median14493
Q316690
95-th percentile18407
Maximum18632
Range8627
Interquartile range (IQR)4643

Descriptive statistics

Standard deviation2628.0839
Coefficient of variation (CV)0.18277861
Kurtosis-1.2930926
Mean14378.509
Median Absolute Deviation (MAD)2348
Skewness-0.037069521
Sum1.437132 × 108
Variance6906824.9
MonotonicityNot monotonic
2023-12-11T06:31:04.356286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15010 46
 
0.5%
11812 29
 
0.3%
10070 25
 
0.2%
10073 24
 
0.2%
18484 22
 
0.2%
14923 21
 
0.2%
10068 21
 
0.2%
10895 20
 
0.2%
12251 20
 
0.2%
16698 19
 
0.2%
Other values (3272) 9748
97.5%
ValueCountFrequency (%)
10005 1
 
< 0.1%
10012 1
 
< 0.1%
10016 3
< 0.1%
10017 2
 
< 0.1%
10018 3
< 0.1%
10019 5
0.1%
10021 1
 
< 0.1%
10031 3
< 0.1%
10032 4
< 0.1%
10037 1
 
< 0.1%
ValueCountFrequency (%)
18632 1
 
< 0.1%
18623 1
 
< 0.1%
18622 1
 
< 0.1%
18616 1
 
< 0.1%
18615 4
< 0.1%
18614 2
 
< 0.1%
18613 6
0.1%
18612 1
 
< 0.1%
18611 3
< 0.1%
18610 7
0.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct9244
Distinct (%)92.5%
Missing8
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean37.434514
Minimum36.951203
Maximum38.158877
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:31:04.470928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.951203
5-th percentile37.077624
Q137.27525
median37.391965
Q337.638173
95-th percentile37.796384
Maximum38.158877
Range1.2076742
Interquartile range (IQR)0.36292334

Descriptive statistics

Standard deviation0.2207098
Coefficient of variation (CV)0.0058958907
Kurtosis-0.63779501
Mean37.434514
Median Absolute Deviation (MAD)0.1480065
Skewness0.2129179
Sum374045.67
Variance0.048712818
MonotonicityNot monotonic
2023-12-11T06:31:04.611521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6115918 16
 
0.2%
37.2543241 9
 
0.1%
37.726232 7
 
0.1%
37.7496528 7
 
0.1%
37.8246967 7
 
0.1%
37.2363523 7
 
0.1%
37.2463833 7
 
0.1%
37.7310427 7
 
0.1%
37.4749942 6
 
0.1%
37.7716715 6
 
0.1%
Other values (9234) 9913
99.1%
(Missing) 8
 
0.1%
ValueCountFrequency (%)
36.9512029715 1
< 0.1%
36.9517666318 1
< 0.1%
36.9563987261 1
< 0.1%
36.9576412931 1
< 0.1%
36.9599472203 1
< 0.1%
36.9601679407 1
< 0.1%
36.9603820342 1
< 0.1%
36.9613355905 1
< 0.1%
36.9613566529 1
< 0.1%
36.9616744086 1
< 0.1%
ValueCountFrequency (%)
38.158877195 1
< 0.1%
38.1095320661 1
< 0.1%
38.1090938769 1
< 0.1%
38.0964663782 1
< 0.1%
38.0927508943 1
< 0.1%
38.091908273 1
< 0.1%
38.0917668245 1
< 0.1%
38.0905998143 1
< 0.1%
38.0889911776 1
< 0.1%
38.0870515563 1
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct9244
Distinct (%)92.5%
Missing8
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean127.00958
Minimum126.55376
Maximum127.75134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:31:04.767347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55376
5-th percentile126.72855
Q1126.84902
median127.04474
Q3127.12418
95-th percentile127.27572
Maximum127.75134
Range1.197583
Interquartile range (IQR)0.27515727

Descriptive statistics

Standard deviation0.18565007
Coefficient of variation (CV)0.0014617013
Kurtosis0.19069588
Mean127.00958
Median Absolute Deviation (MAD)0.11655185
Skewness0.23830912
Sum1269079.7
Variance0.034465948
MonotonicityNot monotonic
2023-12-11T06:31:04.896457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1602068 16
 
0.2%
127.0654752 9
 
0.1%
126.7441798 7
 
0.1%
127.1153388 7
 
0.1%
127.0199797 7
 
0.1%
127.0603157 7
 
0.1%
126.9733113 7
 
0.1%
127.089397 7
 
0.1%
126.7514102 6
 
0.1%
127.1525944 6
 
0.1%
Other values (9234) 9913
99.1%
(Missing) 8
 
0.1%
ValueCountFrequency (%)
126.5537612382 1
< 0.1%
126.5684198594 1
< 0.1%
126.5815586321 1
< 0.1%
126.5879878609 1
< 0.1%
126.5921729358 1
< 0.1%
126.5937122283 1
< 0.1%
126.5939262162 1
< 0.1%
126.5941793253 1
< 0.1%
126.5943919211 1
< 0.1%
126.5954407931 1
< 0.1%
ValueCountFrequency (%)
127.7513442 1
< 0.1%
127.7115372 1
< 0.1%
127.687916 1
< 0.1%
127.6792366 1
< 0.1%
127.6759631 1
< 0.1%
127.6736858 1
< 0.1%
127.6630823 1
< 0.1%
127.6597718 1
< 0.1%
127.6582504 1
< 0.1%
127.6567238 1
< 0.1%

Interactions

2023-12-11T06:31:00.218868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:59.667876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:59.939333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:31:00.313900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:59.741953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:31:00.030346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:31:00.423651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:59.835364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:31:00.125733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:31:04.985771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명공사립구분명소재지우편번호WGS84위도WGS84경도
시군명1.0000.2670.9910.9610.939
공사립구분명0.2671.0000.1570.1440.133
소재지우편번호0.9910.1571.0000.9180.860
WGS84위도0.9610.1440.9181.0000.647
WGS84경도0.9390.1330.8600.6471.000
2023-12-11T06:31:05.069643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사립구분명시군명
공사립구분명1.0000.107
시군명0.1071.000
2023-12-11T06:31:05.144734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명공사립구분명
소재지우편번호1.000-0.9290.1960.9260.076
WGS84위도-0.9291.000-0.1680.7740.069
WGS84경도0.196-0.1681.0000.6980.063
시군명0.9260.7740.6981.0000.107
공사립구분명0.0760.0690.0630.1071.000

Missing values

2023-12-11T06:31:00.564397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:31:00.759133image/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.
2023-12-11T06:31:00.882010image/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

시군명시설구분명공사립구분명시설명전화번호소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도
2983부천시어린이집가정참조은어린이집032-321-5496경기도 부천시 상동 393번지 한아름아파트 1529동 101호경기도 부천시 부흥로 100 1529동 101호(상동, 한아름아파트)1459637.494922126.752925
7641용인시어린이집가정에벤에셀어린이집031-263-8044경기도 용인시 수지구 성복동 726번지 성동마을엘지빌리지3차아파트 302동 103호경기도 용인시 수지구 성복2로 126 302동 103호(성복동, 성동마을엘지빌리지3차아파트)1685137.316649127.072049
3432성남시어린이집가정빛나는어린이집070-8193-3215경기도 성남시 중원구 상대원동 279-1번지 선경아파트 102동 101호경기도 성남시 중원구 금상로 134 102동 101호(상대원동, 선경아파트)1320837.440069127.168039
7945의정부시어린이집가정아이뜰어린이집031-878-3144경기도 의정부시 호원동 308-139번지 회룡역풍림아이원아파트 204동 103호경기도 의정부시 외미로 64 204동 103호(호원동, 회룡역풍림아이원아파트)1163637.72387127.041992
479고양시어린이집가정햇살가득어린이집031-976-7911경기도 고양시 일산서구 일산동 1670번지 산들마을5단지아파트 506동 101호경기도 고양시 일산서구 일중로 30 506동 101호(일산동, 산들마을5단지아파트)1035437.680967126.774822
4904수원시어린이집민간솔마루어린이집031-222-4242경기도 수원시 권선구 세류동 1148-12번지경기도 수원시 권선구 경수대로225번길 66 (세류동)1665837.248655127.015258
772광명시어린이집민간다솜어린이집02-897-5580경기도 광명시 소하동 937-2번지경기도 광명시 영당로 18 (소하동)1433337.434902126.877668
1117광주시어린이집민간너울가지어린이집031-766-5521경기도 광주시 송정동 90-13번지경기도 광주시 수하길 30 (송정동)1274137.414824127.263568
4815수원시어린이집가정꽃별어린이집031-215-0210경기도 수원시 영통구 매탄동 810-2번지 동남아파트 1동 115호경기도 수원시 영통구 동수원로 432 1동 115호 (매탄동, 동남아파트)1653737.267309127.042577
2606동두천시어린이집민간좋은열매어린이집031-864-8852경기도 동두천시 생연동 791-2번지경기도 동두천시 강변로336번길 18 (생연동)1134237.899633127.047008
시군명시설구분명공사립구분명시설명전화번호소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도
10303화성시어린이집민간숲속키즈어린이집031-298-7164경기도 화성시 봉담읍 하가등리 415번지 (도로명 미고시 지역)경기도 화성시 봉담읍 신양2길 166 (도로명 미고시 지역)1833637.145738126.929647
9217평택시어린이집민간야호 어린이집031-657-3488경기도 평택시 비전동 225-25번지경기도 평택시 신한4길 26-1 (비전동)1789936.992934127.106044
5941안성시어린이집가정꼬망새어린이집031-672-1969경기도 안성시 일죽면 송천리 610번지 일죽IC타운아파트 104동 107호경기도 안성시 일죽면 서동대로 7416-10 104동 107호(송천리, 일죽IC타운 아파트)1752937.089849127.472331
2711부천시어린이집민간꿈동산어린이집032-655-6556경기도 부천시 원미동 151-1번지 두산아파트 관리동 1층경기도 부천시 원미로144번길 51 관리동 1층 (원미동, 두산아파트)1456337.494823126.794069
3492성남시어린이집민간새봄어린이집031-745-5220경기도 성남시 중원구 금광동 3208번지 금광빌라 1층경기도 성남시 중원구 광명로361번길 15 1층 (금광동)1317637.447524127.165264
8110의정부시어린이집법인·단체의정부어린이집031-844-5490경기도 의정부시 의정부동 226-10번지경기도 의정부시 가능로136번길 7 (의정부동)1169037.746572127.046712
1390군포시어린이집가정은빛어린이집031-392-5553경기도 군포시 산본동 1156-1번지 한라1차아파트 407동 112호경기도 군포시 번영로 380 407동 112호(산본동, 한라1차아파트)1587037.348887126.928147
50고양시어린이집국공립고양시립아이솔어린이집031-963-9090경기도 고양시 덕양구 원흥동 614번지 고양삼송엘에이치10단지아파트 1003동경기도 고양시 덕양구 원흥1로 31 1003동1056237.651946126.865715
3295성남시어린이집법인·단체선사어린이집031-723-9407경기도 성남시 수정구 사송동 631-10번지경기도 성남시 수정구 탄천로319번길 4 (사송동)1344637.420164127.116189
1805김포시어린이집국공립시립한강숲속어린이집031-986-7535경기도 김포시 장기동 2060-2번지 김포한강LH 1단지 관리동 어린이집경기도 김포시 허산길 50 김포한강LH 1단지 관리동 어린이집1008637.636782126.667908