Overview

Dataset statistics

Number of variables10
Number of observations6171
Missing cells3238
Missing cells (%)5.2%
Duplicate rows21
Duplicate rows (%)0.3%
Total size in memory500.3 KiB
Average record size in memory83.0 B

Variable types

Categorical2
Text5
Numeric3

Alerts

Dataset has 21 (0.3%) duplicate rowsDuplicates
시군명 is highly overall correlated with 정제우편번호 and 3 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 정제우편번호 and 2 other fieldsHigh correlation
정제우편번호 is highly overall correlated with 정제WGS84위도 and 2 other fieldsHigh correlation
정제WGS84위도 is highly overall correlated with 정제우편번호 and 2 other fieldsHigh correlation
정제WGS84경도 is highly overall correlated with 시군명High correlation
취득일 has 1333 (21.6%) missing valuesMissing
정제도로명주소 has 1259 (20.4%) missing valuesMissing
정제우편번호 has 214 (3.5%) missing valuesMissing
정제WGS84위도 has 216 (3.5%) missing valuesMissing
정제WGS84경도 has 216 (3.5%) missing valuesMissing

Reproduction

Analysis started2024-04-11 04:55:50.848904
Analysis finished2024-04-11 04:55:54.390559
Duration3.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
수원시
640 
안양시
537 
포천시
505 
이천시
463 
파주시
453 
Other values (26)
3573 

Length

Max length4
Median length3
Mean length3.0427807
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
수원시 640
 
10.4%
안양시 537
 
8.7%
포천시 505
 
8.2%
이천시 463
 
7.5%
파주시 453
 
7.3%
양평군 445
 
7.2%
안산시 413
 
6.7%
부천시 365
 
5.9%
가평군 336
 
5.4%
성남시 276
 
4.5%
Other values (21) 1738
28.2%

Length

2024-04-11T13:55:54.449173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 640
 
10.4%
안양시 537
 
8.7%
포천시 505
 
8.2%
이천시 463
 
7.5%
파주시 453
 
7.3%
양평군 445
 
7.2%
안산시 413
 
6.7%
부천시 365
 
5.9%
가평군 336
 
5.4%
성남시 276
 
4.5%
Other values (21) 1738
28.2%

건축물명
Text

Distinct5664
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
2024-04-11T13:55:54.723999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length31
Mean length9.4547075
Min length2

Characters and Unicode

Total characters58345
Distinct characters666
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5450 ?
Unique (%)88.3%

Sample

1st row수리산 탐방안내소
2nd row포천병원 본관동 환경개선
3rd row안성 원곡119안전센터
4th row안산 신길119안전센터
5th row화성 봉담 119안전센터
ValueCountFrequency (%)
경로당 121
 
1.3%
행정복지센터 104
 
1.2%
마을회관 102
 
1.1%
공중화장실 83
 
0.9%
및 73
 
0.8%
화장실 69
 
0.8%
수원환경사업소 41
 
0.5%
경기도 33
 
0.4%
하수종말처리장 31
 
0.3%
주민센터 28
 
0.3%
Other values (6219) 8327
92.4%
2024-04-11T13:55:55.131162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2881
 
4.9%
동 1888
 
3.2%
장 1784
 
3.1%
관 1538
 
2.6%
지 1194
 
2.0%
리 1109
 
1.9%
소 1100
 
1.9%
수 1013
 
1.7%
) 962
 
1.6%
터 957
 
1.6%
Other values (656) 43919
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51370
88.0%
Space Separator 2881
 
4.9%
Decimal Number 1717
 
2.9%
Close Punctuation 963
 
1.7%
Open Punctuation 944
 
1.6%
Uppercase Letter 289
 
0.5%
Dash Punctuation 118
 
0.2%
Other Punctuation 33
 
0.1%
Lowercase Letter 14
 
< 0.1%
Other Symbol 9
 
< 0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1888
 
3.7%
장 1784
 
3.5%
관 1538
 
3.0%
지 1194
 
2.3%
리 1109
 
2.2%
소 1100
 
2.1%
수 1013
 
2.0%
터 957
 
1.9%
시 937
 
1.8%
사 937
 
1.8%
Other values (596) 38913
75.8%
Uppercase Letter
ValueCountFrequency (%)
B 45
15.6%
A 44
15.2%
C 43
14.9%
D 21
 
7.3%
E 21
 
7.3%
M 19
 
6.6%
T 14
 
4.8%
G 11
 
3.8%
S 11
 
3.8%
L 7
 
2.4%
Other values (15) 53
18.3%
Decimal Number
ValueCountFrequency (%)
1 630
36.7%
2 432
25.2%
3 199
 
11.6%
9 106
 
6.2%
4 89
 
5.2%
5 65
 
3.8%
6 55
 
3.2%
0 50
 
2.9%
8 47
 
2.7%
7 44
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
i 4
28.6%
c 2
14.3%
t 2
14.3%
v 1
 
7.1%
n 1
 
7.1%
h 1
 
7.1%
b 1
 
7.1%
y 1
 
7.1%
a 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 12
36.4%
/ 8
24.2%
, 4
 
12.1%
· 3
 
9.1%
: 3
 
9.1%
' 2
 
6.1%
? 1
 
3.0%
Close Punctuation
ValueCountFrequency (%)
) 962
99.9%
] 1
 
0.1%
Other Symbol
ValueCountFrequency (%)
㎡ 8
88.9%
㎥ 1
 
11.1%
Space Separator
ValueCountFrequency (%)
2881
100.0%
Open Punctuation
ValueCountFrequency (%)
( 944
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51370
88.0%
Common 6672
 
11.4%
Latin 303
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1888
 
3.7%
장 1784
 
3.5%
관 1538
 
3.0%
지 1194
 
2.3%
리 1109
 
2.2%
소 1100
 
2.1%
수 1013
 
2.0%
터 957
 
1.9%
시 937
 
1.8%
사 937
 
1.8%
Other values (596) 38913
75.8%
Latin
ValueCountFrequency (%)
B 45
14.9%
A 44
14.5%
C 43
14.2%
D 21
 
6.9%
E 21
 
6.9%
M 19
 
6.3%
T 14
 
4.6%
G 11
 
3.6%
S 11
 
3.6%
L 7
 
2.3%
Other values (24) 67
22.1%
Common
ValueCountFrequency (%)
2881
43.2%
) 962
 
14.4%
( 944
 
14.1%
1 630
 
9.4%
2 432
 
6.5%
3 199
 
3.0%
- 118
 
1.8%
9 106
 
1.6%
4 89
 
1.3%
5 65
 
1.0%
Other values (16) 246
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51370
88.0%
ASCII 6963
 
11.9%
CJK Compat 9
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2881
41.4%
) 962
 
13.8%
( 944
 
13.6%
1 630
 
9.0%
2 432
 
6.2%
3 199
 
2.9%
- 118
 
1.7%
9 106
 
1.5%
4 89
 
1.3%
5 65
 
0.9%
Other values (47) 537
 
7.7%
Hangul
ValueCountFrequency (%)
동 1888
 
3.7%
장 1784
 
3.5%
관 1538
 
3.0%
지 1194
 
2.3%
리 1109
 
2.2%
소 1100
 
2.1%
수 1013
 
2.0%
터 957
 
1.9%
시 937
 
1.8%
사 937
 
1.8%
Other values (596) 38913
75.8%
CJK Compat
ValueCountFrequency (%)
㎡ 8
88.9%
㎥ 1
 
11.1%
None
ValueCountFrequency (%)
· 3
100.0%

면적
Text

Distinct5286
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
2024-04-11T13:55:55.434643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length15
Mean length6.4986226
Min length1

Characters and Unicode

Total characters40103
Distinct characters70
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4842 ?
Unique (%)78.5%

Sample

1st row연면적 685.59㎡
2nd row리모델링공사
3rd row연면적 942㎡
4th row연면적 990㎡
5th row연면적 893㎡
ValueCountFrequency (%)
연면적 1437
 
18.7%
건축면적 34
 
0.4%
12.96 21
 
0.3%
100.98 16
 
0.2%
232.81 13
 
0.2%
198 13
 
0.2%
60 12
 
0.2%
40 12
 
0.2%
36 11
 
0.1%
132 10
 
0.1%
Other values (5281) 6087
79.4%
2024-04-11T13:55:55.852069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4799
12.0%
1 4065
10.1%
2 3381
 
8.4%
4 2911
 
7.3%
3 2744
 
6.8%
6 2690
 
6.7%
9 2673
 
6.7%
8 2553
 
6.4%
5 2481
 
6.2%
7 2365
 
5.9%
Other values (60) 9441
23.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27821
69.4%
Other Punctuation 5046
 
12.6%
Other Letter 4540
 
11.3%
Space Separator 1495
 
3.7%
Other Symbol 1191
 
3.0%
Uppercase Letter 4
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 1478
32.6%
적 1477
32.5%
연 1438
31.7%
축 36
 
0.8%
건 34
 
0.7%
개 4
 
0.1%
지 3
 
0.1%
장 3
 
0.1%
성 3
 
0.1%
사 3
 
0.1%
Other values (41) 61
 
1.3%
Decimal Number
ValueCountFrequency (%)
1 4065
14.6%
2 3381
12.2%
4 2911
10.5%
3 2744
9.9%
6 2690
9.7%
9 2673
9.6%
8 2553
9.2%
5 2481
8.9%
7 2365
8.5%
0 1958
7.0%
Other Punctuation
ValueCountFrequency (%)
. 4799
95.1%
, 247
 
4.9%
Other Symbol
ValueCountFrequency (%)
㎡ 1190
99.9%
㎥ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1495
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35557
88.7%
Hangul 4540
 
11.3%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 1478
32.6%
적 1477
32.5%
연 1438
31.7%
축 36
 
0.8%
건 34
 
0.7%
개 4
 
0.1%
지 3
 
0.1%
장 3
 
0.1%
성 3
 
0.1%
사 3
 
0.1%
Other values (41) 61
 
1.3%
Common
ValueCountFrequency (%)
. 4799
13.5%
1 4065
11.4%
2 3381
9.5%
4 2911
8.2%
3 2744
7.7%
6 2690
7.6%
9 2673
7.5%
8 2553
7.2%
5 2481
7.0%
7 2365
6.7%
Other values (7) 4895
13.8%
Latin
ValueCountFrequency (%)
F 4
66.7%
m 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34372
85.7%
Hangul 4540
 
11.3%
CJK Compat 1191
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4799
14.0%
1 4065
11.8%
2 3381
9.8%
4 2911
8.5%
3 2744
8.0%
6 2690
7.8%
9 2673
7.8%
8 2553
7.4%
5 2481
7.2%
7 2365
6.9%
Other values (7) 3710
10.8%
Hangul
ValueCountFrequency (%)
면 1478
32.6%
적 1477
32.5%
연 1438
31.7%
축 36
 
0.8%
건 34
 
0.7%
개 4
 
0.1%
지 3
 
0.1%
장 3
 
0.1%
성 3
 
0.1%
사 3
 
0.1%
Other values (41) 61
 
1.3%
CJK Compat
ValueCountFrequency (%)
㎡ 1190
99.9%
㎥ 1
 
0.1%

취득일
Text

MISSING 

Distinct2985
Distinct (%)61.7%
Missing1333
Missing (%)21.6%
Memory size48.3 KiB
2024-04-11T13:55:56.121745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters48380
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

Unique2150 ?
Unique (%)44.4%

Sample

1st row2019-05-09
2nd row2017-09-21
3rd row2014-03-26
4th row2007-07-26
5th row2009-04-22
ValueCountFrequency (%)
2018-01-31 27
 
0.6%
1995-02-28 27
 
0.6%
2007-12-28 23
 
0.5%
2019-01-01 22
 
0.5%
2003-10-30 19
 
0.4%
2012-06-29 17
 
0.4%
2005-02-28 17
 
0.4%
2018-01-01 16
 
0.3%
2012-05-22 16
 
0.3%
2008-02-01 15
 
0.3%
Other values (2975) 4639
95.9%
2024-04-11T13:55:56.471809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10981
22.7%
- 9676
20.0%
1 8135
16.8%
2 7635
15.8%
9 3480
 
7.2%
3 1802
 
3.7%
8 1709
 
3.5%
5 1401
 
2.9%
6 1267
 
2.6%
7 1238
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38704
80.0%
Dash Punctuation 9676
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10981
28.4%
1 8135
21.0%
2 7635
19.7%
9 3480
 
9.0%
3 1802
 
4.7%
8 1709
 
4.4%
5 1401
 
3.6%
6 1267
 
3.3%
7 1238
 
3.2%
4 1056
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 9676
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48380
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10981
22.7%
- 9676
20.0%
1 8135
16.8%
2 7635
15.8%
9 3480
 
7.2%
3 1802
 
3.7%
8 1709
 
3.5%
5 1401
 
2.9%
6 1267
 
2.6%
7 1238
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10981
22.7%
- 9676
20.0%
1 8135
16.8%
2 7635
15.8%
9 3480
 
7.2%
3 1802
 
3.7%
8 1709
 
3.5%
5 1401
 
2.9%
6 1267
 
2.6%
7 1238
 
2.6%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
2024-03-06
958 
2023-03-21
902 
2023-03-20
859 
2024-03-18
619 
2024-03-15
463 
Other values (15)
2370 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2024-03-06 958
15.5%
2023-03-21 902
14.6%
2023-03-20 859
13.9%
2024-03-18 619
10.0%
2024-03-15 463
7.5%
2024-02-27 442
7.2%
2023-03-23 377
 
6.1%
2023-03-22 373
 
6.0%
2024-02-14 336
 
5.4%
2023-03-16 164
 
2.7%
Other values (10) 678
11.0%

Length

2024-04-11T13:55:56.759896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-03-06 958
15.5%
2023-03-21 902
14.6%
2023-03-20 859
13.9%
2024-03-18 619
10.0%
2024-03-15 463
7.5%
2024-02-27 442
7.2%
2023-03-23 377
 
6.1%
2023-03-22 373
 
6.0%
2024-02-14 336
 
5.4%
2023-03-16 164
 
2.7%
Other values (10) 678
11.0%

정제도로명주소
Text

MISSING 

Distinct3571
Distinct (%)72.7%
Missing1259
Missing (%)20.4%
Memory size48.3 KiB
2024-04-11T13:55:57.019356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length19.712744
Min length13

Characters and Unicode

Total characters96829
Distinct characters400
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2987 ?
Unique (%)60.8%

Sample

1st row경기도 군포시 속달로 347-4
2nd row경기도 포천시 포천로 1648
3rd row경기도 안성시 원곡면 원곡물류단지로 162-20
4th row경기도 안산시 단원구 삼일로 50
5th row경기도 화성시 봉담읍 동화새터길 135
ValueCountFrequency (%)
경기도 4912
 
21.3%
수원시 507
 
2.2%
포천시 435
 
1.9%
안양시 424
 
1.8%
이천시 368
 
1.6%
파주시 344
 
1.5%
안산시 332
 
1.4%
부천시 314
 
1.4%
양평군 311
 
1.3%
성남시 265
 
1.1%
Other values (3794) 14862
64.4%
2024-04-11T13:55:57.409490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18162
18.8%
경 5108
 
5.3%
도 5008
 
5.2%
기 4995
 
5.2%
시 4547
 
4.7%
로 4219
 
4.4%
1 3556
 
3.7%
2 2255
 
2.3%
길 2235
 
2.3%
3 1974
 
2.0%
Other values (390) 44770
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60351
62.3%
Space Separator 18162
 
18.8%
Decimal Number 17347
 
17.9%
Dash Punctuation 969
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 5108
 
8.5%
도 5008
 
8.3%
기 4995
 
8.3%
시 4547
 
7.5%
로 4219
 
7.0%
길 2235
 
3.7%
구 1848
 
3.1%
안 1611
 
2.7%
천 1557
 
2.6%
번 1478
 
2.4%
Other values (378) 27745
46.0%
Decimal Number
ValueCountFrequency (%)
1 3556
20.5%
2 2255
13.0%
3 1974
11.4%
4 1633
9.4%
5 1527
8.8%
6 1381
 
8.0%
0 1378
 
7.9%
7 1247
 
7.2%
8 1227
 
7.1%
9 1169
 
6.7%
Space Separator
ValueCountFrequency (%)
18162
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 969
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60351
62.3%
Common 36478
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 5108
 
8.5%
도 5008
 
8.3%
기 4995
 
8.3%
시 4547
 
7.5%
로 4219
 
7.0%
길 2235
 
3.7%
구 1848
 
3.1%
안 1611
 
2.7%
천 1557
 
2.6%
번 1478
 
2.4%
Other values (378) 27745
46.0%
Common
ValueCountFrequency (%)
18162
49.8%
1 3556
 
9.7%
2 2255
 
6.2%
3 1974
 
5.4%
4 1633
 
4.5%
5 1527
 
4.2%
6 1381
 
3.8%
0 1378
 
3.8%
7 1247
 
3.4%
8 1227
 
3.4%
Other values (2) 2138
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60351
62.3%
ASCII 36478
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18162
49.8%
1 3556
 
9.7%
2 2255
 
6.2%
3 1974
 
5.4%
4 1633
 
4.5%
5 1527
 
4.2%
6 1381
 
3.8%
0 1378
 
3.8%
7 1247
 
3.4%
8 1227
 
3.4%
Other values (2) 2138
 
5.9%
Hangul
ValueCountFrequency (%)
경 5108
 
8.5%
도 5008
 
8.3%
기 4995
 
8.3%
시 4547
 
7.5%
로 4219
 
7.0%
길 2235
 
3.7%
구 1848
 
3.1%
안 1611
 
2.7%
천 1557
 
2.6%
번 1478
 
2.4%
Other values (378) 27745
46.0%

정제지번주소
Text

Distinct4507
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Memory size48.3 KiB
2024-04-11T13:55:57.646903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length20.332199
Min length13

Characters and Unicode

Total characters125470
Distinct characters380
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3824 ?
Unique (%)62.0%

Sample

1st row경기도 군포시 속달동 306번지 일원
2nd row경기도 포천시 신읍동 243-1번지
3rd row경기도 안성시 원곡면 칠곡리 928-3
4th row경기도 안산시 단원구 신길동 1691번지
5th row경기도 화성시 봉담읍 동화리 621번지
ValueCountFrequency (%)
경기도 6169
 
20.5%
수원시 624
 
2.1%
포천시 509
 
1.7%
안양시 506
 
1.7%
이천시 465
 
1.5%
파주시 455
 
1.5%
양평군 446
 
1.5%
안산시 428
 
1.4%
부천시 368
 
1.2%
가평군 338
 
1.1%
Other values (5153) 19853
65.8%
2024-04-11T13:55:58.044596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23991
19.1%
도 6302
 
5.0%
기 6254
 
5.0%
경 6214
 
5.0%
시 5515
 
4.4%
1 4893
 
3.9%
동 4805
 
3.8%
- 3936
 
3.1%
2 2973
 
2.4%
3 2596
 
2.1%
Other values (370) 57991
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73508
58.6%
Space Separator 23991
 
19.1%
Decimal Number 23898
 
19.0%
Dash Punctuation 3936
 
3.1%
Open Punctuation 52
 
< 0.1%
Close Punctuation 52
 
< 0.1%
Uppercase Letter 22
 
< 0.1%
Other Punctuation 9
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 6302
 
8.6%
기 6254
 
8.5%
경 6214
 
8.5%
시 5515
 
7.5%
동 4805
 
6.5%
구 2263
 
3.1%
리 2235
 
3.0%
양 1966
 
2.7%
안 1944
 
2.6%
천 1757
 
2.4%
Other values (340) 34253
46.6%
Uppercase Letter
ValueCountFrequency (%)
B 8
36.4%
A 4
18.2%
I 2
 
9.1%
T 1
 
4.5%
P 1
 
4.5%
J 1
 
4.5%
N 1
 
4.5%
L 1
 
4.5%
C 1
 
4.5%
D 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 4893
20.5%
2 2973
12.4%
3 2596
10.9%
5 2320
9.7%
4 2300
9.6%
6 2009
8.4%
7 1921
 
8.0%
0 1741
 
7.3%
8 1599
 
6.7%
9 1546
 
6.5%
Other Punctuation
ValueCountFrequency (%)
, 7
77.8%
. 1
 
11.1%
? 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
c 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
23991
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3936
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73507
58.6%
Common 51938
41.4%
Latin 24
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 6302
 
8.6%
기 6254
 
8.5%
경 6214
 
8.5%
시 5515
 
7.5%
동 4805
 
6.5%
구 2263
 
3.1%
리 2235
 
3.0%
양 1966
 
2.7%
안 1944
 
2.6%
천 1757
 
2.4%
Other values (339) 34252
46.6%
Common
ValueCountFrequency (%)
23991
46.2%
1 4893
 
9.4%
- 3936
 
7.6%
2 2973
 
5.7%
3 2596
 
5.0%
5 2320
 
4.5%
4 2300
 
4.4%
6 2009
 
3.9%
7 1921
 
3.7%
0 1741
 
3.4%
Other values (7) 3258
 
6.3%
Latin
ValueCountFrequency (%)
B 8
33.3%
A 4
16.7%
I 2
 
8.3%
T 1
 
4.2%
P 1
 
4.2%
J 1
 
4.2%
N 1
 
4.2%
c 1
 
4.2%
L 1
 
4.2%
e 1
 
4.2%
Other values (3) 3
 
12.5%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73507
58.6%
ASCII 51962
41.4%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23991
46.2%
1 4893
 
9.4%
- 3936
 
7.6%
2 2973
 
5.7%
3 2596
 
5.0%
5 2320
 
4.5%
4 2300
 
4.4%
6 2009
 
3.9%
7 1921
 
3.7%
0 1741
 
3.4%
Other values (20) 3282
 
6.3%
Hangul
ValueCountFrequency (%)
도 6302
 
8.6%
기 6254
 
8.5%
경 6214
 
8.5%
시 5515
 
7.5%
동 4805
 
6.5%
구 2263
 
3.1%
리 2235
 
3.0%
양 1966
 
2.7%
안 1944
 
2.6%
천 1757
 
2.4%
Other values (339) 34252
46.6%
CJK
ValueCountFrequency (%)
內 1
100.0%

정제우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2152
Distinct (%)36.1%
Missing214
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean13896.396
Minimum1377
Maximum18626
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-11T13:55:58.185787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1377
5-th percentile10801
Q112280
median13831
Q316041
95-th percentile17519
Maximum18626
Range17249
Interquartile range (IQR)3761

Descriptive statistics

Standard deviation2326.4234
Coefficient of variation (CV)0.167412
Kurtosis-0.92369356
Mean13896.396
Median Absolute Deviation (MAD)1929
Skewness0.16432468
Sum82780828
Variance5412245.9
MonotonicityNot monotonic
2024-04-11T13:55:58.313584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17379 38
 
0.6%
18130 35
 
0.6%
12422 30
 
0.5%
11139 30
 
0.5%
13912 29
 
0.5%
14089 28
 
0.5%
13922 27
 
0.4%
18355 27
 
0.4%
11101 25
 
0.4%
10811 24
 
0.4%
Other values (2142) 5664
91.8%
(Missing) 214
 
3.5%
ValueCountFrequency (%)
1377 2
 
< 0.1%
10046 1
 
< 0.1%
10068 1
 
< 0.1%
10109 1
 
< 0.1%
10210 2
 
< 0.1%
10212 1
 
< 0.1%
10215 1
 
< 0.1%
10218 2
 
< 0.1%
10222 2
 
< 0.1%
10223 7
0.1%
ValueCountFrequency (%)
18626 1
 
< 0.1%
18527 1
 
< 0.1%
18388 2
 
< 0.1%
18358 8
 
0.1%
18355 27
0.4%
18298 1
 
< 0.1%
18151 3
 
< 0.1%
18150 1
 
< 0.1%
18148 1
 
< 0.1%
18147 1
 
< 0.1%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct4190
Distinct (%)70.4%
Missing216
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean37.498516
Minimum36.916889
Maximum38.18295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-11T13:55:58.434597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.916889
5-th percentile37.149716
Q137.30179
median37.439634
Q337.698574
95-th percentile37.934078
Maximum38.18295
Range1.2660606
Interquartile range (IQR)0.39678419

Descriptive statistics

Standard deviation0.24912358
Coefficient of variation (CV)0.0066435584
Kurtosis-0.54399669
Mean37.498516
Median Absolute Deviation (MAD)0.15610098
Skewness0.50625019
Sum223303.66
Variance0.062062557
MonotonicityNot monotonic
2024-04-11T13:55:58.601426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4183798984 27
 
0.4%
37.3889976474 27
 
0.4%
37.8773715659 24
 
0.4%
37.4018698265 21
 
0.3%
37.1404782493 19
 
0.3%
37.3831019563 18
 
0.3%
37.8557615302 18
 
0.3%
37.5131520747 17
 
0.3%
37.3810305854 17
 
0.3%
37.1797651409 16
 
0.3%
Other values (4180) 5751
93.2%
(Missing) 216
 
3.5%
ValueCountFrequency (%)
36.9168894764 1
< 0.1%
36.9350364703 1
< 0.1%
36.9433047732 2
< 0.1%
36.943676386 1
< 0.1%
36.9517666318 1
< 0.1%
36.9597572254 1
< 0.1%
36.9602913498 1
< 0.1%
36.9645754499 2
< 0.1%
36.9651786777 1
< 0.1%
36.9673433617 1
< 0.1%
ValueCountFrequency (%)
38.182950099 1
< 0.1%
38.1666893514 1
< 0.1%
38.1664994489 1
< 0.1%
38.1661954165 1
< 0.1%
38.1659979498 1
< 0.1%
38.1623108065 1
< 0.1%
38.1604142789 1
< 0.1%
38.1603753855 1
< 0.1%
38.1588427797 2
< 0.1%
38.1581025812 1
< 0.1%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct4190
Distinct (%)70.4%
Missing216
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean127.09936
Minimum126.38913
Maximum127.79132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.4 KiB
2024-04-11T13:55:58.766540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.38913
5-th percentile126.75436
Q1126.86973
median127.05435
Q3127.28755
95-th percentile127.54276
Maximum127.79132
Range1.4021954
Interquartile range (IQR)0.41782112

Descriptive statistics

Standard deviation0.26582667
Coefficient of variation (CV)0.002091487
Kurtosis-0.7856847
Mean127.09936
Median Absolute Deviation (MAD)0.2013854
Skewness0.38980635
Sum756876.71
Variance0.070663816
MonotonicityNot monotonic
2024-04-11T13:55:58.959802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9183187069 27
 
0.4%
126.9280462689 27
 
0.4%
126.8048065471 24
 
0.4%
126.9667477669 21
 
0.3%
127.0645822452 19
 
0.3%
126.9704727553 18
 
0.3%
127.1190825052 18
 
0.3%
126.7452297663 17
 
0.3%
126.9778048454 17
 
0.3%
127.445102989 16
 
0.3%
Other values (4180) 5751
93.2%
(Missing) 216
 
3.5%
ValueCountFrequency (%)
126.3891261111 1
< 0.1%
126.3915488852 1
< 0.1%
126.3923701162 1
< 0.1%
126.3929010601 1
< 0.1%
126.450515871 1
< 0.1%
126.4532254318 1
< 0.1%
126.547640313 2
< 0.1%
126.5526162746 1
< 0.1%
126.5540584899 1
< 0.1%
126.5669484651 1
< 0.1%
ValueCountFrequency (%)
127.7913215403 2
< 0.1%
127.7910921485 1
< 0.1%
127.7766029235 1
< 0.1%
127.7727365668 1
< 0.1%
127.7711531862 1
< 0.1%
127.7706997381 1
< 0.1%
127.7705441813 1
< 0.1%
127.770290524 1
< 0.1%
127.7688750232 1
< 0.1%
127.7666402442 1
< 0.1%

Interactions

2024-04-11T13:55:53.806073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:55:53.273120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:55:53.557688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:55:53.883179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:55:53.400588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:55:53.637957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:55:53.972581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:55:53.478576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:55:53.717882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-11T13:55:59.043727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명데이터기준일자정제우편번호정제WGS84위도정제WGS84경도
시군명1.0001.0000.9910.9360.912
데이터기준일자1.0001.0000.9870.9260.881
정제우편번호0.9910.9871.0000.9340.843
정제WGS84위도0.9360.9260.9341.0000.727
정제WGS84경도0.9120.8810.8430.7271.000
2024-04-11T13:55:59.253086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명데이터기준일자
시군명1.0000.999
데이터기준일자0.9991.000
2024-04-11T13:55:59.377693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정제우편번호정제WGS84위도정제WGS84경도시군명데이터기준일자
정제우편번호1.000-0.9200.0510.8520.756
정제WGS84위도-0.9201.000-0.0200.6870.587
정제WGS84경도0.051-0.0201.0000.6240.497
시군명0.8520.6870.6241.0000.999
데이터기준일자0.7560.5870.4970.9991.000

Missing values

2024-04-11T13:55:54.086057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-11T13:55:54.216469image/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.
2024-04-11T13:55:54.328104image/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

시군명건축물명면적취득일데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
0경기도수리산 탐방안내소연면적 685.59㎡<NA>2022-12-31경기도 군포시 속달로 347-4경기도 군포시 속달동 306번지 일원1588937.348002126.900526
1경기도포천병원 본관동 환경개선리모델링공사<NA>2022-12-31경기도 포천시 포천로 1648경기도 포천시 신읍동 243-1번지1114237.903093127.198349
2경기도안성 원곡119안전센터연면적 942㎡<NA>2022-12-31경기도 안성시 원곡면 원곡물류단지로 162-20경기도 안성시 원곡면 칠곡리 928-31755537.042071127.158226
3경기도안산 신길119안전센터연면적 990㎡<NA>2022-12-31경기도 안산시 단원구 삼일로 50경기도 안산시 단원구 신길동 1691번지1540337.335039126.783624
4경기도화성 봉담 119안전센터연면적 893㎡<NA>2022-12-31경기도 화성시 봉담읍 동화새터길 135경기도 화성시 봉담읍 동화리 621번지1829837.215031126.962915
5경기도의정부병원 본관동 환경개선 및 장례식장 증축연면적 969㎡<NA>2022-12-31경기도 의정부시 흥선로 142경기도 의정부시 의정부동 433번지1167137.741076127.042514
6구리시갈매동 제설작업 전진기지4,8932019-05-092023-03-15경기도 구리시 금강로 164경기도 구리시 갈매동 8-10 외1필지1190137.640195127.128664
7구리시구리 남자청소년 쉼터195.42017-09-212023-03-15경기도 구리시 안골로 32-1경기도 구리시 교문동 7361193437.597102127.134452
8구리시구리시 멀티스포츠센터10,6922014-03-262023-03-15경기도 구리시 체육관로 137-25경기도 구리시 교문동 153-1 외12필지1193437.596158127.13517
9경기도양주 옥정119안전센터연면적 992㎡<NA>2022-12-31<NA>경기도 양주시 옥정동 119-6번지<NA>37.82745127.094035
시군명건축물명면적취득일데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
6161포천시폐수종말처리시설 가동349.372007-12-312024-03-06경기도 포천시 영중면 양문공단로 98경기도 포천시 영중면 양문리 9941112838.007934127.257803
6162포천시금주2리경로당199.932003-03-042024-03-06경기도 포천시 영중면 물안3길 14경기도 포천시 영중면 금주리 275-61113137.976763127.273652
6163포천시거사2리경로당179.882002-03-182024-03-06경기도 포천시 영중면 금화봉길 569경기도 포천시 영중면 거사리 295-11113037.987725127.235913
6164포천시성동4리 경로당 리모델링 대상 건물110.072021-06-082024-03-06경기도 포천시 영중면 성장로166번길 12-17경기도 포천시 영중면 성동리 139-41112838.027582127.275593
6165포천시성동3리 경로당 화장실(옥외)1442008-11-102024-03-06경기도 포천시 영중면 나삼길 197경기도 포천시 영중면 성동리 241-31112838.019963127.265089
6166포천시희망애찬 제작소662021-07-312024-03-06경기도 포천시 영중면 전영로 1382경기도 포천시 영중면 영평리 209-41112638.017187127.212111
6167포천시영평2리 경로당137.162013-06-052024-03-06경기도 포천시 영중면 전영로 1355-41경기도 포천시 영중면 영평리 453-21112638.018566127.208768
6168포천시영송리 분뇨처리장 나동1611986-12-302024-03-06<NA>경기도 포천시 영중면 영송리 6161113037.998872127.20747
6169포천시영송리 분뇨처리장 다동1081992-10-312024-03-06<NA>경기도 포천시 영중면 영송리 6161113037.998872127.20747
6170포천시영송리 분뇨처리장 라동32.81992-10-312024-03-06<NA>경기도 포천시 영중면 영송리 6161113037.998872127.20747

Duplicate rows

Most frequently occurring

시군명건축물명면적취득일데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도# duplicates
13안양시관양두산벤처다임232.812007-12-282024-03-18경기도 안양시 동안구 학의로 250경기도 안양시 동안구 관양동 1307-37번지1405637.40187126.96674813
1가평군산장관광지 숙박시설16.742009-03-122024-02-14<NA>경기도 가평군 상면 덕현리 산 74-61244637.753713127.4108395
14안양시관양두산벤처다임244.192007-12-282024-03-18경기도 안양시 동안구 학의로 250경기도 안양시 동안구 관양동 1307-37번지1405637.40187126.9667484
2가평군산장국민관광지92005-12-222024-02-14<NA>경기도 가평군 상면 덕현리 산 74-61244637.753713127.4108393
6동두천시종합운동장56.541997-09-102023-03-15경기도 동두천시 어등로 45경기도 동두천시 생연동 70 종합운동장(화장실)1132037.90084127.0704973
0가평군가평정수장9.222004-11-292024-02-14<NA>경기도 가평군 가평읍 달전리 510-31242237.807265127.5146612
3가평군연인산캠핑장공동화장실138.42008-06-262024-02-14<NA>경기도 가평군 북면 백둔리 3601240637.901667127.4593292
4가평군연하희망마을센터202.652012-08-312024-02-14<NA>경기도 가평군 상면 연하리 218-121244437.803148127.3484972
5광명시3급관사364.28<NA>2023-03-20<NA>경기도 광명시 모세로 27 (철산동)<NA><NA><NA>2
7부천시삼삼약수경로당34.31<NA>2023-03-20경기도 부천시 지양로158번길 66경기도 부천시 고강동 422-191446937.522973126.8219372