Overview

Dataset statistics

Number of variables12
Number of observations547
Missing cells13
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory53.0 KiB
Average record size in memory99.2 B

Variable types

Categorical2
Text6
DateTime1
Numeric3

Alerts

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
전화번호 has 9 (1.6%) missing valuesMissing

Reproduction

Analysis started2024-01-14 07:30:42.206524
Analysis finished2024-01-14 07:30:44.749885
Duration2.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
용인시
73 
부천시
50 
광주시
43 
화성시
38 
파주시
32 
Other values (26)
311 

Length

Max length4
Median length3
Mean length3.047532
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row김포시
2nd row김포시
3rd row김포시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
용인시 73
 
13.3%
부천시 50
 
9.1%
광주시 43
 
7.9%
화성시 38
 
6.9%
파주시 32
 
5.9%
하남시 27
 
4.9%
과천시 24
 
4.4%
수원시 21
 
3.8%
고양시 21
 
3.8%
이천시 17
 
3.1%
Other values (21) 201
36.7%

Length

2024-01-14T16:30:44.878793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용인시 73
 
13.3%
부천시 50
 
9.1%
광주시 43
 
7.9%
화성시 38
 
6.9%
파주시 32
 
5.9%
하남시 27
 
4.9%
과천시 24
 
4.4%
수원시 21
 
3.8%
고양시 21
 
3.8%
이천시 17
 
3.1%
Other values (21) 201
36.7%

신고번호
Text

Distinct535
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-01-14T16:30:45.243771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length15.312614
Min length12

Characters and Unicode

Total characters8376
Distinct characters39
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

Unique527 ?
Unique (%)96.3%

Sample

1st row경기김포시-건축사사무소-53
2nd row경기김포시-건축사사무소-92
3rd row경기김포시-건축사사무소-64
4th row경기고양시-건축사사무소-80
5th row경기고양시-건축사사무소-338
ValueCountFrequency (%)
경기도-건축사사무소-3741 6
 
1.1%
경기성남시-건축사사무소-308 2
 
0.4%
경기도-건축사사무소-3478 2
 
0.4%
경기안양시-건축사사무소-237 2
 
0.4%
경기도-건축사사무소-2484 2
 
0.4%
경기용인시-건축사사무소-70 2
 
0.4%
경기도-건축사사무소-3051 2
 
0.4%
경기안양시-건축사사무소-272 2
 
0.4%
경기안산시-건축사사무소-39 1
 
0.2%
경기수원시-건축사사무소-433 1
 
0.2%
Other values (525) 525
96.0%
2024-01-14T16:30:45.806377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1094
13.1%
사 1094
13.1%
경 547
 
6.5%
건 547
 
6.5%
축 547
 
6.5%
무 547
 
6.5%
소 547
 
6.5%
기 547
 
6.5%
2 340
 
4.1%
시 287
 
3.4%
Other values (29) 2279
27.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5488
65.5%
Decimal Number 1794
 
21.4%
Dash Punctuation 1094
 
13.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1094
19.9%
경 547
10.0%
건 547
10.0%
축 547
10.0%
무 547
10.0%
소 547
10.0%
기 547
10.0%
시 287
 
5.2%
도 270
 
4.9%
인 73
 
1.3%
Other values (18) 482
8.8%
Decimal Number
ValueCountFrequency (%)
2 340
19.0%
3 249
13.9%
1 230
12.8%
7 161
9.0%
4 153
8.5%
6 150
8.4%
5 138
7.7%
8 134
 
7.5%
9 120
 
6.7%
0 119
 
6.6%
Dash Punctuation
ValueCountFrequency (%)
- 1094
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5488
65.5%
Common 2888
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1094
19.9%
경 547
10.0%
건 547
10.0%
축 547
10.0%
무 547
10.0%
소 547
10.0%
기 547
10.0%
시 287
 
5.2%
도 270
 
4.9%
인 73
 
1.3%
Other values (18) 482
8.8%
Common
ValueCountFrequency (%)
- 1094
37.9%
2 340
 
11.8%
3 249
 
8.6%
1 230
 
8.0%
7 161
 
5.6%
4 153
 
5.3%
6 150
 
5.2%
5 138
 
4.8%
8 134
 
4.6%
9 120
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5488
65.5%
ASCII 2888
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1094
37.9%
2 340
 
11.8%
3 249
 
8.6%
1 230
 
8.0%
7 161
 
5.6%
4 153
 
5.3%
6 150
 
5.2%
5 138
 
4.8%
8 134
 
4.6%
9 120
 
4.2%
Hangul
ValueCountFrequency (%)
사 1094
19.9%
경 547
10.0%
건 547
10.0%
축 547
10.0%
무 547
10.0%
소 547
10.0%
기 547
10.0%
시 287
 
5.2%
도 270
 
4.9%
인 73
 
1.3%
Other values (18) 482
8.8%

신고일자
Date

Distinct494
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum1984-10-26 00:00:00
Maximum2023-06-19 00:00:00
2024-01-14T16:30:46.006854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:30:46.190446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

신고구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
개인
345 
법인
202 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row개인
3rd row개인
4th row개인
5th row법인

Common Values

ValueCountFrequency (%)
개인 345
63.1%
법인 202
36.9%

Length

2024-01-14T16:30:46.363751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T16:30:46.476968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 345
63.1%
법인 202
36.9%

사무소명
Text

Distinct512
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-01-14T16:30:47.075691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19
Mean length10.749543
Min length7

Characters and Unicode

Total characters5880
Distinct characters274
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique484 ?
Unique (%)88.5%

Sample

1st row광림건축사사무소
2nd row나우건축사사무소
3rd row주가인 건축사사무소
4th row테마건축사사무소
5th row(주)가와종합건축사사무소
ValueCountFrequency (%)
건축사사무소 155
 
19.5%
주식회사 56
 
7.1%
주)종합건축사사무소근정 6
 
0.8%
종합건축사사무소 6
 
0.8%
주)건축사사무소 6
 
0.8%
다온건축사사무소 5
 
0.6%
사무소 4
 
0.5%
에이드건축사사무소 3
 
0.4%
주)종합건축사사무소 3
 
0.4%
미담 3
 
0.4%
Other values (513) 546
68.9%
2024-01-14T16:30:47.714812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 1175
20.0%
건 571
 
9.7%
축 561
 
9.5%
무 555
 
9.4%
소 552
 
9.4%
246
 
4.2%
주 206
 
3.5%
) 127
 
2.2%
( 126
 
2.1%
이 84
 
1.4%
Other values (264) 1677
28.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5326
90.6%
Space Separator 246
 
4.2%
Close Punctuation 127
 
2.2%
Open Punctuation 126
 
2.1%
Uppercase Letter 34
 
0.6%
Lowercase Letter 13
 
0.2%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1175
22.1%
건 571
10.7%
축 561
10.5%
무 555
 
10.4%
소 552
 
10.4%
주 206
 
3.9%
이 84
 
1.6%
회 77
 
1.4%
식 77
 
1.4%
합 76
 
1.4%
Other values (232) 1392
26.1%
Uppercase Letter
ValueCountFrequency (%)
H 6
17.6%
A 6
17.6%
S 3
8.8%
D 2
 
5.9%
Y 2
 
5.9%
T 2
 
5.9%
C 2
 
5.9%
M 2
 
5.9%
J 1
 
2.9%
P 1
 
2.9%
Other values (7) 7
20.6%
Lowercase Letter
ValueCountFrequency (%)
d 3
23.1%
o 2
15.4%
i 1
 
7.7%
e 1
 
7.7%
h 1
 
7.7%
t 1
 
7.7%
l 1
 
7.7%
c 1
 
7.7%
m 1
 
7.7%
a 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 5
62.5%
, 3
37.5%
Space Separator
ValueCountFrequency (%)
246
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5326
90.6%
Common 507
 
8.6%
Latin 47
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1175
22.1%
건 571
10.7%
축 561
10.5%
무 555
 
10.4%
소 552
 
10.4%
주 206
 
3.9%
이 84
 
1.6%
회 77
 
1.4%
식 77
 
1.4%
합 76
 
1.4%
Other values (232) 1392
26.1%
Latin
ValueCountFrequency (%)
H 6
 
12.8%
A 6
 
12.8%
d 3
 
6.4%
S 3
 
6.4%
o 2
 
4.3%
D 2
 
4.3%
Y 2
 
4.3%
T 2
 
4.3%
C 2
 
4.3%
M 2
 
4.3%
Other values (17) 17
36.2%
Common
ValueCountFrequency (%)
246
48.5%
) 127
25.0%
( 126
24.9%
. 5
 
1.0%
, 3
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5326
90.6%
ASCII 554
 
9.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 1175
22.1%
건 571
10.7%
축 561
10.5%
무 555
 
10.4%
소 552
 
10.4%
주 206
 
3.9%
이 84
 
1.6%
회 77
 
1.4%
식 77
 
1.4%
합 76
 
1.4%
Other values (232) 1392
26.1%
ASCII
ValueCountFrequency (%)
246
44.4%
) 127
22.9%
( 126
22.7%
H 6
 
1.1%
A 6
 
1.1%
. 5
 
0.9%
d 3
 
0.5%
, 3
 
0.5%
S 3
 
0.5%
o 2
 
0.4%
Other values (22) 27
 
4.9%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct321
Distinct (%)58.8%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean14425.879
Minimum10108
Maximum18598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2024-01-14T16:30:47.923882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10108
5-th percentile10886
Q112618
median14216.5
Q317013.5
95-th percentile18295
Maximum18598
Range8490
Interquartile range (IQR)4395.5

Descriptive statistics

Standard deviation2468.6972
Coefficient of variation (CV)0.17112976
Kurtosis-1.2677344
Mean14425.879
Median Absolute Deviation (MAD)2286
Skewness0.093423717
Sum7876530
Variance6094465.9
MonotonicityIncreasing
2024-01-14T16:30:48.115528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12739 16
 
2.9%
14548 15
 
2.7%
17051 9
 
1.6%
17049 8
 
1.5%
13840 8
 
1.5%
12925 8
 
1.5%
14998 7
 
1.3%
11498 7
 
1.3%
14566 6
 
1.1%
16972 6
 
1.1%
Other values (311) 456
83.4%
ValueCountFrequency (%)
10108 1
 
0.2%
10109 1
 
0.2%
10113 1
 
0.2%
10265 1
 
0.2%
10300 1
 
0.2%
10364 1
 
0.2%
10401 1
 
0.2%
10449 2
0.4%
10497 3
0.5%
10546 1
 
0.2%
ValueCountFrequency (%)
18598 1
0.2%
18536 1
0.2%
18528 1
0.2%
18469 1
0.2%
18468 2
0.4%
18467 1
0.2%
18423 2
0.4%
18421 1
0.2%
18412 1
0.2%
18411 2
0.4%

소재지도로명주소
Text

Distinct469
Distinct (%)86.2%
Missing3
Missing (%)0.5%
Memory size4.4 KiB
2024-01-14T16:30:48.556806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length18.097426
Min length13

Characters and Unicode

Total characters9845
Distinct characters230
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

Unique410 ?
Unique (%)75.4%

Sample

1st row경기도 김포시 돌문로 95
2nd row경기도 김포시 봉화로 9-1
3rd row경기도 김포시 김포대로679번길 14-4
4th row경기도 고양시 덕양구 고골길 51-46
5th row경기도 고양시 일산동구 고일로 203-4
ValueCountFrequency (%)
경기도 544
 
22.8%
용인시 72
 
3.0%
부천시 50
 
2.1%
처인구 45
 
1.9%
광주시 43
 
1.8%
화성시 38
 
1.6%
파주시 32
 
1.3%
하남시 27
 
1.1%
중앙로 26
 
1.1%
과천시 24
 
1.0%
Other values (699) 1482
62.2%
2024-01-14T16:30:49.175679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1839
18.7%
기 571
 
5.8%
경 557
 
5.7%
시 553
 
5.6%
도 548
 
5.6%
로 509
 
5.2%
1 409
 
4.2%
2 244
 
2.5%
길 189
 
1.9%
5 186
 
1.9%
Other values (220) 4240
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6059
61.5%
Space Separator 1839
 
18.7%
Decimal Number 1836
 
18.6%
Dash Punctuation 111
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 571
 
9.4%
경 557
 
9.2%
시 553
 
9.1%
도 548
 
9.0%
로 509
 
8.4%
길 189
 
3.1%
구 167
 
2.8%
천 142
 
2.3%
번 138
 
2.3%
양 125
 
2.1%
Other values (208) 2560
42.3%
Decimal Number
ValueCountFrequency (%)
1 409
22.3%
2 244
13.3%
5 186
10.1%
3 174
9.5%
4 167
9.1%
7 148
 
8.1%
0 134
 
7.3%
9 129
 
7.0%
6 128
 
7.0%
8 117
 
6.4%
Space Separator
ValueCountFrequency (%)
1839
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6059
61.5%
Common 3786
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 571
 
9.4%
경 557
 
9.2%
시 553
 
9.1%
도 548
 
9.0%
로 509
 
8.4%
길 189
 
3.1%
구 167
 
2.8%
천 142
 
2.3%
번 138
 
2.3%
양 125
 
2.1%
Other values (208) 2560
42.3%
Common
ValueCountFrequency (%)
1839
48.6%
1 409
 
10.8%
2 244
 
6.4%
5 186
 
4.9%
3 174
 
4.6%
4 167
 
4.4%
7 148
 
3.9%
0 134
 
3.5%
9 129
 
3.4%
6 128
 
3.4%
Other values (2) 228
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6059
61.5%
ASCII 3786
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1839
48.6%
1 409
 
10.8%
2 244
 
6.4%
5 186
 
4.9%
3 174
 
4.6%
4 167
 
4.4%
7 148
 
3.9%
0 134
 
3.5%
9 129
 
3.4%
6 128
 
3.4%
Other values (2) 228
 
6.0%
Hangul
ValueCountFrequency (%)
기 571
 
9.4%
경 557
 
9.2%
시 553
 
9.1%
도 548
 
9.0%
로 509
 
8.4%
길 189
 
3.1%
구 167
 
2.8%
천 142
 
2.3%
번 138
 
2.3%
양 125
 
2.1%
Other values (208) 2560
42.3%

소재지지번주소
Text

Distinct471
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-01-14T16:30:49.569645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length31
Mean length20.711152
Min length15

Characters and Unicode

Total characters11329
Distinct characters220
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique411 ?
Unique (%)75.1%

Sample

1st row경기도 김포시 사우동 204-10번지
2nd row경기도 김포시 사우동 250번지
3rd row경기도 김포시 풍무동 1026번지
4th row경기도 고양시 덕양구 관산동 654-12번지
5th row경기도 고양시 일산동구 풍동 450-10번지
ValueCountFrequency (%)
경기도 547
 
22.6%
용인시 73
 
3.0%
부천시 50
 
2.1%
처인구 46
 
1.9%
광주시 43
 
1.8%
화성시 38
 
1.6%
파주시 32
 
1.3%
김량장동 30
 
1.2%
하남시 27
 
1.1%
송정동 26
 
1.1%
Other values (735) 1509
62.3%
2024-01-14T16:30:50.185803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1874
 
16.5%
기 566
 
5.0%
지 561
 
5.0%
도 554
 
4.9%
경 549
 
4.8%
번 545
 
4.8%
시 535
 
4.7%
동 530
 
4.7%
1 455
 
4.0%
- 441
 
3.9%
Other values (210) 4719
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6797
60.0%
Decimal Number 2216
 
19.6%
Space Separator 1874
 
16.5%
Dash Punctuation 441
 
3.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 566
 
8.3%
지 561
 
8.3%
도 554
 
8.2%
경 549
 
8.1%
번 545
 
8.0%
시 535
 
7.9%
동 530
 
7.8%
구 170
 
2.5%
양 143
 
2.1%
천 129
 
1.9%
Other values (197) 2515
37.0%
Decimal Number
ValueCountFrequency (%)
1 455
20.5%
2 274
12.4%
4 262
11.8%
3 261
11.8%
5 214
9.7%
8 170
 
7.7%
6 169
 
7.6%
0 144
 
6.5%
7 135
 
6.1%
9 132
 
6.0%
Space Separator
ValueCountFrequency (%)
1874
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 441
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6797
60.0%
Common 4532
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 566
 
8.3%
지 561
 
8.3%
도 554
 
8.2%
경 549
 
8.1%
번 545
 
8.0%
시 535
 
7.9%
동 530
 
7.8%
구 170
 
2.5%
양 143
 
2.1%
천 129
 
1.9%
Other values (197) 2515
37.0%
Common
ValueCountFrequency (%)
1874
41.4%
1 455
 
10.0%
- 441
 
9.7%
2 274
 
6.0%
4 262
 
5.8%
3 261
 
5.8%
5 214
 
4.7%
8 170
 
3.8%
6 169
 
3.7%
0 144
 
3.2%
Other values (3) 268
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6797
60.0%
ASCII 4532
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1874
41.4%
1 455
 
10.0%
- 441
 
9.7%
2 274
 
6.0%
4 262
 
5.8%
3 261
 
5.8%
5 214
 
4.7%
8 170
 
3.8%
6 169
 
3.7%
0 144
 
3.2%
Other values (3) 268
 
5.9%
Hangul
ValueCountFrequency (%)
기 566
 
8.3%
지 561
 
8.3%
도 554
 
8.2%
경 549
 
8.1%
번 545
 
8.0%
시 535
 
7.9%
동 530
 
7.8%
구 170
 
2.5%
양 143
 
2.1%
천 129
 
1.9%
Other values (197) 2515
37.0%

전화번호
Text

MISSING 

Distinct496
Distinct (%)92.2%
Missing9
Missing (%)1.6%
Memory size4.4 KiB
2024-01-14T16:30:50.605194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.410781
Min length10

Characters and Unicode

Total characters6139
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique461 ?
Unique (%)85.7%

Sample

1st row07044529698
2nd row0328808477
3rd row02-534-3127
4th row0313387466
5th row02-3143-0057
ValueCountFrequency (%)
070-4272-6110 6
 
1.1%
031-856-0491 5
 
0.9%
02-442-2777 2
 
0.4%
0313050288 2
 
0.4%
07077336657 2
 
0.4%
0312422407 2
 
0.4%
032-710-2815 2
 
0.4%
0312245620 2
 
0.4%
02-597-4381 2
 
0.4%
02-501-4582 2
 
0.4%
Other values (486) 511
95.0%
2024-01-14T16:30:51.141157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1033
16.8%
3 847
13.8%
- 705
11.5%
1 705
11.5%
2 567
9.2%
7 497
8.1%
6 400
 
6.5%
5 384
 
6.3%
8 357
 
5.8%
4 352
 
5.7%
Other values (2) 292
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5431
88.5%
Dash Punctuation 705
 
11.5%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1033
19.0%
3 847
15.6%
1 705
13.0%
2 567
10.4%
7 497
9.2%
6 400
 
7.4%
5 384
 
7.1%
8 357
 
6.6%
4 352
 
6.5%
9 289
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 705
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6139
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1033
16.8%
3 847
13.8%
- 705
11.5%
1 705
11.5%
2 567
9.2%
7 497
8.1%
6 400
 
6.5%
5 384
 
6.3%
8 357
 
5.8%
4 352
 
5.7%
Other values (2) 292
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6139
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1033
16.8%
3 847
13.8%
- 705
11.5%
1 705
11.5%
2 567
9.2%
7 497
8.1%
6 400
 
6.5%
5 384
 
6.3%
8 357
 
5.8%
4 352
 
5.7%
Other values (2) 292
 
4.8%

대표자명
Text

Distinct539
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-01-14T16:30:51.621758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9835466
Min length2

Characters and Unicode

Total characters1632
Distinct characters174
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique531 ?
Unique (%)97.1%

Sample

1st row김민우
2nd row우순식
3rd row박준영
4th row김미애
5th row최삼영
ValueCountFrequency (%)
이상진 2
 
0.4%
박성준 2
 
0.4%
이정훈 2
 
0.4%
김영준 2
 
0.4%
김복열 2
 
0.4%
이재철 2
 
0.4%
박준영 2
 
0.4%
김정수 2
 
0.4%
이상두 1
 
0.2%
정유진 1
 
0.2%
Other values (529) 529
96.7%
2024-01-14T16:30:52.231994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 115
 
7.0%
이 83
 
5.1%
정 70
 
4.3%
영 47
 
2.9%
박 38
 
2.3%
성 37
 
2.3%
진 31
 
1.9%
현 31
 
1.9%
재 31
 
1.9%
호 30
 
1.8%
Other values (164) 1119
68.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1632
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 115
 
7.0%
이 83
 
5.1%
정 70
 
4.3%
영 47
 
2.9%
박 38
 
2.3%
성 37
 
2.3%
진 31
 
1.9%
현 31
 
1.9%
재 31
 
1.9%
호 30
 
1.8%
Other values (164) 1119
68.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1632
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 115
 
7.0%
이 83
 
5.1%
정 70
 
4.3%
영 47
 
2.9%
박 38
 
2.3%
성 37
 
2.3%
진 31
 
1.9%
현 31
 
1.9%
재 31
 
1.9%
호 30
 
1.8%
Other values (164) 1119
68.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1632
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 115
 
7.0%
이 83
 
5.1%
정 70
 
4.3%
영 47
 
2.9%
박 38
 
2.3%
성 37
 
2.3%
진 31
 
1.9%
현 31
 
1.9%
재 31
 
1.9%
호 30
 
1.8%
Other values (164) 1119
68.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct471
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.435179
Minimum36.987088
Maximum38.096196
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2024-01-14T16:30:52.385529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.987088
5-th percentile37.152309
Q137.269651
median37.41646
Q337.553078
95-th percentile37.819088
Maximum38.096196
Range1.1091078
Interquartile range (IQR)0.28342733

Descriptive statistics

Standard deviation0.21178711
Coefficient of variation (CV)0.0056574354
Kurtosis-0.40240862
Mean37.435179
Median Absolute Deviation (MAD)0.14239635
Skewness0.33530994
Sum20477.043
Variance0.04485378
MonotonicityNot monotonic
2024-01-14T16:30:52.565181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.41412976 7
 
1.3%
37.55678745 4
 
0.7%
37.50130701 4
 
0.7%
37.4009701 4
 
0.7%
37.15548687 3
 
0.5%
37.2691657 3
 
0.5%
37.50295985 3
 
0.5%
37.55885606 3
 
0.5%
37.44805969 3
 
0.5%
37.42906212 2
 
0.4%
Other values (461) 511
93.4%
ValueCountFrequency (%)
36.98708822 1
0.2%
36.98838438 1
0.2%
36.9900935 1
0.2%
36.99017401 1
0.2%
36.99527387 1
0.2%
36.99808444 1
0.2%
36.99956545 1
0.2%
37.00429447 1
0.2%
37.00448752 1
0.2%
37.00473256 1
0.2%
ValueCountFrequency (%)
38.09619602 1
0.2%
37.90358377 1
0.2%
37.90343034 1
0.2%
37.89951524 1
0.2%
37.8948741 1
0.2%
37.89418652 1
0.2%
37.89289347 1
0.2%
37.89272321 1
0.2%
37.89037171 1
0.2%
37.89003829 1
0.2%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct471
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.06119
Minimum126.56963
Maximum127.64478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2024-01-14T16:30:52.821762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.56963
5-th percentile126.76342
Q1126.8762
median127.06022
Q3127.20107
95-th percentile127.48353
Maximum127.64478
Range1.0751528
Interquartile range (IQR)0.32486995

Descriptive statistics

Standard deviation0.21526244
Coefficient of variation (CV)0.0016941635
Kurtosis-0.1525275
Mean127.06119
Median Absolute Deviation (MAD)0.1434373
Skewness0.34040515
Sum69502.471
Variance0.046337917
MonotonicityNot monotonic
2024-01-14T16:30:53.005038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9791704 7
 
1.3%
127.2064192 4
 
0.7%
126.7708382 4
 
0.7%
126.9691155 4
 
0.7%
127.0572264 3
 
0.5%
127.0905784 3
 
0.5%
126.7728473 3
 
0.5%
127.2046108 3
 
0.5%
126.9942656 3
 
0.5%
127.2572047 2
 
0.4%
Other values (461) 511
93.4%
ValueCountFrequency (%)
126.5696251 1
0.2%
126.5713678 1
0.2%
126.5820334 1
0.2%
126.7030333 1
0.2%
126.7107251 1
0.2%
126.7112195 1
0.2%
126.7132337 1
0.2%
126.7166377 1
0.2%
126.725669 1
0.2%
126.730295 1
0.2%
ValueCountFrequency (%)
127.6447779 1
0.2%
127.6394244 1
0.2%
127.6381504 1
0.2%
127.6377444 1
0.2%
127.6377326 1
0.2%
127.6362553 1
0.2%
127.6327265 1
0.2%
127.6314556 1
0.2%
127.6251345 1
0.2%
127.6242895 2
0.4%

Interactions

2024-01-14T16:30:43.897395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:30:43.174686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:30:43.536570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:30:44.010819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:30:43.298038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:30:43.636512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:30:44.120087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:30:43.432899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:30:43.744781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-14T16:30:53.125328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명신고구분소재지우편번호WGS84위도WGS84경도
시군명1.0000.3260.9970.9850.962
신고구분0.3261.0000.2930.1240.285
소재지우편번호0.9970.2931.0000.9250.914
WGS84위도0.9850.1240.9251.0000.785
WGS84경도0.9620.2850.9140.7851.000
2024-01-14T16:30:53.289283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신고구분시군명
신고구분1.0000.270
시군명0.2701.000
2024-01-14T16:30:53.406024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명신고구분
소재지우편번호1.000-0.8950.0740.9510.224
WGS84위도-0.8951.000-0.2130.8700.094
WGS84경도0.074-0.2131.0000.7660.217
시군명0.9510.8700.7661.0000.270
신고구분0.2240.0940.2170.2701.000

Missing values

2024-01-14T16:30:44.261267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-14T16:30:44.475340image/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.
2024-01-14T16:30:44.641759image/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

시군명신고번호신고일자신고구분사무소명소재지우편번호소재지도로명주소소재지지번주소전화번호대표자명WGS84위도WGS84경도
0김포시경기김포시-건축사사무소-532016-03-10개인광림건축사사무소10108경기도 김포시 돌문로 95경기도 김포시 사우동 204-10번지07044529698김민우37.621563126.713234
1김포시경기김포시-건축사사무소-922021-10-20개인나우건축사사무소10109경기도 김포시 봉화로 9-1경기도 김포시 사우동 250번지0328808477우순식37.61789126.716638
2김포시경기김포시-건축사사무소-642000-08-30개인주가인 건축사사무소10113경기도 김포시 김포대로679번길 14-4경기도 김포시 풍무동 1026번지02-534-3127박준영37.611188126.733714
3고양시경기고양시-건축사사무소-802002-01-15개인테마건축사사무소10265경기도 고양시 덕양구 고골길 51-46경기도 고양시 덕양구 관산동 654-12번지0313387466김미애37.713926126.858277
4고양시경기고양시-건축사사무소-3382002-07-10법인(주)가와종합건축사사무소10300경기도 고양시 일산동구 고일로 203-4경기도 고양시 일산동구 풍동 450-10번지02-3143-0057최삼영37.656321126.800921
5고양시경기고양시-건축사사무소-2702007-12-21개인가현건축사사무소10364경기도 고양시 일산동구 무궁화로 43-15경기도 고양시 일산동구 장항동 733번지070-5121-9812이강근37.663782126.767914
6고양시경기고양시-건축사사무소-3272016-07-22법인주식회사 이안이레건축사사무소10401경기도 고양시 일산동구 무궁화로 8-38경기도 고양시 일산동구 장항동 752-1번지07088316789서현수37.659818126.766796
7고양시경기고양시-건축사사무소-4072023-05-24개인일현건축사사무소10449경기도 고양시 일산동구 일산로 38경기도 고양시 일산동구 백석동 1309번지02-6953-7689김재준37.641854126.787285
8고양시경기고양시-건축사사무소-2892004-06-03개인에이아이지 건축사사무소10449경기도 고양시 일산동구 호수로 336경기도 고양시 일산동구 백석동 1330번지07042494401한인범37.637611126.787756
9고양시경기고양시-건축사사무소-151994-03-18개인신세대건축사사무소10497경기도 고양시 덕양구 화중로 100경기도 고양시 덕양구 화정동 968번지031-965-7744이만용37.636137126.831474
시군명신고번호신고일자신고구분사무소명소재지우편번호소재지도로명주소소재지지번주소전화번호대표자명WGS84위도WGS84경도
537화성시경기화성시-건축사사무소-132016-02-11법인(주)이음건축사사무소18423경기도 화성시 동탄원천로 354-28경기도 화성시 능동 1064-5번지0312382202김은영37.218275127.058731
538화성시경기화성시-건축사사무소-2072019-01-29개인아로건축사사무소18423경기도 화성시 동탄원천로 354-28경기도 화성시 능동 1064-5번지0312382202김혜성37.218275127.058731
539화성시경기화성시-건축사사무소-2742013-06-18법인주식회사 건축사사무소 빅18467경기도 화성시 동탄대로 636-3경기도 화성시 영천동 873-4번지031-553-0701진태호37.21077127.100316
540화성시경기화성시-건축사사무소-2412020-11-20개인건축사사무소 오앤에이18468경기도 화성시 동탄대로 635경기도 화성시 영천동 853-3번지070-4735-5206온상원37.20996127.098101
541화성시경기화성시-건축사사무소-2972017-01-06개인소담재 건축사사무소18468경기도 화성시 동탄대로 677-5경기도 화성시 영천동 848-1번지07041380538이병성37.213905127.099702
542화성시경기화성시-건축사사무소-3052020-07-07개인일리있는 건축사사무소18469경기도 화성시 동탄기흥로 590경기도 화성시 영천동 837번지0313778206권순혁37.212832127.094343
543화성시경기화성시-건축사사무소-312013-08-22개인다연이엔씨종합건축사사무소18528경기도 화성시 팔탄면 푸른들판로 712-7경기도 화성시 팔탄면 구장리 3-1번지0313598090김연희37.171404126.892158
544화성시경기화성시-건축사사무소-682015-01-20법인(주)준종합건축사사무소18536경기도 화성시 팔탄면 무하로 148경기도 화성시 팔탄면 하저리 930-3번지0313553317유서준37.184436126.859179
545화성시경기화성시-건축사사무소-1842003-12-18법인(주)연합 건축사사무소18598경기도 화성시 향남읍 발안로 62경기도 화성시 향남읍 행정리 425-7번지031-354-6489이석기37.131425126.917021
546평택시경기도-건축사사무소-20712005-05-13개인건축사사무소 미담<NA><NA>경기도 평택시 합정동 21-21, 201호031-845-1685이효정36.988384127.118252