Overview

Dataset statistics

Number of variables9
Number of observations911
Missing cells1854
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory64.2 KiB
Average record size in memory72.1 B

Variable types

Text6
Categorical2
DateTime1

Dataset

Description서울특별시 동대문구에 등록되어 있는 부동산중개업소에 대한 데이터(등록번호, 사무소명, 주소, 전화번호 등)를 등록합니다
Author서울특별시 동대문구
URLhttps://www.data.go.kr/data/15086254/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
사무소전화번호1 has 68 (7.5%) missing valuesMissing
사무소전화번호2 has 879 (96.5%) missing valuesMissing
사무소전화번호3 has 907 (99.6%) missing valuesMissing
등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:07:06.809936
Analysis finished2023-12-12 13:07:07.661579
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct911
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T22:07:07.840640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length16.125137
Min length8

Characters and Unicode

Total characters14690
Distinct characters17
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

Unique911 ?
Unique (%)100.0%

Sample

1st row92240000-992
2nd row나-92280000-66
3rd row나-92280000-220
4th row나-92280000-204
5th row나-92280000-1013
ValueCountFrequency (%)
92240000-992 1
 
0.1%
11230-2018-00124 1
 
0.1%
11230-2018-00205 1
 
0.1%
11230-2018-00185 1
 
0.1%
11230-2018-00187 1
 
0.1%
11230-2018-00189 1
 
0.1%
11230-2018-00192 1
 
0.1%
11230-2018-00193 1
 
0.1%
11230-2018-00195 1
 
0.1%
11230-2018-00196 1
 
0.1%
Other values (901) 901
98.9%
2023-12-12T22:07:08.216123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4262
29.0%
2 2380
16.2%
1 1985
13.5%
- 1798
12.2%
3 932
 
6.3%
8 658
 
4.5%
9 655
 
4.5%
가 341
 
2.3%
인 302
 
2.1%
공 302
 
2.1%
Other values (7) 1075
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11930
81.2%
Dash Punctuation 1798
 
12.2%
Other Letter 962
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4262
35.7%
2 2380
19.9%
1 1985
16.6%
3 932
 
7.8%
8 658
 
5.5%
9 655
 
5.5%
6 292
 
2.4%
7 268
 
2.2%
5 252
 
2.1%
4 246
 
2.1%
Other Letter
ValueCountFrequency (%)
가 341
35.4%
인 302
31.4%
공 302
31.4%
나 15
 
1.6%
풍 1
 
0.1%
양 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1798
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13728
93.5%
Hangul 962
 
6.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4262
31.0%
2 2380
17.3%
1 1985
14.5%
- 1798
13.1%
3 932
 
6.8%
8 658
 
4.8%
9 655
 
4.8%
6 292
 
2.1%
7 268
 
2.0%
5 252
 
1.8%
Hangul
ValueCountFrequency (%)
가 341
35.4%
인 302
31.4%
공 302
31.4%
나 15
 
1.6%
풍 1
 
0.1%
양 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13728
93.5%
Hangul 962
 
6.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4262
31.0%
2 2380
17.3%
1 1985
14.5%
- 1798
13.1%
3 932
 
6.8%
8 658
 
4.8%
9 655
 
4.8%
6 292
 
2.1%
7 268
 
2.0%
5 252
 
1.8%
Hangul
ValueCountFrequency (%)
가 341
35.4%
인 302
31.4%
공 302
31.4%
나 15
 
1.6%
풍 1
 
0.1%
양 1
 
0.1%

사무소명
Text

Distinct731
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T22:07:08.437733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length11.851811
Min length7

Characters and Unicode

Total characters10797
Distinct characters382
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

Unique633 ?
Unique (%)69.5%

Sample

1st row엔탑부동산공인중개사사무소
2nd row대명부동산중개인사무소
3rd row용두부동산중개인사무소
4th row중앙부동산중개인사무소
5th row삼성래미안부동산중개인사무소
ValueCountFrequency (%)
현대공인중개사사무소 10
 
1.1%
삼성공인중개사사무소 10
 
1.1%
공인중개사사무소 9
 
1.0%
탑공인중개사사무소 7
 
0.8%
래미안공인중개사사무소 6
 
0.6%
행복공인중개사사무소 6
 
0.6%
한양공인중개사사무소 6
 
0.6%
하나공인중개사사무소 6
 
0.6%
롯데공인중개사사무소 5
 
0.5%
미소공인중개사사무소 5
 
0.5%
Other values (728) 857
92.4%
2023-12-12T22:07:08.838524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 1763
16.3%
중 916
 
8.5%
소 914
 
8.5%
개 913
 
8.5%
인 906
 
8.4%
무 901
 
8.3%
공 844
 
7.8%
동 332
 
3.1%
부 314
 
2.9%
산 309
 
2.9%
Other values (372) 2685
24.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10570
97.9%
Uppercase Letter 73
 
0.7%
Decimal Number 67
 
0.6%
Lowercase Letter 29
 
0.3%
Open Punctuation 18
 
0.2%
Close Punctuation 18
 
0.2%
Space Separator 16
 
0.1%
Dash Punctuation 4
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1763
16.7%
중 916
 
8.7%
소 914
 
8.6%
개 913
 
8.6%
인 906
 
8.6%
무 901
 
8.5%
공 844
 
8.0%
동 332
 
3.1%
부 314
 
3.0%
산 309
 
2.9%
Other values (327) 2458
23.3%
Uppercase Letter
ValueCountFrequency (%)
K 19
26.0%
S 11
15.1%
O 11
15.1%
B 3
 
4.1%
A 3
 
4.1%
H 3
 
4.1%
L 3
 
4.1%
N 3
 
4.1%
M 2
 
2.7%
G 2
 
2.7%
Other values (8) 13
17.8%
Lowercase Letter
ValueCountFrequency (%)
e 8
27.6%
t 4
13.8%
s 3
 
10.3%
n 2
 
6.9%
i 2
 
6.9%
r 2
 
6.9%
y 2
 
6.9%
h 1
 
3.4%
o 1
 
3.4%
f 1
 
3.4%
Other values (3) 3
 
10.3%
Decimal Number
ValueCountFrequency (%)
1 20
29.9%
0 10
14.9%
2 8
 
11.9%
6 8
 
11.9%
9 7
 
10.4%
4 5
 
7.5%
5 3
 
4.5%
8 3
 
4.5%
3 3
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10569
97.9%
Common 125
 
1.2%
Latin 102
 
0.9%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1763
16.7%
중 916
 
8.7%
소 914
 
8.6%
개 913
 
8.6%
인 906
 
8.6%
무 901
 
8.5%
공 844
 
8.0%
동 332
 
3.1%
부 314
 
3.0%
산 309
 
2.9%
Other values (326) 2457
23.2%
Latin
ValueCountFrequency (%)
K 19
18.6%
S 11
 
10.8%
O 11
 
10.8%
e 8
 
7.8%
t 4
 
3.9%
B 3
 
2.9%
A 3
 
2.9%
H 3
 
2.9%
L 3
 
2.9%
N 3
 
2.9%
Other values (21) 34
33.3%
Common
ValueCountFrequency (%)
1 20
16.0%
( 18
14.4%
) 18
14.4%
16
12.8%
0 10
8.0%
2 8
 
6.4%
6 8
 
6.4%
9 7
 
5.6%
4 5
 
4.0%
- 4
 
3.2%
Other values (4) 11
8.8%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10569
97.9%
ASCII 227
 
2.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 1763
16.7%
중 916
 
8.7%
소 914
 
8.6%
개 913
 
8.6%
인 906
 
8.6%
무 901
 
8.5%
공 844
 
8.0%
동 332
 
3.1%
부 314
 
3.0%
산 309
 
2.9%
Other values (326) 2457
23.2%
ASCII
ValueCountFrequency (%)
1 20
 
8.8%
K 19
 
8.4%
( 18
 
7.9%
) 18
 
7.9%
16
 
7.0%
S 11
 
4.8%
O 11
 
4.8%
0 10
 
4.4%
2 8
 
3.5%
6 8
 
3.5%
Other values (35) 88
38.8%
CJK
ValueCountFrequency (%)
愛 1
100.0%

행정동
Categorical

Distinct15
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
용신동
125 
장안제1동
110 
전농제1동
102 
답십리제1동
84 
장안제2동
81 
Other values (10)
409 

Length

Max length6
Median length5
Mean length4.6103183
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row청량리동
2nd row제기동
3rd row용신동
4th row용신동
5th row이문제1동

Common Values

ValueCountFrequency (%)
용신동 125
13.7%
장안제1동 110
12.1%
전농제1동 102
11.2%
답십리제1동 84
9.2%
장안제2동 81
8.9%
제기동 71
7.8%
이문제1동 60
6.6%
답십리제2동 58
6.4%
청량리동 51
 
5.6%
휘경제2동 41
 
4.5%
Other values (5) 128
14.1%

Length

2023-12-12T22:07:08.978269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용신동 125
13.7%
장안제1동 110
12.1%
전농제1동 102
11.2%
답십리제1동 84
9.2%
장안제2동 81
8.9%
제기동 71
7.8%
이문제1동 60
6.6%
답십리제2동 58
6.4%
청량리동 51
 
5.6%
휘경제2동 41
 
4.5%
Other values (5) 128
14.1%

사무소주소
Text

Distinct892
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T22:07:09.283896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length28.456641
Min length16

Characters and Unicode

Total characters25924
Distinct characters246
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique874 ?
Unique (%)95.9%

Sample

1st row서울특별시 동대문구 홍릉로 70
2nd row서울특별시 동대문구 약령시로15길 26
3rd row서울특별시 동대문구 고산자로28가길 24
4th row서울특별시 동대문구 천호대로45나길 48
5th row서울특별시 동대문구 외대역동로 93
ValueCountFrequency (%)
서울특별시 911
 
19.7%
동대문구 910
 
19.7%
1층 140
 
3.0%
상가동 51
 
1.1%
이문로 42
 
0.9%
왕산로 41
 
0.9%
사가정로 40
 
0.9%
답십리로 37
 
0.8%
101호 34
 
0.7%
천호대로 32
 
0.7%
Other values (981) 2383
51.6%
2023-12-12T22:07:09.800758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3710
 
14.3%
동 1565
 
6.0%
1 1285
 
5.0%
대 1076
 
4.2%
문 1047
 
4.0%
시 1016
 
3.9%
서 944
 
3.6%
울 940
 
3.6%
로 914
 
3.5%
별 911
 
3.5%
Other values (236) 12516
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16068
62.0%
Decimal Number 4243
 
16.4%
Space Separator 3710
 
14.3%
Other Punctuation 764
 
2.9%
Open Punctuation 478
 
1.8%
Close Punctuation 477
 
1.8%
Dash Punctuation 132
 
0.5%
Uppercase Letter 48
 
0.2%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1565
 
9.7%
대 1076
 
6.7%
문 1047
 
6.5%
시 1016
 
6.3%
서 944
 
5.9%
울 940
 
5.9%
로 914
 
5.7%
별 911
 
5.7%
구 911
 
5.7%
특 911
 
5.7%
Other values (203) 5833
36.3%
Uppercase Letter
ValueCountFrequency (%)
S 9
18.8%
K 9
18.8%
B 8
16.7%
M 3
 
6.2%
J 3
 
6.2%
F 2
 
4.2%
E 2
 
4.2%
T 2
 
4.2%
W 2
 
4.2%
C 2
 
4.2%
Other values (6) 6
12.5%
Decimal Number
ValueCountFrequency (%)
1 1285
30.3%
2 544
12.8%
0 454
 
10.7%
3 387
 
9.1%
4 314
 
7.4%
5 310
 
7.3%
6 298
 
7.0%
7 251
 
5.9%
8 227
 
5.3%
9 173
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 760
99.5%
@ 4
 
0.5%
Space Separator
ValueCountFrequency (%)
3710
100.0%
Open Punctuation
ValueCountFrequency (%)
( 478
100.0%
Close Punctuation
ValueCountFrequency (%)
) 477
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16068
62.0%
Common 9804
37.8%
Latin 52
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1565
 
9.7%
대 1076
 
6.7%
문 1047
 
6.5%
시 1016
 
6.3%
서 944
 
5.9%
울 940
 
5.9%
로 914
 
5.7%
별 911
 
5.7%
구 911
 
5.7%
특 911
 
5.7%
Other values (203) 5833
36.3%
Latin
ValueCountFrequency (%)
S 9
17.3%
K 9
17.3%
B 8
15.4%
e 4
7.7%
M 3
 
5.8%
J 3
 
5.8%
F 2
 
3.8%
E 2
 
3.8%
T 2
 
3.8%
W 2
 
3.8%
Other values (7) 8
15.4%
Common
ValueCountFrequency (%)
3710
37.8%
1 1285
 
13.1%
, 760
 
7.8%
2 544
 
5.5%
( 478
 
4.9%
) 477
 
4.9%
0 454
 
4.6%
3 387
 
3.9%
4 314
 
3.2%
5 310
 
3.2%
Other values (6) 1085
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16068
62.0%
ASCII 9856
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3710
37.6%
1 1285
 
13.0%
, 760
 
7.7%
2 544
 
5.5%
( 478
 
4.8%
) 477
 
4.8%
0 454
 
4.6%
3 387
 
3.9%
4 314
 
3.2%
5 310
 
3.1%
Other values (23) 1137
 
11.5%
Hangul
ValueCountFrequency (%)
동 1565
 
9.7%
대 1076
 
6.7%
문 1047
 
6.5%
시 1016
 
6.3%
서 944
 
5.9%
울 940
 
5.9%
로 914
 
5.7%
별 911
 
5.7%
구 911
 
5.7%
특 911
 
5.7%
Other values (203) 5833
36.3%

사무소전화번호1
Text

MISSING 

Distinct827
Distinct (%)98.1%
Missing68
Missing (%)7.5%
Memory size7.2 KiB
2023-12-12T22:07:10.126893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length8.9264531
Min length8

Characters and Unicode

Total characters7525
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique811 ?
Unique (%)96.2%

Sample

1st row968-8900
2nd row963-3340
3rd row967-6888
4th row962-9653
5th row957-2040
ValueCountFrequency (%)
926-6000 2
 
0.2%
928-3300 2
 
0.2%
2249-1008 2
 
0.2%
957-7773 2
 
0.2%
3394-9088 2
 
0.2%
924-8808 2
 
0.2%
2247-8949 2
 
0.2%
2213-8000 2
 
0.2%
927-1800 2
 
0.2%
2217-1199 2
 
0.2%
Other values (817) 823
97.6%
2023-12-12T22:07:10.669928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1407
18.7%
0 993
13.2%
- 941
12.5%
9 852
11.3%
4 752
10.0%
6 483
 
6.4%
5 456
 
6.1%
8 447
 
5.9%
1 424
 
5.6%
3 387
 
5.1%
Other values (3) 383
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6571
87.3%
Dash Punctuation 941
 
12.5%
Space Separator 12
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1407
21.4%
0 993
15.1%
9 852
13.0%
4 752
11.4%
6 483
 
7.4%
5 456
 
6.9%
8 447
 
6.8%
1 424
 
6.5%
3 387
 
5.9%
7 370
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 941
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7525
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1407
18.7%
0 993
13.2%
- 941
12.5%
9 852
11.3%
4 752
10.0%
6 483
 
6.4%
5 456
 
6.1%
8 447
 
5.9%
1 424
 
5.6%
3 387
 
5.1%
Other values (3) 383
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1407
18.7%
0 993
13.2%
- 941
12.5%
9 852
11.3%
4 752
10.0%
6 483
 
6.4%
5 456
 
6.1%
8 447
 
5.9%
1 424
 
5.6%
3 387
 
5.1%
Other values (3) 383
 
5.1%

사무소전화번호2
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing879
Missing (%)96.5%
Memory size7.2 KiB
2023-12-12T22:07:10.898061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.96875
Min length8

Characters and Unicode

Total characters287
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

Unique32 ?
Unique (%)100.0%

Sample

1st row2213-7071
2nd row925-2222
3rd row2245-8855
4th row2216-7777
5th row2244-0025
ValueCountFrequency (%)
2213-7071 1
 
3.1%
925-2222 1
 
3.1%
2256-7357 1
 
3.1%
6405-2728 1
 
3.1%
2215-8287 1
 
3.1%
922-6900 1
 
3.1%
928-5850 1
 
3.1%
3394-5513 1
 
3.1%
969-7200 1
 
3.1%
757-7870 1
 
3.1%
Other values (22) 22
68.8%
2023-12-12T22:07:11.240935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 61
21.3%
- 35
12.2%
4 31
10.8%
5 26
9.1%
0 24
 
8.4%
1 21
 
7.3%
6 20
 
7.0%
7 19
 
6.6%
9 19
 
6.6%
3 17
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 252
87.8%
Dash Punctuation 35
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 61
24.2%
4 31
12.3%
5 26
10.3%
0 24
 
9.5%
1 21
 
8.3%
6 20
 
7.9%
7 19
 
7.5%
9 19
 
7.5%
3 17
 
6.7%
8 14
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 287
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 61
21.3%
- 35
12.2%
4 31
10.8%
5 26
9.1%
0 24
 
8.4%
1 21
 
7.3%
6 20
 
7.0%
7 19
 
6.6%
9 19
 
6.6%
3 17
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 287
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 61
21.3%
- 35
12.2%
4 31
10.8%
5 26
9.1%
0 24
 
8.4%
1 21
 
7.3%
6 20
 
7.0%
7 19
 
6.6%
9 19
 
6.6%
3 17
 
5.9%

사무소전화번호3
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing907
Missing (%)99.6%
Memory size7.2 KiB
2023-12-12T22:07:11.382710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.75
Min length8

Characters and Unicode

Total characters35
Distinct characters10
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

Unique4 ?
Unique (%)100.0%

Sample

1st row967-0444
2nd row2032-8400
3rd row3394-5534
4th row2256-7358
ValueCountFrequency (%)
967-0444 1
25.0%
2032-8400 1
25.0%
3394-5534 1
25.0%
2256-7358 1
25.0%
2023-12-12T22:07:11.665688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 6
17.1%
3 5
14.3%
- 4
11.4%
0 4
11.4%
2 4
11.4%
5 4
11.4%
9 2
 
5.7%
6 2
 
5.7%
7 2
 
5.7%
8 2
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31
88.6%
Dash Punctuation 4
 
11.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 6
19.4%
3 5
16.1%
0 4
12.9%
2 4
12.9%
5 4
12.9%
9 2
 
6.5%
6 2
 
6.5%
7 2
 
6.5%
8 2
 
6.5%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 6
17.1%
3 5
14.3%
- 4
11.4%
0 4
11.4%
2 4
11.4%
5 4
11.4%
9 2
 
5.7%
6 2
 
5.7%
7 2
 
5.7%
8 2
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 6
17.1%
3 5
14.3%
- 4
11.4%
0 4
11.4%
2 4
11.4%
5 4
11.4%
9 2
 
5.7%
6 2
 
5.7%
7 2
 
5.7%
8 2
 
5.7%

등록일자
Date

Distinct750
Distinct (%)82.3%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
Minimum1984-06-09 00:00:00
Maximum2021-08-11 00:00:00
2023-12-12T22:07:11.787103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:07:12.137574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2021-08-19
911 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-08-19
2nd row2021-08-19
3rd row2021-08-19
4th row2021-08-19
5th row2021-08-19

Common Values

ValueCountFrequency (%)
2021-08-19 911
100.0%

Length

2023-12-12T22:07:12.250725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:07:12.316543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-08-19 911
100.0%

Correlations

2023-12-12T22:07:12.357694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동사무소전화번호2사무소전화번호3
행정동1.0001.0001.000
사무소전화번호21.0001.0001.000
사무소전화번호31.0001.0001.000

Missing values

2023-12-12T22:07:07.289683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:07:07.437114image/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.
2023-12-12T22:07:07.564481image/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

등록번호사무소명행정동사무소주소사무소전화번호1사무소전화번호2사무소전화번호3등록일자데이터기준일자
092240000-992엔탑부동산공인중개사사무소청량리동서울특별시 동대문구 홍릉로 70968-8900<NA><NA>2004-03-022021-08-19
1나-92280000-66대명부동산중개인사무소제기동서울특별시 동대문구 약령시로15길 26963-3340<NA><NA>1984-06-092021-08-19
2나-92280000-220용두부동산중개인사무소용신동서울특별시 동대문구 고산자로28가길 24967-6888<NA><NA>1984-06-182021-08-19
3나-92280000-204중앙부동산중개인사무소용신동서울특별시 동대문구 천호대로45나길 48962-9653<NA><NA>1984-06-182021-08-19
4나-92280000-1013삼성래미안부동산중개인사무소이문제1동서울특별시 동대문구 외대역동로 93957-2040<NA><NA>1984-06-202021-08-19
5나-92280000-1463동신부동산중개인사무소장안제2동서울특별시 동대문구 장한로33길 192245-2736<NA><NA>1984-06-202021-08-19
6나-92280000-1372대지부동산중개인사무소장안제2동서울특별시 동대문구 장한로28가길 762212-4270<NA><NA>1984-06-202021-08-19
7나-92280000-1521삼진부동산중개인사무소답십리제2동서울특별시 동대문구 한천로 17, B동2층44호2212-2168<NA><NA>1984-06-202021-08-19
8나-92280000-1515장평부동산중개인사무소장안제2동서울특별시 동대문구 답십리로63길 212212-2672<NA><NA>1984-06-202021-08-19
9나-92280000-1724삼우부동산중개인사무소회기동서울특별시 동대문구 이문로 43962-1478<NA><NA>1984-06-252021-08-19
등록번호사무소명행정동사무소주소사무소전화번호1사무소전화번호2사무소전화번호3등록일자데이터기준일자
90111230-2021-00087장안공인중개사사무소장안제2동서울특별시 동대문구 한천로 224, 상가동 102호 (장안동,현대아파트)2216-7800<NA><NA>2021-07-212021-08-19
90211230-2021-00088드림부동산공인중개사사무소장안제1동서울특별시 동대문구 천호대로77나길 2, 1층 (장안동)2244-8895<NA><NA>2021-07-222021-08-19
90311230-2021-00089청광2차공인중개사사무소용신동서울특별시 동대문구 청계천로 471, 102호 (용두동,청계천대성스카이렉스2)<NA><NA><NA>2021-03-022021-08-19
90411230-2021-00090힐스테이트공인중개사사무소전농제1동서울특별시 동대문구 왕산로 250, 101호 (전농동,리베르떼)<NA><NA><NA>2021-07-292021-08-19
90511230-2021-00091복부동산공인중개사사무소전농제1동서울특별시 동대문구 사가정로 65, 근린생활시설1 101호(전농동,래미안크레시티)2242-6000<NA><NA>2021-07-292021-08-19
90611230-2021-00092조이부동산공인중개사사무소전농제1동서울특별시 동대문구 사가정로 65, 근린생활시설1 107호(전농동,래미안크레시티)<NA><NA><NA>2021-07-302021-08-19
90711230-2021-00093청포도공인중개사사무소용신동서울특별시 동대문구 청계천로 483, 103호(용두동,창보리버리치)929-1114<NA><NA>2021-08-112021-08-19
90811230-2021-00094석사공인중개사사무소회기동서울특별시 동대문구 경희대로 8, 1층(회기동)969-7788<NA><NA>2018-06-012021-08-19
90992380000-2709대은공인중개사사무소청량리동서울특별시 동대문구 홍릉로25길 16-1959-4356<NA><NA>2006-03-082021-08-19
910가-3620-411황소공인중개사사무소휘경제2동서울특별시 동대문구 한천로 250, 주상가동 101호(휘경동,주공아파트)2244-4445<NA><NA>2003-11-192021-08-19