Overview

Dataset statistics

Number of variables7
Number of observations219
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory56.6 B

Variable types

Text3
Categorical3
DateTime1

Dataset

Description경기도 여주시 공인중개사정보 공공데이터입니다. 등록번호, 중개업소명, 소재지도로명주소, 등록일자, 관리기관명, 데이터기준일자 등의 데이터를 제공합니다.
Author경기도 여주시
URLhttps://www.data.go.kr/data/15090609/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
중개업소구분 is highly imbalanced (84.5%)Imbalance
등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:19:49.670320
Analysis finished2023-12-12 21:19:50.191216
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct219
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-13T06:19:50.370796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length12.616438
Min length9

Characters and Unicode

Total characters2763
Distinct characters13
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

Unique219 ?
Unique (%)100.0%

Sample

1st row가3624-021
2nd row가3624-047
3rd row가3624-050
4th row가3624-491
5th row가3624-319
ValueCountFrequency (%)
가3624-021 1
 
0.5%
41670-2018-00033 1
 
0.5%
41670-2019-00017 1
 
0.5%
41670-2018-00020 1
 
0.5%
41670-2018-00022 1
 
0.5%
41670-2018-00021 1
 
0.5%
41670-2018-00023 1
 
0.5%
41670-2018-00018 1
 
0.5%
41670-2018-00028 1
 
0.5%
41670-2018-00029 1
 
0.5%
Other values (209) 209
95.4%
2023-12-13T06:19:50.724158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 650
23.5%
2 337
12.2%
- 331
12.0%
6 281
10.2%
1 273
9.9%
4 266
9.6%
3 169
 
6.1%
7 168
 
6.1%
가 107
 
3.9%
8 70
 
2.5%
Other values (3) 111
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2317
83.9%
Dash Punctuation 331
 
12.0%
Other Letter 115
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 650
28.1%
2 337
14.5%
6 281
12.1%
1 273
11.8%
4 266
11.5%
3 169
 
7.3%
7 168
 
7.3%
8 70
 
3.0%
5 52
 
2.2%
9 51
 
2.2%
Other Letter
ValueCountFrequency (%)
가 107
93.0%
호 8
 
7.0%
Dash Punctuation
ValueCountFrequency (%)
- 331
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2648
95.8%
Hangul 115
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 650
24.5%
2 337
12.7%
- 331
12.5%
6 281
10.6%
1 273
10.3%
4 266
10.0%
3 169
 
6.4%
7 168
 
6.3%
8 70
 
2.6%
5 52
 
2.0%
Hangul
ValueCountFrequency (%)
가 107
93.0%
호 8
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2648
95.8%
Hangul 115
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 650
24.5%
2 337
12.7%
- 331
12.5%
6 281
10.6%
1 273
10.3%
4 266
10.0%
3 169
 
6.4%
7 168
 
6.3%
8 70
 
2.6%
5 52
 
2.0%
Hangul
ValueCountFrequency (%)
가 107
93.0%
호 8
 
7.0%

중개업소구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
공인중개사
211 
중개인
 
7
법인
 
1

Length

Max length5
Median length5
Mean length4.9223744
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
공인중개사 211
96.3%
중개인 7
 
3.2%
법인 1
 
0.5%

Length

2023-12-13T06:19:50.859805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:19:50.964890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공인중개사 211
96.3%
중개인 7
 
3.2%
법인 1
 
0.5%

중개업소명
Text

Distinct216
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-13T06:19:51.158966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length11.305936
Min length4

Characters and Unicode

Total characters2476
Distinct characters229
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

Unique214 ?
Unique (%)97.7%

Sample

1st row여주부동산중개랜드
2nd row쌍용부동산중개사무소
3rd row와룡부동산중개사무소
4th row국일부동산중개사무소
5th row믿음부동산중개사무소
ValueCountFrequency (%)
신동부동산중개사무소 3
 
1.4%
해든공인중개사사무소 2
 
0.9%
부동산중개법인 1
 
0.5%
동남부동산공인중개사무소 1
 
0.5%
바름공인중개사사무소 1
 
0.5%
여주부동산중개랜드 1
 
0.5%
강남공인중개사사무소 1
 
0.5%
한강공인중개사사무소 1
 
0.5%
동명공인중개사사무소 1
 
0.5%
월드공인중개사사무소 1
 
0.5%
Other values (207) 207
94.1%
2023-12-13T06:19:51.515522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 407
16.4%
중 220
 
8.9%
개 218
 
8.8%
소 215
 
8.7%
무 214
 
8.6%
인 206
 
8.3%
공 201
 
8.1%
동 78
 
3.2%
산 71
 
2.9%
부 68
 
2.7%
Other values (219) 578
23.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2443
98.7%
Uppercase Letter 26
 
1.1%
Decimal Number 3
 
0.1%
Open Punctuation 1
 
< 0.1%
Space Separator 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 407
16.7%
중 220
9.0%
개 218
 
8.9%
소 215
 
8.8%
무 214
 
8.8%
인 206
 
8.4%
공 201
 
8.2%
동 78
 
3.2%
산 71
 
2.9%
부 68
 
2.8%
Other values (198) 545
22.3%
Uppercase Letter
ValueCountFrequency (%)
K 4
15.4%
C 4
15.4%
T 3
11.5%
P 2
7.7%
A 2
7.7%
O 2
7.7%
H 2
7.7%
R 1
 
3.8%
I 1
 
3.8%
V 1
 
3.8%
Other values (4) 4
15.4%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
3 1
33.3%
1 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2443
98.7%
Latin 26
 
1.1%
Common 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 407
16.7%
중 220
9.0%
개 218
 
8.9%
소 215
 
8.8%
무 214
 
8.8%
인 206
 
8.4%
공 201
 
8.2%
동 78
 
3.2%
산 71
 
2.9%
부 68
 
2.8%
Other values (198) 545
22.3%
Latin
ValueCountFrequency (%)
K 4
15.4%
C 4
15.4%
T 3
11.5%
P 2
7.7%
A 2
7.7%
O 2
7.7%
H 2
7.7%
R 1
 
3.8%
I 1
 
3.8%
V 1
 
3.8%
Other values (4) 4
15.4%
Common
ValueCountFrequency (%)
2 1
14.3%
( 1
14.3%
3 1
14.3%
1
14.3%
1 1
14.3%
& 1
14.3%
) 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2443
98.7%
ASCII 33
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 407
16.7%
중 220
9.0%
개 218
 
8.9%
소 215
 
8.8%
무 214
 
8.8%
인 206
 
8.4%
공 201
 
8.2%
동 78
 
3.2%
산 71
 
2.9%
부 68
 
2.8%
Other values (198) 545
22.3%
ASCII
ValueCountFrequency (%)
K 4
 
12.1%
C 4
 
12.1%
T 3
 
9.1%
P 2
 
6.1%
A 2
 
6.1%
O 2
 
6.1%
H 2
 
6.1%
2 1
 
3.0%
( 1
 
3.0%
3 1
 
3.0%
Other values (11) 11
33.3%

소재지도로명주소
Text

Distinct209
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-13T06:19:51.802978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length43
Mean length21.671233
Min length14

Characters and Unicode

Total characters4746
Distinct characters137
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

Unique200 ?
Unique (%)91.3%

Sample

1st row경기도 여주시 장여로 1755
2nd row경기도 여주시 세종로 351, 103호(점봉동)
3rd row경기도 여주시 세종로 41(홍문동)
4th row경기도 여주시 금사면 금사로 205
5th row경기도 여주시 금사면 금사로 71
ValueCountFrequency (%)
경기도 216
19.9%
여주시 215
19.8%
세종로 45
 
4.2%
1층 30
 
2.8%
여양로 20
 
1.8%
대신면 19
 
1.8%
상가동 19
 
1.8%
가남읍 17
 
1.6%
능서면 11
 
1.0%
산북면 10
 
0.9%
Other values (295) 482
44.5%
2023-12-13T06:19:52.205350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
865
18.2%
여 275
 
5.8%
1 247
 
5.2%
주 231
 
4.9%
도 230
 
4.8%
경 225
 
4.7%
기 216
 
4.6%
시 216
 
4.6%
로 196
 
4.1%
2 138
 
2.9%
Other values (127) 1907
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2689
56.7%
Decimal Number 911
 
19.2%
Space Separator 865
 
18.2%
Other Punctuation 90
 
1.9%
Open Punctuation 61
 
1.3%
Dash Punctuation 61
 
1.3%
Close Punctuation 61
 
1.3%
Uppercase Letter 7
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 275
 
10.2%
주 231
 
8.6%
도 230
 
8.6%
경 225
 
8.4%
기 216
 
8.0%
시 216
 
8.0%
로 196
 
7.3%
동 97
 
3.6%
면 65
 
2.4%
세 53
 
2.0%
Other values (108) 885
32.9%
Decimal Number
ValueCountFrequency (%)
1 247
27.1%
2 138
15.1%
3 93
 
10.2%
0 89
 
9.8%
4 80
 
8.8%
5 59
 
6.5%
8 54
 
5.9%
6 54
 
5.9%
7 49
 
5.4%
9 48
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
C 4
57.1%
K 2
28.6%
B 1
 
14.3%
Space Separator
ValueCountFrequency (%)
865
100.0%
Other Punctuation
ValueCountFrequency (%)
, 90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2689
56.7%
Common 2049
43.2%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 275
 
10.2%
주 231
 
8.6%
도 230
 
8.6%
경 225
 
8.4%
기 216
 
8.0%
시 216
 
8.0%
로 196
 
7.3%
동 97
 
3.6%
면 65
 
2.4%
세 53
 
2.0%
Other values (108) 885
32.9%
Common
ValueCountFrequency (%)
865
42.2%
1 247
 
12.1%
2 138
 
6.7%
3 93
 
4.5%
, 90
 
4.4%
0 89
 
4.3%
4 80
 
3.9%
( 61
 
3.0%
- 61
 
3.0%
) 61
 
3.0%
Other values (5) 264
 
12.9%
Latin
ValueCountFrequency (%)
C 4
50.0%
K 2
25.0%
b 1
 
12.5%
B 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2689
56.7%
ASCII 2057
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
865
42.1%
1 247
 
12.0%
2 138
 
6.7%
3 93
 
4.5%
, 90
 
4.4%
0 89
 
4.3%
4 80
 
3.9%
( 61
 
3.0%
- 61
 
3.0%
) 61
 
3.0%
Other values (9) 272
 
13.2%
Hangul
ValueCountFrequency (%)
여 275
 
10.2%
주 231
 
8.6%
도 230
 
8.6%
경 225
 
8.4%
기 216
 
8.0%
시 216
 
8.0%
로 196
 
7.3%
동 97
 
3.6%
면 65
 
2.4%
세 53
 
2.0%
Other values (108) 885
32.9%

등록일자
Date

Distinct201
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1984-09-20 00:00:00
Maximum2021-07-27 00:00:00
2023-12-13T06:19:52.637509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:52.766056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
경기도 여주시청
219 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 여주시청 219
100.0%

Length

2023-12-13T06:19:52.881792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:19:53.013083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 219
50.0%
여주시청 219
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2021-09-27
219 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-27
2nd row2021-09-27
3rd row2021-09-27
4th row2021-09-27
5th row2021-09-27

Common Values

ValueCountFrequency (%)
2021-09-27 219
100.0%

Length

2023-12-13T06:19:53.138258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:19:53.248144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-27 219
100.0%

Missing values

2023-12-13T06:19:50.003823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:19:50.142992image/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.

Sample

등록번호중개업소구분중개업소명소재지도로명주소등록일자관리기관명데이터기준일자
0가3624-021중개인여주부동산중개랜드경기도 여주시 장여로 17551984-09-20경기도 여주시청2021-09-27
1가3624-047중개인쌍용부동산중개사무소경기도 여주시 세종로 351, 103호(점봉동)1986-07-29경기도 여주시청2021-09-27
2가3624-050중개인와룡부동산중개사무소경기도 여주시 세종로 41(홍문동)1986-09-30경기도 여주시청2021-09-27
3가3624-491중개인국일부동산중개사무소경기도 여주시 금사면 금사로 2052006-12-08경기도 여주시청2021-09-27
4가3624-319중개인믿음부동산중개사무소경기도 여주시 금사면 금사로 711986-03-17경기도 여주시청2021-09-27
5가3624-454중개인팔도부동산중개사무소경기도 여주시 세종로58번길 12(창동)2006-04-04경기도 여주시청2021-09-27
6가3624-060호중개인대교부동산중개사무소경기도 여주시 대신면 여양로 19871987-05-11경기도 여주시청2021-09-27
7가3624-073공인중개사대신공인중개사사무소경기도 여주시 대신면 여양로 14851989-01-10경기도 여주시청2021-09-27
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