Overview

Dataset statistics

Number of variables11
Number of observations500
Missing cells101
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.6 KiB
Average record size in memory89.3 B

Variable types

Numeric1
Categorical5
Text5

Dataset

Description2021년 부산광역시 남구에 영업하고 있는 부동산중개업소의 업소명, 대표자, 주소, 전화번호 등의 자료 제공합니다
Author부산광역시 남구
URLhttps://www.data.go.kr/data/15047919/fileData.do

Alerts

시군구 has constant value ""Constant
행정처분상태 has constant value ""Constant
직위 has constant value ""Constant
중개업소종별 is highly imbalanced (89.2%)Imbalance
사무소전화번호 has 101 (20.2%) missing valuesMissing
연번 has unique valuesUnique
등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:51:08.585666
Analysis finished2023-12-12 06:51:09.329378
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean250.5
Minimum1
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T15:51:09.398641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.95
Q1125.75
median250.5
Q3375.25
95-th percentile475.05
Maximum500
Range499
Interquartile range (IQR)249.5

Descriptive statistics

Standard deviation144.48183
Coefficient of variation (CV)0.57677378
Kurtosis-1.2
Mean250.5
Median Absolute Deviation (MAD)125
Skewness0
Sum125250
Variance20875
MonotonicityStrictly increasing
2023-12-12T15:51:09.562205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
331 1
 
0.2%
344 1
 
0.2%
343 1
 
0.2%
342 1
 
0.2%
341 1
 
0.2%
340 1
 
0.2%
339 1
 
0.2%
338 1
 
0.2%
337 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
500 1
0.2%
499 1
0.2%
498 1
0.2%
497 1
0.2%
496 1
0.2%
495 1
0.2%
494 1
0.2%
493 1
0.2%
492 1
0.2%
491 1
0.2%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
부산광역시 남구
500 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 남구
2nd row부산광역시 남구
3rd row부산광역시 남구
4th row부산광역시 남구
5th row부산광역시 남구

Common Values

ValueCountFrequency (%)
부산광역시 남구 500
100.0%

Length

2023-12-12T15:51:09.725981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:51:10.170124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 500
50.0%
남구 500
50.0%

등록번호
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T15:51:10.390913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length13.35
Min length6

Characters and Unicode

Total characters6675
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

Unique500 ?
Unique (%)100.0%

Sample

1st row가-7-1700
2nd row가-7-1770
3rd row가-7-1186
4th row가-7-1184
5th row가-7-1182
ValueCountFrequency (%)
가-7-1700 1
 
0.2%
26290-2018-00002 1
 
0.2%
26290-2018-00031 1
 
0.2%
26290-2018-00030 1
 
0.2%
26290-2018-00028 1
 
0.2%
26290-2018-00026 1
 
0.2%
26290-2018-00025 1
 
0.2%
26290-2018-00023 1
 
0.2%
26290-2018-00022 1
 
0.2%
26290-2018-00020 1
 
0.2%
Other values (490) 490
98.0%
2023-12-12T15:51:10.858755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1685
25.2%
2 1205
18.1%
- 1000
15.0%
1 642
 
9.6%
9 507
 
7.6%
6 493
 
7.4%
7 356
 
5.3%
8 203
 
3.0%
5 161
 
2.4%
가 160
 
2.4%
Other values (3) 263
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5512
82.6%
Dash Punctuation 1000
 
15.0%
Other Letter 163
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1685
30.6%
2 1205
21.9%
1 642
 
11.6%
9 507
 
9.2%
6 493
 
8.9%
7 356
 
6.5%
8 203
 
3.7%
5 161
 
2.9%
3 137
 
2.5%
4 123
 
2.2%
Other Letter
ValueCountFrequency (%)
가 160
98.2%
나 3
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6512
97.6%
Hangul 163
 
2.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1685
25.9%
2 1205
18.5%
- 1000
15.4%
1 642
 
9.9%
9 507
 
7.8%
6 493
 
7.6%
7 356
 
5.5%
8 203
 
3.1%
5 161
 
2.5%
3 137
 
2.1%
Hangul
ValueCountFrequency (%)
가 160
98.2%
나 3
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6512
97.6%
Hangul 163
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1685
25.9%
2 1205
18.5%
- 1000
15.4%
1 642
 
9.9%
9 507
 
7.8%
6 493
 
7.6%
7 356
 
5.5%
8 203
 
3.1%
5 161
 
2.5%
3 137
 
2.1%
Hangul
ValueCountFrequency (%)
가 160
98.2%
나 3
 
1.8%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
영업중
500 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 500
100.0%

Length

2023-12-12T15:51:11.024543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:51:11.161157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 500
100.0%

사무소명
Text

Distinct469
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T15:51:11.374994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length11.506
Min length7

Characters and Unicode

Total characters5753
Distinct characters293
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique446 ?
Unique (%)89.2%

Sample

1st row뉴부산부동산중개인사무소
2nd row탑공인중개사사무소
3rd row오륙도SK공인중개사사무소
4th row대연바다공인중개사사무소
5th row오륙도드림부동산중개사무소
ValueCountFrequency (%)
미래공인중개사사무소 4
 
0.8%
삼성공인중개사사무소 4
 
0.8%
굿모닝공인중개사사무소 3
 
0.6%
현대공인중개사사무소 3
 
0.6%
금빛공인중개사사무소 3
 
0.6%
대길공인중개사사무소 3
 
0.6%
다온부동산공인중개사사무소 2
 
0.4%
우리부동산공인중개사사무소 2
 
0.4%
자유공인중개사사무소 2
 
0.4%
그린공인중개사사무소 2
 
0.4%
Other values (465) 479
94.5%
2023-12-12T15:51:11.789374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 895
15.6%
중 503
 
8.7%
개 502
 
8.7%
소 497
 
8.6%
무 493
 
8.6%
인 409
 
7.1%
공 397
 
6.9%
동 227
 
3.9%
부 226
 
3.9%
산 218
 
3.8%
Other values (283) 1386
24.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5599
97.3%
Uppercase Letter 107
 
1.9%
Decimal Number 22
 
0.4%
Lowercase Letter 10
 
0.2%
Space Separator 7
 
0.1%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 895
16.0%
중 503
9.0%
개 502
9.0%
소 497
8.9%
무 493
8.8%
인 409
 
7.3%
공 397
 
7.1%
동 227
 
4.1%
부 226
 
4.0%
산 218
 
3.9%
Other values (250) 1232
22.0%
Uppercase Letter
ValueCountFrequency (%)
K 26
24.3%
S 19
17.8%
L 14
13.1%
G 14
13.1%
W 13
12.1%
T 4
 
3.7%
O 3
 
2.8%
H 3
 
2.8%
E 2
 
1.9%
I 2
 
1.9%
Other values (7) 7
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 7
31.8%
8 7
31.8%
9 2
 
9.1%
4 2
 
9.1%
2 1
 
4.5%
3 1
 
4.5%
6 1
 
4.5%
5 1
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
e 5
50.0%
h 3
30.0%
s 1
 
10.0%
k 1
 
10.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5599
97.3%
Latin 117
 
2.0%
Common 37
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 895
16.0%
중 503
9.0%
개 502
9.0%
소 497
8.9%
무 493
8.8%
인 409
 
7.3%
공 397
 
7.1%
동 227
 
4.1%
부 226
 
4.0%
산 218
 
3.9%
Other values (250) 1232
22.0%
Latin
ValueCountFrequency (%)
K 26
22.2%
S 19
16.2%
L 14
12.0%
G 14
12.0%
W 13
11.1%
e 5
 
4.3%
T 4
 
3.4%
h 3
 
2.6%
O 3
 
2.6%
H 3
 
2.6%
Other values (11) 13
11.1%
Common
ValueCountFrequency (%)
7
18.9%
1 7
18.9%
8 7
18.9%
( 3
8.1%
) 3
8.1%
9 2
 
5.4%
4 2
 
5.4%
- 2
 
5.4%
2 1
 
2.7%
3 1
 
2.7%
Other values (2) 2
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5599
97.3%
ASCII 154
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 895
16.0%
중 503
9.0%
개 502
9.0%
소 497
8.9%
무 493
8.8%
인 409
 
7.3%
공 397
 
7.1%
동 227
 
4.1%
부 226
 
4.0%
산 218
 
3.9%
Other values (250) 1232
22.0%
ASCII
ValueCountFrequency (%)
K 26
16.9%
S 19
12.3%
L 14
 
9.1%
G 14
 
9.1%
W 13
 
8.4%
7
 
4.5%
1 7
 
4.5%
8 7
 
4.5%
e 5
 
3.2%
T 4
 
2.6%
Other values (23) 38
24.7%

중개업소종별
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
공인중개사
489 
중개인
 
8
법인
 
3

Length

Max length5
Median length5
Mean length4.95
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공인중개사 489
97.8%
중개인 8
 
1.6%
법인 3
 
0.6%

Length

2023-12-12T15:51:11.943924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:51:12.063942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공인중개사 489
97.8%
중개인 8
 
1.6%
법인 3
 
0.6%

중개업자명
Text

Distinct486
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T15:51:12.403704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.988
Min length2

Characters and Unicode

Total characters1494
Distinct characters166
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

Unique474 ?
Unique (%)94.8%

Sample

1st row강진홍
2nd row박진옥
3rd row손호성
4th row송도호
5th row윤영주
ValueCountFrequency (%)
김만수 3
 
0.6%
이정옥 3
 
0.6%
이정희 2
 
0.4%
김인숙 2
 
0.4%
유명희 2
 
0.4%
김미화 2
 
0.4%
김수현 2
 
0.4%
임수정 2
 
0.4%
박경란 2
 
0.4%
김미란 2
 
0.4%
Other values (476) 478
95.6%
2023-12-12T15:51:12.923969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 103
 
6.9%
이 90
 
6.0%
정 66
 
4.4%
영 62
 
4.1%
희 54
 
3.6%
경 36
 
2.4%
숙 34
 
2.3%
박 34
 
2.3%
수 32
 
2.1%
미 31
 
2.1%
Other values (156) 952
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1494
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 103
 
6.9%
이 90
 
6.0%
정 66
 
4.4%
영 62
 
4.1%
희 54
 
3.6%
경 36
 
2.4%
숙 34
 
2.3%
박 34
 
2.3%
수 32
 
2.1%
미 31
 
2.1%
Other values (156) 952
63.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1494
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 103
 
6.9%
이 90
 
6.0%
정 66
 
4.4%
영 62
 
4.1%
희 54
 
3.6%
경 36
 
2.4%
숙 34
 
2.3%
박 34
 
2.3%
수 32
 
2.1%
미 31
 
2.1%
Other values (156) 952
63.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1494
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 103
 
6.9%
이 90
 
6.0%
정 66
 
4.4%
영 62
 
4.1%
희 54
 
3.6%
경 36
 
2.4%
숙 34
 
2.3%
박 34
 
2.3%
수 32
 
2.1%
미 31
 
2.1%
Other values (156) 952
63.7%

직위
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
대표
500 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대표 500
100.0%

Length

2023-12-12T15:51:13.064228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:51:13.157999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대표 500
100.0%

사무소전화번호
Text

MISSING 

Distinct394
Distinct (%)98.7%
Missing101
Missing (%)20.2%
Memory size4.0 KiB
2023-12-12T15:51:13.408841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.005013
Min length12

Characters and Unicode

Total characters4790
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

Unique389 ?
Unique (%)97.5%

Sample

1st row051-809-6111
2nd row051-612-6114
3rd row051-623-2624
4th row051-625-3006
5th row051-623-5482
ValueCountFrequency (%)
051-611-3500 2
 
0.5%
051-918-0808 2
 
0.5%
051-633-4800 2
 
0.5%
051-622-8300 2
 
0.5%
051-632-2489 2
 
0.5%
051-612-9900 1
 
0.3%
051-628-9989 1
 
0.3%
051-638-3031 1
 
0.3%
051-626-5800 1
 
0.3%
051-647-6664 1
 
0.3%
Other values (384) 384
96.2%
2023-12-12T15:51:13.865463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 798
16.7%
0 778
16.2%
1 706
14.7%
5 562
11.7%
6 504
10.5%
2 387
8.1%
3 274
 
5.7%
8 241
 
5.0%
9 196
 
4.1%
7 180
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3992
83.3%
Dash Punctuation 798
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 778
19.5%
1 706
17.7%
5 562
14.1%
6 504
12.6%
2 387
9.7%
3 274
 
6.9%
8 241
 
6.0%
9 196
 
4.9%
7 180
 
4.5%
4 164
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 798
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4790
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 798
16.7%
0 778
16.2%
1 706
14.7%
5 562
11.7%
6 504
10.5%
2 387
8.1%
3 274
 
5.7%
8 241
 
5.0%
9 196
 
4.1%
7 180
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4790
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 798
16.7%
0 778
16.2%
1 706
14.7%
5 562
11.7%
6 504
10.5%
2 387
8.1%
3 274
 
5.7%
8 241
 
5.0%
9 196
 
4.1%
7 180
 
3.8%

사무소주소
Text

Distinct481
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T15:51:14.187007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length41
Mean length29.464
Min length15

Characters and Unicode

Total characters14732
Distinct characters212
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

Unique465 ?
Unique (%)93.0%

Sample

1st row부산광역시 남구 전포대로67번길 4(문현동)
2nd row부산광역시 남구 수영로 201(대연동)
3rd row부산광역시 남구 동명로132번길 77(용호동)
4th row부산광역시 남구 유엔로75번길 5, 상가 101호(우암동,동림리라)
5th row부산광역시 남구 용호로 225(용호동)
ValueCountFrequency (%)
부산광역시 499
 
19.3%
남구 499
 
19.3%
수영로 81
 
3.1%
분포로 44
 
1.7%
상가동 23
 
0.9%
101호(대연동 19
 
0.7%
345 18
 
0.7%
용호로 17
 
0.7%
진남로 15
 
0.6%
엘지메트로시티 15
 
0.6%
Other values (700) 1356
52.4%
2023-12-12T15:51:14.606656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2086
 
14.2%
1 904
 
6.1%
동 592
 
4.0%
시 534
 
3.6%
로 525
 
3.6%
남 521
 
3.5%
산 504
 
3.4%
부 501
 
3.4%
광 500
 
3.4%
구 500
 
3.4%
Other values (202) 7565
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8500
57.7%
Decimal Number 2760
 
18.7%
Space Separator 2086
 
14.2%
Other Punctuation 468
 
3.2%
Close Punctuation 394
 
2.7%
Open Punctuation 394
 
2.7%
Dash Punctuation 77
 
0.5%
Uppercase Letter 44
 
0.3%
Lowercase Letter 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 592
 
7.0%
시 534
 
6.3%
로 525
 
6.2%
남 521
 
6.1%
산 504
 
5.9%
부 501
 
5.9%
광 500
 
5.9%
구 500
 
5.9%
역 499
 
5.9%
호 366
 
4.3%
Other values (173) 3458
40.7%
Decimal Number
ValueCountFrequency (%)
1 904
32.8%
0 364
13.2%
2 332
 
12.0%
3 264
 
9.6%
5 226
 
8.2%
4 197
 
7.1%
6 171
 
6.2%
9 108
 
3.9%
7 97
 
3.5%
8 97
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
A 12
27.3%
W 8
18.2%
B 7
15.9%
S 5
11.4%
G 5
11.4%
L 2
 
4.5%
K 2
 
4.5%
O 1
 
2.3%
N 1
 
2.3%
E 1
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
a 5
55.6%
e 2
 
22.2%
b 1
 
11.1%
w 1
 
11.1%
Space Separator
ValueCountFrequency (%)
2086
100.0%
Other Punctuation
ValueCountFrequency (%)
, 468
100.0%
Close Punctuation
ValueCountFrequency (%)
) 394
100.0%
Open Punctuation
ValueCountFrequency (%)
( 394
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8500
57.7%
Common 6179
41.9%
Latin 53
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 592
 
7.0%
시 534
 
6.3%
로 525
 
6.2%
남 521
 
6.1%
산 504
 
5.9%
부 501
 
5.9%
광 500
 
5.9%
구 500
 
5.9%
역 499
 
5.9%
호 366
 
4.3%
Other values (173) 3458
40.7%
Common
ValueCountFrequency (%)
2086
33.8%
1 904
14.6%
, 468
 
7.6%
) 394
 
6.4%
( 394
 
6.4%
0 364
 
5.9%
2 332
 
5.4%
3 264
 
4.3%
5 226
 
3.7%
4 197
 
3.2%
Other values (5) 550
 
8.9%
Latin
ValueCountFrequency (%)
A 12
22.6%
W 8
15.1%
B 7
13.2%
S 5
9.4%
a 5
9.4%
G 5
9.4%
e 2
 
3.8%
L 2
 
3.8%
K 2
 
3.8%
O 1
 
1.9%
Other values (4) 4
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8500
57.7%
ASCII 6232
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2086
33.5%
1 904
14.5%
, 468
 
7.5%
) 394
 
6.3%
( 394
 
6.3%
0 364
 
5.8%
2 332
 
5.3%
3 264
 
4.2%
5 226
 
3.6%
4 197
 
3.2%
Other values (19) 603
 
9.7%
Hangul
ValueCountFrequency (%)
동 592
 
7.0%
시 534
 
6.3%
로 525
 
6.2%
남 521
 
6.1%
산 504
 
5.9%
부 501
 
5.9%
광 500
 
5.9%
구 500
 
5.9%
역 499
 
5.9%
호 366
 
4.3%
Other values (173) 3458
40.7%

행정동
Categorical

Distinct18
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
대연3동
105 
용호1동
59 
대연1동
57 
<NA>
37 
대연6동
36 
Other values (13)
206 

Length

Max length4
Median length4
Mean length3.944
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문현2동
2nd row대연5동
3rd row용호4동
4th row대연4동
5th row용호2동

Common Values

ValueCountFrequency (%)
대연3동 105
21.0%
용호1동 59
11.8%
대연1동 57
11.4%
<NA> 37
 
7.4%
대연6동 36
 
7.2%
대연5동 32
 
6.4%
용호2동 27
 
5.4%
감만1동 20
 
4.0%
우암동 19
 
3.8%
문현3동 18
 
3.6%
Other values (8) 90
18.0%

Length

2023-12-12T15:51:14.723073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대연3동 105
21.0%
용호1동 59
11.8%
대연1동 57
11.4%
na 37
 
7.4%
대연6동 36
 
7.2%
대연5동 32
 
6.4%
용호2동 27
 
5.4%
감만1동 20
 
4.0%
우암동 19
 
3.8%
문현3동 18
 
3.6%
Other values (8) 90
18.0%

Interactions

2023-12-12T15:51:09.010763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:51:14.792660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번중개업소종별행정동
연번1.0000.3860.157
중개업소종별0.3861.0000.100
행정동0.1570.1001.000
2023-12-12T15:51:14.877741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중개업소종별행정동
중개업소종별1.0000.052
행정동0.0521.000
2023-12-12T15:51:14.952728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번중개업소종별행정동
연번1.0000.2500.061
중개업소종별0.2501.0000.052
행정동0.0610.0521.000

Missing values

2023-12-12T15:51:09.125932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:51:09.271997image/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

연번시군구등록번호행정처분상태사무소명중개업소종별중개업자명직위사무소전화번호사무소주소행정동
01부산광역시 남구가-7-1700영업중뉴부산부동산중개인사무소중개인강진홍대표051-809-6111부산광역시 남구 전포대로67번길 4(문현동)문현2동
12부산광역시 남구가-7-1770영업중탑공인중개사사무소공인중개사박진옥대표051-612-6114부산광역시 남구 수영로 201(대연동)대연5동
23부산광역시 남구가-7-1186영업중오륙도SK공인중개사사무소공인중개사손호성대표051-623-2624부산광역시 남구 동명로132번길 77(용호동)용호4동
34부산광역시 남구가-7-1184영업중대연바다공인중개사사무소공인중개사송도호대표<NA>부산광역시 남구 유엔로75번길 5, 상가 101호(우암동,동림리라)대연4동
45부산광역시 남구가-7-1182영업중오륙도드림부동산중개사무소공인중개사윤영주대표051-625-3006부산광역시 남구 용호로 225(용호동)용호2동
56부산광역시 남구가-7-1164영업중성원공인중개사사무소공인중개사황경희대표051-623-5482부산광역시 남구 동명로164번길 94(용호동)용호2동
67부산광역시 남구가-7-1153영업중제일부동산중개사무소공인중개사이명철대표051-633-7172부산광역시 남구 고동골로 42-1(문현동)문현3동
78부산광역시 남구가-7-1232영업중LG공인중개사사무소공인중개사박해영대표051-627-0077부산광역시 남구 분포로 111, 1001동 107호(용호동, 엘지메트로시티)용호1동
89부산광역시 남구가-7-1239영업중경동부동산중개사사무소공인중개사이민영대표051-623-3939부산광역시 남구 황령대로319번길 26, 상가동 102호(대연동, 경동메르빌)대연3동
910부산광역시 남구가-7-1248영업중명일부동산공인중개사사무소공인중개사한희영대표051-637-8084부산광역시 남구 전포대로 78-1, 1층<NA>
연번시군구등록번호행정처분상태사무소명중개업소종별중개업자명직위사무소전화번호사무소주소행정동
490491부산광역시 남구26290-2019-00074영업중혁신스타공인중개사사무소공인중개사김은아대표<NA>부산광역시 남구 수영로 345, 301동 106호<NA>
491492부산광역시 남구26290-2019-00075영업중SK마루공인중개사사무소공인중개사김광수대표<NA>부산광역시 남구 수영로 253-1, 2층<NA>
492493부산광역시 남구26290-2019-00076영업중W해동부동산공인중개사사무소공인중개사박미정대표<NA>부산광역시 남구 분포로 145, 제스퀘어동 1144호<NA>
493494부산광역시 남구26290-2019-00077영업중황금VIP공인중개사사무소공인중개사강민성대표<NA>부산광역시 남구 수영로250번길 21-4, 1층<NA>
494495부산광역시 남구26290-2019-00078영업중마로니에공인중개사사무소공인중개사이은정대표051-628-0015부산광역시 남구 수영로325번길 11, 1층 103호<NA>
495496부산광역시 남구26290-2019-00079영업중청구상가공인중개사사무소공인중개사김귀영대표051-611-3500부산광역시 남구 황령대로319번가길 110, 청구아파트 상가 101호<NA>
496497부산광역시 남구26290-2019-00081영업중태화공인중개사사무소공인중개사홍선화대표051-624-1526부산광역시 남구 용소로13번길 107, 101호(대연동)대연3동
497498부산광역시 남구26290-2019-00080영업중한일오피스공인중개사사무소공인중개사이보영대표<NA>부산광역시 남구 자성로 152, 201호(문현동,한일오피스텔)<NA>
498499부산광역시 남구26290-2019-00082영업중행복부동산중개사무소공인중개사문부식대표<NA>부산광역시 남구 홍곡로 27<NA>
499500부산광역시 남구26290-2019-00083영업중대우공인중개사사무소공인중개사조복자대표<NA>부산광역시 남구 우암로 57<NA>