Overview

Dataset statistics

Number of variables10
Number of observations492
Missing cells2451
Missing cells (%)49.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.0 KiB
Average record size in memory81.3 B

Variable types

Numeric1
Text9

Dataset

Description부산광역시사하구_부동산중개업소현황_20230609
Author부산광역시 사하구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15084207

Alerts

전화번호6 has constant value ""Constant
전화번호1 has 58 (11.8%) missing valuesMissing
전화번호2 has 450 (91.5%) missing valuesMissing
전화번호3 has 473 (96.1%) missing valuesMissing
전화번호4 has 489 (99.4%) missing valuesMissing
전화번호5 has 490 (99.6%) missing valuesMissing
전화번호6 has 491 (99.8%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 08:13:16.150442
Analysis finished2024-04-21 08:13:17.785270
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct492
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean246.5
Minimum1
Maximum492
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-21T17:13:17.924236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.55
Q1123.75
median246.5
Q3369.25
95-th percentile467.45
Maximum492
Range491
Interquartile range (IQR)245.5

Descriptive statistics

Standard deviation142.17243
Coefficient of variation (CV)0.57676442
Kurtosis-1.2
Mean246.5
Median Absolute Deviation (MAD)123
Skewness0
Sum121278
Variance20213
MonotonicityStrictly increasing
2024-04-21T17:13:18.182878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
340 1
 
0.2%
338 1
 
0.2%
337 1
 
0.2%
336 1
 
0.2%
335 1
 
0.2%
334 1
 
0.2%
333 1
 
0.2%
332 1
 
0.2%
331 1
 
0.2%
Other values (482) 482
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 (%)
492 1
0.2%
491 1
0.2%
490 1
0.2%
489 1
0.2%
488 1
0.2%
487 1
0.2%
486 1
0.2%
485 1
0.2%
484 1
0.2%
483 1
0.2%

업소명
Text

Distinct428
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-21T17:13:18.835826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length10
Mean length10.953252
Min length8

Characters and Unicode

Total characters5389
Distinct characters289
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

Unique377 ?
Unique (%)76.6%

Sample

1st row삼진부동산중개인사무소
2nd row다복부동산중개인사무소
3rd row갑을부동산중개인사무소
4th row의령부동산중개인사무소
5th row다대부동산마트부동산중개사무소
ValueCountFrequency (%)
스타공인중개사사무소 4
 
0.8%
자유공인중개사사무소 4
 
0.8%
ok공인중개사사무소 4
 
0.8%
롯데공인중개사사무소 4
 
0.8%
행운공인중개사사무소 3
 
0.6%
한솔공인중개사사무소 3
 
0.6%
삼성공인중개사사무소 3
 
0.6%
대성공인중개사사무소 3
 
0.6%
현대공인중개사사무소 3
 
0.6%
동원공인중개사사무소 2
 
0.4%
Other values (420) 461
93.3%
2024-04-21T17:13:19.744935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 926
17.2%
개 494
9.2%
중 493
9.1%
소 490
9.1%
무 487
9.0%
인 432
 
8.0%
공 427
 
7.9%
동 158
 
2.9%
부 142
 
2.6%
산 141
 
2.6%
Other values (279) 1199
22.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5317
98.7%
Uppercase Letter 32
 
0.6%
Decimal Number 19
 
0.4%
Lowercase Letter 12
 
0.2%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Space Separator 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 926
17.4%
개 494
9.3%
중 493
9.3%
소 490
9.2%
무 487
9.2%
인 432
 
8.1%
공 427
 
8.0%
동 158
 
3.0%
부 142
 
2.7%
산 141
 
2.7%
Other values (252) 1127
21.2%
Uppercase Letter
ValueCountFrequency (%)
K 9
28.1%
S 7
21.9%
O 4
12.5%
T 4
12.5%
W 3
 
9.4%
J 1
 
3.1%
H 1
 
3.1%
E 1
 
3.1%
B 1
 
3.1%
G 1
 
3.1%
Decimal Number
ValueCountFrequency (%)
1 6
31.6%
4 4
21.1%
8 3
15.8%
9 2
 
10.5%
6 1
 
5.3%
5 1
 
5.3%
3 1
 
5.3%
2 1
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 5
41.7%
h 4
33.3%
t 1
 
8.3%
k 1
 
8.3%
s 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5317
98.7%
Latin 44
 
0.8%
Common 28
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 926
17.4%
개 494
9.3%
중 493
9.3%
소 490
9.2%
무 487
9.2%
인 432
 
8.1%
공 427
 
8.0%
동 158
 
3.0%
부 142
 
2.7%
산 141
 
2.7%
Other values (252) 1127
21.2%
Latin
ValueCountFrequency (%)
K 9
20.5%
S 7
15.9%
e 5
11.4%
O 4
9.1%
h 4
9.1%
T 4
9.1%
W 3
 
6.8%
J 1
 
2.3%
H 1
 
2.3%
E 1
 
2.3%
Other values (5) 5
11.4%
Common
ValueCountFrequency (%)
1 6
21.4%
4 4
14.3%
8 3
10.7%
( 3
10.7%
) 3
10.7%
2
 
7.1%
9 2
 
7.1%
- 1
 
3.6%
6 1
 
3.6%
5 1
 
3.6%
Other values (2) 2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5317
98.7%
ASCII 72
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 926
17.4%
개 494
9.3%
중 493
9.3%
소 490
9.2%
무 487
9.2%
인 432
 
8.1%
공 427
 
8.0%
동 158
 
3.0%
부 142
 
2.7%
산 141
 
2.7%
Other values (252) 1127
21.2%
ASCII
ValueCountFrequency (%)
K 9
 
12.5%
S 7
 
9.7%
1 6
 
8.3%
e 5
 
6.9%
4 4
 
5.6%
O 4
 
5.6%
h 4
 
5.6%
T 4
 
5.6%
8 3
 
4.2%
( 3
 
4.2%
Other values (17) 23
31.9%

대표자
Text

Distinct483
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-21T17:13:20.842760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length3
Mean length3.0284553
Min length2

Characters and Unicode

Total characters1490
Distinct characters191
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique477 ?
Unique (%)97.0%

Sample

1st row윤병환
2nd row이병철
3rd row강민남
4th row주광수
5th row이실한
ValueCountFrequency (%)
김정희 5
 
1.0%
김미희 2
 
0.4%
신미라 2
 
0.4%
이영희 2
 
0.4%
이승희 2
 
0.4%
김민정 2
 
0.4%
김진영 1
 
0.2%
박지안 1
 
0.2%
박민철 1
 
0.2%
김용근 1
 
0.2%
Other values (476) 476
96.2%
2024-04-21T17:13:22.156228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 121
 
8.1%
정 80
 
5.4%
이 60
 
4.0%
영 54
 
3.6%
박 52
 
3.5%
희 49
 
3.3%
경 36
 
2.4%
미 34
 
2.3%
숙 30
 
2.0%
현 30
 
2.0%
Other values (181) 944
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1471
98.7%
Lowercase Letter 12
 
0.8%
Uppercase Letter 4
 
0.3%
Space Separator 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 121
 
8.2%
정 80
 
5.4%
이 60
 
4.1%
영 54
 
3.7%
박 52
 
3.5%
희 49
 
3.3%
경 36
 
2.4%
미 34
 
2.3%
숙 30
 
2.0%
현 30
 
2.0%
Other values (168) 925
62.9%
Lowercase Letter
ValueCountFrequency (%)
e 4
33.3%
a 2
16.7%
s 1
 
8.3%
y 1
 
8.3%
u 1
 
8.3%
n 1
 
8.3%
g 1
 
8.3%
w 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
25.0%
C 1
25.0%
S 1
25.0%
H 1
25.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1471
98.7%
Latin 16
 
1.1%
Common 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 121
 
8.2%
정 80
 
5.4%
이 60
 
4.1%
영 54
 
3.7%
박 52
 
3.5%
희 49
 
3.3%
경 36
 
2.4%
미 34
 
2.3%
숙 30
 
2.0%
현 30
 
2.0%
Other values (168) 925
62.9%
Latin
ValueCountFrequency (%)
e 4
25.0%
a 2
12.5%
L 1
 
6.2%
C 1
 
6.2%
s 1
 
6.2%
y 1
 
6.2%
S 1
 
6.2%
u 1
 
6.2%
n 1
 
6.2%
g 1
 
6.2%
Other values (2) 2
12.5%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1471
98.7%
ASCII 19
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 121
 
8.2%
정 80
 
5.4%
이 60
 
4.1%
영 54
 
3.7%
박 52
 
3.5%
희 49
 
3.3%
경 36
 
2.4%
미 34
 
2.3%
숙 30
 
2.0%
현 30
 
2.0%
Other values (168) 925
62.9%
ASCII
ValueCountFrequency (%)
e 4
21.1%
3
15.8%
a 2
10.5%
L 1
 
5.3%
C 1
 
5.3%
s 1
 
5.3%
y 1
 
5.3%
S 1
 
5.3%
u 1
 
5.3%
n 1
 
5.3%
Other values (3) 3
15.8%

전화번호1
Text

MISSING 

Distinct429
Distinct (%)98.8%
Missing58
Missing (%)11.8%
Memory size4.0 KiB
2024-04-21T17:13:22.986999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.997696
Min length11

Characters and Unicode

Total characters5207
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

Unique425 ?
Unique (%)97.9%

Sample

1st row051-203-2222
2nd row051-261-2896
3rd row051-292-9283
4th row051-261-2510
5th row051-206-9688
ValueCountFrequency (%)
051-208-4988 3
 
0.7%
051-261-3113 2
 
0.5%
051-263-9888 2
 
0.5%
051-201-5400 2
 
0.5%
051-293-0077 1
 
0.2%
051-266-6108 1
 
0.2%
051-866-1688 1
 
0.2%
051-203-3736 1
 
0.2%
051-206-8899 1
 
0.2%
051-710-0120 1
 
0.2%
Other values (419) 419
96.5%
2024-04-21T17:13:24.105763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1038
19.9%
- 867
16.7%
5 670
12.9%
1 669
12.8%
2 617
11.8%
6 264
 
5.1%
8 236
 
4.5%
9 236
 
4.5%
3 232
 
4.5%
4 205
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4340
83.3%
Dash Punctuation 867
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1038
23.9%
5 670
15.4%
1 669
15.4%
2 617
14.2%
6 264
 
6.1%
8 236
 
5.4%
9 236
 
5.4%
3 232
 
5.3%
4 205
 
4.7%
7 173
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 867
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5207
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1038
19.9%
- 867
16.7%
5 670
12.9%
1 669
12.8%
2 617
11.8%
6 264
 
5.1%
8 236
 
4.5%
9 236
 
4.5%
3 232
 
4.5%
4 205
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5207
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1038
19.9%
- 867
16.7%
5 670
12.9%
1 669
12.8%
2 617
11.8%
6 264
 
5.1%
8 236
 
4.5%
9 236
 
4.5%
3 232
 
4.5%
4 205
 
3.9%

전화번호2
Text

MISSING 

Distinct42
Distinct (%)100.0%
Missing450
Missing (%)91.5%
Memory size4.0 KiB
2024-04-21T17:13:24.907289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters504
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

Unique42 ?
Unique (%)100.0%

Sample

1st row051-266-2244
2nd row051-204-4800
3rd row051-292-1588
4th row051-292-2114
5th row051-203-9115
ValueCountFrequency (%)
051-202-4200 1
 
2.4%
051-207-9887 1
 
2.4%
051-206-6213 1
 
2.4%
051-203-0242 1
 
2.4%
051-710-5136 1
 
2.4%
051-292-5160 1
 
2.4%
051-203-1473 1
 
2.4%
051-231-1110 1
 
2.4%
051-294-8981 1
 
2.4%
051-204-9991 1
 
2.4%
Other values (32) 32
76.2%
2024-04-21T17:13:26.010053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 97
19.2%
- 84
16.7%
1 77
15.3%
5 63
12.5%
2 62
12.3%
9 25
 
5.0%
3 22
 
4.4%
4 20
 
4.0%
8 20
 
4.0%
6 18
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 420
83.3%
Dash Punctuation 84
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 97
23.1%
1 77
18.3%
5 63
15.0%
2 62
14.8%
9 25
 
6.0%
3 22
 
5.2%
4 20
 
4.8%
8 20
 
4.8%
6 18
 
4.3%
7 16
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 504
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 97
19.2%
- 84
16.7%
1 77
15.3%
5 63
12.5%
2 62
12.3%
9 25
 
5.0%
3 22
 
4.4%
4 20
 
4.0%
8 20
 
4.0%
6 18
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 97
19.2%
- 84
16.7%
1 77
15.3%
5 63
12.5%
2 62
12.3%
9 25
 
5.0%
3 22
 
4.4%
4 20
 
4.0%
8 20
 
4.0%
6 18
 
3.6%

전화번호3
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing473
Missing (%)96.1%
Memory size4.0 KiB
2024-04-21T17:13:26.613196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters228
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

Unique19 ?
Unique (%)100.0%

Sample

1st row051-207-4001
2nd row051-201-3335
3rd row051-291-4900
4th row051-710-5081
5th row051-294-9401
ValueCountFrequency (%)
051-207-4001 1
 
5.3%
051-206-2580 1
 
5.3%
051-202-2055 1
 
5.3%
051-913-8998 1
 
5.3%
051-715-9535 1
 
5.3%
051-710-2588 1
 
5.3%
051-715-5389 1
 
5.3%
051-203-9991 1
 
5.3%
051-294-8982 1
 
5.3%
051-710-5139 1
 
5.3%
Other values (9) 9
47.4%
2024-04-21T17:13:27.464836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41
18.0%
- 38
16.7%
1 36
15.8%
5 35
15.4%
2 20
8.8%
9 20
8.8%
3 11
 
4.8%
8 10
 
4.4%
7 8
 
3.5%
4 7
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190
83.3%
Dash Punctuation 38
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41
21.6%
1 36
18.9%
5 35
18.4%
2 20
10.5%
9 20
10.5%
3 11
 
5.8%
8 10
 
5.3%
7 8
 
4.2%
4 7
 
3.7%
6 2
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 228
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41
18.0%
- 38
16.7%
1 36
15.8%
5 35
15.4%
2 20
8.8%
9 20
8.8%
3 11
 
4.8%
8 10
 
4.4%
7 8
 
3.5%
4 7
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 228
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41
18.0%
- 38
16.7%
1 36
15.8%
5 35
15.4%
2 20
8.8%
9 20
8.8%
3 11
 
4.8%
8 10
 
4.4%
7 8
 
3.5%
4 7
 
3.1%

전화번호4
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing489
Missing (%)99.4%
Memory size4.0 KiB
2024-04-21T17:13:28.003923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters36
Distinct characters9
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

Unique3 ?
Unique (%)100.0%

Sample

1st row051-208-4700
2nd row051-912-8998
3rd row051-292-9022
ValueCountFrequency (%)
051-208-4700 1
33.3%
051-912-8998 1
33.3%
051-292-9022 1
33.3%
2024-04-21T17:13:28.903898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7
19.4%
- 6
16.7%
2 6
16.7%
9 5
13.9%
1 4
11.1%
5 3
8.3%
8 3
8.3%
4 1
 
2.8%
7 1
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
83.3%
Dash Punctuation 6
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7
23.3%
2 6
20.0%
9 5
16.7%
1 4
13.3%
5 3
10.0%
8 3
10.0%
4 1
 
3.3%
7 1
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7
19.4%
- 6
16.7%
2 6
16.7%
9 5
13.9%
1 4
11.1%
5 3
8.3%
8 3
8.3%
4 1
 
2.8%
7 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7
19.4%
- 6
16.7%
2 6
16.7%
9 5
13.9%
1 4
11.1%
5 3
8.3%
8 3
8.3%
4 1
 
2.8%
7 1
 
2.8%

전화번호5
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing490
Missing (%)99.6%
Memory size4.0 KiB
2024-04-21T17:13:29.427576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters24
Distinct characters8
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

Unique2 ?
Unique (%)100.0%

Sample

1st row051-208-2008
2nd row051-293-9022
ValueCountFrequency (%)
051-208-2008 1
50.0%
051-293-9022 1
50.0%
2024-04-21T17:13:30.303970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6
25.0%
2 5
20.8%
- 4
16.7%
5 2
 
8.3%
1 2
 
8.3%
8 2
 
8.3%
9 2
 
8.3%
3 1
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
83.3%
Dash Punctuation 4
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
30.0%
2 5
25.0%
5 2
 
10.0%
1 2
 
10.0%
8 2
 
10.0%
9 2
 
10.0%
3 1
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6
25.0%
2 5
20.8%
- 4
16.7%
5 2
 
8.3%
1 2
 
8.3%
8 2
 
8.3%
9 2
 
8.3%
3 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6
25.0%
2 5
20.8%
- 4
16.7%
5 2
 
8.3%
1 2
 
8.3%
8 2
 
8.3%
9 2
 
8.3%
3 1
 
4.2%

전화번호6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing491
Missing (%)99.8%
Memory size4.0 KiB
2024-04-21T17:13:30.812717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12
Distinct characters7
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

Unique1 ?
Unique (%)100.0%

Sample

1st row051-201-5908
ValueCountFrequency (%)
051-201-5908 1
100.0%
2024-04-21T17:13:31.678407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3
25.0%
5 2
16.7%
1 2
16.7%
- 2
16.7%
2 1
 
8.3%
9 1
 
8.3%
8 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
83.3%
Dash Punctuation 2
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
30.0%
5 2
20.0%
1 2
20.0%
2 1
 
10.0%
9 1
 
10.0%
8 1
 
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
25.0%
5 2
16.7%
1 2
16.7%
- 2
16.7%
2 1
 
8.3%
9 1
 
8.3%
8 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
25.0%
5 2
16.7%
1 2
16.7%
- 2
16.7%
2 1
 
8.3%
9 1
 
8.3%
8 1
 
8.3%

소재지(도로명주소)
Text

Distinct462
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-21T17:13:32.726819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length32.060976
Min length20

Characters and Unicode

Total characters15774
Distinct characters227
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

Unique438 ?
Unique (%)89.0%

Sample

1st row부산광역시 사하구 낙동대로536번길 27 4층(하단동)
2nd row부산광역시 사하구 낙동대로 454 (당리동)
3rd row부산광역시 사하구 다대로 474 상가가동 101호(다대동, 해송아파트)
4th row부산광역시 사하구 낙동남로1373번길 13 105호(하단동)
5th row부산광역시 사하구 다대로 551 1층(다대동)
ValueCountFrequency (%)
부산광역시 492
 
17.7%
사하구 492
 
17.7%
낙동대로 74
 
2.7%
1층(괴정동 55
 
2.0%
다대로 38
 
1.4%
괴정동 34
 
1.2%
괴정로 31
 
1.1%
30
 
1.1%
하신번영로 29
 
1.0%
1층(하단동 24
 
0.9%
Other values (681) 1488
53.4%
2024-04-21T17:13:34.229693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2295
 
14.5%
1 793
 
5.0%
동 759
 
4.8%
하 741
 
4.7%
사 546
 
3.5%
산 514
 
3.3%
구 509
 
3.2%
역 502
 
3.2%
시 501
 
3.2%
부 495
 
3.1%
Other values (217) 8119
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9486
60.1%
Decimal Number 2674
 
17.0%
Space Separator 2295
 
14.5%
Open Punctuation 489
 
3.1%
Close Punctuation 489
 
3.1%
Other Punctuation 258
 
1.6%
Dash Punctuation 44
 
0.3%
Uppercase Letter 36
 
0.2%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 759
 
8.0%
하 741
 
7.8%
사 546
 
5.8%
산 514
 
5.4%
구 509
 
5.4%
역 502
 
5.3%
시 501
 
5.3%
부 495
 
5.2%
광 492
 
5.2%
로 481
 
5.1%
Other values (187) 3946
41.6%
Uppercase Letter
ValueCountFrequency (%)
B 15
41.7%
A 8
22.2%
W 2
 
5.6%
S 2
 
5.6%
H 2
 
5.6%
K 1
 
2.8%
T 1
 
2.8%
R 1
 
2.8%
L 1
 
2.8%
D 1
 
2.8%
Other values (2) 2
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 793
29.7%
2 383
14.3%
0 324
12.1%
3 304
 
11.4%
4 220
 
8.2%
5 171
 
6.4%
6 134
 
5.0%
7 131
 
4.9%
9 121
 
4.5%
8 93
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 253
98.1%
@ 4
 
1.6%
. 1
 
0.4%
Space Separator
ValueCountFrequency (%)
2295
100.0%
Open Punctuation
ValueCountFrequency (%)
( 489
100.0%
Close Punctuation
ValueCountFrequency (%)
) 489
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9486
60.1%
Common 6249
39.6%
Latin 39
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 759
 
8.0%
하 741
 
7.8%
사 546
 
5.8%
산 514
 
5.4%
구 509
 
5.4%
역 502
 
5.3%
시 501
 
5.3%
부 495
 
5.2%
광 492
 
5.2%
로 481
 
5.1%
Other values (187) 3946
41.6%
Common
ValueCountFrequency (%)
2295
36.7%
1 793
 
12.7%
( 489
 
7.8%
) 489
 
7.8%
2 383
 
6.1%
0 324
 
5.2%
3 304
 
4.9%
, 253
 
4.0%
4 220
 
3.5%
5 171
 
2.7%
Other values (7) 528
 
8.4%
Latin
ValueCountFrequency (%)
B 15
38.5%
A 8
20.5%
e 3
 
7.7%
W 2
 
5.1%
S 2
 
5.1%
H 2
 
5.1%
K 1
 
2.6%
T 1
 
2.6%
R 1
 
2.6%
L 1
 
2.6%
Other values (3) 3
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9486
60.1%
ASCII 6288
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2295
36.5%
1 793
 
12.6%
( 489
 
7.8%
) 489
 
7.8%
2 383
 
6.1%
0 324
 
5.2%
3 304
 
4.8%
, 253
 
4.0%
4 220
 
3.5%
5 171
 
2.7%
Other values (20) 567
 
9.0%
Hangul
ValueCountFrequency (%)
동 759
 
8.0%
하 741
 
7.8%
사 546
 
5.8%
산 514
 
5.4%
구 509
 
5.4%
역 502
 
5.3%
시 501
 
5.3%
부 495
 
5.2%
광 492
 
5.2%
로 481
 
5.1%
Other values (187) 3946
41.6%

Interactions

2024-04-21T17:13:16.957421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T17:13:34.489240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전화번호2전화번호3전화번호4전화번호5
연번1.0001.0001.0001.0000.000
전화번호21.0001.0001.0001.0000.000
전화번호31.0001.0001.0001.0000.000
전화번호41.0001.0001.0001.0000.000
전화번호50.0000.0000.0000.0001.000

Missing values

2024-04-21T17:13:17.176571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T17:13:17.442219image/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.
2024-04-21T17:13:17.652222image/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

연번업소명대표자전화번호1전화번호2전화번호3전화번호4전화번호5전화번호6소재지(도로명주소)
01삼진부동산중개인사무소윤병환<NA><NA><NA><NA><NA><NA>부산광역시 사하구 낙동대로536번길 27 4층(하단동)
12다복부동산중개인사무소이병철051-203-2222<NA><NA><NA><NA><NA>부산광역시 사하구 낙동대로 454 (당리동)
23갑을부동산중개인사무소강민남051-261-2896<NA><NA><NA><NA><NA>부산광역시 사하구 다대로 474 상가가동 101호(다대동, 해송아파트)
34의령부동산중개인사무소주광수051-292-9283<NA><NA><NA><NA><NA>부산광역시 사하구 낙동남로1373번길 13 105호(하단동)
45다대부동산마트부동산중개사무소이실한051-261-2510<NA><NA><NA><NA><NA>부산광역시 사하구 다대로 551 1층(다대동)
56다선공인중개사사무소김영부<NA><NA><NA><NA><NA><NA>부산광역시 사하구 다대로 582 1층(다대동, 건영빌딩)
67신우공인중개사사무소하봉주051-206-9688<NA><NA><NA><NA><NA>부산광역시 사하구 낙동대로 261 자유아파트상가 119호(괴정동)
78동남공인중개사사무소유병규051-208-8000<NA><NA><NA><NA><NA>부산광역시 사하구 하신번영로 233 상가 106호(하단동, 가락타운2단지)
89동서공인중개사사무소오이근051-203-0569<NA><NA><NA><NA><NA>부산광역시 사하구 낙동대로 454 (당리동)
910우경공인중개사사무소이민자051-261-5344<NA><NA><NA><NA><NA>부산광역시 사하구 다대로 617 상가106호(다대동, 자유아파트)
연번업소명대표자전화번호1전화번호2전화번호3전화번호4전화번호5전화번호6소재지(도로명주소)
482483엘림부동산중개사무소심정훈<NA><NA><NA><NA><NA><NA>부산광역시 사하구 낙동대로 159 , 2층(괴정동)
483484낫개부동산공인중개사사무소김기영051-264-1119<NA><NA><NA><NA><NA>부산광역시 사하구 다대로 397 , 1층(다대동)
484485뉴알파공인중개사사무소김동한<NA><NA><NA><NA><NA><NA>부산광역시 사하구 낙동대로 519 ,1층(하단동)
485486더블루원공인중개사사무소정의성051-987-3233<NA><NA><NA><NA><NA>부산광역시 사하구 낙동대로 484 , 3층(하단동)
486487하나블루공인중개사사무소신수미051-294-0240<NA><NA><NA><NA><NA>부산광역시 사하구 낙동대로 484 , 3층(하단동)
487488신평장림산업단지관리공단 부동산중개사무소김광규051-205-0209<NA><NA><NA><NA><NA>부산광역시 사하구 신산로 169 ,2층(신평동)
488489(주)일오팔팔부동산중개법인김경례051-266-1588<NA><NA><NA><NA><NA>부산광역시 사하구 하신중앙로54번길 27 1층(신평동)
489490(주)뉴데일리부동산중개법인송경환<NA><NA><NA><NA><NA><NA>부산광역시 사하구 장평로 160 (장림동)
490491코오롱부동산중개법인주식회사배은주051-294-7676<NA><NA><NA><NA><NA>부산광역시 사하구 신산북로 45 1층(신평동)
491492(주)올집종합서비스부동산중개박준석051-204-7667051-271-7664<NA><NA><NA><NA>부산광역시 사하구 장림번영로104번길 10 113호(장림동,사하장림역스마트더블유아파트)