Overview

Dataset statistics

Number of variables7
Number of observations324
Missing cells124
Missing cells (%)5.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.5 KiB
Average record size in memory58.4 B

Variable types

Numeric2
Text5

Dataset

Description여수시 개설등록 신청을 한 개업공인중개사 현황으로 등록번호, 주소, 대표자 성명, 연락처 등을 표기하여 무등록 중개행위 예방으로 건전한 부동산 거래 문화 정착을 위한 제공자료입니다
Author전라남도 여수시
URLhttps://www.data.go.kr/data/3079910/fileData.do

Alerts

전화번호_팩스번호 has 124 (38.3%) missing valuesMissing
연번 has unique valuesUnique
등록번호 has unique valuesUnique
상호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:34:48.637949
Analysis finished2023-12-12 23:34:49.590519
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct324
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.5
Minimum1
Maximum324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-13T08:34:49.657801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.15
Q181.75
median162.5
Q3243.25
95-th percentile307.85
Maximum324
Range323
Interquartile range (IQR)161.5

Descriptive statistics

Standard deviation93.67497
Coefficient of variation (CV)0.57646135
Kurtosis-1.2
Mean162.5
Median Absolute Deviation (MAD)81
Skewness0
Sum52650
Variance8775
MonotonicityStrictly increasing
2023-12-13T08:34:49.792773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
205 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
220 1
 
0.3%
219 1
 
0.3%
218 1
 
0.3%
217 1
 
0.3%
216 1
 
0.3%
Other values (314) 314
96.9%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
324 1
0.3%
323 1
0.3%
322 1
0.3%
321 1
0.3%
320 1
0.3%
319 1
0.3%
318 1
0.3%
317 1
0.3%
316 1
0.3%
315 1
0.3%

우편번호
Real number (ℝ)

Distinct91
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59518.133
Minimum5967
Maximum59796
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-13T08:34:49.954461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5967
5-th percentile59632
Q159662
median59687
Q359714.5
95-th percentile59792
Maximum59796
Range53829
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation2989.132
Coefficient of variation (CV)0.050222207
Kurtosis321.88144
Mean59518.133
Median Absolute Deviation (MAD)25
Skewness-17.914812
Sum19283875
Variance8934909.9
MonotonicityNot monotonic
2023-12-13T08:34:50.146312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59655 23
 
7.1%
59691 22
 
6.8%
59792 19
 
5.9%
59723 13
 
4.0%
59672 10
 
3.1%
59640 9
 
2.8%
59769 9
 
2.8%
59674 9
 
2.8%
59681 8
 
2.5%
59693 8
 
2.5%
Other values (81) 194
59.9%
ValueCountFrequency (%)
5967 1
 
0.3%
56737 1
 
0.3%
59601 1
 
0.3%
59602 5
1.5%
59622 1
 
0.3%
59624 2
 
0.6%
59625 1
 
0.3%
59628 2
 
0.6%
59630 1
 
0.3%
59632 6
1.9%
ValueCountFrequency (%)
59796 1
 
0.3%
59792 19
5.9%
59786 1
 
0.3%
59779 2
 
0.6%
59776 1
 
0.3%
59769 9
2.8%
59765 1
 
0.3%
59762 1
 
0.3%
59761 5
 
1.5%
59760 3
 
0.9%

등록번호
Text

UNIQUE 

Distinct324
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T08:34:50.365957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length14.151235
Min length8

Characters and Unicode

Total characters4585
Distinct characters12
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

Unique324 ?
Unique (%)100.0%

Sample

1st row가4130-44
2nd row가3615-76
3rd row가4110-195
4th row가4110-565
5th row가4110-581
ValueCountFrequency (%)
가4130-44 1
 
0.3%
46130-2019-00016 1
 
0.3%
46130-2019-00046 1
 
0.3%
46130-2019-00043 1
 
0.3%
46130-2019-00042 1
 
0.3%
46130-2019-00041 1
 
0.3%
46130-2019-00039 1
 
0.3%
46130-2019-00037 1
 
0.3%
46130-2019-00036 1
 
0.3%
46130-2019-00047 1
 
0.3%
Other values (314) 314
96.9%
2023-12-13T08:34:50.729513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1425
31.1%
1 669
14.6%
- 563
 
12.3%
2 418
 
9.1%
4 404
 
8.8%
6 336
 
7.3%
3 324
 
7.1%
5 116
 
2.5%
가 85
 
1.9%
8 85
 
1.9%
Other values (2) 160
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3937
85.9%
Dash Punctuation 563
 
12.3%
Other Letter 85
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1425
36.2%
1 669
17.0%
2 418
 
10.6%
4 404
 
10.3%
6 336
 
8.5%
3 324
 
8.2%
5 116
 
2.9%
8 85
 
2.2%
7 83
 
2.1%
9 77
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 563
100.0%
Other Letter
ValueCountFrequency (%)
가 85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4500
98.1%
Hangul 85
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1425
31.7%
1 669
14.9%
- 563
 
12.5%
2 418
 
9.3%
4 404
 
9.0%
6 336
 
7.5%
3 324
 
7.2%
5 116
 
2.6%
8 85
 
1.9%
7 83
 
1.8%
Hangul
ValueCountFrequency (%)
가 85
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4500
98.1%
Hangul 85
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1425
31.7%
1 669
14.9%
- 563
 
12.5%
2 418
 
9.3%
4 404
 
9.0%
6 336
 
7.5%
3 324
 
7.2%
5 116
 
2.6%
8 85
 
1.9%
7 83
 
1.8%
Hangul
ValueCountFrequency (%)
가 85
100.0%

성명(대표자)
Text

Distinct321
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T08:34:51.084554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9783951
Min length2

Characters and Unicode

Total characters965
Distinct characters157
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique318 ?
Unique (%)98.1%

Sample

1st row장정섭
2nd row김봉수
3rd row최평조
4th row이지윤
5th row신선희
ValueCountFrequency (%)
김일환 2
 
0.6%
박선희 2
 
0.6%
서은정 2
 
0.6%
정광희 1
 
0.3%
강정호 1
 
0.3%
권 1
 
0.3%
유정화 1
 
0.3%
전선옥 1
 
0.3%
강재영 1
 
0.3%
김정곤 1
 
0.3%
Other values (312) 312
96.0%
2023-12-13T08:34:51.563008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 82
 
8.5%
정 55
 
5.7%
이 41
 
4.2%
박 30
 
3.1%
영 25
 
2.6%
희 20
 
2.1%
미 20
 
2.1%
숙 18
 
1.9%
최 18
 
1.9%
경 18
 
1.9%
Other values (147) 638
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 964
99.9%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 82
 
8.5%
정 55
 
5.7%
이 41
 
4.3%
박 30
 
3.1%
영 25
 
2.6%
희 20
 
2.1%
미 20
 
2.1%
숙 18
 
1.9%
최 18
 
1.9%
경 18
 
1.9%
Other values (146) 637
66.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 964
99.9%
Common 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 82
 
8.5%
정 55
 
5.7%
이 41
 
4.3%
박 30
 
3.1%
영 25
 
2.6%
희 20
 
2.1%
미 20
 
2.1%
숙 18
 
1.9%
최 18
 
1.9%
경 18
 
1.9%
Other values (146) 637
66.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 964
99.9%
ASCII 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 82
 
8.5%
정 55
 
5.7%
이 41
 
4.3%
박 30
 
3.1%
영 25
 
2.6%
희 20
 
2.1%
미 20
 
2.1%
숙 18
 
1.9%
최 18
 
1.9%
경 18
 
1.9%
Other values (146) 637
66.1%
ASCII
ValueCountFrequency (%)
1
100.0%

상호
Text

UNIQUE 

Distinct324
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T08:34:51.791173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length11.188272
Min length8

Characters and Unicode

Total characters3625
Distinct characters282
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique324 ?
Unique (%)100.0%

Sample

1st row경성부동산중개사무소
2nd row부일 부동산중개인
3rd row호남부동산중개사무소
4th row대광공인중개사사무소
5th rowLBA신선 공인중개사사무소
ValueCountFrequency (%)
공인중개사사무소 14
 
4.0%
사무소 5
 
1.4%
공인중개사 2
 
0.6%
여수대림공인중개사사무소 1
 
0.3%
새웅천공인중개사사무소 1
 
0.3%
한국공인중개사사무소 1
 
0.3%
여수부동산선박공인중개사무소 1
 
0.3%
부동산카페공인중개사사무소 1
 
0.3%
행복부동산공인중개사사무소 1
 
0.3%
동양n공인중개사사무소 1
 
0.3%
Other values (322) 322
92.0%
2023-12-13T08:34:52.151227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 624
17.2%
중 327
 
9.0%
개 325
 
9.0%
소 324
 
8.9%
무 321
 
8.9%
인 309
 
8.5%
공 306
 
8.4%
산 69
 
1.9%
동 66
 
1.8%
부 63
 
1.7%
Other values (272) 891
24.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3554
98.0%
Space Separator 26
 
0.7%
Uppercase Letter 16
 
0.4%
Lowercase Letter 14
 
0.4%
Decimal Number 11
 
0.3%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 624
17.6%
중 327
 
9.2%
개 325
 
9.1%
소 324
 
9.1%
무 321
 
9.0%
인 309
 
8.7%
공 306
 
8.6%
산 69
 
1.9%
동 66
 
1.9%
부 63
 
1.8%
Other values (243) 820
23.1%
Uppercase Letter
ValueCountFrequency (%)
K 3
18.8%
S 2
12.5%
L 2
12.5%
T 2
12.5%
N 1
 
6.2%
J 1
 
6.2%
G 1
 
6.2%
D 1
 
6.2%
A 1
 
6.2%
I 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 3
21.4%
y 2
14.3%
o 2
14.3%
h 2
14.3%
s 1
 
7.1%
t 1
 
7.1%
f 1
 
7.1%
r 1
 
7.1%
u 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 3
27.3%
6 2
18.2%
3 2
18.2%
5 2
18.2%
2 1
 
9.1%
4 1
 
9.1%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3550
97.9%
Common 41
 
1.1%
Latin 30
 
0.8%
Han 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 624
17.6%
중 327
9.2%
개 325
 
9.2%
소 324
 
9.1%
무 321
 
9.0%
인 309
 
8.7%
공 306
 
8.6%
산 69
 
1.9%
동 66
 
1.9%
부 63
 
1.8%
Other values (239) 816
23.0%
Latin
ValueCountFrequency (%)
e 3
 
10.0%
K 3
 
10.0%
S 2
 
6.7%
y 2
 
6.7%
L 2
 
6.7%
o 2
 
6.7%
h 2
 
6.7%
T 2
 
6.7%
s 1
 
3.3%
N 1
 
3.3%
Other values (10) 10
33.3%
Common
ValueCountFrequency (%)
26
63.4%
1 3
 
7.3%
6 2
 
4.9%
3 2
 
4.9%
5 2
 
4.9%
( 2
 
4.9%
) 2
 
4.9%
2 1
 
2.4%
4 1
 
2.4%
Han
ValueCountFrequency (%)
信 1
25.0%
正 1
25.0%
竹 1
25.0%
山 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3550
97.9%
ASCII 71
 
2.0%
CJK 4
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 624
17.6%
중 327
9.2%
개 325
 
9.2%
소 324
 
9.1%
무 321
 
9.0%
인 309
 
8.7%
공 306
 
8.6%
산 69
 
1.9%
동 66
 
1.9%
부 63
 
1.8%
Other values (239) 816
23.0%
ASCII
ValueCountFrequency (%)
26
36.6%
e 3
 
4.2%
K 3
 
4.2%
1 3
 
4.2%
S 2
 
2.8%
6 2
 
2.8%
3 2
 
2.8%
5 2
 
2.8%
y 2
 
2.8%
L 2
 
2.8%
Other values (19) 24
33.8%
CJK
ValueCountFrequency (%)
信 1
25.0%
正 1
25.0%
竹 1
25.0%
山 1
25.0%

소재지
Text

Distinct308
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T08:34:52.400452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length19.416667
Min length13

Characters and Unicode

Total characters6291
Distinct characters146
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

Unique292 ?
Unique (%)90.1%

Sample

1st row여수시 신월로 803-2, 2층(서교동)
2nd row여수시 시청로 34(학동)
3rd row여수시 광무1길 7(광무동)
4th row여수시 봉계대곡길 70, 상가동 207호(봉계동)
5th row여수시 신월로 699-1(국동)
ValueCountFrequency (%)
여수시 325
26.6%
소라면 25
 
2.0%
상가동 18
 
1.5%
신월로 17
 
1.4%
도원로 15
 
1.2%
죽림중앙로 14
 
1.1%
쌍봉로 13
 
1.1%
무선로 13
 
1.1%
웅천로 13
 
1.1%
웅천남8로 13
 
1.1%
Other values (484) 758
61.9%
2023-12-13T08:34:52.791247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
910
 
14.5%
여 358
 
5.7%
수 353
 
5.6%
동 341
 
5.4%
시 339
 
5.4%
1 297
 
4.7%
( 279
 
4.4%
) 279
 
4.4%
로 223
 
3.5%
2 199
 
3.2%
Other values (136) 2713
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3350
53.3%
Decimal Number 1247
 
19.8%
Space Separator 910
 
14.5%
Open Punctuation 279
 
4.4%
Close Punctuation 279
 
4.4%
Other Punctuation 147
 
2.3%
Dash Punctuation 71
 
1.1%
Uppercase Letter 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 358
 
10.7%
수 353
 
10.5%
동 341
 
10.2%
시 339
 
10.1%
로 223
 
6.7%
웅 106
 
3.2%
길 101
 
3.0%
천 97
 
2.9%
호 94
 
2.8%
학 58
 
1.7%
Other values (116) 1280
38.2%
Decimal Number
ValueCountFrequency (%)
1 297
23.8%
2 199
16.0%
3 155
12.4%
0 117
 
9.4%
4 100
 
8.0%
6 93
 
7.5%
5 87
 
7.0%
7 74
 
5.9%
8 72
 
5.8%
9 53
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 132
89.8%
/ 13
 
8.8%
@ 2
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
A 5
62.5%
C 2
 
25.0%
B 1
 
12.5%
Space Separator
ValueCountFrequency (%)
910
100.0%
Open Punctuation
ValueCountFrequency (%)
( 279
100.0%
Close Punctuation
ValueCountFrequency (%)
) 279
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3350
53.3%
Common 2933
46.6%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 358
 
10.7%
수 353
 
10.5%
동 341
 
10.2%
시 339
 
10.1%
로 223
 
6.7%
웅 106
 
3.2%
길 101
 
3.0%
천 97
 
2.9%
호 94
 
2.8%
학 58
 
1.7%
Other values (116) 1280
38.2%
Common
ValueCountFrequency (%)
910
31.0%
1 297
 
10.1%
( 279
 
9.5%
) 279
 
9.5%
2 199
 
6.8%
3 155
 
5.3%
, 132
 
4.5%
0 117
 
4.0%
4 100
 
3.4%
6 93
 
3.2%
Other values (7) 372
12.7%
Latin
ValueCountFrequency (%)
A 5
62.5%
C 2
 
25.0%
B 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3350
53.3%
ASCII 2941
46.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
910
30.9%
1 297
 
10.1%
( 279
 
9.5%
) 279
 
9.5%
2 199
 
6.8%
3 155
 
5.3%
, 132
 
4.5%
0 117
 
4.0%
4 100
 
3.4%
6 93
 
3.2%
Other values (10) 380
12.9%
Hangul
ValueCountFrequency (%)
여 358
 
10.7%
수 353
 
10.5%
동 341
 
10.2%
시 339
 
10.1%
로 223
 
6.7%
웅 106
 
3.2%
길 101
 
3.0%
천 97
 
2.9%
호 94
 
2.8%
학 58
 
1.7%
Other values (116) 1280
38.2%

전화번호_팩스번호
Text

MISSING 

Distinct197
Distinct (%)98.5%
Missing124
Missing (%)38.3%
Memory size2.7 KiB
2023-12-13T08:34:53.043931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length136
Median length12
Mean length13.04
Min length12

Characters and Unicode

Total characters2608
Distinct characters18
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique194 ?
Unique (%)97.0%

Sample

1st row061-685-4984
2nd row061-681-5169
3rd row061-655-2470
4th row061-665-2701
5th row061-643-1518
ValueCountFrequency (%)
061-686-4980 2
 
0.9%
061-681-6111 2
 
0.9%
061-684-7887 2
 
0.9%
061-683-0019,f)061-683-0018 1
 
0.5%
061-666-5700 1
 
0.5%
061-681-5566 1
 
0.5%
061-684-4585 1
 
0.5%
061-683-3800 1
 
0.5%
061-685-7421 1
 
0.5%
061-683-8242 1
 
0.5%
Other values (198) 198
93.8%
2023-12-13T08:34:53.417398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 517
19.8%
- 421
16.1%
0 355
13.6%
1 344
13.2%
8 221
8.5%
5 151
 
5.8%
4 145
 
5.6%
9 133
 
5.1%
2 115
 
4.4%
3 88
 
3.4%
Other values (8) 118
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2144
82.2%
Dash Punctuation 421
 
16.1%
Other Punctuation 20
 
0.8%
Space Separator 11
 
0.4%
Lowercase Letter 6
 
0.2%
Close Punctuation 4
 
0.2%
Open Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 517
24.1%
0 355
16.6%
1 344
16.0%
8 221
10.3%
5 151
 
7.0%
4 145
 
6.8%
9 133
 
6.2%
2 115
 
5.4%
3 88
 
4.1%
7 75
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
f 4
66.7%
a 1
 
16.7%
x 1
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 421
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2602
99.8%
Latin 6
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
6 517
19.9%
- 421
16.2%
0 355
13.6%
1 344
13.2%
8 221
8.5%
5 151
 
5.8%
4 145
 
5.6%
9 133
 
5.1%
2 115
 
4.4%
3 88
 
3.4%
Other values (5) 112
 
4.3%
Latin
ValueCountFrequency (%)
f 4
66.7%
a 1
 
16.7%
x 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2608
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 517
19.8%
- 421
16.1%
0 355
13.6%
1 344
13.2%
8 221
8.5%
5 151
 
5.8%
4 145
 
5.6%
9 133
 
5.1%
2 115
 
4.4%
3 88
 
3.4%
Other values (8) 118
 
4.5%

Interactions

2023-12-13T08:34:49.216331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:49.036005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:49.327188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:49.120345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:34:53.514468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호
연번1.000NaN
우편번호NaN1.000
2023-12-13T08:34:53.615816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호
연번1.0000.018
우편번호0.0181.000

Missing values

2023-12-13T08:34:49.449059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:34:49.549598image/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

연번우편번호등록번호성명(대표자)상호소재지전화번호_팩스번호
0159755가4130-44장정섭경성부동산중개사무소여수시 신월로 803-2, 2층(서교동)061-685-4984
1259677가3615-76김봉수부일 부동산중개인여수시 시청로 34(학동)061-681-5169
2359718가4110-195최평조호남부동산중개사무소여수시 광무1길 7(광무동)061-655-2470
3459632가4110-565이지윤대광공인중개사사무소여수시 봉계대곡길 70, 상가동 207호(봉계동)061-665-2701
4559757가4110-581신선희LBA신선 공인중개사사무소여수시 신월로 699-1(국동)061-643-1518
5659740가4110-587김승훈여수로공인중개사사무소여수시 하멜로 46(종화동)061-665-7300
6759792가4110-566윤남순가나공인중개사사무소여수시 웅천로 90, 상가 114호(웅천동)061-655-0500
7859723가4110-614정세아거명공인중개사사무소여수시 박람회길 61, 상가동 104호 (덕충동, 엑스포힐스테이트1단지)061-665-0166
8959643가4110-356고광연공인중개사 고광연 사무소여수시 화산2길 78 (화장동)061-685-8087
91059679가4110-284강생훈여수대표공인중개사사무소여수시 흥국로 31(학동)061-691-4060
연번우편번호등록번호성명(대표자)상호소재지전화번호_팩스번호
3143155970646130-2021-00018김상권하이공인중개사사무소여수시 여문문화길 62, 2층(문수동)<NA>
3153165964546130-2021-00019김규완비타민공인중개사사무소여수시 무선로 65 (선원동)<NA>
3163175973046130-2021-00020이재삼한결공인중개사사무소여수시 동문로 35(관문동)<NA>
3173185970546130-2021-00022박종윤여수부동산중개사무소여수시 여서로 134, 상가 20/105(여서동)<NA>
3183195968546130-2021-00023심정원다산부동산공인중개사사무소여수시 시전6길 13(신기동)<NA>
3193205969246130-2021-00024서민규비고공인중개사사무소여수시 웅천로 19-9, 105호(웅천동)061-684-7887
3203215965546130-2021-00025김금정for you 부동산공인중개사사무소여수시 소라면 죽림중앙로 30-20061-684-7887
3213225975746130-2021-00026손성원성원공인중개사사무소여수시 신월로 675-2(국동)<NA>
3223235973446130-2021-00027김일환명신공인중개사사무소여수시 충무로 25-2(교동)<NA>
3233245969246130-2021-00028이재욱의주부동산공인중개사사무소여수시 웅천남1로 99, 232동 106(웅천동)<NA>