Overview

Dataset statistics

Number of variables5
Number of observations398
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.1 KiB
Average record size in memory41.3 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description전라남도 시군별 소독업체 현황 자료입니다.(영업신고일, 업소명, 사무실 소재지, 데이터 기준일 등의 정보 제공)
Author전라남도
URLhttps://www.data.go.kr/data/15073267/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:15:11.838764
Analysis finished2023-12-13 00:15:12.358241
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct398
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean199.5
Minimum1
Maximum398
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-13T09:15:12.413279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.85
Q1100.25
median199.5
Q3298.75
95-th percentile378.15
Maximum398
Range397
Interquartile range (IQR)198.5

Descriptive statistics

Standard deviation115.03695
Coefficient of variation (CV)0.57662632
Kurtosis-1.2
Mean199.5
Median Absolute Deviation (MAD)99.5
Skewness0
Sum79401
Variance13233.5
MonotonicityStrictly increasing
2023-12-13T09:15:12.518583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
275 1
 
0.3%
273 1
 
0.3%
272 1
 
0.3%
271 1
 
0.3%
270 1
 
0.3%
269 1
 
0.3%
268 1
 
0.3%
267 1
 
0.3%
266 1
 
0.3%
Other values (388) 388
97.5%
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 (%)
398 1
0.3%
397 1
0.3%
396 1
0.3%
395 1
0.3%
394 1
0.3%
393 1
0.3%
392 1
0.3%
391 1
0.3%
390 1
0.3%
389 1
0.3%

영업신고일
Text

Distinct361
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-13T09:15:12.782729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9924623
Min length9

Characters and Unicode

Total characters3977
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

Unique328 ?
Unique (%)82.4%

Sample

1st row1995-05-10
2nd row1998-04-10
3rd row2003-07-29
4th row2005-02-15
5th row2005-04-14
ValueCountFrequency (%)
2020-06-05 3
 
0.8%
2020-09-10 3
 
0.8%
2018-11-06 3
 
0.8%
2020-07-13 3
 
0.8%
2016-05-10 2
 
0.5%
2020-05-11 2
 
0.5%
2020-07-30 2
 
0.5%
2018-12-18 2
 
0.5%
2020-01-31 2
 
0.5%
2017-01-17 2
 
0.5%
Other values (351) 374
94.0%
2023-12-13T09:15:13.128992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1045
26.3%
- 798
20.1%
2 739
18.6%
1 582
14.6%
9 145
 
3.6%
3 129
 
3.2%
4 112
 
2.8%
7 111
 
2.8%
8 111
 
2.8%
6 106
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3179
79.9%
Dash Punctuation 798
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1045
32.9%
2 739
23.2%
1 582
18.3%
9 145
 
4.6%
3 129
 
4.1%
4 112
 
3.5%
7 111
 
3.5%
8 111
 
3.5%
6 106
 
3.3%
5 99
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 798
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3977
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1045
26.3%
- 798
20.1%
2 739
18.6%
1 582
14.6%
9 145
 
3.6%
3 129
 
3.2%
4 112
 
2.8%
7 111
 
2.8%
8 111
 
2.8%
6 106
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1045
26.3%
- 798
20.1%
2 739
18.6%
1 582
14.6%
9 145
 
3.6%
3 129
 
3.2%
4 112
 
2.8%
7 111
 
2.8%
8 111
 
2.8%
6 106
 
2.7%

업소명
Text

Distinct394
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-13T09:15:13.342347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length7.2085427
Min length2

Characters and Unicode

Total characters2869
Distinct characters332
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique390 ?
Unique (%)98.0%

Sample

1st row(주)서한산업개발
2nd row(유)유달환경
3rd row(유)미래
4th row대신환경
5th row(유)신안용역
ValueCountFrequency (%)
주식회사 30
 
6.0%
유한회사 14
 
2.8%
유 3
 
0.6%
한국방역 2
 
0.4%
주)세스코 2
 
0.4%
주)세이프코리아 2
 
0.4%
그린라인 2
 
0.4%
영농조합법인 2
 
0.4%
청소박사 2
 
0.4%
119 2
 
0.4%
Other values (425) 439
87.8%
2023-12-13T09:15:13.651261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 144
 
5.0%
( 137
 
4.8%
주 135
 
4.7%
103
 
3.6%
사 95
 
3.3%
유 68
 
2.4%
경 64
 
2.2%
환 62
 
2.2%
업 57
 
2.0%
역 52
 
1.8%
Other values (322) 1952
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2420
84.3%
Close Punctuation 144
 
5.0%
Open Punctuation 137
 
4.8%
Space Separator 103
 
3.6%
Uppercase Letter 26
 
0.9%
Decimal Number 18
 
0.6%
Lowercase Letter 9
 
0.3%
Other Symbol 8
 
0.3%
Other Punctuation 3
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 135
 
5.6%
사 95
 
3.9%
유 68
 
2.8%
경 64
 
2.6%
환 62
 
2.6%
업 57
 
2.4%
역 52
 
2.1%
회 52
 
2.1%
린 51
 
2.1%
스 44
 
1.8%
Other values (287) 1740
71.9%
Uppercase Letter
ValueCountFrequency (%)
M 3
11.5%
O 3
11.5%
S 3
11.5%
T 2
 
7.7%
H 2
 
7.7%
R 2
 
7.7%
F 2
 
7.7%
P 1
 
3.8%
G 1
 
3.8%
J 1
 
3.8%
Other values (6) 6
23.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
a 2
22.2%
r 1
11.1%
t 1
11.1%
s 1
11.1%
n 1
11.1%
l 1
11.1%
Decimal Number
ValueCountFrequency (%)
1 8
44.4%
9 3
 
16.7%
5 3
 
16.7%
0 2
 
11.1%
6 1
 
5.6%
3 1
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 144
100.0%
Open Punctuation
ValueCountFrequency (%)
( 137
100.0%
Space Separator
ValueCountFrequency (%)
103
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 8
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2428
84.6%
Common 406
 
14.2%
Latin 35
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 135
 
5.6%
사 95
 
3.9%
유 68
 
2.8%
경 64
 
2.6%
환 62
 
2.6%
업 57
 
2.3%
역 52
 
2.1%
회 52
 
2.1%
린 51
 
2.1%
스 44
 
1.8%
Other values (288) 1748
72.0%
Latin
ValueCountFrequency (%)
M 3
 
8.6%
O 3
 
8.6%
S 3
 
8.6%
T 2
 
5.7%
e 2
 
5.7%
a 2
 
5.7%
H 2
 
5.7%
R 2
 
5.7%
F 2
 
5.7%
P 1
 
2.9%
Other values (13) 13
37.1%
Common
ValueCountFrequency (%)
) 144
35.5%
( 137
33.7%
103
25.4%
1 8
 
2.0%
& 3
 
0.7%
9 3
 
0.7%
5 3
 
0.7%
0 2
 
0.5%
- 1
 
0.2%
6 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2420
84.3%
ASCII 441
 
15.4%
None 8
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 144
32.7%
( 137
31.1%
103
23.4%
1 8
 
1.8%
M 3
 
0.7%
O 3
 
0.7%
S 3
 
0.7%
& 3
 
0.7%
9 3
 
0.7%
5 3
 
0.7%
Other values (24) 31
 
7.0%
Hangul
ValueCountFrequency (%)
주 135
 
5.6%
사 95
 
3.9%
유 68
 
2.8%
경 64
 
2.6%
환 62
 
2.6%
업 57
 
2.4%
역 52
 
2.1%
회 52
 
2.1%
린 51
 
2.1%
스 44
 
1.8%
Other values (287) 1740
71.9%
None
ValueCountFrequency (%)
㈜ 8
100.0%

사무실 소재지
Text

Distinct387
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-13T09:15:13.949665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length36
Mean length23.570352
Min length11

Characters and Unicode

Total characters9381
Distinct characters291
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 (%)94.7%

Sample

1st row 목포시 원형서로 42 (상동)
2nd row 목포시 송림로 41 (용해동)
3rd row 목포시 산정로 87-3 (산정동)
4th row 목포시 산정로150번길 17 (산정동)
5th row 목포시 비파로124번길 14-1 (상동)
ValueCountFrequency (%)
전라남도 271
 
12.8%
순천시 89
 
4.2%
여수시 64
 
3.0%
광양시 52
 
2.4%
목포시 49
 
2.3%
1층 46
 
2.2%
2층 45
 
2.1%
전남 40
 
1.9%
나주시 37
 
1.7%
광양읍 22
 
1.0%
Other values (795) 1410
66.4%
2023-12-13T09:15:14.373364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1785
 
19.0%
남 371
 
4.0%
1 366
 
3.9%
전 319
 
3.4%
시 298
 
3.2%
도 295
 
3.1%
동 285
 
3.0%
라 273
 
2.9%
2 258
 
2.8%
( 243
 
2.6%
Other values (281) 4888
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5384
57.4%
Space Separator 1785
 
19.0%
Decimal Number 1425
 
15.2%
Open Punctuation 243
 
2.6%
Close Punctuation 243
 
2.6%
Other Punctuation 174
 
1.9%
Dash Punctuation 119
 
1.3%
Uppercase Letter 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 371
 
6.9%
전 319
 
5.9%
시 298
 
5.5%
도 295
 
5.5%
동 285
 
5.3%
라 273
 
5.1%
길 213
 
4.0%
로 208
 
3.9%
층 127
 
2.4%
순 117
 
2.2%
Other values (259) 2878
53.5%
Decimal Number
ValueCountFrequency (%)
1 366
25.7%
2 258
18.1%
3 182
12.8%
4 129
 
9.1%
6 102
 
7.2%
0 97
 
6.8%
5 92
 
6.5%
8 73
 
5.1%
7 69
 
4.8%
9 57
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
25.0%
T 1
12.5%
K 1
12.5%
S 1
12.5%
P 1
12.5%
A 1
12.5%
R 1
12.5%
Space Separator
ValueCountFrequency (%)
1785
100.0%
Open Punctuation
ValueCountFrequency (%)
( 243
100.0%
Close Punctuation
ValueCountFrequency (%)
) 243
100.0%
Other Punctuation
ValueCountFrequency (%)
, 174
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 119
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5384
57.4%
Common 3989
42.5%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 371
 
6.9%
전 319
 
5.9%
시 298
 
5.5%
도 295
 
5.5%
동 285
 
5.3%
라 273
 
5.1%
길 213
 
4.0%
로 208
 
3.9%
층 127
 
2.4%
순 117
 
2.2%
Other values (259) 2878
53.5%
Common
ValueCountFrequency (%)
1785
44.7%
1 366
 
9.2%
2 258
 
6.5%
( 243
 
6.1%
) 243
 
6.1%
3 182
 
4.6%
, 174
 
4.4%
4 129
 
3.2%
- 119
 
3.0%
6 102
 
2.6%
Other values (5) 388
 
9.7%
Latin
ValueCountFrequency (%)
B 2
25.0%
T 1
12.5%
K 1
12.5%
S 1
12.5%
P 1
12.5%
A 1
12.5%
R 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5384
57.4%
ASCII 3997
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1785
44.7%
1 366
 
9.2%
2 258
 
6.5%
( 243
 
6.1%
) 243
 
6.1%
3 182
 
4.6%
, 174
 
4.4%
4 129
 
3.2%
- 119
 
3.0%
6 102
 
2.6%
Other values (12) 396
 
9.9%
Hangul
ValueCountFrequency (%)
남 371
 
6.9%
전 319
 
5.9%
시 298
 
5.5%
도 295
 
5.5%
동 285
 
5.3%
라 273
 
5.1%
길 213
 
4.0%
로 208
 
3.9%
층 127
 
2.4%
순 117
 
2.2%
Other values (259) 2878
53.5%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2020-09-30
398 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-09-30
2nd row2020-09-30
3rd row2020-09-30
4th row2020-09-30
5th row2020-09-30

Common Values

ValueCountFrequency (%)
2020-09-30 398
100.0%

Length

2023-12-13T09:15:14.479977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:15:14.546411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-09-30 398
100.0%

Interactions

2023-12-13T09:15:12.161067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T09:15:12.258103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:15:12.329667image/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

연번영업신고일업소명사무실 소재지데이터기준일
011995-05-10(주)서한산업개발목포시 원형서로 42 (상동)2020-09-30
121998-04-10(유)유달환경목포시 송림로 41 (용해동)2020-09-30
232003-07-29(유)미래목포시 산정로 87-3 (산정동)2020-09-30
342005-02-15대신환경목포시 산정로150번길 17 (산정동)2020-09-30
452005-04-14(유)신안용역목포시 비파로124번길 14-1 (상동)2020-09-30
562005-05-27유한회사 에코피아목포시 호남로52번길 7, 2층 (창평동)2020-09-30
672006-06-14(유)금강종합산업목포시 양을로 246 (용해동)2020-09-30
782006-06-28유달종합관리목포시 입암로4번길 4-1 (상동)2020-09-30
892007-03-22(유)남도산업목포시 청호로220번길 24 (산정동)2020-09-30
9102009-03-13(주)캐치크린목포시 수문로83번길 1 (북교동)2020-09-30
연번영업신고일업소명사무실 소재지데이터기준일
3883892020-09-10전남장성지역자활센터(멀티그린)장성군 장성읍 영천로 2122020-09-30
3893902020-09-22세프로장성군 장성읍 매화6길 8, 1층2020-09-30
3903912004-07-16그린종합방역전라남도 완도군 완도읍 청해진남로39번길 9-12020-09-30
3913922008-04-10제일소독환경공사전라남도 완도군 군외면 원동1길 262020-09-30
3923932013-03-07수세미청소용역전라남도 완도군 완도읍 청해진서로 823-372020-09-30
3933942014-05-02새하얀청소용역전라남도 완도군 완도읍 군내11번길 24-102020-09-30
3943952015-02-25맑고고운세상전라남도 완도군 완도읍 청해진남로 44-12020-09-30
3953962020-02-14주)이레워터전라남도 완도군 완도읍 청해진남로 32-12020-09-30
3963972018-12-18두성재단전남진도지역자활센터전남 진도군 진도읍 공설운동장길 14-82020-09-30
3973982014-08-01신안씨엔에스전라남도 신안군 압해읍 압해로 8592020-09-30