Overview

Dataset statistics

Number of variables6
Number of observations77
Missing cells5
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory51.7 B

Variable types

Text3
Numeric2
DateTime1

Dataset

Description제주특별자치도 서귀포시 관내에 등록된 농약판매업체 현황에 관한 데이터로 상호, 주소, 전화번호 등 정보를 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/15017283/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
전화번호 has 5 (6.5%) missing valuesMissing
상호 has unique valuesUnique
도로명 주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:15:22.037914
Analysis finished2023-12-12 00:15:22.882976
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-12T09:15:23.023404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length10.415584
Min length4

Characters and Unicode

Total characters802
Distinct characters115
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)100.0%

Sample

1st row강남농약사
2nd row강정새마을금고
3rd row남원농업협동조합
4th row남원농업협동조합신흥2리지점
5th row남원농업협동조합신흥지점
ValueCountFrequency (%)
강남농약사 1
 
1.2%
주식회사 1
 
1.2%
제주아그로 1
 
1.2%
제주베스트상사 1
 
1.2%
제주남원동부새마을금고 1
 
1.2%
제주감귤농업협동조합표선지점 1
 
1.2%
제주감귤농업협동조합중문지점 1
 
1.2%
제주감귤농업협동조합위미지점 1
 
1.2%
제주감귤농업협동조합안덕지점 1
 
1.2%
위미농업협동조합하례2리지점 1
 
1.2%
Other values (72) 72
87.8%
2023-12-12T09:15:23.388667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 51
 
6.4%
농 50
 
6.2%
협 48
 
6.0%
조 46
 
5.7%
합 45
 
5.6%
업 41
 
5.1%
지 39
 
4.9%
점 34
 
4.2%
주 18
 
2.2%
제 16
 
2.0%
Other values (105) 414
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 792
98.8%
Space Separator 5
 
0.6%
Decimal Number 3
 
0.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 51
 
6.4%
농 50
 
6.3%
협 48
 
6.1%
조 46
 
5.8%
합 45
 
5.7%
업 41
 
5.2%
지 39
 
4.9%
점 34
 
4.3%
주 18
 
2.3%
제 16
 
2.0%
Other values (100) 404
51.0%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 792
98.8%
Common 10
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 51
 
6.4%
농 50
 
6.3%
협 48
 
6.1%
조 46
 
5.8%
합 45
 
5.7%
업 41
 
5.2%
지 39
 
4.9%
점 34
 
4.3%
주 18
 
2.3%
제 16
 
2.0%
Other values (100) 404
51.0%
Common
ValueCountFrequency (%)
5
50.0%
2 2
 
20.0%
( 1
 
10.0%
) 1
 
10.0%
1 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 792
98.8%
ASCII 10
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 51
 
6.4%
농 50
 
6.3%
협 48
 
6.1%
조 46
 
5.8%
합 45
 
5.7%
업 41
 
5.2%
지 39
 
4.9%
점 34
 
4.3%
주 18
 
2.3%
제 16
 
2.0%
Other values (100) 404
51.0%
ASCII
ValueCountFrequency (%)
5
50.0%
2 2
 
20.0%
( 1
 
10.0%
) 1
 
10.0%
1 1
 
10.0%

도로명 주소
Text

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-12T09:15:23.702628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length23.519481
Min length19

Characters and Unicode

Total characters1811
Distinct characters95
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 서귀포시 남원읍 태위로 211
2nd row제주특별자치도 서귀포시 이어도로 567
3rd row제주특별자치도 서귀포시 남원읍 남조로 57
4th row제주특별자치도 서귀포시 남원읍 중산간동로 5804
5th row제주특별자치도 서귀포시 남원읍 신흥로 11
ValueCountFrequency (%)
서귀포시 79
22.2%
제주특별자치도 77
21.6%
남원읍 19
 
5.3%
태위로 8
 
2.2%
대정읍 7
 
2.0%
안덕면 6
 
1.7%
표선면 5
 
1.4%
이어도로 4
 
1.1%
중산간동로 4
 
1.1%
성산읍 4
 
1.1%
Other values (129) 143
40.2%
2023-12-12T09:15:24.221968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
279
 
15.4%
서 92
 
5.1%
주 86
 
4.7%
제 81
 
4.5%
도 81
 
4.5%
포 80
 
4.4%
시 80
 
4.4%
귀 79
 
4.4%
자 78
 
4.3%
특 77
 
4.3%
Other values (85) 798
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1294
71.5%
Space Separator 279
 
15.4%
Decimal Number 233
 
12.9%
Dash Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 92
 
7.1%
주 86
 
6.6%
제 81
 
6.3%
도 81
 
6.3%
포 80
 
6.2%
시 80
 
6.2%
귀 79
 
6.1%
자 78
 
6.0%
특 77
 
6.0%
별 77
 
6.0%
Other values (73) 483
37.3%
Decimal Number
ValueCountFrequency (%)
2 37
15.9%
1 35
15.0%
5 27
11.6%
6 23
9.9%
3 23
9.9%
9 21
9.0%
0 20
8.6%
4 19
8.2%
8 17
7.3%
7 11
 
4.7%
Space Separator
ValueCountFrequency (%)
279
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1294
71.5%
Common 517
 
28.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 92
 
7.1%
주 86
 
6.6%
제 81
 
6.3%
도 81
 
6.3%
포 80
 
6.2%
시 80
 
6.2%
귀 79
 
6.1%
자 78
 
6.0%
특 77
 
6.0%
별 77
 
6.0%
Other values (73) 483
37.3%
Common
ValueCountFrequency (%)
279
54.0%
2 37
 
7.2%
1 35
 
6.8%
5 27
 
5.2%
6 23
 
4.4%
3 23
 
4.4%
9 21
 
4.1%
0 20
 
3.9%
4 19
 
3.7%
8 17
 
3.3%
Other values (2) 16
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1294
71.5%
ASCII 517
 
28.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
279
54.0%
2 37
 
7.2%
1 35
 
6.8%
5 27
 
5.2%
6 23
 
4.4%
3 23
 
4.4%
9 21
 
4.1%
0 20
 
3.9%
4 19
 
3.7%
8 17
 
3.3%
Other values (2) 16
 
3.1%
Hangul
ValueCountFrequency (%)
서 92
 
7.1%
주 86
 
6.6%
제 81
 
6.3%
도 81
 
6.3%
포 80
 
6.2%
시 80
 
6.2%
귀 79
 
6.1%
자 78
 
6.0%
특 77
 
6.0%
별 77
 
6.0%
Other values (73) 483
37.3%

전화번호
Text

MISSING 

Distinct70
Distinct (%)97.2%
Missing5
Missing (%)6.5%
Memory size748.0 B
2023-12-12T09:15:24.501083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters864
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

Unique68 ?
Unique (%)94.4%

Sample

1st row064-764-3423
2nd row064-739-1008
3rd row064-766-1535
4th row064-764-1580
5th row064-764-2674
ValueCountFrequency (%)
064-794-9719 2
 
2.8%
064-763-8314 2
 
2.8%
064-764-3423 1
 
1.4%
064-764-4603 1
 
1.4%
064-739-0101 1
 
1.4%
064-764-4454 1
 
1.4%
064-764-0113 1
 
1.4%
064-794-5211 1
 
1.4%
064-730-7855 1
 
1.4%
064-767-0636 1
 
1.4%
Other values (60) 60
83.3%
2023-12-12T09:15:24.914137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 144
16.7%
4 125
14.5%
0 117
13.5%
6 116
13.4%
7 101
11.7%
3 70
8.1%
1 46
 
5.3%
8 45
 
5.2%
9 44
 
5.1%
2 30
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 720
83.3%
Dash Punctuation 144
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 125
17.4%
0 117
16.2%
6 116
16.1%
7 101
14.0%
3 70
9.7%
1 46
 
6.4%
8 45
 
6.2%
9 44
 
6.1%
2 30
 
4.2%
5 26
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 864
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 144
16.7%
4 125
14.5%
0 117
13.5%
6 116
13.4%
7 101
11.7%
3 70
8.1%
1 46
 
5.3%
8 45
 
5.2%
9 44
 
5.1%
2 30
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 144
16.7%
4 125
14.5%
0 117
13.5%
6 116
13.4%
7 101
11.7%
3 70
8.1%
1 46
 
5.3%
8 45
 
5.2%
9 44
 
5.1%
2 30
 
3.5%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.119602
Minimum33.223703
Maximum126.66133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-12T09:15:25.390698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.223703
5-th percentile33.235656
Q133.250034
median33.266228
Q333.288848
95-th percentile52.018769
Maximum126.66133
Range93.437629
Interquartile range (IQR)0.03881387

Descriptive statistics

Standard deviation20.822534
Coefficient of variation (CV)0.54624217
Kurtosis15.361239
Mean38.119602
Median Absolute Deviation (MAD)0.01920054
Skewness4.1185723
Sum2935.2093
Variance433.57792
MonotonicityNot monotonic
2023-12-12T09:15:25.559029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.27499276 1
 
1.3%
33.27980481 1
 
1.3%
33.32226493 1
 
1.3%
33.25210518 1
 
1.3%
33.27997192 1
 
1.3%
33.24877152 1
 
1.3%
33.4465091 1
 
1.3%
33.26491238 1
 
1.3%
33.24513478 1
 
1.3%
126.59114 1
 
1.3%
Other values (67) 67
87.0%
ValueCountFrequency (%)
33.22370267 1
1.3%
33.22421017 1
1.3%
33.23072618 1
1.3%
33.23404246 1
1.3%
33.23605984 1
1.3%
33.23657507 1
1.3%
33.23759269 1
1.3%
33.23795989 1
1.3%
33.24148343 1
1.3%
33.24280086 1
1.3%
ValueCountFrequency (%)
126.6613313 1
1.3%
126.59114 1
1.3%
126.4174056 1
1.3%
126.3048016 1
1.3%
33.44726124 1
1.3%
33.4465091 1
1.3%
33.44625413 1
1.3%
33.39048272 1
1.3%
33.38192303 1
1.3%
33.35223513 1
1.3%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121.7264
Minimum33.255482
Maximum126.91437
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-12T09:15:25.703320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.255482
5-th percentile107.61759
Q1126.43221
median126.56817
Q3126.67006
95-th percentile126.8403
Maximum126.91437
Range93.658887
Interquartile range (IQR)0.2378418

Descriptive statistics

Standard deviation20.842729
Coefficient of variation (CV)0.17122604
Kurtosis15.358823
Mean121.7264
Median Absolute Deviation (MAD)0.1359578
Skewness-4.1181368
Sum9372.9327
Variance434.41934
MonotonicityNot monotonic
2023-12-12T09:15:25.879335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6700551 1
 
1.3%
126.7223562 1
 
1.3%
126.8305106 1
 
1.3%
126.4226607 1
 
1.3%
126.6690707 1
 
1.3%
126.3341758 1
 
1.3%
126.9143698 1
 
1.3%
126.5681711 1
 
1.3%
126.2729317 1
 
1.3%
33.28320264 1
 
1.3%
Other values (67) 67
87.0%
ValueCountFrequency (%)
33.25548231 1
1.3%
33.26011132 1
1.3%
33.27802249 1
1.3%
33.28320264 1
1.3%
126.20119 1
1.3%
126.2254152 1
1.3%
126.252536 1
1.3%
126.2606419 1
1.3%
126.2641987 1
1.3%
126.2729317 1
1.3%
ValueCountFrequency (%)
126.9143698 1
1.3%
126.9119443 1
1.3%
126.9115609 1
1.3%
126.8740365 1
1.3%
126.8318707 1
1.3%
126.8305106 1
1.3%
126.8007326 1
1.3%
126.7919195 1
1.3%
126.7713139 1
1.3%
126.7669329 1
1.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
Minimum2023-10-04 00:00:00
Maximum2023-10-04 00:00:00
2023-12-12T09:15:26.032149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:15:26.152927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T09:15:22.450657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:15:22.317210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:15:22.532503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:15:22.385550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:15:26.243759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호도로명 주소전화번호위도경도
상호1.0001.0001.0001.0001.000
도로명 주소1.0001.0001.0001.0001.000
전화번호1.0001.0001.0000.0000.000
위도1.0001.0000.0001.0000.978
경도1.0001.0000.0000.9781.000
2023-12-12T09:15:26.347188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.584
경도0.5841.000

Missing values

2023-12-12T09:15:22.642351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:15:22.816812image/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

상호도로명 주소전화번호위도경도데이터기준일자
0강남농약사제주특별자치도 서귀포시 남원읍 태위로 211064-764-342333.274993126.6700552023-10-04
1강정새마을금고제주특별자치도 서귀포시 이어도로 567064-739-100833.236575126.4775652023-10-04
2남원농업협동조합제주특별자치도 서귀포시 남원읍 남조로 57064-766-153533.250034126.5675412023-10-04
3남원농업협동조합신흥2리지점제주특별자치도 서귀포시 남원읍 중산간동로 5804064-764-158033.320901126.7463652023-10-04
4남원농업협동조합신흥지점제주특별자치도 서귀포시 남원읍 신흥로 11064-764-267433.302168126.7669332023-10-04
5남원농업협동조합의귀지점제주특별자치도 서귀포시 남원읍 한신로 203064-764-370533.310219126.7129122023-10-04
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