Overview

Dataset statistics

Number of variables15
Number of observations34
Missing cells142
Missing cells (%)27.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory132.9 B

Variable types

Text3
Categorical4
Unsupported4
Numeric3
DateTime1

Dataset

Description- 축산물(식육,원유,식육가공품 등)을 냉동 또는 냉장으로 보관하는 업종의 사업장명, 인허가일자, 영업상태, 소재지주소 등의 정보를 제공합니다. - 1인 기업의 증가로 영업장과 집 주소가 동일하여 개인정보(집주소)가 노출되는 위험을 최소화 하고자 일부 업종의 소재지 주소(동,호수 등)가 비식별 조치되었습니다. - 원본 파일의 좌표가 중부원점 TM(EPSH:2097) 좌표계를 따르고 있는데 위경도(WGS84) 좌표계로 변환 시 정확하게 변환이 되지 않아 파일에서 좌표 정보는 제외하였습니다. 데이터 제공 사이트로 가시면 원본 좌표를 확인하실 수 있습니다. - 데이터 제공처: LOCALDATA
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/834

Alerts

업종구분대분류 has constant value ""Constant
재개업일자 is highly overall correlated with 인허가일자 and 4 other fieldsHigh correlation
영업상태명 is highly overall correlated with 인허가일자 and 2 other fieldsHigh correlation
폐업일자 is highly overall correlated with 인허가일자 and 4 other fieldsHigh correlation
인허가일자 is highly overall correlated with 영업상태명 and 2 other fieldsHigh correlation
소재지면적 is highly overall correlated with 폐업일자 and 1 other fieldsHigh correlation
도로명우편번호 is highly overall correlated with 폐업일자 and 1 other fieldsHigh correlation
폐업일자 is highly imbalanced (63.5%)Imbalance
재개업일자 is highly imbalanced (71.5%)Imbalance
업종구분소분류 has 34 (100.0%) missing valuesMissing
인허가취소일자 has 34 (100.0%) missing valuesMissing
휴업시작일자 has 34 (100.0%) missing valuesMissing
휴업종료일자 has 34 (100.0%) missing valuesMissing
지번주소 has 3 (8.8%) missing valuesMissing
도로명주소 has 1 (2.9%) missing valuesMissing
도로명우편번호 has 2 (5.9%) missing valuesMissing
사업장명 has unique valuesUnique
업종구분소분류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 4 (11.8%) zerosZeros

Reproduction

Analysis started2023-12-11 19:39:00.241195
Analysis finished2023-12-11 19:39:03.689787
Duration3.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T04:39:03.901895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length10.5
Min length2

Characters and Unicode

Total characters357
Distinct characters96
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st row(주)삼다농수산
2nd row대성수산냉동영농조합법인
3rd row(주)비에이치씨 광주물류 제주하치장
4th row(주)제이비엘
5th row농업회사법인(주)대명
ValueCountFrequency (%)
주식회사 5
 
10.2%
농업회사법인 3
 
6.1%
제주로지스틱스 2
 
4.1%
주)비지에프로지스 2
 
4.1%
주)삼다농수산 1
 
2.0%
서귀포센터 1
 
2.0%
주)한라식품 1
 
2.0%
승민 1
 
2.0%
제이비엘 1
 
2.0%
주)21세기축산 1
 
2.0%
Other values (31) 31
63.3%
2023-12-12T04:39:04.441819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 36
 
10.1%
( 20
 
5.6%
) 20
 
5.6%
제 16
 
4.5%
15
 
4.2%
사 14
 
3.9%
회 14
 
3.9%
인 10
 
2.8%
농 10
 
2.8%
식 10
 
2.8%
Other values (86) 192
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
83.5%
Open Punctuation 20
 
5.6%
Close Punctuation 20
 
5.6%
Space Separator 15
 
4.2%
Decimal Number 2
 
0.6%
Uppercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 36
 
12.1%
제 16
 
5.4%
사 14
 
4.7%
회 14
 
4.7%
인 10
 
3.4%
농 10
 
3.4%
식 10
 
3.4%
업 9
 
3.0%
법 9
 
3.0%
지 8
 
2.7%
Other values (79) 162
54.4%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
Z 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 298
83.5%
Common 57
 
16.0%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 36
 
12.1%
제 16
 
5.4%
사 14
 
4.7%
회 14
 
4.7%
인 10
 
3.4%
농 10
 
3.4%
식 10
 
3.4%
업 9
 
3.0%
법 9
 
3.0%
지 8
 
2.7%
Other values (79) 162
54.4%
Common
ValueCountFrequency (%)
( 20
35.1%
) 20
35.1%
15
26.3%
1 1
 
1.8%
2 1
 
1.8%
Latin
ValueCountFrequency (%)
A 1
50.0%
Z 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 298
83.5%
ASCII 59
 
16.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 36
 
12.1%
제 16
 
5.4%
사 14
 
4.7%
회 14
 
4.7%
인 10
 
3.4%
농 10
 
3.4%
식 10
 
3.4%
업 9
 
3.0%
법 9
 
3.0%
지 8
 
2.7%
Other values (79) 162
54.4%
ASCII
ValueCountFrequency (%)
( 20
33.9%
) 20
33.9%
15
25.4%
1 1
 
1.7%
2 1
 
1.7%
A 1
 
1.7%
Z 1
 
1.7%

업종구분대분류
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
축산물보관업
34 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물보관업 34
100.0%

Length

2023-12-12T04:39:04.680580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:39:04.819827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물보관업 34
100.0%

업종구분소분류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

인허가일자
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20180331
Minimum20001125
Maximum20230901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T04:39:04.958176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001125
5-th percentile20017557
Q120160526
median20195866
Q320220465
95-th percentile20230551
Maximum20230901
Range229776
Interquartile range (IQR)59939

Descriptive statistics

Standard deviation60378.67
Coefficient of variation (CV)0.0029919564
Kurtosis3.7064559
Mean20180331
Median Absolute Deviation (MAD)24746
Skewness-2.001987
Sum6.8613124 × 108
Variance3.6455838 × 109
MonotonicityNot monotonic
2023-12-12T04:39:05.137975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20210715 2
 
5.9%
20220510 2
 
5.9%
20190328 2
 
5.9%
20001125 1
 
2.9%
20220208 1
 
2.9%
20220331 1
 
2.9%
20220714 1
 
2.9%
20230209 1
 
2.9%
20230213 1
 
2.9%
20201116 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
20001125 1
2.9%
20011125 1
2.9%
20021021 1
2.9%
20130527 1
2.9%
20141112 1
2.9%
20151021 1
2.9%
20160225 1
2.9%
20160316 1
2.9%
20160401 1
2.9%
20160902 1
2.9%
ValueCountFrequency (%)
20230901 1
2.9%
20230609 1
2.9%
20230520 1
2.9%
20230404 1
2.9%
20230213 1
2.9%
20230209 1
2.9%
20220714 1
2.9%
20220510 2
5.9%
20220331 1
2.9%
20220208 1
2.9%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

영업상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
영업/정상
29 
폐업
5 

Length

Max length5
Median length5
Mean length4.5588235
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row영업/정상
3rd row폐업
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 29
85.3%
폐업 5
 
14.7%

Length

2023-12-12T04:39:05.323866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:39:05.471985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 29
85.3%
폐업 5
 
14.7%

폐업일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size404.0 B
<NA>
29 
20120905
 
1
20180719
 
1
20191129
 
1
20210203
 
1

Length

Max length8
Median length4
Mean length4.5882353
Min length4

Unique

Unique5 ?
Unique (%)14.7%

Sample

1st row20120905
2nd row<NA>
3rd row20180719
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 29
85.3%
20120905 1
 
2.9%
20180719 1
 
2.9%
20191129 1
 
2.9%
20210203 1
 
2.9%
20050302 1
 
2.9%

Length

2023-12-12T04:39:05.609857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:39:05.765095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
85.3%
20120905 1
 
2.9%
20180719 1
 
2.9%
20191129 1
 
2.9%
20210203 1
 
2.9%
20050302 1
 
2.9%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

재개업일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
<NA>
31 
20180719
 
1
20191129
 
1
20210203
 
1

Length

Max length8
Median length4
Mean length4.3529412
Min length4

Unique

Unique3 ?
Unique (%)8.8%

Sample

1st row<NA>
2nd row<NA>
3rd row20180719
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 31
91.2%
20180719 1
 
2.9%
20191129 1
 
2.9%
20210203 1
 
2.9%

Length

2023-12-12T04:39:05.936275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:39:06.072082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
91.2%
20180719 1
 
2.9%
20191129 1
 
2.9%
20210203 1
 
2.9%

소재지면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean809.94118
Minimum0
Maximum12719
Zeros4
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T04:39:06.220089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1106.75
median255.75
Q3488.2875
95-th percentile2809.13
Maximum12719
Range12719
Interquartile range (IQR)381.5375

Descriptive statistics

Standard deviation2246.7544
Coefficient of variation (CV)2.7739723
Kurtosis25.623568
Mean809.94118
Median Absolute Deviation (MAD)165.59
Skewness4.899992
Sum27538
Variance5047905.2
MonotonicityNot monotonic
2023-12-12T04:39:06.438280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 4
 
11.8%
106.0 1
 
2.9%
4298.8 1
 
2.9%
323.64 1
 
2.9%
247.5 1
 
2.9%
82.64 1
 
2.9%
346.86 1
 
2.9%
114.0 1
 
2.9%
598.56 1
 
2.9%
299.1 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
0.0 4
11.8%
7.25 1
 
2.9%
10.0 1
 
2.9%
82.64 1
 
2.9%
97.68 1
 
2.9%
106.0 1
 
2.9%
109.0 1
 
2.9%
114.0 1
 
2.9%
132.0 1
 
2.9%
165.6 1
 
2.9%
ValueCountFrequency (%)
12719.0 1
2.9%
4298.8 1
2.9%
2007.0 1
2.9%
1349.06 1
2.9%
630.0 1
2.9%
598.56 1
2.9%
583.8 1
2.9%
500.0 1
2.9%
495.87 1
2.9%
465.54 1
2.9%

지번주소
Text

MISSING 

Distinct31
Distinct (%)100.0%
Missing3
Missing (%)8.8%
Memory size404.0 B
2023-12-12T04:39:06.762587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length22.83871
Min length19

Characters and Unicode

Total characters708
Distinct characters64
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

Unique31 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 제주시 구좌읍 행원리 542-10
2nd row제주특별자치도 제주시 한림읍 한림리 1596-2
3rd row제주특별자치도 제주시 외도일동 437-5
4th row제주특별자치도 제주시 도두일동 2626-2
5th row제주특별자치도 제주시 애월읍 3333-1
ValueCountFrequency (%)
제주특별자치도 31
23.1%
제주시 28
20.9%
한림읍 5
 
3.7%
외도일동 4
 
3.0%
서귀포시 3
 
2.2%
도두일동 3
 
2.2%
대정읍 2
 
1.5%
이호일동 2
 
1.5%
화북일동 2
 
1.5%
애월읍 2
 
1.5%
Other values (50) 52
38.8%
2023-12-12T04:39:07.288819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
103
 
14.5%
제 59
 
8.3%
주 59
 
8.3%
도 40
 
5.6%
특 31
 
4.4%
별 31
 
4.4%
자 31
 
4.4%
치 31
 
4.4%
시 31
 
4.4%
1 27
 
3.8%
Other values (54) 265
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 450
63.6%
Decimal Number 132
 
18.6%
Space Separator 103
 
14.5%
Dash Punctuation 23
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 59
13.1%
주 59
13.1%
도 40
 
8.9%
특 31
 
6.9%
별 31
 
6.9%
자 31
 
6.9%
치 31
 
6.9%
시 31
 
6.9%
동 20
 
4.4%
일 12
 
2.7%
Other values (42) 105
23.3%
Decimal Number
ValueCountFrequency (%)
1 27
20.5%
2 20
15.2%
3 16
12.1%
5 15
11.4%
4 12
9.1%
6 11
8.3%
7 10
 
7.6%
9 8
 
6.1%
8 8
 
6.1%
0 5
 
3.8%
Space Separator
ValueCountFrequency (%)
103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 450
63.6%
Common 258
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 59
13.1%
주 59
13.1%
도 40
 
8.9%
특 31
 
6.9%
별 31
 
6.9%
자 31
 
6.9%
치 31
 
6.9%
시 31
 
6.9%
동 20
 
4.4%
일 12
 
2.7%
Other values (42) 105
23.3%
Common
ValueCountFrequency (%)
103
39.9%
1 27
 
10.5%
- 23
 
8.9%
2 20
 
7.8%
3 16
 
6.2%
5 15
 
5.8%
4 12
 
4.7%
6 11
 
4.3%
7 10
 
3.9%
9 8
 
3.1%
Other values (2) 13
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 450
63.6%
ASCII 258
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
103
39.9%
1 27
 
10.5%
- 23
 
8.9%
2 20
 
7.8%
3 16
 
6.2%
5 15
 
5.8%
4 12
 
4.7%
6 11
 
4.3%
7 10
 
3.9%
9 8
 
3.1%
Other values (2) 13
 
5.0%
Hangul
ValueCountFrequency (%)
제 59
13.1%
주 59
13.1%
도 40
 
8.9%
특 31
 
6.9%
별 31
 
6.9%
자 31
 
6.9%
치 31
 
6.9%
시 31
 
6.9%
동 20
 
4.4%
일 12
 
2.7%
Other values (42) 105
23.3%

도로명주소
Text

MISSING 

Distinct33
Distinct (%)100.0%
Missing1
Missing (%)2.9%
Memory size404.0 B
2023-12-12T04:39:07.680859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length27.666667
Min length22

Characters and Unicode

Total characters913
Distinct characters97
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 제주시 구좌읍 행원로13길 99
2nd row제주특별자치도 제주시 한림읍 한림해안로 94
3rd row제주특별자치도 제주시 우령8길 10 (외도일동)
4th row제주특별자치도 제주시 선반로6길 9 (화북일동)
5th row제주특별자치도 제주시 애월읍 광성로 166
ValueCountFrequency (%)
제주특별자치도 33
 
18.9%
제주시 31
 
17.7%
한림읍 5
 
2.9%
애월읍 4
 
2.3%
외도일동 3
 
1.7%
화북일동 3
 
1.7%
도두일동 3
 
1.7%
서귀포시 2
 
1.1%
광성로 2
 
1.1%
이호일동 2
 
1.1%
Other values (81) 87
49.7%
2023-12-12T04:39:08.351378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
142
 
15.6%
주 68
 
7.4%
제 65
 
7.1%
도 45
 
4.9%
특 33
 
3.6%
별 33
 
3.6%
자 33
 
3.6%
치 33
 
3.6%
시 33
 
3.6%
1 30
 
3.3%
Other values (87) 398
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 588
64.4%
Space Separator 142
 
15.6%
Decimal Number 121
 
13.3%
Open Punctuation 21
 
2.3%
Close Punctuation 21
 
2.3%
Other Punctuation 11
 
1.2%
Dash Punctuation 9
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 68
 
11.6%
제 65
 
11.1%
도 45
 
7.7%
특 33
 
5.6%
별 33
 
5.6%
자 33
 
5.6%
치 33
 
5.6%
시 33
 
5.6%
동 27
 
4.6%
로 25
 
4.3%
Other values (71) 193
32.8%
Decimal Number
ValueCountFrequency (%)
1 30
24.8%
5 15
12.4%
2 14
11.6%
4 11
 
9.1%
8 10
 
8.3%
3 10
 
8.3%
0 10
 
8.3%
7 8
 
6.6%
6 7
 
5.8%
9 6
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 10
90.9%
. 1
 
9.1%
Space Separator
ValueCountFrequency (%)
142
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 588
64.4%
Common 325
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 68
 
11.6%
제 65
 
11.1%
도 45
 
7.7%
특 33
 
5.6%
별 33
 
5.6%
자 33
 
5.6%
치 33
 
5.6%
시 33
 
5.6%
동 27
 
4.6%
로 25
 
4.3%
Other values (71) 193
32.8%
Common
ValueCountFrequency (%)
142
43.7%
1 30
 
9.2%
( 21
 
6.5%
) 21
 
6.5%
5 15
 
4.6%
2 14
 
4.3%
4 11
 
3.4%
8 10
 
3.1%
3 10
 
3.1%
0 10
 
3.1%
Other values (6) 41
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 588
64.4%
ASCII 325
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
142
43.7%
1 30
 
9.2%
( 21
 
6.5%
) 21
 
6.5%
5 15
 
4.6%
2 14
 
4.3%
4 11
 
3.4%
8 10
 
3.1%
3 10
 
3.1%
0 10
 
3.1%
Other values (6) 41
 
12.6%
Hangul
ValueCountFrequency (%)
주 68
 
11.6%
제 65
 
11.1%
도 45
 
7.7%
특 33
 
5.6%
별 33
 
5.6%
자 33
 
5.6%
치 33
 
5.6%
시 33
 
5.6%
동 27
 
4.6%
로 25
 
4.3%
Other values (71) 193
32.8%

도로명우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)75.0%
Missing2
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean63167.125
Minimum63010
Maximum63581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T04:39:08.568161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum63010
5-th percentile63020.6
Q163066.5
median63109
Q363298.25
95-th percentile63423.7
Maximum63581
Range571
Interquartile range (IQR)231.75

Descriptive statistics

Standard deviation148.56165
Coefficient of variation (CV)0.0023518824
Kurtosis0.68611073
Mean63167.125
Median Absolute Deviation (MAD)61
Skewness1.168764
Sum2021348
Variance22070.565
MonotonicityNot monotonic
2023-12-12T04:39:08.781844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
63116 3
 
8.8%
63069 3
 
8.8%
63062 2
 
5.9%
63308 2
 
5.9%
63108 2
 
5.9%
63026 2
 
5.9%
63074 1
 
2.9%
63504 1
 
2.9%
63581 1
 
2.9%
63299 1
 
2.9%
Other values (14) 14
41.2%
(Missing) 2
 
5.9%
ValueCountFrequency (%)
63010 1
 
2.9%
63014 1
 
2.9%
63026 2
5.9%
63038 1
 
2.9%
63058 1
 
2.9%
63062 2
5.9%
63068 1
 
2.9%
63069 3
8.8%
63072 1
 
2.9%
63074 1
 
2.9%
ValueCountFrequency (%)
63581 1
2.9%
63504 1
2.9%
63358 1
2.9%
63338 1
2.9%
63313 1
2.9%
63308 2
5.9%
63299 1
2.9%
63298 1
2.9%
63297 1
2.9%
63240 1
2.9%

데이터갱신일자
Date

Distinct24
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size404.0 B
Minimum2018-08-31 23:59:00
Maximum2023-09-03 00:18:00
2023-12-12T04:39:08.962059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:39:09.151286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

Interactions

2023-12-12T04:39:02.392531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:39:01.441288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:39:01.922132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:39:02.557207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:39:01.586044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:39:02.065068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:39:02.708801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:39:01.767063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:39:02.224849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:39:09.320931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명인허가일자영업상태명폐업일자재개업일자소재지면적지번주소도로명주소도로명우편번호데이터갱신일자
사업장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
인허가일자1.0001.0000.6931.0001.0000.0001.0001.0000.0000.000
영업상태명1.0000.6931.000NaNNaN0.0001.0001.0000.2310.000
폐업일자1.0001.000NaN1.0001.0001.0001.0001.0001.0001.000
재개업일자1.0001.000NaN1.0001.0001.0001.0001.0001.0001.000
소재지면적1.0000.0000.0001.0001.0001.0001.0001.0000.8631.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명우편번호1.0000.0000.2311.0001.0000.8631.0001.0001.0000.753
데이터갱신일자1.0000.0000.0001.0001.0001.0001.0001.0000.7531.000
2023-12-12T04:39:09.542808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
재개업일자영업상태명폐업일자
재개업일자1.0001.0001.000
영업상태명1.0001.0001.000
폐업일자1.0001.0001.000
2023-12-12T04:39:09.720377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자소재지면적도로명우편번호영업상태명폐업일자재개업일자
인허가일자1.000-0.049-0.0130.5481.0001.000
소재지면적-0.0491.000-0.0380.0001.0001.000
도로명우편번호-0.013-0.0381.0000.2221.0001.000
영업상태명0.5480.0000.2221.0001.0001.000
폐업일자1.0001.0001.0001.0001.0001.000
재개업일자1.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T04:39:02.961590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:39:03.339946image/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.
2023-12-12T04:39:03.578226image/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

사업장명업종구분대분류업종구분소분류인허가일자인허가취소일자영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지면적지번주소도로명주소도로명우편번호데이터갱신일자
0(주)삼다농수산축산물보관업<NA>20001125<NA>폐업20120905<NA><NA><NA>106.0제주특별자치도 제주시 구좌읍 행원리 542-10제주특별자치도 제주시 구좌읍 행원로13길 99633582018-08-31 23:59
1대성수산냉동영농조합법인축산물보관업<NA>20011125<NA>영업/정상<NA><NA><NA><NA>0.0제주특별자치도 제주시 한림읍 한림리 1596-2제주특별자치도 제주시 한림읍 한림해안로 94<NA>2018-08-31 23:59
2(주)비에이치씨 광주물류 제주하치장축산물보관업<NA>20130527<NA>폐업20180719<NA><NA>20180719266.0제주특별자치도 제주시 외도일동 437-5제주특별자치도 제주시 우령8길 10 (외도일동)630692018-08-31 23:59
3(주)제이비엘축산물보관업<NA>20141112<NA>영업/정상<NA><NA><NA><NA>500.0<NA>제주특별자치도 제주시 선반로6길 9 (화북일동)632972023-06-30 2:40
4농업회사법인(주)대명축산물보관업<NA>20151021<NA>영업/정상<NA><NA><NA><NA>583.8<NA>제주특별자치도 제주시 애월읍 광성로 166630622018-08-31 23:59
5(주)금강축산유통축산물보관업<NA>20160225<NA>영업/정상<NA><NA><NA><NA>246.4제주특별자치도 제주시 도두일동 2626-2제주특별자치도 제주시 도공로 25-4 (도두일동)631132018-08-31 23:59
6대상(주)제주물류센터축산물보관업<NA>20160316<NA>영업/정상<NA><NA><NA><NA>495.87제주특별자치도 제주시 애월읍 3333-1제주특별자치도 제주시 애월읍 광성로 175630622018-08-31 23:59
7농업회사법인 제주도화 주식회사축산물보관업<NA>20160401<NA>영업/정상<NA><NA><NA><NA>97.68<NA>제주특별자치도 제주시 애월읍 항몽로 297630582022-06-19 2:40
8제주축산업협동조합 공판장축산물보관업<NA>20160902<NA>폐업20191129<NA><NA>201911291349.06제주특별자치도 제주시 애월읍 어음리 2513-2제주특별자치도 제주시 애월읍 천덕로 440-24630382019-12-01 2:40
9(주)아워홈 제주영업소축산물보관업<NA>20210715<NA>영업/정상<NA><NA><NA><NA>630.0제주특별자치도 제주시 조천읍 신촌리 2784제주특별자치도 제주시 조천읍 신와로 74633382021-07-17 2:40
사업장명업종구분대분류업종구분소분류인허가일자인허가취소일자영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지면적지번주소도로명주소도로명우편번호데이터갱신일자
24서광축산영농조합법인축산물보관업<NA>20220714<NA>영업/정상<NA><NA><NA><NA>0.0제주특별자치도 제주시 외도일동 1823-3제주특별자치도 제주시 우령서로 18(외도일동)630722022-07-17 0:22
25농업회사법인(주)혼디푸드축산물보관업<NA>20230209<NA>영업/정상<NA><NA><NA><NA>299.1제주특별자치도 제주시 이호일동 641-1제주특별자치도 제주시 도리로 78-8, 창고 (이호일동)631082023-02-13 2:40
26주식회사 두원식품축산물보관업<NA>20230213<NA>영업/정상<NA><NA><NA><NA>598.56제주특별자치도 제주시 한림읍 대림리 1752제주특별자치도 제주시 한림읍 한수풀로 73, 지하1층630262023-02-16 0:40
27에이지(AZ) 로지스축산물보관업<NA>20230404<NA>영업/정상<NA><NA><NA><NA>114.0제주특별자치도 제주시 봉개동 485제주특별자치도 제주시 명림로 125 (봉개동)633132023-04-06 0:20
28(주)21세기축산축산물보관업<NA>20230520<NA>영업/정상<NA><NA><NA><NA>346.86제주특별자치도 제주시 한림읍 명월리 157제주특별자치도 제주시 한림읍 중산간서로 4462-12, 마동630142023-05-24 2:40
29농업회사법인 주식회사 제이비엘축산물보관업<NA>20230609<NA>영업/정상<NA><NA><NA><NA>82.64제주특별자치도 제주시 화북일동 2131-9제주특별자치도 제주시 선반남1길 53 (화북일동)632992023-06-11 2:40
30승민축산물보관업<NA>20230901<NA>영업/정상<NA><NA><NA><NA>247.5제주특별자치도 제주시 도두일동 1175-1제주특별자치도 제주시 제성1길 75, 비동 (도두일동)631162023-09-03 0:18
31(주)한라식품축산물보관업<NA>20021021<NA>폐업20050302<NA><NA><NA>323.64제주특별자치도 서귀포시 대정읍 일과리 551-11<NA><NA>2018-08-31 23:59
32(주)비지에프로지스 서귀포센터축산물보관업<NA>20190104<NA>영업/정상<NA><NA><NA><NA>4298.8제주특별자치도 서귀포시 토평동 3268-3제주특별자치도 서귀포시 토평공단로155번길 45, 1동 1층 (토평동)635812022-12-30 2:40
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