Overview

Dataset statistics

Number of variables48
Number of observations3589
Missing cells37339
Missing cells (%)21.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory413.0 B

Variable types

Numeric11
Categorical21
Text6
Unsupported8
DateTime1
Boolean1

Dataset

Description2021-03-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123101

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (98.7%)Imbalance
위생업태명 is highly imbalanced (98.7%)Imbalance
남성종사자수 is highly imbalanced (65.5%)Imbalance
여성종사자수 is highly imbalanced (65.6%)Imbalance
영업장주변구분명 is highly imbalanced (70.9%)Imbalance
등급구분명 is highly imbalanced (52.7%)Imbalance
급수시설구분명 is highly imbalanced (68.8%)Imbalance
공장사무직종업원수 is highly imbalanced (55.9%)Imbalance
공장판매직종업원수 is highly imbalanced (55.3%)Imbalance
보증액 is highly imbalanced (73.0%)Imbalance
월세액 is highly imbalanced (73.0%)Imbalance
홈페이지 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3589 (100.0%) missing valuesMissing
폐업일자 has 1018 (28.4%) missing valuesMissing
휴업시작일자 has 3589 (100.0%) missing valuesMissing
휴업종료일자 has 3589 (100.0%) missing valuesMissing
재개업일자 has 3589 (100.0%) missing valuesMissing
소재지전화 has 981 (27.3%) missing valuesMissing
소재지면적 has 1039 (28.9%) missing valuesMissing
도로명전체주소 has 1719 (47.9%) missing valuesMissing
도로명우편번호 has 1751 (48.8%) missing valuesMissing
좌표정보(x) has 168 (4.7%) missing valuesMissing
좌표정보(y) has 168 (4.7%) missing valuesMissing
총종업원수 has 3589 (100.0%) missing valuesMissing
공장생산직종업원수 has 1748 (48.7%) missing valuesMissing
전통업소지정번호 has 3589 (100.0%) missing valuesMissing
전통업소주된음식 has 3589 (100.0%) missing valuesMissing
Unnamed: 47 has 3589 (100.0%) missing valuesMissing
공장생산직종업원수 is highly skewed (γ1 = 42.90210507)Skewed
시설총규모 is highly skewed (γ1 = 29.9785245)Skewed
번호 has unique valuesUnique
관리번호 has unique valuesUnique
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
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총종업원수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 47 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공장생산직종업원수 has 1802 (50.2%) zerosZeros
시설총규모 has 3344 (93.2%) zerosZeros

Reproduction

Analysis started2024-04-18 02:32:29.320043
Analysis finished2024-04-18 02:32:30.592679
Duration1.27 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3589
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1795
Minimum1
Maximum3589
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:30.660935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile180.4
Q1898
median1795
Q32692
95-th percentile3409.6
Maximum3589
Range3588
Interquartile range (IQR)1794

Descriptive statistics

Standard deviation1036.1994
Coefficient of variation (CV)0.57726985
Kurtosis-1.2
Mean1795
Median Absolute Deviation (MAD)897
Skewness0
Sum6442255
Variance1073709.2
MonotonicityStrictly increasing
2024-04-18T11:32:30.792800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2245 1
 
< 0.1%
2387 1
 
< 0.1%
2388 1
 
< 0.1%
2389 1
 
< 0.1%
2390 1
 
< 0.1%
2391 1
 
< 0.1%
2392 1
 
< 0.1%
2393 1
 
< 0.1%
2394 1
 
< 0.1%
Other values (3579) 3579
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3589 1
< 0.1%
3588 1
< 0.1%
3587 1
< 0.1%
3586 1
< 0.1%
3585 1
< 0.1%
3584 1
< 0.1%
3583 1
< 0.1%
3582 1
< 0.1%
3581 1
< 0.1%
3580 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
식품소분업
3589 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 3589
100.0%

Length

2024-04-18T11:32:30.922733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:31.017486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 3589
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
07_22_08_P
3589 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_08_P
2nd row07_22_08_P
3rd row07_22_08_P
4th row07_22_08_P
5th row07_22_08_P

Common Values

ValueCountFrequency (%)
07_22_08_P 3589
100.0%

Length

2024-04-18T11:32:31.113019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:31.199838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_08_p 3589
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3327793.3
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:31.279709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3330000
Q33350000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation42181.73
Coefficient of variation (CV)0.012675586
Kurtosis-0.85996921
Mean3327793.3
Median Absolute Deviation (MAD)30000
Skewness-0.02901459
Sum1.194345 × 1010
Variance1.7792984 × 109
MonotonicityNot monotonic
2024-04-18T11:32:31.387909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3340000 528
14.7%
3330000 387
10.8%
3290000 362
10.1%
3390000 282
 
7.9%
3300000 267
 
7.4%
3350000 230
 
6.4%
3400000 218
 
6.1%
3320000 202
 
5.6%
3270000 172
 
4.8%
3250000 170
 
4.7%
Other values (6) 771
21.5%
ValueCountFrequency (%)
3250000 170
 
4.7%
3260000 147
 
4.1%
3270000 172
 
4.8%
3280000 78
 
2.2%
3290000 362
10.1%
3300000 267
7.4%
3310000 152
 
4.2%
3320000 202
 
5.6%
3330000 387
10.8%
3340000 528
14.7%
ValueCountFrequency (%)
3400000 218
6.1%
3390000 282
7.9%
3380000 128
 
3.6%
3370000 130
 
3.6%
3360000 136
 
3.8%
3350000 230
6.4%
3340000 528
14.7%
3330000 387
10.8%
3320000 202
 
5.6%
3310000 152
 
4.2%

관리번호
Text

UNIQUE 

Distinct3589
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
2024-04-18T11:32:31.564623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters78958
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

Unique3589 ?
Unique (%)100.0%

Sample

1st row3300000-109-2011-00006
2nd row3300000-109-2014-00006
3rd row3300000-109-2014-00007
4th row3300000-109-2017-00004
5th row3300000-109-2017-00005
ValueCountFrequency (%)
3300000-109-2011-00006 1
 
< 0.1%
3390000-109-1999-00619 1
 
< 0.1%
3340000-109-2000-01022 1
 
< 0.1%
3340000-109-1999-00903 1
 
< 0.1%
3340000-109-1999-00904 1
 
< 0.1%
3340000-109-1999-00930 1
 
< 0.1%
3340000-109-1999-00934 1
 
< 0.1%
3340000-109-2000-00954 1
 
< 0.1%
3340000-109-2000-00963 1
 
< 0.1%
3340000-109-2000-00977 1
 
< 0.1%
Other values (3579) 3579
99.7%
2024-04-18T11:32:31.872175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 36064
45.7%
- 10767
 
13.6%
3 7327
 
9.3%
1 7053
 
8.9%
9 5811
 
7.4%
2 5522
 
7.0%
4 1692
 
2.1%
5 1328
 
1.7%
6 1233
 
1.6%
7 1121
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68191
86.4%
Dash Punctuation 10767
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 36064
52.9%
3 7327
 
10.7%
1 7053
 
10.3%
9 5811
 
8.5%
2 5522
 
8.1%
4 1692
 
2.5%
5 1328
 
1.9%
6 1233
 
1.8%
7 1121
 
1.6%
8 1040
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 10767
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78958
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 36064
45.7%
- 10767
 
13.6%
3 7327
 
9.3%
1 7053
 
8.9%
9 5811
 
7.4%
2 5522
 
7.0%
4 1692
 
2.1%
5 1328
 
1.7%
6 1233
 
1.6%
7 1121
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78958
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 36064
45.7%
- 10767
 
13.6%
3 7327
 
9.3%
1 7053
 
8.9%
9 5811
 
7.4%
2 5522
 
7.0%
4 1692
 
2.1%
5 1328
 
1.7%
6 1233
 
1.6%
7 1121
 
1.4%

인허가일자
Real number (ℝ)

Distinct2512
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20072657
Minimum19780414
Maximum20210129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:32.007470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19780414
5-th percentile19970428
Q120020513
median20061016
Q320130219
95-th percentile20190827
Maximum20210129
Range429715
Interquartile range (IQR)109706

Descriptive statistics

Standard deviation71007.266
Coefficient of variation (CV)0.0035375121
Kurtosis-0.2307323
Mean20072657
Median Absolute Deviation (MAD)50095
Skewness-0.031695974
Sum7.2040764 × 1010
Variance5.0420318 × 109
MonotonicityNot monotonic
2024-04-18T11:32:32.134815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000720 12
 
0.3%
20091016 10
 
0.3%
20051026 9
 
0.3%
20100111 7
 
0.2%
20060921 6
 
0.2%
20010704 6
 
0.2%
20030721 6
 
0.2%
20060424 6
 
0.2%
20100113 6
 
0.2%
20110426 6
 
0.2%
Other values (2502) 3515
97.9%
ValueCountFrequency (%)
19780414 1
< 0.1%
19791217 2
0.1%
19820520 1
< 0.1%
19821209 1
< 0.1%
19830706 1
< 0.1%
19831130 1
< 0.1%
19840526 1
< 0.1%
19840818 1
< 0.1%
19841111 1
< 0.1%
19851025 1
< 0.1%
ValueCountFrequency (%)
20210129 2
0.1%
20210126 1
 
< 0.1%
20210122 2
0.1%
20210120 1
 
< 0.1%
20210115 1
 
< 0.1%
20210114 1
 
< 0.1%
20210113 1
 
< 0.1%
20210112 1
 
< 0.1%
20210111 1
 
< 0.1%
20210108 3
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3589
Missing (%)100.0%
Memory size31.7 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
3
2571 
1
1018 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 2571
71.6%
1 1018
 
28.4%

Length

2024-04-18T11:32:32.253117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:32.344241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2571
71.6%
1 1018
 
28.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
폐업
2571 
영업/정상
1018 

Length

Max length5
Median length2
Mean length2.8509334
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2571
71.6%
영업/정상 1018
 
28.4%

Length

2024-04-18T11:32:32.441940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:32.537346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2571
71.6%
영업/정상 1018
 
28.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
2
2571 
1
1018 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 2571
71.6%
1 1018
 
28.4%

Length

2024-04-18T11:32:32.638297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:32.733922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2571
71.6%
1 1018
 
28.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
폐업
2571 
영업
1018 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2571
71.6%
영업 1018
 
28.4%

Length

2024-04-18T11:32:32.829464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:32.920677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2571
71.6%
영업 1018
 
28.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct1782
Distinct (%)69.3%
Missing1018
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean20095733
Minimum19900725
Maximum20210129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:33.025598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19900725
5-th percentile20010566
Q120050911
median20090508
Q320141210
95-th percentile20191220
Maximum20210129
Range309404
Interquartile range (IQR)90299.5

Descriptive statistics

Standard deviation58146.975
Coefficient of variation (CV)0.0028934986
Kurtosis-0.76101831
Mean20095733
Median Absolute Deviation (MAD)40197
Skewness0.13860698
Sum5.1666129 × 1010
Variance3.3810707 × 109
MonotonicityNot monotonic
2024-04-18T11:32:33.157209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20100111 22
 
0.6%
20050614 19
 
0.5%
20100208 13
 
0.4%
20050322 10
 
0.3%
20051102 10
 
0.3%
20070820 9
 
0.3%
20201006 8
 
0.2%
20201231 8
 
0.2%
20060509 8
 
0.2%
20060131 7
 
0.2%
Other values (1772) 2457
68.5%
(Missing) 1018
28.4%
ValueCountFrequency (%)
19900725 2
0.1%
19910223 1
< 0.1%
19920114 1
< 0.1%
19921128 1
< 0.1%
19921221 1
< 0.1%
19950214 1
< 0.1%
19950313 1
< 0.1%
19950320 1
< 0.1%
19950608 1
< 0.1%
19950612 1
< 0.1%
ValueCountFrequency (%)
20210129 1
 
< 0.1%
20210127 2
 
0.1%
20210122 1
 
< 0.1%
20210120 1
 
< 0.1%
20210115 1
 
< 0.1%
20210113 1
 
< 0.1%
20210112 1
 
< 0.1%
20210106 1
 
< 0.1%
20201231 8
0.2%
20201230 2
 
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3589
Missing (%)100.0%
Memory size31.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3589
Missing (%)100.0%
Memory size31.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3589
Missing (%)100.0%
Memory size31.7 KiB

소재지전화
Text

MISSING 

Distinct2028
Distinct (%)77.8%
Missing981
Missing (%)27.3%
Memory size28.2 KiB
2024-04-18T11:32:33.453340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.498083
Min length3

Characters and Unicode

Total characters27379
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

Unique1801 ?
Unique (%)69.1%

Sample

1st row051 531 8282
2nd row051 529 5005
3rd row0515015810
4th row051 756 9991
5th row051 751 1600
ValueCountFrequency (%)
051 2221
39.6%
070 55
 
1.0%
722 29
 
0.5%
055 18
 
0.3%
262 16
 
0.3%
724 14
 
0.2%
265 12
 
0.2%
266 11
 
0.2%
245 11
 
0.2%
261 10
 
0.2%
Other values (2229) 3205
57.2%
2024-04-18T11:32:33.854096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4763
17.4%
5 4215
15.4%
1 4042
14.8%
3032
11.1%
2 2212
8.1%
6 1766
 
6.5%
3 1719
 
6.3%
7 1610
 
5.9%
8 1557
 
5.7%
4 1460
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24347
88.9%
Space Separator 3032
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4763
19.6%
5 4215
17.3%
1 4042
16.6%
2 2212
9.1%
6 1766
 
7.3%
3 1719
 
7.1%
7 1610
 
6.6%
8 1557
 
6.4%
4 1460
 
6.0%
9 1003
 
4.1%
Space Separator
ValueCountFrequency (%)
3032
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27379
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4763
17.4%
5 4215
15.4%
1 4042
14.8%
3032
11.1%
2 2212
8.1%
6 1766
 
6.5%
3 1719
 
6.3%
7 1610
 
5.9%
8 1557
 
5.7%
4 1460
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27379
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4763
17.4%
5 4215
15.4%
1 4042
14.8%
3032
11.1%
2 2212
8.1%
6 1766
 
6.5%
3 1719
 
6.3%
7 1610
 
5.9%
8 1557
 
5.7%
4 1460
 
5.3%

소재지면적
Text

MISSING 

Distinct1381
Distinct (%)54.2%
Missing1039
Missing (%)28.9%
Memory size28.2 KiB
2024-04-18T11:32:34.125676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.6854902
Min length3

Characters and Unicode

Total characters11948
Distinct characters12
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

Unique1068 ?
Unique (%)41.9%

Sample

1st row21.53
2nd row29.50
3rd row8.00
4th row10.00
5th row9.20
ValueCountFrequency (%)
00 113
 
4.4%
6.60 40
 
1.6%
6.00 40
 
1.6%
4.00 37
 
1.5%
3.00 36
 
1.4%
2.00 35
 
1.4%
10.00 34
 
1.3%
3.30 28
 
1.1%
12.00 24
 
0.9%
5.00 24
 
0.9%
Other values (1371) 2139
83.9%
2024-04-18T11:32:34.516638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2698
22.6%
. 2550
21.3%
1 1074
 
9.0%
2 981
 
8.2%
6 756
 
6.3%
4 741
 
6.2%
3 738
 
6.2%
5 735
 
6.2%
8 638
 
5.3%
9 560
 
4.7%
Other values (2) 477
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9388
78.6%
Other Punctuation 2560
 
21.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2698
28.7%
1 1074
 
11.4%
2 981
 
10.4%
6 756
 
8.1%
4 741
 
7.9%
3 738
 
7.9%
5 735
 
7.8%
8 638
 
6.8%
9 560
 
6.0%
7 467
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 2550
99.6%
, 10
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 11948
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2698
22.6%
. 2550
21.3%
1 1074
 
9.0%
2 981
 
8.2%
6 756
 
6.3%
4 741
 
6.2%
3 738
 
6.2%
5 735
 
6.2%
8 638
 
5.3%
9 560
 
4.7%
Other values (2) 477
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11948
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2698
22.6%
. 2550
21.3%
1 1074
 
9.0%
2 981
 
8.2%
6 756
 
6.3%
4 741
 
6.2%
3 738
 
6.2%
5 735
 
6.2%
8 638
 
5.3%
9 560
 
4.7%
Other values (2) 477
 
4.0%

소재지우편번호
Real number (ℝ)

Distinct645
Distinct (%)18.1%
Missing33
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean610576.51
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:34.656201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601705
Q1604845
median611807.5
Q3614847
95-th percentile619901
Maximum619953
Range19942
Interquartile range (IQR)10002

Descriptive statistics

Standard deviation5834.071
Coefficient of variation (CV)0.0095550204
Kurtosis-1.1585415
Mean610576.51
Median Absolute Deviation (MAD)5013
Skewness-0.12785655
Sum2.1712101 × 109
Variance34036384
MonotonicityNot monotonic
2024-04-18T11:32:34.813308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604842 78
 
2.2%
602030 74
 
2.1%
614843 68
 
1.9%
617831 62
 
1.7%
601803 54
 
1.5%
619904 53
 
1.5%
607804 48
 
1.3%
604843 48
 
1.3%
604846 47
 
1.3%
612020 40
 
1.1%
Other values (635) 2984
83.1%
ValueCountFrequency (%)
600011 1
 
< 0.1%
600012 2
 
0.1%
600015 1
 
< 0.1%
600016 4
 
0.1%
600017 17
0.5%
600021 1
 
< 0.1%
600022 1
 
< 0.1%
600031 1
 
< 0.1%
600032 1
 
< 0.1%
600041 35
1.0%
ValueCountFrequency (%)
619953 1
 
< 0.1%
619952 4
 
0.1%
619951 9
 
0.3%
619913 5
 
0.1%
619912 10
 
0.3%
619911 5
 
0.1%
619906 20
 
0.6%
619905 18
 
0.5%
619904 53
1.5%
619903 30
0.8%
Distinct2765
Distinct (%)77.1%
Missing2
Missing (%)0.1%
Memory size28.2 KiB
2024-04-18T11:32:35.096487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length57
Mean length24.858099
Min length16

Characters and Unicode

Total characters89166
Distinct characters373
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2439 ?
Unique (%)68.0%

Sample

1st row부산광역시 동래구 사직동 114-46번지
2nd row부산광역시 동래구 안락동 243-57번지 1층
3rd row부산광역시 동래구 안락동 425-4번지 1층
4th row부산광역시 동래구 사직동 28-9번지
5th row부산광역시 동래구 명륜동 515-43번지
ValueCountFrequency (%)
부산광역시 3588
 
21.4%
사하구 528
 
3.1%
해운대구 386
 
2.3%
부산진구 362
 
2.2%
사상구 282
 
1.7%
동래구 267
 
1.6%
금정구 230
 
1.4%
장림동 223
 
1.3%
기장군 218
 
1.3%
북구 202
 
1.2%
Other values (3201) 10506
62.6%
2024-04-18T11:32:35.523624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13221
 
14.8%
4435
 
5.0%
4286
 
4.8%
4086
 
4.6%
3839
 
4.3%
1 3785
 
4.2%
3714
 
4.2%
3661
 
4.1%
3595
 
4.0%
3494
 
3.9%
Other values (363) 41050
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54834
61.5%
Decimal Number 17156
 
19.2%
Space Separator 13221
 
14.8%
Dash Punctuation 3029
 
3.4%
Uppercase Letter 310
 
0.3%
Close Punctuation 219
 
0.2%
Open Punctuation 219
 
0.2%
Other Punctuation 173
 
0.2%
Lowercase Letter 3
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4435
 
8.1%
4286
 
7.8%
4086
 
7.5%
3839
 
7.0%
3714
 
6.8%
3661
 
6.7%
3595
 
6.6%
3494
 
6.4%
3380
 
6.2%
880
 
1.6%
Other values (325) 19464
35.5%
Uppercase Letter
ValueCountFrequency (%)
B 129
41.6%
T 89
28.7%
G 26
 
8.4%
A 25
 
8.1%
S 21
 
6.8%
L 8
 
2.6%
E 3
 
1.0%
K 2
 
0.6%
O 1
 
0.3%
C 1
 
0.3%
Other values (5) 5
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 3785
22.1%
2 2327
13.6%
3 1865
10.9%
5 1691
9.9%
4 1477
 
8.6%
0 1408
 
8.2%
6 1403
 
8.2%
7 1244
 
7.3%
8 1014
 
5.9%
9 942
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 150
86.7%
. 12
 
6.9%
@ 9
 
5.2%
/ 2
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
c 1
33.3%
s 1
33.3%
e 1
33.3%
Space Separator
ValueCountFrequency (%)
13221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3029
100.0%
Close Punctuation
ValueCountFrequency (%)
) 219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 219
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54833
61.5%
Common 34019
38.2%
Latin 313
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4435
 
8.1%
4286
 
7.8%
4086
 
7.5%
3839
 
7.0%
3714
 
6.8%
3661
 
6.7%
3595
 
6.6%
3494
 
6.4%
3380
 
6.2%
880
 
1.6%
Other values (324) 19463
35.5%
Common
ValueCountFrequency (%)
13221
38.9%
1 3785
 
11.1%
- 3029
 
8.9%
2 2327
 
6.8%
3 1865
 
5.5%
5 1691
 
5.0%
4 1477
 
4.3%
0 1408
 
4.1%
6 1403
 
4.1%
7 1244
 
3.7%
Other values (10) 2569
 
7.6%
Latin
ValueCountFrequency (%)
B 129
41.2%
T 89
28.4%
G 26
 
8.3%
A 25
 
8.0%
S 21
 
6.7%
L 8
 
2.6%
E 3
 
1.0%
K 2
 
0.6%
c 1
 
0.3%
O 1
 
0.3%
Other values (8) 8
 
2.6%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54833
61.5%
ASCII 34332
38.5%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13221
38.5%
1 3785
 
11.0%
- 3029
 
8.8%
2 2327
 
6.8%
3 1865
 
5.4%
5 1691
 
4.9%
4 1477
 
4.3%
0 1408
 
4.1%
6 1403
 
4.1%
7 1244
 
3.6%
Other values (28) 2882
 
8.4%
Hangul
ValueCountFrequency (%)
4435
 
8.1%
4286
 
7.8%
4086
 
7.5%
3839
 
7.0%
3714
 
6.8%
3661
 
6.7%
3595
 
6.6%
3494
 
6.4%
3380
 
6.2%
880
 
1.6%
Other values (324) 19463
35.5%
CJK
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1736
Distinct (%)92.8%
Missing1719
Missing (%)47.9%
Memory size28.2 KiB
2024-04-18T11:32:35.831821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length55
Mean length31.15508
Min length19

Characters and Unicode

Total characters58260
Distinct characters397
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1644 ?
Unique (%)87.9%

Sample

1st row부산광역시 동래구 아시아드대로114번길 28-1, 1층 (사직동)
2nd row부산광역시 동래구 안남로 112, 1층 (안락동)
3rd row부산광역시 동래구 안락로 14, 1층 (안락동)
4th row부산광역시 동래구 사직북로33번길 34, 1층 (사직동)
5th row부산광역시 동래구 충렬대로182번가길 26, 1층 (명륜동)
ValueCountFrequency (%)
부산광역시 1871
 
16.7%
1층 370
 
3.3%
사하구 304
 
2.7%
해운대구 195
 
1.7%
부산진구 171
 
1.5%
기장군 164
 
1.5%
2층 145
 
1.3%
사상구 144
 
1.3%
장림동 116
 
1.0%
금정구 112
 
1.0%
Other values (2236) 7606
67.9%
2024-04-18T11:32:36.294494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9333
 
16.0%
1 2395
 
4.1%
2384
 
4.1%
2360
 
4.1%
2254
 
3.9%
2081
 
3.6%
1940
 
3.3%
1876
 
3.2%
1827
 
3.1%
1791
 
3.1%
Other values (387) 30019
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34440
59.1%
Space Separator 9333
 
16.0%
Decimal Number 9073
 
15.6%
Open Punctuation 1785
 
3.1%
Close Punctuation 1785
 
3.1%
Other Punctuation 1427
 
2.4%
Dash Punctuation 299
 
0.5%
Uppercase Letter 105
 
0.2%
Math Symbol 10
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2384
 
6.9%
2360
 
6.9%
2254
 
6.5%
2081
 
6.0%
1940
 
5.6%
1876
 
5.4%
1827
 
5.3%
1791
 
5.2%
926
 
2.7%
851
 
2.5%
Other values (349) 16150
46.9%
Uppercase Letter
ValueCountFrequency (%)
B 44
41.9%
A 35
33.3%
C 5
 
4.8%
G 4
 
3.8%
S 4
 
3.8%
E 2
 
1.9%
K 2
 
1.9%
H 1
 
1.0%
Q 1
 
1.0%
V 1
 
1.0%
Other values (6) 6
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 2395
26.4%
2 1374
15.1%
3 933
 
10.3%
4 790
 
8.7%
5 785
 
8.7%
0 679
 
7.5%
6 657
 
7.2%
7 598
 
6.6%
9 465
 
5.1%
8 397
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 1420
99.5%
. 3
 
0.2%
@ 3
 
0.2%
/ 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
b 1
33.3%
c 1
33.3%
s 1
33.3%
Space Separator
ValueCountFrequency (%)
9333
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1785
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1785
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 299
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34440
59.1%
Common 23712
40.7%
Latin 108
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2384
 
6.9%
2360
 
6.9%
2254
 
6.5%
2081
 
6.0%
1940
 
5.6%
1876
 
5.4%
1827
 
5.3%
1791
 
5.2%
926
 
2.7%
851
 
2.5%
Other values (349) 16150
46.9%
Common
ValueCountFrequency (%)
9333
39.4%
1 2395
 
10.1%
( 1785
 
7.5%
) 1785
 
7.5%
, 1420
 
6.0%
2 1374
 
5.8%
3 933
 
3.9%
4 790
 
3.3%
5 785
 
3.3%
0 679
 
2.9%
Other values (9) 2433
 
10.3%
Latin
ValueCountFrequency (%)
B 44
40.7%
A 35
32.4%
C 5
 
4.6%
G 4
 
3.7%
S 4
 
3.7%
E 2
 
1.9%
K 2
 
1.9%
H 1
 
0.9%
b 1
 
0.9%
c 1
 
0.9%
Other values (9) 9
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34440
59.1%
ASCII 23820
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9333
39.2%
1 2395
 
10.1%
( 1785
 
7.5%
) 1785
 
7.5%
, 1420
 
6.0%
2 1374
 
5.8%
3 933
 
3.9%
4 790
 
3.3%
5 785
 
3.3%
0 679
 
2.9%
Other values (28) 2541
 
10.7%
Hangul
ValueCountFrequency (%)
2384
 
6.9%
2360
 
6.9%
2254
 
6.5%
2081
 
6.0%
1940
 
5.6%
1876
 
5.4%
1827
 
5.3%
1791
 
5.2%
926
 
2.7%
851
 
2.5%
Other values (349) 16150
46.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct755
Distinct (%)41.1%
Missing1751
Missing (%)48.8%
Infinite0
Infinite (%)0.0%
Mean47865.616
Minimum46002
Maximum49526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:36.426423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46067.85
Q146926.25
median48013
Q348984
95-th percentile49478
Maximum49526
Range3524
Interquartile range (IQR)2057.75

Descriptive statistics

Standard deviation1157.6773
Coefficient of variation (CV)0.02418599
Kurtosis-1.3311348
Mean47865.616
Median Absolute Deviation (MAD)1029.5
Skewness-0.038956294
Sum87977002
Variance1340216.8
MonotonicityNot monotonic
2024-04-18T11:32:36.555390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49277 48
 
1.3%
46079 40
 
1.1%
47032 35
 
1.0%
49478 34
 
0.9%
48984 31
 
0.9%
47252 28
 
0.8%
48737 28
 
0.8%
48031 24
 
0.7%
48983 22
 
0.6%
47251 17
 
0.5%
Other values (745) 1531
42.7%
(Missing) 1751
48.8%
ValueCountFrequency (%)
46002 2
0.1%
46004 2
0.1%
46008 2
0.1%
46012 2
0.1%
46014 1
 
< 0.1%
46017 3
0.1%
46019 1
 
< 0.1%
46020 4
0.1%
46022 3
0.1%
46023 1
 
< 0.1%
ValueCountFrequency (%)
49526 15
0.4%
49525 1
 
< 0.1%
49523 1
 
< 0.1%
49522 1
 
< 0.1%
49520 3
 
0.1%
49519 6
 
0.2%
49514 1
 
< 0.1%
49511 4
 
0.1%
49507 1
 
< 0.1%
49503 3
 
0.1%
Distinct2659
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
2024-04-18T11:32:36.795696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length5.9116746
Min length2

Characters and Unicode

Total characters21217
Distinct characters630
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

Unique2271 ?
Unique (%)63.3%

Sample

1st row부성상사
2nd row더월마트
3rd row탑플러스마트
4th row(주)서원유통탑마트사직점
5th row찡오언니
ValueCountFrequency (%)
주식회사 82
 
2.1%
영우유통 31
 
0.8%
주)두루찬 31
 
0.8%
진경식품 29
 
0.7%
개미농특산 27
 
0.7%
우리농수산 22
 
0.6%
현식품 20
 
0.5%
남해식품 18
 
0.5%
민속식품 18
 
0.5%
하복식품 18
 
0.5%
Other values (2762) 3655
92.5%
2024-04-18T11:32:37.178436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
943
 
4.4%
) 870
 
4.1%
854
 
4.0%
( 846
 
4.0%
741
 
3.5%
495
 
2.3%
424
 
2.0%
402
 
1.9%
400
 
1.9%
388
 
1.8%
Other values (620) 14854
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18718
88.2%
Close Punctuation 870
 
4.1%
Open Punctuation 846
 
4.0%
Space Separator 363
 
1.7%
Uppercase Letter 259
 
1.2%
Decimal Number 68
 
0.3%
Lowercase Letter 56
 
0.3%
Other Punctuation 33
 
0.2%
Dash Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
943
 
5.0%
854
 
4.6%
741
 
4.0%
495
 
2.6%
424
 
2.3%
402
 
2.1%
400
 
2.1%
388
 
2.1%
320
 
1.7%
312
 
1.7%
Other values (558) 13439
71.8%
Uppercase Letter
ValueCountFrequency (%)
O 29
 
11.2%
F 29
 
11.2%
S 17
 
6.6%
C 16
 
6.2%
A 16
 
6.2%
N 15
 
5.8%
D 15
 
5.8%
G 15
 
5.8%
E 12
 
4.6%
M 12
 
4.6%
Other values (15) 83
32.0%
Lowercase Letter
ValueCountFrequency (%)
a 9
16.1%
s 8
14.3%
n 8
14.3%
e 5
8.9%
r 5
8.9%
m 4
7.1%
o 3
 
5.4%
i 3
 
5.4%
t 2
 
3.6%
d 2
 
3.6%
Other values (7) 7
12.5%
Decimal Number
ValueCountFrequency (%)
2 19
27.9%
3 15
22.1%
1 12
17.6%
8 6
 
8.8%
5 4
 
5.9%
9 4
 
5.9%
7 3
 
4.4%
4 2
 
2.9%
6 2
 
2.9%
0 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 14
42.4%
& 11
33.3%
, 6
18.2%
· 1
 
3.0%
' 1
 
3.0%
Close Punctuation
ValueCountFrequency (%)
) 870
100.0%
Open Punctuation
ValueCountFrequency (%)
( 846
100.0%
Space Separator
ValueCountFrequency (%)
363
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18718
88.2%
Common 2184
 
10.3%
Latin 315
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
943
 
5.0%
854
 
4.6%
741
 
4.0%
495
 
2.6%
424
 
2.3%
402
 
2.1%
400
 
2.1%
388
 
2.1%
320
 
1.7%
312
 
1.7%
Other values (558) 13439
71.8%
Latin
ValueCountFrequency (%)
O 29
 
9.2%
F 29
 
9.2%
S 17
 
5.4%
C 16
 
5.1%
A 16
 
5.1%
N 15
 
4.8%
D 15
 
4.8%
G 15
 
4.8%
E 12
 
3.8%
M 12
 
3.8%
Other values (32) 139
44.1%
Common
ValueCountFrequency (%)
) 870
39.8%
( 846
38.7%
363
16.6%
2 19
 
0.9%
3 15
 
0.7%
. 14
 
0.6%
1 12
 
0.5%
& 11
 
0.5%
8 6
 
0.3%
, 6
 
0.3%
Other values (10) 22
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18718
88.2%
ASCII 2498
 
11.8%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
943
 
5.0%
854
 
4.6%
741
 
4.0%
495
 
2.6%
424
 
2.3%
402
 
2.1%
400
 
2.1%
388
 
2.1%
320
 
1.7%
312
 
1.7%
Other values (558) 13439
71.8%
ASCII
ValueCountFrequency (%)
) 870
34.8%
( 846
33.9%
363
14.5%
O 29
 
1.2%
F 29
 
1.2%
2 19
 
0.8%
S 17
 
0.7%
C 16
 
0.6%
A 16
 
0.6%
N 15
 
0.6%
Other values (51) 278
 
11.1%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

Distinct2898
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0106519 × 1013
Minimum1.9990315 × 1013
Maximum2.0210129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:37.323575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990315 × 1013
5-th percentile2.0011117 × 1013
Q12.0050401 × 1013
median2.0100802 × 1013
Q32.0170818 × 1013
95-th percentile2.0200803 × 1013
Maximum2.0210129 × 1013
Range2.1981415 × 1011
Interquartile range (IQR)1.2041715 × 1011

Descriptive statistics

Standard deviation6.4985258 × 1010
Coefficient of variation (CV)0.0032320491
Kurtosis-1.4024441
Mean2.0106519 × 1013
Median Absolute Deviation (MAD)6.0103952 × 1010
Skewness0.056728418
Sum7.2162298 × 1016
Variance4.2230838 × 1021
MonotonicityNot monotonic
2024-04-18T11:32:37.448410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20010731000000 48
 
1.3%
20020612000000 32
 
0.9%
20020805000000 31
 
0.9%
20020227000000 31
 
0.9%
20020305000000 29
 
0.8%
20010728000000 24
 
0.7%
20040618000000 22
 
0.6%
20020214000000 21
 
0.6%
20020823000000 16
 
0.4%
20010510000000 14
 
0.4%
Other values (2888) 3321
92.5%
ValueCountFrequency (%)
19990315000000 4
0.1%
19990318000000 1
 
< 0.1%
19990322000000 1
 
< 0.1%
19990510000000 1
 
< 0.1%
19990903000000 1
 
< 0.1%
19990918000000 1
 
< 0.1%
19990927000000 2
0.1%
19991012000000 1
 
< 0.1%
19991125000000 1
 
< 0.1%
20000209000000 1
 
< 0.1%
ValueCountFrequency (%)
20210129154627 1
< 0.1%
20210129115011 1
< 0.1%
20210129114643 1
< 0.1%
20210129103247 1
< 0.1%
20210128162143 1
< 0.1%
20210128110609 1
< 0.1%
20210127155638 1
< 0.1%
20210127155558 1
< 0.1%
20210127150527 1
< 0.1%
20210127144512 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
I
3025 
U
564 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowU
2nd rowI
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 3025
84.3%
U 564
 
15.7%

Length

2024-04-18T11:32:37.564546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:37.652407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3025
84.3%
u 564
 
15.7%
Distinct438
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-31 02:40:00
2024-04-18T11:32:37.750697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T11:32:37.876890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
식품소분업
3585 
<NA>
 
4

Length

Max length5
Median length5
Mean length4.9988855
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 3585
99.9%
<NA> 4
 
0.1%

Length

2024-04-18T11:32:37.999729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:38.090878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 3585
99.9%
na 4
 
0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1962
Distinct (%)57.4%
Missing168
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean387278.68
Minimum364927.7
Maximum407820.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:38.188423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum364927.7
5-th percentile378647.02
Q1382202.14
median387539.77
Q3391333.59
95-th percentile401172.34
Maximum407820.17
Range42892.471
Interquartile range (IQR)9131.4476

Descriptive statistics

Standard deviation6523.9594
Coefficient of variation (CV)0.016845646
Kurtosis0.14862057
Mean387278.68
Median Absolute Deviation (MAD)4549.6632
Skewness0.33878677
Sum1.3248804 × 109
Variance42562046
MonotonicityNot monotonic
2024-04-18T11:32:38.313920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387539.767677801 53
 
1.5%
387271.299492377 49
 
1.4%
389097.800933845 46
 
1.3%
389455.109101676 43
 
1.2%
390319.153766629 37
 
1.0%
387564.611330896 36
 
1.0%
393233.931123062 34
 
0.9%
382983.91775577 32
 
0.9%
383449.669961635 31
 
0.9%
379321.651090423 29
 
0.8%
Other values (1952) 3031
84.5%
(Missing) 168
 
4.7%
ValueCountFrequency (%)
364927.696730227 1
 
< 0.1%
367163.559903774 1
 
< 0.1%
367390.559894293 1
 
< 0.1%
367947.282236205 1
 
< 0.1%
368550.469102158 1
 
< 0.1%
368725.685782611 1
 
< 0.1%
368902.33317113 1
 
< 0.1%
368967.073191522 1
 
< 0.1%
369324.667538937 3
0.1%
369510.064865473 2
0.1%
ValueCountFrequency (%)
407820.16806719 1
< 0.1%
407418.648415535 1
< 0.1%
407245.567193252 2
0.1%
406761.100883744 1
< 0.1%
405571.252933322 1
< 0.1%
405546.316597851 1
< 0.1%
405482.261906849 1
< 0.1%
405236.333123992 1
< 0.1%
405188.961854622 2
0.1%
404883.27844185 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct1961
Distinct (%)57.3%
Missing168
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean186472.31
Minimum170813.58
Maximum211459
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:38.436932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170813.58
5-th percentile176373.96
Q1180266.54
median186663.89
Q3191546.13
95-th percentile196546.36
Maximum211459
Range40645.417
Interquartile range (IQR)11279.588

Descriptive statistics

Standard deviation6639.7263
Coefficient of variation (CV)0.035607037
Kurtosis-0.41150493
Mean186472.31
Median Absolute Deviation (MAD)5281.1124
Skewness0.18575752
Sum6.3792177 × 108
Variance44085966
MonotonicityNot monotonic
2024-04-18T11:32:38.566351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
184402.96650913 53
 
1.5%
186099.137533193 49
 
1.4%
192260.811648263 46
 
1.3%
191427.549247975 43
 
1.2%
195305.783615849 37
 
1.0%
183837.166587761 36
 
1.0%
192684.487637586 34
 
0.9%
196375.470354374 32
 
0.9%
174683.069423816 31
 
0.9%
183030.975769364 29
 
0.8%
Other values (1951) 3031
84.5%
(Missing) 168
 
4.7%
ValueCountFrequency (%)
170813.584718477 1
 
< 0.1%
173969.719902491 1
 
< 0.1%
174209.665999624 1
 
< 0.1%
174211.496764498 1
 
< 0.1%
174289.976688419 1
 
< 0.1%
174353.431844675 1
 
< 0.1%
174415.425547526 6
0.2%
174419.270504403 1
 
< 0.1%
174422.347875421 1
 
< 0.1%
174428.418993288 2
 
0.1%
ValueCountFrequency (%)
211459.001777975 1
< 0.1%
210945.104382171 1
< 0.1%
210855.07033937 1
< 0.1%
209943.892133999 1
< 0.1%
208399.251667629 1
< 0.1%
206512.517255249 1
< 0.1%
206150.925111083 1
< 0.1%
205930.084201689 1
< 0.1%
205620.650144116 1
< 0.1%
205540.482346069 2
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
식품소분업
3585 
<NA>
 
4

Length

Max length5
Median length5
Mean length4.9988855
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 3585
99.9%
<NA> 4
 
0.1%

Length

2024-04-18T11:32:38.693138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:38.785104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 3585
99.9%
na 4
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
<NA>
3158 
0
422 
1
 
9

Length

Max length4
Median length4
Mean length3.6397325
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3158
88.0%
0 422
 
11.8%
1 9
 
0.3%

Length

2024-04-18T11:32:38.901923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:39.009914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3158
88.0%
0 422
 
11.8%
1 9
 
0.3%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
<NA>
3158 
0
423 
1
 
8

Length

Max length4
Median length4
Mean length3.6397325
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3158
88.0%
0 423
 
11.8%
1 8
 
0.2%

Length

2024-04-18T11:32:39.109896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:39.204647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3158
88.0%
0 423
 
11.8%
1 8
 
0.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
<NA>
2918 
기타
644 
주택가주변
 
15
아파트지역
 
7
학교정화(상대)
 
4

Length

Max length8
Median length4
Mean length3.6528281
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2918
81.3%
기타 644
 
17.9%
주택가주변 15
 
0.4%
아파트지역 7
 
0.2%
학교정화(상대) 4
 
0.1%
유흥업소밀집지역 1
 
< 0.1%

Length

2024-04-18T11:32:39.305712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:39.406978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2918
81.3%
기타 644
 
17.9%
주택가주변 15
 
0.4%
아파트지역 7
 
0.2%
학교정화(상대 4
 
0.1%
유흥업소밀집지역 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
<NA>
2918 
기타
636 
자율
 
35

Length

Max length4
Median length4
Mean length3.6260797
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2918
81.3%
기타 636
 
17.7%
자율 35
 
1.0%

Length

2024-04-18T11:32:39.521955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:39.622788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2918
81.3%
기타 636
 
17.7%
자율 35
 
1.0%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
<NA>
3045 
상수도전용
540 
간이상수도
 
3
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.1515743
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3045
84.8%
상수도전용 540
 
15.0%
간이상수도 3
 
0.1%
지하수전용 1
 
< 0.1%

Length

2024-04-18T11:32:39.720392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:39.829334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3045
84.8%
상수도전용 540
 
15.0%
간이상수도 3
 
0.1%
지하수전용 1
 
< 0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3589
Missing (%)100.0%
Memory size31.7 KiB
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
0
1832 
<NA>
1754 
1
 
2
3
 
1

Length

Max length4
Median length1
Mean length2.4661466
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1832
51.0%
<NA> 1754
48.9%
1 2
 
0.1%
3 1
 
< 0.1%

Length

2024-04-18T11:32:39.943306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:40.046239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1832
51.0%
na 1754
48.9%
1 2
 
0.1%
3 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
0
1827 
<NA>
1753 
1
 
7
3
 
1
2
 
1

Length

Max length4
Median length1
Mean length2.4653107
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1827
50.9%
<NA> 1753
48.8%
1 7
 
0.2%
3 1
 
< 0.1%
2 1
 
< 0.1%

Length

2024-04-18T11:32:40.151306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:40.258047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1827
50.9%
na 1753
48.8%
1 7
 
0.2%
3 1
 
< 0.1%
2 1
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
0
1823 
<NA>
1752 
1
 
10
2
 
3
3
 
1

Length

Max length4
Median length1
Mean length2.4644748
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1823
50.8%
<NA> 1752
48.8%
1 10
 
0.3%
2 3
 
0.1%
3 1
 
< 0.1%

Length

2024-04-18T11:32:40.365830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:40.477437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1823
50.8%
na 1752
48.8%
1 10
 
0.3%
2 3
 
0.1%
3 1
 
< 0.1%

공장생산직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct7
Distinct (%)0.4%
Missing1748
Missing (%)48.7%
Infinite0
Infinite (%)0.0%
Mean0.66431287
Minimum0
Maximum1170
Zeros1802
Zeros (%)50.2%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:40.564185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1170
Range1170
Interquartile range (IQR)0

Descriptive statistics

Standard deviation27.268697
Coefficient of variation (CV)41.047973
Kurtosis1840.7265
Mean0.66431287
Median Absolute Deviation (MAD)0
Skewness42.902105
Sum1223
Variance743.58182
MonotonicityNot monotonic
2024-04-18T11:32:40.660338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1802
50.2%
1 29
 
0.8%
2 6
 
0.2%
4 1
 
< 0.1%
1170 1
 
< 0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
(Missing) 1748
48.7%
ValueCountFrequency (%)
0 1802
50.2%
1 29
 
0.8%
2 6
 
0.2%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
1170 1
 
< 0.1%
ValueCountFrequency (%)
1170 1
 
< 0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%
2 6
 
0.2%
1 29
 
0.8%
0 1802
50.2%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
<NA>
2737 
자가
536 
임대
316 

Length

Max length4
Median length4
Mean length3.5252159
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2737
76.3%
자가 536
 
14.9%
임대 316
 
8.8%

Length

2024-04-18T11:32:40.780264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:40.882649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2737
76.3%
자가 536
 
14.9%
임대 316
 
8.8%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
<NA>
3423 
0
 
166

Length

Max length4
Median length4
Mean length3.8612427
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3423
95.4%
0 166
 
4.6%

Length

2024-04-18T11:32:40.994447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:41.090715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3423
95.4%
0 166
 
4.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
<NA>
3423 
0
 
166

Length

Max length4
Median length4
Mean length3.8612427
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3423
95.4%
0 166
 
4.6%

Length

2024-04-18T11:32:41.187351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:41.279795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3423
95.4%
0 166
 
4.6%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
False
3589 
ValueCountFrequency (%)
False 3589
100.0%
2024-04-18T11:32:41.358835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct183
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4776372
Minimum0
Maximum1011.02
Zeros3344
Zeros (%)93.2%
Negative0
Negative (%)0.0%
Memory size31.7 KiB
2024-04-18T11:32:42.216966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.12
Maximum1011.02
Range1011.02
Interquartile range (IQR)0

Descriptive statistics

Standard deviation21.939538
Coefficient of variation (CV)8.8550246
Kurtosis1271.4375
Mean2.4776372
Median Absolute Deviation (MAD)0
Skewness29.978524
Sum8892.24
Variance481.34335
MonotonicityNot monotonic
2024-04-18T11:32:42.337054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3344
93.2%
10.0 8
 
0.2%
4.0 8
 
0.2%
6.6 7
 
0.2%
9.9 6
 
0.2%
3.0 5
 
0.1%
16.5 4
 
0.1%
33.0 4
 
0.1%
3.3 4
 
0.1%
12.0 3
 
0.1%
Other values (173) 196
 
5.5%
ValueCountFrequency (%)
0.0 3344
93.2%
0.58 1
 
< 0.1%
1.0 1
 
< 0.1%
1.17 2
 
0.1%
1.44 1
 
< 0.1%
1.51 1
 
< 0.1%
1.6 1
 
< 0.1%
1.7 2
 
0.1%
1.95 1
 
< 0.1%
2.0 1
 
< 0.1%
ValueCountFrequency (%)
1011.02 1
< 0.1%
319.5 1
< 0.1%
246.24 1
< 0.1%
226.98 1
< 0.1%
194.7 1
< 0.1%
175.0 1
< 0.1%
174.89 1
< 0.1%
172.55 1
< 0.1%
157.93 1
< 0.1%
132.0 2
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3589
Missing (%)100.0%
Memory size31.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3589
Missing (%)100.0%
Memory size31.7 KiB

홈페이지
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.2 KiB
<NA>
3588 
8
 
1

Length

Max length4
Median length4
Mean length3.9991641
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3588
> 99.9%
8 1
 
< 0.1%

Length

2024-04-18T11:32:42.461688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:32:42.556598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3588
> 99.9%
8 1
 
< 0.1%

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3589
Missing (%)100.0%
Memory size31.7 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01식품소분업07_22_08_P33000003300000-109-2011-0000620110223<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.53607821부산광역시 동래구 사직동 114-46번지부산광역시 동래구 아시아드대로114번길 28-1, 1층 (사직동)47845부성상사20180920095551U2018-09-20 23:59:59.0식품소분업392206.237892190039.60345식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
12식품소분업07_22_08_P33000003300000-109-2014-0000620140811<NA>1영업/정상1영업<NA><NA><NA><NA>051 531 828229.50607825부산광역시 동래구 안락동 243-57번지 1층부산광역시 동래구 안남로 112, 1층 (안락동)47900더월마트20140811114122I2018-08-31 23:59:59.0식품소분업391562.200354190165.951521식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
23식품소분업07_22_08_P33000003300000-109-2014-0000720141007<NA>1영업/정상1영업<NA><NA><NA><NA>051 529 50058.00607827부산광역시 동래구 안락동 425-4번지 1층부산광역시 동래구 안락로 14, 1층 (안락동)47786탑플러스마트20141007153821I2018-08-31 23:59:59.0식품소분업391050.74744191065.280568식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
34식품소분업07_22_08_P33000003300000-109-2017-0000420170830<NA>1영업/정상1영업<NA><NA><NA><NA>051501581010.00607815부산광역시 동래구 사직동 28-9번지부산광역시 동래구 사직북로33번길 34, 1층 (사직동)47860(주)서원유통탑마트사직점20170901112355I2018-08-31 23:59:59.0식품소분업387382.806313190792.095628식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
45식품소분업07_22_08_P33000003300000-109-2017-0000520171206<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.20607804부산광역시 동래구 명륜동 515-43번지부산광역시 동래구 충렬대로182번가길 26, 1층 (명륜동)47815찡오언니20180102101523I2018-08-31 23:59:59.0식품소분업389358.8991191229.69749식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
56식품소분업07_22_08_P33800003380000-109-2015-0000420150518<NA>1영업/정상1영업<NA><NA><NA><NA>051 756 999155.50613804부산광역시 수영구 광안동 151-23번지부산광역시 수영구 광안로 37, 1,2층 (광안동)48296농축산마트20151203160903I2018-08-31 23:59:59.0식품소분업392776.170928186106.557382식품소분업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
67식품소분업07_22_08_P33800003380000-109-2010-0000120100223<NA>1영업/정상1영업<NA><NA><NA><NA>051 751 160016.00613828부산광역시 수영구 민락동 35-8번지부산광역시 수영구 광안해변로277번길 18 (민락동)48287(주)자이마트20110930170550I2018-08-31 23:59:59.0식품소분업393508.751358186240.494914식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
78식품소분업07_22_08_P33000003300000-109-2017-0000620171218<NA>1영업/정상1영업<NA><NA><NA><NA>051521825316.00607830부산광역시 동래구 안락동 603-1번지 안락시장상가아파트부산광역시 동래구 충렬대로410번길 21, 19호 (안락동, 안락시장상가아파트)47890창대식품20180102103939I2018-08-31 23:59:59.0식품소분업391486.787091190515.879939식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
89식품소분업07_22_08_P33000003300000-109-2018-0000120180214<NA>1영업/정상1영업<NA><NA><NA><NA>051 554 077520.60607831부산광역시 동래구 온천동 147-48번지부산광역시 동래구 온천장로125번길 29, 1층 (온천동)47708대영상사20180221171558I2018-08-31 23:59:59.0식품소분업389652.962403193482.631799식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
910식품소분업07_22_08_P33000003300000-109-2018-0000220180517<NA>1영업/정상1영업<NA><NA><NA><NA>051555720015.40607802부산광역시 동래구 명륜동 9-2번지부산광역시 동래구 시실로24번길 5, 1층 (명륜동)47744지마트 명륜점20180530173644I2018-08-31 23:59:59.0식품소분업389897.081046192781.060821식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
35793580식품소분업07_22_08_P33300003330000-109-2016-0000320160318<NA>3폐업2폐업20191113<NA><NA><NA>051 724 7781100.00612040부산광역시 해운대구 송정동 189-20번지부산광역시 해운대구 송정중앙로21번길 67, 1층 (송정동)48070우진유통20191113153406U2019-11-15 02:40:00.0식품소분업400753.655089189624.712393식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
35803581식품소분업07_22_08_P33300003330000-109-2016-0000420160323<NA>3폐업2폐업20160810<NA><NA><NA><NA>78.00612810부산광역시 해운대구 반여동 763-11번지부산광역시 해운대구 선수촌로207번가길 21, 1층 (반여동)48032채미원20160323152229I2018-08-31 23:59:59.0식품소분업393332.617596192155.203339식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
35813582식품소분업07_22_08_P33300003330000-109-2013-0000520131113<NA>3폐업2폐업20150427<NA><NA><NA><NA>10.14612809부산광역시 해운대구 반여동 232-3번지 1층 일부부산광역시 해운대구 선수촌로208번길 87 (반여동, 1층 일부)48033안선20140417104417I2018-08-31 23:59:59.0식품소분업393818.650605192435.131519식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
35823583식품소분업07_22_08_P33300003330000-109-2014-0000320140331<NA>3폐업2폐업20141219<NA><NA><NA>051 723 02359.86612809부산광역시 해운대구 반여동 910-1번지부산광역시 해운대구 선수촌로 164-10 (반여동)48034(주)풍년방20140415172558I2018-08-31 23:59:59.0식품소분업393256.407763191848.772596식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N4.55<NA><NA><NA><NA>
35833584식품소분업07_22_08_P33300003330000-109-2014-0000420140503<NA>3폐업2폐업20150722<NA><NA><NA><NA>31.00612020부산광역시 해운대구 우동 1495번지 신세계백화점 지하1층 일부부산광역시 해운대구 센텀남대로 35 (우동, 신세계백화점 지하1층 일부)48058샘골잣집20140624092103I2018-08-31 23:59:59.0식품소분업393952.264486187602.933161식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
35843585식품소분업07_22_08_P33300003330000-109-2014-0000520141223<NA>3폐업2폐업20171018<NA><NA><NA><NA>9.87612809부산광역시 해운대구 반여동 910-1번지부산광역시 해운대구 선수촌로 164-10 (반여동)48034(주)풍년방20171018110811I2018-08-31 23:59:59.0식품소분업393256.407763191848.772596식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
35853586식품소분업07_22_08_P34000003400000-109-2018-0001220181228<NA>3폐업2폐업20200716<NA><NA><NA><NA>19.20619873부산광역시 기장군 철마면 송정리 363-12부산광역시 기장군 철마면 철마삼동로 58, 1층46002동우유통20200716161337U2020-09-16 02:40:00.0식품소분업392275.996065203203.409705식품소분업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
35863587식품소분업07_22_08_P33600003360000-109-2019-0000120190104<NA>3폐업2폐업20190620<NA><NA><NA>051 337 257816.12618800부산광역시 강서구 강동동 107-8번지부산광역시 강서구 낙동북로43번길 38-16, 일부 (강동동)46705(주)현백20190620140333U2019-06-22 02:40:00.0식품소분업376268.26048192826.372166식품소분업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
35873588식품소분업07_22_08_P33500003350000-109-2018-0000720181120<NA>3폐업2폐업20200320<NA><NA><NA><NA>6.60609801부산광역시 금정구 구서동 167-9번지부산광역시 금정구 중앙대로1945번길 21, 1층 (구서동)46230우영이네20200320143835U2020-03-22 02:40:00.0식품소분업390137.078464197397.134893식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
35883589식품소분업07_22_08_P33000003300000-109-2020-0000420201214<NA>3폐업2폐업20201228<NA><NA><NA><NA><NA>607802부산광역시 동래구 명륜동 98-17부산광역시 동래구 시실로 54, 2층 (명륜동)47744죽로재20201228160040U2020-12-30 02:40:00.0식품소분업390095.642233192619.170961식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>