Overview

Dataset statistics

Number of variables48
Number of observations3600
Missing cells37437
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

Description2021-04-01
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 (71.0%)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 3600 (100.0%) missing valuesMissing
폐업일자 has 1022 (28.4%) missing valuesMissing
휴업시작일자 has 3600 (100.0%) missing valuesMissing
휴업종료일자 has 3600 (100.0%) missing valuesMissing
재개업일자 has 3600 (100.0%) missing valuesMissing
소재지전화 has 984 (27.3%) missing valuesMissing
소재지면적 has 1037 (28.8%) missing valuesMissing
도로명전체주소 has 1719 (47.8%) missing valuesMissing
도로명우편번호 has 1751 (48.6%) missing valuesMissing
좌표정보(x) has 169 (4.7%) missing valuesMissing
좌표정보(y) has 169 (4.7%) missing valuesMissing
총종업원수 has 3600 (100.0%) missing valuesMissing
공장생산직종업원수 has 1751 (48.6%) missing valuesMissing
전통업소지정번호 has 3600 (100.0%) missing valuesMissing
전통업소주된음식 has 3600 (100.0%) missing valuesMissing
Unnamed: 47 has 3600 (100.0%) missing valuesMissing
공장생산직종업원수 is highly skewed (γ1 = 42.99521854)Skewed
시설총규모 is highly skewed (γ1 = 30.10409442)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 1810 (50.3%) zerosZeros
시설총규모 has 3354 (93.2%) zerosZeros

Reproduction

Analysis started2024-04-18 02:38:18.773494
Analysis finished2024-04-18 02:38:20.109423
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3600
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1800.5
Minimum1
Maximum3600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:20.173197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile180.95
Q1900.75
median1800.5
Q32700.25
95-th percentile3420.05
Maximum3600
Range3599
Interquartile range (IQR)1799.5

Descriptive statistics

Standard deviation1039.3748
Coefficient of variation (CV)0.5772701
Kurtosis-1.2
Mean1800.5
Median Absolute Deviation (MAD)900
Skewness0
Sum6481800
Variance1080300
MonotonicityStrictly increasing
2024-04-18T11:38:20.300412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2365 1
 
< 0.1%
2395 1
 
< 0.1%
2396 1
 
< 0.1%
2397 1
 
< 0.1%
2398 1
 
< 0.1%
2399 1
 
< 0.1%
2400 1
 
< 0.1%
2401 1
 
< 0.1%
2402 1
 
< 0.1%
Other values (3590) 3590
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 (%)
3600 1
< 0.1%
3599 1
< 0.1%
3598 1
< 0.1%
3597 1
< 0.1%
3596 1
< 0.1%
3595 1
< 0.1%
3594 1
< 0.1%
3593 1
< 0.1%
3592 1
< 0.1%
3591 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
식품소분업
3600 

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 3600
100.0%

Length

2024-04-18T11:38:20.433964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:20.516586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 3600
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
07_22_08_P
3600 

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 3600
100.0%

Length

2024-04-18T11:38:20.604464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:20.687694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_08_p 3600
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3327783.3
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:20.767669image/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 deviation42214.048
Coefficient of variation (CV)0.012685335
Kurtosis-0.8629285
Mean3327783.3
Median Absolute Deviation (MAD)30000
Skewness-0.029361564
Sum1.198002 × 1010
Variance1.7820258 × 109
MonotonicityNot monotonic
2024-04-18T11:38:20.868934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3340000 529
14.7%
3330000 387
10.8%
3290000 362
10.1%
3390000 283
 
7.9%
3300000 268
 
7.4%
3350000 231
 
6.4%
3400000 219
 
6.1%
3320000 202
 
5.6%
3270000 172
 
4.8%
3250000 170
 
4.7%
Other values (6) 777
21.6%
ValueCountFrequency (%)
3250000 170
 
4.7%
3260000 150
 
4.2%
3270000 172
 
4.8%
3280000 79
 
2.2%
3290000 362
10.1%
3300000 268
7.4%
3310000 152
 
4.2%
3320000 202
 
5.6%
3330000 387
10.8%
3340000 529
14.7%
ValueCountFrequency (%)
3400000 219
6.1%
3390000 283
7.9%
3380000 128
 
3.6%
3370000 131
 
3.6%
3360000 137
 
3.8%
3350000 231
6.4%
3340000 529
14.7%
3330000 387
10.8%
3320000 202
 
5.6%
3310000 152
 
4.2%

관리번호
Text

UNIQUE 

Distinct3600
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2024-04-18T11:38:21.051414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters79200
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

Unique3600 ?
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%
3330000-109-2015-00001 1
 
< 0.1%
3340000-109-2000-01015 1
 
< 0.1%
3340000-109-1999-00899 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%
Other values (3590) 3590
99.7%
2024-04-18T11:38:21.344091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 36176
45.7%
- 10800
 
13.6%
3 7346
 
9.3%
1 7078
 
8.9%
9 5823
 
7.4%
2 5552
 
7.0%
4 1695
 
2.1%
5 1329
 
1.7%
6 1237
 
1.6%
7 1122
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68400
86.4%
Dash Punctuation 10800
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 36176
52.9%
3 7346
 
10.7%
1 7078
 
10.3%
9 5823
 
8.5%
2 5552
 
8.1%
4 1695
 
2.5%
5 1329
 
1.9%
6 1237
 
1.8%
7 1122
 
1.6%
8 1042
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 10800
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79200
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 36176
45.7%
- 10800
 
13.6%
3 7346
 
9.3%
1 7078
 
8.9%
9 5823
 
7.4%
2 5552
 
7.0%
4 1695
 
2.1%
5 1329
 
1.7%
6 1237
 
1.6%
7 1122
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 36176
45.7%
- 10800
 
13.6%
3 7346
 
9.3%
1 7078
 
8.9%
9 5823
 
7.4%
2 5552
 
7.0%
4 1695
 
2.1%
5 1329
 
1.7%
6 1237
 
1.6%
7 1122
 
1.4%

인허가일자
Real number (ℝ)

Distinct2520
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20073077
Minimum19780414
Maximum20210226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:21.494378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19780414
5-th percentile19970428
Q120020518
median20061025
Q320130321
95-th percentile20191012
Maximum20210226
Range429812
Interquartile range (IQR)109803.25

Descriptive statistics

Standard deviation71304.15
Coefficient of variation (CV)0.0035522282
Kurtosis-0.24210792
Mean20073077
Median Absolute Deviation (MAD)50104.5
Skewness-0.026942121
Sum7.2263077 × 1010
Variance5.0842818 × 109
MonotonicityNot monotonic
2024-04-18T11:38:21.651579image/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
 
0.2%
20100111 7
 
0.2%
20060424 6
 
0.2%
20030721 6
 
0.2%
20010704 6
 
0.2%
20060921 6
 
0.2%
20110426 6
 
0.2%
20100113 6
 
0.2%
Other values (2510) 3526
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 (%)
20210226 1
 
< 0.1%
20210225 1
 
< 0.1%
20210223 1
 
< 0.1%
20210222 2
0.1%
20210219 1
 
< 0.1%
20210216 1
 
< 0.1%
20210215 3
0.1%
20210205 1
 
< 0.1%
20210129 2
0.1%
20210126 1
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3600
Missing (%)100.0%
Memory size31.8 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
3
2578 
1
1022 

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 2578
71.6%
1 1022
 
28.4%

Length

2024-04-18T11:38:21.776077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:21.871267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2578
71.6%
1 1022
 
28.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
폐업
2578 
영업/정상
1022 

Length

Max length5
Median length2
Mean length2.8516667
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 2578
71.6%
영업/정상 1022
 
28.4%

Length

2024-04-18T11:38:21.972800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:22.073100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2578
71.6%
영업/정상 1022
 
28.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2
2578 
1
1022 

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 2578
71.6%
1 1022
 
28.4%

Length

2024-04-18T11:38:22.187209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:22.283561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2578
71.6%
1 1022
 
28.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
폐업
2578 
영업
1022 

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 2578
71.6%
영업 1022
 
28.4%

Length

2024-04-18T11:38:22.382063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:22.469200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2578
71.6%
영업 1022
 
28.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct1787
Distinct (%)69.3%
Missing1022
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean20096043
Minimum19900725
Maximum20210225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:22.582459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19900725
5-th percentile20010595
Q120050913
median20090522
Q320141227
95-th percentile20200117
Maximum20210225
Range309500
Interquartile range (IQR)90314.25

Descriptive statistics

Standard deviation58372.789
Coefficient of variation (CV)0.0029046906
Kurtosis-0.76443818
Mean20096043
Median Absolute Deviation (MAD)40209.5
Skewness0.14114554
Sum5.18076 × 1010
Variance3.4073825 × 109
MonotonicityNot monotonic
2024-04-18T11:38:22.718322image/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%
20051102 10
 
0.3%
20050322 10
 
0.3%
20070820 9
 
0.2%
20060509 8
 
0.2%
20201231 8
 
0.2%
20201006 8
 
0.2%
20100318 7
 
0.2%
Other values (1777) 2464
68.4%
(Missing) 1022
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 (%)
20210225 1
< 0.1%
20210219 1
< 0.1%
20210216 2
0.1%
20210208 1
< 0.1%
20210205 1
< 0.1%
20210129 1
< 0.1%
20210127 2
0.1%
20210122 2
0.1%
20210120 1
< 0.1%
20210115 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3600
Missing (%)100.0%
Memory size31.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3600
Missing (%)100.0%
Memory size31.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3600
Missing (%)100.0%
Memory size31.8 KiB

소재지전화
Text

MISSING 

Distinct2036
Distinct (%)77.8%
Missing984
Missing (%)27.3%
Memory size28.3 KiB
2024-04-18T11:38:23.023508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.506116
Min length3

Characters and Unicode

Total characters27484
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

Unique1808 ?
Unique (%)69.1%

Sample

1st row051 531 8282
2nd row051 529 5005
3rd row0515015810
4th row051 756 9991
5th row051 751 1600
ValueCountFrequency (%)
051 2229
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%
972 10
 
0.2%
Other values (2238) 3222
57.3%
2024-04-18T11:38:23.444010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4781
17.4%
5 4235
15.4%
1 4054
14.8%
3050
11.1%
2 2222
8.1%
6 1772
 
6.4%
3 1724
 
6.3%
7 1617
 
5.9%
8 1560
 
5.7%
4 1463
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24434
88.9%
Space Separator 3050
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4781
19.6%
5 4235
17.3%
1 4054
16.6%
2 2222
9.1%
6 1772
 
7.3%
3 1724
 
7.1%
7 1617
 
6.6%
8 1560
 
6.4%
4 1463
 
6.0%
9 1006
 
4.1%
Space Separator
ValueCountFrequency (%)
3050
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27484
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4781
17.4%
5 4235
15.4%
1 4054
14.8%
3050
11.1%
2 2222
8.1%
6 1772
 
6.4%
3 1724
 
6.3%
7 1617
 
5.9%
8 1560
 
5.7%
4 1463
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27484
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4781
17.4%
5 4235
15.4%
1 4054
14.8%
3050
11.1%
2 2222
8.1%
6 1772
 
6.4%
3 1724
 
6.3%
7 1617
 
5.9%
8 1560
 
5.7%
4 1463
 
5.3%

소재지면적
Text

MISSING 

Distinct1388
Distinct (%)54.2%
Missing1037
Missing (%)28.8%
Memory size28.3 KiB
2024-04-18T11:38:23.711862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.6859149
Min length3

Characters and Unicode

Total characters12010
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

Unique1073 ?
Unique (%)41.9%

Sample

1st row21.53
2nd row29.50
3rd row8.00
4th row10.00
5th row9.20
ValueCountFrequency (%)
00 114
 
4.4%
6.60 40
 
1.6%
6.00 40
 
1.6%
4.00 37
 
1.4%
3.00 36
 
1.4%
2.00 35
 
1.4%
10.00 33
 
1.3%
3.30 28
 
1.1%
12.00 25
 
1.0%
5.00 24
 
0.9%
Other values (1378) 2151
83.9%
2024-04-18T11:38:24.102595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2705
22.5%
. 2563
21.3%
1 1079
 
9.0%
2 991
 
8.3%
6 759
 
6.3%
4 750
 
6.2%
3 740
 
6.2%
5 737
 
6.1%
8 642
 
5.3%
9 564
 
4.7%
Other values (2) 480
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9437
78.6%
Other Punctuation 2573
 
21.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2705
28.7%
1 1079
 
11.4%
2 991
 
10.5%
6 759
 
8.0%
4 750
 
7.9%
3 740
 
7.8%
5 737
 
7.8%
8 642
 
6.8%
9 564
 
6.0%
7 470
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 2563
99.6%
, 10
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 12010
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2705
22.5%
. 2563
21.3%
1 1079
 
9.0%
2 991
 
8.3%
6 759
 
6.3%
4 750
 
6.2%
3 740
 
6.2%
5 737
 
6.1%
8 642
 
5.3%
9 564
 
4.7%
Other values (2) 480
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12010
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2705
22.5%
. 2563
21.3%
1 1079
 
9.0%
2 991
 
8.3%
6 759
 
6.3%
4 750
 
6.2%
3 740
 
6.2%
5 737
 
6.1%
8 642
 
5.3%
9 564
 
4.7%
Other values (2) 480
 
4.0%

소재지우편번호
Real number (ℝ)

Distinct645
Distinct (%)18.1%
Missing33
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean610572.84
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:24.239651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601705.6
Q1604845
median611807
Q3614847
95-th percentile619901
Maximum619953
Range19942
Interquartile range (IQR)10002

Descriptive statistics

Standard deviation5836.7074
Coefficient of variation (CV)0.0095593958
Kurtosis-1.1600566
Mean610572.84
Median Absolute Deviation (MAD)5014
Skewness-0.12593993
Sum2.1779133 × 109
Variance34067154
MonotonicityNot monotonic
2024-04-18T11:38:24.365345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604842 78
 
2.2%
602030 77
 
2.1%
614843 68
 
1.9%
617831 63
 
1.8%
601803 54
 
1.5%
619904 53
 
1.5%
607804 49
 
1.4%
604843 48
 
1.3%
604846 47
 
1.3%
612020 40
 
1.1%
Other values (635) 2990
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
 
0.2%
619913 5
 
0.1%
619912 11
 
0.3%
619911 5
 
0.1%
619906 20
 
0.6%
619905 18
 
0.5%
619904 53
1.5%
619903 30
0.8%
Distinct2776
Distinct (%)77.2%
Missing2
Missing (%)0.1%
Memory size28.3 KiB
2024-04-18T11:38:24.643286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length57
Mean length24.845192
Min length16

Characters and Unicode

Total characters89393
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

Unique2449 ?
Unique (%)68.1%

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 3599
 
21.4%
사하구 529
 
3.1%
해운대구 386
 
2.3%
부산진구 362
 
2.1%
사상구 283
 
1.7%
동래구 268
 
1.6%
금정구 231
 
1.4%
장림동 223
 
1.3%
기장군 219
 
1.3%
북구 202
 
1.2%
Other values (3214) 10544
62.6%
2024-04-18T11:38:25.054612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13264
 
14.8%
4447
 
5.0%
4302
 
4.8%
4098
 
4.6%
3825
 
4.3%
1 3794
 
4.2%
3728
 
4.2%
3673
 
4.1%
3606
 
4.0%
3506
 
3.9%
Other values (363) 41150
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54970
61.5%
Decimal Number 17196
 
19.2%
Space Separator 13264
 
14.8%
Dash Punctuation 3034
 
3.4%
Uppercase Letter 311
 
0.3%
Open Punctuation 220
 
0.2%
Close Punctuation 220
 
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 (%)
4447
 
8.1%
4302
 
7.8%
4098
 
7.5%
3825
 
7.0%
3728
 
6.8%
3673
 
6.7%
3606
 
6.6%
3506
 
6.4%
3363
 
6.1%
882
 
1.6%
Other values (325) 19540
35.5%
Uppercase Letter
ValueCountFrequency (%)
B 130
41.8%
T 89
28.6%
G 26
 
8.4%
A 25
 
8.0%
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 3794
22.1%
2 2331
13.6%
3 1866
10.9%
5 1694
9.9%
4 1478
 
8.6%
0 1411
 
8.2%
6 1409
 
8.2%
7 1250
 
7.3%
8 1018
 
5.9%
9 945
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 150
86.7%
. 12
 
6.9%
@ 9
 
5.2%
/ 2
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
s 1
33.3%
c 1
33.3%
e 1
33.3%
Space Separator
ValueCountFrequency (%)
13264
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3034
100.0%
Open Punctuation
ValueCountFrequency (%)
( 220
100.0%
Close Punctuation
ValueCountFrequency (%)
) 220
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54969
61.5%
Common 34109
38.2%
Latin 314
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4447
 
8.1%
4302
 
7.8%
4098
 
7.5%
3825
 
7.0%
3728
 
6.8%
3673
 
6.7%
3606
 
6.6%
3506
 
6.4%
3363
 
6.1%
882
 
1.6%
Other values (324) 19539
35.5%
Common
ValueCountFrequency (%)
13264
38.9%
1 3794
 
11.1%
- 3034
 
8.9%
2 2331
 
6.8%
3 1866
 
5.5%
5 1694
 
5.0%
4 1478
 
4.3%
0 1411
 
4.1%
6 1409
 
4.1%
7 1250
 
3.7%
Other values (10) 2578
 
7.6%
Latin
ValueCountFrequency (%)
B 130
41.4%
T 89
28.3%
G 26
 
8.3%
A 25
 
8.0%
S 21
 
6.7%
L 8
 
2.5%
E 3
 
1.0%
K 2
 
0.6%
s 1
 
0.3%
c 1
 
0.3%
Other values (8) 8
 
2.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54969
61.5%
ASCII 34423
38.5%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13264
38.5%
1 3794
 
11.0%
- 3034
 
8.8%
2 2331
 
6.8%
3 1866
 
5.4%
5 1694
 
4.9%
4 1478
 
4.3%
0 1411
 
4.1%
6 1409
 
4.1%
7 1250
 
3.6%
Other values (28) 2892
 
8.4%
Hangul
ValueCountFrequency (%)
4447
 
8.1%
4302
 
7.8%
4098
 
7.5%
3825
 
7.0%
3728
 
6.8%
3673
 
6.7%
3606
 
6.6%
3506
 
6.4%
3363
 
6.1%
882
 
1.6%
Other values (324) 19539
35.5%
CJK
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1747
Distinct (%)92.9%
Missing1719
Missing (%)47.8%
Memory size28.3 KiB
2024-04-18T11:38:25.346254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length55
Mean length31.187666
Min length19

Characters and Unicode

Total characters58664
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

Unique1655 ?
Unique (%)88.0%

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 1882
 
16.7%
1층 374
 
3.3%
사하구 305
 
2.7%
해운대구 195
 
1.7%
부산진구 171
 
1.5%
기장군 165
 
1.5%
2층 147
 
1.3%
사상구 145
 
1.3%
장림동 116
 
1.0%
금정구 113
 
1.0%
Other values (2245) 7665
68.0%
2024-04-18T11:38:25.771738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9402
 
16.0%
1 2413
 
4.1%
2401
 
4.1%
2373
 
4.0%
2270
 
3.9%
2096
 
3.6%
1952
 
3.3%
1887
 
3.2%
1839
 
3.1%
1802
 
3.1%
Other values (387) 30229
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34681
59.1%
Space Separator 9402
 
16.0%
Decimal Number 9130
 
15.6%
Close Punctuation 1797
 
3.1%
Open Punctuation 1797
 
3.1%
Other Punctuation 1436
 
2.4%
Dash Punctuation 300
 
0.5%
Uppercase Letter 108
 
0.2%
Math Symbol 10
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2401
 
6.9%
2373
 
6.8%
2270
 
6.5%
2096
 
6.0%
1952
 
5.6%
1887
 
5.4%
1839
 
5.3%
1802
 
5.2%
930
 
2.7%
855
 
2.5%
Other values (349) 16276
46.9%
Uppercase Letter
ValueCountFrequency (%)
B 46
42.6%
A 36
33.3%
C 5
 
4.6%
S 4
 
3.7%
G 4
 
3.7%
K 2
 
1.9%
E 2
 
1.9%
T 1
 
0.9%
Q 1
 
0.9%
O 1
 
0.9%
Other values (6) 6
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 2413
26.4%
2 1381
15.1%
3 939
 
10.3%
4 793
 
8.7%
5 788
 
8.6%
0 683
 
7.5%
6 659
 
7.2%
7 603
 
6.6%
9 469
 
5.1%
8 402
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 1429
99.5%
@ 3
 
0.2%
. 3
 
0.2%
/ 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
b 1
33.3%
s 1
33.3%
c 1
33.3%
Space Separator
ValueCountFrequency (%)
9402
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1797
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1797
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 300
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34681
59.1%
Common 23872
40.7%
Latin 111
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2401
 
6.9%
2373
 
6.8%
2270
 
6.5%
2096
 
6.0%
1952
 
5.6%
1887
 
5.4%
1839
 
5.3%
1802
 
5.2%
930
 
2.7%
855
 
2.5%
Other values (349) 16276
46.9%
Common
ValueCountFrequency (%)
9402
39.4%
1 2413
 
10.1%
) 1797
 
7.5%
( 1797
 
7.5%
, 1429
 
6.0%
2 1381
 
5.8%
3 939
 
3.9%
4 793
 
3.3%
5 788
 
3.3%
0 683
 
2.9%
Other values (9) 2450
 
10.3%
Latin
ValueCountFrequency (%)
B 46
41.4%
A 36
32.4%
C 5
 
4.5%
S 4
 
3.6%
G 4
 
3.6%
K 2
 
1.8%
E 2
 
1.8%
T 1
 
0.9%
b 1
 
0.9%
Q 1
 
0.9%
Other values (9) 9
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34681
59.1%
ASCII 23983
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9402
39.2%
1 2413
 
10.1%
) 1797
 
7.5%
( 1797
 
7.5%
, 1429
 
6.0%
2 1381
 
5.8%
3 939
 
3.9%
4 793
 
3.3%
5 788
 
3.3%
0 683
 
2.8%
Other values (28) 2561
 
10.7%
Hangul
ValueCountFrequency (%)
2401
 
6.9%
2373
 
6.8%
2270
 
6.5%
2096
 
6.0%
1952
 
5.6%
1887
 
5.4%
1839
 
5.3%
1802
 
5.2%
930
 
2.7%
855
 
2.5%
Other values (349) 16276
46.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct757
Distinct (%)40.9%
Missing1751
Missing (%)48.6%
Infinite0
Infinite (%)0.0%
Mean47866.236
Minimum46002
Maximum49526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:25.906178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46067.4
Q146926
median48012
Q348984
95-th percentile49478
Maximum49526
Range3524
Interquartile range (IQR)2058

Descriptive statistics

Standard deviation1158.4141
Coefficient of variation (CV)0.02420107
Kurtosis-1.3331315
Mean47866.236
Median Absolute Deviation (MAD)1030
Skewness-0.039750121
Sum88504670
Variance1341923.3
MonotonicityNot monotonic
2024-04-18T11:38:26.030967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49277 51
 
1.4%
46079 40
 
1.1%
47032 36
 
1.0%
49478 34
 
0.9%
48984 31
 
0.9%
48737 28
 
0.8%
47252 28
 
0.8%
48031 24
 
0.7%
48983 22
 
0.6%
47251 17
 
0.5%
Other values (747) 1538
42.7%
(Missing) 1751
48.6%
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%
Distinct2670
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2024-04-18T11:38:26.238460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length5.9113889
Min length2

Characters and Unicode

Total characters21281
Distinct characters629
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

Unique2282 ?
Unique (%)63.4%

Sample

1st row부성상사
2nd row더월마트
3rd row탑플러스마트
4th row(주)서원유통탑마트사직점
5th row찡오언니
ValueCountFrequency (%)
주식회사 82
 
2.1%
주)두루찬 31
 
0.8%
영우유통 31
 
0.8%
진경식품 29
 
0.7%
개미농특산 27
 
0.7%
우리농수산 22
 
0.6%
현식품 20
 
0.5%
주)서원유통 18
 
0.5%
남해식품 18
 
0.5%
하복식품 18
 
0.5%
Other values (2772) 3667
92.5%
2024-04-18T11:38:26.609993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
944
 
4.4%
) 872
 
4.1%
856
 
4.0%
( 848
 
4.0%
743
 
3.5%
497
 
2.3%
424
 
2.0%
403
 
1.9%
402
 
1.9%
390
 
1.8%
Other values (619) 14902
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18773
88.2%
Close Punctuation 872
 
4.1%
Open Punctuation 848
 
4.0%
Space Separator 364
 
1.7%
Uppercase Letter 261
 
1.2%
Decimal Number 68
 
0.3%
Lowercase Letter 56
 
0.3%
Other Punctuation 34
 
0.2%
Dash Punctuation 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
944
 
5.0%
856
 
4.6%
743
 
4.0%
497
 
2.6%
424
 
2.3%
403
 
2.1%
402
 
2.1%
390
 
2.1%
320
 
1.7%
314
 
1.7%
Other values (557) 13480
71.8%
Uppercase Letter
ValueCountFrequency (%)
O 29
 
11.1%
F 29
 
11.1%
S 17
 
6.5%
G 16
 
6.1%
A 16
 
6.1%
C 16
 
6.1%
D 15
 
5.7%
N 15
 
5.7%
M 12
 
4.6%
E 12
 
4.6%
Other values (15) 84
32.2%
Lowercase Letter
ValueCountFrequency (%)
a 9
16.1%
n 8
14.3%
s 8
14.3%
r 5
8.9%
e 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%
6 2
 
2.9%
4 2
 
2.9%
0 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 14
41.2%
& 12
35.3%
, 6
17.6%
· 1
 
2.9%
' 1
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 872
100.0%
Open Punctuation
ValueCountFrequency (%)
( 848
100.0%
Space Separator
ValueCountFrequency (%)
364
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18773
88.2%
Common 2191
 
10.3%
Latin 317
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
944
 
5.0%
856
 
4.6%
743
 
4.0%
497
 
2.6%
424
 
2.3%
403
 
2.1%
402
 
2.1%
390
 
2.1%
320
 
1.7%
314
 
1.7%
Other values (557) 13480
71.8%
Latin
ValueCountFrequency (%)
O 29
 
9.1%
F 29
 
9.1%
S 17
 
5.4%
G 16
 
5.0%
A 16
 
5.0%
C 16
 
5.0%
D 15
 
4.7%
N 15
 
4.7%
M 12
 
3.8%
E 12
 
3.8%
Other values (32) 140
44.2%
Common
ValueCountFrequency (%)
) 872
39.8%
( 848
38.7%
364
16.6%
2 19
 
0.9%
3 15
 
0.7%
. 14
 
0.6%
1 12
 
0.5%
& 12
 
0.5%
8 6
 
0.3%
, 6
 
0.3%
Other values (10) 23
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18773
88.2%
ASCII 2507
 
11.8%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
944
 
5.0%
856
 
4.6%
743
 
4.0%
497
 
2.6%
424
 
2.3%
403
 
2.1%
402
 
2.1%
390
 
2.1%
320
 
1.7%
314
 
1.7%
Other values (557) 13480
71.8%
ASCII
ValueCountFrequency (%)
) 872
34.8%
( 848
33.8%
364
14.5%
O 29
 
1.2%
F 29
 
1.2%
2 19
 
0.8%
S 17
 
0.7%
G 16
 
0.6%
A 16
 
0.6%
C 16
 
0.6%
Other values (51) 281
 
11.2%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

Distinct2911
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0107045 × 1013
Minimum1.9990315 × 1013
Maximum2.0210226 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:26.766509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990315 × 1013
5-th percentile2.0011119 × 1013
Q12.0050413 × 1013
median2.0100828 × 1013
Q32.0170909 × 1013
95-th percentile2.0200917 × 1013
Maximum2.0210226 × 1013
Range2.1991117 × 1011
Interquartile range (IQR)1.2049616 × 1011

Descriptive statistics

Standard deviation6.5298831 × 1010
Coefficient of variation (CV)0.0032475599
Kurtosis-1.4015134
Mean2.0107045 × 1013
Median Absolute Deviation (MAD)6.0125117 × 1010
Skewness0.05582304
Sum7.2385361 × 1016
Variance4.2639373 × 1021
MonotonicityNot monotonic
2024-04-18T11:38:26.924281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20010731000000 48
 
1.3%
20020612000000 32
 
0.9%
20020227000000 31
 
0.9%
20020805000000 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 (2901) 3332
92.6%
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 (%)
20210226174803 1
< 0.1%
20210226141014 1
< 0.1%
20210225134829 1
< 0.1%
20210225112428 1
< 0.1%
20210224210104 1
< 0.1%
20210224170934 1
< 0.1%
20210224153936 1
< 0.1%
20210223103618 1
< 0.1%
20210222180122 1
< 0.1%
20210219111549 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
I
3020 
U
580 

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 3020
83.9%
U 580
 
16.1%

Length

2024-04-18T11:38:27.047995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:27.135871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3020
83.9%
u 580
 
16.1%
Distinct446
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-02-28 02:40:00
2024-04-18T11:38:27.233903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T11:38:27.359230image/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 size28.3 KiB
식품소분업
3596 
<NA>
 
4

Length

Max length5
Median length5
Mean length4.9988889
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 3596
99.9%
<NA> 4
 
0.1%

Length

2024-04-18T11:38:27.479243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:28.336003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 3596
99.9%
na 4
 
0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1967
Distinct (%)57.3%
Missing169
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean387271.41
Minimum364927.7
Maximum407820.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:28.432956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum364927.7
5-th percentile378642.66
Q1382201.98
median387537.8
Q3391313.41
95-th percentile401128.32
Maximum407820.17
Range42892.471
Interquartile range (IQR)9111.424

Descriptive statistics

Standard deviation6519.7474
Coefficient of variation (CV)0.016835086
Kurtosis0.15099352
Mean387271.41
Median Absolute Deviation (MAD)4533.5115
Skewness0.34023237
Sum1.3287282 × 109
Variance42507106
MonotonicityNot monotonic
2024-04-18T11:38:28.565677image/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 32
 
0.9%
379321.651090423 29
 
0.8%
Other values (1957) 3040
84.4%
(Missing) 169
 
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 

Distinct1966
Distinct (%)57.3%
Missing169
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean186462.58
Minimum170813.58
Maximum211459
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:28.711478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170813.58
5-th percentile176329.79
Q1180234.86
median186654.62
Q3191531.8
95-th percentile196546.25
Maximum211459
Range40645.417
Interquartile range (IQR)11296.948

Descriptive statistics

Standard deviation6646.9057
Coefficient of variation (CV)0.035647398
Kurtosis-0.4162942
Mean186462.58
Median Absolute Deviation (MAD)5276.3958
Skewness0.18370637
Sum6.397531 × 108
Variance44181355
MonotonicityNot monotonic
2024-04-18T11:38:28.842391image/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%
174683.069423816 32
 
0.9%
196375.470354374 32
 
0.9%
183030.975769364 29
 
0.8%
Other values (1956) 3040
84.4%
(Missing) 169
 
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 size28.3 KiB
식품소분업
3596 
<NA>
 
4

Length

Max length5
Median length5
Mean length4.9988889
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 3596
99.9%
<NA> 4
 
0.1%

Length

2024-04-18T11:38:28.989686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:29.113650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 3596
99.9%
na 4
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3169 
0
422 
1
 
9

Length

Max length4
Median length4
Mean length3.6408333
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> 3169
88.0%
0 422
 
11.7%
1 9
 
0.2%

Length

2024-04-18T11:38:29.222397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:29.316838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3169
88.0%
0 422
 
11.7%
1 9
 
0.2%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3169 
0
423 
1
 
8

Length

Max length4
Median length4
Mean length3.6408333
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> 3169
88.0%
0 423
 
11.8%
1 8
 
0.2%

Length

2024-04-18T11:38:29.423216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:29.516089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3169
88.0%
0 423
 
11.8%
1 8
 
0.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
2929 
기타
644 
주택가주변
 
15
아파트지역
 
7
학교정화(상대)
 
4

Length

Max length8
Median length4
Mean length3.6538889
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> 2929
81.4%
기타 644
 
17.9%
주택가주변 15
 
0.4%
아파트지역 7
 
0.2%
학교정화(상대) 4
 
0.1%
유흥업소밀집지역 1
 
< 0.1%

Length

2024-04-18T11:38:29.618595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:29.719112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2929
81.4%
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 size28.3 KiB
<NA>
2929 
기타
636 
자율
 
35

Length

Max length4
Median length4
Mean length3.6272222
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> 2929
81.4%
기타 636
 
17.7%
자율 35
 
1.0%

Length

2024-04-18T11:38:29.833341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:29.931979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2929
81.4%
기타 636
 
17.7%
자율 35
 
1.0%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3055 
상수도전용
541 
간이상수도
 
3
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.1513889
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> 3055
84.9%
상수도전용 541
 
15.0%
간이상수도 3
 
0.1%
지하수전용 1
 
< 0.1%

Length

2024-04-18T11:38:30.037787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:30.129488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3055
84.9%
상수도전용 541
 
15.0%
간이상수도 3
 
0.1%
지하수전용 1
 
< 0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3600
Missing (%)100.0%
Memory size31.8 KiB
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
0
1840 
<NA>
1757 
1
 
2
3
 
1

Length

Max length4
Median length1
Mean length2.4641667
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1840
51.1%
<NA> 1757
48.8%
1 2
 
0.1%
3 1
 
< 0.1%

Length

2024-04-18T11:38:30.233929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:30.340860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1840
51.1%
na 1757
48.8%
1 2
 
0.1%
3 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
0
1835 
<NA>
1756 
1
 
7
3
 
1
2
 
1

Length

Max length4
Median length1
Mean length2.4633333
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1835
51.0%
<NA> 1756
48.8%
1 7
 
0.2%
3 1
 
< 0.1%
2 1
 
< 0.1%

Length

2024-04-18T11:38:30.444796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:30.544287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1835
51.0%
na 1756
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 size28.3 KiB
0
1831 
<NA>
1755 
1
 
10
2
 
3
3
 
1

Length

Max length4
Median length1
Mean length2.4625
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1831
50.9%
<NA> 1755
48.8%
1 10
 
0.3%
2 3
 
0.1%
3 1
 
< 0.1%

Length

2024-04-18T11:38:30.652584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:30.752117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1831
50.9%
na 1755
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%
Missing1751
Missing (%)48.6%
Infinite0
Infinite (%)0.0%
Mean0.66143862
Minimum0
Maximum1170
Zeros1810
Zeros (%)50.3%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:30.838043image/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 deviation27.209644
Coefficient of variation (CV)41.137067
Kurtosis1848.7253
Mean0.66143862
Median Absolute Deviation (MAD)0
Skewness42.995219
Sum1223
Variance740.36475
MonotonicityNot monotonic
2024-04-18T11:38:30.936746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1810
50.3%
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) 1751
48.6%
ValueCountFrequency (%)
0 1810
50.3%
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 1810
50.3%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
2742 
자가
542 
임대
316 

Length

Max length4
Median length4
Mean length3.5233333
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> 2742
76.2%
자가 542
 
15.1%
임대 316
 
8.8%

Length

2024-04-18T11:38:31.050634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:31.150933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2742
76.2%
자가 542
 
15.1%
임대 316
 
8.8%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3434 
0
 
166

Length

Max length4
Median length4
Mean length3.8616667
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> 3434
95.4%
0 166
 
4.6%

Length

2024-04-18T11:38:31.252925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:31.343026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3434
95.4%
0 166
 
4.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3434 
0
 
166

Length

Max length4
Median length4
Mean length3.8616667
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> 3434
95.4%
0 166
 
4.6%

Length

2024-04-18T11:38:31.460293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:31.570027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3434
95.4%
0 166
 
4.6%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
False
3600 
ValueCountFrequency (%)
False 3600
100.0%
2024-04-18T11:38:31.651480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct186
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4538556
Minimum0
Maximum1011.02
Zeros3354
Zeros (%)93.2%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-04-18T11:38:31.747693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation21.886454
Coefficient of variation (CV)8.9192103
Kurtosis1280.0296
Mean2.4538556
Median Absolute Deviation (MAD)0
Skewness30.104094
Sum8833.88
Variance479.01685
MonotonicityNot monotonic
2024-04-18T11:38:31.878344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3354
93.2%
4.0 8
 
0.2%
6.6 7
 
0.2%
10.0 7
 
0.2%
9.9 6
 
0.2%
3.0 5
 
0.1%
3.3 4
 
0.1%
33.0 4
 
0.1%
16.5 4
 
0.1%
12.0 3
 
0.1%
Other values (176) 198
 
5.5%
ValueCountFrequency (%)
0.0 3354
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 

Missing3600
Missing (%)100.0%
Memory size31.8 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3600
Missing (%)100.0%
Memory size31.8 KiB

홈페이지
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3599 
8
 
1

Length

Max length4
Median length4
Mean length3.9991667
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> 3599
> 99.9%
8 1
 
< 0.1%

Length

2024-04-18T11:38:32.001882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:38:32.107129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3599
> 99.9%
8 1
 
< 0.1%

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3600
Missing (%)100.0%
Memory size31.8 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>
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번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
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35913592식품소분업07_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>
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35953596식품소분업07_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>
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35993600식품소분업07_22_08_P34000003400000-109-2021-0000120210122<NA>3폐업2폐업20210219<NA><NA><NA><NA>85.00619901부산광역시 기장군 기장읍 교리 323-7부산광역시 기장군 기장읍 차성로 413, 1층46057(주)재이에스푸드20210219111549U2021-02-21 02:40:00.0식품소분업401564.071525197243.253434식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N85.0<NA><NA><NA><NA>