Overview

Dataset statistics

Number of variables48
Number of observations3625
Missing cells37681
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

Description2021-06-01
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 (98.8%)Imbalance
위생업태명 is highly imbalanced (98.8%)Imbalance
남성종사자수 is highly imbalanced (65.7%)Imbalance
여성종사자수 is highly imbalanced (65.8%)Imbalance
영업장주변구분명 is highly imbalanced (71.1%)Imbalance
등급구분명 is highly imbalanced (52.9%)Imbalance
급수시설구분명 is highly imbalanced (68.9%)Imbalance
공장사무직종업원수 is highly imbalanced (55.9%)Imbalance
공장판매직종업원수 is highly imbalanced (55.4%)Imbalance
보증액 is highly imbalanced (73.2%)Imbalance
월세액 is highly imbalanced (73.2%)Imbalance
홈페이지 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3625 (100.0%) missing valuesMissing
폐업일자 has 1036 (28.6%) missing valuesMissing
휴업시작일자 has 3625 (100.0%) missing valuesMissing
휴업종료일자 has 3625 (100.0%) missing valuesMissing
재개업일자 has 3625 (100.0%) missing valuesMissing
소재지전화 has 999 (27.6%) missing valuesMissing
소재지면적 has 1039 (28.7%) missing valuesMissing
도로명전체주소 has 1719 (47.4%) missing valuesMissing
도로명우편번호 has 1752 (48.3%) missing valuesMissing
좌표정보(x) has 169 (4.7%) missing valuesMissing
좌표정보(y) has 169 (4.7%) missing valuesMissing
총종업원수 has 3625 (100.0%) missing valuesMissing
공장생산직종업원수 has 1762 (48.6%) missing valuesMissing
전통업소지정번호 has 3625 (100.0%) missing valuesMissing
전통업소주된음식 has 3625 (100.0%) missing valuesMissing
Unnamed: 47 has 3625 (100.0%) missing valuesMissing
공장생산직종업원수 is highly skewed (γ1 = 43.1576837)Skewed
시설총규모 is highly skewed (γ1 = 28.60479873)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 1824 (50.3%) zerosZeros
시설총규모 has 3376 (93.1%) zerosZeros

Reproduction

Analysis started2024-04-18 02:30:35.846137
Analysis finished2024-04-18 02:30:37.009673
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3625
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1813
Minimum1
Maximum3625
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:37.074349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile182.2
Q1907
median1813
Q32719
95-th percentile3443.8
Maximum3625
Range3624
Interquartile range (IQR)1812

Descriptive statistics

Standard deviation1046.5917
Coefficient of variation (CV)0.57727065
Kurtosis-1.2
Mean1813
Median Absolute Deviation (MAD)906
Skewness0
Sum6572125
Variance1095354.2
MonotonicityStrictly increasing
2024-04-18T11:30:37.202752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2436 1
 
< 0.1%
2410 1
 
< 0.1%
2411 1
 
< 0.1%
2412 1
 
< 0.1%
2413 1
 
< 0.1%
2414 1
 
< 0.1%
2415 1
 
< 0.1%
2416 1
 
< 0.1%
2417 1
 
< 0.1%
Other values (3615) 3615
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 (%)
3625 1
< 0.1%
3624 1
< 0.1%
3623 1
< 0.1%
3622 1
< 0.1%
3621 1
< 0.1%
3620 1
< 0.1%
3619 1
< 0.1%
3618 1
< 0.1%
3617 1
< 0.1%
3616 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
식품소분업
3625 

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 3625
100.0%

Length

2024-04-18T11:30:37.327738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:37.411737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 3625
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
07_22_08_P
3625 

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 3625
100.0%

Length

2024-04-18T11:30:37.503084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:37.589071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_08_p 3625
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3327804.1
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:37.675284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3330000
Q33360000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)70000

Descriptive statistics

Standard deviation42277.599
Coefficient of variation (CV)0.012704353
Kurtosis-0.86810906
Mean3327804.1
Median Absolute Deviation (MAD)30000
Skewness-0.030698942
Sum1.206329 × 1010
Variance1.7873954 × 109
MonotonicityNot monotonic
2024-04-18T11:30:37.780308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3340000 532
14.7%
3330000 389
10.7%
3290000 363
10.0%
3390000 285
 
7.9%
3300000 269
 
7.4%
3350000 233
 
6.4%
3400000 222
 
6.1%
3320000 202
 
5.6%
3270000 174
 
4.8%
3250000 170
 
4.7%
Other values (6) 786
21.7%
ValueCountFrequency (%)
3250000 170
 
4.7%
3260000 155
 
4.3%
3270000 174
 
4.8%
3280000 79
 
2.2%
3290000 363
10.0%
3300000 269
7.4%
3310000 152
 
4.2%
3320000 202
 
5.6%
3330000 389
10.7%
3340000 532
14.7%
ValueCountFrequency (%)
3400000 222
6.1%
3390000 285
7.9%
3380000 129
 
3.6%
3370000 133
 
3.7%
3360000 138
 
3.8%
3350000 233
6.4%
3340000 532
14.7%
3330000 389
10.7%
3320000 202
 
5.6%
3310000 152
 
4.2%

관리번호
Text

UNIQUE 

Distinct3625
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
2024-04-18T11:30:37.957093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters79750
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

Unique3625 ?
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%
3340000-109-2000-01037 1
 
< 0.1%
3340000-109-1999-00854 1
 
< 0.1%
3340000-109-2006-00019 1
 
< 0.1%
3340000-109-2000-00977 1
 
< 0.1%
3340000-109-2006-00020 1
 
< 0.1%
3340000-109-2013-00010 1
 
< 0.1%
3340000-109-2013-00011 1
 
< 0.1%
3340000-109-1999-00865 1
 
< 0.1%
3340000-109-1999-00899 1
 
< 0.1%
Other values (3615) 3615
99.7%
2024-04-18T11:30:38.270512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 36429
45.7%
- 10875
 
13.6%
3 7392
 
9.3%
1 7132
 
8.9%
9 5853
 
7.3%
2 5613
 
7.0%
4 1707
 
2.1%
5 1333
 
1.7%
6 1244
 
1.6%
7 1127
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68875
86.4%
Dash Punctuation 10875
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 36429
52.9%
3 7392
 
10.7%
1 7132
 
10.4%
9 5853
 
8.5%
2 5613
 
8.1%
4 1707
 
2.5%
5 1333
 
1.9%
6 1244
 
1.8%
7 1127
 
1.6%
8 1045
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 10875
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79750
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 36429
45.7%
- 10875
 
13.6%
3 7392
 
9.3%
1 7132
 
8.9%
9 5853
 
7.3%
2 5613
 
7.0%
4 1707
 
2.1%
5 1333
 
1.7%
6 1244
 
1.6%
7 1127
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 36429
45.7%
- 10875
 
13.6%
3 7392
 
9.3%
1 7132
 
8.9%
9 5853
 
7.3%
2 5613
 
7.0%
4 1707
 
2.1%
5 1333
 
1.7%
6 1244
 
1.6%
7 1127
 
1.4%

인허가일자
Real number (ℝ)

Distinct2540
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20074005
Minimum19780414
Maximum20210429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:38.406045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19780414
5-th percentile19970443
Q120020605
median20061110
Q320130506
95-th percentile20191227
Maximum20210429
Range430015
Interquartile range (IQR)109901

Descriptive statistics

Standard deviation71933.671
Coefficient of variation (CV)0.0035834241
Kurtosis-0.26767556
Mean20074005
Median Absolute Deviation (MAD)50191
Skewness-0.018472694
Sum7.2768267 × 1010
Variance5.1744531 × 109
MonotonicityNot monotonic
2024-04-18T11:30:38.531243image/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%
20030721 6
 
0.2%
20030926 6
 
0.2%
20100113 6
 
0.2%
20010704 6
 
0.2%
20110426 6
 
0.2%
20060424 6
 
0.2%
Other values (2530) 3551
98.0%
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 (%)
20210429 1
< 0.1%
20210426 1
< 0.1%
20210422 1
< 0.1%
20210420 1
< 0.1%
20210416 2
0.1%
20210415 1
< 0.1%
20210409 1
< 0.1%
20210408 1
< 0.1%
20210406 2
0.1%
20210401 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3625
Missing (%)100.0%
Memory size32.0 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
3
2589 
1
1036 

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 2589
71.4%
1 1036
28.6%

Length

2024-04-18T11:30:38.657739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:38.747734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2589
71.4%
1 1036
28.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
폐업
2589 
영업/정상
1036 

Length

Max length5
Median length2
Mean length2.8573793
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 2589
71.4%
영업/정상 1036
28.6%

Length

2024-04-18T11:30:38.839726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:38.939330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2589
71.4%
영업/정상 1036
28.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
2
2589 
1
1036 

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 2589
71.4%
1 1036
28.6%

Length

2024-04-18T11:30:39.052746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:39.150177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2589
71.4%
1 1036
28.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
폐업
2589 
영업
1036 

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 2589
71.4%
영업 1036
28.6%

Length

2024-04-18T11:30:39.242716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:39.332892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2589
71.4%
영업 1036
28.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct1798
Distinct (%)69.4%
Missing1036
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean20096529
Minimum19900725
Maximum20210421
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:39.436841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19900725
5-th percentile20010608
Q120050914
median20090615
Q320150119
95-th percentile20200220
Maximum20210421
Range309696
Interquartile range (IQR)99205

Descriptive statistics

Standard deviation58721.453
Coefficient of variation (CV)0.0029219699
Kurtosis-0.77045684
Mean20096529
Median Absolute Deviation (MAD)40299
Skewness0.14460639
Sum5.2029914 × 1010
Variance3.448209 × 109
MonotonicityNot monotonic
2024-04-18T11:30:39.564126image/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%
20201006 8
 
0.2%
20201231 8
 
0.2%
20100318 7
 
0.2%
Other values (1788) 2475
68.3%
(Missing) 1036
28.6%
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 (%)
20210421 1
< 0.1%
20210416 1
< 0.1%
20210413 1
< 0.1%
20210408 1
< 0.1%
20210405 1
< 0.1%
20210401 1
< 0.1%
20210325 1
< 0.1%
20210322 1
< 0.1%
20210317 1
< 0.1%
20210310 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3625
Missing (%)100.0%
Memory size32.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3625
Missing (%)100.0%
Memory size32.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3625
Missing (%)100.0%
Memory size32.0 KiB

소재지전화
Text

MISSING 

Distinct2044
Distinct (%)77.8%
Missing999
Missing (%)27.6%
Memory size28.4 KiB
2024-04-18T11:30:39.856625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.511805
Min length3

Characters and Unicode

Total characters27604
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

Unique1814 ?
Unique (%)69.1%

Sample

1st row051 531 8282
2nd row051 529 5005
3rd row0515015810
4th row051 756 9991
5th row051 751 1600
ValueCountFrequency (%)
051 2238
39.6%
070 56
 
1.0%
722 29
 
0.5%
055 18
 
0.3%
262 17
 
0.3%
724 14
 
0.2%
265 13
 
0.2%
266 11
 
0.2%
245 11
 
0.2%
261 10
 
0.2%
Other values (2247) 3240
57.3%
2024-04-18T11:30:40.261595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4801
17.4%
5 4250
15.4%
1 4074
14.8%
3069
11.1%
2 2227
8.1%
6 1779
 
6.4%
3 1730
 
6.3%
7 1624
 
5.9%
8 1566
 
5.7%
4 1469
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24535
88.9%
Space Separator 3069
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4801
19.6%
5 4250
17.3%
1 4074
16.6%
2 2227
9.1%
6 1779
 
7.3%
3 1730
 
7.1%
7 1624
 
6.6%
8 1566
 
6.4%
4 1469
 
6.0%
9 1015
 
4.1%
Space Separator
ValueCountFrequency (%)
3069
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4801
17.4%
5 4250
15.4%
1 4074
14.8%
3069
11.1%
2 2227
8.1%
6 1779
 
6.4%
3 1730
 
6.3%
7 1624
 
5.9%
8 1566
 
5.7%
4 1469
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4801
17.4%
5 4250
15.4%
1 4074
14.8%
3069
11.1%
2 2227
8.1%
6 1779
 
6.4%
3 1730
 
6.3%
7 1624
 
5.9%
8 1566
 
5.7%
4 1469
 
5.3%

소재지면적
Text

MISSING 

Distinct1401
Distinct (%)54.2%
Missing1039
Missing (%)28.7%
Memory size28.4 KiB
2024-04-18T11:30:40.608010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.6887084
Min length3

Characters and Unicode

Total characters12125
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

Unique1083 ?
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
 
1.5%
6.00 40
 
1.5%
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%
5.00 25
 
1.0%
12.00 25
 
1.0%
Other values (1391) 2173
84.0%
2024-04-18T11:30:41.094263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2730
22.5%
. 2586
21.3%
1 1090
 
9.0%
2 1000
 
8.2%
6 761
 
6.3%
4 756
 
6.2%
3 751
 
6.2%
5 748
 
6.2%
8 653
 
5.4%
9 565
 
4.7%
Other values (2) 485
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9529
78.6%
Other Punctuation 2596
 
21.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2730
28.6%
1 1090
 
11.4%
2 1000
 
10.5%
6 761
 
8.0%
4 756
 
7.9%
3 751
 
7.9%
5 748
 
7.8%
8 653
 
6.9%
9 565
 
5.9%
7 475
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 2586
99.6%
, 10
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 12125
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2730
22.5%
. 2586
21.3%
1 1090
 
9.0%
2 1000
 
8.2%
6 761
 
6.3%
4 756
 
6.2%
3 751
 
6.2%
5 748
 
6.2%
8 653
 
5.4%
9 565
 
4.7%
Other values (2) 485
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12125
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2730
22.5%
. 2586
21.3%
1 1090
 
9.0%
2 1000
 
8.2%
6 761
 
6.3%
4 756
 
6.2%
3 751
 
6.2%
5 748
 
6.2%
8 653
 
5.4%
9 565
 
4.7%
Other values (2) 485
 
4.0%

소재지우편번호
Real number (ℝ)

Distinct645
Distinct (%)18.0%
Missing34
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean610565.89
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:41.234826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601707
Q1604845
median611807
Q3614847
95-th percentile619901
Maximum619953
Range19942
Interquartile range (IQR)10002

Descriptive statistics

Standard deviation5841.095
Coefficient of variation (CV)0.0095666907
Kurtosis-1.1627087
Mean610565.89
Median Absolute Deviation (MAD)5019
Skewness-0.12377313
Sum2.1925421 × 109
Variance34118390
MonotonicityNot monotonic
2024-04-18T11:30:41.369239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
602030 80
 
2.2%
604842 78
 
2.2%
614843 68
 
1.9%
617831 63
 
1.7%
619904 54
 
1.5%
601803 54
 
1.5%
604846 49
 
1.4%
607804 49
 
1.4%
604843 48
 
1.3%
612020 40
 
1.1%
Other values (635) 3008
83.0%
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 54
1.5%
619903 30
0.8%
Distinct2799
Distinct (%)77.3%
Missing2
Missing (%)0.1%
Memory size28.4 KiB
2024-04-18T11:30:41.638139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length57
Mean length24.811206
Min length16

Characters and Unicode

Total characters89891
Distinct characters376
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

Unique2469 ?
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 3624
 
21.4%
사하구 532
 
3.1%
해운대구 388
 
2.3%
부산진구 363
 
2.1%
사상구 285
 
1.7%
동래구 269
 
1.6%
금정구 233
 
1.4%
장림동 225
 
1.3%
기장군 222
 
1.3%
북구 202
 
1.2%
Other values (3245) 10616
62.6%
2024-04-18T11:30:42.034751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13352
 
14.9%
4474
 
5.0%
4331
 
4.8%
4128
 
4.6%
1 3818
 
4.2%
3802
 
4.2%
3754
 
4.2%
3699
 
4.1%
3631
 
4.0%
3528
 
3.9%
Other values (366) 41374
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55252
61.5%
Decimal Number 17305
 
19.3%
Space Separator 13352
 
14.9%
Dash Punctuation 3053
 
3.4%
Uppercase Letter 311
 
0.3%
Close Punctuation 220
 
0.2%
Open 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 (%)
4474
 
8.1%
4331
 
7.8%
4128
 
7.5%
3802
 
6.9%
3754
 
6.8%
3699
 
6.7%
3631
 
6.6%
3528
 
6.4%
3339
 
6.0%
888
 
1.6%
Other values (328) 19678
35.6%
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%
M 1
 
0.3%
O 1
 
0.3%
Other values (5) 5
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 3818
22.1%
2 2341
13.5%
3 1878
10.9%
5 1708
9.9%
4 1489
 
8.6%
6 1420
 
8.2%
0 1417
 
8.2%
7 1260
 
7.3%
8 1024
 
5.9%
9 950
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 150
86.7%
. 12
 
6.9%
@ 9
 
5.2%
/ 2
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
s 1
33.3%
c 1
33.3%
Space Separator
ValueCountFrequency (%)
13352
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3053
100.0%
Close Punctuation
ValueCountFrequency (%)
) 220
100.0%
Open Punctuation
ValueCountFrequency (%)
( 220
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55251
61.5%
Common 34325
38.2%
Latin 314
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4474
 
8.1%
4331
 
7.8%
4128
 
7.5%
3802
 
6.9%
3754
 
6.8%
3699
 
6.7%
3631
 
6.6%
3528
 
6.4%
3339
 
6.0%
888
 
1.6%
Other values (327) 19677
35.6%
Common
ValueCountFrequency (%)
13352
38.9%
1 3818
 
11.1%
- 3053
 
8.9%
2 2341
 
6.8%
3 1878
 
5.5%
5 1708
 
5.0%
4 1489
 
4.3%
6 1420
 
4.1%
0 1417
 
4.1%
7 1260
 
3.7%
Other values (10) 2589
 
7.5%
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%
M 1
 
0.3%
O 1
 
0.3%
Other values (8) 8
 
2.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55251
61.5%
ASCII 34639
38.5%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13352
38.5%
1 3818
 
11.0%
- 3053
 
8.8%
2 2341
 
6.8%
3 1878
 
5.4%
5 1708
 
4.9%
4 1489
 
4.3%
6 1420
 
4.1%
0 1417
 
4.1%
7 1260
 
3.6%
Other values (28) 2903
 
8.4%
Hangul
ValueCountFrequency (%)
4474
 
8.1%
4331
 
7.8%
4128
 
7.5%
3802
 
6.9%
3754
 
6.8%
3699
 
6.7%
3631
 
6.6%
3528
 
6.4%
3339
 
6.0%
888
 
1.6%
Other values (327) 19677
35.6%
CJK
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1770
Distinct (%)92.9%
Missing1719
Missing (%)47.4%
Memory size28.4 KiB
2024-04-18T11:30:42.342523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length55
Mean length31.208814
Min length19

Characters and Unicode

Total characters59484
Distinct characters399
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

Unique1676 ?
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 1907
 
16.7%
1층 386
 
3.4%
사하구 308
 
2.7%
해운대구 197
 
1.7%
부산진구 172
 
1.5%
기장군 168
 
1.5%
2층 152
 
1.3%
사상구 147
 
1.3%
장림동 118
 
1.0%
금정구 115
 
1.0%
Other values (2263) 7773
67.9%
2024-04-18T11:30:42.783055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9542
 
16.0%
1 2453
 
4.1%
2430
 
4.1%
2401
 
4.0%
2302
 
3.9%
2123
 
3.6%
1979
 
3.3%
1912
 
3.2%
1861
 
3.1%
1825
 
3.1%
Other values (389) 30656
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35153
59.1%
Space Separator 9542
 
16.0%
Decimal Number 9262
 
15.6%
Close Punctuation 1818
 
3.1%
Open Punctuation 1818
 
3.1%
Other Punctuation 1465
 
2.5%
Dash Punctuation 303
 
0.5%
Uppercase Letter 110
 
0.2%
Math Symbol 10
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2430
 
6.9%
2401
 
6.8%
2302
 
6.5%
2123
 
6.0%
1979
 
5.6%
1912
 
5.4%
1861
 
5.3%
1825
 
5.2%
947
 
2.7%
869
 
2.5%
Other values (350) 16504
46.9%
Uppercase Letter
ValueCountFrequency (%)
B 47
42.7%
A 36
32.7%
C 5
 
4.5%
S 4
 
3.6%
G 4
 
3.6%
K 2
 
1.8%
E 2
 
1.8%
O 1
 
0.9%
T 1
 
0.9%
Q 1
 
0.9%
Other values (7) 7
 
6.4%
Decimal Number
ValueCountFrequency (%)
1 2453
26.5%
2 1393
15.0%
3 959
 
10.4%
4 803
 
8.7%
5 802
 
8.7%
0 690
 
7.4%
6 667
 
7.2%
7 611
 
6.6%
9 479
 
5.2%
8 405
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 1458
99.5%
. 3
 
0.2%
@ 3
 
0.2%
/ 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
s 1
33.3%
c 1
33.3%
b 1
33.3%
Space Separator
ValueCountFrequency (%)
9542
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1818
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1818
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 303
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35153
59.1%
Common 24218
40.7%
Latin 113
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2430
 
6.9%
2401
 
6.8%
2302
 
6.5%
2123
 
6.0%
1979
 
5.6%
1912
 
5.4%
1861
 
5.3%
1825
 
5.2%
947
 
2.7%
869
 
2.5%
Other values (350) 16504
46.9%
Latin
ValueCountFrequency (%)
B 47
41.6%
A 36
31.9%
C 5
 
4.4%
S 4
 
3.5%
G 4
 
3.5%
K 2
 
1.8%
E 2
 
1.8%
O 1
 
0.9%
T 1
 
0.9%
s 1
 
0.9%
Other values (10) 10
 
8.8%
Common
ValueCountFrequency (%)
9542
39.4%
1 2453
 
10.1%
) 1818
 
7.5%
( 1818
 
7.5%
, 1458
 
6.0%
2 1393
 
5.8%
3 959
 
4.0%
4 803
 
3.3%
5 802
 
3.3%
0 690
 
2.8%
Other values (9) 2482
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35153
59.1%
ASCII 24331
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9542
39.2%
1 2453
 
10.1%
) 1818
 
7.5%
( 1818
 
7.5%
, 1458
 
6.0%
2 1393
 
5.7%
3 959
 
3.9%
4 803
 
3.3%
5 802
 
3.3%
0 690
 
2.8%
Other values (29) 2595
 
10.7%
Hangul
ValueCountFrequency (%)
2430
 
6.9%
2401
 
6.8%
2302
 
6.5%
2123
 
6.0%
1979
 
5.6%
1912
 
5.4%
1861
 
5.3%
1825
 
5.2%
947
 
2.7%
869
 
2.5%
Other values (350) 16504
46.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct762
Distinct (%)40.7%
Missing1752
Missing (%)48.3%
Infinite0
Infinite (%)0.0%
Mean47867.588
Minimum46002
Maximum49526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:42.911249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46067.6
Q146926
median48014
Q348984
95-th percentile49478
Maximum49526
Range3524
Interquartile range (IQR)2058

Descriptive statistics

Standard deviation1159.4501
Coefficient of variation (CV)0.024222028
Kurtosis-1.3344471
Mean47867.588
Median Absolute Deviation (MAD)1032
Skewness-0.042331824
Sum89655992
Variance1344324.5
MonotonicityNot monotonic
2024-04-18T11:30:43.040694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49277 53
 
1.5%
46079 41
 
1.1%
47032 36
 
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 (752) 1559
43.0%
(Missing) 1752
48.3%
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 4
0.1%
46023 1
 
< 0.1%
ValueCountFrequency (%)
49526 16
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%
Distinct2691
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
2024-04-18T11:30:43.286774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length5.9216552
Min length2

Characters and Unicode

Total characters21466
Distinct characters631
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

Unique2300 ?
Unique (%)63.4%

Sample

1st row부성상사
2nd row더월마트
3rd row탑플러스마트
4th row(주)서원유통탑마트사직점
5th row찡오언니
ValueCountFrequency (%)
주식회사 87
 
2.2%
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%
남해식품 18
 
0.5%
하복식품 18
 
0.5%
주)서원유통 18
 
0.5%
Other values (2796) 3696
92.5%
2024-04-18T11:30:43.666810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
953
 
4.4%
) 878
 
4.1%
859
 
4.0%
( 854
 
4.0%
742
 
3.5%
498
 
2.3%
425
 
2.0%
404
 
1.9%
403
 
1.9%
391
 
1.8%
Other values (621) 15059
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18940
88.2%
Close Punctuation 878
 
4.1%
Open Punctuation 854
 
4.0%
Space Separator 373
 
1.7%
Uppercase Letter 265
 
1.2%
Decimal Number 68
 
0.3%
Lowercase Letter 49
 
0.2%
Other Punctuation 35
 
0.2%
Dash Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
953
 
5.0%
859
 
4.5%
742
 
3.9%
498
 
2.6%
425
 
2.2%
404
 
2.1%
403
 
2.1%
391
 
2.1%
323
 
1.7%
320
 
1.7%
Other values (559) 13622
71.9%
Uppercase Letter
ValueCountFrequency (%)
F 30
 
11.3%
O 29
 
10.9%
S 17
 
6.4%
A 16
 
6.0%
C 16
 
6.0%
G 16
 
6.0%
N 15
 
5.7%
D 15
 
5.7%
E 13
 
4.9%
M 12
 
4.5%
Other values (15) 86
32.5%
Lowercase Letter
ValueCountFrequency (%)
a 8
16.3%
n 7
14.3%
r 5
10.2%
s 5
10.2%
m 4
8.2%
e 4
8.2%
i 3
 
6.1%
t 2
 
4.1%
d 2
 
4.1%
o 2
 
4.1%
Other values (7) 7
14.3%
Decimal Number
ValueCountFrequency (%)
2 19
27.9%
3 15
22.1%
1 12
17.6%
8 6
 
8.8%
9 4
 
5.9%
5 4
 
5.9%
7 3
 
4.4%
4 2
 
2.9%
6 2
 
2.9%
0 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 14
40.0%
& 13
37.1%
, 6
17.1%
· 1
 
2.9%
' 1
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 878
100.0%
Open Punctuation
ValueCountFrequency (%)
( 854
100.0%
Space Separator
ValueCountFrequency (%)
373
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18940
88.2%
Common 2212
 
10.3%
Latin 314
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
953
 
5.0%
859
 
4.5%
742
 
3.9%
498
 
2.6%
425
 
2.2%
404
 
2.1%
403
 
2.1%
391
 
2.1%
323
 
1.7%
320
 
1.7%
Other values (559) 13622
71.9%
Latin
ValueCountFrequency (%)
F 30
 
9.6%
O 29
 
9.2%
S 17
 
5.4%
A 16
 
5.1%
C 16
 
5.1%
G 16
 
5.1%
N 15
 
4.8%
D 15
 
4.8%
E 13
 
4.1%
M 12
 
3.8%
Other values (32) 135
43.0%
Common
ValueCountFrequency (%)
) 878
39.7%
( 854
38.6%
373
16.9%
2 19
 
0.9%
3 15
 
0.7%
. 14
 
0.6%
& 13
 
0.6%
1 12
 
0.5%
8 6
 
0.3%
, 6
 
0.3%
Other values (10) 22
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18940
88.2%
ASCII 2525
 
11.8%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
953
 
5.0%
859
 
4.5%
742
 
3.9%
498
 
2.6%
425
 
2.2%
404
 
2.1%
403
 
2.1%
391
 
2.1%
323
 
1.7%
320
 
1.7%
Other values (559) 13622
71.9%
ASCII
ValueCountFrequency (%)
) 878
34.8%
( 854
33.8%
373
14.8%
F 30
 
1.2%
O 29
 
1.1%
2 19
 
0.8%
S 17
 
0.7%
A 16
 
0.6%
C 16
 
0.6%
G 16
 
0.6%
Other values (51) 277
 
11.0%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

Distinct2936
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0108009 × 1013
Minimum1.9990315 × 1013
Maximum2.021043 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:43.797773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990315 × 1013
5-th percentile2.0011121 × 1013
Q12.0050429 × 1013
median2.0101027 × 1013
Q32.0171113 × 1013
95-th percentile2.0201104 × 1013
Maximum2.021043 × 1013
Range2.2011517 × 1011
Interquartile range (IQR)1.2068412 × 1011

Descriptive statistics

Standard deviation6.590381 × 1010
Coefficient of variation (CV)0.0032774906
Kurtosis-1.4027785
Mean2.0108009 × 1013
Median Absolute Deviation (MAD)6.0313144 × 1010
Skewness0.053463169
Sum7.2891532 × 1016
Variance4.3433122 × 1021
MonotonicityNot monotonic
2024-04-18T11:30:43.923906image/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 (2926) 3357
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 (%)
20210430170503 1
< 0.1%
20210430145652 1
< 0.1%
20210429175803 1
< 0.1%
20210429175226 1
< 0.1%
20210429113223 1
< 0.1%
20210428132353 1
< 0.1%
20210427145906 1
< 0.1%
20210426171358 1
< 0.1%
20210426143803 1
< 0.1%
20210421180137 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
I
3020 
U
605 

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
83.3%
U 605
 
16.7%

Length

2024-04-18T11:30:44.041826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:44.131593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3020
83.3%
u 605
 
16.7%
Distinct479
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-02 02:40:00
2024-04-18T11:30:44.229484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T11:30:44.360825image/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 size28.4 KiB
식품소분업
3621 
<NA>
 
4

Length

Max length5
Median length5
Mean length4.9988966
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 3621
99.9%
<NA> 4
 
0.1%

Length

2024-04-18T11:30:44.474920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:44.564844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 3621
99.9%
na 4
 
0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1982
Distinct (%)57.3%
Missing169
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean387274.73
Minimum364927.7
Maximum407820.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:44.664034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum364927.7
5-th percentile378648.94
Q1382216.09
median387531.12
Q3391320.27
95-th percentile401173.52
Maximum407820.17
Range42892.471
Interquartile range (IQR)9104.176

Descriptive statistics

Standard deviation6519.8573
Coefficient of variation (CV)0.016835225
Kurtosis0.14840176
Mean387274.73
Median Absolute Deviation (MAD)4540.6057
Skewness0.34281761
Sum1.3384215 × 109
Variance42508539
MonotonicityNot monotonic
2024-04-18T11:30:44.780235image/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%
383449.669961635 33
 
0.9%
382983.91775577 32
 
0.9%
379321.651090423 29
 
0.8%
Other values (1972) 3064
84.5%
(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 

Distinct1981
Distinct (%)57.3%
Missing169
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean186460.01
Minimum170813.58
Maximum211459
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:44.902378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170813.58
5-th percentile176318.94
Q1180223.02
median186667.51
Q3191546.27
95-th percentile196546.2
Maximum211459
Range40645.417
Interquartile range (IQR)11323.246

Descriptive statistics

Standard deviation6656.5462
Coefficient of variation (CV)0.035699591
Kurtosis-0.41605691
Mean186460.01
Median Absolute Deviation (MAD)5302.3592
Skewness0.18250306
Sum6.444058 × 108
Variance44309608
MonotonicityNot monotonic
2024-04-18T11:30:45.029880image/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 33
 
0.9%
196375.470354374 32
 
0.9%
183030.975769364 29
 
0.8%
Other values (1971) 3064
84.5%
(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 7
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 size28.4 KiB
식품소분업
3621 
<NA>
 
4

Length

Max length5
Median length5
Mean length4.9988966
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 3621
99.9%
<NA> 4
 
0.1%

Length

2024-04-18T11:30:45.158075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:45.258238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 3621
99.9%
na 4
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
<NA>
3194 
0
422 
1
 
9

Length

Max length4
Median length4
Mean length3.6433103
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> 3194
88.1%
0 422
 
11.6%
1 9
 
0.2%

Length

2024-04-18T11:30:45.354517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:45.447750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3194
88.1%
0 422
 
11.6%
1 9
 
0.2%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
<NA>
3194 
0
423 
1
 
8

Length

Max length4
Median length4
Mean length3.6433103
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> 3194
88.1%
0 423
 
11.7%
1 8
 
0.2%

Length

2024-04-18T11:30:45.549461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:45.643312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3194
88.1%
0 423
 
11.7%
1 8
 
0.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
<NA>
2954 
기타
644 
주택가주변
 
15
아파트지역
 
7
학교정화(상대)
 
4

Length

Max length8
Median length4
Mean length3.6562759
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> 2954
81.5%
기타 644
 
17.8%
주택가주변 15
 
0.4%
아파트지역 7
 
0.2%
학교정화(상대) 4
 
0.1%
유흥업소밀집지역 1
 
< 0.1%

Length

2024-04-18T11:30:45.741604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:45.868483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2954
81.5%
기타 644
 
17.8%
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 size28.4 KiB
<NA>
2954 
기타
636 
자율
 
35

Length

Max length4
Median length4
Mean length3.6297931
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> 2954
81.5%
기타 636
 
17.5%
자율 35
 
1.0%

Length

2024-04-18T11:30:45.981026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:46.080361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2954
81.5%
기타 636
 
17.5%
자율 35
 
1.0%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
<NA>
3079 
상수도전용
542 
간이상수도
 
3
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.1506207
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> 3079
84.9%
상수도전용 542
 
15.0%
간이상수도 3
 
0.1%
지하수전용 1
 
< 0.1%

Length

2024-04-18T11:30:46.181943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:46.281023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3079
84.9%
상수도전용 542
 
15.0%
간이상수도 3
 
0.1%
지하수전용 1
 
< 0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3625
Missing (%)100.0%
Memory size32.0 KiB
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
0
1854 
<NA>
1768 
1
 
2
3
 
1

Length

Max length4
Median length1
Mean length2.4631724
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1854
51.1%
<NA> 1768
48.8%
1 2
 
0.1%
3 1
 
< 0.1%

Length

2024-04-18T11:30:46.398557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:46.504631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1854
51.1%
na 1768
48.8%
1 2
 
0.1%
3 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
0
1849 
<NA>
1767 
1
 
7
3
 
1
2
 
1

Length

Max length4
Median length1
Mean length2.4623448
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1849
51.0%
<NA> 1767
48.7%
1 7
 
0.2%
3 1
 
< 0.1%
2 1
 
< 0.1%

Length

2024-04-18T11:30:46.610569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:46.716982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1849
51.0%
na 1767
48.7%
1 7
 
0.2%
3 1
 
< 0.1%
2 1
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
0
1845 
<NA>
1766 
1
 
10
2
 
3
3
 
1

Length

Max length4
Median length1
Mean length2.4615172
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1845
50.9%
<NA> 1766
48.7%
1 10
 
0.3%
2 3
 
0.1%
3 1
 
< 0.1%

Length

2024-04-18T11:30:46.823441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:46.924889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1845
50.9%
na 1766
48.7%
1 10
 
0.3%
2 3
 
0.1%
3 1
 
< 0.1%

공장생산직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct7
Distinct (%)0.4%
Missing1762
Missing (%)48.6%
Infinite0
Infinite (%)0.0%
Mean0.65646806
Minimum0
Maximum1170
Zeros1824
Zeros (%)50.3%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:47.015797image/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 deviation27.10722
Coefficient of variation (CV)41.292519
Kurtosis1862.7232
Mean0.65646806
Median Absolute Deviation (MAD)0
Skewness43.157684
Sum1223
Variance734.80136
MonotonicityNot monotonic
2024-04-18T11:30:47.108500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1824
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) 1762
48.6%
ValueCountFrequency (%)
0 1824
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 1824
50.3%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
<NA>
2754 
자가
555 
임대
316 

Length

Max length4
Median length4
Mean length3.5194483
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> 2754
76.0%
자가 555
 
15.3%
임대 316
 
8.7%

Length

2024-04-18T11:30:47.228219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:47.329057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2754
76.0%
자가 555
 
15.3%
임대 316
 
8.7%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
<NA>
3459 
0
 
166

Length

Max length4
Median length4
Mean length3.8626207
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> 3459
95.4%
0 166
 
4.6%

Length

2024-04-18T11:30:47.434990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:47.526975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3459
95.4%
0 166
 
4.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
<NA>
3459 
0
 
166

Length

Max length4
Median length4
Mean length3.8626207
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> 3459
95.4%
0 166
 
4.6%

Length

2024-04-18T11:30:47.628924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:47.725779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3459
95.4%
0 166
 
4.6%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
False
3625 
ValueCountFrequency (%)
False 3625
100.0%
2024-04-18T11:30:47.800898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct187
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5522703
Minimum0
Maximum1011.02
Zeros3376
Zeros (%)93.1%
Negative0
Negative (%)0.0%
Memory size32.0 KiB
2024-04-18T11:30:47.915227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.16
Maximum1011.02
Range1011.02
Interquartile range (IQR)0

Descriptive statistics

Standard deviation22.319926
Coefficient of variation (CV)8.745126
Kurtosis1178.7392
Mean2.5522703
Median Absolute Deviation (MAD)0
Skewness28.604799
Sum9251.98
Variance498.17909
MonotonicityNot monotonic
2024-04-18T11:30:48.071469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3376
93.1%
4.0 8
 
0.2%
10.0 7
 
0.2%
6.6 7
 
0.2%
9.9 6
 
0.2%
3.0 5
 
0.1%
3.3 4
 
0.1%
16.5 4
 
0.1%
33.0 4
 
0.1%
7.0 3
 
0.1%
Other values (177) 201
 
5.5%
ValueCountFrequency (%)
0.0 3376
93.1%
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%
238.33 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%
165.03 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3625
Missing (%)100.0%
Memory size32.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3625
Missing (%)100.0%
Memory size32.0 KiB

홈페이지
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
<NA>
3624 
8
 
1

Length

Max length4
Median length4
Mean length3.9991724
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> 3624
> 99.9%
8 1
 
< 0.1%

Length

2024-04-18T11:30:48.192102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:30:48.286925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3624
> 99.9%
8 1
 
< 0.1%

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3625
Missing (%)100.0%
Memory size32.0 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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36203621식품소분업07_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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