Overview

Dataset statistics

Number of variables48
Number of observations4902
Missing cells57469
Missing cells (%)24.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 MiB
Average record size in memory413.0 B

Variable types

Numeric12
Categorical19
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description2021-05-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123093

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
남성종사자수 is highly imbalanced (67.4%)Imbalance
영업장주변구분명 is highly imbalanced (69.4%)Imbalance
등급구분명 is highly imbalanced (60.1%)Imbalance
급수시설구분명 is highly imbalanced (53.8%)Imbalance
공장사무직종업원수 is highly imbalanced (99.7%)Imbalance
공장판매직종업원수 is highly imbalanced (99.7%)Imbalance
공장생산직종업원수 is highly imbalanced (99.7%)Imbalance
건물소유구분명 is highly imbalanced (73.6%)Imbalance
다중이용업소여부 is highly imbalanced (98.6%)Imbalance
인허가취소일자 has 4902 (100.0%) missing valuesMissing
폐업일자 has 2939 (60.0%) missing valuesMissing
휴업시작일자 has 4902 (100.0%) missing valuesMissing
휴업종료일자 has 4902 (100.0%) missing valuesMissing
재개업일자 has 4902 (100.0%) missing valuesMissing
소재지전화 has 579 (11.8%) missing valuesMissing
소재지면적 has 1098 (22.4%) missing valuesMissing
소재지우편번호 has 163 (3.3%) missing valuesMissing
도로명전체주소 has 816 (16.6%) missing valuesMissing
도로명우편번호 has 876 (17.9%) missing valuesMissing
좌표정보(x) has 242 (4.9%) missing valuesMissing
좌표정보(y) has 242 (4.9%) missing valuesMissing
여성종사자수 has 4331 (88.4%) missing valuesMissing
총종업원수 has 4902 (100.0%) missing valuesMissing
본사종업원수 has 2054 (41.9%) missing valuesMissing
전통업소지정번호 has 4902 (100.0%) missing valuesMissing
전통업소주된음식 has 4902 (100.0%) missing valuesMissing
홈페이지 has 4902 (100.0%) missing valuesMissing
Unnamed: 47 has 4902 (100.0%) missing valuesMissing
폐업일자 is highly skewed (γ1 = -37.89612656)Skewed
본사종업원수 is highly skewed (γ1 = 27.50677235)Skewed
시설총규모 is highly skewed (γ1 = 38.42149563)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
홈페이지 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
여성종사자수 has 532 (10.9%) zerosZeros
본사종업원수 has 2560 (52.2%) zerosZeros
시설총규모 has 1873 (38.2%) zerosZeros

Reproduction

Analysis started2024-04-17 13:22:28.912360
Analysis finished2024-04-17 13:22:30.667588
Duration1.76 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct4902
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2451.5
Minimum1
Maximum4902
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:30.733012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile246.05
Q11226.25
median2451.5
Q33676.75
95-th percentile4656.95
Maximum4902
Range4901
Interquartile range (IQR)2450.5

Descriptive statistics

Standard deviation1415.2298
Coefficient of variation (CV)0.57729139
Kurtosis-1.2
Mean2451.5
Median Absolute Deviation (MAD)1225.5
Skewness0
Sum12017253
Variance2002875.5
MonotonicityStrictly increasing
2024-04-17T22:22:30.855992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3267 1
 
< 0.1%
3274 1
 
< 0.1%
3273 1
 
< 0.1%
3272 1
 
< 0.1%
3271 1
 
< 0.1%
3270 1
 
< 0.1%
3269 1
 
< 0.1%
3268 1
 
< 0.1%
3266 1
 
< 0.1%
Other values (4892) 4892
99.8%
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 (%)
4902 1
< 0.1%
4901 1
< 0.1%
4900 1
< 0.1%
4899 1
< 0.1%
4898 1
< 0.1%
4897 1
< 0.1%
4896 1
< 0.1%
4895 1
< 0.1%
4894 1
< 0.1%
4893 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
집단급식소
4902 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
집단급식소 4902
100.0%

Length

2024-04-17T22:22:30.959368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:31.056319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 4902
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
07_21_02_P
4902 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_21_02_P
2nd row07_21_02_P
3rd row07_21_02_P
4th row07_21_02_P
5th row07_21_02_P

Common Values

ValueCountFrequency (%)
07_21_02_P 4902
100.0%

Length

2024-04-17T22:22:31.139437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:31.220711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_21_02_p 4902
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3334324.8
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:31.298455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13300000
median3340000
Q33360000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation40022.731
Coefficient of variation (CV)0.012003249
Kurtosis-0.87619008
Mean3334324.8
Median Absolute Deviation (MAD)30000
Skewness-0.15358771
Sum1.634486 × 1010
Variance1.601819 × 109
MonotonicityNot monotonic
2024-04-17T22:22:31.406719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3360000 640
13.1%
3340000 498
10.2%
3330000 420
8.6%
3290000 412
8.4%
3390000 376
 
7.7%
3400000 321
 
6.5%
3310000 314
 
6.4%
3300000 312
 
6.4%
3350000 307
 
6.3%
3320000 307
 
6.3%
Other values (6) 995
20.3%
ValueCountFrequency (%)
3250000 81
 
1.7%
3260000 173
 
3.5%
3270000 148
 
3.0%
3280000 188
 
3.8%
3290000 412
8.4%
3300000 312
6.4%
3310000 314
6.4%
3320000 307
6.3%
3330000 420
8.6%
3340000 498
10.2%
ValueCountFrequency (%)
3400000 321
6.5%
3390000 376
7.7%
3380000 171
 
3.5%
3370000 234
 
4.8%
3360000 640
13.1%
3350000 307
6.3%
3340000 498
10.2%
3330000 420
8.6%
3320000 307
6.3%
3310000 314
6.4%

관리번호
Text

UNIQUE 

Distinct4902
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
2024-04-17T22:22:31.589959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters107844
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

Unique4902 ?
Unique (%)100.0%

Sample

1st row3310000-105-2014-00005
2nd row3300000-105-1999-00034
3rd row3330000-105-2017-00002
4th row3330000-105-2017-00003
5th row3330000-105-2017-00004
ValueCountFrequency (%)
3310000-105-2014-00005 1
 
< 0.1%
3340000-105-1990-00030 1
 
< 0.1%
3370000-105-1998-00037 1
 
< 0.1%
3340000-105-1995-00081 1
 
< 0.1%
3370000-105-1982-00004 1
 
< 0.1%
3370000-105-1981-00001 1
 
< 0.1%
3370000-105-1981-00002 1
 
< 0.1%
3370000-105-1980-00007 1
 
< 0.1%
3370000-105-1998-00025 1
 
< 0.1%
3340000-105-1989-00029 1
 
< 0.1%
Other values (4892) 4892
99.8%
2024-04-17T22:22:31.872183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 49191
45.6%
- 14706
 
13.6%
1 10248
 
9.5%
3 10200
 
9.5%
2 7204
 
6.7%
5 6333
 
5.9%
9 3209
 
3.0%
4 1933
 
1.8%
6 1917
 
1.8%
8 1504
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93138
86.4%
Dash Punctuation 14706
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49191
52.8%
1 10248
 
11.0%
3 10200
 
11.0%
2 7204
 
7.7%
5 6333
 
6.8%
9 3209
 
3.4%
4 1933
 
2.1%
6 1917
 
2.1%
8 1504
 
1.6%
7 1399
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 14706
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107844
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 49191
45.6%
- 14706
 
13.6%
1 10248
 
9.5%
3 10200
 
9.5%
2 7204
 
6.7%
5 6333
 
5.9%
9 3209
 
3.0%
4 1933
 
1.8%
6 1917
 
1.8%
8 1504
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 49191
45.6%
- 14706
 
13.6%
1 10248
 
9.5%
3 10200
 
9.5%
2 7204
 
6.7%
5 6333
 
5.9%
9 3209
 
3.0%
4 1933
 
1.8%
6 1917
 
1.8%
8 1504
 
1.4%

인허가일자
Real number (ℝ)

Distinct3008
Distinct (%)61.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20079209
Minimum19670101
Maximum20210331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:32.008917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19670101
5-th percentile19911010
Q120021018
median20080812
Q320141027
95-th percentile20200108
Maximum20210331
Range540230
Interquartile range (IQR)120008.75

Descriptive statistics

Standard deviation82937.615
Coefficient of variation (CV)0.004130522
Kurtosis0.5704457
Mean20079209
Median Absolute Deviation (MAD)60088
Skewness-0.67560322
Sum9.8428283 × 1010
Variance6.878648 × 109
MonotonicityNot monotonic
2024-04-17T22:22:32.138838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19900518 29
 
0.6%
19900330 25
 
0.5%
19980427 24
 
0.5%
19870528 18
 
0.4%
20000529 17
 
0.3%
19900612 17
 
0.3%
19980511 16
 
0.3%
19900326 14
 
0.3%
19890622 14
 
0.3%
19991130 13
 
0.3%
Other values (2998) 4715
96.2%
ValueCountFrequency (%)
19670101 1
 
< 0.1%
19690901 1
 
< 0.1%
19691120 1
 
< 0.1%
19701015 1
 
< 0.1%
19710518 1
 
< 0.1%
19740116 3
0.1%
19740201 1
 
< 0.1%
19750101 1
 
< 0.1%
19760101 1
 
< 0.1%
19760110 1
 
< 0.1%
ValueCountFrequency (%)
20210331 3
0.1%
20210330 3
0.1%
20210326 1
 
< 0.1%
20210325 1
 
< 0.1%
20210318 1
 
< 0.1%
20210316 1
 
< 0.1%
20210315 1
 
< 0.1%
20210312 1
 
< 0.1%
20210311 2
< 0.1%
20210310 1
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4902
Missing (%)100.0%
Memory size43.2 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
1
2939 
3
1963 

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 (%)
1 2939
60.0%
3 1963
40.0%

Length

2024-04-17T22:22:32.260779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:32.341388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2939
60.0%
3 1963
40.0%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
영업/정상
2939 
폐업
1963 

Length

Max length5
Median length5
Mean length3.7986536
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 (%)
영업/정상 2939
60.0%
폐업 1963
40.0%

Length

2024-04-17T22:22:32.439727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:32.527332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 2939
60.0%
폐업 1963
40.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
1
2939 
2
1963 

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 (%)
1 2939
60.0%
2 1963
40.0%

Length

2024-04-17T22:22:32.616117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:32.697589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2939
60.0%
2 1963
40.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
영업
2939 
폐업
1963 

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 (%)
영업 2939
60.0%
폐업 1963
40.0%

Length

2024-04-17T22:22:32.787396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:32.871521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 2939
60.0%
폐업 1963
40.0%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct1441
Distinct (%)73.4%
Missing2939
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean20129545
Minimum11920429
Maximum20210331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:32.973217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11920429
5-th percentile20010113
Q120100129
median20150615
Q320180718
95-th percentile20200826
Maximum20210331
Range8289902
Interquartile range (IQR)80588.5

Descriptive statistics

Standard deviation195333.28
Coefficient of variation (CV)0.0097038098
Kurtosis1591.8398
Mean20129545
Median Absolute Deviation (MAD)39888
Skewness-37.896127
Sum3.9514297 × 1010
Variance3.8155088 × 1010
MonotonicityNot monotonic
2024-04-17T22:22:33.095824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180704 11
 
0.2%
19960615 10
 
0.2%
20100608 8
 
0.2%
20200609 7
 
0.1%
20040624 7
 
0.1%
20070322 6
 
0.1%
20190521 5
 
0.1%
20191017 5
 
0.1%
20190719 5
 
0.1%
20080325 5
 
0.1%
Other values (1431) 1894
38.6%
(Missing) 2939
60.0%
ValueCountFrequency (%)
11920429 1
< 0.1%
19870309 1
< 0.1%
19891110 1
< 0.1%
19900621 1
< 0.1%
19950331 1
< 0.1%
19950412 1
< 0.1%
19950417 1
< 0.1%
19950502 1
< 0.1%
19950503 1
< 0.1%
19950530 2
< 0.1%
ValueCountFrequency (%)
20210331 1
 
< 0.1%
20210330 1
 
< 0.1%
20210324 1
 
< 0.1%
20210323 2
< 0.1%
20210322 1
 
< 0.1%
20210318 1
 
< 0.1%
20210316 3
0.1%
20210315 2
< 0.1%
20210312 3
0.1%
20210311 2
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4902
Missing (%)100.0%
Memory size43.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4902
Missing (%)100.0%
Memory size43.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4902
Missing (%)100.0%
Memory size43.2 KiB

소재지전화
Text

MISSING 

Distinct3925
Distinct (%)90.8%
Missing579
Missing (%)11.8%
Memory size38.4 KiB
2024-04-17T22:22:33.406357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.261624
Min length3

Characters and Unicode

Total characters48684
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

Unique3670 ?
Unique (%)84.9%

Sample

1st row051 626 3691
2nd row070 82804784
3rd row051 742 2365
4th row051 720 9518
5th row051 746 2619
ValueCountFrequency (%)
051 4006
37.8%
831 79
 
0.7%
070 52
 
0.5%
727 47
 
0.4%
330 38
 
0.4%
728 31
 
0.3%
332 27
 
0.3%
200 20
 
0.2%
714 19
 
0.2%
320 18
 
0.2%
Other values (3947) 6266
59.1%
2024-04-17T22:22:33.825847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8631
17.7%
1 7420
15.2%
5 7218
14.8%
6321
13.0%
2 3474
7.1%
3 3121
 
6.4%
7 2983
 
6.1%
6 2720
 
5.6%
8 2466
 
5.1%
4 2335
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42363
87.0%
Space Separator 6321
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8631
20.4%
1 7420
17.5%
5 7218
17.0%
2 3474
8.2%
3 3121
 
7.4%
7 2983
 
7.0%
6 2720
 
6.4%
8 2466
 
5.8%
4 2335
 
5.5%
9 1995
 
4.7%
Space Separator
ValueCountFrequency (%)
6321
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48684
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8631
17.7%
1 7420
15.2%
5 7218
14.8%
6321
13.0%
2 3474
7.1%
3 3121
 
6.4%
7 2983
 
6.1%
6 2720
 
5.6%
8 2466
 
5.1%
4 2335
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48684
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8631
17.7%
1 7420
15.2%
5 7218
14.8%
6321
13.0%
2 3474
7.1%
3 3121
 
6.4%
7 2983
 
6.1%
6 2720
 
5.6%
8 2466
 
5.1%
4 2335
 
4.8%

소재지면적
Text

MISSING 

Distinct2352
Distinct (%)61.8%
Missing1098
Missing (%)22.4%
Memory size38.4 KiB
2024-04-17T22:22:34.126341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.8974763
Min length3

Characters and Unicode

Total characters18630
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

Unique1961 ?
Unique (%)51.6%

Sample

1st row16.12
2nd row581.56
3rd row70.01
4th row111.10
5th row67.32
ValueCountFrequency (%)
00 753
 
19.8%
1.00 20
 
0.5%
12.00 19
 
0.5%
8.00 14
 
0.4%
20.00 14
 
0.4%
25.00 10
 
0.3%
10.00 10
 
0.3%
9.00 9
 
0.2%
18.00 9
 
0.2%
5.00 8
 
0.2%
Other values (2342) 2938
77.2%
2024-04-17T22:22:34.571964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4000
21.5%
. 3804
20.4%
1 2040
11.0%
2 1467
 
7.9%
3 1148
 
6.2%
4 1126
 
6.0%
5 1118
 
6.0%
6 1054
 
5.7%
8 1016
 
5.5%
9 926
 
5.0%
Other values (2) 931
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14794
79.4%
Other Punctuation 3836
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4000
27.0%
1 2040
13.8%
2 1467
 
9.9%
3 1148
 
7.8%
4 1126
 
7.6%
5 1118
 
7.6%
6 1054
 
7.1%
8 1016
 
6.9%
9 926
 
6.3%
7 899
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 3804
99.2%
, 32
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 18630
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4000
21.5%
. 3804
20.4%
1 2040
11.0%
2 1467
 
7.9%
3 1148
 
6.2%
4 1126
 
6.0%
5 1118
 
6.0%
6 1054
 
5.7%
8 1016
 
5.5%
9 926
 
5.0%
Other values (2) 931
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18630
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4000
21.5%
. 3804
20.4%
1 2040
11.0%
2 1467
 
7.9%
3 1148
 
6.2%
4 1126
 
6.0%
5 1118
 
6.0%
6 1054
 
5.7%
8 1016
 
5.5%
9 926
 
5.0%
Other values (2) 931
 
5.0%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct770
Distinct (%)16.2%
Missing163
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean611821.08
Minimum600012
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:34.723749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600012
5-th percentile602030
Q1607809
median612811
Q3616854
95-th percentile618819
Maximum619953
Range19941
Interquartile range (IQR)9045

Descriptive statistics

Standard deviation5534.9245
Coefficient of variation (CV)0.009046639
Kurtosis-1.1163896
Mean611821.08
Median Absolute Deviation (MAD)4993
Skewness-0.27708979
Sum2.8994201 × 109
Variance30635389
MonotonicityNot monotonic
2024-04-17T22:22:34.861603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
618819 80
 
1.6%
618230 74
 
1.5%
618818 62
 
1.3%
618817 58
 
1.2%
618820 57
 
1.2%
604836 46
 
0.9%
618280 33
 
0.7%
618814 33
 
0.7%
618220 32
 
0.7%
606080 31
 
0.6%
Other values (760) 4233
86.4%
(Missing) 163
 
3.3%
ValueCountFrequency (%)
600012 5
0.1%
600013 3
0.1%
600015 4
0.1%
600016 1
 
< 0.1%
600017 2
 
< 0.1%
600021 1
 
< 0.1%
600022 1
 
< 0.1%
600023 2
 
< 0.1%
600025 1
 
< 0.1%
600033 1
 
< 0.1%
ValueCountFrequency (%)
619953 9
0.2%
619952 20
0.4%
619951 16
0.3%
619950 1
 
< 0.1%
619913 9
0.2%
619912 19
0.4%
619911 3
 
0.1%
619906 17
0.3%
619905 5
 
0.1%
619904 5
 
0.1%
Distinct4277
Distinct (%)87.4%
Missing11
Missing (%)0.2%
Memory size38.4 KiB
2024-04-17T22:22:35.145168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length57
Mean length23.295236
Min length14

Characters and Unicode

Total characters113937
Distinct characters440
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3789 ?
Unique (%)77.5%

Sample

1st row부산광역시 남구 용호동 393-4번지
2nd row부산광역시 동래구 명장동 151-5번지 충렬고등학교
3rd row부산광역시 해운대구 좌동 1363-1번지
4th row부산광역시 해운대구 우동 1505
5th row부산광역시 해운대구 중동 228-8번지
ValueCountFrequency (%)
부산광역시 4891
 
22.3%
강서구 638
 
2.9%
사하구 497
 
2.3%
해운대구 420
 
1.9%
부산진구 412
 
1.9%
사상구 377
 
1.7%
기장군 320
 
1.5%
남구 314
 
1.4%
동래구 313
 
1.4%
북구 307
 
1.4%
Other values (4770) 13483
61.4%
2024-04-17T22:22:35.545580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17099
 
15.0%
5854
 
5.1%
5671
 
5.0%
5474
 
4.8%
1 5022
 
4.4%
5016
 
4.4%
4950
 
4.3%
4902
 
4.3%
4897
 
4.3%
4796
 
4.2%
Other values (430) 50256
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70739
62.1%
Decimal Number 21576
 
18.9%
Space Separator 17099
 
15.0%
Dash Punctuation 3701
 
3.2%
Uppercase Letter 417
 
0.4%
Open Punctuation 144
 
0.1%
Close Punctuation 142
 
0.1%
Other Punctuation 99
 
0.1%
Lowercase Letter 17
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5854
 
8.3%
5671
 
8.0%
5474
 
7.7%
5016
 
7.1%
4950
 
7.0%
4902
 
6.9%
4897
 
6.9%
4796
 
6.8%
4393
 
6.2%
1110
 
1.6%
Other values (378) 23676
33.5%
Uppercase Letter
ValueCountFrequency (%)
B 149
35.7%
T 130
31.2%
A 29
 
7.0%
L 17
 
4.1%
K 14
 
3.4%
C 13
 
3.1%
S 13
 
3.1%
I 10
 
2.4%
H 10
 
2.4%
E 5
 
1.2%
Other values (11) 27
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 5022
23.3%
2 2643
12.2%
3 2259
10.5%
5 2050
9.5%
4 1986
 
9.2%
0 1637
 
7.6%
6 1623
 
7.5%
7 1601
 
7.4%
8 1472
 
6.8%
9 1283
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
i 5
29.4%
e 5
29.4%
c 2
 
11.8%
l 2
 
11.8%
s 1
 
5.9%
o 1
 
5.9%
k 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 71
71.7%
: 11
 
11.1%
. 7
 
7.1%
& 4
 
4.0%
@ 3
 
3.0%
/ 3
 
3.0%
Open Punctuation
ValueCountFrequency (%)
( 143
99.3%
[ 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 141
99.3%
] 1
 
0.7%
Space Separator
ValueCountFrequency (%)
17099
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3701
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70739
62.1%
Common 42762
37.5%
Latin 436
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5854
 
8.3%
5671
 
8.0%
5474
 
7.7%
5016
 
7.1%
4950
 
7.0%
4902
 
6.9%
4897
 
6.9%
4796
 
6.8%
4393
 
6.2%
1110
 
1.6%
Other values (378) 23676
33.5%
Latin
ValueCountFrequency (%)
B 149
34.2%
T 130
29.8%
A 29
 
6.7%
L 17
 
3.9%
K 14
 
3.2%
C 13
 
3.0%
S 13
 
3.0%
I 10
 
2.3%
H 10
 
2.3%
i 5
 
1.1%
Other values (19) 46
 
10.6%
Common
ValueCountFrequency (%)
17099
40.0%
1 5022
 
11.7%
- 3701
 
8.7%
2 2643
 
6.2%
3 2259
 
5.3%
5 2050
 
4.8%
4 1986
 
4.6%
0 1637
 
3.8%
6 1623
 
3.8%
7 1601
 
3.7%
Other values (13) 3141
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70739
62.1%
ASCII 43196
37.9%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17099
39.6%
1 5022
 
11.6%
- 3701
 
8.6%
2 2643
 
6.1%
3 2259
 
5.2%
5 2050
 
4.7%
4 1986
 
4.6%
0 1637
 
3.8%
6 1623
 
3.8%
7 1601
 
3.7%
Other values (41) 3575
 
8.3%
Hangul
ValueCountFrequency (%)
5854
 
8.3%
5671
 
8.0%
5474
 
7.7%
5016
 
7.1%
4950
 
7.0%
4902
 
6.9%
4897
 
6.9%
4796
 
6.8%
4393
 
6.2%
1110
 
1.6%
Other values (378) 23676
33.5%
Number Forms
ValueCountFrequency (%)
2
100.0%

도로명전체주소
Text

MISSING 

Distinct3677
Distinct (%)90.0%
Missing816
Missing (%)16.6%
Memory size38.4 KiB
2024-04-17T22:22:35.879545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length53
Mean length28.712188
Min length19

Characters and Unicode

Total characters117318
Distinct characters481
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3343 ?
Unique (%)81.8%

Sample

1st row부산광역시 남구 동명로146번길 3 (용호동)
2nd row부산광역시 동래구 명장로106번길 26, 충렬고등학교 (명장동)
3rd row부산광역시 해운대구 좌동순환로15번길 24 (좌동, 장산마을아파트)
4th row부산광역시 해운대구 센텀3로 20, 지하2층 (우동, 센텀호텔 지하2층)
5th row부산광역시 해운대구 대천로42번길 42, 1층 (중동)
ValueCountFrequency (%)
부산광역시 4086
 
18.0%
강서구 542
 
2.4%
사하구 395
 
1.7%
해운대구 361
 
1.6%
1층 340
 
1.5%
부산진구 319
 
1.4%
동래구 281
 
1.2%
기장군 276
 
1.2%
남구 266
 
1.2%
사상구 265
 
1.2%
Other values (3693) 15578
68.6%
2024-04-17T22:22:36.581136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18642
 
15.9%
5498
 
4.7%
5012
 
4.3%
4783
 
4.1%
4270
 
3.6%
4268
 
3.6%
4091
 
3.5%
4038
 
3.4%
3951
 
3.4%
( 3945
 
3.4%
Other values (471) 58820
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71466
60.9%
Space Separator 18642
 
15.9%
Decimal Number 16894
 
14.4%
Open Punctuation 3945
 
3.4%
Close Punctuation 3943
 
3.4%
Other Punctuation 1716
 
1.5%
Dash Punctuation 534
 
0.5%
Uppercase Letter 155
 
0.1%
Lowercase Letter 14
 
< 0.1%
Math Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5498
 
7.7%
5012
 
7.0%
4783
 
6.7%
4270
 
6.0%
4268
 
6.0%
4091
 
5.7%
4038
 
5.7%
3951
 
5.5%
1825
 
2.6%
1739
 
2.4%
Other values (422) 31991
44.8%
Uppercase Letter
ValueCountFrequency (%)
B 32
20.6%
A 21
13.5%
C 20
12.9%
K 13
8.4%
S 11
 
7.1%
H 9
 
5.8%
L 9
 
5.8%
E 8
 
5.2%
P 5
 
3.2%
G 4
 
2.6%
Other values (10) 23
14.8%
Decimal Number
ValueCountFrequency (%)
1 3740
22.1%
2 2415
14.3%
3 1930
11.4%
4 1544
9.1%
5 1432
 
8.5%
6 1379
 
8.2%
7 1265
 
7.5%
0 1262
 
7.5%
9 1042
 
6.2%
8 885
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
35.7%
c 3
21.4%
l 2
 
14.3%
s 1
 
7.1%
i 1
 
7.1%
k 1
 
7.1%
o 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 1697
98.9%
: 6
 
0.3%
. 5
 
0.3%
@ 3
 
0.2%
& 3
 
0.2%
/ 2
 
0.1%
Space Separator
ValueCountFrequency (%)
18642
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3945
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3943
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 534
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71466
60.9%
Common 45682
38.9%
Latin 170
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5498
 
7.7%
5012
 
7.0%
4783
 
6.7%
4270
 
6.0%
4268
 
6.0%
4091
 
5.7%
4038
 
5.7%
3951
 
5.5%
1825
 
2.6%
1739
 
2.4%
Other values (422) 31991
44.8%
Latin
ValueCountFrequency (%)
B 32
18.8%
A 21
12.4%
C 20
11.8%
K 13
 
7.6%
S 11
 
6.5%
H 9
 
5.3%
L 9
 
5.3%
E 8
 
4.7%
P 5
 
2.9%
e 5
 
2.9%
Other values (18) 37
21.8%
Common
ValueCountFrequency (%)
18642
40.8%
( 3945
 
8.6%
) 3943
 
8.6%
1 3740
 
8.2%
2 2415
 
5.3%
3 1930
 
4.2%
, 1697
 
3.7%
4 1544
 
3.4%
5 1432
 
3.1%
6 1379
 
3.0%
Other values (11) 5015
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71466
60.9%
ASCII 45851
39.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18642
40.7%
( 3945
 
8.6%
) 3943
 
8.6%
1 3740
 
8.2%
2 2415
 
5.3%
3 1930
 
4.2%
, 1697
 
3.7%
4 1544
 
3.4%
5 1432
 
3.1%
6 1379
 
3.0%
Other values (38) 5184
 
11.3%
Hangul
ValueCountFrequency (%)
5498
 
7.7%
5012
 
7.0%
4783
 
6.7%
4270
 
6.0%
4268
 
6.0%
4091
 
5.7%
4038
 
5.7%
3951
 
5.5%
1825
 
2.6%
1739
 
2.4%
Other values (422) 31991
44.8%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1429
Distinct (%)35.5%
Missing876
Missing (%)17.9%
Infinite0
Infinite (%)0.0%
Mean47644.263
Minimum46000
Maximum49526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:36.728975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46000
5-th percentile46048
Q146743
median47569.5
Q348486
95-th percentile49438
Maximum49526
Range3526
Interquartile range (IQR)1743

Descriptive statistics

Standard deviation1068.657
Coefficient of variation (CV)0.02242992
Kurtosis-1.1659254
Mean47644.263
Median Absolute Deviation (MAD)840.5
Skewness0.23237434
Sum1.918158 × 108
Variance1142027.8
MonotonicityNot monotonic
2024-04-17T22:22:36.853131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46742 51
 
1.0%
46753 47
 
1.0%
46754 41
 
0.8%
46757 37
 
0.8%
46752 28
 
0.6%
46755 27
 
0.6%
46726 27
 
0.6%
46751 25
 
0.5%
46744 19
 
0.4%
46004 18
 
0.4%
Other values (1419) 3706
75.6%
(Missing) 876
 
17.9%
ValueCountFrequency (%)
46000 1
 
< 0.1%
46002 7
 
0.1%
46004 18
0.4%
46005 2
 
< 0.1%
46006 3
 
0.1%
46007 3
 
0.1%
46008 5
 
0.1%
46009 4
 
0.1%
46010 2
 
< 0.1%
46011 5
 
0.1%
ValueCountFrequency (%)
49526 5
0.1%
49525 2
 
< 0.1%
49524 2
 
< 0.1%
49523 1
 
< 0.1%
49522 2
 
< 0.1%
49521 2
 
< 0.1%
49520 2
 
< 0.1%
49518 2
 
< 0.1%
49516 3
0.1%
49515 1
 
< 0.1%
Distinct4211
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
2024-04-17T22:22:37.076209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length8.1556508
Min length2

Characters and Unicode

Total characters39979
Distinct characters631
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3690 ?
Unique (%)75.3%

Sample

1st row해누리 어린이집
2nd row충렬고등학교
3rd row충렬어린이집
4th row해운대센텀호텔 구내식당
5th row비엔케이(BNK)해운대어린이집
ValueCountFrequency (%)
어린이집 142
 
2.4%
주식회사 55
 
0.9%
의료법인 53
 
0.9%
사회복지법인 34
 
0.6%
구내식당 29
 
0.5%
유치원 19
 
0.3%
집단급식소 18
 
0.3%
요양병원 18
 
0.3%
부산광역시 16
 
0.3%
부경대학교 15
 
0.3%
Other values (4460) 5477
93.2%
2024-04-17T22:22:37.415468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1532
 
3.8%
1416
 
3.5%
1286
 
3.2%
1242
 
3.1%
1242
 
3.1%
996
 
2.5%
978
 
2.4%
962
 
2.4%
907
 
2.3%
) 897
 
2.2%
Other values (621) 28521
71.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36683
91.8%
Space Separator 978
 
2.4%
Close Punctuation 897
 
2.2%
Open Punctuation 889
 
2.2%
Uppercase Letter 298
 
0.7%
Decimal Number 162
 
0.4%
Other Punctuation 48
 
0.1%
Lowercase Letter 22
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1532
 
4.2%
1416
 
3.9%
1286
 
3.5%
1242
 
3.4%
1242
 
3.4%
996
 
2.7%
962
 
2.6%
907
 
2.5%
853
 
2.3%
729
 
2.0%
Other values (569) 25518
69.6%
Uppercase Letter
ValueCountFrequency (%)
S 38
12.8%
K 32
 
10.7%
C 28
 
9.4%
B 21
 
7.0%
A 19
 
6.4%
T 18
 
6.0%
G 15
 
5.0%
N 14
 
4.7%
M 14
 
4.7%
L 14
 
4.7%
Other values (13) 85
28.5%
Decimal Number
ValueCountFrequency (%)
2 67
41.4%
1 39
24.1%
3 23
 
14.2%
4 15
 
9.3%
5 6
 
3.7%
7 4
 
2.5%
6 3
 
1.9%
0 3
 
1.9%
9 2
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
e 6
27.3%
i 5
22.7%
w 4
18.2%
s 2
 
9.1%
k 1
 
4.5%
r 1
 
4.5%
f 1
 
4.5%
a 1
 
4.5%
h 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 20
41.7%
, 9
18.8%
& 6
 
12.5%
· 6
 
12.5%
/ 5
 
10.4%
! 1
 
2.1%
* 1
 
2.1%
Space Separator
ValueCountFrequency (%)
978
100.0%
Close Punctuation
ValueCountFrequency (%)
) 897
100.0%
Open Punctuation
ValueCountFrequency (%)
( 889
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36683
91.8%
Common 2976
 
7.4%
Latin 320
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1532
 
4.2%
1416
 
3.9%
1286
 
3.5%
1242
 
3.4%
1242
 
3.4%
996
 
2.7%
962
 
2.6%
907
 
2.5%
853
 
2.3%
729
 
2.0%
Other values (569) 25518
69.6%
Latin
ValueCountFrequency (%)
S 38
 
11.9%
K 32
 
10.0%
C 28
 
8.8%
B 21
 
6.6%
A 19
 
5.9%
T 18
 
5.6%
G 15
 
4.7%
N 14
 
4.4%
M 14
 
4.4%
L 14
 
4.4%
Other values (22) 107
33.4%
Common
ValueCountFrequency (%)
978
32.9%
) 897
30.1%
( 889
29.9%
2 67
 
2.3%
1 39
 
1.3%
3 23
 
0.8%
. 20
 
0.7%
4 15
 
0.5%
, 9
 
0.3%
5 6
 
0.2%
Other values (10) 33
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36683
91.8%
ASCII 3290
 
8.2%
None 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1532
 
4.2%
1416
 
3.9%
1286
 
3.5%
1242
 
3.4%
1242
 
3.4%
996
 
2.7%
962
 
2.6%
907
 
2.5%
853
 
2.3%
729
 
2.0%
Other values (569) 25518
69.6%
ASCII
ValueCountFrequency (%)
978
29.7%
) 897
27.3%
( 889
27.0%
2 67
 
2.0%
1 39
 
1.2%
S 38
 
1.2%
K 32
 
1.0%
C 28
 
0.9%
3 23
 
0.7%
B 21
 
0.6%
Other values (41) 278
 
8.4%
None
ValueCountFrequency (%)
· 6
100.0%

최종수정시점
Real number (ℝ)

Distinct4243
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0159177 × 1013
Minimum1.9990209 × 1013
Maximum2.0210331 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:37.567077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990209 × 1013
5-th percentile2.0030905 × 1013
Q12.0160809 × 1013
median2.0170822 × 1013
Q32.0190526 × 1013
95-th percentile2.0201222 × 1013
Maximum2.0210331 × 1013
Range2.2012218 × 1011
Interquartile range (IQR)2.9717021 × 1010

Descriptive statistics

Standard deviation4.9505216 × 1010
Coefficient of variation (CV)0.0024557162
Kurtosis2.1269674
Mean2.0159177 × 1013
Median Absolute Deviation (MAD)1.9599961 × 1010
Skewness-1.7029207
Sum9.8820285 × 1016
Variance2.4507665 × 1021
MonotonicityNot monotonic
2024-04-17T22:22:37.689955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170822192441 204
 
4.2%
20170822191707 114
 
2.3%
20170822191632 91
 
1.9%
20020830000000 52
 
1.1%
20170822191614 42
 
0.9%
20010725000000 19
 
0.4%
20020226000000 11
 
0.2%
20020625000000 10
 
0.2%
19990304000000 8
 
0.2%
20031216000000 8
 
0.2%
Other values (4233) 4343
88.6%
ValueCountFrequency (%)
19990209000000 1
 
< 0.1%
19990304000000 8
0.2%
19990318000000 6
0.1%
19990326000000 1
 
< 0.1%
19990406000000 4
0.1%
19990415000000 2
 
< 0.1%
19990504000000 1
 
< 0.1%
19990519000000 1
 
< 0.1%
19990708000000 1
 
< 0.1%
19990723000000 1
 
< 0.1%
ValueCountFrequency (%)
20210331175231 1
< 0.1%
20210331163617 1
< 0.1%
20210331162314 1
< 0.1%
20210331155720 1
< 0.1%
20210331152105 1
< 0.1%
20210331112839 1
< 0.1%
20210331101442 1
< 0.1%
20210331100901 1
< 0.1%
20210330161101 1
< 0.1%
20210330160239 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
I
3415 
U
1487 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 3415
69.7%
U 1487
30.3%

Length

2024-04-17T22:22:37.801731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:37.883227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3415
69.7%
u 1487
30.3%
Distinct593
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-02 02:40:00
2024-04-17T22:22:38.002675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:22:38.145433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
집단급식소
1255 
어린이집
1250 
산업체
798 
학교
711 
병원
482 
Other values (6)
406 

Length

Max length8
Median length6
Mean length3.7399021
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row어린이집
2nd row학교
3rd row어린이집
4th row산업체
5th row어린이집

Common Values

ValueCountFrequency (%)
집단급식소 1255
25.6%
어린이집 1250
25.5%
산업체 798
16.3%
학교 711
14.5%
병원 482
 
9.8%
사회복지시설 225
 
4.6%
공공기관 101
 
2.1%
기타 집단급식소 56
 
1.1%
기숙사 17
 
0.3%
수련원 5
 
0.1%

Length

2024-04-17T22:22:38.270959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
집단급식소 1311
26.4%
어린이집 1250
25.2%
산업체 798
16.1%
학교 711
14.3%
병원 482
 
9.7%
사회복지시설 225
 
4.5%
공공기관 101
 
2.0%
기타 56
 
1.1%
기숙사 17
 
0.3%
수련원 5
 
0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3498
Distinct (%)75.1%
Missing242
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean385720.35
Minimum365010.39
Maximum407879.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:38.391116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum365010.39
5-th percentile368652.98
Q1381053.65
median386787.8
Q3391000.32
95-th percentile398193.28
Maximum407879.3
Range42868.907
Interquartile range (IQR)9946.6676

Descriptive statistics

Standard deviation8284.7973
Coefficient of variation (CV)0.021478767
Kurtosis0.12266615
Mean385720.35
Median Absolute Deviation (MAD)4949.647
Skewness-0.44737822
Sum1.7974568 × 109
Variance68637867
MonotonicityNot monotonic
2024-04-17T22:22:38.512863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
391796.495138673 11
 
0.2%
379240.573215267 10
 
0.2%
383898.91114891 9
 
0.2%
388182.381367829 8
 
0.2%
382570.401135476 8
 
0.2%
382865.897094966 7
 
0.1%
383322.180241811 7
 
0.1%
371070.269343027 7
 
0.1%
389816.233000769 7
 
0.1%
389811.392307835 7
 
0.1%
Other values (3488) 4579
93.4%
(Missing) 242
 
4.9%
ValueCountFrequency (%)
365010.390597385 1
 
< 0.1%
365093.532168897 1
 
< 0.1%
365094.004922601 1
 
< 0.1%
365115.866440903 1
 
< 0.1%
365292.225416155 3
0.1%
365307.209621952 1
 
< 0.1%
365331.554111646 1
 
< 0.1%
365359.221940167 1
 
< 0.1%
365395.142740959 1
 
< 0.1%
365399.645488953 4
0.1%
ValueCountFrequency (%)
407879.297470728 1
< 0.1%
407785.942175253 1
< 0.1%
407561.613314864 1
< 0.1%
407533.057972118 2
< 0.1%
407509.292975868 1
< 0.1%
406868.288952732 1
< 0.1%
406544.35494323 1
< 0.1%
406242.577428169 1
< 0.1%
405967.49653678 1
< 0.1%
405914.665215376 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct3498
Distinct (%)75.1%
Missing242
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean186558.6
Minimum173008.04
Maximum211242.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:38.653001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173008.04
5-th percentile177295.08
Q1180437.54
median186114.74
Q3190962.43
95-th percentile198761.32
Maximum211242.85
Range38234.819
Interquartile range (IQR)10524.89

Descriptive statistics

Standard deviation6981.4329
Coefficient of variation (CV)0.037422198
Kurtosis0.31289143
Mean186558.6
Median Absolute Deviation (MAD)5119.9389
Skewness0.66068241
Sum8.6936307 × 108
Variance48740405
MonotonicityNot monotonic
2024-04-17T22:22:38.782344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
183632.373950837 11
 
0.2%
181413.478007094 10
 
0.2%
182014.846889314 9
 
0.2%
185024.662471639 8
 
0.2%
187570.045156033 8
 
0.2%
190186.827804782 7
 
0.1%
197560.128736032 7
 
0.1%
178844.957191338 7
 
0.1%
193329.605871168 7
 
0.1%
180523.822532435 7
 
0.1%
Other values (3488) 4579
93.4%
(Missing) 242
 
4.9%
ValueCountFrequency (%)
173008.035213696 1
< 0.1%
173992.30883079 1
< 0.1%
174047.04848343 1
< 0.1%
174073.798168057 1
< 0.1%
174114.148590962 1
< 0.1%
174122.568890976 2
< 0.1%
174140.916066183 1
< 0.1%
174195.454037802 1
< 0.1%
174213.492106852 1
< 0.1%
174256.59992362 2
< 0.1%
ValueCountFrequency (%)
211242.854248711 1
< 0.1%
211219.461687024 1
< 0.1%
210727.650444124 1
< 0.1%
210670.814435815 1
< 0.1%
210424.660206307 1
< 0.1%
210246.141637797 1
< 0.1%
210015.613769918 1
< 0.1%
209816.460852413 1
< 0.1%
209053.527592549 1
< 0.1%
208963.76199907 2
< 0.1%

위생업태명
Categorical

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
집단급식소
1255 
어린이집
1249 
산업체
802 
학교
713 
병원
482 
Other values (6)
401 

Length

Max length8
Median length6
Mean length3.7337821
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row어린이집
2nd row학교
3rd row어린이집
4th row산업체
5th row어린이집

Common Values

ValueCountFrequency (%)
집단급식소 1255
25.6%
어린이집 1249
25.5%
산업체 802
16.4%
학교 713
14.5%
병원 482
 
9.8%
사회복지시설 226
 
4.6%
공공기관 101
 
2.1%
기타 집단급식소 50
 
1.0%
기숙사 17
 
0.3%
수련원 5
 
0.1%

Length

2024-04-17T22:22:38.912074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
집단급식소 1305
26.4%
어린이집 1249
25.2%
산업체 802
16.2%
학교 713
14.4%
병원 482
 
9.7%
사회복지시설 226
 
4.6%
공공기관 101
 
2.0%
기타 50
 
1.0%
기숙사 17
 
0.3%
수련원 5
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
4350 
0
546 
1
 
6

Length

Max length4
Median length4
Mean length3.6621787
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> 4350
88.7%
0 546
 
11.1%
1 6
 
0.1%

Length

2024-04-17T22:22:39.024398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:39.110816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4350
88.7%
0 546
 
11.1%
1 6
 
0.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)2.5%
Missing4331
Missing (%)88.4%
Infinite0
Infinite (%)0.0%
Mean0.40980736
Minimum0
Maximum20
Zeros532
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:39.190812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8992635
Coefficient of variation (CV)4.6345276
Kurtosis45.896119
Mean0.40980736
Median Absolute Deviation (MAD)0
Skewness6.2231678
Sum234
Variance3.6072019
MonotonicityNot monotonic
2024-04-17T22:22:39.294034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 532
 
10.9%
3 7
 
0.1%
5 6
 
0.1%
2 5
 
0.1%
9 4
 
0.1%
4 4
 
0.1%
8 3
 
0.1%
6 2
 
< 0.1%
14 2
 
< 0.1%
1 2
 
< 0.1%
Other values (4) 4
 
0.1%
(Missing) 4331
88.4%
ValueCountFrequency (%)
0 532
10.9%
1 2
 
< 0.1%
2 5
 
0.1%
3 7
 
0.1%
4 4
 
0.1%
5 6
 
0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
8 3
 
0.1%
9 4
 
0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
18 1
 
< 0.1%
14 2
 
< 0.1%
10 1
 
< 0.1%
9 4
0.1%
8 3
0.1%
7 1
 
< 0.1%
6 2
 
< 0.1%
5 6
0.1%
4 4
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
3884 
기타
986 
주택가주변
 
15
학교정화(상대)
 
9
학교정화(절대)
 
6

Length

Max length8
Median length4
Mean length3.6134231
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3884
79.2%
기타 986
 
20.1%
주택가주변 15
 
0.3%
학교정화(상대) 9
 
0.2%
학교정화(절대) 6
 
0.1%
아파트지역 2
 
< 0.1%

Length

2024-04-17T22:22:39.408326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:39.506310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3884
79.2%
기타 986
 
20.1%
주택가주변 15
 
0.3%
학교정화(상대 9
 
0.2%
학교정화(절대 6
 
0.1%
아파트지역 2
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
3884 
기타
966 
자율
 
51
우수
 
1

Length

Max length4
Median length4
Mean length3.5846593
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3884
79.2%
기타 966
 
19.7%
자율 51
 
1.0%
우수 1
 
< 0.1%

Length

2024-04-17T22:22:39.624165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:39.715338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3884
79.2%
기타 966
 
19.7%
자율 51
 
1.0%
우수 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
상수도전용
2996 
<NA>
1830 
지하수전용
 
55
상수도(음용)지하수(주방용)겸용
 
18
간이상수도
 
3

Length

Max length17
Median length5
Mean length4.6707466
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2996
61.1%
<NA> 1830
37.3%
지하수전용 55
 
1.1%
상수도(음용)지하수(주방용)겸용 18
 
0.4%
간이상수도 3
 
0.1%

Length

2024-04-17T22:22:39.814435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:39.904984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2996
61.1%
na 1830
37.3%
지하수전용 55
 
1.1%
상수도(음용)지하수(주방용)겸용 18
 
0.4%
간이상수도 3
 
0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4902
Missing (%)100.0%
Memory size43.2 KiB

본사종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct19
Distinct (%)0.7%
Missing2054
Missing (%)41.9%
Infinite0
Infinite (%)0.0%
Mean0.3809691
Minimum0
Maximum113
Zeros2560
Zeros (%)52.2%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:39.999569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum113
Range113
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.8104657
Coefficient of variation (CV)7.3771487
Kurtosis992.10335
Mean0.3809691
Median Absolute Deviation (MAD)0
Skewness27.506772
Sum1085
Variance7.8987174
MonotonicityNot monotonic
2024-04-17T22:22:40.096277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 2560
52.2%
1 108
 
2.2%
2 58
 
1.2%
3 37
 
0.8%
4 24
 
0.5%
5 19
 
0.4%
6 12
 
0.2%
8 7
 
0.1%
7 5
 
0.1%
9 4
 
0.1%
Other values (9) 14
 
0.3%
(Missing) 2054
41.9%
ValueCountFrequency (%)
0 2560
52.2%
1 108
 
2.2%
2 58
 
1.2%
3 37
 
0.8%
4 24
 
0.5%
5 19
 
0.4%
6 12
 
0.2%
7 5
 
0.1%
8 7
 
0.1%
9 4
 
0.1%
ValueCountFrequency (%)
113 1
 
< 0.1%
61 1
 
< 0.1%
35 1
 
< 0.1%
20 1
 
< 0.1%
18 1
 
< 0.1%
16 3
0.1%
13 1
 
< 0.1%
12 1
 
< 0.1%
10 4
0.1%
9 4
0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
4901 
0
 
1

Length

Max length4
Median length4
Mean length3.999388
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> 4901
> 99.9%
0 1
 
< 0.1%

Length

2024-04-17T22:22:40.227779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:40.315106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4901
> 99.9%
0 1
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
4901 
0
 
1

Length

Max length4
Median length4
Mean length3.999388
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> 4901
> 99.9%
0 1
 
< 0.1%

Length

2024-04-17T22:22:40.402381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:40.515928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4901
> 99.9%
0 1
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
4901 
0
 
1

Length

Max length4
Median length4
Mean length3.999388
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> 4901
> 99.9%
0 1
 
< 0.1%

Length

2024-04-17T22:22:40.601633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:40.690356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4901
> 99.9%
0 1
 
< 0.1%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
4506 
자가
 
386
임대
 
10

Length

Max length4
Median length4
Mean length3.8384333
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> 4506
91.9%
자가 386
 
7.9%
임대 10
 
0.2%

Length

2024-04-17T22:22:40.781076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:40.873300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4506
91.9%
자가 386
 
7.9%
임대 10
 
0.2%

보증액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
3197 
0
1705 

Length

Max length4
Median length4
Mean length2.9565483
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> 3197
65.2%
0 1705
34.8%

Length

2024-04-17T22:22:40.986048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:41.078544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3197
65.2%
0 1705
34.8%

월세액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
3197 
0
1705 

Length

Max length4
Median length4
Mean length2.9565483
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> 3197
65.2%
0 1705
34.8%

Length

2024-04-17T22:22:41.164826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:22:41.244889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3197
65.2%
0 1705
34.8%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
False
4896 
True
 
6
ValueCountFrequency (%)
False 4896
99.9%
True 6
 
0.1%
2024-04-17T22:22:41.318256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct2095
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.477587
Minimum0
Maximum17067
Zeros1873
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-17T22:22:41.414193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median13.735
Q343.875
95-th percentile206.775
Maximum17067
Range17067
Interquartile range (IQR)43.875

Descriptive statistics

Standard deviation320.14294
Coefficient of variation (CV)5.8765992
Kurtosis1838.3417
Mean54.477587
Median Absolute Deviation (MAD)13.735
Skewness38.421496
Sum267049.13
Variance102491.5
MonotonicityNot monotonic
2024-04-17T22:22:41.835821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1873
38.2%
12.0 22
 
0.4%
20.0 17
 
0.3%
30.0 15
 
0.3%
18.0 15
 
0.3%
25.0 12
 
0.2%
24.0 12
 
0.2%
10.0 11
 
0.2%
14.0 11
 
0.2%
8.0 11
 
0.2%
Other values (2085) 2903
59.2%
ValueCountFrequency (%)
0.0 1873
38.2%
1.0 1
 
< 0.1%
1.38 1
 
< 0.1%
2.08 2
 
< 0.1%
3.0 2
 
< 0.1%
3.2 1
 
< 0.1%
3.22 1
 
< 0.1%
3.37 1
 
< 0.1%
3.62 1
 
< 0.1%
3.67 1
 
< 0.1%
ValueCountFrequency (%)
17067.0 1
< 0.1%
10058.04 1
< 0.1%
4950.0 1
< 0.1%
3623.63 1
< 0.1%
2491.24 2
< 0.1%
2288.8 1
< 0.1%
2115.5 1
< 0.1%
1914.0 1
< 0.1%
1887.0 1
< 0.1%
1534.5 2
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4902
Missing (%)100.0%
Memory size43.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4902
Missing (%)100.0%
Memory size43.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4902
Missing (%)100.0%
Memory size43.2 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4902
Missing (%)100.0%
Memory size43.2 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01집단급식소07_21_02_P33100003310000-105-2014-0000520140519<NA>1영업/정상1영업<NA><NA><NA><NA>051 626 369116.12608834부산광역시 남구 용호동 393-4번지부산광역시 남구 동명로146번길 3 (용호동)48584해누리 어린이집20191119104729U2019-11-21 02:40:00.0어린이집392546.857164182042.264355어린이집<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N9.45<NA><NA><NA><NA>
12집단급식소07_21_02_P33000003300000-105-1999-0003419990406<NA>1영업/정상1영업<NA><NA><NA><NA>070 82804784581.56607810부산광역시 동래구 명장동 151-5번지 충렬고등학교부산광역시 동래구 명장로106번길 26, 충렬고등학교 (명장동)47776충렬고등학교20180112171504I2018-08-31 23:59:59.0학교392063.322531191275.517897학교<NA><NA>기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N198.96<NA><NA><NA><NA>
23집단급식소07_21_02_P33300003330000-105-2017-0000220170228<NA>1영업/정상1영업<NA><NA><NA><NA>051 742 236570.01612853부산광역시 해운대구 좌동 1363-1번지부산광역시 해운대구 좌동순환로15번길 24 (좌동, 장산마을아파트)48084충렬어린이집20170308160315I2018-08-31 23:59:59.0어린이집397149.283455187795.336413어린이집<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N27.8<NA><NA><NA><NA>
34집단급식소07_21_02_P33300003330000-105-2017-0000320170228<NA>1영업/정상1영업<NA><NA><NA><NA>051 720 9518111.10612889부산광역시 해운대구 우동 1505부산광역시 해운대구 센텀3로 20, 지하2층 (우동, 센텀호텔 지하2층)48060해운대센텀호텔 구내식당20210112110358U2021-01-14 02:40:00.0산업체394254.000317187484.983032산업체<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N50.42<NA><NA><NA><NA>
45집단급식소07_21_02_P33300003330000-105-2017-0000420170228<NA>1영업/정상1영업<NA><NA><NA><NA>051 746 261967.32612846부산광역시 해운대구 중동 228-8번지부산광역시 해운대구 대천로42번길 42, 1층 (중동)48082비엔케이(BNK)해운대어린이집20170307172035I2018-08-31 23:59:59.0어린이집397754.135252187964.286349어린이집<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N27.27<NA><NA><NA><NA>
56집단급식소07_21_02_P33300003330000-105-2017-0000520170728<NA>1영업/정상1영업<NA><NA><NA><NA>051 610 307175.17612821부산광역시 해운대구 우동 603-19번지부산광역시 해운대구 구남로 9, 4층 (우동, 라마다앙코르해운대호텔 4층)48095라마다앙코르해운대호텔 직원식당20171206171953I2018-08-31 23:59:59.0산업체396697.41331187037.673015산업체<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N31.11<NA><NA><NA><NA>
67집단급식소07_21_02_P33300003330000-105-2017-0000920171103<NA>1영업/정상1영업<NA><NA><NA><NA>051 720 4584101.61612070부산광역시 해운대구 석대동 637번지부산광역시 해운대구 반송로 523, 4층 (석대동)48002해운대우체국 석대동20171107165054I2018-08-31 23:59:59.0공공기관392971.294534193081.482641공공기관<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N53.57<NA><NA><NA><NA>
78집단급식소07_21_02_P34000003400000-105-2014-0001620140617<NA>1영업/정상1영업<NA><NA><NA><NA>0517281902864.84<NA>부산광역시 기장군 정관읍 용수리 221번지 3층 중 3층부산광역시 기장군 정관읍 가동옛길 37 (3층 중 3층)46004피터팬유치원20170714134518I2018-08-31 23:59:59.0어린이집398134.354653206060.329231어린이집<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N39.09<NA><NA><NA><NA>
89집단급식소07_21_02_P34000003400000-105-2013-0002420131018<NA>1영업/정상1영업<NA><NA><NA><NA>051 727 5080223.69619951부산광역시 기장군 장안읍 기룡리 69-1번지부산광역시 기장군 장안읍 한골길 159-1646031효성노인건강센터20190201143440U2019-02-03 02:40:00.0사회복지시설405496.613204208963.761999사회복지시설<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N82.26<NA><NA><NA><NA>
910집단급식소07_21_02_P34000003400000-105-2014-0002020141203<NA>1영업/정상1영업<NA><NA><NA><NA>051 7275270151.30<NA>부산광역시 기장군 정관읍 달산리 1110-4번지 1층부산광역시 기장군 정관읍 산단5로 103-14, 1층46026경신사20170707144158I2018-08-31 23:59:59.0산업체400028.969816204398.62101산업체<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N49.5<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
48924893집단급식소07_21_02_P34000003400000-105-2016-0001220161013<NA>3폐업2폐업20180206<NA><NA><NA>051 727 788111.47<NA>부산광역시 기장군 정관읍 용수리 1275번지 116동부산광역시 기장군 정관읍 정관5로 144, 116동 1층46013풀리페어린이집20180206144741I2018-08-31 23:59:59.0어린이집398180.304244205553.364264어린이집<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N11.47<NA><NA><NA><NA>
48934894집단급식소07_21_02_P34000003400000-105-2016-0001320161019<NA>3폐업2폐업20200518<NA><NA><NA>070 47730388113.13619906부산광역시 기장군 기장읍 청강리 60-4번지부산광역시 기장군 기장읍 차성남로 103, 지하1층46064우리들요양병원20200518141743U2020-05-20 02:40:00.0병원401956.660841195812.485272병원<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N113.13<NA><NA><NA><NA>
48944895집단급식소07_21_02_P34000003400000-105-2015-0000920150622<NA>3폐업2폐업20200818<NA><NA><NA>051 728 5307320.51619952부산광역시 기장군 장안읍 반룡리 839-2 3층부산광역시 기장군 장안읍 장안산단9로 172, 3층46034태흥테크20200818165046U2020-09-16 02:40:00.0산업체405252.086588205193.47087산업체<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N51.75<NA><NA><NA><NA>
48954896집단급식소07_21_02_P34000003400000-105-2017-0001720170927<NA>3폐업2폐업20191211<NA><NA><NA><NA>539.10619912부산광역시 기장군 일광면 삼성리 H7번지 일광도시개발사업지구<NA><NA>지에스건설(주)부산일광자이함바식당20191211160029U2019-12-13 02:40:00.0산업체<NA><NA>산업체<NA><NA><NA><NA>지하수전용<NA>0<NA><NA><NA><NA>00N114.9<NA><NA><NA><NA>
48964897집단급식소07_21_02_P32800003280000-105-2018-0000520181213<NA>3폐업2폐업20210330<NA><NA><NA><NA>52.34606080부산광역시 영도구 동삼동 1121부산광역시 영도구 상리로 30 (동삼동)49093동삼사회복지관20210330114808U2021-04-01 02:40:00.0사회복지시설388488.108655177979.767287사회복지시설<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N17.85<NA><NA><NA><NA>
48974898집단급식소07_21_02_P33100003310000-105-2018-0000620181203<NA>3폐업2폐업20200703<NA><NA><NA>051 621 44139.90608836부산광역시 남구 용호동 465 삼육탕부산광역시 남구 이기대공원로26번길 45-4, 1층 (용호동)48580푸른숲어린이집20200703175211U2020-07-05 02:40:00.0어린이집392710.930601182408.104137어린이집<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N9.9<NA><NA><NA><NA>
48984899집단급식소07_21_02_P32900003290000-105-2018-0002120181221<NA>3폐업2폐업20210219<NA><NA><NA>051 7147131.00614812부산광역시 부산진구 개금동 511-1 개금메디칼빌딩부산광역시 부산진구 가야대로 451, 개금메디칼빌딩 3층 (개금동)47268진아동병원20210219152727U2021-02-21 02:40:00.0병원384150.489572185697.071402병원<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N0.0<NA><NA><NA><NA>
48994900집단급식소07_21_02_P33500003350000-105-2018-0000920181119<NA>3폐업2폐업20200507<NA><NA><NA><NA>15.91609390부산광역시 금정구 장전동 732번지 금정산 쌍용예가 아파트부산광역시 금정구 금강로379번길 50, 301동 1층 (장전동, 금정산 쌍용예가 아파트)46246아이미래어린이집20200507112355U2020-05-09 02:40:00.0어린이집389664.786093195729.022284어린이집<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N15.91<NA><NA><NA><NA>
49004901집단급식소07_21_02_P33000003300000-105-2018-0001720181221<NA>3폐업2폐업20200406<NA><NA><NA>051 506 355736.46607840부산광역시 동래구 온천동 1643번지부산광역시 동래구 쇠미로121번길 106 (온천동)47870동래새싹유치원20200406113715U2020-04-08 02:40:00.0기타 집단급식소387319.654988191455.905223기타 집단급식소<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N31.06<NA><NA><NA><NA>
49014902집단급식소07_21_02_P34000003400000-105-2020-0001520201204<NA>3폐업2폐업20210303<NA><NA><NA><NA>26.30619901부산광역시 기장군 기장읍 교리 345-5 하늘빛어린이집부산광역시 기장군 기장읍 차성로390번길 24, 하늘빛어린이집 1층46056하늘빛 어린이집20210303112859U2021-03-05 02:40:00.0어린이집401686.661673197019.356662어린이집<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA>00N15.4<NA><NA><NA><NA>