Overview

Dataset statistics

Number of variables48
Number of observations10000
Missing cells132033
Missing cells (%)27.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 MiB
Average record size in memory421.0 B

Variable types

Numeric12
Categorical18
Text7
Unsupported9
DateTime1
Boolean1

Dataset

Description2021-02-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123123

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
전통업소주된음식 has constant value ""Constant
영업장주변구분명 is highly imbalanced (59.1%)Imbalance
등급구분명 is highly imbalanced (58.2%)Imbalance
급수시설구분명 is highly imbalanced (59.9%)Imbalance
본사종업원수 is highly imbalanced (99.6%)Imbalance
공장사무직종업원수 is highly imbalanced (99.6%)Imbalance
공장판매직종업원수 is highly imbalanced (99.6%)Imbalance
공장생산직종업원수 is highly imbalanced (99.6%)Imbalance
보증액 is highly imbalanced (99.6%)Imbalance
월세액 is highly imbalanced (99.6%)Imbalance
다중이용업소여부 is highly imbalanced (76.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 4425 (44.2%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
소재지전화 has 4339 (43.4%) missing valuesMissing
소재지면적 has 1158 (11.6%) missing valuesMissing
소재지우편번호 has 202 (2.0%) missing valuesMissing
도로명전체주소 has 2955 (29.5%) missing valuesMissing
도로명우편번호 has 3031 (30.3%) missing valuesMissing
좌표정보(x) has 378 (3.8%) missing valuesMissing
좌표정보(y) has 378 (3.8%) missing valuesMissing
남성종사자수 has 7592 (75.9%) missing valuesMissing
여성종사자수 has 7556 (75.6%) missing valuesMissing
총종업원수 has 10000 (100.0%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 9999 (> 99.9%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
Unnamed: 47 has 10000 (100.0%) missing valuesMissing
인허가일자 is highly skewed (γ1 = -29.25017632)Skewed
폐업일자 is highly skewed (γ1 = -36.81901961)Skewed
남성종사자수 is highly skewed (γ1 = 21.86567491)Skewed
여성종사자수 is highly skewed (γ1 = 23.8799923)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
건물소유구분명 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
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
남성종사자수 has 2301 (23.0%) zerosZeros
여성종사자수 has 2221 (22.2%) zerosZeros
시설총규모 has 1499 (15.0%) zerosZeros

Reproduction

Analysis started2024-04-16 19:35:43.180071
Analysis finished2024-04-16 19:35:45.634226
Duration2.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11757.7
Minimum1
Maximum23418
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:45.692643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1211.95
Q15896.25
median11786.5
Q317649.25
95-th percentile22230.05
Maximum23418
Range23417
Interquartile range (IQR)11753

Descriptive statistics

Standard deviation6773.1174
Coefficient of variation (CV)0.57605801
Kurtosis-1.2111535
Mean11757.7
Median Absolute Deviation (MAD)5873
Skewness-0.010237329
Sum1.17577 × 108
Variance45875119
MonotonicityNot monotonic
2024-04-17T04:35:45.819541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20521 1
 
< 0.1%
13023 1
 
< 0.1%
10686 1
 
< 0.1%
21137 1
 
< 0.1%
20967 1
 
< 0.1%
207 1
 
< 0.1%
13785 1
 
< 0.1%
50 1
 
< 0.1%
22006 1
 
< 0.1%
14886 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
4 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
ValueCountFrequency (%)
23418 1
< 0.1%
23409 1
< 0.1%
23408 1
< 0.1%
23406 1
< 0.1%
23404 1
< 0.1%
23403 1
< 0.1%
23402 1
< 0.1%
23401 1
< 0.1%
23400 1
< 0.1%
23399 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
휴게음식점
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
휴게음식점 10000
100.0%

Length

2024-04-17T04:35:45.939230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:46.027398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 10000
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
07_24_05_P
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_24_05_P
2nd row07_24_05_P
3rd row07_24_05_P
4th row07_24_05_P
5th row07_24_05_P

Common Values

ValueCountFrequency (%)
07_24_05_P 10000
100.0%

Length

2024-04-17T04:35:46.112226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:46.200364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_24_05_p 10000
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3322747
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:46.277560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3320000
Q33350000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation42373.855
Coefficient of variation (CV)0.012752658
Kurtosis-0.91185213
Mean3322747
Median Absolute Deviation (MAD)30000
Skewness0.200538
Sum3.322747 × 1010
Variance1.7955435 × 109
MonotonicityNot monotonic
2024-04-17T04:35:46.399172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 1564
15.6%
3330000 1212
12.1%
3300000 808
 
8.1%
3350000 745
 
7.4%
3320000 646
 
6.5%
3310000 642
 
6.4%
3380000 634
 
6.3%
3390000 588
 
5.9%
3250000 547
 
5.5%
3400000 527
 
5.3%
Other values (6) 2087
20.9%
ValueCountFrequency (%)
3250000 547
 
5.5%
3260000 348
 
3.5%
3270000 455
 
4.5%
3280000 291
 
2.9%
3290000 1564
15.6%
3300000 808
8.1%
3310000 642
6.4%
3320000 646
6.5%
3330000 1212
12.1%
3340000 388
 
3.9%
ValueCountFrequency (%)
3400000 527
5.3%
3390000 588
5.9%
3380000 634
6.3%
3370000 274
 
2.7%
3360000 331
 
3.3%
3350000 745
7.4%
3340000 388
 
3.9%
3330000 1212
12.1%
3320000 646
6.5%
3310000 642
6.4%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T04:35:46.601542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3290000-104-1998-06481
2nd row3290000-104-1993-06590
3rd row3340000-104-2016-00077
4th row3290000-104-1998-06153
5th row3380000-104-2010-00007
ValueCountFrequency (%)
3290000-104-1998-06481 1
 
< 0.1%
3400000-104-2015-00066 1
 
< 0.1%
3300000-104-2016-00043 1
 
< 0.1%
3290000-104-2014-00154 1
 
< 0.1%
3300000-104-1995-00737 1
 
< 0.1%
3330000-104-2014-00076 1
 
< 0.1%
3290000-104-1984-06071 1
 
< 0.1%
3300000-104-2008-00021 1
 
< 0.1%
3370000-104-2005-00020 1
 
< 0.1%
3380000-104-2016-00079 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T04:35:46.915612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89450
40.7%
- 30000
 
13.6%
1 23063
 
10.5%
3 20949
 
9.5%
2 16494
 
7.5%
4 14286
 
6.5%
9 8982
 
4.1%
5 4610
 
2.1%
8 4440
 
2.0%
7 3912
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89450
47.1%
1 23063
 
12.1%
3 20949
 
11.0%
2 16494
 
8.7%
4 14286
 
7.5%
9 8982
 
4.7%
5 4610
 
2.4%
8 4440
 
2.3%
7 3912
 
2.1%
6 3814
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89450
40.7%
- 30000
 
13.6%
1 23063
 
10.5%
3 20949
 
9.5%
2 16494
 
7.5%
4 14286
 
6.5%
9 8982
 
4.1%
5 4610
 
2.1%
8 4440
 
2.0%
7 3912
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89450
40.7%
- 30000
 
13.6%
1 23063
 
10.5%
3 20949
 
9.5%
2 16494
 
7.5%
4 14286
 
6.5%
9 8982
 
4.1%
5 4610
 
2.1%
8 4440
 
2.0%
7 3912
 
1.8%

인허가일자
Real number (ℝ)

SKEWED 

Distinct5175
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20085020
Minimum9890425
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:47.064511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9890425
5-th percentile19850722
Q120020327
median20130766
Q320180312
95-th percentile20200609
Maximum20201231
Range10310806
Interquartile range (IQR)159985

Descriptive statistics

Standard deviation154473.19
Coefficient of variation (CV)0.007690965
Kurtosis1896.5169
Mean20085020
Median Absolute Deviation (MAD)59755.5
Skewness-29.250176
Sum2.008502 × 1011
Variance2.3861966 × 1010
MonotonicityNot monotonic
2024-04-17T04:35:47.198427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170630 12
 
0.1%
19951206 12
 
0.1%
20190503 11
 
0.1%
20200527 11
 
0.1%
20161026 11
 
0.1%
20140605 10
 
0.1%
20141222 10
 
0.1%
20200206 10
 
0.1%
20190611 10
 
0.1%
20170627 10
 
0.1%
Other values (5165) 9893
98.9%
ValueCountFrequency (%)
9890425 1
< 0.1%
19640327 1
< 0.1%
19651123 1
< 0.1%
19651125 1
< 0.1%
19660725 1
< 0.1%
19660827 1
< 0.1%
19660928 1
< 0.1%
19661116 1
< 0.1%
19661205 1
< 0.1%
19661223 1
< 0.1%
ValueCountFrequency (%)
20201231 2
 
< 0.1%
20201230 1
 
< 0.1%
20201229 2
 
< 0.1%
20201228 4
< 0.1%
20201224 5
0.1%
20201223 2
 
< 0.1%
20201222 4
< 0.1%
20201221 3
< 0.1%
20201218 2
 
< 0.1%
20201217 4
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
5575 
1
4425 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row1
4th row3
5th row1

Common Values

ValueCountFrequency (%)
3 5575
55.8%
1 4425
44.2%

Length

2024-04-17T04:35:47.337193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:47.420218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 5575
55.8%
1 4425
44.2%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
5575 
영업/정상
4425 

Length

Max length5
Median length2
Mean length3.3275
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 5575
55.8%
영업/정상 4425
44.2%

Length

2024-04-17T04:35:47.518967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:47.619376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5575
55.8%
영업/정상 4425
44.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
5575 
1
4425 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 5575
55.8%
1 4425
44.2%

Length

2024-04-17T04:35:47.707241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:47.792634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5575
55.8%
1 4425
44.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
5575 
영업
4425 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 5575
55.8%
영업 4425
44.2%

Length

2024-04-17T04:35:47.879435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:47.963195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5575
55.8%
영업 4425
44.2%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct3394
Distinct (%)60.9%
Missing4425
Missing (%)44.2%
Infinite0
Infinite (%)0.0%
Mean20094887
Minimum9900312
Maximum21200505
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:48.072699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9900312
5-th percentile19971120
Q120030526
median20120106
Q320170604
95-th percentile20200615
Maximum21200505
Range11300193
Interquartile range (IQR)140077.5

Descriptive statistics

Standard deviation247888.89
Coefficient of variation (CV)0.012335918
Kurtosis1504.5563
Mean20094887
Median Absolute Deviation (MAD)68885
Skewness-36.81902
Sum1.12029 × 1011
Variance6.1448901 × 1010
MonotonicityNot monotonic
2024-04-17T04:35:48.203800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110405 58
 
0.6%
20141229 38
 
0.4%
20190724 26
 
0.3%
19980619 23
 
0.2%
20130412 20
 
0.2%
20011008 19
 
0.2%
20080225 16
 
0.2%
20000120 13
 
0.1%
20060622 12
 
0.1%
20191025 10
 
0.1%
Other values (3384) 5340
53.4%
(Missing) 4425
44.2%
ValueCountFrequency (%)
9900312 1
< 0.1%
9970214 1
< 0.1%
10000101 1
< 0.1%
19900622 1
< 0.1%
19901124 1
< 0.1%
19901203 1
< 0.1%
19910716 1
< 0.1%
19910917 1
< 0.1%
19920622 1
< 0.1%
19921030 1
< 0.1%
ValueCountFrequency (%)
21200505 1
 
< 0.1%
20201231 5
0.1%
20201230 4
< 0.1%
20201229 2
 
< 0.1%
20201228 5
0.1%
20201224 7
0.1%
20201223 2
 
< 0.1%
20201222 2
 
< 0.1%
20201221 6
0.1%
20201218 3
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

소재지전화
Text

MISSING 

Distinct4316
Distinct (%)76.2%
Missing4339
Missing (%)43.4%
Memory size156.2 KiB
2024-04-17T04:35:48.532127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.624448
Min length1

Characters and Unicode

Total characters54484
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4212 ?
Unique (%)74.4%

Sample

1st row051
2nd row051
3rd row051 201 5051
4th row051 8976020
5th row051 7316523
ValueCountFrequency (%)
051 5115
42.9%
070 143
 
1.2%
02 73
 
0.6%
728 55
 
0.5%
727 55
 
0.5%
031 23
 
0.2%
363 22
 
0.2%
231 20
 
0.2%
745 20
 
0.2%
724 19
 
0.2%
Other values (4387) 6384
53.5%
2024-04-17T04:35:48.998894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9296
17.1%
5 8812
16.2%
1 8474
15.6%
6373
11.7%
2 3894
7.1%
7 3457
 
6.3%
3 3274
 
6.0%
6 2999
 
5.5%
8 2964
 
5.4%
4 2883
 
5.3%
Other values (2) 2058
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48108
88.3%
Space Separator 6373
 
11.7%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9296
19.3%
5 8812
18.3%
1 8474
17.6%
2 3894
8.1%
7 3457
 
7.2%
3 3274
 
6.8%
6 2999
 
6.2%
8 2964
 
6.2%
4 2883
 
6.0%
9 2055
 
4.3%
Space Separator
ValueCountFrequency (%)
6373
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54484
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9296
17.1%
5 8812
16.2%
1 8474
15.6%
6373
11.7%
2 3894
7.1%
7 3457
 
6.3%
3 3274
 
6.0%
6 2999
 
5.5%
8 2964
 
5.4%
4 2883
 
5.3%
Other values (2) 2058
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54484
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9296
17.1%
5 8812
16.2%
1 8474
15.6%
6373
11.7%
2 3894
7.1%
7 3457
 
6.3%
3 3274
 
6.0%
6 2999
 
5.5%
8 2964
 
5.4%
4 2883
 
5.3%
Other values (2) 2058
 
3.8%

소재지면적
Text

MISSING 

Distinct4848
Distinct (%)54.8%
Missing1158
Missing (%)11.6%
Memory size156.2 KiB
2024-04-17T04:35:49.352660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.925017
Min length3

Characters and Unicode

Total characters43547
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

Unique3450 ?
Unique (%)39.0%

Sample

1st row4.20
2nd row95.15
3rd row44.10
4th row42.64
5th row16.00
ValueCountFrequency (%)
00 290
 
3.3%
3.30 139
 
1.6%
6.60 104
 
1.2%
10.00 87
 
1.0%
33.00 53
 
0.6%
15.00 42
 
0.5%
13.20 37
 
0.4%
16.50 35
 
0.4%
9.90 34
 
0.4%
3.00 33
 
0.4%
Other values (4838) 7988
90.3%
2024-04-17T04:35:49.822738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8842
20.3%
0 7061
16.2%
1 4119
9.5%
2 3861
8.9%
3 3483
 
8.0%
4 3094
 
7.1%
6 3072
 
7.1%
5 2979
 
6.8%
8 2575
 
5.9%
7 2278
 
5.2%
Other values (2) 2183
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34703
79.7%
Other Punctuation 8844
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7061
20.3%
1 4119
11.9%
2 3861
11.1%
3 3483
10.0%
4 3094
8.9%
6 3072
8.9%
5 2979
8.6%
8 2575
 
7.4%
7 2278
 
6.6%
9 2181
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 8842
> 99.9%
, 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 43547
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 8842
20.3%
0 7061
16.2%
1 4119
9.5%
2 3861
8.9%
3 3483
 
8.0%
4 3094
 
7.1%
6 3072
 
7.1%
5 2979
 
6.8%
8 2575
 
5.9%
7 2278
 
5.2%
Other values (2) 2183
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43547
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 8842
20.3%
0 7061
16.2%
1 4119
9.5%
2 3861
8.9%
3 3483
 
8.0%
4 3094
 
7.1%
6 3072
 
7.1%
5 2979
 
6.8%
8 2575
 
5.9%
7 2278
 
5.2%
Other values (2) 2183
 
5.0%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct867
Distinct (%)8.8%
Missing202
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean611162.48
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:49.968361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile600814
Q1607825
median612767
Q3614849
95-th percentile618440
Maximum619953
Range19942
Interquartile range (IQR)7024

Descriptive statistics

Standard deviation5397.7251
Coefficient of variation (CV)0.0088318987
Kurtosis-0.69418031
Mean611162.48
Median Absolute Deviation (MAD)3962
Skewness-0.47755362
Sum5.98817 × 109
Variance29135436
MonotonicityNot monotonic
2024-04-17T04:35:50.118486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
612020 219
 
2.2%
614847 141
 
1.4%
614846 106
 
1.1%
614845 104
 
1.0%
612704 101
 
1.0%
618200 96
 
1.0%
609839 86
 
0.9%
616852 82
 
0.8%
600017 76
 
0.8%
608805 75
 
0.8%
Other values (857) 8712
87.1%
(Missing) 202
 
2.0%
ValueCountFrequency (%)
600011 12
 
0.1%
600012 9
 
0.1%
600013 2
 
< 0.1%
600014 1
 
< 0.1%
600015 4
 
< 0.1%
600016 6
 
0.1%
600017 76
0.8%
600021 8
 
0.1%
600022 4
 
< 0.1%
600023 5
 
0.1%
ValueCountFrequency (%)
619953 30
0.3%
619952 12
 
0.1%
619951 28
0.3%
619913 11
 
0.1%
619912 37
0.4%
619911 21
 
0.2%
619906 22
 
0.2%
619905 35
0.4%
619904 11
 
0.1%
619903 59
0.6%
Distinct8599
Distinct (%)86.2%
Missing20
Missing (%)0.2%
Memory size156.2 KiB
2024-04-17T04:35:50.436814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length55
Mean length24.828858
Min length12

Characters and Unicode

Total characters247792
Distinct characters559
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7938 ?
Unique (%)79.5%

Sample

1st row부산광역시 부산진구 범천동 839-49번지 ,69
2nd row부산광역시 부산진구 전포동 660-1번지
3rd row부산광역시 사하구 하단동 500-11번지
4th row부산광역시 부산진구 당감동 887-6번지
5th row부산광역시 수영구 광안동 144-5번지
ValueCountFrequency (%)
부산광역시 9980
 
21.3%
부산진구 1564
 
3.3%
해운대구 1207
 
2.6%
동래구 808
 
1.7%
금정구 744
 
1.6%
북구 646
 
1.4%
남구 642
 
1.4%
수영구 634
 
1.4%
부전동 603
 
1.3%
사상구 588
 
1.3%
Other values (9446) 29350
62.8%
2024-04-17T04:35:50.925435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36799
 
14.9%
13100
 
5.3%
12215
 
4.9%
1 11832
 
4.8%
11624
 
4.7%
10437
 
4.2%
10270
 
4.1%
10054
 
4.1%
9976
 
4.0%
9809
 
4.0%
Other values (549) 111676
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150616
60.8%
Decimal Number 49697
 
20.1%
Space Separator 36799
 
14.9%
Dash Punctuation 8637
 
3.5%
Open Punctuation 533
 
0.2%
Close Punctuation 531
 
0.2%
Other Punctuation 470
 
0.2%
Uppercase Letter 447
 
0.2%
Lowercase Letter 31
 
< 0.1%
Math Symbol 30
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13100
 
8.7%
12215
 
8.1%
11624
 
7.7%
10437
 
6.9%
10270
 
6.8%
10054
 
6.7%
9976
 
6.6%
9809
 
6.5%
8848
 
5.9%
2246
 
1.5%
Other values (494) 52037
34.5%
Uppercase Letter
ValueCountFrequency (%)
B 107
23.9%
A 62
13.9%
S 57
12.8%
K 42
 
9.4%
C 28
 
6.3%
G 21
 
4.7%
E 16
 
3.6%
L 15
 
3.4%
H 12
 
2.7%
Y 11
 
2.5%
Other values (13) 76
17.0%
Decimal Number
ValueCountFrequency (%)
1 11832
23.8%
2 6847
13.8%
3 5478
11.0%
4 4541
 
9.1%
5 4525
 
9.1%
0 4102
 
8.3%
6 3405
 
6.9%
7 3340
 
6.7%
8 2873
 
5.8%
9 2754
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
e 20
64.5%
c 4
 
12.9%
a 2
 
6.5%
z 1
 
3.2%
l 1
 
3.2%
b 1
 
3.2%
u 1
 
3.2%
p 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 429
91.3%
. 19
 
4.0%
@ 12
 
2.6%
/ 8
 
1.7%
& 1
 
0.2%
· 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 532
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 530
99.8%
] 1
 
0.2%
Space Separator
ValueCountFrequency (%)
36799
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8637
100.0%
Math Symbol
ValueCountFrequency (%)
~ 30
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150616
60.8%
Common 96697
39.0%
Latin 479
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13100
 
8.7%
12215
 
8.1%
11624
 
7.7%
10437
 
6.9%
10270
 
6.8%
10054
 
6.7%
9976
 
6.6%
9809
 
6.5%
8848
 
5.9%
2246
 
1.5%
Other values (494) 52037
34.5%
Latin
ValueCountFrequency (%)
B 107
22.3%
A 62
12.9%
S 57
11.9%
K 42
 
8.8%
C 28
 
5.8%
G 21
 
4.4%
e 20
 
4.2%
E 16
 
3.3%
L 15
 
3.1%
H 12
 
2.5%
Other values (22) 99
20.7%
Common
ValueCountFrequency (%)
36799
38.1%
1 11832
 
12.2%
- 8637
 
8.9%
2 6847
 
7.1%
3 5478
 
5.7%
4 4541
 
4.7%
5 4525
 
4.7%
0 4102
 
4.2%
6 3405
 
3.5%
7 3340
 
3.5%
Other values (13) 7191
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150616
60.8%
ASCII 97174
39.2%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36799
37.9%
1 11832
 
12.2%
- 8637
 
8.9%
2 6847
 
7.0%
3 5478
 
5.6%
4 4541
 
4.7%
5 4525
 
4.7%
0 4102
 
4.2%
6 3405
 
3.5%
7 3340
 
3.4%
Other values (43) 7668
 
7.9%
Hangul
ValueCountFrequency (%)
13100
 
8.7%
12215
 
8.1%
11624
 
7.7%
10437
 
6.9%
10270
 
6.8%
10054
 
6.7%
9976
 
6.6%
9809
 
6.5%
8848
 
5.9%
2246
 
1.5%
Other values (494) 52037
34.5%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

도로명전체주소
Text

MISSING 

Distinct6592
Distinct (%)93.6%
Missing2955
Missing (%)29.5%
Memory size156.2 KiB
2024-04-17T04:35:51.247688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length55
Mean length32.997445
Min length19

Characters and Unicode

Total characters232467
Distinct characters567
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6355 ?
Unique (%)90.2%

Sample

1st row부산광역시 사하구 낙동대로535번길 47, 1층 (하단동)
2nd row부산광역시 수영구 광안로 13-1, 1층 (광안동)
3rd row부산광역시 연제구 쌍미천로 58, 상가동 1층 101-B호 (연산동, 연산훼미리타운)
4th row부산광역시 수영구 황령대로489번길 27 (남천동)
5th row부산광역시 남구 문현금융로 40, 부산국제금융센터 A동 1층 120호 (문현동)
ValueCountFrequency (%)
부산광역시 7045
 
15.6%
1층 2380
 
5.3%
부산진구 1045
 
2.3%
해운대구 958
 
2.1%
금정구 505
 
1.1%
남구 488
 
1.1%
2층 480
 
1.1%
기장군 468
 
1.0%
우동 467
 
1.0%
동래구 463
 
1.0%
Other values (5942) 30973
68.4%
2024-04-17T04:35:51.716213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38245
 
16.5%
1 10793
 
4.6%
9677
 
4.2%
9025
 
3.9%
8820
 
3.8%
7733
 
3.3%
7629
 
3.3%
7114
 
3.1%
6993
 
3.0%
( 6958
 
3.0%
Other values (557) 119480
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135593
58.3%
Space Separator 38245
 
16.5%
Decimal Number 35435
 
15.2%
Open Punctuation 6960
 
3.0%
Close Punctuation 6958
 
3.0%
Other Punctuation 6944
 
3.0%
Uppercase Letter 1197
 
0.5%
Dash Punctuation 1013
 
0.4%
Math Symbol 89
 
< 0.1%
Lowercase Letter 32
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9677
 
7.1%
9025
 
6.7%
8820
 
6.5%
7733
 
5.7%
7629
 
5.6%
7114
 
5.2%
6993
 
5.2%
6945
 
5.1%
4376
 
3.2%
3852
 
2.8%
Other values (498) 63429
46.8%
Uppercase Letter
ValueCountFrequency (%)
A 254
21.2%
C 202
16.9%
E 171
14.3%
B 164
13.7%
P 151
12.6%
S 60
 
5.0%
K 39
 
3.3%
D 22
 
1.8%
G 22
 
1.8%
I 15
 
1.3%
Other values (14) 97
 
8.1%
Decimal Number
ValueCountFrequency (%)
1 10793
30.5%
2 5079
14.3%
3 3582
 
10.1%
0 3259
 
9.2%
5 2687
 
7.6%
4 2566
 
7.2%
6 2256
 
6.4%
7 2065
 
5.8%
9 1584
 
4.5%
8 1564
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 6909
99.5%
. 15
 
0.2%
@ 7
 
0.1%
/ 6
 
0.1%
& 2
 
< 0.1%
' 2
 
< 0.1%
· 2
 
< 0.1%
* 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 23
71.9%
b 2
 
6.2%
c 2
 
6.2%
m 1
 
3.1%
u 1
 
3.1%
s 1
 
3.1%
g 1
 
3.1%
p 1
 
3.1%
Open Punctuation
ValueCountFrequency (%)
( 6958
> 99.9%
[ 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 6956
> 99.9%
] 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 88
98.9%
× 1
 
1.1%
Space Separator
ValueCountFrequency (%)
38245
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1013
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135593
58.3%
Common 95644
41.1%
Latin 1230
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9677
 
7.1%
9025
 
6.7%
8820
 
6.5%
7733
 
5.7%
7629
 
5.6%
7114
 
5.2%
6993
 
5.2%
6945
 
5.1%
4376
 
3.2%
3852
 
2.8%
Other values (498) 63429
46.8%
Latin
ValueCountFrequency (%)
A 254
20.7%
C 202
16.4%
E 171
13.9%
B 164
13.3%
P 151
12.3%
S 60
 
4.9%
K 39
 
3.2%
e 23
 
1.9%
D 22
 
1.8%
G 22
 
1.8%
Other values (23) 122
9.9%
Common
ValueCountFrequency (%)
38245
40.0%
1 10793
 
11.3%
( 6958
 
7.3%
) 6956
 
7.3%
, 6909
 
7.2%
2 5079
 
5.3%
3 3582
 
3.7%
0 3259
 
3.4%
5 2687
 
2.8%
4 2566
 
2.7%
Other values (16) 8610
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135592
58.3%
ASCII 96870
41.7%
None 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38245
39.5%
1 10793
 
11.1%
( 6958
 
7.2%
) 6956
 
7.2%
, 6909
 
7.1%
2 5079
 
5.2%
3 3582
 
3.7%
0 3259
 
3.4%
5 2687
 
2.8%
4 2566
 
2.6%
Other values (46) 9836
 
10.2%
Hangul
ValueCountFrequency (%)
9677
 
7.1%
9025
 
6.7%
8820
 
6.5%
7733
 
5.7%
7629
 
5.6%
7114
 
5.2%
6993
 
5.2%
6945
 
5.1%
4376
 
3.2%
3852
 
2.8%
Other values (497) 63428
46.8%
None
ValueCountFrequency (%)
· 2
66.7%
× 1
33.3%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1537
Distinct (%)22.1%
Missing3031
Missing (%)30.3%
Infinite0
Infinite (%)0.0%
Mean47698.775
Minimum46003
Maximum49527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:51.857050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46003
5-th percentile46066
Q146957
median47787
Q348434
95-th percentile49304
Maximum49527
Range3524
Interquartile range (IQR)1477

Descriptive statistics

Standard deviation985.35603
Coefficient of variation (CV)0.02065789
Kurtosis-1.0301204
Mean47698.775
Median Absolute Deviation (MAD)728
Skewness-0.036119786
Sum3.3241276 × 108
Variance970926.5
MonotonicityNot monotonic
2024-04-17T04:35:51.978912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48060 163
 
1.6%
48058 146
 
1.5%
46726 99
 
1.0%
47285 74
 
0.7%
48944 69
 
0.7%
47296 49
 
0.5%
46015 49
 
0.5%
48095 49
 
0.5%
48953 46
 
0.5%
48735 43
 
0.4%
Other values (1527) 6182
61.8%
(Missing) 3031
30.3%
ValueCountFrequency (%)
46003 2
 
< 0.1%
46004 3
 
< 0.1%
46005 1
 
< 0.1%
46006 1
 
< 0.1%
46007 5
 
0.1%
46008 17
0.2%
46009 1
 
< 0.1%
46010 2
 
< 0.1%
46012 6
 
0.1%
46013 6
 
0.1%
ValueCountFrequency (%)
49527 1
 
< 0.1%
49525 1
 
< 0.1%
49524 5
0.1%
49523 1
 
< 0.1%
49522 2
 
< 0.1%
49521 9
0.1%
49520 2
 
< 0.1%
49519 2
 
< 0.1%
49518 4
< 0.1%
49515 2
 
< 0.1%
Distinct8967
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T04:35:52.303234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length6.9636
Min length1

Characters and Unicode

Total characters69636
Distinct characters1062
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8326 ?
Unique (%)83.3%

Sample

1st row미리내
2nd row커피리오21세기
3rd row하모니피자
4th row이색
5th row나디아컵케이크&커피
ValueCountFrequency (%)
씨유 98
 
0.8%
세븐일레븐 91
 
0.7%
카페 80
 
0.6%
gs25 77
 
0.6%
coffee 60
 
0.5%
커피 55
 
0.4%
미니스톱 48
 
0.4%
컴포즈커피 45
 
0.4%
이디야 36
 
0.3%
cafe 31
 
0.2%
Other values (9471) 12229
95.2%
2024-04-17T04:35:52.741008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2854
 
4.1%
2745
 
3.9%
2010
 
2.9%
1718
 
2.5%
1466
 
2.1%
1456
 
2.1%
) 1137
 
1.6%
( 1132
 
1.6%
1094
 
1.6%
888
 
1.3%
Other values (1052) 53136
76.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57465
82.5%
Uppercase Letter 2974
 
4.3%
Space Separator 2854
 
4.1%
Lowercase Letter 2447
 
3.5%
Decimal Number 1410
 
2.0%
Close Punctuation 1139
 
1.6%
Open Punctuation 1134
 
1.6%
Other Punctuation 176
 
0.3%
Dash Punctuation 28
 
< 0.1%
Modifier Symbol 6
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2745
 
4.8%
2010
 
3.5%
1718
 
3.0%
1466
 
2.6%
1456
 
2.5%
1094
 
1.9%
888
 
1.5%
866
 
1.5%
797
 
1.4%
766
 
1.3%
Other values (966) 43659
76.0%
Lowercase Letter
ValueCountFrequency (%)
e 426
17.4%
a 249
10.2%
o 247
10.1%
f 234
 
9.6%
c 180
 
7.4%
n 121
 
4.9%
r 102
 
4.2%
t 101
 
4.1%
l 101
 
4.1%
i 100
 
4.1%
Other values (16) 586
23.9%
Uppercase Letter
ValueCountFrequency (%)
C 421
14.2%
S 324
 
10.9%
G 277
 
9.3%
E 227
 
7.6%
P 207
 
7.0%
O 172
 
5.8%
F 152
 
5.1%
A 149
 
5.0%
T 117
 
3.9%
B 103
 
3.5%
Other values (16) 825
27.7%
Other Punctuation
ValueCountFrequency (%)
& 65
36.9%
. 48
27.3%
, 23
 
13.1%
' 16
 
9.1%
: 8
 
4.5%
/ 4
 
2.3%
! 3
 
1.7%
· 2
 
1.1%
" 2
 
1.1%
% 2
 
1.1%
Other values (3) 3
 
1.7%
Decimal Number
ValueCountFrequency (%)
2 417
29.6%
5 350
24.8%
1 195
13.8%
0 125
 
8.9%
3 89
 
6.3%
4 65
 
4.6%
9 57
 
4.0%
7 43
 
3.0%
8 40
 
2.8%
6 29
 
2.1%
Close Punctuation
ValueCountFrequency (%)
) 1137
99.8%
] 2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1132
99.8%
[ 2
 
0.2%
Modifier Symbol
ValueCountFrequency (%)
` 5
83.3%
˚ 1
 
16.7%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
2854
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57447
82.5%
Common 6750
 
9.7%
Latin 5421
 
7.8%
Han 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2745
 
4.8%
2010
 
3.5%
1718
 
3.0%
1466
 
2.6%
1456
 
2.5%
1094
 
1.9%
888
 
1.5%
866
 
1.5%
797
 
1.4%
766
 
1.3%
Other values (953) 43641
76.0%
Latin
ValueCountFrequency (%)
e 426
 
7.9%
C 421
 
7.8%
S 324
 
6.0%
G 277
 
5.1%
a 249
 
4.6%
o 247
 
4.6%
f 234
 
4.3%
E 227
 
4.2%
P 207
 
3.8%
c 180
 
3.3%
Other values (42) 2629
48.5%
Common
ValueCountFrequency (%)
2854
42.3%
) 1137
 
16.8%
( 1132
 
16.8%
2 417
 
6.2%
5 350
 
5.2%
1 195
 
2.9%
0 125
 
1.9%
3 89
 
1.3%
& 65
 
1.0%
4 65
 
1.0%
Other values (24) 321
 
4.8%
Han
ValueCountFrequency (%)
3
16.7%
3
16.7%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (3) 3
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57444
82.5%
ASCII 12167
 
17.5%
CJK 17
 
< 0.1%
None 3
 
< 0.1%
Compat Jamo 3
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2854
23.5%
) 1137
 
9.3%
( 1132
 
9.3%
e 426
 
3.5%
C 421
 
3.5%
2 417
 
3.4%
5 350
 
2.9%
S 324
 
2.7%
G 277
 
2.3%
a 249
 
2.0%
Other values (73) 4580
37.6%
Hangul
ValueCountFrequency (%)
2745
 
4.8%
2010
 
3.5%
1718
 
3.0%
1466
 
2.6%
1456
 
2.5%
1094
 
1.9%
888
 
1.5%
866
 
1.5%
797
 
1.4%
766
 
1.3%
Other values (950) 43638
76.0%
CJK
ValueCountFrequency (%)
3
17.6%
3
17.6%
2
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (2) 2
11.8%
None
ValueCountFrequency (%)
· 2
66.7%
° 1
33.3%
Compat Jamo
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Modifier Letters
ValueCountFrequency (%)
˚ 1
100.0%

최종수정시점
Real number (ℝ)

Distinct8493
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0134314 × 1013
Minimum1.9990225 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:53.188425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990225 × 1013
5-th percentile2.0010613 × 1013
Q12.0080225 × 1013
median2.0170417 × 1013
Q32.0190919 × 1013
95-th percentile2.0201021 × 1013
Maximum2.0201231 × 1013
Range2.1100618 × 1011
Interquartile range (IQR)1.1069402 × 1011

Descriptive statistics

Standard deviation7.0435621 × 1010
Coefficient of variation (CV)0.0034982875
Kurtosis-0.90062338
Mean2.0134314 × 1013
Median Absolute Deviation (MAD)3.0287472 × 1010
Skewness-0.79341054
Sum2.0134314 × 1017
Variance4.9611766 × 1021
MonotonicityNot monotonic
2024-04-17T04:35:53.317572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020228000000 108
 
1.1%
20010803000000 65
 
0.7%
19990318000000 56
 
0.6%
20010823000000 56
 
0.6%
20020110000000 52
 
0.5%
20020827000000 47
 
0.5%
19990317000000 37
 
0.4%
20020225000000 35
 
0.4%
20011221000000 35
 
0.4%
20011220000000 33
 
0.3%
Other values (8483) 9476
94.8%
ValueCountFrequency (%)
19990225000000 1
 
< 0.1%
19990303000000 7
 
0.1%
19990304000000 1
 
< 0.1%
19990305000000 16
 
0.2%
19990308000000 2
 
< 0.1%
19990311000000 1
 
< 0.1%
19990316000000 6
 
0.1%
19990317000000 37
0.4%
19990318000000 56
0.6%
19990319000000 26
0.3%
ValueCountFrequency (%)
20201231175023 1
< 0.1%
20201231174056 1
< 0.1%
20201231165658 1
< 0.1%
20201231152224 1
< 0.1%
20201231134809 1
< 0.1%
20201231133216 1
< 0.1%
20201231133130 1
< 0.1%
20201231132042 1
< 0.1%
20201231125817 1
< 0.1%
20201231121238 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6655 
U
3345 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6655
66.5%
U 3345
33.5%

Length

2024-04-17T04:35:53.432786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:53.526478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6655
66.5%
u 3345
33.5%
Distinct916
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-02 02:40:00
2024-04-17T04:35:53.622994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T04:35:53.759305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
커피숍
2889 
일반조리판매
1874 
다방
1416 
기타 휴게음식점
1401 
과자점
930 
Other values (16)
1490 

Length

Max length8
Median length6
Mean length4.2789
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row일반조리판매
2nd row다방
3rd row패스트푸드
4th row다방
5th row커피숍

Common Values

ValueCountFrequency (%)
커피숍 2889
28.9%
일반조리판매 1874
18.7%
다방 1416
14.2%
기타 휴게음식점 1401
14.0%
과자점 930
 
9.3%
패스트푸드 639
 
6.4%
편의점 483
 
4.8%
푸드트럭 98
 
1.0%
백화점 75
 
0.8%
전통찻집 64
 
0.6%
Other values (11) 131
 
1.3%

Length

2024-04-17T04:35:53.891316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 2889
25.3%
일반조리판매 1874
16.4%
다방 1416
12.4%
기타 1401
12.3%
휴게음식점 1401
12.3%
과자점 930
 
8.2%
패스트푸드 639
 
5.6%
편의점 483
 
4.2%
푸드트럭 98
 
0.9%
백화점 75
 
0.7%
Other values (12) 195
 
1.7%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct6758
Distinct (%)70.2%
Missing378
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean388439.04
Minimum364927.7
Maximum407878.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:54.009744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum364927.7
5-th percentile379544.65
Q1384937.99
median388164.77
Q3392016.79
95-th percentile398337.45
Maximum407878.31
Range42950.616
Interquartile range (IQR)7078.7967

Descriptive statistics

Standard deviation5913.7295
Coefficient of variation (CV)0.015224344
Kurtosis0.78128355
Mean388439.04
Median Absolute Deviation (MAD)3504.6371
Skewness0.0026464819
Sum3.7375604 × 109
Variance34972197
MonotonicityNot monotonic
2024-04-17T04:35:54.142330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
394482.139208377 113
 
1.1%
393952.264486105 99
 
1.0%
387271.299492377 93
 
0.9%
385590.814676765 71
 
0.7%
387539.767677801 65
 
0.7%
389097.800933845 60
 
0.6%
389314.662085919 31
 
0.3%
389816.233000769 30
 
0.3%
382983.91775577 25
 
0.2%
394457.407487917 23
 
0.2%
Other values (6748) 9012
90.1%
(Missing) 378
 
3.8%
ValueCountFrequency (%)
364927.696730227 1
< 0.1%
365045.343077193 1
< 0.1%
365131.369476857 1
< 0.1%
365181.573312611 1
< 0.1%
366168.207165745 1
< 0.1%
366543.906759876 2
< 0.1%
366799.216536177 2
< 0.1%
366854.076165373 1
< 0.1%
366932.944608323 1
< 0.1%
366972.949891217 1
< 0.1%
ValueCountFrequency (%)
407878.31227469 1
< 0.1%
407765.887806571 1
< 0.1%
407756.907308392 1
< 0.1%
407593.3507086 1
< 0.1%
407465.821054169 1
< 0.1%
407446.416940698 1
< 0.1%
407432.77113005 1
< 0.1%
407420.202291118 2
< 0.1%
407157.520969703 1
< 0.1%
407102.268015548 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct6759
Distinct (%)70.2%
Missing378
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean187371.47
Minimum169966.61
Maximum210945.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:54.266935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169966.61
5-th percentile178849.07
Q1183932.64
median186836.3
Q3191010.93
95-th percentile197081.35
Maximum210945.1
Range40978.495
Interquartile range (IQR)7078.2869

Descriptive statistics

Standard deviation5880.3114
Coefficient of variation (CV)0.031383174
Kurtosis0.85421612
Mean187371.47
Median Absolute Deviation (MAD)3642.8721
Skewness0.62455768
Sum1.8028883 × 109
Variance34578062
MonotonicityNot monotonic
2024-04-17T04:35:54.396349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187606.035424193 113
 
1.1%
187602.933160728 99
 
1.0%
186099.137533193 93
 
0.9%
179553.867031936 71
 
0.7%
184402.96650913 65
 
0.7%
192260.811648263 60
 
0.6%
194669.898821687 31
 
0.3%
193329.605871168 30
 
0.3%
196375.470354374 25
 
0.2%
187231.530457387 23
 
0.2%
Other values (6749) 9012
90.1%
(Missing) 378
 
3.8%
ValueCountFrequency (%)
169966.609440153 1
< 0.1%
170114.596522953 1
< 0.1%
170813.584718477 1
< 0.1%
171536.903133138 1
< 0.1%
172924.332699075 1
< 0.1%
173029.051447573 1
< 0.1%
173080.332146413 1
< 0.1%
173725.8041865 1
< 0.1%
173765.464798248 1
< 0.1%
173880.935177659 1
< 0.1%
ValueCountFrequency (%)
210945.104382171 1
< 0.1%
210284.515757078 1
< 0.1%
210196.721153795 1
< 0.1%
210147.321236588 1
< 0.1%
210111.800324086 1
< 0.1%
210105.311815156 1
< 0.1%
209997.104379978 1
< 0.1%
209835.840601069 1
< 0.1%
209640.461628918 1
< 0.1%
209469.032000262 1
< 0.1%

위생업태명
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
커피숍
2889 
일반조리판매
1888 
다방
1417 
기타 휴게음식점
1412 
과자점
931 
Other values (16)
1463 

Length

Max length8
Median length6
Mean length4.2885
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row일반조리판매
2nd row다방
3rd row패스트푸드
4th row다방
5th row커피숍

Common Values

ValueCountFrequency (%)
커피숍 2889
28.9%
일반조리판매 1888
18.9%
다방 1417
14.2%
기타 휴게음식점 1412
14.1%
과자점 931
 
9.3%
패스트푸드 640
 
6.4%
편의점 456
 
4.6%
푸드트럭 98
 
1.0%
백화점 75
 
0.8%
전통찻집 64
 
0.6%
Other values (11) 130
 
1.3%

Length

2024-04-17T04:35:54.528674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 2889
25.3%
일반조리판매 1888
16.5%
다방 1417
12.4%
기타 1412
12.4%
휴게음식점 1412
12.4%
과자점 931
 
8.2%
패스트푸드 640
 
5.6%
편의점 456
 
4.0%
푸드트럭 98
 
0.9%
백화점 75
 
0.7%
Other values (12) 194
 
1.7%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct6
Distinct (%)0.2%
Missing7592
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean0.059385382
Minimum0
Maximum15
Zeros2301
Zeros (%)23.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:54.621686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.41995701
Coefficient of variation (CV)7.0717237
Kurtosis701.14407
Mean0.059385382
Median Absolute Deviation (MAD)0
Skewness21.865675
Sum143
Variance0.17636389
MonotonicityNot monotonic
2024-04-17T04:35:54.730754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 2301
 
23.0%
1 92
 
0.9%
2 10
 
0.1%
3 3
 
< 0.1%
7 1
 
< 0.1%
15 1
 
< 0.1%
(Missing) 7592
75.9%
ValueCountFrequency (%)
0 2301
23.0%
1 92
 
0.9%
2 10
 
0.1%
3 3
 
< 0.1%
7 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
7 1
 
< 0.1%
3 3
 
< 0.1%
2 10
 
0.1%
1 92
 
0.9%
0 2301
23.0%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.3%
Missing7556
Missing (%)75.6%
Infinite0
Infinite (%)0.0%
Mean0.13420622
Minimum0
Maximum29
Zeros2221
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:54.830958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum29
Range29
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.80470891
Coefficient of variation (CV)5.9960627
Kurtosis766.09059
Mean0.13420622
Median Absolute Deviation (MAD)0
Skewness23.879992
Sum328
Variance0.64755643
MonotonicityNot monotonic
2024-04-17T04:35:54.933810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 2221
 
22.2%
1 176
 
1.8%
2 38
 
0.4%
3 4
 
< 0.1%
4 2
 
< 0.1%
10 1
 
< 0.1%
29 1
 
< 0.1%
17 1
 
< 0.1%
(Missing) 7556
75.6%
ValueCountFrequency (%)
0 2221
22.2%
1 176
 
1.8%
2 38
 
0.4%
3 4
 
< 0.1%
4 2
 
< 0.1%
10 1
 
< 0.1%
17 1
 
< 0.1%
29 1
 
< 0.1%
ValueCountFrequency (%)
29 1
 
< 0.1%
17 1
 
< 0.1%
10 1
 
< 0.1%
4 2
 
< 0.1%
3 4
 
< 0.1%
2 38
 
0.4%
1 176
 
1.8%
0 2221
22.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6943 
기타
2430 
주택가주변
 
315
아파트지역
 
137
유흥업소밀집지역
 
122
Other values (3)
 
53

Length

Max length8
Median length4
Mean length3.6287
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6943
69.4%
기타 2430
 
24.3%
주택가주변 315
 
3.1%
아파트지역 137
 
1.4%
유흥업소밀집지역 122
 
1.2%
학교정화(상대) 35
 
0.4%
학교정화(절대) 13
 
0.1%
결혼예식장주변 5
 
0.1%

Length

2024-04-17T04:35:55.052130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:55.189995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6943
69.4%
기타 2430
 
24.3%
주택가주변 315
 
3.1%
아파트지역 137
 
1.4%
유흥업소밀집지역 122
 
1.2%
학교정화(상대 35
 
0.4%
학교정화(절대 13
 
0.1%
결혼예식장주변 5
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7248 
기타
2103 
자율
 
631
우수
 
9
지도
 
8

Length

Max length4
Median length4
Mean length3.4495
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7248
72.5%
기타 2103
 
21.0%
자율 631
 
6.3%
우수 9
 
0.1%
지도 8
 
0.1%
1
 
< 0.1%

Length

2024-04-17T04:35:55.310792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:55.442159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7248
72.5%
기타 2103
 
21.0%
자율 631
 
6.3%
우수 9
 
0.1%
지도 8
 
0.1%
1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5143 
상수도전용
4820 
지하수전용
 
19
상수도(음용)지하수(주방용)겸용
 
10
간이상수도
 
6

Length

Max length19
Median length4
Mean length4.5005
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5143
51.4%
상수도전용 4820
48.2%
지하수전용 19
 
0.2%
상수도(음용)지하수(주방용)겸용 10
 
0.1%
간이상수도 6
 
0.1%
전용상수도(특정시설의 자가용 수도) 2
 
< 0.1%

Length

2024-04-17T04:35:55.559671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:55.664018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5143
51.4%
상수도전용 4820
48.2%
지하수전용 19
 
0.2%
상수도(음용)지하수(주방용)겸용 10
 
0.1%
간이상수도 6
 
0.1%
전용상수도(특정시설의 2
 
< 0.1%
자가용 2
 
< 0.1%
수도 2
 
< 0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
0
 
3

Length

Max length4
Median length4
Mean length3.9991
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> 9997
> 99.9%
0 3
 
< 0.1%

Length

2024-04-17T04:35:55.775162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:55.867751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
0 3
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
0
 
3

Length

Max length4
Median length4
Mean length3.9991
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> 9997
> 99.9%
0 3
 
< 0.1%

Length

2024-04-17T04:35:55.964657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:56.051206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
0 3
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
0
 
3

Length

Max length4
Median length4
Mean length3.9991
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> 9997
> 99.9%
0 3
 
< 0.1%

Length

2024-04-17T04:35:56.146893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:56.236787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
0 3
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
0
 
3

Length

Max length4
Median length4
Mean length3.9991
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> 9997
> 99.9%
0 3
 
< 0.1%

Length

2024-04-17T04:35:56.331278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:56.422028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
0 3
 
< 0.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
0
 
3

Length

Max length4
Median length4
Mean length3.9991
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> 9997
> 99.9%
0 3
 
< 0.1%

Length

2024-04-17T04:35:56.516750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:56.602652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
0 3
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
0
 
3

Length

Max length4
Median length4
Mean length3.9991
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> 9997
> 99.9%
0 3
 
< 0.1%

Length

2024-04-17T04:35:56.700637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:56.799537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
0 3
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9624 
True
 
376
ValueCountFrequency (%)
False 9624
96.2%
True 376
 
3.8%
2024-04-17T04:35:56.870417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct4830
Distinct (%)48.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.035718
Minimum0
Maximum1067.14
Zeros1499
Zeros (%)15.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:56.970105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18.1
median27.995
Q361.1925
95-th percentile174.603
Maximum1067.14
Range1067.14
Interquartile range (IQR)53.0925

Descriptive statistics

Standard deviation71.681454
Coefficient of variation (CV)1.4618212
Kurtosis26.091462
Mean49.035718
Median Absolute Deviation (MAD)23.695
Skewness4.009442
Sum490357.18
Variance5138.2309
MonotonicityNot monotonic
2024-04-17T04:35:57.109708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1499
 
15.0%
3.3 137
 
1.4%
6.6 102
 
1.0%
10.0 88
 
0.9%
33.0 53
 
0.5%
15.0 41
 
0.4%
13.2 37
 
0.4%
16.5 35
 
0.4%
9.9 34
 
0.3%
30.0 32
 
0.3%
Other values (4820) 7942
79.4%
ValueCountFrequency (%)
0.0 1499
15.0%
0.01 1
 
< 0.1%
0.5 1
 
< 0.1%
0.64 1
 
< 0.1%
0.7 1
 
< 0.1%
0.77 1
 
< 0.1%
0.8 1
 
< 0.1%
0.82 1
 
< 0.1%
0.92 1
 
< 0.1%
0.96 1
 
< 0.1%
ValueCountFrequency (%)
1067.14 1
< 0.1%
1022.0 1
< 0.1%
919.37 1
< 0.1%
865.88 1
< 0.1%
787.5 1
< 0.1%
773.72 1
< 0.1%
701.39 1
< 0.1%
669.39 1
< 0.1%
668.84 1
< 0.1%
637.46 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전통업소주된음식
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T04:35:57.216952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row전통차
ValueCountFrequency (%)
전통차 1
100.0%
2024-04-17T04:35:57.418074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
2052020521휴게음식점07_24_05_P32900003290000-104-1998-0648119981229<NA>3폐업2폐업20030121<NA><NA><NA>0514.20614020부산광역시 부산진구 범천동 839-49번지 ,69<NA><NA>미리내20020621000000I2018-08-31 23:59:59.0일반조리판매<NA><NA>일반조리판매<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N4.2<NA><NA><NA><NA>
2082020821휴게음식점07_24_05_P32900003290000-104-1993-0659019930324<NA>3폐업2폐업19990721<NA><NA><NA>05195.15614865부산광역시 부산진구 전포동 660-1번지<NA><NA>커피리오21세기20020618000000I2018-08-31 23:59:59.0다방387869.134318186381.281847다방<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N95.15<NA><NA><NA><NA>
1000610007휴게음식점07_24_05_P33400003340000-104-2016-0007720161116<NA>1영업/정상1영업<NA><NA><NA><NA>051 201 505144.10604851부산광역시 사하구 하단동 500-11번지부산광역시 사하구 낙동대로535번길 47, 1층 (하단동)49307하모니피자20161214165108I2018-08-31 23:59:59.0패스트푸드378795.877879180878.627696패스트푸드<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N44.1<NA><NA><NA><NA>
2043520436휴게음식점07_24_05_P32900003290000-104-1998-0615319980228<NA>3폐업2폐업19991203<NA><NA><NA>051 897602042.64614817부산광역시 부산진구 당감동 887-6번지<NA><NA>이색19990706000000I2018-08-31 23:59:59.0다방<NA><NA>다방<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N42.64<NA><NA><NA><NA>
859860휴게음식점07_24_05_P33800003380000-104-2010-0000720100423<NA>1영업/정상1영업<NA><NA><NA><NA>051 731652316.00613804부산광역시 수영구 광안동 144-5번지부산광역시 수영구 광안로 13-1, 1층 (광안동)48297나디아컵케이크&커피20180601151959I2018-08-31 23:59:59.0커피숍392587.985551186247.494481커피숍<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N16.0<NA><NA><NA><NA>
1833118332휴게음식점07_24_05_P33600003360000-104-2017-0002720170414<NA>3폐업2폐업20170423<NA><NA><NA><NA><NA>618803부산광역시 강서구 대저1동 2314-11번지 대저생태공원(유채꽃축제행사장)<NA><NA>코브라독스20170424190347I2018-08-31 23:59:59.0푸드트럭<NA><NA>푸드트럭<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1563815639휴게음식점07_24_05_P33500003350000-104-1999-0390119990804<NA>3폐업2폐업20020805<NA><NA><NA>051 5184117<NA>609852부산광역시 금정구 부곡동 244-7번지 대우APT29-109<NA><NA>신라명과부곡점20020806000000I2018-08-31 23:59:59.0과자점390226.191824194536.608163과자점00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
76017602휴게음식점07_24_05_P33700003370000-104-2020-0008120200903<NA>1영업/정상1영업<NA><NA><NA><NA>051 868 032536.48611836부산광역시 연제구 연산동 1777-11 연산훼미리타운부산광역시 연제구 쌍미천로 58, 상가동 1층 101-B호 (연산동, 연산훼미리타운)47589몬요거트20200929175844U2020-10-01 02:40:00.0일반조리판매390279.461515188544.073982일반조리판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N36.48<NA><NA><NA><NA>
1654416545휴게음식점07_24_05_P32500003250000-104-2011-0002520110614<NA>3폐업2폐업20111014<NA><NA><NA>051 678 25004.00600017부산광역시 중구 중앙동7가 20-1번지 롯데백화점 지하1층<NA><NA>황제그린푸드20110629110959I2018-08-31 23:59:59.0일반조리판매385590.814677179553.867032일반조리판매<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N4.0<NA><NA><NA><NA>
973974휴게음식점07_24_05_P33800003380000-104-2016-0006420161010<NA>1영업/정상1영업<NA><NA><NA><NA>051 612 559636.36613816부산광역시 수영구 남천동 247-1번지부산광역시 수영구 황령대로489번길 27 (남천동)48311컴포즈커피 남천해변시장점20190103170710U2019-01-05 02:40:00.0커피숍392089.195831184287.436527커피숍<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N36.36<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
68486849휴게음식점07_24_05_P33800003380000-104-2020-0009720200828<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30613809부산광역시 수영구 광안동 570-12부산광역시 수영구 장대골로39번길 42-1, 1층 (광안동)48256이마트24 광안에일린점20200828172858I2020-08-30 00:23:13.0편의점392044.737042186311.917093편의점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N3.3<NA><NA><NA><NA>
1621816219휴게음식점07_24_05_P33500003350000-104-1991-0040919910810<NA>3폐업2폐업19990812<NA><NA><NA>051<NA>609848부산광역시 금정구 서동 165-7번지<NA><NA>천지20010803000000I2018-08-31 23:59:59.0다방391265.399818192931.992187다방<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
840841휴게음식점07_24_05_P33100003310000-104-2016-0006520160829<NA>1영업/정상1영업<NA><NA><NA><NA><NA>57.06608823부산광역시 남구 문현동 262-7번지부산광역시 남구 수영로69번길 59 (문현동)48455바라기20160829115804I2018-08-31 23:59:59.0커피숍389250.064396183898.629351커피숍<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N57.06<NA><NA><NA><NA>
2234322344휴게음식점07_24_05_P32900003290000-104-2006-0004920061228<NA>3폐업2폐업20090519<NA><NA><NA>051 891552545.08614811부산광역시 부산진구 개금동 482-20번지 외2필지<NA><NA>정다원전통찻집20070103000000I2018-08-31 23:59:59.0전통찻집383722.698037185680.052102전통찻집00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N45.08<NA><NA><NA><NA>
61026103휴게음식점07_24_05_P32900003290000-104-2017-0007520170510<NA>1영업/정상1영업<NA><NA><NA><NA><NA>262.15614865부산광역시 부산진구 전포동 663-10번지부산광역시 부산진구 서전로37번길 18, 지상1층 (전포동)47247플라스틱(Plastic)20180627094132I2018-08-31 23:59:59.0커피숍388014.499241186326.165744커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N262.15<NA><NA><NA><NA>
1093510936휴게음식점07_24_05_P33000003300000-104-2007-0002920070423<NA>3폐업2폐업20080709<NA><NA><NA>0510506973136.40607815부산광역시 동래구 사직동 26-6번지<NA><NA>후르츠젤라떼리아20070423000000I2018-08-31 23:59:59.0기타 휴게음식점387513.434672190791.002764기타 휴게음식점00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N36.4<NA><NA><NA><NA>
1585715858휴게음식점07_24_05_P33500003350000-104-2001-0480720010829<NA>3폐업2폐업20141229<NA><NA><NA>051 5089174<NA>609814부산광역시 금정구 남산동 68-1번지부산광역시 금정구 중앙대로 1989 (남산동)46227코펜하겐(남산점)20011031000000I2018-08-31 23:59:59.0과자점390241.469793197865.684207과자점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
39193920휴게음식점07_24_05_P32700003270000-104-2012-0002420120719<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.25601838부산광역시 동구 초량동 1197-2번지부산광역시 동구 중앙대로226번길 3-8 (초량동)48733GS25 초량스타점20181212093242U2018-12-14 02:40:00.0편의점386076.992729181737.931195과자점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N8.25<NA><NA><NA><NA>
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48884889휴게음식점07_24_05_P32700003270000-104-1989-0026619890703<NA>1영업/정상1영업<NA><NA><NA><NA>051 6325005136.87601807부산광역시 동구 범일동 830-61부산광역시 동구 조방로 21 (범일동)48744석화20201228174712U2020-12-30 02:40:00.0기타 휴게음식점387849.727171184129.233339기타 휴게음식점00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y136.87<NA><NA><NA><NA>