Overview

Dataset statistics

Number of variables48
Number of observations10000
Missing cells122027
Missing cells (%)25.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 MiB
Average record size in memory421.0 B

Variable types

Numeric12
Categorical19
Text7
Unsupported8
DateTime1
Boolean1

Dataset

Description2021-03-01
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 (99.5%)Imbalance
공장사무직종업원수 is highly imbalanced (99.5%)Imbalance
공장판매직종업원수 is highly imbalanced (99.5%)Imbalance
공장생산직종업원수 is highly imbalanced (99.5%)Imbalance
보증액 is highly imbalanced (99.5%)Imbalance
월세액 is highly imbalanced (99.5%)Imbalance
다중이용업소여부 is highly imbalanced (77.7%)Imbalance
전통업소지정번호 is highly imbalanced (99.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 4442 (44.4%) 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 4331 (43.3%) missing valuesMissing
소재지면적 has 1150 (11.5%) missing valuesMissing
소재지우편번호 has 179 (1.8%) missing valuesMissing
도로명전체주소 has 2946 (29.5%) missing valuesMissing
도로명우편번호 has 3011 (30.1%) missing valuesMissing
좌표정보(x) has 411 (4.1%) missing valuesMissing
좌표정보(y) has 411 (4.1%) missing valuesMissing
남성종사자수 has 7587 (75.9%) missing valuesMissing
여성종사자수 has 7551 (75.5%) missing valuesMissing
총종업원수 has 10000 (100.0%) missing valuesMissing
건물소유구분명 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 = -28.42287122)Skewed
폐업일자 is highly skewed (γ1 = -36.82657335)Skewed
남성종사자수 is highly skewed (γ1 = 22.71923499)Skewed
여성종사자수 is highly skewed (γ1 = 22.15372718)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
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 2318 (23.2%) zerosZeros
여성종사자수 has 2247 (22.5%) zerosZeros
시설총규모 has 1526 (15.3%) zerosZeros

Reproduction

Analysis started2024-04-16 19:35:21.072252
Analysis finished2024-04-16 19:35:23.699307
Duration2.63 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%
Mean11734.242
Minimum1
Maximum23413
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:23.766806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1162.95
Q15937.75
median11801.5
Q317558.25
95-th percentile22234.05
Maximum23413
Range23412
Interquartile range (IQR)11620.5

Descriptive statistics

Standard deviation6737.5541
Coefficient of variation (CV)0.5741789
Kurtosis-1.1927615
Mean11734.242
Median Absolute Deviation (MAD)5811.5
Skewness-0.010226005
Sum1.1734242 × 108
Variance45394635
MonotonicityNot monotonic
2024-04-17T04:35:23.887359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14377 1
 
< 0.1%
21665 1
 
< 0.1%
5523 1
 
< 0.1%
9978 1
 
< 0.1%
3455 1
 
< 0.1%
15384 1
 
< 0.1%
16448 1
 
< 0.1%
22403 1
 
< 0.1%
12146 1
 
< 0.1%
2991 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
13 1
< 0.1%
ValueCountFrequency (%)
23413 1
< 0.1%
23412 1
< 0.1%
23410 1
< 0.1%
23409 1
< 0.1%
23408 1
< 0.1%
23406 1
< 0.1%
23405 1
< 0.1%
23399 1
< 0.1%
23398 1
< 0.1%
23396 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

2024-04-17T04:35:24.006773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:24.088805image/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

2024-04-17T04:35:24.179722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:24.265950image/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%
Mean3323037
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:24.351974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3320000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation42422.242
Coefficient of variation (CV)0.012766106
Kurtosis-0.93125909
Mean3323037
Median Absolute Deviation (MAD)30000
Skewness0.17846654
Sum3.323037 × 1010
Variance1.7996466 × 109
MonotonicityNot monotonic
2024-04-17T04:35:24.464731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 1522
15.2%
3330000 1167
11.7%
3300000 782
 
7.8%
3350000 774
 
7.7%
3310000 686
 
6.9%
3380000 647
 
6.5%
3320000 644
 
6.4%
3390000 612
 
6.1%
3250000 554
 
5.5%
3400000 499
 
5.0%
Other values (6) 2113
21.1%
ValueCountFrequency (%)
3250000 554
 
5.5%
3260000 342
 
3.4%
3270000 461
 
4.6%
3280000 292
 
2.9%
3290000 1522
15.2%
3300000 782
7.8%
3310000 686
6.9%
3320000 644
6.4%
3330000 1167
11.7%
3340000 372
 
3.7%
ValueCountFrequency (%)
3400000 499
5.0%
3390000 612
6.1%
3380000 647
6.5%
3370000 281
 
2.8%
3360000 365
 
3.6%
3350000 774
7.7%
3340000 372
 
3.7%
3330000 1167
11.7%
3320000 644
6.4%
3310000 686
6.9%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T04:35:24.668292image/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 row3310000-104-1996-01999
2nd row3280000-104-1995-00076
3rd row3350000-104-2018-00105
4th row3340000-104-2001-00429
5th row3270000-104-1990-00309
ValueCountFrequency (%)
3310000-104-1996-01999 1
 
< 0.1%
3290000-104-2010-00010 1
 
< 0.1%
3350000-104-2020-00019 1
 
< 0.1%
3290000-104-2015-00103 1
 
< 0.1%
3350000-104-2020-00025 1
 
< 0.1%
3350000-104-2018-00111 1
 
< 0.1%
3390000-104-2019-00066 1
 
< 0.1%
3350000-104-1992-00433 1
 
< 0.1%
3330000-104-2019-00095 1
 
< 0.1%
3330000-104-2006-00049 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T04:35:24.979365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89513
40.7%
- 30000
 
13.6%
1 22980
 
10.4%
3 20901
 
9.5%
2 16400
 
7.5%
4 14351
 
6.5%
9 9041
 
4.1%
5 4594
 
2.1%
8 4529
 
2.1%
7 3865
 
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 89513
47.1%
1 22980
 
12.1%
3 20901
 
11.0%
2 16400
 
8.6%
4 14351
 
7.6%
9 9041
 
4.8%
5 4594
 
2.4%
8 4529
 
2.4%
7 3865
 
2.0%
6 3826
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89513
40.7%
- 30000
 
13.6%
1 22980
 
10.4%
3 20901
 
9.5%
2 16400
 
7.5%
4 14351
 
6.5%
9 9041
 
4.1%
5 4594
 
2.1%
8 4529
 
2.1%
7 3865
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89513
40.7%
- 30000
 
13.6%
1 22980
 
10.4%
3 20901
 
9.5%
2 16400
 
7.5%
4 14351
 
6.5%
9 9041
 
4.1%
5 4594
 
2.1%
8 4529
 
2.1%
7 3865
 
1.8%

인허가일자
Real number (ℝ)

SKEWED 

Distinct5217
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20084230
Minimum9890425
Maximum20210129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:25.123763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9890425
5-th percentile19850406
Q120011114
median20130816
Q320180425
95-th percentile20200701
Maximum20210129
Range10319704
Interquartile range (IQR)169310.75

Descriptive statistics

Standard deviation156003.93
Coefficient of variation (CV)0.0077674841
Kurtosis1822.5973
Mean20084230
Median Absolute Deviation (MAD)59802.5
Skewness-28.422871
Sum2.008423 × 1011
Variance2.4337228 × 1010
MonotonicityNot monotonic
2024-04-17T04:35:25.255787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091215 16
 
0.2%
20200527 12
 
0.1%
20090217 12
 
0.1%
20140825 11
 
0.1%
20141222 11
 
0.1%
20200211 10
 
0.1%
20170626 10
 
0.1%
20190523 10
 
0.1%
20200504 10
 
0.1%
20170203 10
 
0.1%
Other values (5207) 9888
98.9%
ValueCountFrequency (%)
9890425 1
 
< 0.1%
19630105 1
 
< 0.1%
19640219 1
 
< 0.1%
19640226 1
 
< 0.1%
19640929 1
 
< 0.1%
19650424 1
 
< 0.1%
19650728 1
 
< 0.1%
19651010 1
 
< 0.1%
19651103 3
< 0.1%
19651123 1
 
< 0.1%
ValueCountFrequency (%)
20210129 4
< 0.1%
20210128 3
< 0.1%
20210127 2
 
< 0.1%
20210126 5
0.1%
20210125 6
0.1%
20210122 3
< 0.1%
20210121 2
 
< 0.1%
20210120 4
< 0.1%
20210119 3
< 0.1%
20210118 6
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
5558 
1
4442 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 5558
55.6%
1 4442
44.4%

Length

2024-04-17T04:35:25.373427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:25.457662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 5558
55.6%
1 4442
44.4%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
5558 
영업/정상
4442 

Length

Max length5
Median length2
Mean length3.3326
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 5558
55.6%
영업/정상 4442
44.4%

Length

2024-04-17T04:35:25.554319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:25.642459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5558
55.6%
영업/정상 4442
44.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
5558 
1
4442 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 5558
55.6%
1 4442
44.4%

Length

2024-04-17T04:35:25.735727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:25.823286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5558
55.6%
1 4442
44.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
5558 
영업
4442 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 5558
55.6%
영업 4442
44.4%

Length

2024-04-17T04:35:25.923851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:26.006227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5558
55.6%
영업 4442
44.4%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct3401
Distinct (%)61.2%
Missing4442
Missing (%)44.4%
Infinite0
Infinite (%)0.0%
Mean20094191
Minimum9970214
Maximum20500228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:26.116600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9970214
5-th percentile19971009
Q120030416
median20111229
Q320170622
95-th percentile20200629
Maximum20500228
Range10530014
Interquartile range (IQR)140205.25

Descriptive statistics

Standard deviation247322.05
Coefficient of variation (CV)0.012308137
Kurtosis1502.5335
Mean20094191
Median Absolute Deviation (MAD)69682
Skewness-36.826573
Sum1.1168351 × 1011
Variance6.1168197 × 1010
MonotonicityNot monotonic
2024-04-17T04:35:26.254578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20141229 35
 
0.4%
20110405 32
 
0.3%
19980619 24
 
0.2%
20130412 20
 
0.2%
20190724 18
 
0.2%
20080225 16
 
0.2%
20011008 15
 
0.1%
20191231 14
 
0.1%
20000120 12
 
0.1%
20190618 11
 
0.1%
Other values (3391) 5361
53.6%
(Missing) 4442
44.4%
ValueCountFrequency (%)
9970214 1
< 0.1%
10000101 2
< 0.1%
19880724 1
< 0.1%
19900622 1
< 0.1%
19900706 1
< 0.1%
19900726 1
< 0.1%
19901124 1
< 0.1%
19921203 1
< 0.1%
19930610 1
< 0.1%
19930916 1
< 0.1%
ValueCountFrequency (%)
20500228 1
 
< 0.1%
20210129 3
< 0.1%
20210127 3
< 0.1%
20210126 1
 
< 0.1%
20210121 1
 
< 0.1%
20210120 4
< 0.1%
20210119 1
 
< 0.1%
20210118 3
< 0.1%
20210115 1
 
< 0.1%
20210114 4
< 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 

Distinct4319
Distinct (%)76.2%
Missing4331
Missing (%)43.3%
Memory size156.2 KiB
2024-04-17T04:35:26.581337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.6283295
Min length1

Characters and Unicode

Total characters54583
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

Unique4201 ?
Unique (%)74.1%

Sample

1st row051 6373344
2nd row051
3rd row051 2073350
4th row051 4682750
5th row051 914 8285
ValueCountFrequency (%)
051 5132
42.9%
070 140
 
1.2%
02 78
 
0.7%
727 51
 
0.4%
728 50
 
0.4%
031 21
 
0.2%
747 19
 
0.2%
611 18
 
0.2%
583 18
 
0.2%
757 18
 
0.2%
Other values (4390) 6404
53.6%
2024-04-17T04:35:27.010708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9325
17.1%
5 8839
16.2%
1 8422
15.4%
6386
11.7%
2 3936
7.2%
7 3582
 
6.6%
3 3263
 
6.0%
6 2950
 
5.4%
8 2933
 
5.4%
4 2927
 
5.4%
Other values (2) 2020
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48196
88.3%
Space Separator 6386
 
11.7%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9325
19.3%
5 8839
18.3%
1 8422
17.5%
2 3936
8.2%
7 3582
 
7.4%
3 3263
 
6.8%
6 2950
 
6.1%
8 2933
 
6.1%
4 2927
 
6.1%
9 2019
 
4.2%
Space Separator
ValueCountFrequency (%)
6386
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54583
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9325
17.1%
5 8839
16.2%
1 8422
15.4%
6386
11.7%
2 3936
7.2%
7 3582
 
6.6%
3 3263
 
6.0%
6 2950
 
5.4%
8 2933
 
5.4%
4 2927
 
5.4%
Other values (2) 2020
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54583
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9325
17.1%
5 8839
16.2%
1 8422
15.4%
6386
11.7%
2 3936
7.2%
7 3582
 
6.6%
3 3263
 
6.0%
6 2950
 
5.4%
8 2933
 
5.4%
4 2927
 
5.4%
Other values (2) 2020
 
3.7%

소재지면적
Text

MISSING 

Distinct4767
Distinct (%)53.9%
Missing1150
Missing (%)11.5%
Memory size156.2 KiB
2024-04-17T04:35:27.378891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9239548
Min length3

Characters and Unicode

Total characters43577
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

Unique3393 ?
Unique (%)38.3%

Sample

1st row154.80
2nd row35.90
3rd row33.42
4th row74.70
5th row28.07
ValueCountFrequency (%)
00 315
 
3.6%
3.30 145
 
1.6%
6.60 107
 
1.2%
10.00 73
 
0.8%
33.00 52
 
0.6%
12.00 41
 
0.5%
15.00 41
 
0.5%
20.00 39
 
0.4%
16.50 36
 
0.4%
3.00 33
 
0.4%
Other values (4757) 7968
90.0%
2024-04-17T04:35:27.842756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8850
20.3%
0 7178
16.5%
1 4103
9.4%
2 3890
8.9%
3 3406
 
7.8%
4 3050
 
7.0%
6 3010
 
6.9%
5 2965
 
6.8%
8 2614
 
6.0%
7 2300
 
5.3%
Other values (2) 2211
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34725
79.7%
Other Punctuation 8852
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7178
20.7%
1 4103
11.8%
2 3890
11.2%
3 3406
9.8%
4 3050
8.8%
6 3010
8.7%
5 2965
8.5%
8 2614
 
7.5%
7 2300
 
6.6%
9 2209
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 8850
> 99.9%
, 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 43577
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 8850
20.3%
0 7178
16.5%
1 4103
9.4%
2 3890
8.9%
3 3406
 
7.8%
4 3050
 
7.0%
6 3010
 
6.9%
5 2965
 
6.8%
8 2614
 
6.0%
7 2300
 
5.3%
Other values (2) 2211
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43577
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 8850
20.3%
0 7178
16.5%
1 4103
9.4%
2 3890
8.9%
3 3406
 
7.8%
4 3050
 
7.0%
6 3010
 
6.9%
5 2965
 
6.8%
8 2614
 
6.0%
7 2300
 
5.3%
Other values (2) 2211
 
5.1%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct859
Distinct (%)8.7%
Missing179
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean611161
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:27.980120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile600814
Q1607826
median612730
Q3614850
95-th percentile618440
Maximum619953
Range19942
Interquartile range (IQR)7024

Descriptive statistics

Standard deviation5411.4642
Coefficient of variation (CV)0.0088544004
Kurtosis-0.70142495
Mean611161
Median Absolute Deviation (MAD)3925
Skewness-0.47369026
Sum6.0022122 × 109
Variance29283945
MonotonicityNot monotonic
2024-04-17T04:35:28.118989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
612020 194
 
1.9%
614847 147
 
1.5%
614845 112
 
1.1%
618200 106
 
1.1%
609839 101
 
1.0%
614846 97
 
1.0%
600017 90
 
0.9%
612704 87
 
0.9%
608805 81
 
0.8%
601803 76
 
0.8%
Other values (849) 8730
87.3%
(Missing) 179
 
1.8%
ValueCountFrequency (%)
600011 8
 
0.1%
600012 8
 
0.1%
600013 7
 
0.1%
600015 6
 
0.1%
600016 8
 
0.1%
600017 90
0.9%
600021 11
 
0.1%
600022 4
 
< 0.1%
600023 5
 
0.1%
600024 1
 
< 0.1%
ValueCountFrequency (%)
619953 27
0.3%
619952 8
 
0.1%
619951 29
0.3%
619913 13
 
0.1%
619912 36
0.4%
619911 19
0.2%
619906 19
0.2%
619905 43
0.4%
619904 18
0.2%
619903 43
0.4%
Distinct8655
Distinct (%)86.6%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-04-17T04:35:28.641903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length59
Mean length24.867781
Min length7

Characters and Unicode

Total characters248454
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

Unique7996 ?
Unique (%)80.0%

Sample

1st row부산광역시 남구 문현동 405-3번지
2nd row부산광역시 영도구 동삼동 510-9번지 영구임대상가 .동 101호
3rd row부산광역시 금정구 장전동 135-25번지
4th row부산광역시 사하구 하단동 494-3번지
5th row부산광역시 동구 초량동 444-3번지
ValueCountFrequency (%)
부산광역시 9990
 
21.3%
부산진구 1522
 
3.2%
해운대구 1165
 
2.5%
동래구 783
 
1.7%
금정구 774
 
1.6%
남구 685
 
1.5%
수영구 647
 
1.4%
북구 643
 
1.4%
사상구 613
 
1.3%
부전동 575
 
1.2%
Other values (9597) 29532
62.9%
2024-04-17T04:35:29.083601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36948
 
14.9%
13018
 
5.2%
12217
 
4.9%
1 11806
 
4.8%
11619
 
4.7%
10434
 
4.2%
10274
 
4.1%
10065
 
4.1%
9963
 
4.0%
9835
 
4.0%
Other values (549) 112275
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150692
60.7%
Decimal Number 49997
 
20.1%
Space Separator 36948
 
14.9%
Dash Punctuation 8680
 
3.5%
Open Punctuation 560
 
0.2%
Close Punctuation 558
 
0.2%
Other Punctuation 493
 
0.2%
Uppercase Letter 439
 
0.2%
Lowercase Letter 43
 
< 0.1%
Math Symbol 41
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13018
 
8.6%
12217
 
8.1%
11619
 
7.7%
10434
 
6.9%
10274
 
6.8%
10065
 
6.7%
9963
 
6.6%
9835
 
6.5%
8769
 
5.8%
2215
 
1.5%
Other values (490) 52283
34.7%
Uppercase Letter
ValueCountFrequency (%)
B 104
23.7%
S 57
13.0%
A 57
13.0%
K 38
 
8.7%
C 21
 
4.8%
G 20
 
4.6%
E 18
 
4.1%
D 17
 
3.9%
L 12
 
2.7%
I 11
 
2.5%
Other values (15) 84
19.1%
Decimal Number
ValueCountFrequency (%)
1 11806
23.6%
2 6912
13.8%
3 5567
11.1%
5 4568
 
9.1%
4 4554
 
9.1%
0 4103
 
8.2%
6 3434
 
6.9%
7 3320
 
6.6%
8 2877
 
5.8%
9 2856
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
e 27
62.8%
c 4
 
9.3%
l 3
 
7.0%
a 2
 
4.7%
p 2
 
4.7%
z 1
 
2.3%
s 1
 
2.3%
i 1
 
2.3%
v 1
 
2.3%
m 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 438
88.8%
. 21
 
4.3%
@ 17
 
3.4%
/ 6
 
1.2%
: 5
 
1.0%
& 3
 
0.6%
· 2
 
0.4%
' 1
 
0.2%
Space Separator
ValueCountFrequency (%)
36948
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8680
100.0%
Open Punctuation
ValueCountFrequency (%)
( 560
100.0%
Close Punctuation
ValueCountFrequency (%)
) 558
100.0%
Math Symbol
ValueCountFrequency (%)
~ 41
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150692
60.7%
Common 97277
39.2%
Latin 485
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13018
 
8.6%
12217
 
8.1%
11619
 
7.7%
10434
 
6.9%
10274
 
6.8%
10065
 
6.7%
9963
 
6.6%
9835
 
6.5%
8769
 
5.8%
2215
 
1.5%
Other values (490) 52283
34.7%
Latin
ValueCountFrequency (%)
B 104
21.4%
S 57
11.8%
A 57
11.8%
K 38
 
7.8%
e 27
 
5.6%
C 21
 
4.3%
G 20
 
4.1%
E 18
 
3.7%
D 17
 
3.5%
L 12
 
2.5%
Other values (26) 114
23.5%
Common
ValueCountFrequency (%)
36948
38.0%
1 11806
 
12.1%
- 8680
 
8.9%
2 6912
 
7.1%
3 5567
 
5.7%
5 4568
 
4.7%
4 4554
 
4.7%
0 4103
 
4.2%
6 3434
 
3.5%
7 3320
 
3.4%
Other values (13) 7385
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150692
60.7%
ASCII 97757
39.3%
Number Forms 3
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36948
37.8%
1 11806
 
12.1%
- 8680
 
8.9%
2 6912
 
7.1%
3 5567
 
5.7%
5 4568
 
4.7%
4 4554
 
4.7%
0 4103
 
4.2%
6 3434
 
3.5%
7 3320
 
3.4%
Other values (47) 7865
 
8.0%
Hangul
ValueCountFrequency (%)
13018
 
8.6%
12217
 
8.1%
11619
 
7.7%
10434
 
6.9%
10274
 
6.8%
10065
 
6.7%
9963
 
6.6%
9835
 
6.5%
8769
 
5.8%
2215
 
1.5%
Other values (490) 52283
34.7%
Number Forms
ValueCountFrequency (%)
3
100.0%
None
ValueCountFrequency (%)
· 2
100.0%

도로명전체주소
Text

MISSING 

Distinct6587
Distinct (%)93.4%
Missing2946
Missing (%)29.5%
Memory size156.2 KiB
2024-04-17T04:35:29.425518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length58
Mean length33.094131
Min length19

Characters and Unicode

Total characters233446
Distinct characters577
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

Unique6349 ?
Unique (%)90.0%

Sample

1st row부산광역시 남구 수영로 21-1 (문현동)
2nd row부산광역시 금정구 수림로85번길 43, 1층 (장전동)
3rd row부산광역시 남구 용소로40번길 10, 지하1층 (대연동)
4th row부산광역시 사하구 낙동대로516번길 55, 103호 (하단동, 동아맨션)
5th row부산광역시 사하구 낙동남로 1413, 아트몰링 지하1층 (하단동)
ValueCountFrequency (%)
부산광역시 7054
 
15.5%
1층 2452
 
5.4%
부산진구 998
 
2.2%
해운대구 944
 
2.1%
금정구 539
 
1.2%
남구 533
 
1.2%
2층 478
 
1.1%
동래구 442
 
1.0%
기장군 438
 
1.0%
우동 434
 
1.0%
Other values (5983) 31201
68.6%
2024-04-17T04:35:29.914683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38473
 
16.5%
1 10827
 
4.6%
9583
 
4.1%
9034
 
3.9%
8787
 
3.8%
7750
 
3.3%
7632
 
3.3%
7118
 
3.0%
, 7031
 
3.0%
7016
 
3.0%
Other values (567) 120195
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136022
58.3%
Space Separator 38473
 
16.5%
Decimal Number 35719
 
15.3%
Other Punctuation 7063
 
3.0%
Open Punctuation 6999
 
3.0%
Close Punctuation 6998
 
3.0%
Uppercase Letter 1043
 
0.4%
Dash Punctuation 984
 
0.4%
Math Symbol 95
 
< 0.1%
Lowercase Letter 47
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9583
 
7.0%
9034
 
6.6%
8787
 
6.5%
7750
 
5.7%
7632
 
5.6%
7118
 
5.2%
7016
 
5.2%
6938
 
5.1%
4448
 
3.3%
3852
 
2.8%
Other values (506) 63864
47.0%
Uppercase Letter
ValueCountFrequency (%)
A 214
20.5%
C 167
16.0%
B 160
15.3%
E 144
13.8%
P 127
12.2%
S 55
 
5.3%
K 35
 
3.4%
D 23
 
2.2%
G 15
 
1.4%
H 15
 
1.4%
Other values (15) 88
8.4%
Lowercase Letter
ValueCountFrequency (%)
e 29
61.7%
s 4
 
8.5%
c 2
 
4.3%
l 2
 
4.3%
a 2
 
4.3%
p 2
 
4.3%
m 2
 
4.3%
y 1
 
2.1%
b 1
 
2.1%
v 1
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 10827
30.3%
2 5242
14.7%
3 3456
 
9.7%
0 3285
 
9.2%
4 2688
 
7.5%
5 2671
 
7.5%
6 2241
 
6.3%
7 2135
 
6.0%
8 1590
 
4.5%
9 1584
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 7031
99.5%
. 13
 
0.2%
@ 9
 
0.1%
· 3
 
< 0.1%
/ 3
 
< 0.1%
& 2
 
< 0.1%
' 1
 
< 0.1%
: 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 94
98.9%
× 1
 
1.1%
Space Separator
ValueCountFrequency (%)
38473
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6999
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6998
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 984
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136022
58.3%
Common 96331
41.3%
Latin 1093
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9583
 
7.0%
9034
 
6.6%
8787
 
6.5%
7750
 
5.7%
7632
 
5.6%
7118
 
5.2%
7016
 
5.2%
6938
 
5.1%
4448
 
3.3%
3852
 
2.8%
Other values (506) 63864
47.0%
Latin
ValueCountFrequency (%)
A 214
19.6%
C 167
15.3%
B 160
14.6%
E 144
13.2%
P 127
11.6%
S 55
 
5.0%
K 35
 
3.2%
e 29
 
2.7%
D 23
 
2.1%
G 15
 
1.4%
Other values (27) 124
11.3%
Common
ValueCountFrequency (%)
38473
39.9%
1 10827
 
11.2%
, 7031
 
7.3%
( 6999
 
7.3%
) 6998
 
7.3%
2 5242
 
5.4%
3 3456
 
3.6%
0 3285
 
3.4%
4 2688
 
2.8%
5 2671
 
2.8%
Other values (14) 8661
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136022
58.3%
ASCII 97417
41.7%
None 4
 
< 0.1%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38473
39.5%
1 10827
 
11.1%
, 7031
 
7.2%
( 6999
 
7.2%
) 6998
 
7.2%
2 5242
 
5.4%
3 3456
 
3.5%
0 3285
 
3.4%
4 2688
 
2.8%
5 2671
 
2.7%
Other values (48) 9747
 
10.0%
Hangul
ValueCountFrequency (%)
9583
 
7.0%
9034
 
6.6%
8787
 
6.5%
7750
 
5.7%
7632
 
5.6%
7118
 
5.2%
7016
 
5.2%
6938
 
5.1%
4448
 
3.3%
3852
 
2.8%
Other values (506) 63864
47.0%
Number Forms
ValueCountFrequency (%)
3
100.0%
None
ValueCountFrequency (%)
· 3
75.0%
× 1
 
25.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1523
Distinct (%)21.8%
Missing3011
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean47691.961
Minimum46002
Maximum49527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:30.053363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46069.4
Q146932
median47786
Q348439
95-th percentile49276
Maximum49527
Range3525
Interquartile range (IQR)1507

Descriptive statistics

Standard deviation984.01052
Coefficient of variation (CV)0.020632629
Kurtosis-1.0544525
Mean47691.961
Median Absolute Deviation (MAD)741
Skewness-0.031882599
Sum3.3331911 × 108
Variance968276.71
MonotonicityNot monotonic
2024-04-17T04:35:30.187820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48060 131
 
1.3%
48058 119
 
1.2%
46726 110
 
1.1%
48944 84
 
0.8%
47285 82
 
0.8%
48735 51
 
0.5%
48953 49
 
0.5%
48095 49
 
0.5%
48059 44
 
0.4%
47296 44
 
0.4%
Other values (1513) 6226
62.3%
(Missing) 3011
30.1%
ValueCountFrequency (%)
46002 1
 
< 0.1%
46004 4
 
< 0.1%
46005 1
 
< 0.1%
46006 1
 
< 0.1%
46007 8
 
0.1%
46008 22
0.2%
46010 1
 
< 0.1%
46012 6
 
0.1%
46013 7
 
0.1%
46014 2
 
< 0.1%
ValueCountFrequency (%)
49527 2
 
< 0.1%
49525 1
 
< 0.1%
49524 4
< 0.1%
49523 1
 
< 0.1%
49522 2
 
< 0.1%
49521 6
0.1%
49520 3
< 0.1%
49519 2
 
< 0.1%
49518 6
0.1%
49515 4
< 0.1%
Distinct8953
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T04:35:30.485543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length35
Mean length6.9898
Min length1

Characters and Unicode

Total characters69898
Distinct characters1059
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8320 ?
Unique (%)83.2%

Sample

1st row베네치아
2nd row이딸리앙제과점
3rd row달디1031
4th row버즈
5th row중앙
ValueCountFrequency (%)
세븐일레븐 93
 
0.7%
씨유 87
 
0.7%
카페 84
 
0.6%
gs25 82
 
0.6%
coffee 60
 
0.5%
미니스톱 51
 
0.4%
커피 45
 
0.3%
스타벅스 42
 
0.3%
컴포즈커피 42
 
0.3%
cafe 31
 
0.2%
Other values (9464) 12321
95.2%
2024-04-17T04:35:30.905554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2944
 
4.2%
2693
 
3.9%
2053
 
2.9%
1655
 
2.4%
1416
 
2.0%
1402
 
2.0%
) 1133
 
1.6%
( 1124
 
1.6%
1111
 
1.6%
886
 
1.3%
Other values (1049) 53481
76.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57251
81.9%
Uppercase Letter 3159
 
4.5%
Space Separator 2944
 
4.2%
Lowercase Letter 2605
 
3.7%
Decimal Number 1429
 
2.0%
Close Punctuation 1135
 
1.6%
Open Punctuation 1126
 
1.6%
Other Punctuation 191
 
0.3%
Dash Punctuation 37
 
0.1%
Modifier Symbol 9
 
< 0.1%
Other values (5) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2693
 
4.7%
2053
 
3.6%
1655
 
2.9%
1416
 
2.5%
1402
 
2.4%
1111
 
1.9%
886
 
1.5%
866
 
1.5%
847
 
1.5%
808
 
1.4%
Other values (960) 43514
76.0%
Uppercase Letter
ValueCountFrequency (%)
C 454
14.4%
S 325
 
10.3%
G 271
 
8.6%
P 237
 
7.5%
E 233
 
7.4%
O 192
 
6.1%
A 169
 
5.3%
T 142
 
4.5%
F 137
 
4.3%
L 105
 
3.3%
Other values (16) 894
28.3%
Lowercase Letter
ValueCountFrequency (%)
e 440
16.9%
a 283
10.9%
o 256
9.8%
f 242
 
9.3%
c 184
 
7.1%
n 137
 
5.3%
s 112
 
4.3%
r 108
 
4.1%
t 106
 
4.1%
i 100
 
3.8%
Other values (16) 637
24.5%
Other Punctuation
ValueCountFrequency (%)
& 65
34.0%
. 62
32.5%
, 24
 
12.6%
' 18
 
9.4%
/ 8
 
4.2%
: 5
 
2.6%
! 3
 
1.6%
" 2
 
1.0%
% 1
 
0.5%
1
 
0.5%
Other values (2) 2
 
1.0%
Decimal Number
ValueCountFrequency (%)
2 445
31.1%
5 347
24.3%
1 175
 
12.2%
0 124
 
8.7%
3 89
 
6.2%
4 79
 
5.5%
8 46
 
3.2%
9 46
 
3.2%
7 42
 
2.9%
6 36
 
2.5%
Close Punctuation
ValueCountFrequency (%)
) 1133
99.8%
] 2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1124
99.8%
[ 2
 
0.2%
Modifier Symbol
ValueCountFrequency (%)
` 6
66.7%
˚ 3
33.3%
Math Symbol
ValueCountFrequency (%)
+ 3
75.0%
~ 1
 
25.0%
Other Symbol
ValueCountFrequency (%)
° 2
50.0%
2
50.0%
Space Separator
ValueCountFrequency (%)
2944
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Number
ValueCountFrequency (%)
1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57241
81.9%
Common 6882
 
9.8%
Latin 5765
 
8.2%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2693
 
4.7%
2053
 
3.6%
1655
 
2.9%
1416
 
2.5%
1402
 
2.4%
1111
 
1.9%
886
 
1.5%
866
 
1.5%
847
 
1.5%
808
 
1.4%
Other values (952) 43504
76.0%
Latin
ValueCountFrequency (%)
C 454
 
7.9%
e 440
 
7.6%
S 325
 
5.6%
a 283
 
4.9%
G 271
 
4.7%
o 256
 
4.4%
f 242
 
4.2%
P 237
 
4.1%
E 233
 
4.0%
O 192
 
3.3%
Other values (43) 2832
49.1%
Common
ValueCountFrequency (%)
2944
42.8%
) 1133
 
16.5%
( 1124
 
16.3%
2 445
 
6.5%
5 347
 
5.0%
1 175
 
2.5%
0 124
 
1.8%
3 89
 
1.3%
4 79
 
1.1%
& 65
 
0.9%
Other values (26) 357
 
5.2%
Han
ValueCountFrequency (%)
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57239
81.9%
ASCII 12636
 
18.1%
CJK 10
 
< 0.1%
None 5
 
< 0.1%
Modifier Letters 3
 
< 0.1%
Letterlike Symbols 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2944
23.3%
) 1133
 
9.0%
( 1124
 
8.9%
C 454
 
3.6%
2 445
 
3.5%
e 440
 
3.5%
5 347
 
2.7%
S 325
 
2.6%
a 283
 
2.2%
G 271
 
2.1%
Other values (72) 4870
38.5%
Hangul
ValueCountFrequency (%)
2693
 
4.7%
2053
 
3.6%
1655
 
2.9%
1416
 
2.5%
1402
 
2.4%
1111
 
1.9%
886
 
1.5%
866
 
1.5%
847
 
1.5%
808
 
1.4%
Other values (951) 43502
76.0%
Modifier Letters
ValueCountFrequency (%)
˚ 3
100.0%
None
ValueCountFrequency (%)
° 2
40.0%
1
20.0%
1
20.0%
· 1
20.0%
CJK
ValueCountFrequency (%)
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Letterlike Symbols
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct8488
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0134683 × 1013
Minimum1.9990211 × 1013
Maximum2.0210129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:31.038470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0010498 × 1013
Q12.0080225 × 1013
median2.0170427 × 1013
Q32.0191018 × 1013
95-th percentile2.020112 × 1013
Maximum2.0210129 × 1013
Range2.1991817 × 1011
Interquartile range (IQR)1.1079298 × 1011

Descriptive statistics

Standard deviation7.0994595 × 1010
Coefficient of variation (CV)0.0035259853
Kurtosis-0.8988704
Mean2.0134683 × 1013
Median Absolute Deviation (MAD)3.0289017 × 1010
Skewness-0.792743
Sum2.0134683 × 1017
Variance5.0402325 × 1021
MonotonicityNot monotonic
2024-04-17T04:35:31.177180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020228000000 98
 
1.0%
20010803000000 64
 
0.6%
20010823000000 54
 
0.5%
20020827000000 53
 
0.5%
19990318000000 53
 
0.5%
20020110000000 51
 
0.5%
19990317000000 36
 
0.4%
20020828000000 36
 
0.4%
20020618000000 33
 
0.3%
20020225000000 31
 
0.3%
Other values (8478) 9491
94.9%
ValueCountFrequency (%)
19990211000000 1
 
< 0.1%
19990225000000 1
 
< 0.1%
19990303000000 10
 
0.1%
19990304000000 4
 
< 0.1%
19990305000000 18
 
0.2%
19990308000000 2
 
< 0.1%
19990311000000 1
 
< 0.1%
19990316000000 7
 
0.1%
19990317000000 36
0.4%
19990318000000 53
0.5%
ValueCountFrequency (%)
20210129173246 1
< 0.1%
20210129165539 1
< 0.1%
20210129165348 1
< 0.1%
20210129163518 1
< 0.1%
20210129162509 1
< 0.1%
20210129162340 1
< 0.1%
20210129160808 1
< 0.1%
20210129160035 1
< 0.1%
20210129152233 1
< 0.1%
20210129115141 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6615 
U
3385 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6615
66.1%
U 3385
33.9%

Length

2024-04-17T04:35:31.290984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:31.374417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6615
66.1%
u 3385
33.9%
Distinct941
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-31 02:40:00
2024-04-17T04:35:31.470276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T04:35:31.603724image/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
2925 
일반조리판매
1790 
기타 휴게음식점
1482 
다방
1459 
과자점
929 
Other values (16)
1415 

Length

Max length8
Median length6
Mean length4.2812
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row커피숍
2nd row과자점
3rd row커피숍
4th row다방
5th row과자점

Common Values

ValueCountFrequency (%)
커피숍 2925
29.2%
일반조리판매 1790
17.9%
기타 휴게음식점 1482
14.8%
다방 1459
14.6%
과자점 929
 
9.3%
패스트푸드 606
 
6.1%
편의점 463
 
4.6%
백화점 91
 
0.9%
푸드트럭 81
 
0.8%
전통찻집 48
 
0.5%
Other values (11) 126
 
1.3%

Length

2024-04-17T04:35:31.733412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 2925
25.5%
일반조리판매 1790
15.6%
기타 1482
12.9%
휴게음식점 1482
12.9%
다방 1459
12.7%
과자점 929
 
8.1%
패스트푸드 606
 
5.3%
편의점 463
 
4.0%
백화점 91
 
0.8%
푸드트럭 81
 
0.7%
Other values (12) 174
 
1.5%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct6726
Distinct (%)70.1%
Missing411
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean388365.17
Minimum364927.7
Maximum408182.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:31.856186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum364927.7
5-th percentile379352.81
Q1384820.12
median388172.85
Q3392022.01
95-th percentile398345.25
Maximum408182.16
Range43254.465
Interquartile range (IQR)7201.892

Descriptive statistics

Standard deviation5993.8378
Coefficient of variation (CV)0.01543351
Kurtosis0.87463958
Mean388365.17
Median Absolute Deviation (MAD)3554.1316
Skewness-0.071752
Sum3.7240336 × 109
Variance35926092
MonotonicityNot monotonic
2024-04-17T04:35:31.985980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
394482.139208377 98
 
1.0%
387271.299492377 96
 
1.0%
393952.264486105 87
 
0.9%
385590.814676765 83
 
0.8%
387539.767677801 78
 
0.8%
389097.800933845 39
 
0.4%
389314.662085919 30
 
0.3%
392495.046847798 25
 
0.2%
392321.102334852 24
 
0.2%
380128.339808636 23
 
0.2%
Other values (6716) 9006
90.1%
(Missing) 411
 
4.1%
ValueCountFrequency (%)
364927.696730227 3
< 0.1%
365045.343077193 2
< 0.1%
365331.554111646 1
 
< 0.1%
365359.1028736 1
 
< 0.1%
365434.715726108 2
< 0.1%
366678.639686731 1
 
< 0.1%
366779.273666901 2
< 0.1%
366799.216536177 3
< 0.1%
366829.531355754 1
 
< 0.1%
366854.076165373 2
< 0.1%
ValueCountFrequency (%)
408182.162093325 1
< 0.1%
407878.31227469 1
< 0.1%
407818.998027909 1
< 0.1%
407756.907308392 1
< 0.1%
407434.691805327 1
< 0.1%
407082.695163351 1
< 0.1%
407012.469380515 1
< 0.1%
406968.18195989 1
< 0.1%
406962.984916538 1
< 0.1%
406949.405821447 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct6727
Distinct (%)70.2%
Missing411
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean187322.1
Minimum169466.97
Maximum211459
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:32.134571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169466.97
5-th percentile178904.81
Q1183896.97
median186795.12
Q3191004.23
95-th percentile197066.06
Maximum211459
Range41992.031
Interquartile range (IQR)7107.2602

Descriptive statistics

Standard deviation5864.1684
Coefficient of variation (CV)0.031305268
Kurtosis0.85492247
Mean187322.1
Median Absolute Deviation (MAD)3672.9441
Skewness0.62419017
Sum1.7962316 × 109
Variance34388472
MonotonicityNot monotonic
2024-04-17T04:35:32.258564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187606.035424193 98
 
1.0%
186099.137533193 96
 
1.0%
187602.933160728 87
 
0.9%
179553.867031936 83
 
0.8%
184402.96650913 78
 
0.8%
192260.811648263 39
 
0.4%
194669.898821687 30
 
0.3%
183633.944535074 25
 
0.2%
184041.758684038 24
 
0.2%
186803.363627811 23
 
0.2%
Other values (6717) 9006
90.1%
(Missing) 411
 
4.1%
ValueCountFrequency (%)
169466.971226381 1
 
< 0.1%
170813.584718477 3
< 0.1%
172487.88651035 1
 
< 0.1%
172497.470216223 2
< 0.1%
173080.332146413 2
< 0.1%
173725.8041865 1
 
< 0.1%
173765.464798248 2
< 0.1%
173880.935177659 1
 
< 0.1%
173914.718015169 1
 
< 0.1%
173920.699770928 1
 
< 0.1%
ValueCountFrequency (%)
211459.001777975 2
< 0.1%
210945.104382171 3
< 0.1%
210284.515757078 1
 
< 0.1%
210184.120503763 1
 
< 0.1%
210111.800324086 1
 
< 0.1%
209997.104379978 1
 
< 0.1%
209321.781147486 1
 
< 0.1%
208694.830978882 1
 
< 0.1%
208621.775293103 1
 
< 0.1%
208616.491041704 1
 
< 0.1%

위생업태명
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
커피숍
2927 
일반조리판매
1802 
기타 휴게음식점
1495 
다방
1458 
과자점
930 
Other values (16)
1388 

Length

Max length8
Median length6
Mean length4.2915
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row커피숍
2nd row과자점
3rd row커피숍
4th row다방
5th row과자점

Common Values

ValueCountFrequency (%)
커피숍 2927
29.3%
일반조리판매 1802
18.0%
기타 휴게음식점 1495
14.9%
다방 1458
14.6%
과자점 930
 
9.3%
패스트푸드 608
 
6.1%
편의점 435
 
4.3%
백화점 91
 
0.9%
푸드트럭 81
 
0.8%
전통찻집 49
 
0.5%
Other values (11) 124
 
1.2%

Length

2024-04-17T04:35:32.395395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 2927
25.5%
일반조리판매 1802
15.7%
기타 1495
13.0%
휴게음식점 1495
13.0%
다방 1458
12.7%
과자점 930
 
8.1%
패스트푸드 608
 
5.3%
편의점 435
 
3.8%
백화점 91
 
0.8%
푸드트럭 81
 
0.7%
Other values (12) 173
 
1.5%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct6
Distinct (%)0.2%
Missing7587
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean0.058433485
Minimum0
Maximum15
Zeros2318
Zeros (%)23.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:32.502106image/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 deviation0.50812669
Coefficient of variation (CV)8.6958135
Kurtosis634.99989
Mean0.058433485
Median Absolute Deviation (MAD)0
Skewness22.719235
Sum141
Variance0.25819274
MonotonicityNot monotonic
2024-04-17T04:35:32.602150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 2318
 
23.2%
1 82
 
0.8%
2 8
 
0.1%
15 2
 
< 0.1%
3 2
 
< 0.1%
7 1
 
< 0.1%
(Missing) 7587
75.9%
ValueCountFrequency (%)
0 2318
23.2%
1 82
 
0.8%
2 8
 
0.1%
3 2
 
< 0.1%
7 1
 
< 0.1%
15 2
 
< 0.1%
ValueCountFrequency (%)
15 2
 
< 0.1%
7 1
 
< 0.1%
3 2
 
< 0.1%
2 8
 
0.1%
1 82
 
0.8%
0 2318
23.2%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.4%
Missing7551
Missing (%)75.5%
Infinite0
Infinite (%)0.0%
Mean0.12903226
Minimum0
Maximum29
Zeros2247
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:32.695777image/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 deviation0.89461575
Coefficient of variation (CV)6.9332721
Kurtosis605.85248
Mean0.12903226
Median Absolute Deviation (MAD)0
Skewness22.153727
Sum316
Variance0.80033734
MonotonicityNot monotonic
2024-04-17T04:35:32.799865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 2247
 
22.5%
1 161
 
1.6%
2 35
 
0.4%
3 1
 
< 0.1%
4 1
 
< 0.1%
17 1
 
< 0.1%
20 1
 
< 0.1%
29 1
 
< 0.1%
12 1
 
< 0.1%
(Missing) 7551
75.5%
ValueCountFrequency (%)
0 2247
22.5%
1 161
 
1.6%
2 35
 
0.4%
3 1
 
< 0.1%
4 1
 
< 0.1%
12 1
 
< 0.1%
17 1
 
< 0.1%
20 1
 
< 0.1%
29 1
 
< 0.1%
ValueCountFrequency (%)
29 1
 
< 0.1%
20 1
 
< 0.1%
17 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%
2 35
 
0.4%
1 161
 
1.6%
0 2247
22.5%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6928 
기타
2453 
주택가주변
 
317
유흥업소밀집지역
 
124
아파트지역
 
116
Other values (3)
 
62

Length

Max length8
Median length4
Mean length3.6265
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6928
69.3%
기타 2453
 
24.5%
주택가주변 317
 
3.2%
유흥업소밀집지역 124
 
1.2%
아파트지역 116
 
1.2%
학교정화(상대) 42
 
0.4%
학교정화(절대) 14
 
0.1%
결혼예식장주변 6
 
0.1%

Length

2024-04-17T04:35:32.948846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:33.058055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6928
69.3%
기타 2453
 
24.5%
주택가주변 317
 
3.2%
유흥업소밀집지역 124
 
1.2%
아파트지역 116
 
1.2%
학교정화(상대 42
 
0.4%
학교정화(절대 14
 
0.1%
결혼예식장주변 6
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7222 
기타
2148 
자율
 
613
지도
 
10
우수
 
6

Length

Max length4
Median length4
Mean length3.4443
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7222
72.2%
기타 2148
 
21.5%
자율 613
 
6.1%
지도 10
 
0.1%
우수 6
 
0.1%
1
 
< 0.1%

Length

2024-04-17T04:35:33.206885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:33.307957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7222
72.2%
기타 2148
 
21.5%
자율 613
 
6.1%
지도 10
 
0.1%
우수 6
 
0.1%
1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5213 
상수도전용
4749 
지하수전용
 
19
간이상수도
 
9
상수도(음용)지하수(주방용)겸용
 
8

Length

Max length19
Median length4
Mean length4.4911
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5213
52.1%
상수도전용 4749
47.5%
지하수전용 19
 
0.2%
간이상수도 9
 
0.1%
상수도(음용)지하수(주방용)겸용 8
 
0.1%
전용상수도(특정시설의 자가용 수도) 2
 
< 0.1%

Length

2024-04-17T04:35:33.426308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:33.525815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5213
52.1%
상수도전용 4749
47.5%
지하수전용 19
 
0.2%
간이상수도 9
 
0.1%
상수도(음용)지하수(주방용)겸용 8
 
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>
9996 
0
 
4

Length

Max length4
Median length4
Mean length3.9988
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> 9996
> 99.9%
0 4
 
< 0.1%

Length

2024-04-17T04:35:33.646145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:33.737095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9996
> 99.9%
0 4
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9996 
0
 
4

Length

Max length4
Median length4
Mean length3.9988
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> 9996
> 99.9%
0 4
 
< 0.1%

Length

2024-04-17T04:35:33.830259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:33.919135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9996
> 99.9%
0 4
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9996 
0
 
4

Length

Max length4
Median length4
Mean length3.9988
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> 9996
> 99.9%
0 4
 
< 0.1%

Length

2024-04-17T04:35:34.038011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:34.144095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9996
> 99.9%
0 4
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9996 
0
 
4

Length

Max length4
Median length4
Mean length3.9988
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> 9996
> 99.9%
0 4
 
< 0.1%

Length

2024-04-17T04:35:34.239754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:34.326966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9996
> 99.9%
0 4
 
< 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>
9996 
0
 
4

Length

Max length4
Median length4
Mean length3.9988
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> 9996
> 99.9%
0 4
 
< 0.1%

Length

2024-04-17T04:35:34.747143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:34.842395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9996
> 99.9%
0 4
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9996 
0
 
4

Length

Max length4
Median length4
Mean length3.9988
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> 9996
> 99.9%
0 4
 
< 0.1%

Length

2024-04-17T04:35:34.938558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:35.039294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9996
> 99.9%
0 4
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9642 
True
 
358
ValueCountFrequency (%)
False 9642
96.4%
True 358
 
3.6%
2024-04-17T04:35:35.108796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct4744
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.226838
Minimum0
Maximum1697.06
Zeros1526
Zeros (%)15.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T04:35:35.211040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.9
median27.985
Q362.7
95-th percentile170.0035
Maximum1697.06
Range1697.06
Interquartile range (IQR)54.8

Descriptive statistics

Standard deviation73.164316
Coefficient of variation (CV)1.4862689
Kurtosis49.285599
Mean49.226838
Median Absolute Deviation (MAD)24.265
Skewness4.8516162
Sum492268.38
Variance5353.0172
MonotonicityNot monotonic
2024-04-17T04:35:35.357205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1526
 
15.3%
3.3 145
 
1.5%
6.6 104
 
1.0%
10.0 74
 
0.7%
33.0 52
 
0.5%
12.0 41
 
0.4%
15.0 40
 
0.4%
20.0 37
 
0.4%
16.5 36
 
0.4%
13.2 33
 
0.3%
Other values (4734) 7912
79.1%
ValueCountFrequency (%)
0.0 1526
15.3%
0.4 1
 
< 0.1%
0.7 1
 
< 0.1%
0.8 3
 
< 0.1%
0.92 1
 
< 0.1%
0.96 1
 
< 0.1%
1.0 12
 
0.1%
1.17 1
 
< 0.1%
1.19 1
 
< 0.1%
1.2 7
 
0.1%
ValueCountFrequency (%)
1697.06 1
< 0.1%
1175.98 1
< 0.1%
901.57 1
< 0.1%
865.88 1
< 0.1%
791.8 1
< 0.1%
787.5 1
< 0.1%
722.81 1
< 0.1%
701.39 1
< 0.1%
685.6 1
< 0.1%
669.39 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
2
 
1

Length

Max length4
Median length4
Mean length3.9997
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> 9999
> 99.9%
2 1
 
< 0.1%

Length

2024-04-17T04:35:35.523804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:35:35.636673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
2 1
 
< 0.1%

전통업소주된음식
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T04:35:35.712512image/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%
2024-04-17T04:35:35.924654image/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
1437614377휴게음식점07_24_05_P33100003310000-104-1996-0199919961108<NA>3폐업2폐업20131231<NA><NA><NA>051 6373344154.80608824부산광역시 남구 문현동 405-3번지부산광역시 남구 수영로 21-1 (문현동)48415베네치아20131231155329I2018-08-31 23:59:59.0커피숍388611.317841183980.324941커피숍00주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N154.8<NA><NA><NA><NA>
1967819679휴게음식점07_24_05_P32800003280000-104-1995-0007619950302<NA>3폐업2폐업20001122<NA><NA><NA>05135.90606809부산광역시 영도구 동삼동 510-9번지 영구임대상가 .동 101호<NA><NA>이딸리앙제과점20001122000000I2018-08-31 23:59:59.0과자점388284.875872177081.087826과자점00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N35.9<NA><NA><NA><NA>
1001710018휴게음식점07_24_05_P33500003350000-104-2018-0010520181119<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.42609837부산광역시 금정구 장전동 135-25번지부산광역시 금정구 수림로85번길 43, 1층 (장전동)46281달디103120181217143128U2018-12-19 02:40:00.0커피숍389554.133569195171.437801커피숍<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N33.42<NA><NA><NA><NA>
1132111322휴게음식점07_24_05_P33400003340000-104-2001-0042920011208<NA>3폐업2폐업20030128<NA><NA><NA>051 2073350<NA>604851부산광역시 사하구 하단동 494-3번지<NA><NA>버즈20011208000000I2018-08-31 23:59:59.0다방379182.55302181081.44391다방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1708717088휴게음식점07_24_05_P32700003270000-104-1990-0030919900111<NA>3폐업2폐업19950523<NA><NA><NA>051 468275074.70601829부산광역시 동구 초량동 444-3번지<NA><NA>중앙20010823000000I2018-08-31 23:59:59.0과자점385762.905978181589.196297과자점00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N74.7<NA><NA><NA><NA>
1579915800휴게음식점07_24_05_P33500003350000-104-2008-0001320080626<NA>3폐업2폐업20090430<NA><NA><NA><NA>28.07609847부산광역시 금정구 구서동 252-32번지 구서골드1상가 B103호<NA><NA>찬이20080717171549I2018-08-31 23:59:59.0커피숍390022.176704196436.295019커피숍<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N28.07<NA><NA><NA><NA>
1198211983휴게음식점07_24_05_P33100003310000-104-2008-0004220081216<NA>3폐업2폐업20180905<NA><NA><NA><NA>114.98608810부산광역시 남구 대연동 511-1번지 지하1층부산광역시 남구 용소로40번길 10, 지하1층 (대연동)48498커피 아이엔지(ing)20180905153054U2018-09-05 23:59:59.0커피숍391373.521722183664.647541커피숍<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y114.98<NA><NA><NA><NA>
80808081휴게음식점07_24_05_P33400003340000-104-2015-0006420151208<NA>1영업/정상1영업<NA><NA><NA><NA>051 914 828557.95604849부산광역시 사하구 하단동 816-3번지부산광역시 사하구 낙동대로516번길 55, 103호 (하단동, 동아맨션)49324빽다방 동아대승학점20170608143442I2018-08-31 23:59:59.0다방379134.586457181124.93358다방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N57.95<NA><NA><NA><NA>
44334434휴게음식점07_24_05_P33400003340000-104-2019-0013220191118<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.80604852부산광역시 사하구 하단동 526-6번지 아트몰링부산광역시 사하구 낙동남로 1413, 아트몰링 지하1층 (하단동)49311떡만드는앙드레20191127124524U2019-11-29 02:40:00.0떡카페379212.079722180390.068955떡카페<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N16.8<NA><NA><NA><NA>
91099110휴게음식점07_24_05_P33700003370000-104-2016-0003420160722<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.16611817부산광역시 연제구 연산동 406-7부산광역시 연제구 과정로 223-2, 1층 (연산동)47558오늘도, 커피20210121113222U2021-01-23 02:40:00.0커피숍391466.260778189607.095108커피숍<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N33.16<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
1046210463휴게음식점07_24_05_P32600003260000-104-2021-0000420210119<NA>1영업/정상1영업<NA><NA><NA><NA><NA>39.02602825부산광역시 서구 서대신동3가 580부산광역시 서구 망양로21번길 18-1, 1층 (서대신동3가)49210샌치하다20210127164304U2021-01-29 02:40:00.0커피숍383380.403145181178.134133커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N39.02<NA><NA><NA><NA>
1971619717휴게음식점07_24_05_P32500003250000-104-1987-0009719870708<NA>3폐업2폐업20031211<NA><NA><NA>051145.25600046부산광역시 중구 남포동6가 83-2번지 (82-5)<NA><NA>이어도20020712000000I2018-08-31 23:59:59.0다방384847.461936179528.146629다방<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N145.25<NA><NA><NA><NA>
1397113972휴게음식점07_24_05_P33200003320000-104-2012-0001420120523<NA>3폐업2폐업20171017<NA><NA><NA>051 343 656551.10616805부산광역시 북구 구포동 1217-8번지부산광역시 북구 시랑로 62 (구포동)46631옥커피숍20171017160144I2018-08-31 23:59:59.0다방382538.760664190835.937828다방<NA>2<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N51.1<NA><NA><NA><NA>
1171411715휴게음식점07_24_05_P33000003300000-104-1999-0012019990128<NA>3폐업2폐업20001208<NA><NA><NA>05138.38607824부산광역시 동래구 수안동 521-0번지<NA><NA>구피커피전문점20001208000000I2018-08-31 23:59:59.0다방389725.962943191365.792134다방00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N38.38<NA><NA><NA><NA>
13091310휴게음식점07_24_05_P32500003250000-104-2019-0000620190211<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.07600801부산광역시 중구 대청동4가 82-32번지부산광역시 중구 중구로62번길 5-1, 1-2층 (대청동4가)48933음료실20190318165100U2019-03-20 02:40:00.0커피숍384897.251322180140.252516커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N40.07<NA><NA><NA><NA>
67596760휴게음식점07_24_05_P33400003340000-104-2020-0007620200722<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30604806부산광역시 사하구 감천동 552 감천자유아파트부산광역시 사하구 감천로105번길 55, 자유연립 상가동 1층 (감천동)49373세븐일레븐 부산감천자유점20200818130950U2020-08-20 02:40:00.0일반조리판매382698.273665178754.029808일반조리판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N3.3<NA><NA><NA><NA>
1419914200휴게음식점07_24_05_P33900003390000-104-2006-0001620060523<NA>3폐업2폐업20070122<NA><NA><NA>051 3327006<NA>617818부산광역시 사상구 모라동 202-2번지 벽산@상가지하102호<NA><NA>세븐벨치킨피자20060704000000I2018-08-31 23:59:59.0기타 휴게음식점381511.170752189844.425247기타 휴게음식점00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1031210313휴게음식점07_24_05_P33800003380000-104-2020-0012520201123<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.64613820부산광역시 수영구 망미동 212-17부산광역시 수영구 수미로71번길 9, 1층 (망미동)48215솔(sol)20201123150918I2020-11-25 00:23:07.0커피숍392914.632477188102.200929커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N42.64<NA><NA><NA><NA>
75007501휴게음식점07_24_05_P32900003290000-104-2020-0021220200910<NA>1영업/정상1영업<NA><NA><NA><NA><NA>37.25614846부산광역시 부산진구 부전동 226-9부산광역시 부산진구 중앙대로666번길 17, 7층 (부전동)47296터프앤쿠키(TUFF&COOKIE)20200910164248I2020-09-12 00:23:12.0커피숍387674.292977185628.880769커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N37.25<NA><NA><NA><NA>
1993519936휴게음식점07_24_05_P33300003330000-104-2020-0009320200515<NA>3폐업2폐업20200703<NA><NA><NA><NA>9.00612020부산광역시 해운대구 우동 1495 신세계백화점센텀시티점부산광역시 해운대구 센텀남대로 35, 신세계백화점센텀시티점 지하1층 일부호 (우동)48058교토마블20200703132319U2020-07-05 02:40:00.0백화점393952.264486187602.933161백화점<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N9.0<NA><NA><NA><NA>