Overview

Dataset statistics

Number of variables48
Number of observations10000
Missing cells108494
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 MiB
Average record size in memory421.0 B

Variable types

Numeric10
Categorical21
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description2021-03-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123112

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (98.9%)Imbalance
위생업태명 is highly imbalanced (98.8%)Imbalance
남성종사자수 is highly imbalanced (79.8%)Imbalance
여성종사자수 is highly imbalanced (74.7%)Imbalance
영업장주변구분명 is highly imbalanced (67.6%)Imbalance
등급구분명 is highly imbalanced (51.7%)Imbalance
급수시설구분명 is highly imbalanced (68.4%)Imbalance
공장판매직종업원수 is highly imbalanced (58.6%)Imbalance
공장생산직종업원수 is highly imbalanced (58.3%)Imbalance
보증액 is highly imbalanced (65.9%)Imbalance
월세액 is highly imbalanced (65.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2567 (25.7%) 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 4632 (46.3%) missing valuesMissing
소재지면적 has 4911 (49.1%) missing valuesMissing
소재지우편번호 has 213 (2.1%) missing valuesMissing
도로명전체주소 has 2695 (27.0%) missing valuesMissing
도로명우편번호 has 2752 (27.5%) missing valuesMissing
좌표정보(x) has 326 (3.3%) missing valuesMissing
좌표정보(y) has 326 (3.3%) missing valuesMissing
총종업원수 has 10000 (100.0%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
Unnamed: 47 has 10000 (100.0%) missing valuesMissing
폐업일자 is highly skewed (γ1 = -35.51670837)Skewed
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총종업원수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 47 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 9376 (93.8%) zerosZeros

Reproduction

Analysis started2024-04-17 12:35:43.204169
Analysis finished2024-04-17 12:35:44.979485
Duration1.78 second
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%
Mean11178.978
Minimum3
Maximum22372
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:45.034329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile1153.9
Q15612.5
median11159
Q316762.5
95-th percentile21277.1
Maximum22372
Range22369
Interquartile range (IQR)11150

Descriptive statistics

Standard deviation6440.4304
Coefficient of variation (CV)0.57611978
Kurtosis-1.1950798
Mean11178.978
Median Absolute Deviation (MAD)5579.5
Skewness0.0072253835
Sum1.1178978 × 108
Variance41479144
MonotonicityNot monotonic
2024-04-17T21:35:45.133263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3462 1
 
< 0.1%
5864 1
 
< 0.1%
17573 1
 
< 0.1%
21350 1
 
< 0.1%
21705 1
 
< 0.1%
2702 1
 
< 0.1%
21920 1
 
< 0.1%
19258 1
 
< 0.1%
12179 1
 
< 0.1%
14731 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
5 1
< 0.1%
10 1
< 0.1%
12 1
< 0.1%
15 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
21 1
< 0.1%
22 1
< 0.1%
29 1
< 0.1%
ValueCountFrequency (%)
22372 1
< 0.1%
22371 1
< 0.1%
22368 1
< 0.1%
22367 1
< 0.1%
22366 1
< 0.1%
22365 1
< 0.1%
22364 1
< 0.1%
22363 1
< 0.1%
22362 1
< 0.1%
22361 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

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

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 10000
100.0%

Length

2024-04-17T21:35:45.224505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:45.299921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 10000
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
07_22_19_P
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_19_P
2nd row07_22_19_P
3rd row07_22_19_P
4th row07_22_19_P
5th row07_22_19_P

Common Values

ValueCountFrequency (%)
07_22_19_P 10000
100.0%

Length

2024-04-17T21:35:45.368584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:45.441067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_19_p 10000
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3326117
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:45.508973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3330000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation39690.425
Coefficient of variation (CV)0.011932961
Kurtosis-0.85761952
Mean3326117
Median Absolute Deviation (MAD)40000
Skewness0.15806978
Sum3.326117 × 1010
Variance1.5753298 × 109
MonotonicityNot monotonic
2024-04-17T21:35:45.594889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1933
19.3%
3290000 1595
16.0%
3300000 927
9.3%
3370000 757
 
7.6%
3380000 657
 
6.6%
3350000 528
 
5.3%
3340000 492
 
4.9%
3390000 484
 
4.8%
3400000 451
 
4.5%
3320000 440
 
4.4%
Other values (6) 1736
17.4%
ValueCountFrequency (%)
3250000 329
 
3.3%
3260000 222
 
2.2%
3270000 292
 
2.9%
3280000 355
 
3.5%
3290000 1595
16.0%
3300000 927
9.3%
3310000 421
 
4.2%
3320000 440
 
4.4%
3330000 1933
19.3%
3340000 492
 
4.9%
ValueCountFrequency (%)
3400000 451
 
4.5%
3390000 484
 
4.8%
3380000 657
 
6.6%
3370000 757
 
7.6%
3360000 117
 
1.2%
3350000 528
 
5.3%
3340000 492
 
4.9%
3330000 1933
19.3%
3320000 440
 
4.4%
3310000 421
 
4.2%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T21:35:45.757072image/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 row3300000-107-1986-00057
2nd row3290000-107-2009-00066
3rd row3350000-107-2010-00014
4th row3290000-107-2011-00105
5th row3250000-107-2019-00017
ValueCountFrequency (%)
3300000-107-1986-00057 1
 
< 0.1%
3290000-107-2010-00122 1
 
< 0.1%
3400000-107-1994-00109 1
 
< 0.1%
3290000-107-2001-01595 1
 
< 0.1%
3370000-107-2018-00064 1
 
< 0.1%
3270000-107-2004-00011 1
 
< 0.1%
3300000-107-1988-00421 1
 
< 0.1%
3380000-107-1980-00398 1
 
< 0.1%
3350000-107-2003-00012 1
 
< 0.1%
3280000-107-2015-00005 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T21:35:46.008165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 92087
41.9%
- 30000
 
13.6%
1 21993
 
10.0%
3 21733
 
9.9%
2 16700
 
7.6%
7 14101
 
6.4%
9 8209
 
3.7%
8 4540
 
2.1%
4 3808
 
1.7%
5 3520
 
1.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92087
48.5%
1 21993
 
11.6%
3 21733
 
11.4%
2 16700
 
8.8%
7 14101
 
7.4%
9 8209
 
4.3%
8 4540
 
2.4%
4 3808
 
2.0%
5 3520
 
1.9%
6 3309
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92087
41.9%
- 30000
 
13.6%
1 21993
 
10.0%
3 21733
 
9.9%
2 16700
 
7.6%
7 14101
 
6.4%
9 8209
 
3.7%
8 4540
 
2.1%
4 3808
 
1.7%
5 3520
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92087
41.9%
- 30000
 
13.6%
1 21993
 
10.0%
3 21733
 
9.9%
2 16700
 
7.6%
7 14101
 
6.4%
9 8209
 
3.7%
8 4540
 
2.1%
4 3808
 
1.7%
5 3520
 
1.6%

인허가일자
Real number (ℝ)

Distinct4524
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20104856
Minimum19640629
Maximum20210129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:46.116482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19640629
5-th percentile19880409
Q120050206
median20150614
Q320190410
95-th percentile20200812
Maximum20210129
Range569500
Interquartile range (IQR)140203.5

Descriptive statistics

Standard deviation104897.73
Coefficient of variation (CV)0.005217532
Kurtosis1.5709129
Mean20104856
Median Absolute Deviation (MAD)49814.5
Skewness-1.3527434
Sum2.0104856 × 1011
Variance1.1003534 × 1010
MonotonicityNot monotonic
2024-04-17T21:35:46.217636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180709 18
 
0.2%
20190930 17
 
0.2%
20190401 17
 
0.2%
20190211 14
 
0.1%
20190715 14
 
0.1%
20190429 14
 
0.1%
20191125 13
 
0.1%
20180305 13
 
0.1%
19760407 13
 
0.1%
20190805 13
 
0.1%
Other values (4514) 9854
98.5%
ValueCountFrequency (%)
19640629 1
< 0.1%
19650614 1
< 0.1%
19650629 1
< 0.1%
19680222 1
< 0.1%
19680316 1
< 0.1%
19680430 1
< 0.1%
19680827 1
< 0.1%
19680904 1
< 0.1%
19681026 1
< 0.1%
19681129 1
< 0.1%
ValueCountFrequency (%)
20210129 6
0.1%
20210128 4
 
< 0.1%
20210127 12
0.1%
20210126 5
0.1%
20210125 4
 
< 0.1%
20210122 8
0.1%
20210121 4
 
< 0.1%
20210120 3
 
< 0.1%
20210119 4
 
< 0.1%
20210118 10
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
7433 
1
2567 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7433
74.3%
1 2567
 
25.7%

Length

2024-04-17T21:35:46.336725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:46.596312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7433
74.3%
1 2567
 
25.7%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7433 
영업/정상
2567 

Length

Max length5
Median length2
Mean length2.7701
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7433
74.3%
영업/정상 2567
 
25.7%

Length

2024-04-17T21:35:46.672774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:46.750907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7433
74.3%
영업/정상 2567
 
25.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7433 
1
2567 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7433
74.3%
1 2567
 
25.7%

Length

2024-04-17T21:35:46.823017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:46.891412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7433
74.3%
1 2567
 
25.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7433 
영업
2567 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7433
74.3%
영업 2567
 
25.7%

Length

2024-04-17T21:35:46.964395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:47.031269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7433
74.3%
영업 2567
 
25.7%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct3433
Distinct (%)46.2%
Missing2567
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean20132058
Minimum10000101
Maximum20210129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:47.121264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000101
5-th percentile20020228
Q120091022
median20170303
Q320190629
95-th percentile20200812
Maximum20210129
Range10210028
Interquartile range (IQR)99607

Descriptive statistics

Standard deviation270127.31
Coefficient of variation (CV)0.013417769
Kurtosis1329.6494
Mean20132058
Median Absolute Deviation (MAD)30116
Skewness-35.516708
Sum1.4964159 × 1011
Variance7.2968763 × 1010
MonotonicityNot monotonic
2024-04-17T21:35:47.227838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20100111 24
 
0.2%
20021011 18
 
0.2%
20120222 16
 
0.2%
20191016 15
 
0.1%
20190331 15
 
0.1%
20051102 14
 
0.1%
20200603 14
 
0.1%
20201104 14
 
0.1%
20190228 13
 
0.1%
20200111 13
 
0.1%
Other values (3423) 7277
72.8%
(Missing) 2567
 
25.7%
ValueCountFrequency (%)
10000101 5
0.1%
19940711 1
 
< 0.1%
19940913 2
 
< 0.1%
19941124 1
 
< 0.1%
19950112 1
 
< 0.1%
19950704 1
 
< 0.1%
19950724 1
 
< 0.1%
19950802 1
 
< 0.1%
19950919 1
 
< 0.1%
19950926 3
< 0.1%
ValueCountFrequency (%)
20210129 1
 
< 0.1%
20210125 1
 
< 0.1%
20210122 2
< 0.1%
20210118 1
 
< 0.1%
20210115 1
 
< 0.1%
20210114 1
 
< 0.1%
20210113 1
 
< 0.1%
20210106 1
 
< 0.1%
20201231 2
< 0.1%
20201230 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 

Distinct3573
Distinct (%)66.6%
Missing4632
Missing (%)46.3%
Memory size156.2 KiB
2024-04-17T21:35:47.514502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.665238
Min length1

Characters and Unicode

Total characters57251
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

Unique3246 ?
Unique (%)60.5%

Sample

1st row051 5545421
2nd row051 892 4668
3rd row051 8517701
4th row02 845 4358
5th row051 3059338
ValueCountFrequency (%)
051 3950
32.3%
031 235
 
1.9%
055 231
 
1.9%
02 146
 
1.2%
831 139
 
1.1%
070 137
 
1.1%
5711 95
 
0.8%
053 80
 
0.7%
343 53
 
0.4%
062 49
 
0.4%
Other values (3799) 7113
58.2%
2024-04-17T21:35:47.892248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9562
16.7%
5 8605
15.0%
1 7853
13.7%
7041
12.3%
2 4446
7.8%
3 3869
6.8%
8 3692
 
6.4%
7 3488
 
6.1%
6 3375
 
5.9%
4 3067
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50210
87.7%
Space Separator 7041
 
12.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9562
19.0%
5 8605
17.1%
1 7853
15.6%
2 4446
8.9%
3 3869
7.7%
8 3692
 
7.4%
7 3488
 
6.9%
6 3375
 
6.7%
4 3067
 
6.1%
9 2253
 
4.5%
Space Separator
ValueCountFrequency (%)
7041
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57251
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9562
16.7%
5 8605
15.0%
1 7853
13.7%
7041
12.3%
2 4446
7.8%
3 3869
6.8%
8 3692
 
6.4%
7 3488
 
6.1%
6 3375
 
5.9%
4 3067
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9562
16.7%
5 8605
15.0%
1 7853
13.7%
7041
12.3%
2 4446
7.8%
3 3869
6.8%
8 3692
 
6.4%
7 3488
 
6.1%
6 3375
 
5.9%
4 3067
 
5.4%

소재지면적
Text

MISSING 

Distinct2003
Distinct (%)39.4%
Missing4911
Missing (%)49.1%
Memory size156.2 KiB
2024-04-17T21:35:48.216000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.5910788
Min length3

Characters and Unicode

Total characters23364
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

Unique1325 ?
Unique (%)26.0%

Sample

1st row33.20
2nd row6.60
3rd row13.50
4th row125.40
5th row19.47
ValueCountFrequency (%)
00 273
 
5.4%
3.00 141
 
2.8%
6.00 116
 
2.3%
6.60 80
 
1.6%
3.30 75
 
1.5%
4.00 68
 
1.3%
33.00 60
 
1.2%
2.00 56
 
1.1%
9.90 53
 
1.0%
10.00 53
 
1.0%
Other values (1993) 4114
80.8%
2024-04-17T21:35:48.660339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5241
22.4%
. 5089
21.8%
1 2095
 
9.0%
2 2041
 
8.7%
3 1813
 
7.8%
6 1431
 
6.1%
5 1379
 
5.9%
4 1364
 
5.8%
8 1076
 
4.6%
9 947
 
4.1%
Other values (2) 888
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18274
78.2%
Other Punctuation 5090
 
21.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5241
28.7%
1 2095
 
11.5%
2 2041
 
11.2%
3 1813
 
9.9%
6 1431
 
7.8%
5 1379
 
7.5%
4 1364
 
7.5%
8 1076
 
5.9%
9 947
 
5.2%
7 887
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 5089
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 23364
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5241
22.4%
. 5089
21.8%
1 2095
 
9.0%
2 2041
 
8.7%
3 1813
 
7.8%
6 1431
 
6.1%
5 1379
 
5.9%
4 1364
 
5.8%
8 1076
 
4.6%
9 947
 
4.1%
Other values (2) 888
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23364
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5241
22.4%
. 5089
21.8%
1 2095
 
9.0%
2 2041
 
8.7%
3 1813
 
7.8%
6 1431
 
6.1%
5 1379
 
5.9%
4 1364
 
5.8%
8 1076
 
4.6%
9 947
 
4.1%
Other values (2) 888
 
3.8%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct721
Distinct (%)7.4%
Missing213
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean611352.6
Minimum600011
Maximum642829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:48.778267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601807
Q1607835
median612020
Q3614814
95-th percentile617834
Maximum642829
Range42818
Interquartile range (IQR)6979

Descriptive statistics

Standard deviation4720.1812
Coefficient of variation (CV)0.0077208818
Kurtosis0.010062361
Mean611352.6
Median Absolute Deviation (MAD)2827
Skewness-0.54654257
Sum5.9833079 × 109
Variance22280110
MonotonicityNot monotonic
2024-04-17T21:35:48.879222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
612020 608
 
6.1%
612851 217
 
2.2%
600017 211
 
2.1%
611807 193
 
1.9%
613819 191
 
1.9%
614847 182
 
1.8%
612811 156
 
1.6%
614843 147
 
1.5%
612824 139
 
1.4%
611840 139
 
1.4%
Other values (711) 7604
76.0%
(Missing) 213
 
2.1%
ValueCountFrequency (%)
600011 1
 
< 0.1%
600012 1
 
< 0.1%
600016 1
 
< 0.1%
600017 211
2.1%
600021 1
 
< 0.1%
600041 4
 
< 0.1%
600044 4
 
< 0.1%
600045 3
 
< 0.1%
600046 42
 
0.4%
600051 2
 
< 0.1%
ValueCountFrequency (%)
642829 1
 
< 0.1%
619953 7
 
0.1%
619952 1
 
< 0.1%
619951 11
 
0.1%
619913 4
 
< 0.1%
619912 37
0.4%
619911 2
 
< 0.1%
619906 80
0.8%
619905 54
0.5%
619904 12
 
0.1%
Distinct5415
Distinct (%)54.5%
Missing60
Missing (%)0.6%
Memory size156.2 KiB
2024-04-17T21:35:49.094383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length51
Mean length25.714588
Min length16

Characters and Unicode

Total characters255603
Distinct characters440
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4697 ?
Unique (%)47.3%

Sample

1st row부산광역시 동래구 명륜동 676-105번지
2nd row부산광역시 부산진구 전포동 891-38번지 외2필지(지하2층)
3rd row부산광역시 금정구 금사동 85-6번지 탑마트금사점내
4th row부산광역시 부산진구 당감동 123번지
5th row부산광역시 중구 남포동6가 1번지
ValueCountFrequency (%)
부산광역시 9939
 
20.9%
해운대구 1932
 
4.1%
부산진구 1558
 
3.3%
동래구 919
 
1.9%
우동 843
 
1.8%
연제구 757
 
1.6%
수영구 657
 
1.4%
부전동 571
 
1.2%
금정구 515
 
1.1%
연산동 506
 
1.1%
Other values (5769) 29441
61.8%
2024-04-17T21:35:49.419234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37704
 
14.8%
12961
 
5.1%
12572
 
4.9%
11420
 
4.5%
10640
 
4.2%
10364
 
4.1%
9953
 
3.9%
9949
 
3.9%
9787
 
3.8%
1 9728
 
3.8%
Other values (430) 120525
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162709
63.7%
Decimal Number 44996
 
17.6%
Space Separator 37704
 
14.8%
Dash Punctuation 7578
 
3.0%
Uppercase Letter 1246
 
0.5%
Open Punctuation 574
 
0.2%
Close Punctuation 572
 
0.2%
Other Punctuation 184
 
0.1%
Lowercase Letter 30
 
< 0.1%
Math Symbol 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12961
 
8.0%
12572
 
7.7%
11420
 
7.0%
10640
 
6.5%
10364
 
6.4%
9953
 
6.1%
9949
 
6.1%
9787
 
6.0%
8984
 
5.5%
2767
 
1.7%
Other values (382) 63312
38.9%
Uppercase Letter
ValueCountFrequency (%)
B 267
21.4%
S 248
19.9%
T 188
15.1%
G 184
14.8%
E 121
9.7%
K 63
 
5.1%
A 32
 
2.6%
H 29
 
2.3%
U 29
 
2.3%
Y 29
 
2.3%
Other values (12) 56
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 9728
21.6%
2 6231
13.8%
5 5040
11.2%
3 4272
9.5%
4 4082
9.1%
0 3596
 
8.0%
7 3522
 
7.8%
6 3103
 
6.9%
9 2789
 
6.2%
8 2633
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 149
81.0%
@ 11
 
6.0%
. 10
 
5.4%
· 8
 
4.3%
/ 5
 
2.7%
& 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
g 13
43.3%
s 13
43.3%
e 3
 
10.0%
b 1
 
3.3%
Space Separator
ValueCountFrequency (%)
37704
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7578
100.0%
Open Punctuation
ValueCountFrequency (%)
( 574
100.0%
Close Punctuation
ValueCountFrequency (%)
) 572
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162708
63.7%
Common 91617
35.8%
Latin 1277
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12961
 
8.0%
12572
 
7.7%
11420
 
7.0%
10640
 
6.5%
10364
 
6.4%
9953
 
6.1%
9949
 
6.1%
9787
 
6.0%
8984
 
5.5%
2767
 
1.7%
Other values (381) 63311
38.9%
Latin
ValueCountFrequency (%)
B 267
20.9%
S 248
19.4%
T 188
14.7%
G 184
14.4%
E 121
9.5%
K 63
 
4.9%
A 32
 
2.5%
H 29
 
2.3%
U 29
 
2.3%
Y 29
 
2.3%
Other values (17) 87
 
6.8%
Common
ValueCountFrequency (%)
37704
41.2%
1 9728
 
10.6%
- 7578
 
8.3%
2 6231
 
6.8%
5 5040
 
5.5%
3 4272
 
4.7%
4 4082
 
4.5%
0 3596
 
3.9%
7 3522
 
3.8%
6 3103
 
3.4%
Other values (11) 6761
 
7.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162708
63.7%
ASCII 92885
36.3%
None 8
 
< 0.1%
CJK 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37704
40.6%
1 9728
 
10.5%
- 7578
 
8.2%
2 6231
 
6.7%
5 5040
 
5.4%
3 4272
 
4.6%
4 4082
 
4.4%
0 3596
 
3.9%
7 3522
 
3.8%
6 3103
 
3.3%
Other values (36) 8029
 
8.6%
Hangul
ValueCountFrequency (%)
12961
 
8.0%
12572
 
7.7%
11420
 
7.0%
10640
 
6.5%
10364
 
6.4%
9953
 
6.1%
9949
 
6.1%
9787
 
6.0%
8984
 
5.5%
2767
 
1.7%
Other values (381) 63311
38.9%
None
ValueCountFrequency (%)
· 8
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct4272
Distinct (%)58.5%
Missing2695
Missing (%)27.0%
Memory size156.2 KiB
2024-04-17T21:35:49.628010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length57
Mean length32.835044
Min length19

Characters and Unicode

Total characters239860
Distinct characters473
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3736 ?
Unique (%)51.1%

Sample

1st row부산광역시 동래구 문화로 5-1 (명륜동)
2nd row부산광역시 부산진구 가야대로679번길 134, 지상1층 (당감동)
3rd row부산광역시 중구 구덕로 73 (남포동6가)
4th row부산광역시 사하구 다송로 58, 탑마트신다대점 (다대동)
5th row부산광역시 연제구 연동로 8 (연산동)
ValueCountFrequency (%)
부산광역시 7304
 
15.9%
1층 1443
 
3.1%
해운대구 1389
 
3.0%
부산진구 972
 
2.1%
지하1층 760
 
1.7%
동래구 664
 
1.4%
우동 658
 
1.4%
연제구 552
 
1.2%
수영구 431
 
0.9%
센텀남대로 429
 
0.9%
Other values (3900) 31450
68.3%
2024-04-17T21:35:49.951631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38774
 
16.2%
9469
 
3.9%
9458
 
3.9%
9259
 
3.9%
8317
 
3.5%
1 8225
 
3.4%
7840
 
3.3%
7361
 
3.1%
7311
 
3.0%
7255
 
3.0%
Other values (463) 126591
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149087
62.2%
Space Separator 38774
 
16.2%
Decimal Number 29594
 
12.3%
Open Punctuation 7246
 
3.0%
Close Punctuation 7243
 
3.0%
Other Punctuation 6043
 
2.5%
Uppercase Letter 1051
 
0.4%
Dash Punctuation 677
 
0.3%
Lowercase Letter 132
 
0.1%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9469
 
6.4%
9458
 
6.3%
9259
 
6.2%
8317
 
5.6%
7840
 
5.3%
7361
 
4.9%
7311
 
4.9%
7255
 
4.9%
5049
 
3.4%
3010
 
2.0%
Other values (408) 74758
50.1%
Uppercase Letter
ValueCountFrequency (%)
S 262
24.9%
G 187
17.8%
B 156
14.8%
E 126
12.0%
K 57
 
5.4%
A 52
 
4.9%
C 50
 
4.8%
N 27
 
2.6%
Y 26
 
2.5%
U 26
 
2.5%
Other values (13) 82
 
7.8%
Decimal Number
ValueCountFrequency (%)
1 8225
27.8%
2 4287
14.5%
3 3000
 
10.1%
5 2739
 
9.3%
7 2460
 
8.3%
4 2314
 
7.8%
0 1718
 
5.8%
6 1643
 
5.6%
9 1632
 
5.5%
8 1576
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 6020
99.6%
· 8
 
0.1%
@ 7
 
0.1%
. 4
 
0.1%
/ 2
 
< 0.1%
& 1
 
< 0.1%
* 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
s 56
42.4%
g 50
37.9%
n 9
 
6.8%
c 9
 
6.8%
b 4
 
3.0%
e 3
 
2.3%
a 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 7245
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 7242
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
38774
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 677
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149086
62.2%
Common 89589
37.4%
Latin 1184
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9469
 
6.4%
9458
 
6.3%
9259
 
6.2%
8317
 
5.6%
7840
 
5.3%
7361
 
4.9%
7311
 
4.9%
7255
 
4.9%
5049
 
3.4%
3010
 
2.0%
Other values (407) 74757
50.1%
Latin
ValueCountFrequency (%)
S 262
22.1%
G 187
15.8%
B 156
13.2%
E 126
10.6%
K 57
 
4.8%
s 56
 
4.7%
A 52
 
4.4%
C 50
 
4.2%
g 50
 
4.2%
N 27
 
2.3%
Other values (21) 161
13.6%
Common
ValueCountFrequency (%)
38774
43.3%
1 8225
 
9.2%
( 7245
 
8.1%
) 7242
 
8.1%
, 6020
 
6.7%
2 4287
 
4.8%
3 3000
 
3.3%
5 2739
 
3.1%
7 2460
 
2.7%
4 2314
 
2.6%
Other values (14) 7283
 
8.1%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149086
62.2%
ASCII 90764
37.8%
None 8
 
< 0.1%
CJK 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38774
42.7%
1 8225
 
9.1%
( 7245
 
8.0%
) 7242
 
8.0%
, 6020
 
6.6%
2 4287
 
4.7%
3 3000
 
3.3%
5 2739
 
3.0%
7 2460
 
2.7%
4 2314
 
2.5%
Other values (43) 8458
 
9.3%
Hangul
ValueCountFrequency (%)
9469
 
6.4%
9458
 
6.3%
9259
 
6.2%
8317
 
5.6%
7840
 
5.3%
7361
 
4.9%
7311
 
4.9%
7255
 
4.9%
5049
 
3.4%
3010
 
2.0%
Other values (407) 74757
50.1%
None
ValueCountFrequency (%)
· 8
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1134
Distinct (%)15.6%
Missing2752
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean47751.575
Minimum46002
Maximum51498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:50.056998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46209.75
Q147171
median47814
Q348301.25
95-th percentile49329.95
Maximum51498
Range5496
Interquartile range (IQR)1130.25

Descriptive statistics

Standard deviation913.7892
Coefficient of variation (CV)0.019136315
Kurtosis-0.6332748
Mean47751.575
Median Absolute Deviation (MAD)564
Skewness-0.050250613
Sum3.4610342 × 108
Variance835010.7
MonotonicityNot monotonic
2024-04-17T21:35:50.158611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48058 437
 
4.4%
48944 207
 
2.1%
48096 191
 
1.9%
47285 180
 
1.8%
48313 148
 
1.5%
47500 131
 
1.3%
46970 110
 
1.1%
46233 108
 
1.1%
47727 107
 
1.1%
47604 102
 
1.0%
Other values (1124) 5527
55.3%
(Missing) 2752
27.5%
ValueCountFrequency (%)
46002 1
 
< 0.1%
46003 3
 
< 0.1%
46004 4
 
< 0.1%
46006 1
 
< 0.1%
46007 3
 
< 0.1%
46008 15
0.1%
46010 3
 
< 0.1%
46012 4
 
< 0.1%
46013 1
 
< 0.1%
46015 34
0.3%
ValueCountFrequency (%)
51498 1
 
< 0.1%
49525 1
 
< 0.1%
49523 2
 
< 0.1%
49522 1
 
< 0.1%
49520 2
 
< 0.1%
49519 49
0.5%
49518 3
 
< 0.1%
49515 3
 
< 0.1%
49514 2
 
< 0.1%
49511 4
 
< 0.1%
Distinct5331
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T21:35:50.387933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length5.8951
Min length1

Characters and Unicode

Total characters58951
Distinct characters837
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4366 ?
Unique (%)43.7%

Sample

1st row진주떡방앗간
2nd row영우유통
3rd row화성종합식품(주)
4th row현대식육점
5th row초림단지묵
ValueCountFrequency (%)
주식회사 201
 
1.8%
현승유통 131
 
1.2%
주)정성 106
 
0.9%
주경식품 103
 
0.9%
현재상사 102
 
0.9%
주)미트벨리 90
 
0.8%
주)모두랑식품 89
 
0.8%
주)부산축산 86
 
0.8%
부산축산 80
 
0.7%
아라식품 73
 
0.7%
Other values (5573) 10116
90.5%
2024-04-17T21:35:50.712345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2297
 
3.9%
) 2090
 
3.5%
( 2044
 
3.5%
1541
 
2.6%
1414
 
2.4%
1178
 
2.0%
1100
 
1.9%
938
 
1.6%
902
 
1.5%
855
 
1.5%
Other values (827) 44592
75.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52174
88.5%
Close Punctuation 2090
 
3.5%
Open Punctuation 2044
 
3.5%
Space Separator 1178
 
2.0%
Uppercase Letter 680
 
1.2%
Lowercase Letter 442
 
0.7%
Decimal Number 158
 
0.3%
Other Punctuation 156
 
0.3%
Dash Punctuation 21
 
< 0.1%
Modifier Symbol 3
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2297
 
4.4%
1541
 
3.0%
1414
 
2.7%
1100
 
2.1%
938
 
1.8%
902
 
1.7%
855
 
1.6%
809
 
1.6%
755
 
1.4%
731
 
1.4%
Other values (752) 40832
78.3%
Lowercase Letter
ValueCountFrequency (%)
e 61
13.8%
o 41
 
9.3%
a 37
 
8.4%
r 28
 
6.3%
t 27
 
6.1%
i 27
 
6.1%
s 26
 
5.9%
n 24
 
5.4%
u 22
 
5.0%
l 21
 
4.8%
Other values (14) 128
29.0%
Uppercase Letter
ValueCountFrequency (%)
N 104
15.3%
T 101
14.9%
S 100
14.7%
I 91
13.4%
F 32
 
4.7%
E 30
 
4.4%
O 26
 
3.8%
C 25
 
3.7%
A 22
 
3.2%
G 22
 
3.2%
Other values (13) 127
18.7%
Decimal Number
ValueCountFrequency (%)
1 30
19.0%
2 29
18.4%
0 20
12.7%
5 16
10.1%
3 14
8.9%
4 12
 
7.6%
8 12
 
7.6%
9 10
 
6.3%
6 9
 
5.7%
7 6
 
3.8%
Other Punctuation
ValueCountFrequency (%)
' 80
51.3%
& 28
 
17.9%
. 25
 
16.0%
, 14
 
9.0%
! 4
 
2.6%
; 2
 
1.3%
: 1
 
0.6%
/ 1
 
0.6%
% 1
 
0.6%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 2090
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2044
100.0%
Space Separator
ValueCountFrequency (%)
1178
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52171
88.5%
Common 5654
 
9.6%
Latin 1122
 
1.9%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2297
 
4.4%
1541
 
3.0%
1414
 
2.7%
1100
 
2.1%
938
 
1.8%
902
 
1.7%
855
 
1.6%
809
 
1.6%
755
 
1.4%
731
 
1.4%
Other values (749) 40829
78.3%
Latin
ValueCountFrequency (%)
N 104
 
9.3%
T 101
 
9.0%
S 100
 
8.9%
I 91
 
8.1%
e 61
 
5.4%
o 41
 
3.7%
a 37
 
3.3%
F 32
 
2.9%
E 30
 
2.7%
r 28
 
2.5%
Other values (37) 497
44.3%
Common
ValueCountFrequency (%)
) 2090
37.0%
( 2044
36.2%
1178
20.8%
' 80
 
1.4%
1 30
 
0.5%
2 29
 
0.5%
& 28
 
0.5%
. 25
 
0.4%
- 21
 
0.4%
0 20
 
0.4%
Other values (17) 109
 
1.9%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52168
88.5%
ASCII 6776
 
11.5%
CJK 4
 
< 0.1%
Compat Jamo 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2297
 
4.4%
1541
 
3.0%
1414
 
2.7%
1100
 
2.1%
938
 
1.8%
902
 
1.7%
855
 
1.6%
809
 
1.6%
755
 
1.4%
731
 
1.4%
Other values (746) 40826
78.3%
ASCII
ValueCountFrequency (%)
) 2090
30.8%
( 2044
30.2%
1178
17.4%
N 104
 
1.5%
T 101
 
1.5%
S 100
 
1.5%
I 91
 
1.3%
' 80
 
1.2%
e 61
 
0.9%
o 41
 
0.6%
Other values (64) 886
13.1%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct7646
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0142452 × 1013
Minimum1.9990304 × 1013
Maximum2.0210129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:50.823765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990304 × 1013
5-th percentile2.0020612 × 1013
Q12.0100308 × 1013
median2.0170905 × 1013
Q32.0190808 × 1013
95-th percentile2.0201012 × 1013
Maximum2.0210129 × 1013
Range2.1982516 × 1011
Interquartile range (IQR)9.0499949 × 1010

Descriptive statistics

Standard deviation6.2285868 × 1010
Coefficient of variation (CV)0.0030922684
Kurtosis-0.5734916
Mean2.0142452 × 1013
Median Absolute Deviation (MAD)2.9680474 × 1010
Skewness-0.88665688
Sum2.0142452 × 1017
Variance3.8795293 × 1021
MonotonicityNot monotonic
2024-04-17T21:35:50.923378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020612000000 61
 
0.6%
20020305000000 54
 
0.5%
20020821000000 44
 
0.4%
20020621000000 38
 
0.4%
20010728000000 35
 
0.4%
20020724000000 33
 
0.3%
20010731000000 28
 
0.3%
20020611000000 27
 
0.3%
20010918000000 26
 
0.3%
20020719000000 25
 
0.2%
Other values (7636) 9629
96.3%
ValueCountFrequency (%)
19990304000000 11
0.1%
19990305000000 3
 
< 0.1%
19990318000000 17
0.2%
19990319000000 13
0.1%
19990322000000 2
 
< 0.1%
19990323000000 6
 
0.1%
19990324000000 5
 
0.1%
19990326000000 4
 
< 0.1%
19990329000000 1
 
< 0.1%
19990331000000 1
 
< 0.1%
ValueCountFrequency (%)
20210129162853 1
< 0.1%
20210129153240 1
< 0.1%
20210129152302 1
< 0.1%
20210129142605 1
< 0.1%
20210129135721 1
< 0.1%
20210129120114 1
< 0.1%
20210129115207 1
< 0.1%
20210129113339 1
< 0.1%
20210129113314 1
< 0.1%
20210129112256 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6401 
U
3599 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6401
64.0%
U 3599
36.0%

Length

2024-04-17T21:35:51.036700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:51.113247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6401
64.0%
u 3599
36.0%
Distinct978
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-31 02:40:00
2024-04-17T21:35:51.190906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T21:35:51.327738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9985 
기타
 
14
한식
 
1

Length

Max length9
Median length9
Mean length8.9895
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9985
99.9%
기타 14
 
0.1%
한식 1
 
< 0.1%

Length

2024-04-17T21:35:51.431647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:51.514103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9985
99.9%
기타 14
 
0.1%
한식 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3610
Distinct (%)37.3%
Missing326
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean389200.69
Minimum353660.89
Maximum407418.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:51.596783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum353660.89
5-th percentile380225.64
Q1385891.14
median389097.8
Q3392709.65
95-th percentile398196.18
Maximum407418.65
Range53757.759
Interquartile range (IQR)6818.507

Descriptive statistics

Standard deviation5490.4092
Coefficient of variation (CV)0.014106885
Kurtosis0.62047095
Mean389200.69
Median Absolute Deviation (MAD)3459.4178
Skewness-0.085114198
Sum3.7651275 × 109
Variance30144593
MonotonicityNot monotonic
2024-04-17T21:35:51.702507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393952.264486105 332
 
3.3%
387271.299492377 301
 
3.0%
397397.83276594 215
 
2.1%
385590.814676765 191
 
1.9%
392321.102334852 178
 
1.8%
387686.194940483 155
 
1.6%
389097.800933845 151
 
1.5%
387539.767677801 137
 
1.4%
389532.511756755 133
 
1.3%
394083.501537578 130
 
1.3%
Other values (3600) 7751
77.5%
(Missing) 326
 
3.3%
ValueCountFrequency (%)
353660.889782036 1
< 0.1%
366798.269419272 1
< 0.1%
366820.787750249 1
< 0.1%
366829.531355754 1
< 0.1%
367011.799190228 1
< 0.1%
367027.575037614 1
< 0.1%
367041.984452276 1
< 0.1%
367055.286163177 1
< 0.1%
367088.901392071 1
< 0.1%
367169.234957368 1
< 0.1%
ValueCountFrequency (%)
407418.648415535 1
< 0.1%
407245.567193252 1
< 0.1%
407036.696092095 2
< 0.1%
407015.247908441 1
< 0.1%
406982.053033795 1
< 0.1%
406949.405821447 1
< 0.1%
406200.972892162 1
< 0.1%
405688.580680087 1
< 0.1%
405511.30268554 1
< 0.1%
405434.718582706 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct3611
Distinct (%)37.3%
Missing326
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean187540.33
Minimum169678.05
Maximum211459
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:51.808354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169678.05
5-th percentile178823.38
Q1184575.18
median187562.68
Q3190926.9
95-th percentile196375.47
Maximum211459
Range41780.954
Interquartile range (IQR)6351.7158

Descriptive statistics

Standard deviation5408.632
Coefficient of variation (CV)0.028839834
Kurtosis0.90714639
Mean187540.33
Median Absolute Deviation (MAD)3159.7122
Skewness0.35193357
Sum1.8142652 × 109
Variance29253300
MonotonicityNot monotonic
2024-04-17T21:35:51.935977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187602.933160728 332
 
3.3%
186099.137533193 301
 
3.0%
187354.835259309 215
 
2.1%
179553.867031936 191
 
1.9%
184041.758684038 178
 
1.8%
189911.430545728 155
 
1.6%
192260.811648263 151
 
1.5%
184402.96650913 137
 
1.4%
188309.453546847 133
 
1.3%
187707.586117775 130
 
1.3%
Other values (3601) 7751
77.5%
(Missing) 326
 
3.3%
ValueCountFrequency (%)
169678.048271107 1
< 0.1%
173914.718015169 1
< 0.1%
174181.52961765 1
< 0.1%
174289.976688419 1
< 0.1%
174333.833259042 1
< 0.1%
174422.480246459 1
< 0.1%
174491.469961028 1
< 0.1%
174526.100850246 1
< 0.1%
174587.185782495 1
< 0.1%
174634.323253202 1
< 0.1%
ValueCountFrequency (%)
211459.001777975 1
 
< 0.1%
210945.104382171 1
 
< 0.1%
210004.830136767 1
 
< 0.1%
209383.598383269 1
 
< 0.1%
208089.112228672 1
 
< 0.1%
207739.619868549 1
 
< 0.1%
207716.999117547 1
 
< 0.1%
206788.899936301 1
 
< 0.1%
206512.517255249 3
< 0.1%
206353.855586145 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9979 
기타
 
14
<NA>
 
6
한식
 
1

Length

Max length9
Median length9
Mean length8.9865
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9979
99.8%
기타 14
 
0.1%
<NA> 6
 
0.1%
한식 1
 
< 0.1%

Length

2024-04-17T21:35:52.259677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:52.352806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9979
99.8%
기타 14
 
0.1%
na 6
 
0.1%
한식 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9247 
0
 
726
1
 
25
2
 
2

Length

Max length4
Median length4
Mean length3.7741
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9247
92.5%
0 726
 
7.3%
1 25
 
0.2%
2 2
 
< 0.1%

Length

2024-04-17T21:35:52.432523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:52.505968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9247
92.5%
0 726
 
7.3%
1 25
 
0.2%
2 2
 
< 0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9248 
0
 
726
1
 
26

Length

Max length4
Median length4
Mean length3.7744
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9248
92.5%
0 726
 
7.3%
1 26
 
0.3%

Length

2024-04-17T21:35:52.587564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:52.661893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9248
92.5%
0 726
 
7.3%
1 26
 
0.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8160 
기타
1739 
주택가주변
 
84
아파트지역
 
15
유흥업소밀집지역
 
2

Length

Max length8
Median length4
Mean length3.6629
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8160
81.6%
기타 1739
 
17.4%
주택가주변 84
 
0.8%
아파트지역 15
 
0.1%
유흥업소밀집지역 2
 
< 0.1%

Length

2024-04-17T21:35:52.743385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:52.833584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8160
81.6%
기타 1739
 
17.4%
주택가주변 84
 
0.8%
아파트지역 15
 
0.1%
유흥업소밀집지역 2
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8160 
기타
1683 
자율
 
157

Length

Max length4
Median length4
Mean length3.632
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8160
81.6%
기타 1683
 
16.8%
자율 157
 
1.6%

Length

2024-04-17T21:35:52.934429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:53.034629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8160
81.6%
기타 1683
 
16.8%
자율 157
 
1.6%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8444 
상수도전용
1547 
지하수전용
 
7
간이상수도
 
2

Length

Max length5
Median length4
Mean length4.1556
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8444
84.4%
상수도전용 1547
 
15.5%
지하수전용 7
 
0.1%
간이상수도 2
 
< 0.1%

Length

2024-04-17T21:35:53.129878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:53.202844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8444
84.4%
상수도전용 1547
 
15.5%
지하수전용 7
 
0.1%
간이상수도 2
 
< 0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6510 
0
3489 
1
 
1

Length

Max length4
Median length4
Mean length2.953
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6510
65.1%
0 3489
34.9%
1 1
 
< 0.1%

Length

2024-04-17T21:35:53.285822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:53.362952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6510
65.1%
0 3489
34.9%
1 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6510 
0
3490 

Length

Max length4
Median length4
Mean length2.953
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6510
65.1%
0 3490
34.9%

Length

2024-04-17T21:35:53.442105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:53.517620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6510
65.1%
0 3490
34.9%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6506 
0
3463 
1
 
29
2
 
1
3
 
1

Length

Max length4
Median length4
Mean length2.9518
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6506
65.1%
0 3463
34.6%
1 29
 
0.3%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T21:35:53.605926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:53.685910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6506
65.1%
0 3463
34.6%
1 29
 
0.3%
2 1
 
< 0.1%
3 1
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6504 
0
3454 
1
 
36
2
 
5
10
 
1

Length

Max length4
Median length4
Mean length2.9513
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6504
65.0%
0 3454
34.5%
1 36
 
0.4%
2 5
 
0.1%
10 1
 
< 0.1%

Length

2024-04-17T21:35:53.771183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:53.859547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6504
65.0%
0 3454
34.5%
1 36
 
0.4%
2 5
 
< 0.1%
10 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7735 
자가
1387 
임대
878 

Length

Max length4
Median length4
Mean length3.547
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7735
77.3%
자가 1387
 
13.9%
임대 878
 
8.8%

Length

2024-04-17T21:35:53.962082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:54.039910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7735
77.3%
자가 1387
 
13.9%
임대 878
 
8.8%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9366 
0
 
634

Length

Max length4
Median length4
Mean length3.8098
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> 9366
93.7%
0 634
 
6.3%

Length

2024-04-17T21:35:54.119161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:54.206504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9366
93.7%
0 634
 
6.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9366 
0
 
634

Length

Max length4
Median length4
Mean length3.8098
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> 9366
93.7%
0 634
 
6.3%

Length

2024-04-17T21:35:54.289568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:54.363223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9366
93.7%
0 634
 
6.3%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing6
Missing (%)0.1%
Memory size97.7 KiB
False
9994 
(Missing)
 
6
ValueCountFrequency (%)
False 9994
99.9%
(Missing) 6
 
0.1%
2024-04-17T21:35:54.417499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct404
Distinct (%)4.0%
Missing6
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean1.2029818
Minimum0
Maximum239
Zeros9376
Zeros (%)93.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:54.492771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.3
Maximum239
Range239
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.0447565
Coefficient of variation (CV)6.6873469
Kurtosis228.66934
Mean1.2029818
Median Absolute Deviation (MAD)0
Skewness12.635273
Sum12022.6
Variance64.718107
MonotonicityNot monotonic
2024-04-17T21:35:54.597430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9376
93.8%
3.3 25
 
0.2%
2.0 17
 
0.2%
9.9 16
 
0.2%
3.0 13
 
0.1%
4.0 12
 
0.1%
19.8 10
 
0.1%
10.0 8
 
0.1%
13.2 8
 
0.1%
16.5 8
 
0.1%
Other values (394) 501
 
5.0%
ValueCountFrequency (%)
0.0 9376
93.8%
0.3 1
 
< 0.1%
0.4 1
 
< 0.1%
0.55 1
 
< 0.1%
0.7 1
 
< 0.1%
0.75 1
 
< 0.1%
0.8 1
 
< 0.1%
0.84 1
 
< 0.1%
0.94 1
 
< 0.1%
1.0 5
 
0.1%
ValueCountFrequency (%)
239.0 1
< 0.1%
191.91 1
< 0.1%
190.64 1
< 0.1%
172.64 1
< 0.1%
144.6 1
< 0.1%
140.4 1
< 0.1%
133.03 1
< 0.1%
120.15 1
< 0.1%
107.78 1
< 0.1%
106.74 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

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
34613462즉석판매제조가공업07_22_19_P33000003300000-107-1986-0005719860616<NA>1영업/정상1영업<NA><NA><NA><NA>051 554542133.20607853부산광역시 동래구 명륜동 676-105번지부산광역시 동래구 문화로 5-1 (명륜동)47747진주떡방앗간20000801000000I2018-08-31 23:59:59.0즉석판매제조가공업389616.57365192128.234512즉석판매제조가공업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1207012071즉석판매제조가공업07_22_19_P32900003290000-107-2009-0006620090714<NA>3폐업2폐업20090722<NA><NA><NA><NA><NA>614868부산광역시 부산진구 전포동 891-38번지 외2필지(지하2층)<NA><NA>영우유통20090714102011I2018-08-31 23:59:59.0즉석판매제조가공업388095.097363185326.192499즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
2089520896즉석판매제조가공업07_22_19_P33500003350000-107-2010-0001420100324<NA>3폐업2폐업20101124<NA><NA><NA><NA>6.60609809부산광역시 금정구 금사동 85-6번지 탑마트금사점내<NA><NA>화성종합식품(주)20100324133736I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA><NA>
1897618977즉석판매제조가공업07_22_19_P32900003290000-107-2011-0010520111121<NA>3폐업2폐업20171121<NA><NA><NA>051 892 466813.50614816부산광역시 부산진구 당감동 123번지부산광역시 부산진구 가야대로679번길 134, 지상1층 (당감동)47274현대식육점20171121172910I2018-08-31 23:59:59.0즉석판매제조가공업385832.690455186056.393279즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
65926593즉석판매제조가공업07_22_19_P32500003250000-107-2019-0001720190214<NA>3폐업2폐업20190228<NA><NA><NA><NA><NA>600046부산광역시 중구 남포동6가 1번지부산광역시 중구 구덕로 73 (남포동6가)48982초림단지묵20190301041509U2019-03-03 02:40:00.0즉석판매제조가공업384820.119269179460.841059즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
2007120072즉석판매제조가공업07_22_19_P33400003340000-107-2018-0015020180914<NA>3폐업2폐업20180923<NA><NA><NA><NA><NA>604822부산광역시 사하구 다대동 120-19번지부산광역시 사하구 다송로 58, 탑마트신다대점 (다대동)49519현승유통20180924041526U2018-09-24 23:59:59.0즉석판매제조가공업380816.783733175515.467302즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
55795580즉석판매제조가공업07_22_19_P33700003370000-107-2021-0001120210127<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>611811부산광역시 연제구 연산동 312-42부산광역시 연제구 연동로 8 (연산동)47552최고집호떡20210127143610I2021-01-29 00:23:13.0즉석판매제조가공업390602.008218189702.104852즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1755717558즉석판매제조가공업07_22_19_P33700003370000-107-1998-0055519980225<NA>3폐업2폐업20120222<NA><NA><NA>051 8517701125.40611830부산광역시 연제구 연산동 1000-0번지<NA><NA>동백즉석도시락20010720000000I2018-08-31 23:59:59.0즉석판매제조가공업388911.641295188733.276764즉석판매제조가공업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
56645665즉석판매제조가공업07_22_19_P32500003250000-107-2021-0000520210113<NA>1영업/정상1영업<NA><NA><NA><NA>02 845 4358<NA>600017부산광역시 중구 중앙동7가 20-1 롯데백화점광복점부산광역시 중구 중앙대로 2, 롯데백화점광복점 지하1층 (중앙동7가)48944주식회사 행복생활건강20210113155742I2021-01-15 00:23:04.0즉석판매제조가공업385590.814677179553.867032즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
46034604즉석판매제조가공업07_22_19_P33900003390000-107-1996-0050219960704<NA>1영업/정상1영업<NA><NA><NA><NA>051 3059338<NA>617816부산광역시 사상구 덕포동 422-4번지부산광역시 사상구 삼덕로46번길 63 (덕포동)46950우일흑염소20150724091552I2018-08-31 23:59:59.0즉석판매제조가공업380433.121544187546.054807즉석판매제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
1670816709즉석판매제조가공업07_22_19_P32900003290000-107-2001-0153420010919<NA>3폐업2폐업20030207<NA><NA><NA>051 806993026.73614843부산광역시 부산진구 부전동 345-30번지 T통B반<NA><NA>일성중탕20020708000000I2018-08-31 23:59:59.0즉석판매제조가공업387601.464669186800.923562즉석판매제조가공업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
59025903즉석판매제조가공업07_22_19_P32800003280000-107-2017-0000120170102<NA>3폐업2폐업20181228<NA><NA><NA><NA>32.88606817부산광역시 영도구 영선동4가 245-1번지 상가 11동 4호부산광역시 영도구 남항새싹길 81, 상가동 1층 114호 (영선동4가)49078빵&쿠키20181228105450U2018-12-30 02:40:00.0즉석판매제조가공업386284.315674177801.686463즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
38283829즉석판매제조가공업07_22_19_P33000003300000-107-2007-0002920070326<NA>1영업/정상1영업<NA><NA><NA><NA>051 553333649.00607813부산광역시 동래구 사직동 143-56번지부산광역시 동래구 여고로135번길 55, 1층 (사직동)47832낙원떡집20170224155336I2018-08-31 23:59:59.0즉석판매제조가공업389087.975912191147.235187즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA><NA>
2215822159즉석판매제조가공업07_22_19_P33300003330000-107-2008-0008520080618<NA>3폐업2폐업20080625<NA><NA><NA>051<NA>612020부산광역시 해운대구 우동 1499번지 홈플러스(1층)<NA><NA>(주)야미20080618150156I2018-08-31 23:59:59.0즉석판매제조가공업394314.881157187833.001648즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1801718018즉석판매제조가공업07_22_19_P33700003370000-107-2003-0002220030326<NA>3폐업2폐업20080124<NA><NA><NA>051 500800011.40611807부산광역시 연제구 거제동 1208번지<NA><NA>(주)청정이20080123103717I2018-08-31 23:59:59.0즉석판매제조가공업387686.19494189911.430546즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
1884218843즉석판매제조가공업07_22_19_P32900003290000-107-2006-0012120061227<NA>3폐업2폐업20150422<NA><NA><NA>051 890800020.00614801부산광역시 부산진구 가야동 624-7번지 외2필지(홈플러스가야점)부산광역시 부산진구 가야대로 506 (가야동,외2필지(홈플러스가야점))47324대륙20120716114030I2018-08-31 23:59:59.0즉석판매제조가공업384668.52046185579.964272즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA><NA>
2184421845즉석판매제조가공업07_22_19_P33000003300000-107-1995-0049919950609<NA>3폐업2폐업20080725<NA><NA><NA>051 553245334.49607020부산광역시 동래구 복천동 215-1번지<NA><NA>웰푸른20060718000000I2018-08-31 23:59:59.0즉석판매제조가공업389981.670673191419.197903즉석판매제조가공업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1435814359즉석판매제조가공업07_22_19_P34000003400000-107-1999-0021419990701<NA>3폐업2폐업20080801<NA><NA><NA>051 7219716.00619913부산광역시 기장군 일광면 이천리 445-4번지<NA><NA>일광민물탕제원20050222000000I2018-08-31 23:59:59.0즉석판매제조가공업403518.459682198631.01065즉석판매제조가공업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1493414935즉석판매제조가공업07_22_19_P33300003330000-107-2011-0005220110518<NA>3폐업2폐업20110526<NA><NA><NA>022281634025.00612020부산광역시 해운대구 우동 1495번지 신세계백화점 센텀시티점(지하1층)<NA><NA>(주)해가원20110518174247I2018-08-31 23:59:59.0즉석판매제조가공업393952.264486187602.933161즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA><NA>
1815018151즉석판매제조가공업07_22_19_P32900003290000-107-1983-0019419830429<NA>3폐업2폐업20020316<NA><NA><NA>05116.50614852부산광역시 부산진구 양정동 39-2번지<NA><NA>매일상회19990712000000I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>