Overview

Dataset statistics

Number of variables48
Number of observations10000
Missing cells108399
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

Description2021-02-01
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 (99.1%)Imbalance
위생업태명 is highly imbalanced (98.8%)Imbalance
남성종사자수 is highly imbalanced (80.4%)Imbalance
여성종사자수 is highly imbalanced (80.3%)Imbalance
영업장주변구분명 is highly imbalanced (71.2%)Imbalance
등급구분명 is highly imbalanced (62.1%)Imbalance
급수시설구분명 is highly imbalanced (68.1%)Imbalance
공장판매직종업원수 is highly imbalanced (51.5%)Imbalance
공장생산직종업원수 is highly imbalanced (58.1%)Imbalance
보증액 is highly imbalanced (77.9%)Imbalance
월세액 is highly imbalanced (77.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2545 (25.4%) 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 4529 (45.3%) missing valuesMissing
소재지면적 has 4895 (48.9%) missing valuesMissing
소재지우편번호 has 214 (2.1%) missing valuesMissing
도로명전체주소 has 2720 (27.2%) missing valuesMissing
도로명우편번호 has 2776 (27.8%) missing valuesMissing
좌표정보(x) has 322 (3.2%) missing valuesMissing
좌표정보(y) has 322 (3.2%) 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 = -50.17609289)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 9401 (94.0%) zerosZeros

Reproduction

Analysis started2024-04-17 12:35:24.036857
Analysis finished2024-04-17 12:35:25.695258
Duration1.66 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%
Mean11214.879
Minimum1
Maximum22378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:25.754350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1115.85
Q15596.75
median11195.5
Q316827.25
95-th percentile21313.1
Maximum22378
Range22377
Interquartile range (IQR)11230.5

Descriptive statistics

Standard deviation6474.3354
Coefficient of variation (CV)0.57729876
Kurtosis-1.1990013
Mean11214.879
Median Absolute Deviation (MAD)5615.5
Skewness0.0038982141
Sum1.1214878 × 108
Variance41917019
MonotonicityNot monotonic
2024-04-17T21:35:25.870702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3882 1
 
< 0.1%
15259 1
 
< 0.1%
10435 1
 
< 0.1%
15388 1
 
< 0.1%
19805 1
 
< 0.1%
7570 1
 
< 0.1%
17203 1
 
< 0.1%
2904 1
 
< 0.1%
7046 1
 
< 0.1%
8005 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
7 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
17 1
< 0.1%
20 1
< 0.1%
21 1
< 0.1%
23 1
< 0.1%
24 1
< 0.1%
28 1
< 0.1%
ValueCountFrequency (%)
22378 1
< 0.1%
22374 1
< 0.1%
22372 1
< 0.1%
22371 1
< 0.1%
22369 1
< 0.1%
22368 1
< 0.1%
22364 1
< 0.1%
22363 1
< 0.1%
22362 1
< 0.1%
22360 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

2024-04-17T21:35:25.959923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:26.028530image/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

2024-04-17T21:35:26.099228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:26.167705image/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%
Mean3326471
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:26.244548image/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 deviation39613.294
Coefficient of variation (CV)0.011908504
Kurtosis-0.85114665
Mean3326471
Median Absolute Deviation (MAD)40000
Skewness0.15158649
Sum3.326471 × 1010
Variance1.5692131 × 109
MonotonicityNot monotonic
2024-04-17T21:35:26.350101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1958
19.6%
3290000 1539
15.4%
3300000 902
9.0%
3370000 724
 
7.2%
3380000 674
 
6.7%
3350000 544
 
5.4%
3390000 514
 
5.1%
3340000 491
 
4.9%
3320000 460
 
4.6%
3310000 451
 
4.5%
Other values (6) 1743
17.4%
ValueCountFrequency (%)
3250000 323
 
3.2%
3260000 205
 
2.1%
3270000 312
 
3.1%
3280000 354
 
3.5%
3290000 1539
15.4%
3300000 902
9.0%
3310000 451
 
4.5%
3320000 460
 
4.6%
3330000 1958
19.6%
3340000 491
 
4.9%
ValueCountFrequency (%)
3400000 445
 
4.5%
3390000 514
 
5.1%
3380000 674
 
6.7%
3370000 724
 
7.2%
3360000 104
 
1.0%
3350000 544
 
5.4%
3340000 491
 
4.9%
3330000 1958
19.6%
3320000 460
 
4.6%
3310000 451
 
4.5%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T21:35:26.509942image/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 row3310000-107-2014-00007
2nd row3340000-107-2020-00043
3rd row3310000-107-2003-00071
4th row3330000-107-1999-00539
5th row3370000-107-2007-00023
ValueCountFrequency (%)
3310000-107-2014-00007 1
 
< 0.1%
3290000-107-2010-00063 1
 
< 0.1%
3330000-107-2020-00241 1
 
< 0.1%
3260000-107-2004-00001 1
 
< 0.1%
3390000-107-2018-00127 1
 
< 0.1%
3310000-107-2018-00101 1
 
< 0.1%
3380000-107-2006-00001 1
 
< 0.1%
3370000-107-2019-00078 1
 
< 0.1%
3370000-107-2012-00001 1
 
< 0.1%
3290000-107-2014-00009 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T21:35:26.775704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 92174
41.9%
- 30000
 
13.6%
1 21985
 
10.0%
3 21860
 
9.9%
2 16696
 
7.6%
7 14051
 
6.4%
9 8214
 
3.7%
8 4443
 
2.0%
4 3823
 
1.7%
5 3577
 
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 92174
48.5%
1 21985
 
11.6%
3 21860
 
11.5%
2 16696
 
8.8%
7 14051
 
7.4%
9 8214
 
4.3%
8 4443
 
2.3%
4 3823
 
2.0%
5 3577
 
1.9%
6 3177
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92174
41.9%
- 30000
 
13.6%
1 21985
 
10.0%
3 21860
 
9.9%
2 16696
 
7.6%
7 14051
 
6.4%
9 8214
 
3.7%
8 4443
 
2.0%
4 3823
 
1.7%
5 3577
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92174
41.9%
- 30000
 
13.6%
1 21985
 
10.0%
3 21860
 
9.9%
2 16696
 
7.6%
7 14051
 
6.4%
9 8214
 
3.7%
8 4443
 
2.0%
4 3823
 
1.7%
5 3577
 
1.6%

인허가일자
Real number (ℝ)

Distinct4527
Distinct (%)45.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20104464
Minimum19640629
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:26.886621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19640629
5-th percentile19890120
Q120050321
median20150104
Q320190403
95-th percentile20200728
Maximum20201231
Range560602
Interquartile range (IQR)140082

Descriptive statistics

Standard deviation104047.67
Coefficient of variation (CV)0.0051753519
Kurtosis1.6857228
Mean20104464
Median Absolute Deviation (MAD)50122.5
Skewness-1.3665153
Sum2.0104464 × 1011
Variance1.0825919 × 1010
MonotonicityNot monotonic
2024-04-17T21:35:26.999086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190930 22
 
0.2%
20200310 17
 
0.2%
20200420 16
 
0.2%
20190702 16
 
0.2%
20200330 15
 
0.1%
20190207 14
 
0.1%
20200323 14
 
0.1%
19760331 14
 
0.1%
20190429 14
 
0.1%
20190305 14
 
0.1%
Other values (4517) 9844
98.4%
ValueCountFrequency (%)
19640629 1
< 0.1%
19680222 1
< 0.1%
19680316 1
< 0.1%
19680430 1
< 0.1%
19680827 1
< 0.1%
19680904 1
< 0.1%
19680930 1
< 0.1%
19681129 2
< 0.1%
19690113 2
< 0.1%
19690429 1
< 0.1%
ValueCountFrequency (%)
20201231 2
 
< 0.1%
20201230 4
< 0.1%
20201229 6
0.1%
20201228 9
0.1%
20201224 9
0.1%
20201223 7
0.1%
20201222 2
 
< 0.1%
20201221 8
0.1%
20201218 5
0.1%
20201217 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
7455 
1
2545 

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 7455
74.6%
1 2545
 
25.4%

Length

2024-04-17T21:35:27.094479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:27.164310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7455
74.6%
1 2545
 
25.4%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7455 
영업/정상
2545 

Length

Max length5
Median length2
Mean length2.7635
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7455
74.6%
영업/정상 2545
 
25.4%

Length

2024-04-17T21:35:27.243214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:27.318074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7455
74.6%
영업/정상 2545
 
25.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7455 
1
2545 

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 7455
74.6%
1 2545
 
25.4%

Length

2024-04-17T21:35:27.390205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:27.458030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7455
74.6%
1 2545
 
25.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7455 
영업
2545 

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 7455
74.6%
영업 2545
 
25.4%

Length

2024-04-17T21:35:27.538437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:27.605720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7455
74.6%
영업 2545
 
25.4%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct3422
Distinct (%)45.9%
Missing2545
Missing (%)25.4%
Infinite0
Infinite (%)0.0%
Mean20135464
Minimum10000101
Maximum20201230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:27.691132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000101
5-th percentile20020409
Q120090818
median20170106
Q320190615
95-th percentile20200731
Maximum20201230
Range10201129
Interquartile range (IQR)99797

Descriptive statistics

Standard deviation177288.78
Coefficient of variation (CV)0.0088048022
Kurtosis2865.3214
Mean20135464
Median Absolute Deviation (MAD)30309
Skewness-50.176093
Sum1.5010989 × 1011
Variance3.1431311 × 1010
MonotonicityNot monotonic
2024-04-17T21:35:27.797951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021011 24
 
0.2%
20100111 20
 
0.2%
20191016 16
 
0.2%
20180930 15
 
0.1%
20100208 14
 
0.1%
20201202 14
 
0.1%
20190421 14
 
0.1%
20200311 13
 
0.1%
20190331 13
 
0.1%
20200331 13
 
0.1%
Other values (3412) 7299
73.0%
(Missing) 2545
 
25.4%
ValueCountFrequency (%)
10000101 2
< 0.1%
19940120 1
< 0.1%
19940913 2
< 0.1%
19941018 1
< 0.1%
19941207 1
< 0.1%
19950110 1
< 0.1%
19950112 1
< 0.1%
19950626 1
< 0.1%
19950704 1
< 0.1%
19950724 1
< 0.1%
ValueCountFrequency (%)
20201230 1
 
< 0.1%
20201229 1
 
< 0.1%
20201228 2
< 0.1%
20201223 2
< 0.1%
20201221 1
 
< 0.1%
20201220 2
< 0.1%
20201218 1
 
< 0.1%
20201217 3
< 0.1%
20201216 4
< 0.1%
20201215 2
< 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 

Distinct3621
Distinct (%)66.2%
Missing4529
Missing (%)45.3%
Memory size156.2 KiB
2024-04-17T21:35:28.055000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.74575
Min length3

Characters and Unicode

Total characters58790
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

Unique3266 ?
Unique (%)59.7%

Sample

1st row051 6274085
2nd row051 6118590
3rd row051 5228429
4th row051 5008154
5th row051 523 3900
ValueCountFrequency (%)
051 4003
31.8%
055 268
 
2.1%
031 236
 
1.9%
070 160
 
1.3%
02 154
 
1.2%
831 136
 
1.1%
5711 89
 
0.7%
053 85
 
0.7%
343 57
 
0.5%
2528 55
 
0.4%
Other values (3858) 7337
58.3%
2024-04-17T21:35:28.421329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9852
16.8%
5 8867
15.1%
1 8032
13.7%
7290
12.4%
2 4550
7.7%
3 4085
6.9%
8 3739
 
6.4%
7 3643
 
6.2%
6 3384
 
5.8%
4 3150
 
5.4%
Other values (2) 2198
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51499
87.6%
Space Separator 7290
 
12.4%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9852
19.1%
5 8867
17.2%
1 8032
15.6%
2 4550
8.8%
3 4085
7.9%
8 3739
 
7.3%
7 3643
 
7.1%
6 3384
 
6.6%
4 3150
 
6.1%
9 2197
 
4.3%
Space Separator
ValueCountFrequency (%)
7290
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58790
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9852
16.8%
5 8867
15.1%
1 8032
13.7%
7290
12.4%
2 4550
7.7%
3 4085
6.9%
8 3739
 
6.4%
7 3643
 
6.2%
6 3384
 
5.8%
4 3150
 
5.4%
Other values (2) 2198
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58790
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9852
16.8%
5 8867
15.1%
1 8032
13.7%
7290
12.4%
2 4550
7.7%
3 4085
6.9%
8 3739
 
6.4%
7 3643
 
6.2%
6 3384
 
5.8%
4 3150
 
5.4%
Other values (2) 2198
 
3.7%

소재지면적
Text

MISSING 

Distinct2007
Distinct (%)39.3%
Missing4895
Missing (%)48.9%
Memory size156.2 KiB
2024-04-17T21:35:28.749052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.5833497
Min length3

Characters and Unicode

Total characters23398
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

Unique1333 ?
Unique (%)26.1%

Sample

1st row47.34
2nd row45.60
3rd row14.10
4th row7.50
5th row33.00
ValueCountFrequency (%)
00 258
 
5.1%
3.00 137
 
2.7%
6.00 126
 
2.5%
6.60 96
 
1.9%
4.00 77
 
1.5%
3.30 69
 
1.4%
2.00 62
 
1.2%
5.00 54
 
1.1%
9.90 47
 
0.9%
20.00 47
 
0.9%
Other values (1997) 4132
80.9%
2024-04-17T21:35:29.161352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5168
22.1%
. 5105
21.8%
1 2098
9.0%
2 2079
8.9%
3 1768
 
7.6%
6 1494
 
6.4%
5 1423
 
6.1%
4 1382
 
5.9%
8 1025
 
4.4%
9 941
 
4.0%
Other values (2) 915
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18292
78.2%
Other Punctuation 5106
 
21.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5168
28.3%
1 2098
11.5%
2 2079
11.4%
3 1768
 
9.7%
6 1494
 
8.2%
5 1423
 
7.8%
4 1382
 
7.6%
8 1025
 
5.6%
9 941
 
5.1%
7 914
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 5105
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 23398
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5168
22.1%
. 5105
21.8%
1 2098
9.0%
2 2079
8.9%
3 1768
 
7.6%
6 1494
 
6.4%
5 1423
 
6.1%
4 1382
 
5.9%
8 1025
 
4.4%
9 941
 
4.0%
Other values (2) 915
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23398
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5168
22.1%
. 5105
21.8%
1 2098
9.0%
2 2079
8.9%
3 1768
 
7.6%
6 1494
 
6.4%
5 1423
 
6.1%
4 1382
 
5.9%
8 1025
 
4.4%
9 941
 
4.0%
Other values (2) 915
 
3.9%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct716
Distinct (%)7.3%
Missing214
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean611366.21
Minimum600012
Maximum642829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:29.465007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600012
5-th percentile601803
Q1607835
median612040
Q3614814
95-th percentile617833
Maximum642829
Range42817
Interquartile range (IQR)6979

Descriptive statistics

Standard deviation4721.4545
Coefficient of variation (CV)0.0077227927
Kurtosis0.012564054
Mean611366.21
Median Absolute Deviation (MAD)2807
Skewness-0.54583445
Sum5.9828298 × 109
Variance22292133
MonotonicityNot monotonic
2024-04-17T21:35:29.576905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
612020 587
 
5.9%
612851 218
 
2.2%
600017 211
 
2.1%
613819 211
 
2.1%
611807 184
 
1.8%
614847 162
 
1.6%
612811 158
 
1.6%
614843 146
 
1.5%
611840 131
 
1.3%
607804 129
 
1.3%
Other values (706) 7649
76.5%
(Missing) 214
 
2.1%
ValueCountFrequency (%)
600012 2
 
< 0.1%
600017 211
2.1%
600025 1
 
< 0.1%
600041 3
 
< 0.1%
600043 1
 
< 0.1%
600044 4
 
< 0.1%
600045 2
 
< 0.1%
600046 38
 
0.4%
600051 1
 
< 0.1%
600061 3
 
< 0.1%
ValueCountFrequency (%)
642829 1
 
< 0.1%
621250 1
 
< 0.1%
619953 11
 
0.1%
619952 2
 
< 0.1%
619951 13
 
0.1%
619913 5
 
0.1%
619912 33
0.3%
619911 5
 
0.1%
619906 76
0.8%
619905 56
0.6%
Distinct5355
Distinct (%)53.9%
Missing66
Missing (%)0.7%
Memory size156.2 KiB
2024-04-17T21:35:29.777125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length51
Mean length25.759211
Min length16

Characters and Unicode

Total characters255892
Distinct characters451
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

Unique4630 ?
Unique (%)46.6%

Sample

1st row부산광역시 남구 감만동 33-166번지
2nd row부산광역시 사하구 다대동 120-19번지
3rd row부산광역시 남구 대연동 1394번지
4th row부산광역시 해운대구 반여동 1089-3번지
5th row부산광역시 연제구 거제동 1208번지
ValueCountFrequency (%)
부산광역시 9932
 
20.8%
해운대구 1955
 
4.1%
부산진구 1497
 
3.1%
동래구 891
 
1.9%
우동 800
 
1.7%
연제구 724
 
1.5%
수영구 674
 
1.4%
부전동 550
 
1.2%
금정구 534
 
1.1%
사상구 514
 
1.1%
Other values (5771) 29628
62.1%
2024-04-17T21:35:30.101030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37783
 
14.8%
12895
 
5.0%
12485
 
4.9%
11431
 
4.5%
10600
 
4.1%
10341
 
4.0%
10076
 
3.9%
9941
 
3.9%
1 9835
 
3.8%
9811
 
3.8%
Other values (441) 120694
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162797
63.6%
Decimal Number 45153
 
17.6%
Space Separator 37783
 
14.8%
Dash Punctuation 7586
 
3.0%
Uppercase Letter 1213
 
0.5%
Open Punctuation 572
 
0.2%
Close Punctuation 568
 
0.2%
Other Punctuation 177
 
0.1%
Lowercase Letter 36
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12895
 
7.9%
12485
 
7.7%
11431
 
7.0%
10600
 
6.5%
10341
 
6.4%
10076
 
6.2%
9941
 
6.1%
9811
 
6.0%
9066
 
5.6%
2825
 
1.7%
Other values (392) 63326
38.9%
Uppercase Letter
ValueCountFrequency (%)
B 253
20.9%
S 248
20.4%
G 182
15.0%
T 169
13.9%
E 124
10.2%
K 62
 
5.1%
A 41
 
3.4%
Y 30
 
2.5%
H 29
 
2.4%
U 29
 
2.4%
Other values (10) 46
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 9835
21.8%
2 6196
13.7%
5 5016
11.1%
3 4214
9.3%
4 4094
9.1%
0 3613
 
8.0%
7 3561
 
7.9%
6 3158
 
7.0%
9 2742
 
6.1%
8 2724
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
s 13
36.1%
g 13
36.1%
e 5
 
13.9%
a 2
 
5.6%
b 1
 
2.8%
z 1
 
2.8%
l 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 133
75.1%
. 15
 
8.5%
@ 15
 
8.5%
· 10
 
5.6%
/ 3
 
1.7%
& 1
 
0.6%
Space Separator
ValueCountFrequency (%)
37783
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7586
100.0%
Open Punctuation
ValueCountFrequency (%)
( 572
100.0%
Close Punctuation
ValueCountFrequency (%)
) 568
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162796
63.6%
Common 91845
35.9%
Latin 1250
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12895
 
7.9%
12485
 
7.7%
11431
 
7.0%
10600
 
6.5%
10341
 
6.4%
10076
 
6.2%
9941
 
6.1%
9811
 
6.0%
9066
 
5.6%
2825
 
1.7%
Other values (391) 63325
38.9%
Latin
ValueCountFrequency (%)
B 253
20.2%
S 248
19.8%
G 182
14.6%
T 169
13.5%
E 124
9.9%
K 62
 
5.0%
A 41
 
3.3%
Y 30
 
2.4%
H 29
 
2.3%
U 29
 
2.3%
Other values (18) 83
 
6.6%
Common
ValueCountFrequency (%)
37783
41.1%
1 9835
 
10.7%
- 7586
 
8.3%
2 6196
 
6.7%
5 5016
 
5.5%
3 4214
 
4.6%
4 4094
 
4.5%
0 3613
 
3.9%
7 3561
 
3.9%
6 3158
 
3.4%
Other values (11) 6789
 
7.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162796
63.6%
ASCII 93084
36.4%
None 10
 
< 0.1%
Number Forms 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37783
40.6%
1 9835
 
10.6%
- 7586
 
8.1%
2 6196
 
6.7%
5 5016
 
5.4%
3 4214
 
4.5%
4 4094
 
4.4%
0 3613
 
3.9%
7 3561
 
3.8%
6 3158
 
3.4%
Other values (37) 8028
 
8.6%
Hangul
ValueCountFrequency (%)
12895
 
7.9%
12485
 
7.7%
11431
 
7.0%
10600
 
6.5%
10341
 
6.4%
10076
 
6.2%
9941
 
6.1%
9811
 
6.0%
9066
 
5.6%
2825
 
1.7%
Other values (391) 63325
38.9%
None
ValueCountFrequency (%)
· 10
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct4242
Distinct (%)58.3%
Missing2720
Missing (%)27.2%
Memory size156.2 KiB
2024-04-17T21:35:30.347642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length56
Mean length32.839973
Min length19

Characters and Unicode

Total characters239075
Distinct characters478
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

Unique3692 ?
Unique (%)50.7%

Sample

1st row부산광역시 남구 석포로 43 (감만동)
2nd row부산광역시 사하구 다송로 58 (다대동)
3rd row부산광역시 사하구 다대로 533, 3층 (다대동)
4th row부산광역시 금정구 서동시장뒷길 7, 1층 (서동)
5th row부산광역시 북구 화명대로 47, 롯데마트 (화명동)
ValueCountFrequency (%)
부산광역시 7278
 
15.9%
1층 1477
 
3.2%
해운대구 1401
 
3.1%
부산진구 910
 
2.0%
지하1층 740
 
1.6%
동래구 636
 
1.4%
우동 631
 
1.4%
연제구 528
 
1.2%
수영구 475
 
1.0%
사상구 456
 
1.0%
Other values (3910) 31374
68.3%
2024-04-17T21:35:30.706143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38652
 
16.2%
9417
 
3.9%
9340
 
3.9%
9145
 
3.8%
8265
 
3.5%
1 8210
 
3.4%
7832
 
3.3%
7361
 
3.1%
7282
 
3.0%
7244
 
3.0%
Other values (468) 126327
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148734
62.2%
Space Separator 38652
 
16.2%
Decimal Number 29461
 
12.3%
Open Punctuation 7209
 
3.0%
Close Punctuation 7206
 
3.0%
Other Punctuation 6055
 
2.5%
Uppercase Letter 948
 
0.4%
Dash Punctuation 687
 
0.3%
Lowercase Letter 111
 
< 0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9417
 
6.3%
9340
 
6.3%
9145
 
6.1%
8265
 
5.6%
7832
 
5.3%
7361
 
4.9%
7282
 
4.9%
7244
 
4.9%
5031
 
3.4%
3010
 
2.0%
Other values (414) 74807
50.3%
Uppercase Letter
ValueCountFrequency (%)
S 245
25.8%
G 173
18.2%
B 142
15.0%
E 126
13.3%
K 51
 
5.4%
A 45
 
4.7%
C 37
 
3.9%
Y 25
 
2.6%
H 25
 
2.6%
U 24
 
2.5%
Other values (10) 55
 
5.8%
Lowercase Letter
ValueCountFrequency (%)
s 42
37.8%
g 39
35.1%
c 8
 
7.2%
n 8
 
7.2%
e 5
 
4.5%
b 3
 
2.7%
a 2
 
1.8%
i 1
 
0.9%
h 1
 
0.9%
z 1
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 8210
27.9%
2 4241
14.4%
3 2887
 
9.8%
5 2793
 
9.5%
7 2477
 
8.4%
4 2257
 
7.7%
0 1694
 
5.7%
9 1673
 
5.7%
6 1622
 
5.5%
8 1607
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 6031
99.6%
@ 10
 
0.2%
· 10
 
0.2%
. 2
 
< 0.1%
& 1
 
< 0.1%
/ 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 7208
> 99.9%
{ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
38652
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7206
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 687
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 148734
62.2%
Common 89281
37.3%
Latin 1060
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9417
 
6.3%
9340
 
6.3%
9145
 
6.1%
8265
 
5.6%
7832
 
5.3%
7361
 
4.9%
7282
 
4.9%
7244
 
4.9%
5031
 
3.4%
3010
 
2.0%
Other values (414) 74807
50.3%
Latin
ValueCountFrequency (%)
S 245
23.1%
G 173
16.3%
B 142
13.4%
E 126
11.9%
K 51
 
4.8%
A 45
 
4.2%
s 42
 
4.0%
g 39
 
3.7%
C 37
 
3.5%
Y 25
 
2.4%
Other values (22) 135
12.7%
Common
ValueCountFrequency (%)
38652
43.3%
1 8210
 
9.2%
( 7208
 
8.1%
) 7206
 
8.1%
, 6031
 
6.8%
2 4241
 
4.8%
3 2887
 
3.2%
5 2793
 
3.1%
7 2477
 
2.8%
4 2257
 
2.5%
Other values (12) 7319
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148734
62.2%
ASCII 90330
37.8%
None 10
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38652
42.8%
1 8210
 
9.1%
( 7208
 
8.0%
) 7206
 
8.0%
, 6031
 
6.7%
2 4241
 
4.7%
3 2887
 
3.2%
5 2793
 
3.1%
7 2477
 
2.7%
4 2257
 
2.5%
Other values (42) 8368
 
9.3%
Hangul
ValueCountFrequency (%)
9417
 
6.3%
9340
 
6.3%
9145
 
6.1%
8265
 
5.6%
7832
 
5.3%
7361
 
4.9%
7282
 
4.9%
7244
 
4.9%
5031
 
3.4%
3010
 
2.0%
Other values (414) 74807
50.3%
None
ValueCountFrequency (%)
· 10
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1114
Distinct (%)15.4%
Missing2776
Missing (%)27.8%
Infinite0
Infinite (%)0.0%
Mean47743.918
Minimum46002
Maximum51498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:30.823224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46084
Q147126
median47851
Q348304
95-th percentile49323
Maximum51498
Range5496
Interquartile range (IQR)1178

Descriptive statistics

Standard deviation913.36097
Coefficient of variation (CV)0.019130415
Kurtosis-0.62668422
Mean47743.918
Median Absolute Deviation (MAD)594
Skewness-0.062677151
Sum3.4490206 × 108
Variance834228.27
MonotonicityNot monotonic
2024-04-17T21:35:30.918926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48058 428
 
4.3%
48944 206
 
2.1%
48096 188
 
1.9%
48313 169
 
1.7%
47285 159
 
1.6%
47500 135
 
1.4%
46970 127
 
1.3%
46233 118
 
1.2%
47727 98
 
1.0%
47604 97
 
1.0%
Other values (1104) 5499
55.0%
(Missing) 2776
27.8%
ValueCountFrequency (%)
46002 1
 
< 0.1%
46003 2
 
< 0.1%
46004 4
 
< 0.1%
46005 1
 
< 0.1%
46006 1
 
< 0.1%
46007 2
 
< 0.1%
46008 11
 
0.1%
46010 4
 
< 0.1%
46012 3
 
< 0.1%
46015 45
0.4%
ValueCountFrequency (%)
51498 1
 
< 0.1%
50981 1
 
< 0.1%
49525 1
 
< 0.1%
49524 1
 
< 0.1%
49523 3
 
< 0.1%
49522 1
 
< 0.1%
49520 3
 
< 0.1%
49519 46
0.5%
49518 3
 
< 0.1%
49516 1
 
< 0.1%
Distinct5331
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T21:35:31.150066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length25
Mean length5.8881
Min length1

Characters and Unicode

Total characters58881
Distinct characters836
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4365 ?
Unique (%)43.6%

Sample

1st row우정건강원
2nd row(주)현승에프앤디
3rd row건강랜드
4th row대동상회
5th row동산푸드
ValueCountFrequency (%)
주식회사 213
 
1.9%
현승유통 120
 
1.1%
현재상사 111
 
1.0%
주)정성 102
 
0.9%
주)부산축산 102
 
0.9%
주경식품 100
 
0.9%
주)미트벨리 91
 
0.8%
주)모두랑식품 85
 
0.8%
오에스푸드 83
 
0.7%
수지int's 71
 
0.6%
Other values (5561) 10098
90.4%
2024-04-17T21:35:31.488362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2290
 
3.9%
) 2078
 
3.5%
( 2034
 
3.5%
1564
 
2.7%
1471
 
2.5%
1176
 
2.0%
1129
 
1.9%
934
 
1.6%
884
 
1.5%
813
 
1.4%
Other values (826) 44508
75.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52202
88.7%
Close Punctuation 2078
 
3.5%
Open Punctuation 2034
 
3.5%
Space Separator 1176
 
2.0%
Uppercase Letter 663
 
1.1%
Lowercase Letter 387
 
0.7%
Decimal Number 165
 
0.3%
Other Punctuation 154
 
0.3%
Dash Punctuation 14
 
< 0.1%
Modifier Symbol 3
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2290
 
4.4%
1564
 
3.0%
1471
 
2.8%
1129
 
2.2%
934
 
1.8%
884
 
1.7%
813
 
1.6%
812
 
1.6%
789
 
1.5%
725
 
1.4%
Other values (748) 40791
78.1%
Lowercase Letter
ValueCountFrequency (%)
e 62
16.0%
o 42
10.9%
a 36
 
9.3%
r 31
 
8.0%
l 23
 
5.9%
s 21
 
5.4%
t 20
 
5.2%
n 18
 
4.7%
u 16
 
4.1%
i 14
 
3.6%
Other values (16) 104
26.9%
Uppercase Letter
ValueCountFrequency (%)
N 100
15.1%
T 97
14.6%
S 95
14.3%
I 82
12.4%
F 35
 
5.3%
E 28
 
4.2%
A 26
 
3.9%
O 24
 
3.6%
B 23
 
3.5%
C 23
 
3.5%
Other values (15) 130
19.6%
Decimal Number
ValueCountFrequency (%)
1 38
23.0%
2 34
20.6%
0 26
15.8%
5 15
 
9.1%
3 13
 
7.9%
6 10
 
6.1%
7 10
 
6.1%
8 9
 
5.5%
4 6
 
3.6%
9 4
 
2.4%
Other Punctuation
ValueCountFrequency (%)
' 78
50.6%
. 25
 
16.2%
& 23
 
14.9%
, 16
 
10.4%
/ 4
 
2.6%
; 2
 
1.3%
: 2
 
1.3%
! 2
 
1.3%
· 2
 
1.3%
Close Punctuation
ValueCountFrequency (%)
) 2078
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2034
100.0%
Space Separator
ValueCountFrequency (%)
1176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52200
88.7%
Common 5625
 
9.6%
Latin 1051
 
1.8%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2290
 
4.4%
1564
 
3.0%
1471
 
2.8%
1129
 
2.2%
934
 
1.8%
884
 
1.7%
813
 
1.6%
812
 
1.6%
789
 
1.5%
725
 
1.4%
Other values (744) 40789
78.1%
Latin
ValueCountFrequency (%)
N 100
 
9.5%
T 97
 
9.2%
S 95
 
9.0%
I 82
 
7.8%
e 62
 
5.9%
o 42
 
4.0%
a 36
 
3.4%
F 35
 
3.3%
r 31
 
2.9%
E 28
 
2.7%
Other values (42) 443
42.2%
Common
ValueCountFrequency (%)
) 2078
36.9%
( 2034
36.2%
1176
20.9%
' 78
 
1.4%
1 38
 
0.7%
2 34
 
0.6%
0 26
 
0.5%
. 25
 
0.4%
& 23
 
0.4%
, 16
 
0.3%
Other values (15) 97
 
1.7%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52196
88.6%
ASCII 6673
 
11.3%
None 5
 
< 0.1%
CJK 5
 
< 0.1%
Number Forms 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2290
 
4.4%
1564
 
3.0%
1471
 
2.8%
1129
 
2.2%
934
 
1.8%
884
 
1.7%
813
 
1.6%
812
 
1.6%
789
 
1.5%
725
 
1.4%
Other values (742) 40785
78.1%
ASCII
ValueCountFrequency (%)
) 2078
31.1%
( 2034
30.5%
1176
17.6%
N 100
 
1.5%
T 97
 
1.5%
S 95
 
1.4%
I 82
 
1.2%
' 78
 
1.2%
e 62
 
0.9%
o 42
 
0.6%
Other values (65) 829
 
12.4%
None
ValueCountFrequency (%)
3
60.0%
· 2
40.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct7662
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0141651 × 1013
Minimum1.9990218 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:31.601800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile2.0020612 × 1013
Q12.0100129 × 1013
median2.0170706 × 1013
Q32.0190725 × 1013
95-th percentile2.0200914 × 1013
Maximum2.0201231 × 1013
Range2.1101316 × 1011
Interquartile range (IQR)9.0596183 × 1010

Descriptive statistics

Standard deviation6.1859686 × 1010
Coefficient of variation (CV)0.0030712322
Kurtosis-0.59567812
Mean2.0141651 × 1013
Median Absolute Deviation (MAD)2.9814 × 1010
Skewness-0.8714088
Sum2.0141651 × 1017
Variance3.8266207 × 1021
MonotonicityNot monotonic
2024-04-17T21:35:31.702028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020612000000 64
 
0.6%
20020305000000 51
 
0.5%
20010728000000 43
 
0.4%
20020621000000 39
 
0.4%
20020611000000 32
 
0.3%
20020821000000 31
 
0.3%
20020828000000 30
 
0.3%
20020724000000 30
 
0.3%
20020723000000 28
 
0.3%
20020708000000 27
 
0.3%
Other values (7652) 9625
96.2%
ValueCountFrequency (%)
19990218000000 1
 
< 0.1%
19990223000000 1
 
< 0.1%
19990304000000 9
0.1%
19990305000000 3
 
< 0.1%
19990318000000 18
0.2%
19990319000000 11
0.1%
19990322000000 4
 
< 0.1%
19990323000000 6
 
0.1%
19990324000000 4
 
< 0.1%
19990326000000 4
 
< 0.1%
ValueCountFrequency (%)
20201231163455 1
< 0.1%
20201231152310 1
< 0.1%
20201231143517 1
< 0.1%
20201231105630 1
< 0.1%
20201231101451 1
< 0.1%
20201230172256 1
< 0.1%
20201230154324 1
< 0.1%
20201230150216 1
< 0.1%
20201230144532 1
< 0.1%
20201230132426 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6490 
U
3510 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6490
64.9%
U 3510
35.1%

Length

2024-04-17T21:35:31.809547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:31.896584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6490
64.9%
u 3510
35.1%
Distinct943
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-02 02:40:00
2024-04-17T21:35:31.997911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T21:35:32.103423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9981 
기타
 
16
<NA>
 
1
단란주점
 
1
한식
 
1

Length

Max length9
Median length9
Mean length8.9871
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9981
99.8%
기타 16
 
0.2%
<NA> 1
 
< 0.1%
단란주점 1
 
< 0.1%
한식 1
 
< 0.1%

Length

2024-04-17T21:35:32.216172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:32.296195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9981
99.8%
기타 16
 
0.2%
na 1
 
< 0.1%
단란주점 1
 
< 0.1%
한식 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3562
Distinct (%)36.8%
Missing322
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean389218.97
Minimum353660.89
Maximum407564.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:32.385674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum353660.89
5-th percentile380225.64
Q1385839.76
median389097.8
Q3392725.82
95-th percentile398196.18
Maximum407564.77
Range53903.885
Interquartile range (IQR)6886.0605

Descriptive statistics

Standard deviation5505.7694
Coefficient of variation (CV)0.014145686
Kurtosis0.56309226
Mean389218.97
Median Absolute Deviation (MAD)3506.9863
Skewness-0.069995018
Sum3.7668612 × 109
Variance30313497
MonotonicityNot monotonic
2024-04-17T21:35:32.522622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393952.264486105 319
 
3.2%
387271.299492377 285
 
2.9%
397397.83276594 216
 
2.2%
392321.102334852 199
 
2.0%
385590.814676765 194
 
1.9%
387539.767677801 156
 
1.6%
387686.194940483 152
 
1.5%
389097.800933845 137
 
1.4%
390208.09260128 132
 
1.3%
394083.501537578 131
 
1.3%
Other values (3552) 7757
77.6%
(Missing) 322
 
3.2%
ValueCountFrequency (%)
353660.889782036 1
 
< 0.1%
364626.145566093 1
 
< 0.1%
366820.787750249 1
 
< 0.1%
366829.531355754 4
< 0.1%
367041.984452276 1
 
< 0.1%
367088.901392071 1
 
< 0.1%
367169.234957368 1
 
< 0.1%
367304.900921148 1
 
< 0.1%
367451.087635496 8
0.1%
370622.73282019 1
 
< 0.1%
ValueCountFrequency (%)
407564.774795629 1
 
< 0.1%
407418.648415535 1
 
< 0.1%
407245.567193252 1
 
< 0.1%
407121.882187494 1
 
< 0.1%
407036.696092095 3
< 0.1%
407018.507643148 1
 
< 0.1%
407015.247908441 1
 
< 0.1%
406950.03175562 1
 
< 0.1%
406200.972892162 1
 
< 0.1%
405709.608315206 1
 
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct3565
Distinct (%)36.8%
Missing322
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean187555.76
Minimum173914.72
Maximum211459
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:32.654299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173914.72
5-th percentile178805.75
Q1184512.16
median187593.03
Q3190969.24
95-th percentile196375.47
Maximum211459
Range37544.284
Interquartile range (IQR)6457.0781

Descriptive statistics

Standard deviation5392.5326
Coefficient of variation (CV)0.028751624
Kurtosis0.95172773
Mean187555.76
Median Absolute Deviation (MAD)3190.0602
Skewness0.35828522
Sum1.8151646 × 109
Variance29079408
MonotonicityNot monotonic
2024-04-17T21:35:32.758752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187602.933160728 319
 
3.2%
186099.137533193 285
 
2.9%
187354.835259309 216
 
2.2%
184041.758684038 199
 
2.0%
179553.867031936 194
 
1.9%
184402.96650913 156
 
1.6%
189911.430545728 152
 
1.5%
192260.811648263 137
 
1.4%
196546.356333373 132
 
1.3%
187707.586117775 131
 
1.3%
Other values (3555) 7757
77.6%
(Missing) 322
 
3.2%
ValueCountFrequency (%)
173914.718015169 1
< 0.1%
173961.914773076 1
< 0.1%
174097.616386311 1
< 0.1%
174156.617297535 1
< 0.1%
174289.976688419 1
< 0.1%
174422.480246459 1
< 0.1%
174526.100850246 1
< 0.1%
174637.037992709 1
< 0.1%
174638.869997904 2
< 0.1%
174664.861404161 1
< 0.1%
ValueCountFrequency (%)
211459.001777975 1
< 0.1%
210945.104382171 2
< 0.1%
210458.376643536 1
< 0.1%
210004.830136767 1
< 0.1%
207739.619868549 1
< 0.1%
207716.999117547 1
< 0.1%
206803.94845946 1
< 0.1%
206788.899936301 1
< 0.1%
206690.833564719 1
< 0.1%
206512.517255249 2
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9976 
기타
 
16
<NA>
 
6
단란주점
 
1
한식
 
1

Length

Max length9
Median length9
Mean length8.9846
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9976
99.8%
기타 16
 
0.2%
<NA> 6
 
0.1%
단란주점 1
 
< 0.1%
한식 1
 
< 0.1%

Length

2024-04-17T21:35:32.891383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:32.970906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9976
99.8%
기타 16
 
0.2%
na 6
 
0.1%
단란주점 1
 
< 0.1%
한식 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9270 
0
 
708
1
 
20
2
 
2

Length

Max length4
Median length4
Mean length3.781
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> 9270
92.7%
0 708
 
7.1%
1 20
 
0.2%
2 2
 
< 0.1%

Length

2024-04-17T21:35:33.055416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:33.129545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9270
92.7%
0 708
 
7.1%
1 20
 
0.2%
2 2
 
< 0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9270 
0
 
704
1
 
25
2
 
1

Length

Max length4
Median length4
Mean length3.781
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> 9270
92.7%
0 704
 
7.0%
1 25
 
0.2%
2 1
 
< 0.1%

Length

2024-04-17T21:35:33.207401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:33.290828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9270
92.7%
0 704
 
7.0%
1 25
 
0.2%
2 1
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8207 
기타
1688 
주택가주변
 
86
아파트지역
 
14
유흥업소밀집지역
 
4

Length

Max length8
Median length4
Mean length3.6743
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8207
82.1%
기타 1688
 
16.9%
주택가주변 86
 
0.9%
아파트지역 14
 
0.1%
유흥업소밀집지역 4
 
< 0.1%
결혼예식장주변 1
 
< 0.1%

Length

2024-04-17T21:35:33.373938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:33.451411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8207
82.1%
기타 1688
 
16.9%
주택가주변 86
 
0.9%
아파트지역 14
 
0.1%
유흥업소밀집지역 4
 
< 0.1%
결혼예식장주변 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8207 
기타
1633 
자율
 
159
 
1

Length

Max length4
Median length4
Mean length3.6413
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8207
82.1%
기타 1633
 
16.3%
자율 159
 
1.6%
1
 
< 0.1%

Length

2024-04-17T21:35:33.538962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:33.614413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8207
82.1%
기타 1633
 
16.3%
자율 159
 
1.6%
1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8417 
상수도전용
1576 
지하수전용
 
5
간이상수도
 
2

Length

Max length5
Median length4
Mean length4.1583
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> 8417
84.2%
상수도전용 1576
 
15.8%
지하수전용 5
 
0.1%
간이상수도 2
 
< 0.1%

Length

2024-04-17T21:35:33.695628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:33.790903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8417
84.2%
상수도전용 1576
 
15.8%
지하수전용 5
 
< 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>
6473 
0
3523 
1
 
4

Length

Max length4
Median length4
Mean length2.9419
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6473
64.7%
0 3523
35.2%
1 4
 
< 0.1%

Length

2024-04-17T21:35:33.891375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:33.963849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6473
64.7%
0 3523
35.2%
1 4
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6473 
0
3527 

Length

Max length4
Median length4
Mean length2.9419
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6473
64.7%
0 3527
35.3%

Length

2024-04-17T21:35:34.044242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:34.116010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6473
64.7%
0 3527
35.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6469 
0
3491 
1
 
37
2
 
3

Length

Max length4
Median length4
Mean length2.9407
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6469
64.7%
0 3491
34.9%
1 37
 
0.4%
2 3
 
< 0.1%

Length

2024-04-17T21:35:34.192796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:34.277626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6469
64.7%
0 3491
34.9%
1 37
 
0.4%
2 3
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6468 
0
3489 
1
 
41
2
 
1
10
 
1

Length

Max length4
Median length4
Mean length2.9405
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 6468
64.7%
0 3489
34.9%
1 41
 
0.4%
2 1
 
< 0.1%
10 1
 
< 0.1%

Length

2024-04-17T21:35:34.366861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:34.447134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6468
64.7%
0 3489
34.9%
1 41
 
0.4%
2 1
 
< 0.1%
10 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7668 
자가
1438 
임대
894 

Length

Max length4
Median length4
Mean length3.5336
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7668
76.7%
자가 1438
 
14.4%
임대 894
 
8.9%

Length

2024-04-17T21:35:34.533059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:34.608703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7668
76.7%
자가 1438
 
14.4%
임대 894
 
8.9%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9346 
0
 
653
300
 
1

Length

Max length4
Median length4
Mean length3.804
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9346
93.5%
0 653
 
6.5%
300 1
 
< 0.1%

Length

2024-04-17T21:35:34.688888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:34.776032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9346
93.5%
0 653
 
6.5%
300 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9346 
0
 
653
30
 
1

Length

Max length4
Median length4
Mean length3.8039
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9346
93.5%
0 653
 
6.5%
30 1
 
< 0.1%

Length

2024-04-17T21:35:35.108530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:35:35.188641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9346
93.5%
0 653
 
6.5%
30 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size97.7 KiB
False
9995 
(Missing)
 
5
ValueCountFrequency (%)
False 9995
> 99.9%
(Missing) 5
 
0.1%
2024-04-17T21:35:35.258843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct394
Distinct (%)3.9%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.1898809
Minimum0
Maximum281
Zeros9401
Zeros (%)94.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:35:35.332445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.3
Maximum281
Range281
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.8253213
Coefficient of variation (CV)6.5765583
Kurtosis288.77775
Mean1.1898809
Median Absolute Deviation (MAD)0
Skewness13.4253
Sum11892.86
Variance61.235654
MonotonicityNot monotonic
2024-04-17T21:35:35.428961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9401
94.0%
3.3 25
 
0.2%
2.0 17
 
0.2%
9.9 13
 
0.1%
3.0 12
 
0.1%
19.8 12
 
0.1%
4.0 11
 
0.1%
6.6 10
 
0.1%
6.0 7
 
0.1%
20.0 7
 
0.1%
Other values (384) 480
 
4.8%
ValueCountFrequency (%)
0.0 9401
94.0%
0.4 1
 
< 0.1%
0.49 1
 
< 0.1%
0.6 1
 
< 0.1%
0.69 1
 
< 0.1%
0.8 1
 
< 0.1%
0.81 1
 
< 0.1%
0.84 1
 
< 0.1%
1.0 3
 
< 0.1%
1.07 1
 
< 0.1%
ValueCountFrequency (%)
281.0 1
< 0.1%
191.91 1
< 0.1%
165.0 1
< 0.1%
144.6 1
< 0.1%
135.54 1
< 0.1%
133.03 1
< 0.1%
122.0 1
< 0.1%
120.15 1
< 0.1%
108.4 1
< 0.1%
93.0 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
38813882즉석판매제조가공업07_22_19_P33100003310000-107-2014-0000720140616<NA>1영업/정상1영업<NA><NA><NA><NA>051 627408547.34608800부산광역시 남구 감만동 33-166번지부산광역시 남구 석포로 43 (감만동)48491우정건강원20190108115101U2019-01-10 02:40:00.0즉석판매제조가공업390055.055361182454.897514즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1014710148즉석판매제조가공업07_22_19_P33400003340000-107-2020-0004320200306<NA>3폐업2폐업20200405<NA><NA><NA><NA><NA>604822부산광역시 사하구 다대동 120-19번지부산광역시 사하구 다송로 58 (다대동)49519(주)현승에프앤디20200406041509U2020-04-08 02:40:00.0즉석판매제조가공업380816.783733175515.467302즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
2060320604즉석판매제조가공업07_22_19_P33100003310000-107-2003-0007120031117<NA>3폐업2폐업20050331<NA><NA><NA>051 611859045.60608808부산광역시 남구 대연동 1394번지<NA><NA>건강랜드20031117000000I2018-08-31 23:59:59.0즉석판매제조가공업390318.905203183942.872069즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0001임대<NA><NA>N0.0<NA><NA><NA><NA>
1228312284즉석판매제조가공업07_22_19_P33300003330000-107-1999-0053919990914<NA>3폐업2폐업20100322<NA><NA><NA>051 522842914.10612859부산광역시 해운대구 반여동 1089-3번지<NA><NA>대동상회20020622000000I2018-08-31 23:59:59.0즉석판매제조가공업392890.628994192034.50918즉석판매제조가공업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1635416355즉석판매제조가공업07_22_19_P33700003370000-107-2007-0002320070503<NA>3폐업2폐업20070514<NA><NA><NA>051 50081547.50611807부산광역시 연제구 거제동 1208번지<NA><NA>동산푸드20070503000000I2018-08-31 23:59:59.0즉석판매제조가공업387686.19494189911.430546즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA><NA>
81108111즉석판매제조가공업07_22_19_P33400003340000-107-2019-0018820190917<NA>3폐업2폐업20190925<NA><NA><NA><NA><NA>604823부산광역시 사하구 다대동 1151번지부산광역시 사하구 다대로 533, 3층 (다대동)49523삼부자20190926041525U2019-09-28 02:40:00.0즉석판매제조가공업379842.530652175060.158158즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
49844985즉석판매제조가공업07_22_19_P33500003350000-107-2014-0002520141016<NA>1영업/정상1영업<NA><NA><NA><NA>051 523 390033.00609848부산광역시 금정구 서동 194-23부산광역시 금정구 서동시장뒷길 7, 1층 (서동)46320미로닭발족발20201221130813U2020-12-23 02:40:00.0<NA>391446.587522192703.27779<NA><NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1557315574즉석판매제조가공업07_22_19_P34000003400000-107-2003-0001720031022<NA>3폐업2폐업20040803<NA><NA><NA><NA><NA>619903부산광역시 기장군 기장읍 대라리 57번지<NA><NA>평화식품20031022000000I2018-08-31 23:59:59.0즉석판매제조가공업401671.55937196027.51628즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA><NA>
1408714088즉석판매제조가공업07_22_19_P33100003310000-107-2008-0001320080416<NA>3폐업2폐업20080422<NA><NA><NA>051 6122111<NA>608833부산광역시 남구 용호동 409-16번지 6통4반<NA><NA>도원왕족발20080416141817I2018-08-31 23:59:59.0즉석판매제조가공업392184.487558182043.945269즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
57935794즉석판매제조가공업07_22_19_P33200003320000-107-2018-0011620180709<NA>3폐업2폐업20180801<NA><NA><NA><NA><NA>616744부산광역시 북구 화명동 2273번지 롯데마트부산광역시 북구 화명대로 47, 롯데마트 (화명동)46525누리농특산20180802041526I2018-08-31 23:59:59.0즉석판매제조가공업383175.025397194733.012499즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
20602061즉석판매제조가공업07_22_19_P32600003260000-107-2009-0000820091030<NA>1영업/정상1영업<NA><NA><NA><NA>051 2530384<NA>602011부산광역시 서구 충무동1가 32-29번지부산광역시 서구 새벽시장길 38-1 (충무동1가)49254광재상회20171207151232I2018-08-31 23:59:59.0즉석판매제조가공업384544.322719179166.525552즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
35703571즉석판매제조가공업07_22_19_P33200003320000-107-2010-0004520100816<NA>1영업/정상1영업<NA><NA><NA><NA>051 506 203016.80616846부산광역시 북구 화명동 962-11번지 종합상가 A동부산광역시 북구 금곡대로 189-1, A동 (화명동, 종합상가)46541떡에담은정20131219163416I2018-08-31 23:59:59.0즉석판매제조가공업382921.907625193699.556439즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
57165717즉석판매제조가공업07_22_19_P32800003280000-107-1982-0015119820703<NA>3폐업2폐업20011226<NA><NA><NA>051<NA>606051부산광역시 영도구 신선동1가 산 0-0번지 개량지구 2부럭 6놋트<NA><NA>경북참기름20020611000000I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1789517896즉석판매제조가공업07_22_19_P33700003370000-107-2009-0004720090922<NA>3폐업2폐업20091016<NA><NA><NA>051 500 8154<NA>611807부산광역시 연제구 거제동 1208번지 홈플러스내<NA><NA>피자클럽클래식20090922135221I2018-08-31 23:59:59.0즉석판매제조가공업387686.19494189911.430546즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1761817619즉석판매제조가공업07_22_19_P33300003330000-107-2007-0009520071011<NA>3폐업2폐업20080703<NA><NA><NA>051 702 7455<NA>612852부산광역시 해운대구 좌동 1278-1번지<NA><NA>고향마을 반찬집20071011100944I2018-08-31 23:59:59.0즉석판매제조가공업397521.55385188196.239322즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
73997400즉석판매제조가공업07_22_19_P34000003400000-107-2019-0006420190501<NA>3폐업2폐업20190531<NA><NA><NA><NA><NA>619902부산광역시 기장군 기장읍 당사리 524번지 롯데몰 동부산점부산광역시 기장군 기장읍 기장해안로 147, 롯데몰 동부산점 2층46084꽃피는솜사탕20190601041509U2019-06-04 02:40:00.0즉석판매제조가공업401473.933606190354.279832즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1815018151즉석판매제조가공업07_22_19_P33700003370000-107-1982-0012319820827<NA>3폐업2폐업20021011<NA><NA><NA>051 0000000<NA>611827부산광역시 연제구 연산동 788-12번지<NA><NA>밀양참기름20071128100136I2018-08-31 23:59:59.0즉석판매제조가공업389844.786304188236.799125즉석판매제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
67446745즉석판매제조가공업07_22_19_P32800003280000-107-2008-0001320080630<NA>3폐업2폐업20080717<NA><NA><NA>051 419 8151<NA>606062부산광역시 영도구 봉래동2가 151-1번지<NA><NA>강원도 농특산20080630161539I2018-08-31 23:59:59.0즉석판매제조가공업386335.809603179336.483176즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
52305231즉석판매제조가공업07_22_19_P33900003390000-107-2006-0006320061016<NA>1영업/정상1영업<NA><NA><NA><NA>051 3140452<NA>617831부산광역시 사상구 엄궁동 650번지 청과물도매시장내직판장1층부산광역시 사상구 농산물시장로9번길 11, 1층 (엄궁동, 청과물도매시장내 직판장)47032통영상회20140110113714I2018-08-31 23:59:59.0즉석판매제조가공업378968.772298182801.316045즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA><NA>
42224223즉석판매제조가공업07_22_19_P33100003310000-107-2009-0005920091029<NA>1영업/정상1영업<NA><NA><NA><NA>051 61208806.60608832부산광역시 남구 용호동 176-30번지 엘지메트로시티 1001동 110호부산광역시 남구 분포로 111, 1001동 110호 (용호동, 엘지메트로시티)48516한우박사20190111115443U2019-01-13 02:40:00.0즉석판매제조가공업392474.578116183052.211152즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>