Overview

Dataset statistics

Number of variables48
Number of observations10000
Missing cells108749
Missing cells (%)22.7%
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

Description2021-04-01
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 (98.8%)Imbalance
위생업태명 is highly imbalanced (98.7%)Imbalance
남성종사자수 is highly imbalanced (73.8%)Imbalance
여성종사자수 is highly imbalanced (79.3%)Imbalance
영업장주변구분명 is highly imbalanced (68.3%)Imbalance
등급구분명 is highly imbalanced (62.3%)Imbalance
급수시설구분명 is highly imbalanced (68.3%)Imbalance
공장판매직종업원수 is highly imbalanced (51.9%)Imbalance
공장생산직종업원수 is highly imbalanced (58.3%)Imbalance
보증액 is highly imbalanced (65.0%)Imbalance
월세액 is highly imbalanced (65.0%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2569 (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 4670 (46.7%) missing valuesMissing
소재지면적 has 4945 (49.5%) missing valuesMissing
소재지우편번호 has 217 (2.2%) missing valuesMissing
도로명전체주소 has 2772 (27.7%) missing valuesMissing
도로명우편번호 has 2834 (28.3%) missing valuesMissing
좌표정보(x) has 332 (3.3%) missing valuesMissing
좌표정보(y) has 332 (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 = -32.80658368)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 9377 (93.8%) zerosZeros

Reproduction

Analysis started2024-04-17 12:36:30.758568
Analysis finished2024-04-17 12:36:32.734693
Duration1.98 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%
Mean11231.121
Minimum1
Maximum22367
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:36:32.795026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1091.9
Q15676
median11291.5
Q316813
95-th percentile21225.05
Maximum22367
Range22366
Interquartile range (IQR)11137

Descriptive statistics

Standard deviation6465.4079
Coefficient of variation (CV)0.57566898
Kurtosis-1.1988207
Mean11231.121
Median Absolute Deviation (MAD)5572.5
Skewness-0.016109274
Sum1.1231121 × 108
Variance41801499
MonotonicityNot monotonic
2024-04-17T21:36:32.908622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18084 1
 
< 0.1%
1766 1
 
< 0.1%
6844 1
 
< 0.1%
16144 1
 
< 0.1%
20782 1
 
< 0.1%
3785 1
 
< 0.1%
3287 1
 
< 0.1%
14187 1
 
< 0.1%
18410 1
 
< 0.1%
21890 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
21 1
< 0.1%
22 1
< 0.1%
23 1
< 0.1%
ValueCountFrequency (%)
22367 1
< 0.1%
22364 1
< 0.1%
22362 1
< 0.1%
22361 1
< 0.1%
22360 1
< 0.1%
22357 1
< 0.1%
22356 1
< 0.1%
22354 1
< 0.1%
22352 1
< 0.1%
22351 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

2024-04-17T21:36:33.002127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:33.066377image/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

2024-04-17T21:36:33.134917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:33.202760image/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%
Mean3326788
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:36:33.264680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3269500
Q13290000
median3330000
Q33360000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)70000

Descriptive statistics

Standard deviation39588.127
Coefficient of variation (CV)0.011899804
Kurtosis-0.88311732
Mean3326788
Median Absolute Deviation (MAD)40000
Skewness0.15585985
Sum3.326788 × 1010
Variance1.5672198 × 109
MonotonicityNot monotonic
2024-04-17T21:36:33.355238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1908
19.1%
3290000 1556
15.6%
3300000 909
9.1%
3370000 790
7.9%
3380000 653
 
6.5%
3350000 543
 
5.4%
3390000 510
 
5.1%
3340000 477
 
4.8%
3320000 474
 
4.7%
3400000 454
 
4.5%
Other values (6) 1726
17.3%
ValueCountFrequency (%)
3250000 279
 
2.8%
3260000 221
 
2.2%
3270000 316
 
3.2%
3280000 366
 
3.7%
3290000 1556
15.6%
3300000 909
9.1%
3310000 428
 
4.3%
3320000 474
 
4.7%
3330000 1908
19.1%
3340000 477
 
4.8%
ValueCountFrequency (%)
3400000 454
 
4.5%
3390000 510
 
5.1%
3380000 653
 
6.5%
3370000 790
7.9%
3360000 116
 
1.2%
3350000 543
 
5.4%
3340000 477
 
4.8%
3330000 1908
19.1%
3320000 474
 
4.7%
3310000 428
 
4.3%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T21:36:33.512391image/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 row3370000-107-2010-00030
2nd row3330000-107-2000-00634
3rd row3380000-107-1995-00282
4th row3370000-107-2020-00147
5th row3370000-107-1999-00416
ValueCountFrequency (%)
3370000-107-2010-00030 1
 
< 0.1%
3400000-107-1998-00068 1
 
< 0.1%
3290000-107-2020-00020 1
 
< 0.1%
3330000-107-2008-00138 1
 
< 0.1%
3280000-107-2012-00011 1
 
< 0.1%
3330000-107-2007-00122 1
 
< 0.1%
3350000-107-1998-00290 1
 
< 0.1%
3300000-107-1983-00309 1
 
< 0.1%
3340000-107-2015-00042 1
 
< 0.1%
3300000-107-2003-00076 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T21:36:33.764406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 92131
41.9%
- 30000
 
13.6%
1 21907
 
10.0%
3 21809
 
9.9%
2 16784
 
7.6%
7 14182
 
6.4%
9 8245
 
3.7%
8 4444
 
2.0%
4 3712
 
1.7%
5 3546
 
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 92131
48.5%
1 21907
 
11.5%
3 21809
 
11.5%
2 16784
 
8.8%
7 14182
 
7.5%
9 8245
 
4.3%
8 4444
 
2.3%
4 3712
 
2.0%
5 3546
 
1.9%
6 3240
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92131
41.9%
- 30000
 
13.6%
1 21907
 
10.0%
3 21809
 
9.9%
2 16784
 
7.6%
7 14182
 
6.4%
9 8245
 
3.7%
8 4444
 
2.0%
4 3712
 
1.7%
5 3546
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92131
41.9%
- 30000
 
13.6%
1 21907
 
10.0%
3 21809
 
9.9%
2 16784
 
7.6%
7 14182
 
6.4%
9 8245
 
3.7%
8 4444
 
2.0%
4 3712
 
1.7%
5 3546
 
1.6%

인허가일자
Real number (ℝ)

Distinct4538
Distinct (%)45.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20105260
Minimum19201126
Maximum20210226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:36:33.884734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19201126
5-th percentile19890597
Q120050308
median20150708
Q320190423
95-th percentile20200824
Maximum20210226
Range1009100
Interquartile range (IQR)140115

Descriptive statistics

Standard deviation104685.39
Coefficient of variation (CV)0.0052068658
Kurtosis2.3157961
Mean20105260
Median Absolute Deviation (MAD)49818.5
Skewness-1.4200548
Sum2.010526 × 1011
Variance1.0959031 × 1010
MonotonicityNot monotonic
2024-04-17T21:36:33.998218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190211 16
 
0.2%
20190930 16
 
0.2%
20200310 15
 
0.1%
20190401 14
 
0.1%
20200714 14
 
0.1%
20200629 14
 
0.1%
19760407 14
 
0.1%
20190311 13
 
0.1%
20180821 13
 
0.1%
20190429 13
 
0.1%
Other values (4528) 9858
98.6%
ValueCountFrequency (%)
19201126 1
< 0.1%
19390516 1
< 0.1%
19650629 1
< 0.1%
19651007 1
< 0.1%
19680222 2
< 0.1%
19680316 1
< 0.1%
19680423 1
< 0.1%
19680430 2
< 0.1%
19680904 1
< 0.1%
19680930 1
< 0.1%
ValueCountFrequency (%)
20210226 5
0.1%
20210225 10
0.1%
20210224 6
0.1%
20210223 7
0.1%
20210222 9
0.1%
20210219 6
0.1%
20210218 3
 
< 0.1%
20210217 5
0.1%
20210216 11
0.1%
20210215 7
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
7431 
1
2569 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7431
74.3%
1 2569
 
25.7%

Length

2024-04-17T21:36:34.095261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:34.161147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7431
74.3%
1 2569
 
25.7%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7431 
영업/정상
2569 

Length

Max length5
Median length2
Mean length2.7707
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7431
74.3%
영업/정상 2569
 
25.7%

Length

2024-04-17T21:36:34.240510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:34.320696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7431
74.3%
영업/정상 2569
 
25.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7431 
1
2569 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7431
74.3%
1 2569
 
25.7%

Length

2024-04-17T21:36:34.391427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:34.460177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7431
74.3%
1 2569
 
25.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7431 
영업
2569 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7431
74.3%
영업 2569
 
25.7%

Length

2024-04-17T21:36:34.531354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:34.601397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7431
74.3%
영업 2569
 
25.7%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct3451
Distinct (%)46.4%
Missing2569
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean20129269
Minimum10000101
Maximum20210227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:36:34.694777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000101
5-th percentile20020210
Q120090629
median20170118
Q320190616
95-th percentile20200811
Maximum20210227
Range10210126
Interquartile range (IQR)99987

Descriptive statistics

Standard deviation294688.98
Coefficient of variation (CV)0.014639825
Kurtosis1125.1164
Mean20129269
Median Absolute Deviation (MAD)30310
Skewness-32.806584
Sum1.495806 × 1011
Variance8.6841596 × 1010
MonotonicityNot monotonic
2024-04-17T21:36:34.809917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021011 29
 
0.3%
20191016 21
 
0.2%
20100111 20
 
0.2%
20120222 16
 
0.2%
20021230 16
 
0.2%
20200930 15
 
0.1%
20190331 15
 
0.1%
20200408 14
 
0.1%
20190731 14
 
0.1%
20190828 14
 
0.1%
Other values (3441) 7257
72.6%
(Missing) 2569
 
25.7%
ValueCountFrequency (%)
10000101 6
0.1%
19940120 1
 
< 0.1%
19940913 1
 
< 0.1%
19941018 1
 
< 0.1%
19941024 1
 
< 0.1%
19941124 1
 
< 0.1%
19950112 1
 
< 0.1%
19950724 1
 
< 0.1%
19950802 1
 
< 0.1%
19950816 1
 
< 0.1%
ValueCountFrequency (%)
20210227 2
< 0.1%
20210226 1
< 0.1%
20210225 2
< 0.1%
20210223 2
< 0.1%
20210221 1
< 0.1%
20210218 1
< 0.1%
20210217 1
< 0.1%
20210216 2
< 0.1%
20210213 1
< 0.1%
20210208 1
< 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 

Distinct3503
Distinct (%)65.7%
Missing4670
Missing (%)46.7%
Memory size156.2 KiB
2024-04-17T21:36:35.048699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.626642
Min length3

Characters and Unicode

Total characters56640
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

Unique3165 ?
Unique (%)59.4%

Sample

1st row051 5429946
2nd row051
3rd row051 853 6100
4th row051 4035689
5th row031 529 1741
ValueCountFrequency (%)
051 3956
32.7%
055 239
 
2.0%
031 227
 
1.9%
070 152
 
1.3%
02 132
 
1.1%
831 132
 
1.1%
5711 95
 
0.8%
053 71
 
0.6%
0000000 50
 
0.4%
343 46
 
0.4%
Other values (3747) 6985
57.8%
2024-04-17T21:36:35.384630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9629
17.0%
5 8509
15.0%
1 7882
13.9%
6913
12.2%
2 4299
7.6%
3 3944
7.0%
8 3548
 
6.3%
7 3547
 
6.3%
6 3166
 
5.6%
4 3042
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49727
87.8%
Space Separator 6913
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9629
19.4%
5 8509
17.1%
1 7882
15.9%
2 4299
8.6%
3 3944
7.9%
8 3548
 
7.1%
7 3547
 
7.1%
6 3166
 
6.4%
4 3042
 
6.1%
9 2161
 
4.3%
Space Separator
ValueCountFrequency (%)
6913
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56640
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9629
17.0%
5 8509
15.0%
1 7882
13.9%
6913
12.2%
2 4299
7.6%
3 3944
7.0%
8 3548
 
6.3%
7 3547
 
6.3%
6 3166
 
5.6%
4 3042
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56640
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9629
17.0%
5 8509
15.0%
1 7882
13.9%
6913
12.2%
2 4299
7.6%
3 3944
7.0%
8 3548
 
6.3%
7 3547
 
6.3%
6 3166
 
5.6%
4 3042
 
5.4%

소재지면적
Text

MISSING 

Distinct2015
Distinct (%)39.9%
Missing4945
Missing (%)49.5%
Memory size156.2 KiB
2024-04-17T21:36:35.708185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.5924827
Min length3

Characters and Unicode

Total characters23215
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

Unique1338 ?
Unique (%)26.5%

Sample

1st row42.00
2nd row18.00
3rd row35.36
4th row28.00
5th row45.27
ValueCountFrequency (%)
00 283
 
5.6%
3.00 122
 
2.4%
6.00 98
 
1.9%
6.60 90
 
1.8%
4.00 73
 
1.4%
3.30 66
 
1.3%
2.00 61
 
1.2%
20.00 55
 
1.1%
10.00 50
 
1.0%
5.00 50
 
1.0%
Other values (2005) 4107
81.2%
2024-04-17T21:36:36.117301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5160
22.2%
. 5055
21.8%
1 2095
9.0%
2 2085
9.0%
3 1739
 
7.5%
6 1417
 
6.1%
5 1415
 
6.1%
4 1413
 
6.1%
8 1039
 
4.5%
9 921
 
4.0%
Other values (2) 876
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18159
78.2%
Other Punctuation 5056
 
21.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5160
28.4%
1 2095
11.5%
2 2085
11.5%
3 1739
 
9.6%
6 1417
 
7.8%
5 1415
 
7.8%
4 1413
 
7.8%
8 1039
 
5.7%
9 921
 
5.1%
7 875
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 5055
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 23215
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5160
22.2%
. 5055
21.8%
1 2095
9.0%
2 2085
9.0%
3 1739
 
7.5%
6 1417
 
6.1%
5 1415
 
6.1%
4 1413
 
6.1%
8 1039
 
4.5%
9 921
 
4.0%
Other values (2) 876
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5160
22.2%
. 5055
21.8%
1 2095
9.0%
2 2085
9.0%
3 1739
 
7.5%
6 1417
 
6.1%
5 1415
 
6.1%
4 1413
 
6.1%
8 1039
 
4.5%
9 921
 
4.0%
Other values (2) 876
 
3.8%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct707
Distinct (%)7.2%
Missing217
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean611416.09
Minimum600012
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:36:36.243506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600012
5-th percentile601814
Q1607837
median612040
Q3614816
95-th percentile617833.9
Maximum619953
Range19941
Interquartile range (IQR)6979

Descriptive statistics

Standard deviation4682.061
Coefficient of variation (CV)0.0076577327
Kurtosis-0.17326698
Mean611416.09
Median Absolute Deviation (MAD)2807
Skewness-0.56622561
Sum5.9814836 × 109
Variance21921695
MonotonicityNot monotonic
2024-04-17T21:36:36.560612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
612020 562
 
5.6%
612851 229
 
2.3%
611807 219
 
2.2%
613819 194
 
1.9%
600017 185
 
1.8%
614847 177
 
1.8%
611840 150
 
1.5%
612811 149
 
1.5%
607804 139
 
1.4%
617808 138
 
1.4%
Other values (697) 7641
76.4%
(Missing) 217
 
2.2%
ValueCountFrequency (%)
600012 1
 
< 0.1%
600017 185
1.8%
600021 1
 
< 0.1%
600025 1
 
< 0.1%
600032 1
 
< 0.1%
600041 3
 
< 0.1%
600043 1
 
< 0.1%
600044 2
 
< 0.1%
600045 2
 
< 0.1%
600046 32
 
0.3%
ValueCountFrequency (%)
619953 12
 
0.1%
619952 2
 
< 0.1%
619951 10
 
0.1%
619913 3
 
< 0.1%
619912 28
 
0.3%
619911 3
 
< 0.1%
619906 84
0.8%
619905 59
0.6%
619904 11
 
0.1%
619903 44
0.4%
Distinct5407
Distinct (%)54.4%
Missing68
Missing (%)0.7%
Memory size156.2 KiB
2024-04-17T21:36:36.766326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length52
Mean length25.750906
Min length15

Characters and Unicode

Total characters255758
Distinct characters448
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

Unique4670 ?
Unique (%)47.0%

Sample

1st row부산광역시 연제구 거제동 1208번지 홈플러스내
2nd row부산광역시 해운대구 반송동 250-239번지
3rd row부산광역시 수영구 민락동 24-9번지
4th row부산광역시 연제구 연산동 105-1 홈플러스 부산연산점
5th row부산광역시 연제구 연산동 481-3
ValueCountFrequency (%)
부산광역시 9932
 
20.8%
해운대구 1907
 
4.0%
부산진구 1509
 
3.2%
동래구 900
 
1.9%
연제구 789
 
1.7%
우동 788
 
1.6%
수영구 653
 
1.4%
부전동 546
 
1.1%
금정구 534
 
1.1%
사상구 511
 
1.1%
Other values (5845) 29697
62.2%
2024-04-17T21:36:37.122651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37845
 
14.8%
12881
 
5.0%
12516
 
4.9%
11443
 
4.5%
10598
 
4.1%
10304
 
4.0%
9945
 
3.9%
9925
 
3.9%
9789
 
3.8%
1 9647
 
3.8%
Other values (438) 120865
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162754
63.6%
Decimal Number 44995
 
17.6%
Space Separator 37845
 
14.8%
Dash Punctuation 7586
 
3.0%
Uppercase Letter 1239
 
0.5%
Open Punctuation 562
 
0.2%
Close Punctuation 559
 
0.2%
Other Punctuation 175
 
0.1%
Lowercase Letter 38
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12881
 
7.9%
12516
 
7.7%
11443
 
7.0%
10598
 
6.5%
10304
 
6.3%
9945
 
6.1%
9925
 
6.1%
9789
 
6.0%
8918
 
5.5%
2781
 
1.7%
Other values (392) 63654
39.1%
Uppercase Letter
ValueCountFrequency (%)
B 270
21.8%
S 243
19.6%
T 192
15.5%
G 184
14.9%
E 138
11.1%
K 55
 
4.4%
A 30
 
2.4%
H 25
 
2.0%
U 24
 
1.9%
Y 24
 
1.9%
Other values (10) 54
 
4.4%
Decimal Number
ValueCountFrequency (%)
1 9647
21.4%
2 6278
14.0%
5 4987
11.1%
3 4307
9.6%
4 4064
9.0%
7 3618
 
8.0%
0 3594
 
8.0%
6 3058
 
6.8%
9 2731
 
6.1%
8 2711
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 135
77.1%
. 13
 
7.4%
@ 11
 
6.3%
· 9
 
5.1%
/ 6
 
3.4%
& 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
s 16
42.1%
g 15
39.5%
e 6
 
15.8%
b 1
 
2.6%
Space Separator
ValueCountFrequency (%)
37845
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7586
100.0%
Open Punctuation
ValueCountFrequency (%)
( 562
100.0%
Close Punctuation
ValueCountFrequency (%)
) 559
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162752
63.6%
Common 91726
35.9%
Latin 1278
 
0.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12881
 
7.9%
12516
 
7.7%
11443
 
7.0%
10598
 
6.5%
10304
 
6.3%
9945
 
6.1%
9925
 
6.1%
9789
 
6.0%
8918
 
5.5%
2781
 
1.7%
Other values (391) 63652
39.1%
Latin
ValueCountFrequency (%)
B 270
21.1%
S 243
19.0%
T 192
15.0%
G 184
14.4%
E 138
10.8%
K 55
 
4.3%
A 30
 
2.3%
H 25
 
2.0%
U 24
 
1.9%
Y 24
 
1.9%
Other values (15) 93
 
7.3%
Common
ValueCountFrequency (%)
37845
41.3%
1 9647
 
10.5%
- 7586
 
8.3%
2 6278
 
6.8%
5 4987
 
5.4%
3 4307
 
4.7%
4 4064
 
4.4%
7 3618
 
3.9%
0 3594
 
3.9%
6 3058
 
3.3%
Other values (11) 6742
 
7.4%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162752
63.6%
ASCII 92994
36.4%
None 9
 
< 0.1%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37845
40.7%
1 9647
 
10.4%
- 7586
 
8.2%
2 6278
 
6.8%
5 4987
 
5.4%
3 4307
 
4.6%
4 4064
 
4.4%
7 3618
 
3.9%
0 3594
 
3.9%
6 3058
 
3.3%
Other values (34) 8010
 
8.6%
Hangul
ValueCountFrequency (%)
12881
 
7.9%
12516
 
7.7%
11443
 
7.0%
10598
 
6.5%
10304
 
6.3%
9945
 
6.1%
9925
 
6.1%
9789
 
6.0%
8918
 
5.5%
2781
 
1.7%
Other values (391) 63652
39.1%
None
ValueCountFrequency (%)
· 9
100.0%
CJK
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct4196
Distinct (%)58.1%
Missing2772
Missing (%)27.7%
Memory size156.2 KiB
2024-04-17T21:36:37.422839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length56
Mean length32.870227
Min length19

Characters and Unicode

Total characters237586
Distinct characters483
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3649 ?
Unique (%)50.5%

Sample

1st row부산광역시 연제구 반송로 88, 홈플러스 부산연산점 (연산동)
2nd row부산광역시 연제구 고분로236번길 13 (연산동)
3rd row부산광역시 사상구 광장로 17, 1층 (괘법동, 이마트사상점)
4th row부산광역시 남구 전포대로91번길 47, E마트 1층 (문현동)
5th row부산광역시 동구 범일로 125, 현대백화점 부산점 지하2층 (범일동)
ValueCountFrequency (%)
부산광역시 7228
 
15.8%
1층 1548
 
3.4%
해운대구 1365
 
3.0%
부산진구 926
 
2.0%
지하1층 736
 
1.6%
동래구 622
 
1.4%
우동 618
 
1.4%
연제구 562
 
1.2%
사상구 451
 
1.0%
수영구 438
 
1.0%
Other values (3928) 31214
68.3%
2024-04-17T21:36:37.839116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38500
 
16.2%
9358
 
3.9%
9341
 
3.9%
9130
 
3.8%
1 8227
 
3.5%
8198
 
3.5%
7744
 
3.3%
7276
 
3.1%
7234
 
3.0%
7172
 
3.0%
Other values (473) 125406
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147499
62.1%
Space Separator 38500
 
16.2%
Decimal Number 29362
 
12.4%
Open Punctuation 7151
 
3.0%
Close Punctuation 7147
 
3.0%
Other Punctuation 6090
 
2.6%
Uppercase Letter 1006
 
0.4%
Dash Punctuation 684
 
0.3%
Lowercase Letter 135
 
0.1%
Math Symbol 10
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9358
 
6.3%
9341
 
6.3%
9130
 
6.2%
8198
 
5.6%
7744
 
5.3%
7276
 
4.9%
7234
 
4.9%
7172
 
4.9%
4931
 
3.3%
3076
 
2.1%
Other values (421) 74039
50.2%
Uppercase Letter
ValueCountFrequency (%)
S 242
24.1%
G 166
16.5%
B 156
15.5%
E 142
14.1%
K 54
 
5.4%
A 49
 
4.9%
C 45
 
4.5%
H 25
 
2.5%
N 25
 
2.5%
U 24
 
2.4%
Other values (11) 78
 
7.8%
Decimal Number
ValueCountFrequency (%)
1 8227
28.0%
2 4173
14.2%
3 2956
 
10.1%
5 2757
 
9.4%
7 2458
 
8.4%
4 2270
 
7.7%
0 1687
 
5.7%
9 1681
 
5.7%
8 1603
 
5.5%
6 1550
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
s 59
43.7%
g 53
39.3%
c 7
 
5.2%
n 7
 
5.2%
e 6
 
4.4%
a 1
 
0.7%
i 1
 
0.7%
b 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 6062
99.5%
· 10
 
0.2%
@ 8
 
0.1%
. 5
 
0.1%
/ 4
 
0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
38500
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7151
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7147
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 684
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147498
62.1%
Common 88945
37.4%
Latin 1142
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9358
 
6.3%
9341
 
6.3%
9130
 
6.2%
8198
 
5.6%
7744
 
5.3%
7276
 
4.9%
7234
 
4.9%
7172
 
4.9%
4931
 
3.3%
3076
 
2.1%
Other values (420) 74038
50.2%
Latin
ValueCountFrequency (%)
S 242
21.2%
G 166
14.5%
B 156
13.7%
E 142
12.4%
s 59
 
5.2%
K 54
 
4.7%
g 53
 
4.6%
A 49
 
4.3%
C 45
 
3.9%
H 25
 
2.2%
Other values (20) 151
13.2%
Common
ValueCountFrequency (%)
38500
43.3%
1 8227
 
9.2%
( 7151
 
8.0%
) 7147
 
8.0%
, 6062
 
6.8%
2 4173
 
4.7%
3 2956
 
3.3%
5 2757
 
3.1%
7 2458
 
2.8%
4 2270
 
2.6%
Other values (12) 7244
 
8.1%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147498
62.1%
ASCII 90076
37.9%
None 10
 
< 0.1%
CJK 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38500
42.7%
1 8227
 
9.1%
( 7151
 
7.9%
) 7147
 
7.9%
, 6062
 
6.7%
2 4173
 
4.6%
3 2956
 
3.3%
5 2757
 
3.1%
7 2458
 
2.7%
4 2270
 
2.5%
Other values (40) 8375
 
9.3%
Hangul
ValueCountFrequency (%)
9358
 
6.3%
9341
 
6.3%
9130
 
6.2%
8198
 
5.6%
7744
 
5.3%
7276
 
4.9%
7234
 
4.9%
7172
 
4.9%
4931
 
3.3%
3076
 
2.1%
Other values (420) 74038
50.2%
None
ValueCountFrequency (%)
· 10
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1125
Distinct (%)15.7%
Missing2834
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean47729.503
Minimum46002
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:36:37.962531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46084
Q147124
median47787.5
Q348284
95-th percentile49311
Maximum49525
Range3523
Interquartile range (IQR)1160

Descriptive statistics

Standard deviation913.41083
Coefficient of variation (CV)0.019137237
Kurtosis-0.67968973
Mean47729.503
Median Absolute Deviation (MAD)538
Skewness-0.040599725
Sum3.4202962 × 108
Variance834319.35
MonotonicityNot monotonic
2024-04-17T21:36:38.068242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48058 411
 
4.1%
48096 192
 
1.9%
48944 181
 
1.8%
47285 175
 
1.8%
47500 156
 
1.6%
48313 145
 
1.5%
46970 134
 
1.3%
47604 115
 
1.1%
46233 104
 
1.0%
47727 101
 
1.0%
Other values (1115) 5452
54.5%
(Missing) 2834
28.3%
ValueCountFrequency (%)
46002 1
 
< 0.1%
46003 2
 
< 0.1%
46004 4
 
< 0.1%
46007 2
 
< 0.1%
46008 8
 
0.1%
46010 3
 
< 0.1%
46012 5
 
0.1%
46013 2
 
< 0.1%
46015 46
0.5%
46016 4
 
< 0.1%
ValueCountFrequency (%)
49525 1
 
< 0.1%
49524 1
 
< 0.1%
49523 4
 
< 0.1%
49522 2
 
< 0.1%
49521 1
 
< 0.1%
49520 3
 
< 0.1%
49519 55
0.5%
49518 3
 
< 0.1%
49516 1
 
< 0.1%
49515 5
 
0.1%
Distinct5369
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T21:36:38.268820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length23
Mean length5.8938
Min length1

Characters and Unicode

Total characters58938
Distinct characters834
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4410 ?
Unique (%)44.1%

Sample

1st row연당원
2nd row전통민속떡집
3rd row고려건강원
4th row주경식품
5th row한양스토아현대
ValueCountFrequency (%)
주식회사 193
 
1.7%
현승유통 123
 
1.1%
현재상사 109
 
1.0%
주경식품 97
 
0.9%
부산축산 86
 
0.8%
주)정성 85
 
0.8%
주)미트벨리 85
 
0.8%
주)모두랑식품 85
 
0.8%
주)부산축산 85
 
0.8%
아라식품 68
 
0.6%
Other values (5589) 10160
90.9%
2024-04-17T21:36:38.583125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2212
 
3.8%
) 2066
 
3.5%
( 2031
 
3.4%
1571
 
2.7%
1448
 
2.5%
1176
 
2.0%
1131
 
1.9%
899
 
1.5%
898
 
1.5%
854
 
1.4%
Other values (824) 44652
75.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52300
88.7%
Close Punctuation 2066
 
3.5%
Open Punctuation 2031
 
3.4%
Space Separator 1176
 
2.0%
Uppercase Letter 679
 
1.2%
Lowercase Letter 365
 
0.6%
Decimal Number 148
 
0.3%
Other Punctuation 142
 
0.2%
Dash Punctuation 21
 
< 0.1%
Connector Punctuation 4
 
< 0.1%
Other values (4) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2212
 
4.2%
1571
 
3.0%
1448
 
2.8%
1131
 
2.2%
899
 
1.7%
898
 
1.7%
854
 
1.6%
832
 
1.6%
757
 
1.4%
734
 
1.4%
Other values (749) 40964
78.3%
Uppercase Letter
ValueCountFrequency (%)
N 96
14.1%
S 96
14.1%
T 91
13.4%
I 84
12.4%
F 34
 
5.0%
E 31
 
4.6%
O 29
 
4.3%
A 28
 
4.1%
M 23
 
3.4%
C 21
 
3.1%
Other values (15) 146
21.5%
Lowercase Letter
ValueCountFrequency (%)
e 63
17.3%
o 41
11.2%
r 22
 
6.0%
a 22
 
6.0%
i 22
 
6.0%
l 21
 
5.8%
s 19
 
5.2%
u 18
 
4.9%
t 18
 
4.9%
n 18
 
4.9%
Other values (13) 101
27.7%
Decimal Number
ValueCountFrequency (%)
1 36
24.3%
2 28
18.9%
0 16
10.8%
5 14
 
9.5%
6 12
 
8.1%
3 10
 
6.8%
8 9
 
6.1%
7 9
 
6.1%
4 7
 
4.7%
9 7
 
4.7%
Other Punctuation
ValueCountFrequency (%)
' 71
50.0%
& 27
 
19.0%
. 26
 
18.3%
, 10
 
7.0%
· 3
 
2.1%
; 2
 
1.4%
/ 2
 
1.4%
! 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 2066
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2031
100.0%
Space Separator
ValueCountFrequency (%)
1176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52296
88.7%
Common 5590
 
9.5%
Latin 1045
 
1.8%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2212
 
4.2%
1571
 
3.0%
1448
 
2.8%
1131
 
2.2%
899
 
1.7%
898
 
1.7%
854
 
1.6%
832
 
1.6%
757
 
1.4%
734
 
1.4%
Other values (743) 40960
78.3%
Latin
ValueCountFrequency (%)
N 96
 
9.2%
S 96
 
9.2%
T 91
 
8.7%
I 84
 
8.0%
e 63
 
6.0%
o 41
 
3.9%
F 34
 
3.3%
E 31
 
3.0%
O 29
 
2.8%
A 28
 
2.7%
Other values (39) 452
43.3%
Common
ValueCountFrequency (%)
) 2066
37.0%
( 2031
36.3%
1176
21.0%
' 71
 
1.3%
1 36
 
0.6%
2 28
 
0.5%
& 27
 
0.5%
. 26
 
0.5%
- 21
 
0.4%
0 16
 
0.3%
Other values (15) 92
 
1.6%
Han
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52292
88.7%
ASCII 6631
 
11.3%
CJK 7
 
< 0.1%
None 6
 
< 0.1%
Number Forms 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2212
 
4.2%
1571
 
3.0%
1448
 
2.8%
1131
 
2.2%
899
 
1.7%
898
 
1.7%
854
 
1.6%
832
 
1.6%
757
 
1.4%
734
 
1.4%
Other values (741) 40956
78.3%
ASCII
ValueCountFrequency (%)
) 2066
31.2%
( 2031
30.6%
1176
17.7%
N 96
 
1.4%
S 96
 
1.4%
T 91
 
1.4%
I 84
 
1.3%
' 71
 
1.1%
e 63
 
1.0%
o 41
 
0.6%
Other values (62) 816
 
12.3%
None
ValueCountFrequency (%)
3
50.0%
· 3
50.0%
CJK
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct7660
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0141931 × 1013
Minimum1.9990218 × 1013
Maximum2.0210228 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:36:38.704333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile2.0020612 × 1013
Q12.0091204 × 1013
median2.0170901 × 1013
Q32.0190821 × 1013
95-th percentile2.0201019 × 1013
Maximum2.0210228 × 1013
Range2.2001004 × 1011
Interquartile range (IQR)9.9617151 × 1010

Descriptive statistics

Standard deviation6.2896364 × 1010
Coefficient of variation (CV)0.0031226581
Kurtosis-0.63862131
Mean2.0141931 × 1013
Median Absolute Deviation (MAD)2.9713 × 1010
Skewness-0.85853305
Sum2.0141931 × 1017
Variance3.9559526 × 1021
MonotonicityNot monotonic
2024-04-17T21:36:38.804521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020612000000 66
 
0.7%
20020305000000 53
 
0.5%
20010728000000 44
 
0.4%
20020821000000 41
 
0.4%
20020621000000 40
 
0.4%
20020724000000 32
 
0.3%
20020611000000 28
 
0.3%
20020719000000 27
 
0.3%
20020828000000 26
 
0.3%
20010731000000 26
 
0.3%
Other values (7650) 9617
96.2%
ValueCountFrequency (%)
19990218000000 1
 
< 0.1%
19990223000000 1
 
< 0.1%
19990302000000 1
 
< 0.1%
19990304000000 13
0.1%
19990305000000 2
 
< 0.1%
19990318000000 14
0.1%
19990319000000 11
0.1%
19990322000000 3
 
< 0.1%
19990323000000 3
 
< 0.1%
19990324000000 7
0.1%
ValueCountFrequency (%)
20210228041511 1
< 0.1%
20210228041509 1
< 0.1%
20210226174257 1
< 0.1%
20210226164625 1
< 0.1%
20210226142436 1
< 0.1%
20210226141928 1
< 0.1%
20210226115753 1
< 0.1%
20210226105219 1
< 0.1%
20210226100651 1
< 0.1%
20210226095029 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6391 
U
3609 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6391
63.9%
U 3609
36.1%

Length

2024-04-17T21:36:38.896544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:38.978542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6391
63.9%
u 3609
36.1%
Distinct995
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-03-02 02:40:00
2024-04-17T21:36:39.065763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T21:36:39.189766image/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
9982 
기타
 
17
한식
 
1

Length

Max length9
Median length9
Mean length8.9874
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9982
99.8%
기타 17
 
0.2%
한식 1
 
< 0.1%

Length

2024-04-17T21:36:39.303332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:39.397281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9982
99.8%
기타 17
 
0.2%
한식 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3599
Distinct (%)37.2%
Missing332
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean389175.41
Minimum366798.27
Maximum407564.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:36:39.478692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366798.27
5-th percentile380225.64
Q1385836.5
median389097.8
Q3392694.41
95-th percentile398255.65
Maximum407564.77
Range40766.505
Interquartile range (IQR)6857.9097

Descriptive statistics

Standard deviation5512.9901
Coefficient of variation (CV)0.014165823
Kurtosis0.38617661
Mean389175.41
Median Absolute Deviation (MAD)3495.9296
Skewness-0.031693434
Sum3.7625479 × 109
Variance30393060
MonotonicityNot monotonic
2024-04-17T21:36:39.586255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393952.264486105 298
 
3.0%
387271.299492377 289
 
2.9%
397397.83276594 226
 
2.3%
392321.102334852 183
 
1.8%
387686.194940483 180
 
1.8%
385590.814676765 174
 
1.7%
389097.800933845 148
 
1.5%
389532.511756755 146
 
1.5%
387539.767677801 145
 
1.5%
389455.109101676 134
 
1.3%
Other values (3589) 7745
77.5%
(Missing) 332
 
3.3%
ValueCountFrequency (%)
366798.269419272 1
 
< 0.1%
366829.531355754 3
 
< 0.1%
366931.435995074 1
 
< 0.1%
367011.799190228 1
 
< 0.1%
367041.984452276 1
 
< 0.1%
367169.234957368 1
 
< 0.1%
367227.220529251 1
 
< 0.1%
367304.900921148 1
 
< 0.1%
367451.087635496 8
0.1%
369071.601644319 1
 
< 0.1%
ValueCountFrequency (%)
407564.774795629 1
< 0.1%
406950.03175562 1
< 0.1%
406949.405821447 1
< 0.1%
406910.100470872 1
< 0.1%
406849.904830501 1
< 0.1%
406761.100883744 1
< 0.1%
405688.580680087 1
< 0.1%
405553.977099682 1
< 0.1%
405484.920224281 1
< 0.1%
405372.254329784 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct3600
Distinct (%)37.2%
Missing332
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean187600.75
Minimum169678.05
Maximum211459
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:36:39.698640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169678.05
5-th percentile178817.45
Q1184747.39
median187602.93
Q3190957.43
95-th percentile196375.47
Maximum211459
Range41780.954
Interquartile range (IQR)6210.0419

Descriptive statistics

Standard deviation5388.9128
Coefficient of variation (CV)0.028725432
Kurtosis0.92348932
Mean187600.75
Median Absolute Deviation (MAD)3147.6333
Skewness0.32835343
Sum1.8137241 × 109
Variance29040381
MonotonicityNot monotonic
2024-04-17T21:36:39.799706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187602.933160728 298
 
3.0%
186099.137533193 289
 
2.9%
187354.835259309 226
 
2.3%
184041.758684038 183
 
1.8%
189911.430545728 180
 
1.8%
179553.867031936 174
 
1.7%
192260.811648263 148
 
1.5%
188309.453546847 146
 
1.5%
184402.96650913 145
 
1.5%
191427.549247975 134
 
1.3%
Other values (3590) 7745
77.5%
(Missing) 332
 
3.3%
ValueCountFrequency (%)
169678.048271107 1
< 0.1%
173961.914773076 1
< 0.1%
174156.617297535 1
< 0.1%
174181.52961765 1
< 0.1%
174289.976688419 1
< 0.1%
174422.480246459 1
< 0.1%
174491.469961028 1
< 0.1%
174526.100850246 1
< 0.1%
174587.185782495 1
< 0.1%
174632.012941701 1
< 0.1%
ValueCountFrequency (%)
211459.001777975 1
< 0.1%
210945.104382171 1
< 0.1%
210316.862590787 1
< 0.1%
209383.598383269 1
< 0.1%
207739.619868549 1
< 0.1%
207716.999117547 1
< 0.1%
206788.899936301 1
< 0.1%
206739.517959242 1
< 0.1%
206690.833564719 1
< 0.1%
206335.787689029 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9977 
기타
 
17
<NA>
 
5
한식
 
1

Length

Max length9
Median length9
Mean length8.9849
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9977
99.8%
기타 17
 
0.2%
<NA> 5
 
0.1%
한식 1
 
< 0.1%

Length

2024-04-17T21:36:39.900663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:39.979258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9977
99.8%
기타 17
 
0.2%
na 5
 
< 0.1%
한식 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9206 
0
 
772
1
 
22

Length

Max length4
Median length4
Mean length3.7618
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9206
92.1%
0 772
 
7.7%
1 22
 
0.2%

Length

2024-04-17T21:36:40.061656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:40.156418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9206
92.1%
0 772
 
7.7%
1 22
 
0.2%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9206 
0
 
774
1
 
19
2
 
1

Length

Max length4
Median length4
Mean length3.7618
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9206
92.1%
0 774
 
7.7%
1 19
 
0.2%
2 1
 
< 0.1%

Length

2024-04-17T21:36:40.237548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:40.313003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9206
92.1%
0 774
 
7.7%
1 19
 
0.2%
2 1
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8193 
기타
1723 
주택가주변
 
72
아파트지역
 
7
유흥업소밀집지역
 
5

Length

Max length8
Median length4
Mean length3.6653
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8193
81.9%
기타 1723
 
17.2%
주택가주변 72
 
0.7%
아파트지역 7
 
0.1%
유흥업소밀집지역 5
 
0.1%

Length

2024-04-17T21:36:40.396305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:40.481866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8193
81.9%
기타 1723
 
17.2%
주택가주변 72
 
0.7%
아파트지역 7
 
0.1%
유흥업소밀집지역 5
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8193 
기타
1665 
자율
 
141
 
1

Length

Max length4
Median length4
Mean length3.6385
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8193
81.9%
기타 1665
 
16.7%
자율 141
 
1.4%
1
 
< 0.1%

Length

2024-04-17T21:36:40.594636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:40.690524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8193
81.9%
기타 1665
 
16.7%
자율 141
 
1.4%
1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8426 
상수도전용
1569 
지하수전용
 
3
간이상수도
 
2

Length

Max length5
Median length4
Mean length4.1574
Min length4

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> 8426
84.3%
상수도전용 1569
 
15.7%
지하수전용 3
 
< 0.1%
간이상수도 2
 
< 0.1%

Length

2024-04-17T21:36:40.792499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:40.885112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8426
84.3%
상수도전용 1569
 
15.7%
지하수전용 3
 
< 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>
6466 
0
3531 
1
 
3

Length

Max length4
Median length4
Mean length2.9398
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6466
64.7%
0 3531
35.3%
1 3
 
< 0.1%

Length

2024-04-17T21:36:40.979372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:41.059159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6466
64.7%
0 3531
35.3%
1 3
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6466 
0
3534 

Length

Max length4
Median length4
Mean length2.9398
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6466
64.7%
0 3534
35.3%

Length

2024-04-17T21:36:41.158886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:41.245013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6466
64.7%
0 3534
35.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6462 
0
3511 
1
 
25
2
 
2

Length

Max length4
Median length4
Mean length2.9386
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6462
64.6%
0 3511
35.1%
1 25
 
0.2%
2 2
 
< 0.1%

Length

2024-04-17T21:36:41.323279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:41.401873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6462
64.6%
0 3511
35.1%
1 25
 
0.2%
2 2
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6460 
0
3504 
1
 
31
2
 
4
10
 
1

Length

Max length4
Median length4
Mean length2.9381
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6460
64.6%
0 3504
35.0%
1 31
 
0.3%
2 4
 
< 0.1%
10 1
 
< 0.1%

Length

2024-04-17T21:36:41.736546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:41.829345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6460
64.6%
0 3504
35.0%
1 31
 
0.3%
2 4
 
< 0.1%
10 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7715 
자가
1453 
임대
832 

Length

Max length4
Median length4
Mean length3.543
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7715
77.1%
자가 1453
 
14.5%
임대 832
 
8.3%

Length

2024-04-17T21:36:41.921303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:42.005596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7715
77.1%
자가 1453
 
14.5%
임대 832
 
8.3%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9343 
0
 
657

Length

Max length4
Median length4
Mean length3.8029
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> 9343
93.4%
0 657
 
6.6%

Length

2024-04-17T21:36:42.088663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:42.161255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9343
93.4%
0 657
 
6.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9343 
0
 
657

Length

Max length4
Median length4
Mean length3.8029
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> 9343
93.4%
0 657
 
6.6%

Length

2024-04-17T21:36:42.246288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:36:42.336961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9343
93.4%
0 657
 
6.6%

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%
2024-04-17T21:36:42.405429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct412
Distinct (%)4.1%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.1802311
Minimum0
Maximum233.9
Zeros9377
Zeros (%)93.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:36:42.502175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.3
Maximum233.9
Range233.9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.7018171
Coefficient of variation (CV)6.5256855
Kurtosis234.60149
Mean1.1802311
Median Absolute Deviation (MAD)0
Skewness12.606318
Sum11796.41
Variance59.317986
MonotonicityNot monotonic
2024-04-17T21:36:42.618281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9377
93.8%
3.3 21
 
0.2%
2.0 18
 
0.2%
9.9 13
 
0.1%
1.0 10
 
0.1%
16.5 9
 
0.1%
3.0 9
 
0.1%
19.8 8
 
0.1%
20.0 8
 
0.1%
15.0 7
 
0.1%
Other values (402) 515
 
5.1%
ValueCountFrequency (%)
0.0 9377
93.8%
0.4 1
 
< 0.1%
0.55 1
 
< 0.1%
0.6 1
 
< 0.1%
0.7 1
 
< 0.1%
0.81 1
 
< 0.1%
0.95 1
 
< 0.1%
1.0 10
 
0.1%
1.01 1
 
< 0.1%
1.1 3
 
< 0.1%
ValueCountFrequency (%)
233.9 1
< 0.1%
191.91 1
< 0.1%
190.64 1
< 0.1%
149.58 1
< 0.1%
139.08 1
< 0.1%
133.03 1
< 0.1%
120.15 1
< 0.1%
107.78 1
< 0.1%
106.74 1
< 0.1%
94.89 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
1808318084즉석판매제조가공업07_22_19_P33700003370000-107-2010-0003020100520<NA>3폐업2폐업20100527<NA><NA><NA><NA><NA>611807부산광역시 연제구 거제동 1208번지 홈플러스내<NA><NA>연당원20100520112114I2018-08-31 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>
15311532즉석판매제조가공업07_22_19_P33300003330000-107-2000-0063420000818<NA>1영업/정상1영업<NA><NA><NA><NA>051 542994642.00612802부산광역시 해운대구 반송동 250-239번지<NA><NA>전통민속떡집20020621000000I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1122011221즉석판매제조가공업07_22_19_P33800003380000-107-1995-0028219951110<NA>3폐업2폐업19990413<NA><NA><NA>051<NA>613827부산광역시 수영구 민락동 24-9번지<NA><NA>고려건강원20020828000000I2018-08-31 23:59:59.0즉석판매제조가공업393752.624656186448.606864즉석판매제조가공업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
2033920340즉석판매제조가공업07_22_19_P33700003370000-107-2020-0014720200923<NA>3폐업2폐업20201021<NA><NA><NA><NA><NA>611811부산광역시 연제구 연산동 105-1 홈플러스 부산연산점부산광역시 연제구 반송로 88, 홈플러스 부산연산점 (연산동)47552주경식품20201022041509U2020-10-24 02:40:00.0즉석판매제조가공업390220.954524189976.508573즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
22422243즉석판매제조가공업07_22_19_P33700003370000-107-1999-0041619991227<NA>1영업/정상1영업<NA><NA><NA><NA>051 853 610018.00611812부산광역시 연제구 연산동 481-3부산광역시 연제구 고분로236번길 13 (연산동)47570한양스토아현대20200911174110U2020-09-13 02:40:00.0즉석판매제조가공업391967.978817189197.302076즉석판매제조가공업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
70887089즉석판매제조가공업07_22_19_P32800003280000-107-1991-0010319911104<NA>3폐업2폐업20130628<NA><NA><NA>051 403568935.36606080부산광역시 영도구 동삼동 산 535번지<NA><NA>중리방앗간20081007121006I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
2214722148즉석판매제조가공업07_22_19_P33900003390000-107-2017-0013320171110<NA>3폐업2폐업20171129<NA><NA><NA>031 529 1741<NA>617808부산광역시 사상구 괘법동 531-2번지 이마트부산광역시 사상구 광장로 17, 1층 (괘법동, 이마트사상점)46970가메골푸드20171130041528I2018-08-31 23:59:59.0즉석판매제조가공업380225.635402186791.519407즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
89558956즉석판매제조가공업07_22_19_P33100003310000-107-2019-0017520191209<NA>3폐업2폐업20191215<NA><NA><NA>031 7921824<NA>608827부산광역시 남구 문현동 751번지 E마트부산광역시 남구 전포대로91번길 47, E마트 1층 (문현동)48401(주)남선푸드20191216041510U2019-12-18 02:40:00.0즉석판매제조가공업388052.381944184747.385931즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
79967997즉석판매제조가공업07_22_19_P32700003270000-107-2019-0002820190612<NA>3폐업2폐업20190623<NA><NA><NA>053 741 7927<NA>601718부산광역시 동구 범일동 62-5번지 현대백화점 부산점부산광역시 동구 범일로 125, 현대백화점 부산점 지하2층 (범일동)48735청담20190624041508U2019-06-26 02:40:00.0즉석판매제조가공업387539.767678184402.966509즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
15521553즉석판매제조가공업07_22_19_P33300003330000-107-2003-0005120030730<NA>1영업/정상1영업<NA><NA><NA><NA>051 523 327228.00612060부산광역시 해운대구 반여동 1632번지부산광역시 해운대구 반여로 131 (반여동, 아시아선수촌프레스센타상가 지하217호)48037프레스선수촌떡방앗간20111130142744I2018-08-31 23:59:59.0즉석판매제조가공업393307.129763191421.760662즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
15621563즉석판매제조가공업07_22_19_P33300003330000-107-2004-0001720040326<NA>1영업/정상1영업<NA><NA><NA><NA>0517413 232.00612820부산광역시 해운대구 우동 524-5번지 에이치스위트 해운대부산광역시 해운대구 해운대로 601, 에이치스위트 해운대 107-1호 (우동)48087정관장홍삼 우동점20191218173510U2019-12-20 02:40:00.0즉석판매제조가공업396543.649962186977.05629즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA><NA>
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74087409즉석판매제조가공업07_22_19_P33300003330000-107-2019-0019220190426<NA>3폐업2폐업20200115<NA><NA><NA><NA>17.37612849부산광역시 해운대구 중동 1494-2번지 달맞이슈퍼부산광역시 해운대구 달맞이길117번다길 117, 1층 일부 (중동)48115달빛공장20200115094716U2020-01-17 02:40:00.0즉석판매제조가공업398616.164639186669.183243즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N2.2<NA><NA><NA><NA>
1940019401즉석판매제조가공업07_22_19_P32900003290000-107-2006-0000420060124<NA>3폐업2폐업20060629<NA><NA><NA>051 80701206.00614872부산광역시 부산진구 초읍동 275-4번지 (GS슈퍼마켓초읍점)<NA><NA>우주통상20060124000000I2018-08-31 23:59:59.0즉석판매제조가공업386532.400526188444.325228즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA><NA>
99189919즉석판매제조가공업07_22_19_P33000003300000-107-2020-0003920200228<NA>3폐업2폐업20200308<NA><NA><NA><NA><NA>607815부산광역시 동래구 사직동 28-9번지부산광역시 동래구 사직북로33번길 34 (사직동)47860오에스푸드20200309041509U2020-03-11 02:40:00.0즉석판매제조가공업387382.806313190792.095628즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1217712178즉석판매제조가공업07_22_19_P32900003290000-107-2000-0129720000808<NA>3폐업2폐업20130205<NA><NA><NA>051 807792018.00614843부산광역시 부산진구 부전동 344-5번지 (1층)부산광역시 부산진구 중앙대로775번길 47 (부전동,(1층))47252포항민물상회20110811142757I2018-08-31 23:59:59.0즉석판매제조가공업387672.233065186835.635027즉석판매제조가공업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1863118632즉석판매제조가공업07_22_19_P32900003290000-107-1996-0035319960517<NA>3폐업2폐업20050831<NA><NA><NA>051 891027318.00614813부산광역시 부산진구 개금동 177-158번지<NA><NA>밀양상회20020711000000I2018-08-31 23:59:59.0즉석판매제조가공업384135.019512185427.025406즉석판매제조가공업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1280412805즉석판매제조가공업07_22_19_P33300003330000-107-2002-0085920020108<NA>3폐업2폐업20120125<NA><NA><NA>051 703257916.00612839부산광역시 해운대구 좌동 1314-2번지부산광역시 해운대구 세실로 64 (좌동, 화목데파트상가 지하144호)48107떡메방20111130133804I2018-08-31 23:59:59.0즉석판매제조가공업398320.764293187928.258298즉석판매제조가공업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1979219793즉석판매제조가공업07_22_19_P33800003380000-107-1986-0038119860423<NA>3폐업2폐업20061013<NA><NA><NA>051 753825033.00613802부산광역시 수영구 광안동 120-262번지<NA><NA>영진떡방앗간20050124000000I2018-08-31 23:59:59.0즉석판매제조가공업392658.672914186620.595737즉석판매제조가공업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
30813082즉석판매제조가공업07_22_19_P32500003250000-107-2020-0012220200904<NA>1영업/정상1영업<NA><NA><NA><NA>051 262 022810.20600807부산광역시 중구 부평동2가 26-1부산광역시 중구 중구로23번길 31, 1층 (부평동2가)48979대정양곱창20200904162914I2020-09-06 00:23:13.0즉석판매제조가공업384673.747487179754.939962즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>