Overview

Dataset statistics

Number of variables48
Number of observations10000
Missing cells108441
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

Description2021-05-01
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 (99.2%)Imbalance
위생업태명 is highly imbalanced (99.0%)Imbalance
남성종사자수 is highly imbalanced (74.3%)Imbalance
여성종사자수 is highly imbalanced (74.3%)Imbalance
영업장주변구분명 is highly imbalanced (71.7%)Imbalance
등급구분명 is highly imbalanced (53.0%)Imbalance
급수시설구분명 is highly imbalanced (61.5%)Imbalance
공장판매직종업원수 is highly imbalanced (59.1%)Imbalance
공장생산직종업원수 is highly imbalanced (58.8%)Imbalance
보증액 is highly imbalanced (79.8%)Imbalance
월세액 is highly imbalanced (79.8%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2572 (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 4705 (47.0%) missing valuesMissing
소재지면적 has 5020 (50.2%) missing valuesMissing
소재지우편번호 has 223 (2.2%) missing valuesMissing
도로명전체주소 has 2601 (26.0%) missing valuesMissing
도로명우편번호 has 2656 (26.6%) missing valuesMissing
좌표정보(x) has 299 (3.0%) missing valuesMissing
좌표정보(y) has 299 (3.0%) 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 = -38.88877679)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 9384 (93.8%) zerosZeros

Reproduction

Analysis started2024-04-17 12:33:44.770263
Analysis finished2024-04-17 12:33:46.552642
Duration1.78 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11216.119
Minimum1
Maximum22359
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:33:46.607631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1073.65
Q15714.75
median11236.5
Q316717.25
95-th percentile21254.3
Maximum22359
Range22358
Interquartile range (IQR)11002.5

Descriptive statistics

Standard deviation6437.7456
Coefficient of variation (CV)0.57397266
Kurtosis-1.1862721
Mean11216.119
Median Absolute Deviation (MAD)5502
Skewness-0.0088721703
Sum1.1216119 × 108
Variance41444568
MonotonicityNot monotonic
2024-04-17T21:33:46.705382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9094 1
 
< 0.1%
8697 1
 
< 0.1%
21611 1
 
< 0.1%
19290 1
 
< 0.1%
3487 1
 
< 0.1%
9955 1
 
< 0.1%
6166 1
 
< 0.1%
15535 1
 
< 0.1%
7688 1
 
< 0.1%
14543 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
ValueCountFrequency (%)
22359 1
< 0.1%
22358 1
< 0.1%
22356 1
< 0.1%
22353 1
< 0.1%
22352 1
< 0.1%
22349 1
< 0.1%
22346 1
< 0.1%
22345 1
< 0.1%
22344 1
< 0.1%
22342 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

2024-04-17T21:33:46.796234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:46.874633image/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

2024-04-17T21:33:46.944603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:47.008482image/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%
Mean3326676
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:33:47.071987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3330000
Q33360000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)70000

Descriptive statistics

Standard deviation40123.709
Coefficient of variation (CV)0.012061201
Kurtosis-0.89723519
Mean3326676
Median Absolute Deviation (MAD)40000
Skewness0.1446687
Sum3.326676 × 1010
Variance1.609912 × 109
MonotonicityNot monotonic
2024-04-17T21:33:47.172162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1873
18.7%
3290000 1503
15.0%
3300000 869
8.7%
3370000 794
7.9%
3380000 666
 
6.7%
3350000 506
 
5.1%
3390000 495
 
5.0%
3340000 492
 
4.9%
3400000 490
 
4.9%
3320000 471
 
4.7%
Other values (6) 1841
18.4%
ValueCountFrequency (%)
3250000 313
 
3.1%
3260000 230
 
2.3%
3270000 332
 
3.3%
3280000 397
 
4.0%
3290000 1503
15.0%
3300000 869
8.7%
3310000 452
 
4.5%
3320000 471
 
4.7%
3330000 1873
18.7%
3340000 492
 
4.9%
ValueCountFrequency (%)
3400000 490
 
4.9%
3390000 495
 
5.0%
3380000 666
 
6.7%
3370000 794
7.9%
3360000 117
 
1.2%
3350000 506
 
5.1%
3340000 492
 
4.9%
3330000 1873
18.7%
3320000 471
 
4.7%
3310000 452
 
4.5%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T21:33:47.358950image/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 row3250000-107-2019-00148
2nd row3330000-107-2020-00098
3rd row3380000-107-2018-00057
4th row3380000-107-2004-00004
5th row3370000-107-2003-00012
ValueCountFrequency (%)
3250000-107-2019-00148 1
 
< 0.1%
3350000-107-2007-00035 1
 
< 0.1%
3370000-107-2016-00004 1
 
< 0.1%
3400000-107-2018-00148 1
 
< 0.1%
3330000-107-2009-00058 1
 
< 0.1%
3290000-107-2012-00030 1
 
< 0.1%
3390000-107-2021-00047 1
 
< 0.1%
3360000-107-2020-00013 1
 
< 0.1%
3320000-107-2000-00507 1
 
< 0.1%
3320000-107-2019-00206 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T21:33:47.638490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 92190
41.9%
- 30000
 
13.6%
1 22013
 
10.0%
3 21654
 
9.8%
2 16964
 
7.7%
7 14079
 
6.4%
9 8100
 
3.7%
8 4399
 
2.0%
4 3831
 
1.7%
5 3538
 
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 92190
48.5%
1 22013
 
11.6%
3 21654
 
11.4%
2 16964
 
8.9%
7 14079
 
7.4%
9 8100
 
4.3%
8 4399
 
2.3%
4 3831
 
2.0%
5 3538
 
1.9%
6 3232
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92190
41.9%
- 30000
 
13.6%
1 22013
 
10.0%
3 21654
 
9.8%
2 16964
 
7.7%
7 14079
 
6.4%
9 8100
 
3.7%
8 4399
 
2.0%
4 3831
 
1.7%
5 3538
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92190
41.9%
- 30000
 
13.6%
1 22013
 
10.0%
3 21654
 
9.8%
2 16964
 
7.7%
7 14079
 
6.4%
9 8100
 
3.7%
8 4399
 
2.0%
4 3831
 
1.7%
5 3538
 
1.6%

인허가일자
Real number (ℝ)

Distinct4396
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20109268
Minimum19651007
Maximum20210331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:33:47.755704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19651007
5-th percentile19910719
Q120050818
median20160426
Q320190528
95-th percentile20201005
Maximum20210331
Range559324
Interquartile range (IQR)139710

Descriptive statistics

Standard deviation102529.57
Coefficient of variation (CV)0.0050986228
Kurtosis1.7109938
Mean20109268
Median Absolute Deviation (MAD)40313
Skewness-1.374627
Sum2.0109268 × 1011
Variance1.0512313 × 1010
MonotonicityNot monotonic
2024-04-17T21:33:47.877141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190429 24
 
0.2%
20190225 17
 
0.2%
20210216 16
 
0.2%
20190415 15
 
0.1%
20190401 15
 
0.1%
20190930 15
 
0.1%
20190805 14
 
0.1%
20200310 14
 
0.1%
20180102 14
 
0.1%
20190826 14
 
0.1%
Other values (4386) 9842
98.4%
ValueCountFrequency (%)
19651007 1
< 0.1%
19680222 2
< 0.1%
19680316 1
< 0.1%
19680430 1
< 0.1%
19681129 2
< 0.1%
19690113 2
< 0.1%
19690401 1
< 0.1%
19690429 1
< 0.1%
19690520 1
< 0.1%
19690716 1
< 0.1%
ValueCountFrequency (%)
20210331 3
< 0.1%
20210330 6
0.1%
20210329 7
0.1%
20210326 4
< 0.1%
20210325 2
 
< 0.1%
20210324 4
< 0.1%
20210323 2
 
< 0.1%
20210322 5
0.1%
20210319 4
< 0.1%
20210318 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
7428 
1
2572 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7428
74.3%
1 2572
 
25.7%

Length

2024-04-17T21:33:47.981674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:48.049346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7428
74.3%
1 2572
 
25.7%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7428 
영업/정상
2572 

Length

Max length5
Median length2
Mean length2.7716
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7428
74.3%
영업/정상 2572
 
25.7%

Length

2024-04-17T21:33:48.128511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:48.200323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7428
74.3%
영업/정상 2572
 
25.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7428 
1
2572 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7428
74.3%
1 2572
 
25.7%

Length

2024-04-17T21:33:48.272406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:48.341474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7428
74.3%
1 2572
 
25.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7428 
영업
2572 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7428
74.3%
영업 2572
 
25.7%

Length

2024-04-17T21:33:48.412226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:48.480024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7428
74.3%
영업 2572
 
25.7%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct3367
Distinct (%)45.3%
Missing2572
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean20135054
Minimum10000101
Maximum20210331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:33:48.564233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000101
5-th percentile20020326
Q120091183
median20170504
Q320190726
95-th percentile20200923
Maximum20210331
Range10210230
Interquartile range (IQR)99543

Descriptive statistics

Standard deviation243430.29
Coefficient of variation (CV)0.012089875
Kurtosis1616.5276
Mean20135054
Median Absolute Deviation (MAD)29993.5
Skewness-38.888777
Sum1.4956318 × 1011
Variance5.9258307 × 1010
MonotonicityNot monotonic
2024-04-17T21:33:48.701276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021230 21
 
0.2%
20021011 17
 
0.2%
20100111 17
 
0.2%
20190930 15
 
0.1%
20190331 14
 
0.1%
20210317 14
 
0.1%
20110412 14
 
0.1%
20120222 13
 
0.1%
20200430 13
 
0.1%
20190228 13
 
0.1%
Other values (3357) 7277
72.8%
(Missing) 2572
 
25.7%
ValueCountFrequency (%)
10000101 4
< 0.1%
19890413 1
 
< 0.1%
19940614 1
 
< 0.1%
19940711 1
 
< 0.1%
19940913 1
 
< 0.1%
19941018 1
 
< 0.1%
19941024 1
 
< 0.1%
19941124 1
 
< 0.1%
19941207 1
 
< 0.1%
19950110 1
 
< 0.1%
ValueCountFrequency (%)
20210331 4
 
< 0.1%
20210330 9
0.1%
20210329 1
 
< 0.1%
20210328 3
 
< 0.1%
20210327 2
 
< 0.1%
20210326 2
 
< 0.1%
20210325 2
 
< 0.1%
20210324 11
0.1%
20210323 2
 
< 0.1%
20210322 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 

Distinct3476
Distinct (%)65.6%
Missing4705
Missing (%)47.0%
Memory size156.2 KiB
2024-04-17T21:33:48.973013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.704816
Min length1

Characters and Unicode

Total characters56682
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

Unique3137 ?
Unique (%)59.2%

Sample

1st row063246 4070
2nd row11171160 53
3rd row051 5008000
4th row051 721 7718
5th row051 7820289
ValueCountFrequency (%)
051 3881
31.9%
055 249
 
2.0%
031 222
 
1.8%
070 153
 
1.3%
831 135
 
1.1%
02 128
 
1.1%
053 96
 
0.8%
5711 88
 
0.7%
566 56
 
0.5%
2849 56
 
0.5%
Other values (3729) 7088
58.3%
2024-04-17T21:33:49.361821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9537
16.8%
5 8532
15.1%
1 7715
13.6%
7013
12.4%
2 4371
7.7%
3 3889
6.9%
8 3497
 
6.2%
7 3493
 
6.2%
6 3360
 
5.9%
4 3112
 
5.5%
Other values (2) 2163
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49668
87.6%
Space Separator 7013
 
12.4%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9537
19.2%
5 8532
17.2%
1 7715
15.5%
2 4371
8.8%
3 3889
7.8%
8 3497
 
7.0%
7 3493
 
7.0%
6 3360
 
6.8%
4 3112
 
6.3%
9 2162
 
4.4%
Space Separator
ValueCountFrequency (%)
7013
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56682
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9537
16.8%
5 8532
15.1%
1 7715
13.6%
7013
12.4%
2 4371
7.7%
3 3889
6.9%
8 3497
 
6.2%
7 3493
 
6.2%
6 3360
 
5.9%
4 3112
 
5.5%
Other values (2) 2163
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9537
16.8%
5 8532
15.1%
1 7715
13.6%
7013
12.4%
2 4371
7.7%
3 3889
6.9%
8 3497
 
6.2%
7 3493
 
6.2%
6 3360
 
5.9%
4 3112
 
5.5%
Other values (2) 2163
 
3.8%

소재지면적
Text

MISSING 

Distinct2024
Distinct (%)40.6%
Missing5020
Missing (%)50.2%
Memory size156.2 KiB
2024-04-17T21:33:49.669585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.5901606
Min length3

Characters and Unicode

Total characters22859
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

Unique1357 ?
Unique (%)27.2%

Sample

1st row1.70
2nd row7.20
3rd row29.25
4th row26.40
5th row.00
ValueCountFrequency (%)
00 290
 
5.8%
6.00 125
 
2.5%
3.00 114
 
2.3%
6.60 89
 
1.8%
3.30 72
 
1.4%
4.00 59
 
1.2%
9.90 51
 
1.0%
2.00 48
 
1.0%
10.00 48
 
1.0%
20.00 42
 
0.8%
Other values (2014) 4042
81.2%
2024-04-17T21:33:50.075518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4980
21.8%
0 4974
21.8%
1 2033
8.9%
2 1987
 
8.7%
3 1755
 
7.7%
6 1446
 
6.3%
5 1439
 
6.3%
4 1402
 
6.1%
8 1034
 
4.5%
7 908
 
4.0%
Other values (2) 901
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17876
78.2%
Other Punctuation 4983
 
21.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4974
27.8%
1 2033
11.4%
2 1987
 
11.1%
3 1755
 
9.8%
6 1446
 
8.1%
5 1439
 
8.0%
4 1402
 
7.8%
8 1034
 
5.8%
7 908
 
5.1%
9 898
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 4980
99.9%
, 3
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 22859
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4980
21.8%
0 4974
21.8%
1 2033
8.9%
2 1987
 
8.7%
3 1755
 
7.7%
6 1446
 
6.3%
5 1439
 
6.3%
4 1402
 
6.1%
8 1034
 
4.5%
7 908
 
4.0%
Other values (2) 901
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22859
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4980
21.8%
0 4974
21.8%
1 2033
8.9%
2 1987
 
8.7%
3 1755
 
7.7%
6 1446
 
6.3%
5 1439
 
6.3%
4 1402
 
6.1%
8 1034
 
4.5%
7 908
 
4.0%
Other values (2) 901
 
3.9%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct714
Distinct (%)7.3%
Missing223
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean611331.42
Minimum600011
Maximum642829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:33:50.195399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601803
Q1607835
median612020
Q3614816
95-th percentile617834
Maximum642829
Range42818
Interquartile range (IQR)6981

Descriptive statistics

Standard deviation4775.4828
Coefficient of variation (CV)0.0078116102
Kurtosis-0.06480265
Mean611331.42
Median Absolute Deviation (MAD)2827
Skewness-0.51605966
Sum5.9769873 × 109
Variance22805236
MonotonicityNot monotonic
2024-04-17T21:33:50.292234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
612020 570
 
5.7%
612851 222
 
2.2%
611807 207
 
2.1%
600017 204
 
2.0%
613819 204
 
2.0%
614847 185
 
1.8%
611840 152
 
1.5%
614843 144
 
1.4%
612811 142
 
1.4%
612824 135
 
1.4%
Other values (704) 7612
76.1%
(Missing) 223
 
2.2%
ValueCountFrequency (%)
600011 1
 
< 0.1%
600012 1
 
< 0.1%
600017 204
2.0%
600021 1
 
< 0.1%
600032 1
 
< 0.1%
600041 4
 
< 0.1%
600044 4
 
< 0.1%
600045 2
 
< 0.1%
600046 38
 
0.4%
600051 2
 
< 0.1%
ValueCountFrequency (%)
642829 1
 
< 0.1%
621250 1
 
< 0.1%
619953 10
 
0.1%
619952 1
 
< 0.1%
619951 10
 
0.1%
619913 3
 
< 0.1%
619912 38
0.4%
619911 5
 
0.1%
619906 82
0.8%
619905 64
0.6%
Distinct5363
Distinct (%)53.9%
Missing58
Missing (%)0.6%
Memory size156.2 KiB
2024-04-17T21:33:50.487572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length46
Mean length25.740897
Min length16

Characters and Unicode

Total characters255916
Distinct characters447
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

Unique4662 ?
Unique (%)46.9%

Sample

1st row부산광역시 중구 중앙동7가 20-1번지 롯데백화점광복점
2nd row부산광역시 해운대구 우동 1495번지 신세계백화점센텀시티점
3rd row부산광역시 수영구 남천동 545-2번지 메가마트 남천점
4th row부산광역시 수영구 남천동 545-2번지
5th row부산광역시 연제구 거제동 1208번지
ValueCountFrequency (%)
부산광역시 9940
 
20.8%
해운대구 1872
 
3.9%
부산진구 1459
 
3.0%
동래구 865
 
1.8%
연제구 794
 
1.7%
우동 785
 
1.6%
수영구 666
 
1.4%
부전동 544
 
1.1%
연산동 525
 
1.1%
금정구 499
 
1.0%
Other values (5829) 29946
62.5%
2024-04-17T21:33:50.793316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37967
 
14.8%
12849
 
5.0%
12557
 
4.9%
11448
 
4.5%
10633
 
4.2%
10366
 
4.1%
9950
 
3.9%
9784
 
3.8%
1 9770
 
3.8%
9706
 
3.8%
Other values (437) 120886
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162856
63.6%
Decimal Number 45046
 
17.6%
Space Separator 37967
 
14.8%
Dash Punctuation 7611
 
3.0%
Uppercase Letter 1124
 
0.4%
Open Punctuation 558
 
0.2%
Close Punctuation 555
 
0.2%
Other Punctuation 156
 
0.1%
Lowercase Letter 36
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12849
 
7.9%
12557
 
7.7%
11448
 
7.0%
10633
 
6.5%
10366
 
6.4%
9950
 
6.1%
9784
 
6.0%
9706
 
6.0%
8749
 
5.4%
2777
 
1.7%
Other values (389) 64037
39.3%
Uppercase Letter
ValueCountFrequency (%)
B 258
23.0%
S 196
17.4%
T 177
15.7%
G 151
13.4%
E 140
12.5%
K 48
 
4.3%
A 32
 
2.8%
H 21
 
1.9%
U 20
 
1.8%
Y 20
 
1.8%
Other values (11) 61
 
5.4%
Decimal Number
ValueCountFrequency (%)
1 9770
21.7%
2 6159
13.7%
5 4985
11.1%
3 4296
9.5%
4 4029
8.9%
0 3625
 
8.0%
7 3618
 
8.0%
6 3120
 
6.9%
9 2740
 
6.1%
8 2704
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 121
77.6%
@ 13
 
8.3%
. 11
 
7.1%
/ 6
 
3.8%
· 4
 
2.6%
& 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
s 15
41.7%
g 14
38.9%
e 4
 
11.1%
l 2
 
5.6%
i 1
 
2.8%
Space Separator
ValueCountFrequency (%)
37967
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7611
100.0%
Open Punctuation
ValueCountFrequency (%)
( 558
100.0%
Close Punctuation
ValueCountFrequency (%)
) 555
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162856
63.6%
Common 91899
35.9%
Latin 1161
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12849
 
7.9%
12557
 
7.7%
11448
 
7.0%
10633
 
6.5%
10366
 
6.4%
9950
 
6.1%
9784
 
6.0%
9706
 
6.0%
8749
 
5.4%
2777
 
1.7%
Other values (389) 64037
39.3%
Latin
ValueCountFrequency (%)
B 258
22.2%
S 196
16.9%
T 177
15.2%
G 151
13.0%
E 140
12.1%
K 48
 
4.1%
A 32
 
2.8%
H 21
 
1.8%
U 20
 
1.7%
Y 20
 
1.7%
Other values (17) 98
 
8.4%
Common
ValueCountFrequency (%)
37967
41.3%
1 9770
 
10.6%
- 7611
 
8.3%
2 6159
 
6.7%
5 4985
 
5.4%
3 4296
 
4.7%
4 4029
 
4.4%
0 3625
 
3.9%
7 3618
 
3.9%
6 3120
 
3.4%
Other values (11) 6719
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162856
63.6%
ASCII 93055
36.4%
None 4
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37967
40.8%
1 9770
 
10.5%
- 7611
 
8.2%
2 6159
 
6.6%
5 4985
 
5.4%
3 4296
 
4.6%
4 4029
 
4.3%
0 3625
 
3.9%
7 3618
 
3.9%
6 3120
 
3.4%
Other values (36) 7875
 
8.5%
Hangul
ValueCountFrequency (%)
12849
 
7.9%
12557
 
7.7%
11448
 
7.0%
10633
 
6.5%
10366
 
6.4%
9950
 
6.1%
9784
 
6.0%
9706
 
6.0%
8749
 
5.4%
2777
 
1.7%
Other values (389) 64037
39.3%
None
ValueCountFrequency (%)
· 4
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct4290
Distinct (%)58.0%
Missing2601
Missing (%)26.0%
Memory size156.2 KiB
2024-04-17T21:33:51.019093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length56
Mean length33.00419
Min length19

Characters and Unicode

Total characters244198
Distinct characters465
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

Unique3751 ?
Unique (%)50.7%

Sample

1st row부산광역시 중구 중앙대로 2, 롯데백화점광복점 (중앙동7가)
2nd row부산광역시 해운대구 센텀남대로 35, 신세계백화점센텀시티점 지하1층 (우동)
3rd row부산광역시 수영구 황령대로 521, 메가마트 남천점 1층 (남천동)
4th row부산광역시 기장군 기장읍 동암1길 17-27
5th row부산광역시 해운대구 해운대로61번길 95-47 (반여동)
ValueCountFrequency (%)
부산광역시 7397
 
15.7%
1층 1563
 
3.3%
해운대구 1346
 
2.9%
부산진구 931
 
2.0%
지하1층 755
 
1.6%
우동 623
 
1.3%
동래구 607
 
1.3%
연제구 587
 
1.2%
수영구 460
 
1.0%
사상구 436
 
0.9%
Other values (3977) 32268
68.7%
2024-04-17T21:33:51.353793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39595
 
16.2%
9599
 
3.9%
9526
 
3.9%
9397
 
3.8%
1 8424
 
3.4%
8417
 
3.4%
7963
 
3.3%
7459
 
3.1%
7407
 
3.0%
7372
 
3.0%
Other values (455) 129039
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151730
62.1%
Space Separator 39595
 
16.2%
Decimal Number 30204
 
12.4%
Open Punctuation 7328
 
3.0%
Close Punctuation 7326
 
3.0%
Other Punctuation 6216
 
2.5%
Uppercase Letter 964
 
0.4%
Dash Punctuation 687
 
0.3%
Lowercase Letter 137
 
0.1%
Math Symbol 9
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9599
 
6.3%
9526
 
6.3%
9397
 
6.2%
8417
 
5.5%
7963
 
5.2%
7459
 
4.9%
7407
 
4.9%
7372
 
4.9%
5016
 
3.3%
3149
 
2.1%
Other values (401) 76425
50.4%
Uppercase Letter
ValueCountFrequency (%)
S 225
23.3%
G 167
17.3%
B 150
15.6%
E 143
14.8%
C 51
 
5.3%
K 45
 
4.7%
A 43
 
4.5%
N 31
 
3.2%
H 20
 
2.1%
Y 18
 
1.9%
Other values (12) 71
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 8424
27.9%
2 4389
14.5%
3 2986
 
9.9%
5 2827
 
9.4%
7 2490
 
8.2%
4 2378
 
7.9%
0 1811
 
6.0%
9 1659
 
5.5%
8 1638
 
5.4%
6 1602
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
s 62
45.3%
g 55
40.1%
c 5
 
3.6%
n 5
 
3.6%
e 4
 
2.9%
i 2
 
1.5%
l 2
 
1.5%
h 1
 
0.7%
b 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 6195
99.7%
@ 11
 
0.2%
· 5
 
0.1%
/ 2
 
< 0.1%
. 2
 
< 0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
39595
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7328
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7326
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 687
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151728
62.1%
Common 91366
37.4%
Latin 1102
 
0.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9599
 
6.3%
9526
 
6.3%
9397
 
6.2%
8417
 
5.5%
7963
 
5.2%
7459
 
4.9%
7407
 
4.9%
7372
 
4.9%
5016
 
3.3%
3149
 
2.1%
Other values (400) 76423
50.4%
Latin
ValueCountFrequency (%)
S 225
20.4%
G 167
15.2%
B 150
13.6%
E 143
13.0%
s 62
 
5.6%
g 55
 
5.0%
C 51
 
4.6%
K 45
 
4.1%
A 43
 
3.9%
N 31
 
2.8%
Other values (22) 130
11.8%
Common
ValueCountFrequency (%)
39595
43.3%
1 8424
 
9.2%
( 7328
 
8.0%
) 7326
 
8.0%
, 6195
 
6.8%
2 4389
 
4.8%
3 2986
 
3.3%
5 2827
 
3.1%
7 2490
 
2.7%
4 2378
 
2.6%
Other values (12) 7428
 
8.1%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151728
62.1%
ASCII 92462
37.9%
None 5
 
< 0.1%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39595
42.8%
1 8424
 
9.1%
( 7328
 
7.9%
) 7326
 
7.9%
, 6195
 
6.7%
2 4389
 
4.7%
3 2986
 
3.2%
5 2827
 
3.1%
7 2490
 
2.7%
4 2378
 
2.6%
Other values (42) 8524
 
9.2%
Hangul
ValueCountFrequency (%)
9599
 
6.3%
9526
 
6.3%
9397
 
6.2%
8417
 
5.5%
7963
 
5.2%
7459
 
4.9%
7407
 
4.9%
7372
 
4.9%
5016
 
3.3%
3149
 
2.1%
Other values (400) 76423
50.4%
None
ValueCountFrequency (%)
· 5
100.0%
CJK
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1159
Distinct (%)15.8%
Missing2656
Missing (%)26.6%
Infinite0
Infinite (%)0.0%
Mean47742.415
Minimum46002
Maximum51498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:33:51.462147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46084
Q147124
median47814.5
Q348313
95-th percentile49326
Maximum51498
Range5496
Interquartile range (IQR)1189

Descriptive statistics

Standard deviation927.02472
Coefficient of variation (CV)0.019417215
Kurtosis-0.68488447
Mean47742.415
Median Absolute Deviation (MAD)586.5
Skewness-0.049092955
Sum3.506203 × 108
Variance859374.83
MonotonicityNot monotonic
2024-04-17T21:33:51.567584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48058 433
 
4.3%
48944 202
 
2.0%
48096 186
 
1.9%
47285 180
 
1.8%
48313 160
 
1.6%
47500 150
 
1.5%
47604 123
 
1.2%
46233 119
 
1.2%
46970 115
 
1.1%
47727 94
 
0.9%
Other values (1149) 5582
55.8%
(Missing) 2656
26.6%
ValueCountFrequency (%)
46002 1
 
< 0.1%
46005 1
 
< 0.1%
46006 1
 
< 0.1%
46007 4
 
< 0.1%
46008 9
 
0.1%
46010 2
 
< 0.1%
46012 7
 
0.1%
46013 6
 
0.1%
46015 44
0.4%
46016 4
 
< 0.1%
ValueCountFrequency (%)
51498 1
 
< 0.1%
50981 1
 
< 0.1%
49525 1
 
< 0.1%
49524 1
 
< 0.1%
49522 1
 
< 0.1%
49521 2
 
< 0.1%
49520 1
 
< 0.1%
49519 52
0.5%
49518 2
 
< 0.1%
49516 2
 
< 0.1%
Distinct5274
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T21:33:52.054320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length5.842
Min length1

Characters and Unicode

Total characters58420
Distinct characters847
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

Unique4319 ?
Unique (%)43.2%

Sample

1st row대현유통
2nd row아띠몽
3rd row친구
4th row윤플러스
5th row(주)선달의 고집
ValueCountFrequency (%)
주식회사 196
 
1.8%
현승유통 134
 
1.2%
현재상사 119
 
1.1%
주경식품 113
 
1.0%
주)정성 95
 
0.9%
주)모두랑식품 94
 
0.8%
부산축산 86
 
0.8%
수지int's 84
 
0.8%
주)미트벨리 84
 
0.8%
아라식품 80
 
0.7%
Other values (5498) 10046
90.3%
2024-04-17T21:33:52.422084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2213
 
3.8%
) 2019
 
3.5%
( 1970
 
3.4%
1521
 
2.6%
1445
 
2.5%
1132
 
1.9%
1121
 
1.9%
896
 
1.5%
896
 
1.5%
835
 
1.4%
Other values (837) 44372
76.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51743
88.6%
Close Punctuation 2019
 
3.5%
Open Punctuation 1970
 
3.4%
Space Separator 1132
 
1.9%
Uppercase Letter 737
 
1.3%
Lowercase Letter 480
 
0.8%
Other Punctuation 157
 
0.3%
Decimal Number 151
 
0.3%
Dash Punctuation 21
 
< 0.1%
Modifier Symbol 4
 
< 0.1%
Other values (4) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2213
 
4.3%
1521
 
2.9%
1445
 
2.8%
1121
 
2.2%
896
 
1.7%
896
 
1.7%
835
 
1.6%
776
 
1.5%
766
 
1.5%
727
 
1.4%
Other values (760) 40547
78.4%
Uppercase Letter
ValueCountFrequency (%)
N 119
16.1%
T 118
16.0%
S 112
15.2%
I 107
14.5%
F 33
 
4.5%
E 25
 
3.4%
A 24
 
3.3%
O 23
 
3.1%
D 19
 
2.6%
C 19
 
2.6%
Other values (16) 138
18.7%
Lowercase Letter
ValueCountFrequency (%)
e 66
13.8%
o 61
12.7%
a 41
 
8.5%
r 29
 
6.0%
s 29
 
6.0%
l 29
 
6.0%
n 27
 
5.6%
i 25
 
5.2%
t 21
 
4.4%
m 20
 
4.2%
Other values (13) 132
27.5%
Decimal Number
ValueCountFrequency (%)
2 32
21.2%
1 29
19.2%
0 22
14.6%
3 14
9.3%
5 12
 
7.9%
4 11
 
7.3%
7 10
 
6.6%
6 9
 
6.0%
8 8
 
5.3%
9 4
 
2.6%
Other Punctuation
ValueCountFrequency (%)
' 93
59.2%
. 27
 
17.2%
& 19
 
12.1%
, 7
 
4.5%
· 4
 
2.5%
: 3
 
1.9%
! 2
 
1.3%
% 1
 
0.6%
/ 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 2019
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1970
100.0%
Space Separator
ValueCountFrequency (%)
1132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51740
88.6%
Common 5457
 
9.3%
Latin 1218
 
2.1%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2213
 
4.3%
1521
 
2.9%
1445
 
2.8%
1121
 
2.2%
896
 
1.7%
896
 
1.7%
835
 
1.6%
776
 
1.5%
766
 
1.5%
727
 
1.4%
Other values (756) 40544
78.4%
Latin
ValueCountFrequency (%)
N 119
 
9.8%
T 118
 
9.7%
S 112
 
9.2%
I 107
 
8.8%
e 66
 
5.4%
o 61
 
5.0%
a 41
 
3.4%
F 33
 
2.7%
r 29
 
2.4%
s 29
 
2.4%
Other values (40) 503
41.3%
Common
ValueCountFrequency (%)
) 2019
37.0%
( 1970
36.1%
1132
20.7%
' 93
 
1.7%
2 32
 
0.6%
1 29
 
0.5%
. 27
 
0.5%
0 22
 
0.4%
- 21
 
0.4%
& 19
 
0.3%
Other values (16) 93
 
1.7%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51737
88.6%
ASCII 6670
 
11.4%
None 6
 
< 0.1%
CJK 5
 
< 0.1%
Number Forms 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2213
 
4.3%
1521
 
2.9%
1445
 
2.8%
1121
 
2.2%
896
 
1.7%
896
 
1.7%
835
 
1.6%
776
 
1.5%
766
 
1.5%
727
 
1.4%
Other values (754) 40541
78.4%
ASCII
ValueCountFrequency (%)
) 2019
30.3%
( 1970
29.5%
1132
17.0%
N 119
 
1.8%
T 118
 
1.8%
S 112
 
1.7%
I 107
 
1.6%
' 93
 
1.4%
e 66
 
1.0%
o 61
 
0.9%
Other values (64) 873
13.1%
None
ValueCountFrequency (%)
· 4
66.7%
2
33.3%
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)

Distinct7609
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0144448 × 1013
Minimum1.9990223 × 1013
Maximum2.0210331 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:33:52.567891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990223 × 1013
5-th percentile2.0020612 × 1013
Q12.010042 × 1013
median2.0171122 × 1013
Q32.0190925 × 1013
95-th percentile2.0201123 × 1013
Maximum2.0210331 × 1013
Range2.2010817 × 1011
Interquartile range (IQR)9.0505015 × 1010

Descriptive statistics

Standard deviation6.2230312 × 1010
Coefficient of variation (CV)0.0030892041
Kurtosis-0.50762748
Mean2.0144448 × 1013
Median Absolute Deviation (MAD)2.9495477 × 1010
Skewness-0.91939851
Sum2.0144448 × 1017
Variance3.8726117 × 1021
MonotonicityNot monotonic
2024-04-17T21:33:52.693135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020305000000 56
 
0.6%
20020612000000 56
 
0.6%
20010728000000 47
 
0.5%
20020621000000 42
 
0.4%
20020611000000 38
 
0.4%
20020821000000 37
 
0.4%
20020724000000 30
 
0.3%
20020708000000 29
 
0.3%
20020723000000 28
 
0.3%
20010918000000 26
 
0.3%
Other values (7599) 9611
96.1%
ValueCountFrequency (%)
19990223000000 1
 
< 0.1%
19990304000000 12
0.1%
19990305000000 3
 
< 0.1%
19990318000000 12
0.1%
19990319000000 13
0.1%
19990322000000 2
 
< 0.1%
19990323000000 3
 
< 0.1%
19990324000000 3
 
< 0.1%
19990326000000 5
 
0.1%
19990329000000 1
 
< 0.1%
ValueCountFrequency (%)
20210331165955 1
< 0.1%
20210331161928 1
< 0.1%
20210331141318 1
< 0.1%
20210331132815 1
< 0.1%
20210331114813 1
< 0.1%
20210331114507 1
< 0.1%
20210331104406 1
< 0.1%
20210331101107 1
< 0.1%
20210331093543 1
< 0.1%
20210331041509 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6241 
U
3759 

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 6241
62.4%
U 3759
37.6%

Length

2024-04-17T21:33:52.807919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:52.884466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6241
62.4%
u 3759
37.6%
Distinct1033
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-02 02:40:00
2024-04-17T21:33:52.976208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T21:33:53.084623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9982 
기타
 
14
단란주점
 
1
한식
 
1
<NA>
 
1

Length

Max length9
Median length9
Mean length8.9884
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9982
99.8%
기타 14
 
0.1%
단란주점 1
 
< 0.1%
한식 1
 
< 0.1%
<NA> 1
 
< 0.1%
식육(숯불구이) 1
 
< 0.1%

Length

2024-04-17T21:33:53.192436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:53.276150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9982
99.8%
기타 14
 
0.1%
단란주점 1
 
< 0.1%
한식 1
 
< 0.1%
na 1
 
< 0.1%
식육(숯불구이 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3612
Distinct (%)37.2%
Missing299
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean389193.84
Minimum353660.89
Maximum407121.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:33:53.367907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum353660.89
5-th percentile380225.64
Q1385848.87
median389097.8
Q3392658.67
95-th percentile398256.72
Maximum407121.88
Range53460.992
Interquartile range (IQR)6809.7986

Descriptive statistics

Standard deviation5532.7016
Coefficient of variation (CV)0.0142158
Kurtosis0.50302374
Mean389193.84
Median Absolute Deviation (MAD)3497.6373
Skewness-0.037698568
Sum3.7755694 × 109
Variance30610787
MonotonicityNot monotonic
2024-04-17T21:33:53.468736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393952.264486105 322
 
3.2%
387271.299492377 289
 
2.9%
397397.83276594 219
 
2.2%
385590.814676765 193
 
1.9%
392321.102334852 190
 
1.9%
387686.194940483 172
 
1.7%
387539.767677801 168
 
1.7%
389532.511756755 147
 
1.5%
390208.09260128 133
 
1.3%
389455.109101676 126
 
1.3%
Other values (3602) 7742
77.4%
(Missing) 299
 
3.0%
ValueCountFrequency (%)
353660.889782036 1
 
< 0.1%
364626.145566093 1
 
< 0.1%
366798.269419272 1
 
< 0.1%
366820.787750249 1
 
< 0.1%
366829.531355754 3
< 0.1%
367011.799190228 1
 
< 0.1%
367055.286163177 1
 
< 0.1%
367088.901392071 1
 
< 0.1%
367181.407269982 1
 
< 0.1%
367451.087635496 4
< 0.1%
ValueCountFrequency (%)
407121.882187494 1
 
< 0.1%
407036.696092095 3
< 0.1%
407018.507643148 1
 
< 0.1%
406902.163143777 1
 
< 0.1%
406761.100883744 1
 
< 0.1%
405709.608315206 1
 
< 0.1%
405688.580680087 1
 
< 0.1%
405546.316597851 1
 
< 0.1%
405511.30268554 1
 
< 0.1%
405484.920224281 1
 
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct3614
Distinct (%)37.3%
Missing299
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean187527
Minimum169678.05
Maximum210458.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:33:53.573395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169678.05
5-th percentile178737.05
Q1184402.97
median187546.05
Q3190792.1
95-th percentile196546.36
Maximum210458.38
Range40780.328
Interquartile range (IQR)6389.1291

Descriptive statistics

Standard deviation5468.4856
Coefficient of variation (CV)0.029161057
Kurtosis0.81622105
Mean187527
Median Absolute Deviation (MAD)3143.0883
Skewness0.35607471
Sum1.8191995 × 109
Variance29904334
MonotonicityNot monotonic
2024-04-17T21:33:53.684081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187602.933160728 322
 
3.2%
186099.137533193 289
 
2.9%
187354.835259309 219
 
2.2%
179553.867031936 193
 
1.9%
184041.758684038 190
 
1.9%
189911.430545728 172
 
1.7%
184402.96650913 168
 
1.7%
188309.453546847 147
 
1.5%
196546.356333373 133
 
1.3%
191427.549247975 126
 
1.3%
Other values (3604) 7742
77.4%
(Missing) 299
 
3.0%
ValueCountFrequency (%)
169678.048271107 1
< 0.1%
173914.718015169 1
< 0.1%
174097.616386311 1
< 0.1%
174181.52961765 1
< 0.1%
174211.496764498 1
< 0.1%
174289.976688419 1
< 0.1%
174422.480246459 1
< 0.1%
174491.469961028 1
< 0.1%
174587.185782495 1
< 0.1%
174632.012941701 1
< 0.1%
ValueCountFrequency (%)
210458.376643536 1
 
< 0.1%
207670.589017254 1
 
< 0.1%
206690.833564719 1
 
< 0.1%
206512.517255249 3
< 0.1%
206350.248639167 1
 
< 0.1%
206335.787689029 1
 
< 0.1%
206184.609573703 1
 
< 0.1%
206150.925111083 2
< 0.1%
206113.876185521 1
 
< 0.1%
206087.417102782 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9978 
기타
 
14
<NA>
 
5
단란주점
 
1
한식
 
1

Length

Max length9
Median length9
Mean length8.9864
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9978
99.8%
기타 14
 
0.1%
<NA> 5
 
0.1%
단란주점 1
 
< 0.1%
한식 1
 
< 0.1%
식육(숯불구이) 1
 
< 0.1%

Length

2024-04-17T21:33:53.793374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:53.875305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9978
99.8%
기타 14
 
0.1%
na 5
 
< 0.1%
단란주점 1
 
< 0.1%
한식 1
 
< 0.1%
식육(숯불구이 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9235 
0
 
737
1
 
28

Length

Max length4
Median length4
Mean length3.7705
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> 9235
92.3%
0 737
 
7.4%
1 28
 
0.3%

Length

2024-04-17T21:33:53.975803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:54.053723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9235
92.3%
0 737
 
7.4%
1 28
 
0.3%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9234 
0
 
737
1
 
29

Length

Max length4
Median length4
Mean length3.7702
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> 9234
92.3%
0 737
 
7.4%
1 29
 
0.3%

Length

2024-04-17T21:33:54.130652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:54.204744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9234
92.3%
0 737
 
7.4%
1 29
 
0.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8237 
기타
1672 
주택가주변
 
74
아파트지역
 
14
유흥업소밀집지역
 
2

Length

Max length8
Median length4
Mean length3.6756
Min length2

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> 8237
82.4%
기타 1672
 
16.7%
주택가주변 74
 
0.7%
아파트지역 14
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(상대) 1
 
< 0.1%

Length

2024-04-17T21:33:54.282302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:54.361960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8237
82.4%
기타 1672
 
16.7%
주택가주변 74
 
0.7%
아파트지역 14
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(상대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8237 
기타
1618 
자율
 
145

Length

Max length4
Median length4
Mean length3.6474
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> 8237
82.4%
기타 1618
 
16.2%
자율 145
 
1.5%

Length

2024-04-17T21:33:54.454430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:54.530915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8237
82.4%
기타 1618
 
16.2%
자율 145
 
1.5%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8514 
상수도전용
1483 
지하수전용
 
3

Length

Max length5
Median length4
Mean length4.1486
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> 8514
85.1%
상수도전용 1483
 
14.8%
지하수전용 3
 
< 0.1%

Length

2024-04-17T21:33:54.608819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:54.682580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8514
85.1%
상수도전용 1483
 
14.8%
지하수전용 3
 
< 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>
6565 
0
3431 
1
 
4

Length

Max length4
Median length4
Mean length2.9695
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6565
65.6%
0 3431
34.3%
1 4
 
< 0.1%

Length

2024-04-17T21:33:54.765874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:54.841483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6565
65.6%
0 3431
34.3%
1 4
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6565 
0
3435 

Length

Max length4
Median length4
Mean length2.9695
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6565
65.6%
0 3435
34.4%

Length

2024-04-17T21:33:54.920168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:54.995406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6565
65.6%
0 3435
34.4%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6560 
0
3417 
1
 
20
2
 
2
3
 
1

Length

Max length4
Median length4
Mean length2.968
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6560
65.6%
0 3417
34.2%
1 20
 
0.2%
2 2
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T21:33:55.080017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:55.184854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6560
65.6%
0 3417
34.2%
1 20
 
0.2%
2 2
 
< 0.1%
3 1
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6560 
0
3409 
1
 
28
2
 
2
10
 
1

Length

Max length4
Median length4
Mean length2.9681
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6560
65.6%
0 3409
34.1%
1 28
 
0.3%
2 2
 
< 0.1%
10 1
 
< 0.1%

Length

2024-04-17T21:33:55.281888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:55.359453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6560
65.6%
0 3409
34.1%
1 28
 
0.3%
2 2
 
< 0.1%
10 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7818 
자가
1375 
임대
807 

Length

Max length4
Median length4
Mean length3.5636
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7818
78.2%
자가 1375
 
13.8%
임대 807
 
8.1%

Length

2024-04-17T21:33:55.447205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:55.523599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7818
78.2%
자가 1375
 
13.8%
임대 807
 
8.1%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9421 
0
 
578
300
 
1

Length

Max length4
Median length4
Mean length3.8265
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9421
94.2%
0 578
 
5.8%
300 1
 
< 0.1%

Length

2024-04-17T21:33:55.604870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:55.686435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9421
94.2%
0 578
 
5.8%
300 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9421 
0
 
578
30
 
1

Length

Max length4
Median length4
Mean length3.8264
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9421
94.2%
0 578
 
5.8%
30 1
 
< 0.1%

Length

2024-04-17T21:33:55.763403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:33:55.836591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9421
94.2%
0 578
 
5.8%
30 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size97.7 KiB
False
9996 
(Missing)
 
4
ValueCountFrequency (%)
False 9996
> 99.9%
(Missing) 4
 
< 0.1%
2024-04-17T21:33:55.890696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct399
Distinct (%)4.0%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.2965126
Minimum0
Maximum318.51
Zeros9384
Zeros (%)93.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:33:55.964648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.3
Maximum318.51
Range318.51
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.0312011
Coefficient of variation (CV)6.9657642
Kurtosis383.81825
Mean1.2965126
Median Absolute Deviation (MAD)0
Skewness15.808233
Sum12959.94
Variance81.562594
MonotonicityNot monotonic
2024-04-17T21:33:56.089902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9384
93.8%
3.3 26
 
0.3%
9.9 15
 
0.1%
2.0 15
 
0.1%
6.0 10
 
0.1%
3.0 10
 
0.1%
10.0 9
 
0.1%
19.8 8
 
0.1%
12.0 6
 
0.1%
15.0 6
 
0.1%
Other values (389) 507
 
5.1%
ValueCountFrequency (%)
0.0 9384
93.8%
0.4 1
 
< 0.1%
0.49 1
 
< 0.1%
0.69 1
 
< 0.1%
0.75 1
 
< 0.1%
0.84 1
 
< 0.1%
0.94 1
 
< 0.1%
0.95 1
 
< 0.1%
1.0 3
 
< 0.1%
1.01 1
 
< 0.1%
ValueCountFrequency (%)
318.51 1
< 0.1%
281.0 1
< 0.1%
239.0 1
< 0.1%
233.9 1
< 0.1%
140.4 1
< 0.1%
135.54 1
< 0.1%
133.33 1
< 0.1%
130.0 1
< 0.1%
122.0 1
< 0.1%
120.15 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
90939094즉석판매제조가공업07_22_19_P32500003250000-107-2019-0014820191015<NA>3폐업2폐업20191114<NA><NA><NA>063246 4070<NA>600017부산광역시 중구 중앙동7가 20-1번지 롯데백화점광복점부산광역시 중구 중앙대로 2, 롯데백화점광복점 (중앙동7가)48944대현유통20191115041509U2019-11-19 02:40:00.0즉석판매제조가공업385590.814677179553.867032즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1006210063즉석판매제조가공업07_22_19_P33300003330000-107-2020-0009820200310<NA>3폐업2폐업20200322<NA><NA><NA><NA><NA>612020부산광역시 해운대구 우동 1495번지 신세계백화점센텀시티점부산광역시 해운대구 센텀남대로 35, 신세계백화점센텀시티점 지하1층 (우동)48058아띠몽20200323041509U2020-03-25 02:40:00.0즉석판매제조가공업393952.264486187602.933161즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1243512436즉석판매제조가공업07_22_19_P33800003380000-107-2018-0005720180530<NA>3폐업2폐업20180620<NA><NA><NA><NA><NA>613819부산광역시 수영구 남천동 545-2번지 메가마트 남천점부산광역시 수영구 황령대로 521, 메가마트 남천점 1층 (남천동)48313친구20180620094002I2018-08-31 23:59:59.0즉석판매제조가공업392321.102335184041.758684즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1999819999즉석판매제조가공업07_22_19_P33800003380000-107-2004-0000420040109<NA>3폐업2폐업20040302<NA><NA><NA>11171160 531.70613819부산광역시 수영구 남천동 545-2번지<NA><NA>윤플러스20040109000000I2018-08-31 23:59:59.0즉석판매제조가공업392321.102335184041.758684즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA><NA>
97889789즉석판매제조가공업07_22_19_P33700003370000-107-2003-0001220030326<NA>3폐업2폐업20070409<NA><NA><NA>051 50080007.20611807부산광역시 연제구 거제동 1208번지<NA><NA>(주)선달의 고집20071115160135I2018-08-31 23:59:59.0즉석판매제조가공업387686.19494189911.430546즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
17561757즉석판매제조가공업07_22_19_P34000003400000-107-2013-0000820130415<NA>1영업/정상1영업<NA><NA><NA><NA>051 721 771829.25619902부산광역시 기장군 기장읍 시랑리 111-2번지부산광역시 기장군 기장읍 동암1길 17-2746083풍원장20130415120223I2018-08-31 23:59:59.0즉석판매제조가공업402450.839973190909.558053즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
35603561즉석판매제조가공업07_22_19_P33300003330000-107-2009-0011420090630<NA>1영업/정상1영업<NA><NA><NA><NA>051 782028926.40612813부산광역시 해운대구 반여동 1291-1430번지부산광역시 해운대구 해운대로61번길 95-47 (반여동)48029화목식육점20111201105958I2018-08-31 23:59:59.0즉석판매제조가공업393793.804774190578.07223즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
1390213903즉석판매제조가공업07_22_19_P32900003290000-107-2020-0024520200811<NA>3폐업2폐업20200826<NA><NA><NA><NA><NA>614801부산광역시 부산진구 가야동 624-7 가야홈플러스부산광역시 부산진구 가야대로 506, 가야홈플러스 (가야동)47324부산축산홈플러스가야점20200827041509U2020-08-29 02:40:00.0즉석판매제조가공업384668.52046185579.964272즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1180411805즉석판매제조가공업07_22_19_P33300003330000-107-2017-0020720170612<NA>3폐업2폐업20170628<NA><NA><NA><NA><NA>612851부산광역시 해운대구 중동 1767번지부산광역시 해운대구 좌동순환로 511 (중동, 이마트 해운대점)48096(주)미래식품20170629041529I2018-08-31 23:59:59.0즉석판매제조가공업397397.832766187354.835259즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
2024920250즉석판매제조가공업07_22_19_P33700003370000-107-2020-0013420200902<NA>3폐업2폐업20200916<NA><NA><NA>031 792 4950<NA>611811부산광역시 연제구 연산동 105-1 홈플러스 부산연산점부산광역시 연제구 반송로 88, 홈플러스 부산연산점 (연산동)47552(주)부광 농협하나로마트판부점20200917041508U2020-09-19 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>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
28582859즉석판매제조가공업07_22_19_P32900003290000-107-2010-0001420100217<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.97614813부산광역시 부산진구 개금동 171-165 개금시장내부산광역시 부산진구 가야대로482번길 26 (개금동,개금시장내)47328소문난남도댁김치20200922134820U2020-09-24 02:40:00.0즉석판매제조가공업384419.746446185506.28026즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N26.97<NA><NA><NA><NA>
1394513946즉석판매제조가공업07_22_19_P33300003330000-107-2020-0030120200701<NA>3폐업2폐업20200705<NA><NA><NA><NA><NA>612020부산광역시 해운대구 우동 1467 영화의전당부산광역시 해운대구 수영강변대로 120, 영화의전당 (우동)48058남포조인트마켓20200706041508U2020-07-08 02:40:00.0즉석판매제조가공업393724.655115187847.348783즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1331113312즉석판매제조가공업07_22_19_P33300003330000-107-2000-0080520001208<NA>3폐업2폐업20080304<NA><NA><NA>051 545262654.21612800부산광역시 해운대구 반송동 62-492번지 (지상1층)<NA><NA>백송떡방앗간20080225145645I2018-08-31 23:59:59.0즉석판매제조가공업396244.325805194525.803203즉석판매제조가공업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1710817109즉석판매제조가공업07_22_19_P33000003300000-107-2015-0002920150902<NA>3폐업2폐업20150915<NA><NA><NA><NA><NA>607842부산광역시 동래구 온천동 1452-42번지부산광역시 동래구 충렬대로108번길 45 (온천동)47825홍삼의신비20150902171937I2018-08-31 23:59:59.0즉석판매제조가공업388716.154061191461.137529즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1513515136즉석판매제조가공업07_22_19_P33500003350000-107-2007-0003920070903<NA>3폐업2폐업20090810<NA><NA><NA>051 580 77006.00609819부산광역시 금정구 부곡동 223-1번지<NA><NA>청룡제과20070914110633I2018-08-31 23:59:59.0즉석판매제조가공업390319.153767195305.783616즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
2134221343즉석판매제조가공업07_22_19_P32700003270000-107-1991-0002419911203<NA>3폐업2폐업20040831<NA><NA><NA>051 646061615.61601824부산광역시 동구 좌천동 734-4번지<NA><NA>제일참기름20040614000000I2018-08-31 23:59:59.0즉석판매제조가공업387032.269081183797.006914즉석판매제조가공업00기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
1365513656즉석판매제조가공업07_22_19_P33300003330000-107-2018-0028020180806<NA>3폐업2폐업20180814<NA><NA><NA>02 473 7910<NA>612836부산광역시 해운대구 좌동 1467-4번지 지팝건축물부산광역시 해운대구 해운대로 813, 지팝건축물 B1층 (좌동)48106(주)신풍특산20180815041531I2018-08-31 23:59:59.0즉석판매제조가공업398269.051542187874.778091즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1013710138즉석판매제조가공업07_22_19_P33300003330000-107-2020-0010420200316<NA>3폐업2폐업20200326<NA><NA><NA><NA><NA>612020부산광역시 해운대구 우동 1496번지 롯데백화점센텀시티점부산광역시 해운대구 센텀남대로 59, 롯데백화점센텀시티점 지하1층 (우동)48058초림단지묵20200327041509U2020-03-29 02:40:00.0즉석판매제조가공업394083.501538187707.586118즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
558559즉석판매제조가공업07_22_19_P33700003370000-107-2018-0019120180523<NA>1영업/정상1영업<NA><NA><NA><NA>070 420075992.00611811부산광역시 연제구 연산동 312-22번지부산광역시 연제구 연동로8번길 16, 1층 (연산동)47552목화식당20200422114127U2020-04-24 02:40:00.0즉석판매제조가공업390537.796782189724.093678즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
38573858즉석판매제조가공업07_22_19_P33000003300000-107-1993-0008019930422<NA>1영업/정상1영업<NA><NA><NA><NA>051 502245236.75607814부산광역시 동래구 사직동 54-29번지부산광역시 동래구 사직북로28번길 63-3 (사직동)47857새로운떡방앗간20160825104004I2018-08-31 23:59:59.0즉석판매제조가공업387784.698726190940.742745즉석판매제조가공업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>