Overview

Dataset statistics

Number of variables48
Number of observations10000
Missing cells108301
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

Description2021-01-04
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 (99.0%)Imbalance
위생업태명 is highly imbalanced (99.0%)Imbalance
남성종사자수 is highly imbalanced (79.4%)Imbalance
여성종사자수 is highly imbalanced (74.2%)Imbalance
영업장주변구분명 is highly imbalanced (67.5%)Imbalance
등급구분명 is highly imbalanced (61.4%)Imbalance
급수시설구분명 is highly imbalanced (72.6%)Imbalance
공장판매직종업원수 is highly imbalanced (51.7%)Imbalance
공장생산직종업원수 is highly imbalanced (51.7%)Imbalance
보증액 is highly imbalanced (78.9%)Imbalance
월세액 is highly imbalanced (78.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2555 (25.6%) 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 4538 (45.4%) missing valuesMissing
소재지면적 has 4835 (48.4%) missing valuesMissing
소재지우편번호 has 213 (2.1%) missing valuesMissing
도로명전체주소 has 2715 (27.2%) missing valuesMissing
도로명우편번호 has 2766 (27.7%) missing valuesMissing
좌표정보(x) has 305 (3.0%) missing valuesMissing
좌표정보(y) has 305 (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 = -38.93046685)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 9361 (93.6%) zerosZeros

Reproduction

Analysis started2024-04-17 12:39:46.125148
Analysis finished2024-04-17 12:39:47.940126
Duration1.81 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%
Mean11251.471
Minimum2
Maximum22378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:39:47.998732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile1075.95
Q15575.75
median11282.5
Q316912.25
95-th percentile21341.1
Maximum22378
Range22376
Interquartile range (IQR)11336.5

Descriptive statistics

Standard deviation6492.858
Coefficient of variation (CV)0.57706749
Kurtosis-1.2108417
Mean11251.471
Median Absolute Deviation (MAD)5670
Skewness-0.015382676
Sum1.1251471 × 108
Variance42157205
MonotonicityNot monotonic
2024-04-17T21:39:48.097354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13386 1
 
< 0.1%
5944 1
 
< 0.1%
16092 1
 
< 0.1%
18193 1
 
< 0.1%
22302 1
 
< 0.1%
15855 1
 
< 0.1%
21311 1
 
< 0.1%
2904 1
 
< 0.1%
12829 1
 
< 0.1%
2774 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
7 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
20 1
< 0.1%
ValueCountFrequency (%)
22378 1
< 0.1%
22376 1
< 0.1%
22375 1
< 0.1%
22371 1
< 0.1%
22370 1
< 0.1%
22369 1
< 0.1%
22368 1
< 0.1%
22367 1
< 0.1%
22365 1
< 0.1%
22362 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

2024-04-17T21:39:48.186262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:48.256270image/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

2024-04-17T21:39:48.324059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:48.398181image/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%
Mean3326220
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:39:48.484038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3270000
Q13290000
median3330000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation39240.102
Coefficient of variation (CV)0.011797206
Kurtosis-0.84888797
Mean3326220
Median Absolute Deviation (MAD)40000
Skewness0.17914662
Sum3.32622 × 1010
Variance1.5397856 × 109
MonotonicityNot monotonic
2024-04-17T21:39:48.574156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1938
19.4%
3290000 1585
15.8%
3300000 935
9.3%
3370000 752
 
7.5%
3380000 657
 
6.6%
3340000 529
 
5.3%
3350000 528
 
5.3%
3390000 469
 
4.7%
3320000 447
 
4.5%
3400000 446
 
4.5%
Other values (6) 1714
17.1%
ValueCountFrequency (%)
3250000 277
 
2.8%
3260000 211
 
2.1%
3270000 311
 
3.1%
3280000 376
 
3.8%
3290000 1585
15.8%
3300000 935
9.3%
3310000 436
 
4.4%
3320000 447
 
4.5%
3330000 1938
19.4%
3340000 529
 
5.3%
ValueCountFrequency (%)
3400000 446
 
4.5%
3390000 469
 
4.7%
3380000 657
 
6.6%
3370000 752
 
7.5%
3360000 103
 
1.0%
3350000 528
 
5.3%
3340000 529
 
5.3%
3330000 1938
19.4%
3320000 447
 
4.5%
3310000 436
 
4.4%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T21:39:48.744149image/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 row3290000-107-2018-00153
2nd row3380000-107-2018-00071
3rd row3300000-107-2017-00237
4th row3260000-107-2019-00011
5th row3320000-107-2006-00004
ValueCountFrequency (%)
3290000-107-2018-00153 1
 
< 0.1%
3290000-107-2010-00063 1
 
< 0.1%
3330000-107-2017-00267 1
 
< 0.1%
3400000-107-2018-00032 1
 
< 0.1%
3290000-107-2018-00110 1
 
< 0.1%
3380000-107-2000-00077 1
 
< 0.1%
3330000-107-2011-00104 1
 
< 0.1%
3340000-107-2010-00011 1
 
< 0.1%
3330000-107-2008-00125 1
 
< 0.1%
3320000-107-2002-00732 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T21:39:49.011628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 91917
41.8%
- 30000
 
13.6%
1 21897
 
10.0%
3 21817
 
9.9%
2 16720
 
7.6%
7 14180
 
6.4%
9 8385
 
3.8%
8 4479
 
2.0%
4 3775
 
1.7%
5 3527
 
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 91917
48.4%
1 21897
 
11.5%
3 21817
 
11.5%
2 16720
 
8.8%
7 14180
 
7.5%
9 8385
 
4.4%
8 4479
 
2.4%
4 3775
 
2.0%
5 3527
 
1.9%
6 3303
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 91917
41.8%
- 30000
 
13.6%
1 21897
 
10.0%
3 21817
 
9.9%
2 16720
 
7.6%
7 14180
 
6.4%
9 8385
 
3.8%
8 4479
 
2.0%
4 3775
 
1.7%
5 3527
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 91917
41.8%
- 30000
 
13.6%
1 21897
 
10.0%
3 21817
 
9.9%
2 16720
 
7.6%
7 14180
 
6.4%
9 8385
 
3.8%
8 4479
 
2.0%
4 3775
 
1.7%
5 3527
 
1.6%

인허가일자
Real number (ℝ)

Distinct4534
Distinct (%)45.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20103812
Minimum19390516
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:39:49.133003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19390516
5-th percentile19880912
Q120041085
median20150310
Q320190409
95-th percentile20200803
Maximum20201231
Range810715
Interquartile range (IQR)149324.25

Descriptive statistics

Standard deviation104940.08
Coefficient of variation (CV)0.0052199093
Kurtosis1.6752887
Mean20103812
Median Absolute Deviation (MAD)50001
Skewness-1.3510779
Sum2.0103812 × 1011
Variance1.1012419 × 1010
MonotonicityNot monotonic
2024-04-17T21:39:49.261635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190930 20
 
0.2%
20190225 18
 
0.2%
20200420 18
 
0.2%
20200629 16
 
0.2%
20190401 15
 
0.1%
20190531 15
 
0.1%
20200310 15
 
0.1%
19760407 14
 
0.1%
20190702 14
 
0.1%
20190718 13
 
0.1%
Other values (4524) 9842
98.4%
ValueCountFrequency (%)
19390516 1
 
< 0.1%
19640629 1
 
< 0.1%
19650614 1
 
< 0.1%
19670513 1
 
< 0.1%
19680430 1
 
< 0.1%
19681129 1
 
< 0.1%
19690113 3
< 0.1%
19690429 1
 
< 0.1%
19690430 1
 
< 0.1%
19690516 1
 
< 0.1%
ValueCountFrequency (%)
20201231 4
 
< 0.1%
20201230 2
 
< 0.1%
20201229 8
0.1%
20201228 6
0.1%
20201224 11
0.1%
20201223 8
0.1%
20201222 8
0.1%
20201221 6
0.1%
20201218 6
0.1%
20201217 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
7445 
1
2555 

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 7445
74.5%
1 2555
 
25.6%

Length

2024-04-17T21:39:49.390142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:49.479895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7445
74.5%
1 2555
 
25.6%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7445 
영업/정상
2555 

Length

Max length5
Median length2
Mean length2.7665
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7445
74.5%
영업/정상 2555
 
25.6%

Length

2024-04-17T21:39:49.567314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:49.655780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7445
74.5%
영업/정상 2555
 
25.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7445 
1
2555 

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 7445
74.5%
1 2555
 
25.6%

Length

2024-04-17T21:39:49.728784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:49.796764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7445
74.5%
1 2555
 
25.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7445 
영업
2555 

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 7445
74.5%
영업 2555
 
25.6%

Length

2024-04-17T21:39:49.873208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:49.944082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7445
74.5%
영업 2555
 
25.6%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct3434
Distinct (%)46.1%
Missing2555
Missing (%)25.6%
Infinite0
Infinite (%)0.0%
Mean20132613
Minimum10000101
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:39:50.037374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000101
5-th percentile20020308
Q120090824
median20170126
Q320190626
95-th percentile20200812
Maximum20201231
Range10201130
Interquartile range (IQR)99802

Descriptive statistics

Standard deviation243097.84
Coefficient of variation (CV)0.012074828
Kurtosis1620.1186
Mean20132613
Median Absolute Deviation (MAD)30283
Skewness-38.930467
Sum1.4988731 × 1011
Variance5.9096558 × 1010
MonotonicityNot monotonic
2024-04-17T21:39:50.146020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021011 28
 
0.3%
20100111 19
 
0.2%
20021230 18
 
0.2%
20100208 17
 
0.2%
20051102 17
 
0.2%
20191016 15
 
0.1%
20201104 14
 
0.1%
20200930 14
 
0.1%
20200311 13
 
0.1%
20200506 13
 
0.1%
Other values (3424) 7277
72.8%
(Missing) 2555
 
25.6%
ValueCountFrequency (%)
10000101 4
< 0.1%
19920731 1
 
< 0.1%
19940120 1
 
< 0.1%
19940816 1
 
< 0.1%
19940913 1
 
< 0.1%
19941018 1
 
< 0.1%
19941124 1
 
< 0.1%
19941207 1
 
< 0.1%
19950110 1
 
< 0.1%
19950626 2
< 0.1%
ValueCountFrequency (%)
20201231 1
 
< 0.1%
20201230 1
 
< 0.1%
20201229 1
 
< 0.1%
20201228 1
 
< 0.1%
20201224 1
 
< 0.1%
20201223 1
 
< 0.1%
20201222 1
 
< 0.1%
20201221 1
 
< 0.1%
20201220 3
< 0.1%
20201218 4
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

소재지전화
Text

MISSING 

Distinct3609
Distinct (%)66.1%
Missing4538
Missing (%)45.4%
Memory size156.2 KiB
2024-04-17T21:39:50.424148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.670267
Min length3

Characters and Unicode

Total characters58281
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

Unique3263 ?
Unique (%)59.7%

Sample

1st row053 850 9853
2nd row051 262 2637
3rd row051 727 5997
4th row051 5828406
5th row051 4687546
ValueCountFrequency (%)
051 4004
32.3%
055 242
 
2.0%
031 230
 
1.9%
070 160
 
1.3%
831 142
 
1.1%
02 140
 
1.1%
5711 87
 
0.7%
053 84
 
0.7%
5624 51
 
0.4%
062 50
 
0.4%
Other values (3847) 7200
58.1%
2024-04-17T21:39:50.787609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9809
16.8%
5 8820
15.1%
1 8001
13.7%
7110
12.2%
2 4515
7.7%
3 4011
6.9%
8 3691
 
6.3%
7 3584
 
6.1%
6 3411
 
5.9%
4 3137
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51171
87.8%
Space Separator 7110
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9809
19.2%
5 8820
17.2%
1 8001
15.6%
2 4515
8.8%
3 4011
7.8%
8 3691
 
7.2%
7 3584
 
7.0%
6 3411
 
6.7%
4 3137
 
6.1%
9 2192
 
4.3%
Space Separator
ValueCountFrequency (%)
7110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58281
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9809
16.8%
5 8820
15.1%
1 8001
13.7%
7110
12.2%
2 4515
7.7%
3 4011
6.9%
8 3691
 
6.3%
7 3584
 
6.1%
6 3411
 
5.9%
4 3137
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58281
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9809
16.8%
5 8820
15.1%
1 8001
13.7%
7110
12.2%
2 4515
7.7%
3 4011
6.9%
8 3691
 
6.3%
7 3584
 
6.1%
6 3411
 
5.9%
4 3137
 
5.4%

소재지면적
Text

MISSING 

Distinct2028
Distinct (%)39.3%
Missing4835
Missing (%)48.4%
Memory size156.2 KiB
2024-04-17T21:39:51.102631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.5903195
Min length3

Characters and Unicode

Total characters23709
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

Unique1354 ?
Unique (%)26.2%

Sample

1st row14.74
2nd row20.00
3rd row33.70
4th row34.40
5th row22.00
ValueCountFrequency (%)
00 289
 
5.6%
3.00 123
 
2.4%
6.00 117
 
2.3%
6.60 81
 
1.6%
3.30 77
 
1.5%
4.00 67
 
1.3%
2.00 62
 
1.2%
12.00 53
 
1.0%
20.00 50
 
1.0%
5.00 49
 
0.9%
Other values (2018) 4197
81.3%
2024-04-17T21:39:51.501293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5307
22.4%
. 5165
21.8%
2 2154
9.1%
1 2094
 
8.8%
3 1768
 
7.5%
6 1478
 
6.2%
4 1415
 
6.0%
5 1382
 
5.8%
8 1076
 
4.5%
9 976
 
4.1%
Other values (2) 894
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18543
78.2%
Other Punctuation 5166
 
21.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5307
28.6%
2 2154
11.6%
1 2094
 
11.3%
3 1768
 
9.5%
6 1478
 
8.0%
4 1415
 
7.6%
5 1382
 
7.5%
8 1076
 
5.8%
9 976
 
5.3%
7 893
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 5165
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 23709
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5307
22.4%
. 5165
21.8%
2 2154
9.1%
1 2094
 
8.8%
3 1768
 
7.5%
6 1478
 
6.2%
4 1415
 
6.0%
5 1382
 
5.8%
8 1076
 
4.5%
9 976
 
4.1%
Other values (2) 894
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23709
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5307
22.4%
. 5165
21.8%
2 2154
9.1%
1 2094
 
8.8%
3 1768
 
7.5%
6 1478
 
6.2%
4 1415
 
6.0%
5 1382
 
5.8%
8 1076
 
4.5%
9 976
 
4.1%
Other values (2) 894
 
3.8%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct713
Distinct (%)7.3%
Missing213
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean611339.17
Minimum600012
Maximum642829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:39:51.620481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600012
5-th percentile601812.6
Q1607835
median612020
Q3614814
95-th percentile617832.7
Maximum642829
Range42817
Interquartile range (IQR)6979

Descriptive statistics

Standard deviation4663.7716
Coefficient of variation (CV)0.0076287793
Kurtosis-0.016006648
Mean611339.17
Median Absolute Deviation (MAD)2827
Skewness-0.51303353
Sum5.9831764 × 109
Variance21750766
MonotonicityNot monotonic
2024-04-17T21:39:51.910698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
612020 615
 
6.2%
612851 218
 
2.2%
611807 202
 
2.0%
614847 198
 
2.0%
613819 188
 
1.9%
600017 170
 
1.7%
614843 151
 
1.5%
612811 151
 
1.5%
609847 146
 
1.5%
607804 138
 
1.4%
Other values (703) 7610
76.1%
(Missing) 213
 
2.1%
ValueCountFrequency (%)
600012 1
 
< 0.1%
600016 1
 
< 0.1%
600017 170
1.7%
600032 1
 
< 0.1%
600041 4
 
< 0.1%
600044 3
 
< 0.1%
600045 2
 
< 0.1%
600046 35
 
0.4%
600061 3
 
< 0.1%
600062 1
 
< 0.1%
ValueCountFrequency (%)
642829 1
 
< 0.1%
619953 10
 
0.1%
619952 2
 
< 0.1%
619951 9
 
0.1%
619913 3
 
< 0.1%
619912 30
 
0.3%
619911 4
 
< 0.1%
619906 77
0.8%
619905 62
0.6%
619904 12
 
0.1%
Distinct5387
Distinct (%)54.2%
Missing63
Missing (%)0.6%
Memory size156.2 KiB
2024-04-17T21:39:52.112771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length52
Mean length25.718627
Min length15

Characters and Unicode

Total characters255566
Distinct characters450
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

Unique4647 ?
Unique (%)46.8%

Sample

1st row부산광역시 부산진구 가야동 624-7번지 가야홈플러스
2nd row부산광역시 수영구 남천동 545-2번지 메가마트 남천점
3rd row부산광역시 동래구 명장동 23-2번지 GS슈퍼마켓
4th row부산광역시 서구 서대신동2가 213-8번지 탑마트
5th row부산광역시 북구 화명동 194-2번지 GS슈퍼내
ValueCountFrequency (%)
부산광역시 9936
 
20.9%
해운대구 1936
 
4.1%
부산진구 1539
 
3.2%
동래구 927
 
1.9%
우동 797
 
1.7%
연제구 752
 
1.6%
수영구 657
 
1.4%
부전동 588
 
1.2%
사하구 529
 
1.1%
금정구 521
 
1.1%
Other values (5759) 29427
61.8%
2024-04-17T21:39:52.439161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37681
 
14.7%
12942
 
5.1%
12555
 
4.9%
11477
 
4.5%
10628
 
4.2%
10301
 
4.0%
10017
 
3.9%
9945
 
3.9%
9817
 
3.8%
1 9722
 
3.8%
Other values (440) 120481
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162659
63.6%
Decimal Number 45100
 
17.6%
Space Separator 37681
 
14.7%
Dash Punctuation 7549
 
3.0%
Uppercase Letter 1182
 
0.5%
Open Punctuation 590
 
0.2%
Close Punctuation 589
 
0.2%
Other Punctuation 172
 
0.1%
Lowercase Letter 35
 
< 0.1%
Math Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12942
 
8.0%
12555
 
7.7%
11477
 
7.1%
10628
 
6.5%
10301
 
6.3%
10017
 
6.2%
9945
 
6.1%
9817
 
6.0%
9029
 
5.6%
2791
 
1.7%
Other values (392) 63157
38.8%
Uppercase Letter
ValueCountFrequency (%)
B 277
23.4%
S 232
19.6%
T 191
16.2%
G 175
14.8%
E 124
10.5%
K 53
 
4.5%
A 27
 
2.3%
Y 25
 
2.1%
H 24
 
2.0%
U 24
 
2.0%
Other values (10) 30
 
2.5%
Decimal Number
ValueCountFrequency (%)
1 9722
21.6%
2 6119
13.6%
5 4994
11.1%
3 4370
9.7%
4 4070
9.0%
0 3604
 
8.0%
7 3548
 
7.9%
6 3147
 
7.0%
9 2781
 
6.2%
8 2745
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
s 15
42.9%
g 14
40.0%
e 2
 
5.7%
b 1
 
2.9%
a 1
 
2.9%
t 1
 
2.9%
p 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 127
73.8%
. 20
 
11.6%
· 11
 
6.4%
@ 11
 
6.4%
/ 3
 
1.7%
Space Separator
ValueCountFrequency (%)
37681
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7549
100.0%
Open Punctuation
ValueCountFrequency (%)
( 590
100.0%
Close Punctuation
ValueCountFrequency (%)
) 589
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162659
63.6%
Common 91689
35.9%
Latin 1218
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12942
 
8.0%
12555
 
7.7%
11477
 
7.1%
10628
 
6.5%
10301
 
6.3%
10017
 
6.2%
9945
 
6.1%
9817
 
6.0%
9029
 
5.6%
2791
 
1.7%
Other values (392) 63157
38.8%
Latin
ValueCountFrequency (%)
B 277
22.7%
S 232
19.0%
T 191
15.7%
G 175
14.4%
E 124
10.2%
K 53
 
4.4%
A 27
 
2.2%
Y 25
 
2.1%
H 24
 
2.0%
U 24
 
2.0%
Other values (18) 66
 
5.4%
Common
ValueCountFrequency (%)
37681
41.1%
1 9722
 
10.6%
- 7549
 
8.2%
2 6119
 
6.7%
5 4994
 
5.4%
3 4370
 
4.8%
4 4070
 
4.4%
0 3604
 
3.9%
7 3548
 
3.9%
6 3147
 
3.4%
Other values (10) 6885
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162659
63.6%
ASCII 92895
36.3%
None 11
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37681
40.6%
1 9722
 
10.5%
- 7549
 
8.1%
2 6119
 
6.6%
5 4994
 
5.4%
3 4370
 
4.7%
4 4070
 
4.4%
0 3604
 
3.9%
7 3548
 
3.8%
6 3147
 
3.4%
Other values (36) 8091
 
8.7%
Hangul
ValueCountFrequency (%)
12942
 
8.0%
12555
 
7.7%
11477
 
7.1%
10628
 
6.5%
10301
 
6.3%
10017
 
6.2%
9945
 
6.1%
9817
 
6.0%
9029
 
5.6%
2791
 
1.7%
Other values (392) 63157
38.8%
None
ValueCountFrequency (%)
· 11
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct4223
Distinct (%)58.0%
Missing2715
Missing (%)27.2%
Memory size156.2 KiB
2024-04-17T21:39:52.701286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length57
Mean length32.855731
Min length19

Characters and Unicode

Total characters239354
Distinct characters480
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

Unique3662 ?
Unique (%)50.3%

Sample

1st row부산광역시 부산진구 가야대로 506, 가야홈플러스 (가야동)
2nd row부산광역시 수영구 황령대로 521, 메가마트 남천점 1층 (남천동)
3rd row부산광역시 동래구 반송로 291 (명장동)
4th row부산광역시 서구 대영로 5, 탑마트 (서대신동2가)
5th row부산광역시 금정구 금정로 52, 1층 (장전동)
ValueCountFrequency (%)
부산광역시 7284
 
15.9%
1층 1446
 
3.1%
해운대구 1397
 
3.0%
부산진구 960
 
2.1%
지하1층 751
 
1.6%
동래구 668
 
1.5%
우동 623
 
1.4%
연제구 537
 
1.2%
수영구 452
 
1.0%
센텀남대로 427
 
0.9%
Other values (3917) 31382
68.3%
2024-04-17T21:39:53.107714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38666
 
16.2%
9503
 
4.0%
9422
 
3.9%
9178
 
3.8%
8295
 
3.5%
1 8260
 
3.5%
7762
 
3.2%
7367
 
3.1%
7289
 
3.0%
) 7244
 
3.0%
Other values (470) 126368
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148701
62.1%
Space Separator 38666
 
16.2%
Decimal Number 29724
 
12.4%
Close Punctuation 7245
 
3.0%
Open Punctuation 7244
 
3.0%
Other Punctuation 6004
 
2.5%
Uppercase Letter 972
 
0.4%
Dash Punctuation 657
 
0.3%
Lowercase Letter 128
 
0.1%
Math Symbol 11
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9503
 
6.4%
9422
 
6.3%
9178
 
6.2%
8295
 
5.6%
7762
 
5.2%
7367
 
5.0%
7289
 
4.9%
7235
 
4.9%
5084
 
3.4%
3027
 
2.0%
Other values (414) 74539
50.1%
Uppercase Letter
ValueCountFrequency (%)
S 248
25.5%
G 178
18.3%
B 159
16.4%
E 125
12.9%
K 49
 
5.0%
C 40
 
4.1%
A 37
 
3.8%
N 25
 
2.6%
H 24
 
2.5%
Y 23
 
2.4%
Other values (13) 64
 
6.6%
Decimal Number
ValueCountFrequency (%)
1 8260
27.8%
2 4287
14.4%
3 3045
 
10.2%
5 2699
 
9.1%
7 2462
 
8.3%
4 2346
 
7.9%
0 1718
 
5.8%
9 1679
 
5.6%
6 1621
 
5.5%
8 1607
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
s 59
46.1%
g 49
38.3%
n 7
 
5.5%
c 7
 
5.5%
i 2
 
1.6%
e 2
 
1.6%
a 1
 
0.8%
b 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 5972
99.5%
· 12
 
0.2%
. 10
 
0.2%
@ 7
 
0.1%
/ 2
 
< 0.1%
* 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 7244
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 7243
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
38666
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 657
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 148700
62.1%
Common 89552
37.4%
Latin 1101
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9503
 
6.4%
9422
 
6.3%
9178
 
6.2%
8295
 
5.6%
7762
 
5.2%
7367
 
5.0%
7289
 
4.9%
7235
 
4.9%
5084
 
3.4%
3027
 
2.0%
Other values (413) 74538
50.1%
Latin
ValueCountFrequency (%)
S 248
22.5%
G 178
16.2%
B 159
14.4%
E 125
11.4%
s 59
 
5.4%
g 49
 
4.5%
K 49
 
4.5%
C 40
 
3.6%
A 37
 
3.4%
N 25
 
2.3%
Other values (22) 132
12.0%
Common
ValueCountFrequency (%)
38666
43.2%
1 8260
 
9.2%
) 7244
 
8.1%
( 7243
 
8.1%
, 5972
 
6.7%
2 4287
 
4.8%
3 3045
 
3.4%
5 2699
 
3.0%
7 2462
 
2.7%
4 2346
 
2.6%
Other values (14) 7328
 
8.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148700
62.1%
ASCII 90640
37.9%
None 12
 
< 0.1%
Number Forms 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38666
42.7%
1 8260
 
9.1%
) 7244
 
8.0%
( 7243
 
8.0%
, 5972
 
6.6%
2 4287
 
4.7%
3 3045
 
3.4%
5 2699
 
3.0%
7 2462
 
2.7%
4 2346
 
2.6%
Other values (44) 8416
 
9.3%
Hangul
ValueCountFrequency (%)
9503
 
6.4%
9422
 
6.3%
9178
 
6.2%
8295
 
5.6%
7762
 
5.2%
7367
 
5.0%
7289
 
4.9%
7235
 
4.9%
5084
 
3.4%
3027
 
2.0%
Other values (413) 74538
50.1%
None
ValueCountFrequency (%)
· 12
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1128
Distinct (%)15.6%
Missing2766
Missing (%)27.7%
Infinite0
Infinite (%)0.0%
Mean47753.366
Minimum46002
Maximum51498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:39:53.218158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46211.9
Q147181
median47850
Q348301
95-th percentile49347
Maximum51498
Range5496
Interquartile range (IQR)1120

Descriptive statistics

Standard deviation911.61095
Coefficient of variation (CV)0.019089983
Kurtosis-0.61408565
Mean47753.366
Median Absolute Deviation (MAD)576
Skewness-0.057952051
Sum3.4544785 × 108
Variance831034.52
MonotonicityNot monotonic
2024-04-17T21:39:53.314992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48058 438
 
4.4%
47285 195
 
1.9%
48096 186
 
1.9%
48944 168
 
1.7%
48313 148
 
1.5%
47500 143
 
1.4%
46233 126
 
1.3%
47727 109
 
1.1%
46970 98
 
1.0%
47737 98
 
1.0%
Other values (1118) 5525
55.2%
(Missing) 2766
27.7%
ValueCountFrequency (%)
46002 1
 
< 0.1%
46003 2
 
< 0.1%
46004 1
 
< 0.1%
46007 1
 
< 0.1%
46008 13
 
0.1%
46010 3
 
< 0.1%
46012 5
 
0.1%
46013 3
 
< 0.1%
46015 43
0.4%
46016 2
 
< 0.1%
ValueCountFrequency (%)
51498 1
 
< 0.1%
49524 2
 
< 0.1%
49523 2
 
< 0.1%
49522 1
 
< 0.1%
49520 2
 
< 0.1%
49519 44
0.4%
49518 3
 
< 0.1%
49516 2
 
< 0.1%
49515 4
 
< 0.1%
49514 2
 
< 0.1%
Distinct5346
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T21:39:53.531641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length24
Mean length5.8885
Min length1

Characters and Unicode

Total characters58885
Distinct characters835
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4391 ?
Unique (%)43.9%

Sample

1st row알앤알코리아
2nd row(주)미트벨리
3rd row현재상사
4th row현재상사
5th row디케이엔트프라이즈
ValueCountFrequency (%)
주식회사 203
 
1.8%
현승유통 128
 
1.1%
현재상사 118
 
1.1%
주)정성 107
 
1.0%
주)모두랑식품 93
 
0.8%
주경식품 91
 
0.8%
부산축산 82
 
0.7%
주)미트벨리 80
 
0.7%
수지int's 73
 
0.7%
오에스푸드 72
 
0.6%
Other values (5584) 10140
90.6%
2024-04-17T21:39:53.867875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2267
 
3.8%
) 2072
 
3.5%
( 2034
 
3.5%
1554
 
2.6%
1418
 
2.4%
1188
 
2.0%
1087
 
1.8%
926
 
1.6%
919
 
1.6%
838
 
1.4%
Other values (825) 44582
75.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52191
88.6%
Close Punctuation 2072
 
3.5%
Open Punctuation 2034
 
3.5%
Space Separator 1188
 
2.0%
Uppercase Letter 714
 
1.2%
Lowercase Letter 350
 
0.6%
Decimal Number 163
 
0.3%
Other Punctuation 149
 
0.3%
Dash Punctuation 17
 
< 0.1%
Modifier Symbol 3
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2267
 
4.3%
1554
 
3.0%
1418
 
2.7%
1087
 
2.1%
926
 
1.8%
919
 
1.8%
838
 
1.6%
824
 
1.6%
778
 
1.5%
719
 
1.4%
Other values (749) 40861
78.3%
Uppercase Letter
ValueCountFrequency (%)
N 108
15.1%
T 105
14.7%
S 105
14.7%
I 95
13.3%
F 36
 
5.0%
O 29
 
4.1%
A 26
 
3.6%
C 24
 
3.4%
E 24
 
3.4%
G 21
 
2.9%
Other values (16) 141
19.7%
Lowercase Letter
ValueCountFrequency (%)
e 54
15.4%
a 35
 
10.0%
o 25
 
7.1%
i 22
 
6.3%
s 21
 
6.0%
r 18
 
5.1%
l 18
 
5.1%
t 18
 
5.1%
u 16
 
4.6%
d 15
 
4.3%
Other values (14) 108
30.9%
Decimal Number
ValueCountFrequency (%)
1 34
20.9%
2 33
20.2%
0 26
16.0%
5 16
9.8%
3 16
9.8%
4 12
 
7.4%
6 8
 
4.9%
7 8
 
4.9%
9 5
 
3.1%
8 5
 
3.1%
Other Punctuation
ValueCountFrequency (%)
' 77
51.7%
. 29
 
19.5%
& 27
 
18.1%
, 10
 
6.7%
· 2
 
1.3%
/ 2
 
1.3%
; 1
 
0.7%
! 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 2072
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2034
100.0%
Space Separator
ValueCountFrequency (%)
1188
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52187
88.6%
Common 5629
 
9.6%
Latin 1064
 
1.8%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2267
 
4.3%
1554
 
3.0%
1418
 
2.7%
1087
 
2.1%
926
 
1.8%
919
 
1.8%
838
 
1.6%
824
 
1.6%
778
 
1.5%
719
 
1.4%
Other values (745) 40857
78.3%
Latin
ValueCountFrequency (%)
N 108
 
10.2%
T 105
 
9.9%
S 105
 
9.9%
I 95
 
8.9%
e 54
 
5.1%
F 36
 
3.4%
a 35
 
3.3%
O 29
 
2.7%
A 26
 
2.4%
o 25
 
2.3%
Other values (40) 446
41.9%
Common
ValueCountFrequency (%)
) 2072
36.8%
( 2034
36.1%
1188
21.1%
' 77
 
1.4%
1 34
 
0.6%
2 33
 
0.6%
. 29
 
0.5%
& 27
 
0.5%
0 26
 
0.5%
- 17
 
0.3%
Other values (15) 92
 
1.6%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52185
88.6%
ASCII 6691
 
11.4%
CJK 5
 
< 0.1%
None 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2267
 
4.3%
1554
 
3.0%
1418
 
2.7%
1087
 
2.1%
926
 
1.8%
919
 
1.8%
838
 
1.6%
824
 
1.6%
778
 
1.5%
719
 
1.4%
Other values (743) 40855
78.3%
ASCII
ValueCountFrequency (%)
) 2072
31.0%
( 2034
30.4%
1188
17.8%
N 108
 
1.6%
T 105
 
1.6%
S 105
 
1.6%
I 95
 
1.4%
' 77
 
1.2%
e 54
 
0.8%
F 36
 
0.5%
Other values (64) 817
 
12.2%
None
ValueCountFrequency (%)
· 2
66.7%
1
33.3%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct7641
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0141563 × 1013
Minimum1.9990218 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:39:53.982982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile2.0020612 × 1013
Q12.0100204 × 1013
median2.0170716 × 1013
Q32.0190806 × 1013
95-th percentile2.0200917 × 1013
Maximum2.0201231 × 1013
Range2.1101317 × 1011
Interquartile range (IQR)9.0602483 × 1010

Descriptive statistics

Standard deviation6.2294055 × 1010
Coefficient of variation (CV)0.0030928114
Kurtosis-0.60095852
Mean2.0141563 × 1013
Median Absolute Deviation (MAD)2.98055 × 1010
Skewness-0.87562931
Sum2.0141563 × 1017
Variance3.8805493 × 1021
MonotonicityNot monotonic
2024-04-17T21:39:54.084187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020305000000 53
 
0.5%
20020612000000 53
 
0.5%
20010728000000 49
 
0.5%
20020821000000 38
 
0.4%
20020611000000 38
 
0.4%
20020621000000 38
 
0.4%
20020724000000 33
 
0.3%
20020723000000 29
 
0.3%
20020828000000 29
 
0.3%
20010918000000 26
 
0.3%
Other values (7631) 9614
96.1%
ValueCountFrequency (%)
19990218000000 1
 
< 0.1%
19990223000000 1
 
< 0.1%
19990302000000 1
 
< 0.1%
19990304000000 13
0.1%
19990305000000 1
 
< 0.1%
19990318000000 17
0.2%
19990319000000 13
0.1%
19990322000000 1
 
< 0.1%
19990323000000 4
 
< 0.1%
19990324000000 4
 
< 0.1%
ValueCountFrequency (%)
20201231174349 1
< 0.1%
20201231170956 1
< 0.1%
20201231165923 1
< 0.1%
20201231162757 1
< 0.1%
20201231160157 1
< 0.1%
20201231143517 1
< 0.1%
20201231101451 1
< 0.1%
20201231092415 1
< 0.1%
20201230171343 1
< 0.1%
20201230155158 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6477 
U
3523 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6477
64.8%
U 3523
35.2%

Length

2024-04-17T21:39:54.174573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:54.240689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6477
64.8%
u 3523
35.2%
Distinct955
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-02 02:40:00
2024-04-17T21:39:54.316839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T21:39:54.419835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9983 
기타
 
15
식육(숯불구이)
 
1
한식
 
1

Length

Max length9
Median length9
Mean length8.9887
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9983
99.8%
기타 15
 
0.1%
식육(숯불구이) 1
 
< 0.1%
한식 1
 
< 0.1%

Length

2024-04-17T21:39:54.522360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:54.600835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9983
99.8%
기타 15
 
0.1%
식육(숯불구이 1
 
< 0.1%
한식 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3585
Distinct (%)37.0%
Missing305
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean389224.19
Minimum353660.89
Maximum407418.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:39:54.687908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum353660.89
5-th percentile380225.64
Q1385983.55
median389097.8
Q3392709.65
95-th percentile398220.21
Maximum407418.65
Range53757.759
Interquartile range (IQR)6726.1011

Descriptive statistics

Standard deviation5469.485
Coefficient of variation (CV)0.014052274
Kurtosis0.55475071
Mean389224.19
Median Absolute Deviation (MAD)3410.5156
Skewness-0.057715163
Sum3.7735285 × 109
Variance29915266
MonotonicityNot monotonic
2024-04-17T21:39:54.793914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393952.264486105 333
 
3.3%
387271.299492377 312
 
3.1%
397397.83276594 217
 
2.2%
392321.102334852 171
 
1.7%
387686.194940483 165
 
1.7%
385590.814676765 161
 
1.6%
389097.800933845 152
 
1.5%
387539.767677801 150
 
1.5%
390208.09260128 140
 
1.4%
394083.501537578 138
 
1.4%
Other values (3575) 7756
77.6%
(Missing) 305
 
3.0%
ValueCountFrequency (%)
353660.889782036 1
 
< 0.1%
366820.787750249 1
 
< 0.1%
366829.531355754 4
< 0.1%
366931.435995074 1
 
< 0.1%
367027.575037614 1
 
< 0.1%
367041.984452276 1
 
< 0.1%
367055.286163177 1
 
< 0.1%
367169.234957368 1
 
< 0.1%
367451.087635496 8
0.1%
370718.68095386 2
 
< 0.1%
ValueCountFrequency (%)
407418.648415535 1
< 0.1%
407121.882187494 1
< 0.1%
407036.696092095 1
< 0.1%
407018.507643148 1
< 0.1%
406982.053033795 1
< 0.1%
406910.100470872 1
< 0.1%
405709.608315206 1
< 0.1%
405688.580680087 1
< 0.1%
405449.335650942 1
< 0.1%
405372.254329784 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct3587
Distinct (%)37.0%
Missing305
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean187569.81
Minimum174097.62
Maximum210945.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:39:54.898781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174097.62
5-th percentile178774.55
Q1184648.92
median187602.93
Q3190922.52
95-th percentile196545.92
Maximum210945.1
Range36847.488
Interquartile range (IQR)6273.5973

Descriptive statistics

Standard deviation5392.2455
Coefficient of variation (CV)0.028747939
Kurtosis0.88495607
Mean187569.81
Median Absolute Deviation (MAD)3181.0425
Skewness0.33404986
Sum1.8184893 × 109
Variance29076312
MonotonicityNot monotonic
2024-04-17T21:39:55.014028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187602.933160728 333
 
3.3%
186099.137533193 312
 
3.1%
187354.835259309 217
 
2.2%
184041.758684038 171
 
1.7%
189911.430545728 165
 
1.7%
179553.867031936 161
 
1.6%
192260.811648263 152
 
1.5%
184402.96650913 150
 
1.5%
196546.356333373 140
 
1.4%
187707.586117775 138
 
1.4%
Other values (3577) 7756
77.6%
(Missing) 305
 
3.0%
ValueCountFrequency (%)
174097.616386311 1
 
< 0.1%
174156.617297535 1
 
< 0.1%
174333.833259042 1
 
< 0.1%
174422.480246459 1
 
< 0.1%
174526.100850246 1
 
< 0.1%
174632.012941701 1
 
< 0.1%
174638.869997904 3
< 0.1%
174673.620114069 1
 
< 0.1%
174764.901715256 1
 
< 0.1%
174825.510853792 1
 
< 0.1%
ValueCountFrequency (%)
210945.104382171 1
 
< 0.1%
210458.376643536 1
 
< 0.1%
209383.598383269 1
 
< 0.1%
207739.619868549 1
 
< 0.1%
207716.999117547 1
 
< 0.1%
206803.94845946 1
 
< 0.1%
206739.517959242 1
 
< 0.1%
206690.833564719 1
 
< 0.1%
206512.517255249 3
< 0.1%
206335.787689029 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9980 
기타
 
15
<NA>
 
3
식육(숯불구이)
 
1
한식
 
1

Length

Max length9
Median length9
Mean length8.9872
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9980
99.8%
기타 15
 
0.1%
<NA> 3
 
< 0.1%
식육(숯불구이) 1
 
< 0.1%
한식 1
 
< 0.1%

Length

2024-04-17T21:39:55.118433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:55.202286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9980
99.8%
기타 15
 
0.1%
na 3
 
< 0.1%
식육(숯불구이 1
 
< 0.1%
한식 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9222 
0
 
750
1
 
27
2
 
1

Length

Max length4
Median length4
Mean length3.7666
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9222
92.2%
0 750
 
7.5%
1 27
 
0.3%
2 1
 
< 0.1%

Length

2024-04-17T21:39:55.286393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:55.360623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9222
92.2%
0 750
 
7.5%
1 27
 
0.3%
2 1
 
< 0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9224 
0
 
752
1
 
24

Length

Max length4
Median length4
Mean length3.7672
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> 9224
92.2%
0 752
 
7.5%
1 24
 
0.2%

Length

2024-04-17T21:39:55.440912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:55.527797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9224
92.2%
0 752
 
7.5%
1 24
 
0.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8138 
기타
1765 
주택가주변
 
81
아파트지역
 
14
유흥업소밀집지역
 
2

Length

Max length8
Median length4
Mean length3.6573
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> 8138
81.4%
기타 1765
 
17.6%
주택가주변 81
 
0.8%
아파트지역 14
 
0.1%
유흥업소밀집지역 2
 
< 0.1%

Length

2024-04-17T21:39:55.604829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:55.680000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8138
81.4%
기타 1765
 
17.6%
주택가주변 81
 
0.8%
아파트지역 14
 
0.1%
유흥업소밀집지역 2
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8138 
기타
1706 
자율
 
154
 
2

Length

Max length4
Median length4
Mean length3.6274
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> 8138
81.4%
기타 1706
 
17.1%
자율 154
 
1.5%
2
 
< 0.1%

Length

2024-04-17T21:39:55.767239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:55.846223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8138
81.4%
기타 1706
 
17.1%
자율 154
 
1.5%
2
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8421 
상수도전용
1573 
지하수전용
 
3
간이상수도
 
2
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.1591
Min length4

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> 8421
84.2%
상수도전용 1573
 
15.7%
지하수전용 3
 
< 0.1%
간이상수도 2
 
< 0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2024-04-17T21:39:55.928606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:56.005986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8421
84.2%
상수도전용 1573
 
15.7%
지하수전용 3
 
< 0.1%
간이상수도 2
 
< 0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 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>
6484 
0
3514 
1
 
2

Length

Max length4
Median length4
Mean length2.9452
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6484
64.8%
0 3514
35.1%
1 2
 
< 0.1%

Length

2024-04-17T21:39:56.090640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:56.166231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6484
64.8%
0 3514
35.1%
1 2
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6484 
0
3516 

Length

Max length4
Median length4
Mean length2.9452
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6484
64.8%
0 3516
35.2%

Length

2024-04-17T21:39:56.247803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:56.321672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6484
64.8%
0 3516
35.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6482 
0
3483 
1
 
31
2
 
4

Length

Max length4
Median length4
Mean length2.9446
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6482
64.8%
0 3483
34.8%
1 31
 
0.3%
2 4
 
< 0.1%

Length

2024-04-17T21:39:56.400982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:56.476844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6482
64.8%
0 3483
34.8%
1 31
 
0.3%
2 4
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6481 
0
3483 
1
 
33
2
 
3

Length

Max length4
Median length4
Mean length2.9443
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6481
64.8%
0 3483
34.8%
1 33
 
0.3%
2 3
 
< 0.1%

Length

2024-04-17T21:39:56.559926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:56.636207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6481
64.8%
0 3483
34.8%
1 33
 
0.3%
2 3
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7688 
자가
1411 
임대
901 

Length

Max length4
Median length4
Mean length3.5376
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7688
76.9%
자가 1411
 
14.1%
임대 901
 
9.0%

Length

2024-04-17T21:39:56.718928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:56.797968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7688
76.9%
자가 1411
 
14.1%
임대 901
 
9.0%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9386 
0
 
613
300
 
1

Length

Max length4
Median length4
Mean length3.816
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9386
93.9%
0 613
 
6.1%
300 1
 
< 0.1%

Length

2024-04-17T21:39:56.875250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:56.946945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9386
93.9%
0 613
 
6.1%
300 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9386 
0
 
613
30
 
1

Length

Max length4
Median length4
Mean length3.8159
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9386
93.9%
0 613
 
6.1%
30 1
 
< 0.1%

Length

2024-04-17T21:39:57.268779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:39:57.341574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9386
93.9%
0 613
 
6.1%
30 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Memory size97.7 KiB
False
9997 
(Missing)
 
3
ValueCountFrequency (%)
False 9997
> 99.9%
(Missing) 3
 
< 0.1%
2024-04-17T21:39:57.400903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct385
Distinct (%)3.9%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.220083
Minimum0
Maximum331.86
Zeros9361
Zeros (%)93.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T21:39:57.478320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.3
Maximum331.86
Range331.86
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.6890587
Coefficient of variation (CV)7.1216946
Kurtosis505.92623
Mean1.220083
Median Absolute Deviation (MAD)0
Skewness17.919222
Sum12197.17
Variance75.499741
MonotonicityNot monotonic
2024-04-17T21:39:57.583925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9361
93.6%
3.3 35
 
0.4%
2.0 17
 
0.2%
3.0 13
 
0.1%
4.0 12
 
0.1%
19.8 10
 
0.1%
12.0 10
 
0.1%
9.9 10
 
0.1%
33.0 8
 
0.1%
10.0 8
 
0.1%
Other values (375) 513
 
5.1%
ValueCountFrequency (%)
0.0 9361
93.6%
0.3 1
 
< 0.1%
0.6 1
 
< 0.1%
0.81 1
 
< 0.1%
1.0 7
 
0.1%
1.1 2
 
< 0.1%
1.25 1
 
< 0.1%
1.28 1
 
< 0.1%
1.32 1
 
< 0.1%
1.44 2
 
< 0.1%
ValueCountFrequency (%)
331.86 1
< 0.1%
318.51 1
< 0.1%
233.9 1
< 0.1%
191.91 1
< 0.1%
140.4 1
< 0.1%
133.33 1
< 0.1%
133.03 1
< 0.1%
126.0 1
< 0.1%
108.4 1
< 0.1%
106.74 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
1338513386즉석판매제조가공업07_22_19_P32900003290000-107-2018-0015320180808<NA>3폐업2폐업20180815<NA><NA><NA><NA><NA>614801부산광역시 부산진구 가야동 624-7번지 가야홈플러스부산광역시 부산진구 가야대로 506, 가야홈플러스 (가야동)47324알앤알코리아20180816041528I2018-08-31 23:59:59.0즉석판매제조가공업384668.52046185579.964272즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1321213213즉석판매제조가공업07_22_19_P33800003380000-107-2018-0007120180629<NA>3폐업2폐업20180710<NA><NA><NA><NA><NA>613819부산광역시 수영구 남천동 545-2번지 메가마트 남천점부산광역시 수영구 황령대로 521, 메가마트 남천점 1층 (남천동)48313(주)미트벨리20180711041527I2018-08-31 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>
1950219503즉석판매제조가공업07_22_19_P33000003300000-107-2017-0023720171113<NA>3폐업2폐업20171121<NA><NA><NA><NA><NA>607807부산광역시 동래구 명장동 23-2번지 GS슈퍼마켓부산광역시 동래구 반송로 291 (명장동)47751현재상사20171122041524I2018-08-31 23:59:59.0즉석판매제조가공업391333.589419191690.582021즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
71417142즉석판매제조가공업07_22_19_P32600003260000-107-2019-0001120190305<NA>3폐업2폐업20190324<NA><NA><NA><NA><NA>602819부산광역시 서구 서대신동2가 213-8번지 탑마트부산광역시 서구 대영로 5, 탑마트 (서대신동2가)49227현재상사20190325041509U2019-03-27 02:40:00.0즉석판매제조가공업383454.909818180954.659582즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
60346035즉석판매제조가공업07_22_19_P33200003320000-107-2006-0000420060111<NA>3폐업2폐업20060123<NA><NA><NA><NA><NA>616833부산광역시 북구 화명동 194-2번지 GS슈퍼내<NA><NA>디케이엔트프라이즈20060111000000I2018-08-31 23:59:59.0즉석판매제조가공업383337.206574195335.803166즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA><NA>
618619즉석판매제조가공업07_22_19_P33500003350000-107-2019-0009820190702<NA>1영업/정상1영업<NA><NA><NA><NA><NA>14.74609839부산광역시 금정구 장전동 317-6번지부산광역시 금정구 금정로 52, 1층 (장전동)46292브라운쇼콜라20190704094832U2019-07-06 02:40:00.0즉석판매제조가공업389869.937034194214.002719즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
2210122102즉석판매제조가공업07_22_19_P32900003290000-107-1991-0102219910406<NA>3폐업2폐업20081226<NA><NA><NA><NA><NA>614827부산광역시 부산진구 범천동 845-33번지<NA><NA>강원탕제원20030203000000I2018-08-31 23:59:59.0즉석판매제조가공업387782.508794184654.839803즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
54895490즉석판매제조가공업07_22_19_P33000003300000-107-2020-0021720201215<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>607716부산광역시 동래구 온천동 502-3 롯데백화점부산광역시 동래구 중앙대로 1393, 롯데백화점 지하1층 (온천동)47727트윈스키친(호호찐빵)20201215110151I2020-12-17 00:23:06.0즉석판매제조가공업389097.800934192260.811648즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1550815509즉석판매제조가공업07_22_19_P33000003300000-107-2009-0006820090622<NA>3폐업2폐업20090629<NA><NA><NA><NA><NA>607804부산광역시 동래구 명륜동 506-3번지 메가마트 동래점 내<NA><NA>순창장본가20090623161101I2018-08-31 23:59:59.0즉석판매제조가공업389455.109102191427.549248즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1419914200즉석판매제조가공업07_22_19_P33100003310000-107-2018-0005520180328<NA>3폐업2폐업20180410<NA><NA><NA><NA><NA>608833부산광역시 남구 용호동 395-1번지 휴대폰도매총판부산광역시 남구 동명로 132, 휴대폰도매총판 4층 (용호동)48567삼부자20180411041527I2018-08-31 23:59:59.0즉석판매제조가공업392404.00379182098.194247즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
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1623016231즉석판매제조가공업07_22_19_P33300003330000-107-2007-0003720070425<NA>3폐업2폐업20070508<NA><NA><NA><NA><NA>612020부산광역시 해운대구 우동 1499번지 삼성홈플러스 식품매장내<NA><NA>아름아침20070425000000I2018-08-31 23:59:59.0즉석판매제조가공업394314.881157187833.001648즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA><NA>
93669367즉석판매제조가공업07_22_19_P33400003340000-107-2019-0020620191004<NA>3폐업2폐업20191016<NA><NA><NA><NA><NA>604811부산광역시 사하구 괴정동 961-1번지부산광역시 사하구 사하로 190 (괴정동)49356현승유통20191017041528U2019-10-19 02:40:00.0즉석판매제조가공업381751.003173179575.519982즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
47744775즉석판매제조가공업07_22_19_P33400003340000-107-1998-0060319981223<NA>1영업/정상1영업<NA><NA><NA><NA>051 261559721.60604842부산광역시 사하구 장림동 641-65번지 (641-66,67)부산광역시 사하구 장림시장2길 64 (장림동)49476서포상회20130319134724I2018-08-31 23:59:59.0즉석판매제조가공업379376.688929177529.120024즉석판매제조가공업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
2170821709즉석판매제조가공업07_22_19_P33100003310000-107-1997-0010319970710<NA>3폐업2폐업20050228<NA><NA><NA>051 6347705<NA>608800부산광역시 남구 감만동 34-138번지<NA><NA>예단떡방앗간20081206104620I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA>주택가주변자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1485114852즉석판매제조가공업07_22_19_P32600003260000-107-1985-0040319851210<NA>3폐업2폐업19990512<NA><NA><NA>051 2554703<NA>602011부산광역시 서구 충무동1가 34-18번지<NA><NA>고성상회20080227102010I2018-08-31 23:59:59.0즉석판매제조가공업384600.386663179185.19724즉석판매제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
2102721028즉석판매제조가공업07_22_19_P33300003330000-107-2009-0006420090326<NA>3폐업2폐업20131230<NA><NA><NA><NA>42.90612840부산광역시 해운대구 좌동 1331번지부산광역시 해운대구 세실로 7 (좌동, 상록a분산상가102호)48112쿵더쿵20111201104440I2018-08-31 23:59:59.0즉석판매제조가공업398616.713432187388.675187즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA>2임대<NA><NA>N0.0<NA><NA><NA><NA>
1300813009즉석판매제조가공업07_22_19_P33300003330000-107-2001-0073420010416<NA>3폐업2폐업20020326<NA><NA><NA>051 666688527.00612810부산광역시 해운대구 반여동 559-0번지 반여농산물고추마늘판 매장동 35호호<NA><NA>경북상회20020612000000I2018-08-31 23:59:59.0즉석판매제조가공업393233.931123192684.487638즉석판매제조가공업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
1868218683즉석판매제조가공업07_22_19_P34000003400000-107-2018-0008220180717<NA>3폐업2폐업20180819<NA><NA><NA><NA><NA>619912부산광역시 기장군 일광면 삼성리 547-6번지 메가마트부산광역시 기장군 일광면 기장대로 673, 메가마트46048주경식품20180820041525I2018-08-31 23:59:59.0즉석판매제조가공업402168.434115197304.623745즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
22532254즉석판매제조가공업07_22_19_P32900003290000-107-1998-0094919980723<NA>1영업/정상1영업<NA><NA><NA><NA>051 866181212.00614851부산광역시 부산진구 양정동 88-5번지부산광역시 부산진구 양연로10번길 29 (양정동)47218동호상회20190607110615U2019-06-09 02:40:00.0즉석판매제조가공업389202.524043188079.804661즉석판매제조가공업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
977978즉석판매제조가공업07_22_19_P33800003380000-107-2020-0003020200327<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.00613831부산광역시 수영구 수영동 473-9번지부산광역시 수영구 수미로 32-2, 1층 (수영동)48224따숲케이크20200327153309I2020-03-29 00:23:21.0즉석판매제조가공업392531.881655188101.803653즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N42.0<NA><NA><NA><NA>