Overview

Dataset statistics

Number of variables51
Number of observations4921
Missing cells47829
Missing cells (%)19.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 MiB
Average record size in memory441.0 B

Variable types

Numeric14
Categorical22
Text7
Unsupported5
DateTime1
Boolean2

Dataset

Description2021-05-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123089

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
발한실여부 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (94.3%)Imbalance
위생업태명 is highly imbalanced (94.3%)Imbalance
사용끝지하층 is highly imbalanced (56.9%)Imbalance
조건부허가시작일자 is highly imbalanced (99.6%)Imbalance
조건부허가종료일자 is highly imbalanced (99.6%)Imbalance
건물소유구분명 is highly imbalanced (52.6%)Imbalance
여성종사자수 is highly imbalanced (74.6%)Imbalance
남성종사자수 is highly imbalanced (78.8%)Imbalance
침대수 is highly imbalanced (66.4%)Imbalance
인허가취소일자 has 4921 (100.0%) missing valuesMissing
폐업일자 has 1326 (26.9%) missing valuesMissing
휴업시작일자 has 4921 (100.0%) missing valuesMissing
휴업종료일자 has 4921 (100.0%) missing valuesMissing
재개업일자 has 4921 (100.0%) missing valuesMissing
소재지전화 has 1410 (28.7%) missing valuesMissing
도로명전체주소 has 2596 (52.8%) missing valuesMissing
도로명우편번호 has 2649 (53.8%) missing valuesMissing
좌표정보(x) has 387 (7.9%) missing valuesMissing
좌표정보(y) has 387 (7.9%) missing valuesMissing
건물지상층수 has 1727 (35.1%) missing valuesMissing
건물지하층수 has 2229 (45.3%) missing valuesMissing
사용시작지상층 has 2099 (42.7%) missing valuesMissing
사용끝지상층 has 2727 (55.4%) missing valuesMissing
발한실여부 has 100 (2.0%) missing valuesMissing
의자수 has 606 (12.3%) missing valuesMissing
조건부허가신고사유 has 4920 (> 99.9%) missing valuesMissing
Unnamed: 50 has 4921 (100.0%) missing valuesMissing
인허가일자 is highly skewed (γ1 = -27.01802832)Skewed
폐업일자 is highly skewed (γ1 = -28.16933341)Skewed
건물지하층수 is highly skewed (γ1 = 49.0385786)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
Unnamed: 50 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 1208 (24.5%) zerosZeros
건물지하층수 has 1721 (35.0%) zerosZeros
사용시작지상층 has 1003 (20.4%) zerosZeros
사용끝지상층 has 589 (12.0%) zerosZeros
의자수 has 338 (6.9%) zerosZeros

Reproduction

Analysis started2024-04-17 22:55:55.676888
Analysis finished2024-04-17 22:55:57.052872
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct4921
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2461
Minimum1
Maximum4921
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:55:57.112403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile247
Q11231
median2461
Q33691
95-th percentile4675
Maximum4921
Range4920
Interquartile range (IQR)2460

Descriptive statistics

Standard deviation1420.7147
Coefficient of variation (CV)0.57729162
Kurtosis-1.2
Mean2461
Median Absolute Deviation (MAD)1230
Skewness0
Sum12110581
Variance2018430.2
MonotonicityStrictly increasing
2024-04-18T07:55:57.238245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3279 1
 
< 0.1%
3286 1
 
< 0.1%
3285 1
 
< 0.1%
3284 1
 
< 0.1%
3283 1
 
< 0.1%
3282 1
 
< 0.1%
3281 1
 
< 0.1%
3280 1
 
< 0.1%
3278 1
 
< 0.1%
Other values (4911) 4911
99.8%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
4921 1
< 0.1%
4920 1
< 0.1%
4919 1
< 0.1%
4918 1
< 0.1%
4917 1
< 0.1%
4916 1
< 0.1%
4915 1
< 0.1%
4914 1
< 0.1%
4913 1
< 0.1%
4912 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
이용업
4921 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이용업 4921
100.0%

Length

2024-04-18T07:55:57.360918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:55:57.445206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용업 4921
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
05_19_01_P
4921 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05_19_01_P
2nd row05_19_01_P
3rd row05_19_01_P
4th row05_19_01_P
5th row05_19_01_P

Common Values

ValueCountFrequency (%)
05_19_01_P 4921
100.0%

Length

2024-04-18T07:55:57.539899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:55:57.621365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 4921
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3324509.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:55:57.698122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3320000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation40367.821
Coefficient of variation (CV)0.01214249
Kurtosis-0.94057517
Mean3324509.2
Median Absolute Deviation (MAD)30000
Skewness0.057777767
Sum1.635991 × 1010
Variance1.6295609 × 109
MonotonicityNot monotonic
2024-04-18T07:55:57.820357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 504
10.2%
3340000 496
10.1%
3300000 420
8.5%
3320000 409
 
8.3%
3330000 393
 
8.0%
3350000 384
 
7.8%
3390000 332
 
6.7%
3370000 331
 
6.7%
3310000 324
 
6.6%
3380000 284
 
5.8%
Other values (6) 1044
21.2%
ValueCountFrequency (%)
3250000 166
 
3.4%
3260000 213
4.3%
3270000 257
5.2%
3280000 209
4.2%
3290000 504
10.2%
3300000 420
8.5%
3310000 324
6.6%
3320000 409
8.3%
3330000 393
8.0%
3340000 496
10.1%
ValueCountFrequency (%)
3400000 110
 
2.2%
3390000 332
6.7%
3380000 284
5.8%
3370000 331
6.7%
3360000 89
 
1.8%
3350000 384
7.8%
3340000 496
10.1%
3330000 393
8.0%
3320000 409
8.3%
3310000 324
6.6%

관리번호
Text

UNIQUE 

Distinct4921
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-04-18T07:55:58.024115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters108262
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

Unique4921 ?
Unique (%)100.0%

Sample

1st row3280000-203-2018-00003
2nd row3390000-203-2019-00001
3rd row3350000-203-2019-00001
4th row3390000-203-2019-00002
5th row3390000-203-2019-00003
ValueCountFrequency (%)
3280000-203-2018-00003 1
 
< 0.1%
3380000-203-2007-00008 1
 
< 0.1%
3350000-203-2012-00003 1
 
< 0.1%
3350000-203-2011-00001 1
 
< 0.1%
3380000-203-1998-00009 1
 
< 0.1%
3380000-203-1969-00001 1
 
< 0.1%
3380000-203-1989-00014 1
 
< 0.1%
3380000-203-1996-00007 1
 
< 0.1%
3380000-203-1994-00007 1
 
< 0.1%
3380000-203-2002-00004 1
 
< 0.1%
Other values (4911) 4911
99.8%
2024-04-18T07:55:58.327756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43261
40.0%
3 15457
 
14.3%
- 14763
 
13.6%
2 10889
 
10.1%
1 6163
 
5.7%
9 6021
 
5.6%
8 2657
 
2.5%
7 2444
 
2.3%
4 2331
 
2.2%
5 2139
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93499
86.4%
Dash Punctuation 14763
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43261
46.3%
3 15457
 
16.5%
2 10889
 
11.6%
1 6163
 
6.6%
9 6021
 
6.4%
8 2657
 
2.8%
7 2444
 
2.6%
4 2331
 
2.5%
5 2139
 
2.3%
6 2137
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 14763
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108262
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43261
40.0%
3 15457
 
14.3%
- 14763
 
13.6%
2 10889
 
10.1%
1 6163
 
5.7%
9 6021
 
5.6%
8 2657
 
2.5%
7 2444
 
2.3%
4 2331
 
2.2%
5 2139
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108262
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43261
40.0%
3 15457
 
14.3%
- 14763
 
13.6%
2 10889
 
10.1%
1 6163
 
5.7%
9 6021
 
5.6%
8 2657
 
2.5%
7 2444
 
2.3%
4 2331
 
2.2%
5 2139
 
2.0%

인허가일자
Real number (ℝ)

SKEWED 

Distinct3650
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19958821
Minimum9710223
Maximum20210330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:55:58.475857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9710223
5-th percentile19691125
Q119880105
median19980428
Q320051220
95-th percentile20170818
Maximum20210330
Range10500107
Interquartile range (IQR)171115

Descriptive statistics

Standard deviation201153.22
Coefficient of variation (CV)0.010078412
Kurtosis1368.8196
Mean19958821
Median Absolute Deviation (MAD)89999
Skewness-27.018028
Sum9.821736 × 1010
Variance4.0462617 × 1010
MonotonicityNot monotonic
2024-04-18T07:55:58.619508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19770830 35
 
0.7%
19660301 35
 
0.7%
20000420 19
 
0.4%
20020506 17
 
0.3%
20000623 13
 
0.3%
19630630 9
 
0.2%
20030224 9
 
0.2%
19721129 7
 
0.1%
20030410 7
 
0.1%
20010714 6
 
0.1%
Other values (3640) 4764
96.8%
ValueCountFrequency (%)
9710223 1
 
< 0.1%
19300722 1
 
< 0.1%
19610922 1
 
< 0.1%
19621202 1
 
< 0.1%
19630110 6
0.1%
19630522 1
 
< 0.1%
19630525 1
 
< 0.1%
19630529 4
0.1%
19630601 1
 
< 0.1%
19630622 1
 
< 0.1%
ValueCountFrequency (%)
20210330 1
 
< 0.1%
20210324 1
 
< 0.1%
20210323 1
 
< 0.1%
20210318 1
 
< 0.1%
20210310 2
< 0.1%
20210309 1
 
< 0.1%
20210305 1
 
< 0.1%
20210304 1
 
< 0.1%
20210303 3
0.1%
20210302 1
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4921
Missing (%)100.0%
Memory size43.4 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
3
3595 
1
1326 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 3595
73.1%
1 1326
 
26.9%

Length

2024-04-18T07:55:58.740420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:55:58.821795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3595
73.1%
1 1326
 
26.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
폐업
3595 
영업/정상
1326 

Length

Max length5
Median length2
Mean length2.8083723
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3595
73.1%
영업/정상 1326
 
26.9%

Length

2024-04-18T07:55:58.929160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:55:59.044537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3595
73.1%
영업/정상 1326
 
26.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2
3595 
1
1326 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 3595
73.1%
1 1326
 
26.9%

Length

2024-04-18T07:55:59.149817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:55:59.247227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3595
73.1%
1 1326
 
26.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
폐업
3595 
영업
1326 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3595
73.1%
영업 1326
 
26.9%

Length

2024-04-18T07:55:59.351362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:55:59.442442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3595
73.1%
영업 1326
 
26.9%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct2275
Distinct (%)63.3%
Missing1326
Missing (%)26.9%
Infinite0
Infinite (%)0.0%
Mean20066453
Minimum2019071
Maximum20800812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:55:59.574260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2019071
5-th percentile20000119
Q120040504
median20070619
Q320130625
95-th percentile20190525
Maximum20800812
Range18781741
Interquartile range (IQR)90120.5

Descriptive statistics

Standard deviation453990.34
Coefficient of variation (CV)0.022624345
Kurtosis904.00193
Mean20066453
Median Absolute Deviation (MAD)39904
Skewness-28.169333
Sum7.2138897 × 1010
Variance2.0610723 × 1011
MonotonicityNot monotonic
2024-04-18T07:55:59.712365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030715 58
 
1.2%
20050214 41
 
0.8%
20031213 36
 
0.7%
20020222 33
 
0.7%
20030305 33
 
0.7%
20030221 32
 
0.7%
20030101 17
 
0.3%
20051011 16
 
0.3%
20061226 13
 
0.3%
20030215 13
 
0.3%
Other values (2265) 3303
67.1%
(Missing) 1326
26.9%
ValueCountFrequency (%)
2019071 1
 
< 0.1%
11111111 5
0.1%
19931124 1
 
< 0.1%
19950206 1
 
< 0.1%
19950210 1
 
< 0.1%
19950331 1
 
< 0.1%
19950413 1
 
< 0.1%
19950515 1
 
< 0.1%
19950818 1
 
< 0.1%
19950828 1
 
< 0.1%
ValueCountFrequency (%)
20800812 1
< 0.1%
20210329 1
< 0.1%
20210322 2
< 0.1%
20210317 1
< 0.1%
20210316 1
< 0.1%
20210315 1
< 0.1%
20210311 1
< 0.1%
20210309 1
< 0.1%
20210302 1
< 0.1%
20210225 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4921
Missing (%)100.0%
Memory size43.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4921
Missing (%)100.0%
Memory size43.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4921
Missing (%)100.0%
Memory size43.4 KiB

소재지전화
Text

MISSING 

Distinct2874
Distinct (%)81.9%
Missing1410
Missing (%)28.7%
Memory size38.6 KiB
2024-04-18T07:56:00.025481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.9404728
Min length3

Characters and Unicode

Total characters34901
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

Unique2725 ?
Unique (%)77.6%

Sample

1st row051 727 5320
2nd row051 728 3988
3rd row051 364 2651
4th row051 7549944
5th row051 7596288
ValueCountFrequency (%)
051 3301
48.3%
893 8
 
0.1%
554 8
 
0.1%
754 6
 
0.1%
292 6
 
0.1%
868 6
 
0.1%
727 6
 
0.1%
051643 6
 
0.1%
724 5
 
0.1%
243 5
 
0.1%
Other values (3076) 3482
50.9%
2024-04-18T07:56:00.462541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6048
17.3%
1 5286
15.1%
0 5188
14.9%
3344
9.6%
2 2844
8.1%
4 2312
 
6.6%
6 2243
 
6.4%
3 2210
 
6.3%
7 2077
 
6.0%
8 1971
 
5.6%
Other values (2) 1378
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31555
90.4%
Space Separator 3344
 
9.6%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6048
19.2%
1 5286
16.8%
0 5188
16.4%
2 2844
9.0%
4 2312
 
7.3%
6 2243
 
7.1%
3 2210
 
7.0%
7 2077
 
6.6%
8 1971
 
6.2%
9 1376
 
4.4%
Space Separator
ValueCountFrequency (%)
3344
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34901
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6048
17.3%
1 5286
15.1%
0 5188
14.9%
3344
9.6%
2 2844
8.1%
4 2312
 
6.6%
6 2243
 
6.4%
3 2210
 
6.3%
7 2077
 
6.0%
8 1971
 
5.6%
Other values (2) 1378
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34901
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6048
17.3%
1 5286
15.1%
0 5188
14.9%
3344
9.6%
2 2844
8.1%
4 2312
 
6.6%
6 2243
 
6.4%
3 2210
 
6.3%
7 2077
 
6.0%
8 1971
 
5.6%
Other values (2) 1378
 
3.9%
Distinct2132
Distinct (%)43.6%
Missing34
Missing (%)0.7%
Memory size38.6 KiB
2024-04-18T07:56:00.797251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.6324944
Min length3

Characters and Unicode

Total characters22639
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

Unique1377 ?
Unique (%)28.2%

Sample

1st row10.12
2nd row34.99
3rd row42.80
4th row62.07
5th row16.91
ValueCountFrequency (%)
00 493
 
10.1%
10.00 50
 
1.0%
9.00 50
 
1.0%
12.00 43
 
0.9%
15.00 37
 
0.8%
8.40 33
 
0.7%
8.00 32
 
0.7%
18.00 31
 
0.6%
6.00 29
 
0.6%
20.00 27
 
0.6%
Other values (2122) 4062
83.1%
2024-04-18T07:56:01.264445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4887
21.6%
0 4472
19.8%
1 2288
10.1%
2 2178
9.6%
5 1425
 
6.3%
3 1416
 
6.3%
8 1408
 
6.2%
4 1294
 
5.7%
6 1273
 
5.6%
9 1005
 
4.4%
Other values (2) 993
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17748
78.4%
Other Punctuation 4891
 
21.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4472
25.2%
1 2288
12.9%
2 2178
12.3%
5 1425
 
8.0%
3 1416
 
8.0%
8 1408
 
7.9%
4 1294
 
7.3%
6 1273
 
7.2%
9 1005
 
5.7%
7 989
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 4887
99.9%
, 4
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 22639
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4887
21.6%
0 4472
19.8%
1 2288
10.1%
2 2178
9.6%
5 1425
 
6.3%
3 1416
 
6.3%
8 1408
 
6.2%
4 1294
 
5.7%
6 1273
 
5.6%
9 1005
 
4.4%
Other values (2) 993
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22639
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4887
21.6%
0 4472
19.8%
1 2288
10.1%
2 2178
9.6%
5 1425
 
6.3%
3 1416
 
6.3%
8 1408
 
6.2%
4 1294
 
5.7%
6 1273
 
5.6%
9 1005
 
4.4%
Other values (2) 993
 
4.4%

소재지우편번호
Real number (ℝ)

Distinct777
Distinct (%)15.9%
Missing24
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean610454.77
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:56:01.418255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601812
Q1606070
median609852
Q3614826
95-th percentile617833
Maximum619953
Range19942
Interquartile range (IQR)8756

Descriptive statistics

Standard deviation5291.1534
Coefficient of variation (CV)0.0086675601
Kurtosis-1.0156941
Mean610454.77
Median Absolute Deviation (MAD)4962
Skewness-0.18922633
Sum2.989397 × 109
Variance27996305
MonotonicityNot monotonic
2024-04-18T07:56:01.571083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
607833 31
 
0.6%
616801 28
 
0.6%
601829 28
 
0.6%
604851 27
 
0.5%
612847 26
 
0.5%
607826 24
 
0.5%
616807 24
 
0.5%
611803 23
 
0.5%
617818 22
 
0.4%
604813 22
 
0.4%
Other values (767) 4642
94.3%
(Missing) 24
 
0.5%
ValueCountFrequency (%)
600011 2
 
< 0.1%
600012 8
0.2%
600013 2
 
< 0.1%
600014 2
 
< 0.1%
600015 1
 
< 0.1%
600021 4
0.1%
600022 3
 
0.1%
600023 3
 
0.1%
600024 1
 
< 0.1%
600025 4
0.1%
ValueCountFrequency (%)
619953 3
 
0.1%
619952 6
0.1%
619951 5
 
0.1%
619950 1
 
< 0.1%
619913 3
 
0.1%
619912 5
 
0.1%
619911 6
0.1%
619906 9
0.2%
619905 14
0.3%
619904 2
 
< 0.1%
Distinct4349
Distinct (%)88.4%
Missing3
Missing (%)0.1%
Memory size38.6 KiB
2024-04-18T07:56:01.867702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length48
Mean length23.600041
Min length6

Characters and Unicode

Total characters116065
Distinct characters374
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3914 ?
Unique (%)79.6%

Sample

1st row부산광역시 영도구 동삼동 1123-7
2nd row부산광역시 사상구 학장동 574-57번지 학장동2차삼성아파트상가 205호
3rd row부산광역시 금정구 서동 118-27번지
4th row부산광역시 사상구 주례동 507-1번지
5th row부산광역시 사상구 엄궁동 266번지
ValueCountFrequency (%)
부산광역시 4917
 
22.3%
t통b반 763
 
3.5%
부산진구 504
 
2.3%
사하구 498
 
2.3%
동래구 420
 
1.9%
북구 411
 
1.9%
해운대구 393
 
1.8%
금정구 384
 
1.7%
사상구 332
 
1.5%
연제구 329
 
1.5%
Other values (4734) 13099
59.4%
2024-04-18T07:56:02.296631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17136
 
14.8%
5833
 
5.0%
5782
 
5.0%
5780
 
5.0%
5088
 
4.4%
1 5059
 
4.4%
5051
 
4.4%
4945
 
4.3%
4923
 
4.2%
4729
 
4.1%
Other values (364) 51739
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68946
59.4%
Decimal Number 23413
 
20.2%
Space Separator 17136
 
14.8%
Dash Punctuation 4471
 
3.9%
Uppercase Letter 1573
 
1.4%
Open Punctuation 218
 
0.2%
Close Punctuation 217
 
0.2%
Other Punctuation 88
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5833
 
8.5%
5782
 
8.4%
5780
 
8.4%
5088
 
7.4%
5051
 
7.3%
4945
 
7.2%
4923
 
7.1%
4729
 
6.9%
4530
 
6.6%
946
 
1.4%
Other values (331) 21339
31.0%
Uppercase Letter
ValueCountFrequency (%)
B 783
49.8%
T 766
48.7%
A 10
 
0.6%
L 3
 
0.2%
F 2
 
0.1%
C 2
 
0.1%
G 2
 
0.1%
S 1
 
0.1%
P 1
 
0.1%
O 1
 
0.1%
Other values (2) 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 5059
21.6%
2 3160
13.5%
3 2705
11.6%
4 2233
9.5%
5 2168
9.3%
6 1733
 
7.4%
0 1710
 
7.3%
8 1665
 
7.1%
7 1611
 
6.9%
9 1369
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 76
86.4%
@ 6
 
6.8%
/ 3
 
3.4%
. 2
 
2.3%
& 1
 
1.1%
Space Separator
ValueCountFrequency (%)
17136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4471
100.0%
Open Punctuation
ValueCountFrequency (%)
( 218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 217
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68944
59.4%
Common 45545
39.2%
Latin 1574
 
1.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5833
 
8.5%
5782
 
8.4%
5780
 
8.4%
5088
 
7.4%
5051
 
7.3%
4945
 
7.2%
4923
 
7.1%
4729
 
6.9%
4530
 
6.6%
946
 
1.4%
Other values (330) 21337
30.9%
Common
ValueCountFrequency (%)
17136
37.6%
1 5059
 
11.1%
- 4471
 
9.8%
2 3160
 
6.9%
3 2705
 
5.9%
4 2233
 
4.9%
5 2168
 
4.8%
6 1733
 
3.8%
0 1710
 
3.8%
8 1665
 
3.7%
Other values (10) 3505
 
7.7%
Latin
ValueCountFrequency (%)
B 783
49.7%
T 766
48.7%
A 10
 
0.6%
L 3
 
0.2%
F 2
 
0.1%
C 2
 
0.1%
G 2
 
0.1%
S 1
 
0.1%
P 1
 
0.1%
O 1
 
0.1%
Other values (3) 3
 
0.2%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68944
59.4%
ASCII 47119
40.6%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17136
36.4%
1 5059
 
10.7%
- 4471
 
9.5%
2 3160
 
6.7%
3 2705
 
5.7%
4 2233
 
4.7%
5 2168
 
4.6%
6 1733
 
3.7%
0 1710
 
3.6%
8 1665
 
3.5%
Other values (23) 5079
 
10.8%
Hangul
ValueCountFrequency (%)
5833
 
8.5%
5782
 
8.4%
5780
 
8.4%
5088
 
7.4%
5051
 
7.3%
4945
 
7.2%
4923
 
7.1%
4729
 
6.9%
4530
 
6.6%
946
 
1.4%
Other values (330) 21337
30.9%
CJK
ValueCountFrequency (%)
2
100.0%

도로명전체주소
Text

MISSING 

Distinct2238
Distinct (%)96.3%
Missing2596
Missing (%)52.8%
Memory size38.6 KiB
2024-04-18T07:56:02.619939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length54
Mean length28.699355
Min length17

Characters and Unicode

Total characters66726
Distinct characters396
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2159 ?
Unique (%)92.9%

Sample

1st row부산광역시 영도구 상리로 35 (동삼동)
2nd row부산광역시 사상구 학감대로123번길 89, 학장동2차삼성아파트상가205호 (학장동)
3rd row부산광역시 금정구 금사로 58-12, 1층 (서동)
4th row부산광역시 사상구 가야대로 290-4, 2층 (주례동)
5th row부산광역시 사상구 엄궁북로4번가길 17 (엄궁동, 진주식육점)
ValueCountFrequency (%)
부산광역시 2325
 
17.9%
1층 283
 
2.2%
부산진구 269
 
2.1%
동래구 226
 
1.7%
사하구 213
 
1.6%
사상구 188
 
1.5%
금정구 187
 
1.4%
해운대구 181
 
1.4%
남구 164
 
1.3%
북구 153
 
1.2%
Other values (2644) 8773
67.7%
2024-04-18T07:56:03.083234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10641
 
15.9%
3013
 
4.5%
2838
 
4.3%
2800
 
4.2%
1 2524
 
3.8%
2438
 
3.7%
2435
 
3.6%
2411
 
3.6%
2329
 
3.5%
) 2292
 
3.4%
Other values (386) 33005
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39807
59.7%
Space Separator 10641
 
15.9%
Decimal Number 10172
 
15.2%
Close Punctuation 2292
 
3.4%
Open Punctuation 2292
 
3.4%
Other Punctuation 1055
 
1.6%
Dash Punctuation 427
 
0.6%
Uppercase Letter 37
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3013
 
7.6%
2838
 
7.1%
2800
 
7.0%
2438
 
6.1%
2435
 
6.1%
2411
 
6.1%
2329
 
5.9%
2243
 
5.6%
1270
 
3.2%
1204
 
3.0%
Other values (356) 16826
42.3%
Decimal Number
ValueCountFrequency (%)
1 2524
24.8%
2 1560
15.3%
3 1190
11.7%
4 873
 
8.6%
5 806
 
7.9%
0 718
 
7.1%
6 687
 
6.8%
7 651
 
6.4%
8 608
 
6.0%
9 555
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 19
51.4%
T 6
 
16.2%
A 6
 
16.2%
L 1
 
2.7%
S 1
 
2.7%
H 1
 
2.7%
F 1
 
2.7%
C 1
 
2.7%
E 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 1042
98.8%
/ 5
 
0.5%
@ 5
 
0.5%
. 2
 
0.2%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
10641
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2292
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2292
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 427
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39807
59.7%
Common 26881
40.3%
Latin 38
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3013
 
7.6%
2838
 
7.1%
2800
 
7.0%
2438
 
6.1%
2435
 
6.1%
2411
 
6.1%
2329
 
5.9%
2243
 
5.6%
1270
 
3.2%
1204
 
3.0%
Other values (356) 16826
42.3%
Common
ValueCountFrequency (%)
10641
39.6%
1 2524
 
9.4%
) 2292
 
8.5%
( 2292
 
8.5%
2 1560
 
5.8%
3 1190
 
4.4%
, 1042
 
3.9%
4 873
 
3.2%
5 806
 
3.0%
0 718
 
2.7%
Other values (10) 2943
 
10.9%
Latin
ValueCountFrequency (%)
B 19
50.0%
T 6
 
15.8%
A 6
 
15.8%
L 1
 
2.6%
S 1
 
2.6%
H 1
 
2.6%
F 1
 
2.6%
C 1
 
2.6%
e 1
 
2.6%
E 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39807
59.7%
ASCII 26919
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10641
39.5%
1 2524
 
9.4%
) 2292
 
8.5%
( 2292
 
8.5%
2 1560
 
5.8%
3 1190
 
4.4%
, 1042
 
3.9%
4 873
 
3.2%
5 806
 
3.0%
0 718
 
2.7%
Other values (20) 2981
 
11.1%
Hangul
ValueCountFrequency (%)
3013
 
7.6%
2838
 
7.1%
2800
 
7.0%
2438
 
6.1%
2435
 
6.1%
2411
 
6.1%
2329
 
5.9%
2243
 
5.6%
1270
 
3.2%
1204
 
3.0%
Other values (356) 16826
42.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1156
Distinct (%)50.9%
Missing2649
Missing (%)53.8%
Infinite0
Infinite (%)0.0%
Mean47827.301
Minimum46002
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:56:03.812624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46242
Q147008.75
median47802
Q348725.25
95-th percentile49407
Maximum49525
Range3523
Interquartile range (IQR)1716.5

Descriptive statistics

Standard deviation1011.3852
Coefficient of variation (CV)0.021146608
Kurtosis-1.1147454
Mean47827.301
Median Absolute Deviation (MAD)805
Skewness0.017290585
Sum1.0866363 × 108
Variance1022900
MonotonicityNot monotonic
2024-04-18T07:56:03.953984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49256 12
 
0.2%
47709 11
 
0.2%
46219 9
 
0.2%
49476 9
 
0.2%
47603 7
 
0.1%
48095 7
 
0.1%
49217 7
 
0.1%
48501 7
 
0.1%
47511 7
 
0.1%
48445 7
 
0.1%
Other values (1146) 2189
44.5%
(Missing) 2649
53.8%
ValueCountFrequency (%)
46002 3
0.1%
46007 2
< 0.1%
46008 1
 
< 0.1%
46013 1
 
< 0.1%
46015 3
0.1%
46017 2
< 0.1%
46019 1
 
< 0.1%
46020 1
 
< 0.1%
46021 1
 
< 0.1%
46022 2
< 0.1%
ValueCountFrequency (%)
49525 1
 
< 0.1%
49524 2
 
< 0.1%
49522 2
 
< 0.1%
49521 1
 
< 0.1%
49518 5
0.1%
49516 1
 
< 0.1%
49515 4
0.1%
49514 1
 
< 0.1%
49511 5
0.1%
49509 1
 
< 0.1%
Distinct3334
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-04-18T07:56:04.226411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length4.768543
Min length1

Characters and Unicode

Total characters23466
Distinct characters569
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2653 ?
Unique (%)53.9%

Sample

1st row대광 이발
2nd row퀀즈헤나
3rd row태후사랑
4th row퀸즈헤나
5th row엄궁퀀즈헤나교실
ValueCountFrequency (%)
이용원 369
 
6.5%
구내 53
 
0.9%
컷트실 50
 
0.9%
구내이용원 41
 
0.7%
현대 36
 
0.6%
제일 28
 
0.5%
우리 28
 
0.5%
블루클럽 24
 
0.4%
캇트실 23
 
0.4%
구내이용 23
 
0.4%
Other values (3195) 5022
88.2%
2024-04-18T07:56:04.636508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2094
 
8.9%
2022
 
8.6%
1936
 
8.3%
977
 
4.2%
844
 
3.6%
777
 
3.3%
583
 
2.5%
471
 
2.0%
403
 
1.7%
387
 
1.6%
Other values (559) 12972
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22225
94.7%
Space Separator 777
 
3.3%
Uppercase Letter 146
 
0.6%
Lowercase Letter 125
 
0.5%
Close Punctuation 65
 
0.3%
Open Punctuation 65
 
0.3%
Decimal Number 35
 
0.1%
Other Punctuation 20
 
0.1%
Dash Punctuation 6
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2094
 
9.4%
2022
 
9.1%
1936
 
8.7%
977
 
4.4%
844
 
3.8%
583
 
2.6%
471
 
2.1%
403
 
1.8%
387
 
1.7%
343
 
1.5%
Other values (499) 12165
54.7%
Uppercase Letter
ValueCountFrequency (%)
B 19
13.0%
O 13
 
8.9%
H 11
 
7.5%
R 10
 
6.8%
E 10
 
6.8%
A 9
 
6.2%
S 9
 
6.2%
M 8
 
5.5%
L 7
 
4.8%
N 7
 
4.8%
Other values (12) 43
29.5%
Lowercase Letter
ValueCountFrequency (%)
r 17
13.6%
e 15
12.0%
b 11
8.8%
a 10
8.0%
s 10
8.0%
h 9
 
7.2%
o 9
 
7.2%
i 8
 
6.4%
u 6
 
4.8%
g 6
 
4.8%
Other values (8) 24
19.2%
Decimal Number
ValueCountFrequency (%)
2 11
31.4%
1 9
25.7%
8 8
22.9%
5 3
 
8.6%
9 2
 
5.7%
4 1
 
2.9%
3 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 10
50.0%
& 4
 
20.0%
, 2
 
10.0%
' 1
 
5.0%
# 1
 
5.0%
· 1
 
5.0%
: 1
 
5.0%
Space Separator
ValueCountFrequency (%)
777
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22222
94.7%
Common 970
 
4.1%
Latin 271
 
1.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2094
 
9.4%
2022
 
9.1%
1936
 
8.7%
977
 
4.4%
844
 
3.8%
583
 
2.6%
471
 
2.1%
403
 
1.8%
387
 
1.7%
343
 
1.5%
Other values (496) 12162
54.7%
Latin
ValueCountFrequency (%)
B 19
 
7.0%
r 17
 
6.3%
e 15
 
5.5%
O 13
 
4.8%
b 11
 
4.1%
H 11
 
4.1%
R 10
 
3.7%
E 10
 
3.7%
a 10
 
3.7%
s 10
 
3.7%
Other values (30) 145
53.5%
Common
ValueCountFrequency (%)
777
80.1%
) 65
 
6.7%
( 65
 
6.7%
2 11
 
1.1%
. 10
 
1.0%
1 9
 
0.9%
8 8
 
0.8%
- 6
 
0.6%
& 4
 
0.4%
5 3
 
0.3%
Other values (10) 12
 
1.2%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22222
94.7%
ASCII 1240
 
5.3%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2094
 
9.4%
2022
 
9.1%
1936
 
8.7%
977
 
4.4%
844
 
3.8%
583
 
2.6%
471
 
2.1%
403
 
1.8%
387
 
1.7%
343
 
1.5%
Other values (496) 12162
54.7%
ASCII
ValueCountFrequency (%)
777
62.7%
) 65
 
5.2%
( 65
 
5.2%
B 19
 
1.5%
r 17
 
1.4%
e 15
 
1.2%
O 13
 
1.0%
b 11
 
0.9%
H 11
 
0.9%
2 11
 
0.9%
Other values (49) 236
 
19.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

Distinct3308
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0095811 × 1013
Minimum1.9990218 × 1013
Maximum2.0210331 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:56:04.790328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile1.9990626 × 1013
Q12.0031027 × 1013
median2.0080317 × 1013
Q32.0160905 × 1013
95-th percentile2.020112 × 1013
Maximum2.0210331 × 1013
Range2.2011317 × 1011
Interquartile range (IQR)1.2987816 × 1011

Descriptive statistics

Standard deviation6.8570969 × 1010
Coefficient of variation (CV)0.0034122021
Kurtosis-1.3538606
Mean2.0095811 × 1013
Median Absolute Deviation (MAD)5.0005135 × 1010
Skewness0.26455535
Sum9.8891487 × 1016
Variance4.7019779 × 1021
MonotonicityNot monotonic
2024-04-18T07:56:04.931039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030211000000 57
 
1.2%
20070501000000 49
 
1.0%
20031215000000 38
 
0.8%
20020424000000 38
 
0.8%
20030311000000 37
 
0.8%
19990428000000 35
 
0.7%
20020423000000 34
 
0.7%
20030318000000 33
 
0.7%
20030221000000 33
 
0.7%
20030616000000 31
 
0.6%
Other values (3298) 4536
92.2%
ValueCountFrequency (%)
19990218000000 1
 
< 0.1%
19990223000000 4
 
0.1%
19990224000000 1
 
< 0.1%
19990225000000 3
 
0.1%
19990302000000 11
0.2%
19990303000000 11
0.2%
19990304000000 20
0.4%
19990308000000 15
0.3%
19990309000000 5
 
0.1%
19990310000000 18
0.4%
ValueCountFrequency (%)
20210331170502 1
< 0.1%
20210330165802 1
< 0.1%
20210329101926 1
< 0.1%
20210324102256 1
< 0.1%
20210324101915 1
< 0.1%
20210322180239 1
< 0.1%
20210322165604 1
< 0.1%
20210318135628 1
< 0.1%
20210317154704 1
< 0.1%
20210317154655 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
I
4118 
U
803 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 4118
83.7%
U 803
 
16.3%

Length

2024-04-18T07:56:05.056287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:05.138251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4118
83.7%
u 803
 
16.3%
Distinct403
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-02 02:40:00
2024-04-18T07:56:05.241222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:56:05.381687image/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 size38.6 KiB
일반이용업
4857 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079252
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row일반이용업
2nd row이용업 기타
3rd row이용업 기타
4th row일반이용업
5th row이용업 기타

Common Values

ValueCountFrequency (%)
일반이용업 4857
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-18T07:56:05.518934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:05.619944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4857
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3543
Distinct (%)78.1%
Missing387
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean387476.96
Minimum365567.31
Maximum407739.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:56:05.737943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum365567.31
5-th percentile379535.85
Q1383509.99
median387767.61
Q3390952.27
95-th percentile396566.02
Maximum407739.05
Range42171.732
Interquartile range (IQR)7442.2885

Descriptive statistics

Standard deviation5366.7864
Coefficient of variation (CV)0.013850595
Kurtosis0.59319905
Mean387476.96
Median Absolute Deviation (MAD)3664.9009
Skewness0.11322168
Sum1.7568205 × 109
Variance28802396
MonotonicityNot monotonic
2024-04-18T07:56:05.883658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400730.067993635 8
 
0.2%
388911.5369095 7
 
0.1%
392333.26238725 6
 
0.1%
382867.341996368 6
 
0.1%
381376.053716185 6
 
0.1%
383226.095097284 6
 
0.1%
379140.640735214 5
 
0.1%
387395.906194984 5
 
0.1%
382223.343951843 5
 
0.1%
392883.03399356 5
 
0.1%
Other values (3533) 4475
90.9%
(Missing) 387
 
7.9%
ValueCountFrequency (%)
365567.314347802 1
< 0.1%
365644.37444583 1
< 0.1%
366820.787750249 2
< 0.1%
367094.33981503 2
< 0.1%
367741.522165263 1
< 0.1%
367817.892752005 2
< 0.1%
367848.653623532 1
< 0.1%
370678.90382152 2
< 0.1%
370718.68095386 1
< 0.1%
370949.59316783 1
< 0.1%
ValueCountFrequency (%)
407739.046710947 3
0.1%
407530.734153914 2
< 0.1%
407147.657910169 1
 
< 0.1%
407041.865710589 1
 
< 0.1%
405392.621531798 1
 
< 0.1%
405392.303791546 1
 
< 0.1%
405390.19530521 1
 
< 0.1%
405172.859381319 2
< 0.1%
403998.423742534 1
 
< 0.1%
403520.239041375 1
 
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct3544
Distinct (%)78.2%
Missing387
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean186851.92
Minimum171356.38
Maximum206164.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:56:06.020142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum171356.38
5-th percentile178123.3
Q1181996.4
median187062.88
Q3191096.05
95-th percentile195809.02
Maximum206164.58
Range34808.197
Interquartile range (IQR)9099.6482

Descriptive statistics

Standard deviation5705.0688
Coefficient of variation (CV)0.030532568
Kurtosis-0.31702348
Mean186851.92
Median Absolute Deviation (MAD)4358.8805
Skewness0.13493704
Sum8.4718659 × 108
Variance32547810
MonotonicityNot monotonic
2024-04-18T07:56:06.157415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189145.674198705 8
 
0.2%
189958.23076541 7
 
0.1%
192077.564796439 6
 
0.1%
189006.221241803 6
 
0.1%
191452.16648903 6
 
0.1%
190804.667916156 6
 
0.1%
180128.072887035 5
 
0.1%
194837.216911232 5
 
0.1%
190370.669695795 5
 
0.1%
182777.347387507 5
 
0.1%
Other values (3534) 4475
90.9%
(Missing) 387
 
7.9%
ValueCountFrequency (%)
171356.377819897 1
 
< 0.1%
171745.287844766 1
 
< 0.1%
173914.718015169 2
< 0.1%
173969.719902491 1
 
< 0.1%
174068.494334685 1
 
< 0.1%
174097.616386311 2
< 0.1%
174101.406639044 1
 
< 0.1%
174279.164266 2
< 0.1%
174307.148168245 3
0.1%
174330.963124212 1
 
< 0.1%
ValueCountFrequency (%)
206164.575140106 1
 
< 0.1%
205995.903772118 2
< 0.1%
205709.503717342 2
< 0.1%
205678.034061751 2
< 0.1%
205671.36729929 3
0.1%
205473.9857853 1
 
< 0.1%
205441.669345456 1
 
< 0.1%
205178.593355644 1
 
< 0.1%
205097.400941024 1
 
< 0.1%
205095.722992576 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
일반이용업
4857 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079252
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row일반이용업
2nd row이용업 기타
3rd row이용업 기타
4th row일반이용업
5th row이용업 기타

Common Values

ValueCountFrequency (%)
일반이용업 4857
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-18T07:56:06.293511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:06.392007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4857
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct32
Distinct (%)1.0%
Missing1727
Missing (%)35.1%
Infinite0
Infinite (%)0.0%
Mean2.5078272
Minimum0
Maximum42
Zeros1208
Zeros (%)24.5%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:56:06.507852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile7
Maximum42
Range42
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.329974
Coefficient of variation (CV)1.3278323
Kurtosis29.229943
Mean2.5078272
Median Absolute Deviation (MAD)2
Skewness3.967477
Sum8010
Variance11.088727
MonotonicityNot monotonic
2024-04-18T07:56:06.633462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 1208
24.5%
3 480
 
9.8%
4 420
 
8.5%
2 407
 
8.3%
5 234
 
4.8%
1 167
 
3.4%
6 88
 
1.8%
7 53
 
1.1%
8 28
 
0.6%
9 25
 
0.5%
Other values (22) 84
 
1.7%
(Missing) 1727
35.1%
ValueCountFrequency (%)
0 1208
24.5%
1 167
 
3.4%
2 407
 
8.3%
3 480
 
9.8%
4 420
 
8.5%
5 234
 
4.8%
6 88
 
1.8%
7 53
 
1.1%
8 28
 
0.6%
9 25
 
0.5%
ValueCountFrequency (%)
42 2
< 0.1%
37 1
< 0.1%
34 1
< 0.1%
32 1
< 0.1%
30 1
< 0.1%
29 1
< 0.1%
28 1
< 0.1%
25 2
< 0.1%
23 1
< 0.1%
22 1
< 0.1%

건물지하층수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct10
Distinct (%)0.4%
Missing2229
Missing (%)45.3%
Infinite0
Infinite (%)0.0%
Mean0.52600297
Minimum0
Maximum208
Zeros1721
Zeros (%)35.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:56:06.735653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum208
Range208
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.0770715
Coefficient of variation (CV)7.7510427
Kurtosis2494.6336
Mean0.52600297
Median Absolute Deviation (MAD)0
Skewness49.038579
Sum1416
Variance16.622512
MonotonicityNot monotonic
2024-04-18T07:56:06.842668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 1721
35.0%
1 839
 
17.0%
2 84
 
1.7%
3 22
 
0.4%
5 13
 
0.3%
4 6
 
0.1%
6 4
 
0.1%
208 1
 
< 0.1%
15 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 2229
45.3%
ValueCountFrequency (%)
0 1721
35.0%
1 839
17.0%
2 84
 
1.7%
3 22
 
0.4%
4 6
 
0.1%
5 13
 
0.3%
6 4
 
0.1%
7 1
 
< 0.1%
15 1
 
< 0.1%
208 1
 
< 0.1%
ValueCountFrequency (%)
208 1
 
< 0.1%
15 1
 
< 0.1%
7 1
 
< 0.1%
6 4
 
0.1%
5 13
 
0.3%
4 6
 
0.1%
3 22
 
0.4%
2 84
 
1.7%
1 839
17.0%
0 1721
35.0%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)0.5%
Missing2099
Missing (%)42.7%
Infinite0
Infinite (%)0.0%
Mean1.2586818
Minimum0
Maximum12
Zeros1003
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:56:06.957320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4055597
Coefficient of variation (CV)1.1166919
Kurtosis5.9813674
Mean1.2586818
Median Absolute Deviation (MAD)1
Skewness1.8424094
Sum3552
Variance1.9755981
MonotonicityNot monotonic
2024-04-18T07:56:07.062948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 1003
20.4%
1 876
17.8%
2 510
 
10.4%
3 251
 
5.1%
4 90
 
1.8%
5 56
 
1.1%
6 19
 
0.4%
7 5
 
0.1%
10 4
 
0.1%
9 3
 
0.1%
Other values (3) 5
 
0.1%
(Missing) 2099
42.7%
ValueCountFrequency (%)
0 1003
20.4%
1 876
17.8%
2 510
10.4%
3 251
 
5.1%
4 90
 
1.8%
5 56
 
1.1%
6 19
 
0.4%
7 5
 
0.1%
8 3
 
0.1%
9 3
 
0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
11 1
 
< 0.1%
10 4
 
0.1%
9 3
 
0.1%
8 3
 
0.1%
7 5
 
0.1%
6 19
 
0.4%
5 56
 
1.1%
4 90
 
1.8%
3 251
5.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.5%
Missing2727
Missing (%)55.4%
Infinite0
Infinite (%)0.0%
Mean1.4143118
Minimum0
Maximum10
Zeros589
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:56:07.171611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3576875
Coefficient of variation (CV)0.95996339
Kurtosis3.9712924
Mean1.4143118
Median Absolute Deviation (MAD)1
Skewness1.517797
Sum3103
Variance1.8433154
MonotonicityNot monotonic
2024-04-18T07:56:07.304883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 759
 
15.4%
0 589
 
12.0%
2 477
 
9.7%
3 214
 
4.3%
4 81
 
1.6%
5 46
 
0.9%
6 15
 
0.3%
7 7
 
0.1%
10 3
 
0.1%
8 2
 
< 0.1%
(Missing) 2727
55.4%
ValueCountFrequency (%)
0 589
12.0%
1 759
15.4%
2 477
9.7%
3 214
 
4.3%
4 81
 
1.6%
5 46
 
0.9%
6 15
 
0.3%
7 7
 
0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
10 3
 
0.1%
9 1
 
< 0.1%
8 2
 
< 0.1%
7 7
 
0.1%
6 15
 
0.3%
5 46
 
0.9%
4 81
 
1.6%
3 214
 
4.3%
2 477
9.7%
1 759
15.4%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3068 
0
1526 
1
313 
2
 
13
22
 
1

Length

Max length4
Median length4
Mean length2.8705548
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3068
62.3%
0 1526
31.0%
1 313
 
6.4%
2 13
 
0.3%
22 1
 
< 0.1%

Length

2024-04-18T07:56:07.424263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:07.535503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3068
62.3%
0 1526
31.0%
1 313
 
6.4%
2 13
 
0.3%
22 1
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3719 
0
931 
1
 
264
2
 
6
4
 
1

Length

Max length4
Median length4
Mean length3.2672221
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3719
75.6%
0 931
 
18.9%
1 264
 
5.4%
2 6
 
0.1%
4 1
 
< 0.1%

Length

2024-04-18T07:56:07.653809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:07.752805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3719
75.6%
0 931
 
18.9%
1 264
 
5.4%
2 6
 
0.1%
4 1
 
< 0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2701 
0
2220 

Length

Max length4
Median length4
Mean length2.6466165
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 2701
54.9%
0 2220
45.1%

Length

2024-04-18T07:56:07.861856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:07.959387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2701
54.9%
0 2220
45.1%

양실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2700 
0
2220 
38
 
1

Length

Max length4
Median length4
Mean length2.6462101
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 2700
54.9%
0 2220
45.1%
38 1
 
< 0.1%

Length

2024-04-18T07:56:08.051258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:08.154308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2700
54.9%
0 2220
45.1%
38 1
 
< 0.1%

욕실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2700 
0
2220 
2
 
1

Length

Max length4
Median length4
Mean length2.6460069
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 2700
54.9%
0 2220
45.1%
2 1
 
< 0.1%

Length

2024-04-18T07:56:08.246657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:08.340828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2700
54.9%
0 2220
45.1%
2 1
 
< 0.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing100
Missing (%)2.0%
Memory size9.7 KiB
False
4821 
(Missing)
 
100
ValueCountFrequency (%)
False 4821
98.0%
(Missing) 100
 
2.0%
2024-04-18T07:56:08.413383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.4%
Missing606
Missing (%)12.3%
Infinite0
Infinite (%)0.0%
Mean3.1293163
Minimum0
Maximum24
Zeros338
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:56:08.490678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile8
Maximum24
Range24
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1270408
Coefficient of variation (CV)0.67971422
Kurtosis3.3855995
Mean3.1293163
Median Absolute Deviation (MAD)1
Skewness1.2810087
Sum13503
Variance4.5243026
MonotonicityNot monotonic
2024-04-18T07:56:08.596060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 1346
27.4%
3 884
18.0%
4 583
11.8%
0 338
 
6.9%
1 337
 
6.8%
5 262
 
5.3%
6 178
 
3.6%
7 168
 
3.4%
8 111
 
2.3%
9 66
 
1.3%
Other values (6) 42
 
0.9%
(Missing) 606
12.3%
ValueCountFrequency (%)
0 338
 
6.9%
1 337
 
6.8%
2 1346
27.4%
3 884
18.0%
4 583
11.8%
5 262
 
5.3%
6 178
 
3.6%
7 168
 
3.4%
8 111
 
2.3%
9 66
 
1.3%
ValueCountFrequency (%)
24 1
 
< 0.1%
15 1
 
< 0.1%
13 1
 
< 0.1%
12 3
 
0.1%
11 6
 
0.1%
10 30
 
0.6%
9 66
 
1.3%
8 111
2.3%
7 168
3.4%
6 178
3.6%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing4920
Missing (%)> 99.9%
Memory size38.6 KiB
2024-04-18T07:56:08.709463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row가설건축물
ValueCountFrequency (%)
가설건축물 1
100.0%
2024-04-18T07:56:08.957466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4919 
20050414
 
1
20050520
 
1

Length

Max length8
Median length4
Mean length4.0016257
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4919
> 99.9%
20050414 1
 
< 0.1%
20050520 1
 
< 0.1%

Length

2024-04-18T07:56:09.098558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:09.197825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4919
> 99.9%
20050414 1
 
< 0.1%
20050520 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4919 
20050414
 
1
20060425
 
1

Length

Max length8
Median length4
Mean length4.0016257
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4919
> 99.9%
20050414 1
 
< 0.1%
20060425 1
 
< 0.1%

Length

2024-04-18T07:56:09.309998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:09.412370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4919
> 99.9%
20050414 1
 
< 0.1%
20060425 1
 
< 0.1%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3956 
임대
937 
자가
 
28

Length

Max length4
Median length4
Mean length3.6078033
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> 3956
80.4%
임대 937
 
19.0%
자가 28
 
0.6%

Length

2024-04-18T07:56:09.518751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:09.623304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3956
80.4%
임대 937
 
19.0%
자가 28
 
0.6%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3359 
0
1562 

Length

Max length4
Median length4
Mean length3.0477545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 3359
68.3%
0 1562
31.7%

Length

2024-04-18T07:56:09.719974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:09.812659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3359
68.3%
0 1562
31.7%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4555 
0
 
349
1
 
17

Length

Max length4
Median length4
Mean length3.7768746
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4555
92.6%
0 349
 
7.1%
1 17
 
0.3%

Length

2024-04-18T07:56:09.917081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:10.010238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4555
92.6%
0 349
 
7.1%
1 17
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4544 
0
 
344
1
 
32
2
 
1

Length

Max length4
Median length4
Mean length3.7701687
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4544
92.3%
0 344
 
7.0%
1 32
 
0.7%
2 1
 
< 0.1%

Length

2024-04-18T07:56:10.103997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:10.202842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4544
92.3%
0 344
 
7.0%
1 32
 
0.7%
2 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3541 
0
1380 

Length

Max length4
Median length4
Mean length3.1587076
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 3541
72.0%
0 1380
 
28.0%

Length

2024-04-18T07:56:10.308832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:10.402301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3541
72.0%
0 1380
 
28.0%

침대수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3559 
0
1354 
2
 
4
3
 
2
1
 
1

Length

Max length4
Median length4
Mean length3.169681
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 3559
72.3%
0 1354
 
27.5%
2 4
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-18T07:56:10.498954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:56:10.606638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3559
72.3%
0 1354
 
27.5%
2 4
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
False
4921 
ValueCountFrequency (%)
False 4921
100.0%
2024-04-18T07:56:10.685935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4921
Missing (%)100.0%
Memory size43.4 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
01이용업05_19_01_P32800003280000-203-2018-0000320181102<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.12606080부산광역시 영도구 동삼동 1123-7부산광역시 영도구 상리로 35 (동삼동)49089대광 이발20201217113628U2020-12-19 02:40:00.0일반이용업388546.159102178137.194669일반이용업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
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23이용업05_19_01_P33500003350000-203-2019-0000120190121<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.80609858부산광역시 금정구 서동 118-27번지부산광역시 금정구 금사로 58-12, 1층 (서동)46321태후사랑20190121104943I2019-01-23 02:20:58.0이용업 기타392010.437951192967.812353이용업 기타3111<NA><NA>000N3<NA><NA><NA><NA>00000N<NA>
34이용업05_19_01_P33900003390000-203-2019-0000220190121<NA>1영업/정상1영업<NA><NA><NA><NA><NA>62.07617838부산광역시 사상구 주례동 507-1번지부산광역시 사상구 가야대로 290-4, 2층 (주례동)47013퀸즈헤나20190129144431U2019-01-31 02:40:00.0일반이용업382596.186669185283.584397일반이용업002200000N2<NA><NA><NA><NA>00000N<NA>
45이용업05_19_01_P33900003390000-203-2019-0000320190123<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.91617829부산광역시 사상구 엄궁동 266번지부산광역시 사상구 엄궁북로4번가길 17 (엄궁동, 진주식육점)47041엄궁퀀즈헤나교실20190130162256U2019-02-01 02:40:00.0이용업 기타379535.304649182741.485999이용업 기타001100000N1<NA><NA><NA><NA>00000N<NA>
56이용업05_19_01_P33300003330000-203-2019-0000120190121<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.70612894부산광역시 해운대구 우동 1417번지 부산유스호스텔아르피나부산광역시 해운대구 해운대해변로 35, 부산유스호스텔아르피나 지하1층 (우동)48089아르피나캇트20190121155039I2019-01-23 02:20:58.0일반이용업394725.789471187180.759947일반이용업00<NA><NA>1<NA>000N2<NA><NA><NA><NA>00000N<NA>
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번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
49114912이용업05_19_01_P34000003400000-203-1982-0041019820510<NA>3폐업2폐업20210118<NA><NA><NA>051 5092161.00619873부산광역시 기장군 철마면 송정리 5-0 T통B반부산광역시 기장군 철마면 여락송정로 36346002대우정밀이용소20210118134937U2021-01-20 02:40:00.0일반이용업394117.140329202127.107015일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
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49164917이용업05_19_01_P34000003400000-203-1999-0012019990727<NA>3폐업2폐업20110920<NA><NA><NA>051 722391543.60619901부산광역시 기장군 기장읍 교리 348-12번지<NA><NA>교리이용원20100315131009I2018-08-31 23:59:59.0일반이용업401641.046222196906.772649일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N6<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
49174918이용업05_19_01_P34000003400000-203-2010-0000320101005<NA>3폐업2폐업20111018<NA><NA><NA>070 5146656615.00619952부산광역시 기장군 장안읍 길천리 265번지 길천해수탕<NA><NA>길천해수탕이용원20101005114647I2018-08-31 23:59:59.0이용업 기타407739.046711205671.367299이용업 기타4133<NA><NA>000N2<NA><NA><NA>임대0<NA><NA>00N<NA>
49184919이용업05_19_01_P33000003300000-203-2018-0000720181218<NA>3폐업2폐업20201214<NA><NA><NA><NA>23.13607833부산광역시 동래구 온천동 210-47부산광역시 동래구 금강공원로 25-1, 2층 (온천동)47712아:스타헤어샵20201214102819U2020-12-16 02:40:00.0일반이용업389468.057399193064.168736일반이용업302200000N4<NA><NA><NA><NA>0<NA><NA>00N<NA>
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49204921이용업05_19_01_P32800003280000-203-2021-0000120210129<NA>3폐업2폐업20210225<NA><NA><NA><NA>66.00606042부산광역시 영도구 영선동2가 44-2부산광역시 영도구 영선대로 67 (영선동2가)49056긱스(geeks)20210225131906U2021-02-27 02:40:00.0일반이용업386100.884001178372.437035일반이용업0011<NA><NA>000N4<NA><NA><NA><NA>00000N<NA>