Overview

Dataset statistics

Number of variables51
Number of observations4908
Missing cells47740
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

Description2021-04-01
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 (57.1%)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 (75.2%)Imbalance
남성종사자수 is highly imbalanced (79.2%)Imbalance
침대수 is highly imbalanced (66.5%)Imbalance
인허가취소일자 has 4908 (100.0%) missing valuesMissing
폐업일자 has 1322 (26.9%) missing valuesMissing
휴업시작일자 has 4908 (100.0%) missing valuesMissing
휴업종료일자 has 4908 (100.0%) missing valuesMissing
재개업일자 has 4908 (100.0%) missing valuesMissing
소재지전화 has 1398 (28.5%) missing valuesMissing
도로명전체주소 has 2596 (52.9%) missing valuesMissing
도로명우편번호 has 2649 (54.0%) missing valuesMissing
좌표정보(x) has 387 (7.9%) missing valuesMissing
좌표정보(y) has 387 (7.9%) missing valuesMissing
건물지상층수 has 1729 (35.2%) missing valuesMissing
건물지하층수 has 2231 (45.5%) missing valuesMissing
사용시작지상층 has 2099 (42.8%) missing valuesMissing
사용끝지상층 has 2726 (55.5%) missing valuesMissing
발한실여부 has 100 (2.0%) missing valuesMissing
의자수 has 608 (12.4%) missing valuesMissing
조건부허가신고사유 has 4907 (> 99.9%) missing valuesMissing
Unnamed: 50 has 4908 (100.0%) missing valuesMissing
인허가일자 is highly skewed (γ1 = -27.14606003)Skewed
폐업일자 is highly skewed (γ1 = -28.14241719)Skewed
건물지하층수 is highly skewed (γ1 = 48.91727822)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 1199 (24.4%) zerosZeros
건물지하층수 has 1709 (34.8%) zerosZeros
사용시작지상층 has 1001 (20.4%) zerosZeros
사용끝지상층 has 587 (12.0%) zerosZeros
의자수 has 338 (6.9%) zerosZeros

Reproduction

Analysis started2024-04-17 22:52:39.373191
Analysis finished2024-04-17 22:52:40.920011
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct4908
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2454.5
Minimum1
Maximum4908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:40.987113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile246.35
Q11227.75
median2454.5
Q33681.25
95-th percentile4662.65
Maximum4908
Range4907
Interquartile range (IQR)2453.5

Descriptive statistics

Standard deviation1416.9619
Coefficient of variation (CV)0.57729146
Kurtosis-1.2
Mean2454.5
Median Absolute Deviation (MAD)1227
Skewness0
Sum12046686
Variance2007781
MonotonicityStrictly increasing
2024-04-18T07:52:41.165412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3271 1
 
< 0.1%
3278 1
 
< 0.1%
3277 1
 
< 0.1%
3276 1
 
< 0.1%
3275 1
 
< 0.1%
3274 1
 
< 0.1%
3273 1
 
< 0.1%
3272 1
 
< 0.1%
3270 1
 
< 0.1%
Other values (4898) 4898
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 (%)
4908 1
< 0.1%
4907 1
< 0.1%
4906 1
< 0.1%
4905 1
< 0.1%
4904 1
< 0.1%
4903 1
< 0.1%
4902 1
< 0.1%
4901 1
< 0.1%
4900 1
< 0.1%
4899 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
이용업
4908 

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 4908
100.0%

Length

2024-04-18T07:52:41.357867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:41.466634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용업 4908
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
05_19_01_P
4908 

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 4908
100.0%

Length

2024-04-18T07:52:41.557236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:41.642788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 4908
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3324541.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:41.719602image/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 deviation40375.425
Coefficient of variation (CV)0.012144659
Kurtosis-0.9408151
Mean3324541.6
Median Absolute Deviation (MAD)30000
Skewness0.056930781
Sum1.631685 × 1010
Variance1.630175 × 109
MonotonicityNot monotonic
2024-04-18T07:52:41.827675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 500
10.2%
3340000 496
10.1%
3300000 419
8.5%
3320000 409
 
8.3%
3330000 392
 
8.0%
3350000 381
 
7.8%
3390000 332
 
6.8%
3370000 331
 
6.7%
3310000 323
 
6.6%
3380000 283
 
5.8%
Other values (6) 1042
21.2%
ValueCountFrequency (%)
3250000 165
 
3.4%
3260000 213
4.3%
3270000 257
5.2%
3280000 208
4.2%
3290000 500
10.2%
3300000 419
8.5%
3310000 323
6.6%
3320000 409
8.3%
3330000 392
8.0%
3340000 496
10.1%
ValueCountFrequency (%)
3400000 110
 
2.2%
3390000 332
6.8%
3380000 283
5.8%
3370000 331
6.7%
3360000 89
 
1.8%
3350000 381
7.8%
3340000 496
10.1%
3330000 392
8.0%
3320000 409
8.3%
3310000 323
6.6%

관리번호
Text

UNIQUE 

Distinct4908
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
2024-04-18T07:52:42.033226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters107976
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

Unique4908 ?
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%
3380000-203-1997-00001 1
 
< 0.1%
3380000-203-1969-00001 1
 
< 0.1%
3380000-203-1989-00014 1
 
< 0.1%
3380000-203-1996-00007 1
 
< 0.1%
3380000-203-2001-00006 1
 
< 0.1%
3380000-203-1994-00007 1
 
< 0.1%
3380000-203-2001-00005 1
 
< 0.1%
3380000-203-2008-00005 1
 
< 0.1%
3380000-203-2002-00003 1
 
< 0.1%
Other values (4898) 4898
99.8%
2024-04-18T07:52:42.344689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43130
39.9%
3 15421
 
14.3%
- 14724
 
13.6%
2 10842
 
10.0%
1 6145
 
5.7%
9 6017
 
5.6%
8 2654
 
2.5%
7 2443
 
2.3%
4 2330
 
2.2%
6 2136
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93252
86.4%
Dash Punctuation 14724
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43130
46.3%
3 15421
 
16.5%
2 10842
 
11.6%
1 6145
 
6.6%
9 6017
 
6.5%
8 2654
 
2.8%
7 2443
 
2.6%
4 2330
 
2.5%
6 2136
 
2.3%
5 2134
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 14724
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107976
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43130
39.9%
3 15421
 
14.3%
- 14724
 
13.6%
2 10842
 
10.0%
1 6145
 
5.7%
9 6017
 
5.6%
8 2654
 
2.5%
7 2443
 
2.3%
4 2330
 
2.2%
6 2136
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107976
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43130
39.9%
3 15421
 
14.3%
- 14724
 
13.6%
2 10842
 
10.0%
1 6145
 
5.7%
9 6017
 
5.6%
8 2654
 
2.5%
7 2443
 
2.3%
4 2330
 
2.2%
6 2136
 
2.0%

인허가일자
Real number (ℝ)

SKEWED 

Distinct3640
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19958155
Minimum9710223
Maximum20210222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:42.493788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9710223
5-th percentile19691123
Q119871229
median19980416
Q320051208
95-th percentile20170604
Maximum20210222
Range10499999
Interquartile range (IQR)179979.5

Descriptive statistics

Standard deviation201002.02
Coefficient of variation (CV)0.010071172
Kurtosis1376.235
Mean19958155
Median Absolute Deviation (MAD)89990.5
Skewness-27.14606
Sum9.7954626 × 1010
Variance4.0401811 × 1010
MonotonicityNot monotonic
2024-04-18T07:52:42.622918image/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%
20030410 7
 
0.1%
19721129 7
 
0.1%
20030213 6
 
0.1%
Other values (3630) 4751
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 (%)
20210222 2
< 0.1%
20210208 1
< 0.1%
20210202 2
< 0.1%
20210201 1
< 0.1%
20210129 1
< 0.1%
20210125 1
< 0.1%
20210122 1
< 0.1%
20210119 1
< 0.1%
20210107 1
< 0.1%
20201217 2
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4908
Missing (%)100.0%
Memory size43.3 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
3
3586 
1
1322 

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 3586
73.1%
1 1322
 
26.9%

Length

2024-04-18T07:52:42.737493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:42.819908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3586
73.1%
1 1322
 
26.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
폐업
3586 
영업/정상
1322 

Length

Max length5
Median length2
Mean length2.8080685
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 3586
73.1%
영업/정상 1322
 
26.9%

Length

2024-04-18T07:52:42.917429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:43.013587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3586
73.1%
영업/정상 1322
 
26.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
2
3586 
1
1322 

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 3586
73.1%
1 1322
 
26.9%

Length

2024-04-18T07:52:43.101656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:43.184222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3586
73.1%
1 1322
 
26.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
폐업
3586 
영업
1322 

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 3586
73.1%
영업 1322
 
26.9%

Length

2024-04-18T07:52:43.307483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:43.392854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3586
73.1%
영업 1322
 
26.9%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct2267
Distinct (%)63.2%
Missing1322
Missing (%)26.9%
Infinite0
Infinite (%)0.0%
Mean20066092
Minimum2019071
Maximum20800812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:43.499489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2019071
5-th percentile20000118
Q120040503
median20070614
Q320130607
95-th percentile20190484
Maximum20800812
Range18781741
Interquartile range (IQR)90104

Descriptive statistics

Standard deviation454502.54
Coefficient of variation (CV)0.022650278
Kurtosis902.10119
Mean20066092
Median Absolute Deviation (MAD)39899.5
Skewness-28.142417
Sum7.1957004 × 1010
Variance2.0657256 × 1011
MonotonicityNot monotonic
2024-04-18T07:52:43.635176image/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 (2257) 3294
67.1%
(Missing) 1322
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%
20210225 1
< 0.1%
20210222 1
< 0.1%
20210219 1
< 0.1%
20210216 1
< 0.1%
20210215 1
< 0.1%
20210202 1
< 0.1%
20210125 1
< 0.1%
20210122 1
< 0.1%
20210119 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4908
Missing (%)100.0%
Memory size43.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4908
Missing (%)100.0%
Memory size43.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4908
Missing (%)100.0%
Memory size43.3 KiB

소재지전화
Text

MISSING 

Distinct2873
Distinct (%)81.9%
Missing1398
Missing (%)28.5%
Memory size38.5 KiB
2024-04-18T07:52:43.937775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.939886
Min length3

Characters and Unicode

Total characters34889
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

Unique2724 ?
Unique (%)77.6%

Sample

1st row051 727 5320
2nd row051 728 3988
3rd row051 364 2651
4th row051 7549944
5th row051 7596288
ValueCountFrequency (%)
051 3300
48.3%
893 8
 
0.1%
554 8
 
0.1%
727 6
 
0.1%
868 6
 
0.1%
754 6
 
0.1%
051643 6
 
0.1%
292 6
 
0.1%
305 5
 
0.1%
051624 5
 
0.1%
Other values (3075) 3480
50.9%
2024-04-18T07:52:44.367018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6045
17.3%
1 5285
15.1%
0 5186
14.9%
3342
9.6%
2 2843
8.1%
4 2312
 
6.6%
6 2243
 
6.4%
3 2209
 
6.3%
7 2076
 
6.0%
8 1970
 
5.6%
Other values (2) 1378
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31545
90.4%
Space Separator 3342
 
9.6%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6045
19.2%
1 5285
16.8%
0 5186
16.4%
2 2843
9.0%
4 2312
 
7.3%
6 2243
 
7.1%
3 2209
 
7.0%
7 2076
 
6.6%
8 1970
 
6.2%
9 1376
 
4.4%
Space Separator
ValueCountFrequency (%)
3342
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34889
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6045
17.3%
1 5285
15.1%
0 5186
14.9%
3342
9.6%
2 2843
8.1%
4 2312
 
6.6%
6 2243
 
6.4%
3 2209
 
6.3%
7 2076
 
6.0%
8 1970
 
5.6%
Other values (2) 1378
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34889
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6045
17.3%
1 5285
15.1%
0 5186
14.9%
3342
9.6%
2 2843
8.1%
4 2312
 
6.6%
6 2243
 
6.4%
3 2209
 
6.3%
7 2076
 
6.0%
8 1970
 
5.6%
Other values (2) 1378
 
3.9%
Distinct2126
Distinct (%)43.6%
Missing34
Missing (%)0.7%
Memory size38.5 KiB
2024-04-18T07:52:44.726284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.6317193
Min length3

Characters and Unicode

Total characters22575
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

Unique1375 ?
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 (2116) 4049
83.1%
2024-04-18T07:52:45.173403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4874
21.6%
0 4468
19.8%
1 2285
10.1%
2 2174
9.6%
5 1418
 
6.3%
3 1407
 
6.2%
8 1403
 
6.2%
4 1291
 
5.7%
6 1269
 
5.6%
9 999
 
4.4%
Other values (2) 987
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17697
78.4%
Other Punctuation 4878
 
21.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4468
25.2%
1 2285
12.9%
2 2174
12.3%
5 1418
 
8.0%
3 1407
 
8.0%
8 1403
 
7.9%
4 1291
 
7.3%
6 1269
 
7.2%
9 999
 
5.6%
7 983
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 4874
99.9%
, 4
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 22575
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4874
21.6%
0 4468
19.8%
1 2285
10.1%
2 2174
9.6%
5 1418
 
6.3%
3 1407
 
6.2%
8 1403
 
6.2%
4 1291
 
5.7%
6 1269
 
5.6%
9 999
 
4.4%
Other values (2) 987
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22575
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4874
21.6%
0 4468
19.8%
1 2285
10.1%
2 2174
9.6%
5 1418
 
6.3%
3 1407
 
6.2%
8 1403
 
6.2%
4 1291
 
5.7%
6 1269
 
5.6%
9 999
 
4.4%
Other values (2) 987
 
4.4%

소재지우편번호
Real number (ℝ)

Distinct777
Distinct (%)15.9%
Missing24
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean610454.57
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:45.339513image/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 deviation5293.7242
Coefficient of variation (CV)0.0086717742
Kurtosis-1.0179082
Mean610454.57
Median Absolute Deviation (MAD)4962
Skewness-0.18815095
Sum2.9814601 × 109
Variance28023516
MonotonicityNot monotonic
2024-04-18T07:52:45.479627image/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
 
0.6%
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) 4629
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%
Distinct4337
Distinct (%)88.4%
Missing3
Missing (%)0.1%
Memory size38.5 KiB
2024-04-18T07:52:45.777652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length48
Mean length23.608767
Min length6

Characters and Unicode

Total characters115801
Distinct characters372
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

Unique3903 ?
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 4904
 
22.3%
t통b반 763
 
3.5%
부산진구 500
 
2.3%
사하구 498
 
2.3%
동래구 419
 
1.9%
북구 411
 
1.9%
해운대구 392
 
1.8%
금정구 381
 
1.7%
사상구 332
 
1.5%
연제구 329
 
1.5%
Other values (4714) 13064
59.4%
2024-04-18T07:52:46.207987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17092
 
14.8%
5815
 
5.0%
5768
 
5.0%
5759
 
5.0%
5074
 
4.4%
1 5052
 
4.4%
5037
 
4.3%
4931
 
4.3%
4910
 
4.2%
4741
 
4.1%
Other values (362) 51622
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68786
59.4%
Decimal Number 23363
 
20.2%
Space Separator 17092
 
14.8%
Dash Punctuation 4461
 
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 (%)
5815
 
8.5%
5768
 
8.4%
5759
 
8.4%
5074
 
7.4%
5037
 
7.3%
4931
 
7.2%
4910
 
7.1%
4741
 
6.9%
4544
 
6.6%
944
 
1.4%
Other values (329) 21263
30.9%
Uppercase Letter
ValueCountFrequency (%)
B 783
49.8%
T 766
48.7%
A 10
 
0.6%
L 3
 
0.2%
G 2
 
0.1%
C 2
 
0.1%
F 2
 
0.1%
O 1
 
0.1%
S 1
 
0.1%
P 1
 
0.1%
Other values (2) 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 5052
21.6%
2 3151
13.5%
3 2700
11.6%
4 2228
9.5%
5 2162
9.3%
6 1728
 
7.4%
0 1708
 
7.3%
8 1661
 
7.1%
7 1605
 
6.9%
9 1368
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 76
86.4%
@ 6
 
6.8%
/ 3
 
3.4%
. 2
 
2.3%
& 1
 
1.1%
Space Separator
ValueCountFrequency (%)
17092
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4461
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 68784
59.4%
Common 45441
39.2%
Latin 1574
 
1.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5815
 
8.5%
5768
 
8.4%
5759
 
8.4%
5074
 
7.4%
5037
 
7.3%
4931
 
7.2%
4910
 
7.1%
4741
 
6.9%
4544
 
6.6%
944
 
1.4%
Other values (328) 21261
30.9%
Common
ValueCountFrequency (%)
17092
37.6%
1 5052
 
11.1%
- 4461
 
9.8%
2 3151
 
6.9%
3 2700
 
5.9%
4 2228
 
4.9%
5 2162
 
4.8%
6 1728
 
3.8%
0 1708
 
3.8%
8 1661
 
3.7%
Other values (10) 3498
 
7.7%
Latin
ValueCountFrequency (%)
B 783
49.7%
T 766
48.7%
A 10
 
0.6%
L 3
 
0.2%
G 2
 
0.1%
C 2
 
0.1%
F 2
 
0.1%
O 1
 
0.1%
S 1
 
0.1%
P 1
 
0.1%
Other values (3) 3
 
0.2%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68784
59.4%
ASCII 47015
40.6%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17092
36.4%
1 5052
 
10.7%
- 4461
 
9.5%
2 3151
 
6.7%
3 2700
 
5.7%
4 2228
 
4.7%
5 2162
 
4.6%
6 1728
 
3.7%
0 1708
 
3.6%
8 1661
 
3.5%
Other values (23) 5072
 
10.8%
Hangul
ValueCountFrequency (%)
5815
 
8.5%
5768
 
8.4%
5759
 
8.4%
5074
 
7.4%
5037
 
7.3%
4931
 
7.2%
4910
 
7.1%
4741
 
6.9%
4544
 
6.6%
944
 
1.4%
Other values (328) 21261
30.9%
CJK
ValueCountFrequency (%)
2
100.0%

도로명전체주소
Text

MISSING 

Distinct2227
Distinct (%)96.3%
Missing2596
Missing (%)52.9%
Memory size38.5 KiB
2024-04-18T07:52:46.550421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length54
Mean length28.666522
Min length17

Characters and Unicode

Total characters66277
Distinct characters394
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

Unique2149 ?
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 2312
 
18.0%
1층 278
 
2.2%
부산진구 265
 
2.1%
동래구 225
 
1.7%
사하구 213
 
1.7%
사상구 188
 
1.5%
금정구 184
 
1.4%
해운대구 180
 
1.4%
남구 163
 
1.3%
북구 153
 
1.2%
Other values (2632) 8712
67.7%
2024-04-18T07:52:47.025680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10564
 
15.9%
2996
 
4.5%
2817
 
4.3%
2782
 
4.2%
1 2508
 
3.8%
2423
 
3.7%
2420
 
3.7%
2397
 
3.6%
2316
 
3.5%
) 2279
 
3.4%
Other values (384) 32775
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39537
59.7%
Space Separator 10564
 
15.9%
Decimal Number 10112
 
15.3%
Close Punctuation 2279
 
3.4%
Open Punctuation 2279
 
3.4%
Other Punctuation 1041
 
1.6%
Dash Punctuation 426
 
0.6%
Uppercase Letter 36
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2996
 
7.6%
2817
 
7.1%
2782
 
7.0%
2423
 
6.1%
2420
 
6.1%
2397
 
6.1%
2316
 
5.9%
2231
 
5.6%
1266
 
3.2%
1200
 
3.0%
Other values (354) 16689
42.2%
Decimal Number
ValueCountFrequency (%)
1 2508
24.8%
2 1548
15.3%
3 1184
11.7%
4 865
 
8.6%
5 803
 
7.9%
0 718
 
7.1%
6 682
 
6.7%
7 650
 
6.4%
8 602
 
6.0%
9 552
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 18
50.0%
A 6
 
16.7%
T 6
 
16.7%
S 1
 
2.8%
C 1
 
2.8%
L 1
 
2.8%
H 1
 
2.8%
E 1
 
2.8%
F 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 1028
98.8%
/ 5
 
0.5%
@ 5
 
0.5%
. 2
 
0.2%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
10564
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2279
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2279
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 426
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39537
59.7%
Common 26703
40.3%
Latin 37
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2996
 
7.6%
2817
 
7.1%
2782
 
7.0%
2423
 
6.1%
2420
 
6.1%
2397
 
6.1%
2316
 
5.9%
2231
 
5.6%
1266
 
3.2%
1200
 
3.0%
Other values (354) 16689
42.2%
Common
ValueCountFrequency (%)
10564
39.6%
1 2508
 
9.4%
) 2279
 
8.5%
( 2279
 
8.5%
2 1548
 
5.8%
3 1184
 
4.4%
, 1028
 
3.8%
4 865
 
3.2%
5 803
 
3.0%
0 718
 
2.7%
Other values (10) 2927
 
11.0%
Latin
ValueCountFrequency (%)
B 18
48.6%
A 6
 
16.2%
T 6
 
16.2%
S 1
 
2.7%
C 1
 
2.7%
L 1
 
2.7%
H 1
 
2.7%
e 1
 
2.7%
E 1
 
2.7%
F 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39537
59.7%
ASCII 26740
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10564
39.5%
1 2508
 
9.4%
) 2279
 
8.5%
( 2279
 
8.5%
2 1548
 
5.8%
3 1184
 
4.4%
, 1028
 
3.8%
4 865
 
3.2%
5 803
 
3.0%
0 718
 
2.7%
Other values (20) 2964
 
11.1%
Hangul
ValueCountFrequency (%)
2996
 
7.6%
2817
 
7.1%
2782
 
7.0%
2423
 
6.1%
2420
 
6.1%
2397
 
6.1%
2316
 
5.9%
2231
 
5.6%
1266
 
3.2%
1200
 
3.0%
Other values (354) 16689
42.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1156
Distinct (%)51.2%
Missing2649
Missing (%)54.0%
Infinite0
Infinite (%)0.0%
Mean47828.887
Minimum46002
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:47.155988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46242
Q147008.5
median47802
Q348726
95-th percentile49407
Maximum49525
Range3523
Interquartile range (IQR)1717.5

Descriptive statistics

Standard deviation1011.613
Coefficient of variation (CV)0.021150671
Kurtosis-1.1155007
Mean47828.887
Median Absolute Deviation (MAD)806
Skewness0.0165285
Sum1.0804546 × 108
Variance1023360.9
MonotonicityNot monotonic
2024-04-18T07:52:47.278070image/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%
47511 7
 
0.1%
47603 7
 
0.1%
48501 7
 
0.1%
46321 7
 
0.1%
48095 7
 
0.1%
49217 7
 
0.1%
Other values (1146) 2176
44.3%
(Missing) 2649
54.0%
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%
Distinct3328
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
2024-04-18T07:52:47.568179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length4.7638549
Min length1

Characters and Unicode

Total characters23381
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

Unique2651 ?
Unique (%)54.0%

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%
우리 28
 
0.5%
제일 28
 
0.5%
블루클럽 24
 
0.4%
캇트실 23
 
0.4%
현대이용원 23
 
0.4%
Other values (3188) 5008
88.1%
2024-04-18T07:52:47.989603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2090
 
8.9%
2019
 
8.6%
1934
 
8.3%
977
 
4.2%
843
 
3.6%
776
 
3.3%
583
 
2.5%
470
 
2.0%
402
 
1.7%
387
 
1.7%
Other values (559) 12900
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22161
94.8%
Space Separator 776
 
3.3%
Uppercase Letter 145
 
0.6%
Lowercase Letter 108
 
0.5%
Open Punctuation 64
 
0.3%
Close Punctuation 64
 
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 (%)
2090
 
9.4%
2019
 
9.1%
1934
 
8.7%
977
 
4.4%
843
 
3.8%
583
 
2.6%
470
 
2.1%
402
 
1.8%
387
 
1.7%
343
 
1.5%
Other values (499) 12113
54.7%
Uppercase Letter
ValueCountFrequency (%)
B 19
13.1%
O 13
 
9.0%
H 11
 
7.6%
E 10
 
6.9%
R 10
 
6.9%
S 9
 
6.2%
A 9
 
6.2%
M 8
 
5.5%
N 7
 
4.8%
L 7
 
4.8%
Other values (12) 42
29.0%
Lowercase Letter
ValueCountFrequency (%)
r 15
13.9%
e 11
10.2%
b 9
8.3%
a 9
8.3%
s 8
 
7.4%
o 8
 
7.4%
i 8
 
7.4%
h 7
 
6.5%
u 6
 
5.6%
y 5
 
4.6%
Other values (8) 22
20.4%
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 (%)
776
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
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 22158
94.8%
Common 967
 
4.1%
Latin 253
 
1.1%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2090
 
9.4%
2019
 
9.1%
1934
 
8.7%
977
 
4.4%
843
 
3.8%
583
 
2.6%
470
 
2.1%
402
 
1.8%
387
 
1.7%
343
 
1.5%
Other values (496) 12110
54.7%
Latin
ValueCountFrequency (%)
B 19
 
7.5%
r 15
 
5.9%
O 13
 
5.1%
H 11
 
4.3%
e 11
 
4.3%
E 10
 
4.0%
R 10
 
4.0%
S 9
 
3.6%
b 9
 
3.6%
A 9
 
3.6%
Other values (30) 137
54.2%
Common
ValueCountFrequency (%)
776
80.2%
( 64
 
6.6%
) 64
 
6.6%
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 22158
94.8%
ASCII 1219
 
5.2%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2090
 
9.4%
2019
 
9.1%
1934
 
8.7%
977
 
4.4%
843
 
3.8%
583
 
2.6%
470
 
2.1%
402
 
1.8%
387
 
1.7%
343
 
1.5%
Other values (496) 12110
54.7%
ASCII
ValueCountFrequency (%)
776
63.7%
( 64
 
5.3%
) 64
 
5.3%
B 19
 
1.6%
r 15
 
1.2%
O 13
 
1.1%
2 11
 
0.9%
H 11
 
0.9%
e 11
 
0.9%
. 10
 
0.8%
Other values (49) 225
 
18.5%
None
ValueCountFrequency (%)
· 1
100.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

최종수정시점
Real number (ℝ)

Distinct3295
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0095389 × 1013
Minimum1.9990218 × 1013
Maximum2.0210225 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:48.136432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile1.9990625 × 1013
Q12.0031024 × 1013
median2.0080304 × 1013
Q32.0160621 × 1013
95-th percentile2.0201116 × 1013
Maximum2.0210225 × 1013
Range2.2000717 × 1011
Interquartile range (IQR)1.2959762 × 1011

Descriptive statistics

Standard deviation6.8260852 × 1010
Coefficient of variation (CV)0.0033968416
Kurtosis-1.3500029
Mean2.0095389 × 1013
Median Absolute Deviation (MAD)4.9992603 × 1010
Skewness0.2663621
Sum9.8628167 × 1016
Variance4.6595439 × 1021
MonotonicityNot monotonic
2024-04-18T07:52:48.283551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030211000000 57
 
1.2%
20070501000000 49
 
1.0%
20020424000000 38
 
0.8%
20031215000000 38
 
0.8%
20030311000000 37
 
0.8%
19990428000000 35
 
0.7%
20020423000000 34
 
0.7%
20030221000000 33
 
0.7%
20030318000000 33
 
0.7%
20030616000000 31
 
0.6%
Other values (3285) 4523
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 (%)
20210225165407 1
< 0.1%
20210225132112 1
< 0.1%
20210225131906 1
< 0.1%
20210222145413 1
< 0.1%
20210222140400 1
< 0.1%
20210222131454 1
< 0.1%
20210222104030 1
< 0.1%
20210222100147 1
< 0.1%
20210222093423 1
< 0.1%
20210219212929 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
I
4118 
U
790 

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
83.9%
U 790
 
16.1%

Length

2024-04-18T07:52:48.405942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:48.505458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4118
83.9%
u 790
 
16.1%
Distinct389
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
Minimum2018-08-31 23:59:59
Maximum2021-02-27 02:40:00
2024-04-18T07:52:48.607479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:52:49.325002image/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 size38.5 KiB
일반이용업
4844 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079462
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 4844
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-18T07:52:49.461967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:49.660509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4844
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3536
Distinct (%)78.2%
Missing387
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean387472.89
Minimum365567.31
Maximum407739.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:49.781699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum365567.31
5-th percentile379535.3
Q1383506.67
median387767.42
Q3390958.44
95-th percentile396568.71
Maximum407739.05
Range42171.732
Interquartile range (IQR)7451.7711

Descriptive statistics

Standard deviation5372.3848
Coefficient of variation (CV)0.013865189
Kurtosis0.58836055
Mean387472.89
Median Absolute Deviation (MAD)3671.2757
Skewness0.11492589
Sum1.7517649 × 109
Variance28862519
MonotonicityNot monotonic
2024-04-18T07:52:49.925978image/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%
382867.341996368 6
 
0.1%
381376.053716185 6
 
0.1%
392333.26238725 6
 
0.1%
383226.095097284 6
 
0.1%
385778.531788427 5
 
0.1%
383311.822218513 5
 
0.1%
384400.384127602 5
 
0.1%
379836.31092597 5
 
0.1%
Other values (3526) 4462
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 

Distinct3537
Distinct (%)78.2%
Missing387
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean186847.31
Minimum171356.38
Maximum206164.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:50.054681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum171356.38
5-th percentile178118.53
Q1181986.09
median187062.88
Q3191093.16
95-th percentile195806.31
Maximum206164.58
Range34808.197
Interquartile range (IQR)9107.07

Descriptive statistics

Standard deviation5703.6247
Coefficient of variation (CV)0.030525592
Kurtosis-0.31693432
Mean186847.31
Median Absolute Deviation (MAD)4358.8805
Skewness0.13455512
Sum8.4473668 × 108
Variance32531335
MonotonicityNot monotonic
2024-04-18T07:52:50.229620image/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%
191452.16648903 6
 
0.1%
189006.221241803 6
 
0.1%
190804.667916156 6
 
0.1%
192077.564796439 6
 
0.1%
181489.395657635 5
 
0.1%
181326.139093378 5
 
0.1%
180078.851352476 5
 
0.1%
182777.347387507 5
 
0.1%
Other values (3527) 4462
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 size38.5 KiB
일반이용업
4844 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079462
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 4844
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-18T07:52:50.371063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:50.488572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4844
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%
Missing1729
Missing (%)35.2%
Infinite0
Infinite (%)0.0%
Mean2.5124253
Minimum0
Maximum42
Zeros1199
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:50.598808image/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 deviation3.3341426
Coefficient of variation (CV)1.3270614
Kurtosis29.197368
Mean2.5124253
Median Absolute Deviation (MAD)2
Skewness3.9678256
Sum7987
Variance11.116507
MonotonicityNot monotonic
2024-04-18T07:52:50.806514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 1199
24.4%
3 478
 
9.7%
4 419
 
8.5%
2 406
 
8.3%
5 233
 
4.7%
1 167
 
3.4%
6 87
 
1.8%
7 53
 
1.1%
8 28
 
0.6%
9 25
 
0.5%
Other values (22) 84
 
1.7%
(Missing) 1729
35.2%
ValueCountFrequency (%)
0 1199
24.4%
1 167
 
3.4%
2 406
 
8.3%
3 478
 
9.7%
4 419
 
8.5%
5 233
 
4.7%
6 87
 
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%
Missing2231
Missing (%)45.5%
Infinite0
Infinite (%)0.0%
Mean0.52708256
Minimum0
Maximum208
Zeros1709
Zeros (%)34.8%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:50.926136image/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 deviation4.0880301
Coefficient of variation (CV)7.755958
Kurtosis2481.7897
Mean0.52708256
Median Absolute Deviation (MAD)0
Skewness48.917278
Sum1411
Variance16.71199
MonotonicityNot monotonic
2024-04-18T07:52:51.036407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 1709
34.8%
1 837
 
17.1%
2 84
 
1.7%
3 21
 
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) 2231
45.5%
ValueCountFrequency (%)
0 1709
34.8%
1 837
17.1%
2 84
 
1.7%
3 21
 
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 21
 
0.4%
2 84
 
1.7%
1 837
17.1%
0 1709
34.8%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)0.5%
Missing2099
Missing (%)42.8%
Infinite0
Infinite (%)0.0%
Mean1.257387
Minimum0
Maximum12
Zeros1001
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:51.131689image/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 deviation1.4062474
Coefficient of variation (CV)1.1183887
Kurtosis6.0013464
Mean1.257387
Median Absolute Deviation (MAD)1
Skewness1.846083
Sum3532
Variance1.9775318
MonotonicityNot monotonic
2024-04-18T07:52:51.233729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 1001
20.4%
1 870
17.7%
2 507
 
10.3%
3 251
 
5.1%
4 88
 
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
42.8%
ValueCountFrequency (%)
0 1001
20.4%
1 870
17.7%
2 507
10.3%
3 251
 
5.1%
4 88
 
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 88
 
1.8%
3 251
5.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.5%
Missing2726
Missing (%)55.5%
Infinite0
Infinite (%)0.0%
Mean1.4138405
Minimum0
Maximum10
Zeros587
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:51.339545image/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 deviation1.3581992
Coefficient of variation (CV)0.9606453
Kurtosis3.9880872
Mean1.4138405
Median Absolute Deviation (MAD)1
Skewness1.520181
Sum3085
Variance1.8447052
MonotonicityNot monotonic
2024-04-18T07:52:51.446892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 753
 
15.3%
0 587
 
12.0%
2 475
 
9.7%
3 214
 
4.4%
4 79
 
1.6%
5 46
 
0.9%
6 15
 
0.3%
7 7
 
0.1%
10 3
 
0.1%
8 2
 
< 0.1%
(Missing) 2726
55.5%
ValueCountFrequency (%)
0 587
12.0%
1 753
15.3%
2 475
9.7%
3 214
 
4.4%
4 79
 
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 79
 
1.6%
3 214
 
4.4%
2 475
9.7%
1 753
15.3%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
3062 
0
1521 
1
312 
2
 
12
22
 
1

Length

Max length4
Median length4
Mean length2.8718419
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3062
62.4%
0 1521
31.0%
1 312
 
6.4%
2 12
 
0.2%
22 1
 
< 0.1%

Length

2024-04-18T07:52:51.569146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:51.711022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3062
62.4%
0 1521
31.0%
1 312
 
6.4%
2 12
 
0.2%
22 1
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
3714 
0
925 
1
 
263
2
 
5
4
 
1

Length

Max length4
Median length4
Mean length3.2701711
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3714
75.7%
0 925
 
18.8%
1 263
 
5.4%
2 5
 
0.1%
4 1
 
< 0.1%

Length

2024-04-18T07:52:51.842854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:51.946043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3714
75.7%
0 925
 
18.8%
1 263
 
5.4%
2 5
 
0.1%
4 1
 
< 0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
2703 
0
2205 

Length

Max length4
Median length4
Mean length2.6522005
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2703
55.1%
0 2205
44.9%

Length

2024-04-18T07:52:52.045621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:52.137337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2703
55.1%
0 2205
44.9%

양실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
2702 
0
2205 
38
 
1

Length

Max length4
Median length4
Mean length2.651793
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2702
55.1%
0 2205
44.9%
38 1
 
< 0.1%

Length

2024-04-18T07:52:52.248401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:52.357963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2702
55.1%
0 2205
44.9%
38 1
 
< 0.1%

욕실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
2702 
0
2205 
2
 
1

Length

Max length4
Median length4
Mean length2.6515892
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2702
55.1%
0 2205
44.9%
2 1
 
< 0.1%

Length

2024-04-18T07:52:52.460458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:52.553236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2702
55.1%
0 2205
44.9%
2 1
 
< 0.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing100
Missing (%)2.0%
Memory size9.7 KiB
False
4808 
(Missing)
 
100
ValueCountFrequency (%)
False 4808
98.0%
(Missing) 100
 
2.0%
2024-04-18T07:52:52.627884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.4%
Missing608
Missing (%)12.4%
Infinite0
Infinite (%)0.0%
Mean3.1302326
Minimum0
Maximum24
Zeros338
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-18T07:52:52.734275image/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 deviation2.1289588
Coefficient of variation (CV)0.680128
Kurtosis3.3795842
Mean3.1302326
Median Absolute Deviation (MAD)1
Skewness1.2796214
Sum13460
Variance4.5324656
MonotonicityNot monotonic
2024-04-18T07:52:52.852543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 1339
27.3%
3 880
17.9%
4 582
11.9%
0 338
 
6.9%
1 336
 
6.8%
5 261
 
5.3%
6 178
 
3.6%
7 167
 
3.4%
8 111
 
2.3%
9 66
 
1.3%
Other values (6) 42
 
0.9%
(Missing) 608
12.4%
ValueCountFrequency (%)
0 338
 
6.9%
1 336
 
6.8%
2 1339
27.3%
3 880
17.9%
4 582
11.9%
5 261
 
5.3%
6 178
 
3.6%
7 167
 
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%
7 167
3.4%
6 178
3.6%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing4907
Missing (%)> 99.9%
Memory size38.5 KiB
2024-04-18T07:52:52.971724image/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%
2024-04-18T07:52:53.199001image/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 size38.5 KiB
<NA>
4906 
20050414
 
1
20050520
 
1

Length

Max length8
Median length4
Mean length4.00163
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> 4906
> 99.9%
20050414 1
 
< 0.1%
20050520 1
 
< 0.1%

Length

2024-04-18T07:52:53.330757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:53.427424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4906
> 99.9%
20050414 1
 
< 0.1%
20050520 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
4906 
20050414
 
1
20060425
 
1

Length

Max length8
Median length4
Mean length4.00163
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> 4906
> 99.9%
20050414 1
 
< 0.1%
20060425 1
 
< 0.1%

Length

2024-04-18T07:52:53.524556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:53.626298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4906
> 99.9%
20050414 1
 
< 0.1%
20060425 1
 
< 0.1%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
3944 
임대
936 
자가
 
28

Length

Max length4
Median length4
Mean length3.607172
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> 3944
80.4%
임대 936
 
19.1%
자가 28
 
0.6%

Length

2024-04-18T07:52:53.731382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:53.851163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3944
80.4%
임대 936
 
19.1%
자가 28
 
0.6%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
3361 
0
1547 

Length

Max length4
Median length4
Mean length3.054401
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3361
68.5%
0 1547
31.5%

Length

2024-04-18T07:52:53.951723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:54.051913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3361
68.5%
0 1547
31.5%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
4554 
0
 
338
1
 
16

Length

Max length4
Median length4
Mean length3.7836186
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4554
92.8%
0 338
 
6.9%
1 16
 
0.3%

Length

2024-04-18T07:52:54.150095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:54.240850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4554
92.8%
0 338
 
6.9%
1 16
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
4543 
0
 
332
1
 
32
2
 
1

Length

Max length4
Median length4
Mean length3.7768949
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4543
92.6%
0 332
 
6.8%
1 32
 
0.7%
2 1
 
< 0.1%

Length

2024-04-18T07:52:54.339074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:54.429143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4543
92.6%
0 332
 
6.8%
1 32
 
0.7%
2 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
3543 
0
1365 

Length

Max length4
Median length4
Mean length3.1656479
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3543
72.2%
0 1365
 
27.8%

Length

2024-04-18T07:52:54.525920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:54.616540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3543
72.2%
0 1365
 
27.8%

침대수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
3561 
0
1339 
2
 
4
3
 
2
1
 
1

Length

Max length4
Median length4
Mean length3.1766504
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3561
72.6%
0 1339
 
27.3%
2 4
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-18T07:52:54.714933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:52:54.821032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3561
72.6%
0 1339
 
27.3%
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
4908 
ValueCountFrequency (%)
False 4908
100.0%
2024-04-18T07:52:54.903557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4908
Missing (%)100.0%
Memory size43.3 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>
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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
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49034904이용업05_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>
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