Overview

Dataset statistics

Number of variables4
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory37.0 B

Variable types

Categorical1
Numeric2
Text1

Dataset

Description서울특별시 강동구 내의 청소년 유해업소 현황 정보를 제공합니다. 청소년 유해업소의 업종코드, 업종명, 건수 데이터가 있습니다.
URLhttps://www.data.go.kr/data/15075913/fileData.do

Alerts

처리일자 has constant value ""Constant
청소년유해업소업종코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:45:24.408224
Analysis finished2023-12-12 12:45:25.188192
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

처리일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-08-24
44 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-24
2nd row2023-08-24
3rd row2023-08-24
4th row2023-08-24
5th row2023-08-24

Common Values

ValueCountFrequency (%)
2023-08-24 44
100.0%

Length

2023-12-12T21:45:25.272796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:45:25.389255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-24 44
100.0%

청소년유해업소업종코드
Real number (ℝ)

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11666.091
Minimum10101
Maximum24205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T21:45:25.523213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10103.15
Q110112.75
median10205
Q310409.25
95-th percentile20106.7
Maximum24205
Range14104
Interquartile range (IQR)296.5

Descriptive statistics

Standard deviation3724.7659
Coefficient of variation (CV)0.3192814
Kurtosis3.8257481
Mean11666.091
Median Absolute Deviation (MAD)98.5
Skewness2.310443
Sum513308
Variance13873881
MonotonicityStrictly increasing
2023-12-12T21:45:25.683130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
10101 1
 
2.3%
10207 1
 
2.3%
10210 1
 
2.3%
10299 1
 
2.3%
10301 1
 
2.3%
10401 1
 
2.3%
10402 1
 
2.3%
10403 1
 
2.3%
10408 1
 
2.3%
10409 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
10101 1
2.3%
10102 1
2.3%
10103 1
2.3%
10104 1
2.3%
10105 1
2.3%
10106 1
2.3%
10107 1
2.3%
10108 1
2.3%
10110 1
2.3%
10111 1
2.3%
ValueCountFrequency (%)
24205 1
2.3%
20301 1
2.3%
20107 1
2.3%
20105 1
2.3%
20102 1
2.3%
20101 1
2.3%
10499 1
2.3%
10413 1
2.3%
10412 1
2.3%
10411 1
2.3%

청소년유해업소업종명
Text

Distinct40
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-12T21:45:25.939059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length6.5
Mean length4.0909091
Min length2

Characters and Unicode

Total characters180
Distinct characters98
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)84.1%

Sample

1st row한식
2nd row중국식
3rd row경양식
4th row일식
5th row분식
ValueCountFrequency (%)
기타 3
 
6.8%
전통찻집 2
 
4.5%
패스트푸드 2
 
4.5%
여관업 1
 
2.3%
일반호텔 1
 
2.3%
일반이용업 1
 
2.3%
여인숙업 1
 
2.3%
한식 1
 
2.3%
철도역구내 1
 
2.3%
룸살롱 1
 
2.3%
Other values (30) 30
68.2%
2023-12-12T21:45:26.350244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 7
 
3.9%
) 6
 
3.3%
( 6
 
3.3%
점 5
 
2.8%
호 5
 
2.8%
업 4
 
2.2%
관 4
 
2.2%
일 4
 
2.2%
스 4
 
2.2%
트 4
 
2.2%
Other values (88) 131
72.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 168
93.3%
Close Punctuation 6
 
3.3%
Open Punctuation 6
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 7
 
4.2%
점 5
 
3.0%
호 5
 
3.0%
업 4
 
2.4%
관 4
 
2.4%
일 4
 
2.4%
스 4
 
2.4%
트 4
 
2.4%
이 4
 
2.4%
텔 4
 
2.4%
Other values (86) 123
73.2%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 168
93.3%
Common 12
 
6.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 7
 
4.2%
점 5
 
3.0%
호 5
 
3.0%
업 4
 
2.4%
관 4
 
2.4%
일 4
 
2.4%
스 4
 
2.4%
트 4
 
2.4%
이 4
 
2.4%
텔 4
 
2.4%
Other values (86) 123
73.2%
Common
ValueCountFrequency (%)
) 6
50.0%
( 6
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 168
93.3%
ASCII 12
 
6.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 7
 
4.2%
점 5
 
3.0%
호 5
 
3.0%
업 4
 
2.4%
관 4
 
2.4%
일 4
 
2.4%
스 4
 
2.4%
트 4
 
2.4%
이 4
 
2.4%
텔 4
 
2.4%
Other values (86) 123
73.2%
ASCII
ValueCountFrequency (%)
) 6
50.0%
( 6
50.0%

건수
Real number (ℝ)

Distinct31
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140.29545
Minimum1
Maximum1602
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T21:45:26.518687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median18
Q3104.75
95-th percentile830.7
Maximum1602
Range1601
Interquartile range (IQR)102.75

Descriptive statistics

Standard deviation316.47239
Coefficient of variation (CV)2.2557565
Kurtosis12.224967
Mean140.29545
Median Absolute Deviation (MAD)17
Skewness3.4162675
Sum6173
Variance100154.77
MonotonicityNot monotonic
2023-12-12T21:45:26.670506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 7
 
15.9%
2 5
 
11.4%
3 2
 
4.5%
18 2
 
4.5%
6 2
 
4.5%
489 1
 
2.3%
91 1
 
2.3%
125 1
 
2.3%
143 1
 
2.3%
30 1
 
2.3%
Other values (21) 21
47.7%
ValueCountFrequency (%)
1 7
15.9%
2 5
11.4%
3 2
 
4.5%
4 1
 
2.3%
5 1
 
2.3%
6 2
 
4.5%
14 1
 
2.3%
15 1
 
2.3%
17 1
 
2.3%
18 2
 
4.5%
ValueCountFrequency (%)
1602 1
2.3%
1111 1
2.3%
891 1
2.3%
489 1
2.3%
276 1
2.3%
254 1
2.3%
249 1
2.3%
199 1
2.3%
147 1
2.3%
143 1
2.3%

Interactions

2023-12-12T21:45:24.810027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:24.532230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:24.931442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:24.676079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:45:26.784129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
청소년유해업소업종코드청소년유해업소업종명건수
청소년유해업소업종코드1.0001.0000.000
청소년유해업소업종명1.0001.0000.000
건수0.0000.0001.000
2023-12-12T21:45:26.892010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
청소년유해업소업종코드건수
청소년유해업소업종코드1.000-0.168
건수-0.1681.000

Missing values

2023-12-12T21:45:25.059753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:45:25.150993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

처리일자청소년유해업소업종코드청소년유해업소업종명건수
02023-08-2410101한식1602
12023-08-2410102중국식147
22023-08-2410103경양식891
32023-08-2410104일식276
42023-08-2410105분식254
52023-08-2410106뷔페식6
62023-08-2410107정종39
72023-08-2410108전통찻집2
82023-08-2410110출장조리1
92023-08-2410111패스트푸드17
처리일자청소년유해업소업종코드청소년유해업소업종명건수
342023-08-2410411패스트푸드30
352023-08-2410412커피숍489
362023-08-2410413전통찻집1
372023-08-2410499기타249
382023-08-2420101관광호텔15
392023-08-2420102일반호텔1
402023-08-2420105여관업57
412023-08-2420107여인숙업14
422023-08-2420301일반이용업67
432023-08-2424205노래연습장업75