Overview

Dataset statistics

Number of variables3
Number of observations47
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory28.8 B

Variable types

Numeric2
Text1

Dataset

Description철원군 음식물류폐기물이 다량으로 발생되는 배출사업장에 대한 데이터로 사업장명, 영업면적 등의 항목을 제공합니다
Author강원도 철원군
URLhttps://www.data.go.kr/data/15094445/fileData.do

Alerts

연번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:19:28.729649
Analysis finished2023-12-12 05:19:29.379084
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24
Minimum1
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T14:19:29.485608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.3
Q112.5
median24
Q335.5
95-th percentile44.7
Maximum47
Range46
Interquartile range (IQR)23

Descriptive statistics

Standard deviation13.711309
Coefficient of variation (CV)0.57130455
Kurtosis-1.2
Mean24
Median Absolute Deviation (MAD)12
Skewness0
Sum1128
Variance188
MonotonicityStrictly increasing
2023-12-12T14:19:29.678836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
1 1
 
2.1%
2 1
 
2.1%
27 1
 
2.1%
28 1
 
2.1%
29 1
 
2.1%
30 1
 
2.1%
31 1
 
2.1%
32 1
 
2.1%
33 1
 
2.1%
34 1
 
2.1%
Other values (37) 37
78.7%
ValueCountFrequency (%)
1 1
2.1%
2 1
2.1%
3 1
2.1%
4 1
2.1%
5 1
2.1%
6 1
2.1%
7 1
2.1%
8 1
2.1%
9 1
2.1%
10 1
2.1%
ValueCountFrequency (%)
47 1
2.1%
46 1
2.1%
45 1
2.1%
44 1
2.1%
43 1
2.1%
42 1
2.1%
41 1
2.1%
40 1
2.1%
39 1
2.1%
38 1
2.1%

업소명
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-12T14:19:29.913801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length6.3617021
Min length3

Characters and Unicode

Total characters299
Distinct characters132
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row신철원고등학교
2nd row철원중,고등학교
3rd row신철원초등학교
4th row동송초등학교
5th row철원초등학교
ValueCountFrequency (%)
귀뚜라미랜드 2
 
3.8%
신철원고등학교 1
 
1.9%
민통선한우촌 1
 
1.9%
경복궁 1
 
1.9%
동송뷔페 1
 
1.9%
동송농협채움홀 1
 
1.9%
골프점 1
 
1.9%
둠지능이버섯백숙 1
 
1.9%
금학f.c 1
 
1.9%
기린월드회관 1
 
1.9%
Other values (41) 41
78.8%
2023-12-12T14:19:30.314928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 17
 
5.7%
등 16
 
5.4%
교 16
 
5.4%
원 15
 
5.0%
초 11
 
3.7%
철 10
 
3.3%
고 8
 
2.7%
5
 
1.7%
우 5
 
1.7%
동 5
 
1.7%
Other values (122) 191
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 285
95.3%
Space Separator 5
 
1.7%
Other Punctuation 3
 
1.0%
Close Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%
Uppercase Letter 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 17
 
6.0%
등 16
 
5.6%
교 16
 
5.6%
원 15
 
5.3%
초 11
 
3.9%
철 10
 
3.5%
고 8
 
2.8%
우 5
 
1.8%
동 5
 
1.8%
송 4
 
1.4%
Other values (114) 178
62.5%
Other Punctuation
ValueCountFrequency (%)
. 1
33.3%
, 1
33.3%
& 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
F 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 285
95.3%
Common 12
 
4.0%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 17
 
6.0%
등 16
 
5.6%
교 16
 
5.6%
원 15
 
5.3%
초 11
 
3.9%
철 10
 
3.5%
고 8
 
2.8%
우 5
 
1.8%
동 5
 
1.8%
송 4
 
1.4%
Other values (114) 178
62.5%
Common
ValueCountFrequency (%)
5
41.7%
) 2
 
16.7%
( 2
 
16.7%
. 1
 
8.3%
, 1
 
8.3%
& 1
 
8.3%
Latin
ValueCountFrequency (%)
F 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 285
95.3%
ASCII 14
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 17
 
6.0%
등 16
 
5.6%
교 16
 
5.6%
원 15
 
5.3%
초 11
 
3.9%
철 10
 
3.5%
고 8
 
2.8%
우 5
 
1.8%
동 5
 
1.8%
송 4
 
1.4%
Other values (114) 178
62.5%
ASCII
ValueCountFrequency (%)
5
35.7%
) 2
 
14.3%
( 2
 
14.3%
. 1
 
7.1%
F 1
 
7.1%
C 1
 
7.1%
, 1
 
7.1%
& 1
 
7.1%

영업장면적
Real number (ℝ)

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean328.90149
Minimum8.4
Maximum870.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T14:19:30.459639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.4
5-th percentile87.39
Q1209.59
median283.34
Q3453.04
95-th percentile650.168
Maximum870.45
Range862.05
Interquartile range (IQR)243.45

Descriptive statistics

Standard deviation182.79133
Coefficient of variation (CV)0.55576316
Kurtosis0.40515183
Mean328.90149
Median Absolute Deviation (MAD)115.84
Skewness0.60493046
Sum15458.37
Variance33412.671
MonotonicityNot monotonic
2023-12-12T14:19:30.610080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
453.04 2
 
4.3%
870.45 1
 
2.1%
283.34 1
 
2.1%
463.8 1
 
2.1%
435.56 1
 
2.1%
450.32 1
 
2.1%
399.18 1
 
2.1%
394.39 1
 
2.1%
331.27 1
 
2.1%
320.18 1
 
2.1%
Other values (36) 36
76.6%
ValueCountFrequency (%)
8.4 1
2.1%
15.04 1
2.1%
85.5 1
2.1%
91.8 1
2.1%
98.5 1
2.1%
108.82 1
2.1%
133.6 1
2.1%
180.18 1
2.1%
181.8 1
2.1%
200.0 1
2.1%
ValueCountFrequency (%)
870.45 1
2.1%
668.86 1
2.1%
665.0 1
2.1%
615.56 1
2.1%
530.0 1
2.1%
514.19 1
2.1%
513.13 1
2.1%
508.21 1
2.1%
506.1 1
2.1%
468.76 1
2.1%

Interactions

2023-12-12T14:19:29.042583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:19:28.858967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:19:29.126446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:19:28.953971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:19:30.693032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명영업장면적
연번1.0001.0000.808
업소명1.0001.0001.000
영업장면적0.8081.0001.000
2023-12-12T14:19:30.794057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번영업장면적
연번1.000-0.245
영업장면적-0.2451.000

Missing values

2023-12-12T14:19:29.248803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:19:29.333301image/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

연번업소명영업장면적
01신철원고등학교870.45
12철원중,고등학교668.86
23신철원초등학교665.0
34동송초등학교530.0
45철원초등학교513.13
56철원여자중고등학교506.1
67김화고등학교453.04
78와수초등학교439.5
89오덕초등학교261.66
910청양초등학교211.23
연번업소명영업장면적
3738그린회관280.22
3839본가왕뼈감자탕 동송점270.0
3940철원오대갈비268.99
4041문평가든257.28
4142마늘오리231.0
4243본때감자탕222.81
4344홍대면옥221.4
4445청춘식당219.21
4546한우연215.28
4647맛고을206.88