Overview

Dataset statistics

Number of variables3
Number of observations370
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.2 KiB
Average record size in memory25.4 B

Variable types

Numeric1
Text2

Dataset

Description성주관내 대기배출시설 인허가 현황에 대한 데이터로 사업장의 상호명, 사업장 주소에 대한 공공데이터를 제공합니다.
Author경상북도 성주군
URLhttps://www.data.go.kr/data/15124602/fileData.do

Alerts

순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:29:23.572887
Analysis finished2023-12-12 01:29:24.090011
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct370
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean185.5
Minimum1
Maximum370
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T10:29:24.177056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.45
Q193.25
median185.5
Q3277.75
95-th percentile351.55
Maximum370
Range369
Interquartile range (IQR)184.5

Descriptive statistics

Standard deviation106.95404
Coefficient of variation (CV)0.57657164
Kurtosis-1.2
Mean185.5
Median Absolute Deviation (MAD)92.5
Skewness0
Sum68635
Variance11439.167
MonotonicityStrictly increasing
2023-12-12T10:29:24.368655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
245 1
 
0.3%
254 1
 
0.3%
253 1
 
0.3%
252 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
247 1
 
0.3%
Other values (360) 360
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
370 1
0.3%
369 1
0.3%
368 1
0.3%
367 1
0.3%
366 1
0.3%
365 1
0.3%
364 1
0.3%
363 1
0.3%
362 1
0.3%
361 1
0.3%
Distinct367
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T10:29:24.742422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length5.9054054
Min length2

Characters and Unicode

Total characters2185
Distinct characters288
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique364 ?
Unique (%)98.4%

Sample

1st row한국환경공단(성주폐비닐재활용시설)
2nd row㈜햇토비
3rd row㈜선진
4th row대가산업㈜
5th row㈜지엠앤에스
ValueCountFrequency (%)
성주지점 8
 
2.0%
주식회사 6
 
1.5%
농업회사법인 3
 
0.7%
2공장 3
 
0.7%
와이씨켐㈜ 3
 
0.7%
제3공장 3
 
0.7%
성주공장 3
 
0.7%
㈜디에스 2
 
0.5%
㈜거산알루미늄 2
 
0.5%
㈜삼화산업 2
 
0.5%
Other values (366) 375
91.5%
2023-12-12T10:29:25.282771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
198
 
9.1%
107
 
4.9%
90
 
4.1%
72
 
3.3%
59
 
2.7%
52
 
2.4%
47
 
2.2%
42
 
1.9%
38
 
1.7%
35
 
1.6%
Other values (278) 1445
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1857
85.0%
Other Symbol 198
 
9.1%
Space Separator 42
 
1.9%
Uppercase Letter 33
 
1.5%
Decimal Number 21
 
1.0%
Close Punctuation 15
 
0.7%
Open Punctuation 15
 
0.7%
Other Punctuation 3
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
107
 
5.8%
90
 
4.8%
72
 
3.9%
59
 
3.2%
52
 
2.8%
47
 
2.5%
38
 
2.0%
35
 
1.9%
34
 
1.8%
31
 
1.7%
Other values (255) 1292
69.6%
Uppercase Letter
ValueCountFrequency (%)
H 6
18.2%
C 4
12.1%
S 4
12.1%
T 4
12.1%
P 4
12.1%
M 3
9.1%
K 2
 
6.1%
E 1
 
3.0%
G 1
 
3.0%
A 1
 
3.0%
Other values (3) 3
9.1%
Decimal Number
ValueCountFrequency (%)
2 10
47.6%
3 7
33.3%
1 3
 
14.3%
4 1
 
4.8%
Other Symbol
ValueCountFrequency (%)
198
100.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2055
94.1%
Common 97
 
4.4%
Latin 33
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
198
 
9.6%
107
 
5.2%
90
 
4.4%
72
 
3.5%
59
 
2.9%
52
 
2.5%
47
 
2.3%
38
 
1.8%
35
 
1.7%
34
 
1.7%
Other values (256) 1323
64.4%
Latin
ValueCountFrequency (%)
H 6
18.2%
C 4
12.1%
S 4
12.1%
T 4
12.1%
P 4
12.1%
M 3
9.1%
K 2
 
6.1%
E 1
 
3.0%
G 1
 
3.0%
A 1
 
3.0%
Other values (3) 3
9.1%
Common
ValueCountFrequency (%)
42
43.3%
) 15
 
15.5%
( 15
 
15.5%
2 10
 
10.3%
3 7
 
7.2%
1 3
 
3.1%
& 3
 
3.1%
- 1
 
1.0%
4 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1857
85.0%
None 198
 
9.1%
ASCII 130
 
5.9%

Most frequent character per block

None
ValueCountFrequency (%)
198
100.0%
Hangul
ValueCountFrequency (%)
107
 
5.8%
90
 
4.8%
72
 
3.9%
59
 
3.2%
52
 
2.8%
47
 
2.5%
38
 
2.0%
35
 
1.9%
34
 
1.8%
31
 
1.7%
Other values (255) 1292
69.6%
ASCII
ValueCountFrequency (%)
42
32.3%
) 15
 
11.5%
( 15
 
11.5%
2 10
 
7.7%
3 7
 
5.4%
H 6
 
4.6%
C 4
 
3.1%
S 4
 
3.1%
T 4
 
3.1%
P 4
 
3.1%
Other values (12) 19
14.6%

주소
Text

Distinct361
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T10:29:25.666316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length13.445946
Min length10

Characters and Unicode

Total characters4975
Distinct characters99
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique352 ?
Unique (%)95.1%

Sample

1st row성주군 가천면 가천로 110-9
2nd row금수면 금강로 327
3rd row대가면 대금로 118
4th row대가면 용흥3길 21-41
5th row대가면 참별로 2152
ValueCountFrequency (%)
선남면 152
 
13.5%
성주읍 59
 
5.2%
월항면 58
 
5.2%
용암면 51
 
4.5%
선노로 31
 
2.8%
명관로 27
 
2.4%
초전면 25
 
2.2%
성주로 15
 
1.3%
주천로 13
 
1.2%
나선로 11
 
1.0%
Other values (445) 683
60.7%
2023-12-12T10:29:26.285645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
762
 
15.3%
309
 
6.2%
1 283
 
5.7%
2 217
 
4.4%
210
 
4.2%
- 196
 
3.9%
195
 
3.9%
3 194
 
3.9%
154
 
3.1%
4 153
 
3.1%
Other values (89) 2302
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2566
51.6%
Decimal Number 1441
29.0%
Space Separator 762
 
15.3%
Dash Punctuation 196
 
3.9%
Other Punctuation 8
 
0.2%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
309
 
12.0%
210
 
8.2%
195
 
7.6%
154
 
6.0%
138
 
5.4%
137
 
5.3%
129
 
5.0%
98
 
3.8%
96
 
3.7%
85
 
3.3%
Other values (74) 1015
39.6%
Decimal Number
ValueCountFrequency (%)
1 283
19.6%
2 217
15.1%
3 194
13.5%
4 153
10.6%
5 120
8.3%
7 103
 
7.1%
9 97
 
6.7%
6 97
 
6.7%
8 90
 
6.2%
0 87
 
6.0%
Space Separator
ValueCountFrequency (%)
762
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 196
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2566
51.6%
Common 2409
48.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
309
 
12.0%
210
 
8.2%
195
 
7.6%
154
 
6.0%
138
 
5.4%
137
 
5.3%
129
 
5.0%
98
 
3.8%
96
 
3.7%
85
 
3.3%
Other values (74) 1015
39.6%
Common
ValueCountFrequency (%)
762
31.6%
1 283
 
11.7%
2 217
 
9.0%
- 196
 
8.1%
3 194
 
8.1%
4 153
 
6.4%
5 120
 
5.0%
7 103
 
4.3%
9 97
 
4.0%
6 97
 
4.0%
Other values (5) 187
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2566
51.6%
ASCII 2409
48.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
762
31.6%
1 283
 
11.7%
2 217
 
9.0%
- 196
 
8.1%
3 194
 
8.1%
4 153
 
6.4%
5 120
 
5.0%
7 103
 
4.3%
9 97
 
4.0%
6 97
 
4.0%
Other values (5) 187
 
7.8%
Hangul
ValueCountFrequency (%)
309
 
12.0%
210
 
8.2%
195
 
7.6%
154
 
6.0%
138
 
5.4%
137
 
5.3%
129
 
5.0%
98
 
3.8%
96
 
3.7%
85
 
3.3%
Other values (74) 1015
39.6%

Interactions

2023-12-12T10:29:23.793973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T10:29:23.952550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:29:24.057431image/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

순번상호명주소
01한국환경공단(성주폐비닐재활용시설)성주군 가천면 가천로 110-9
12㈜햇토비금수면 금강로 327
23㈜선진대가면 대금로 118
34대가산업㈜대가면 용흥3길 21-41
45㈜지엠앤에스대가면 참별로 2152
56주식회사 대일프린텍대가면 용흥3길 21-31
67㈜디에이치원 성주지점벽진면 문덕로 112
78성원산업벽진면 문덕로 114
89㈜대한실업 성주지점벽진면 문덕로 112
910태산산업벽진면 문덕로 58-6
순번상호명주소
360361㈜엠에스인더스트리선남면 본성로 490-46
361362㈜디피시스템선남면 관용로 453-36
362363㈜에스에이치환경산업선남면 선노로 545-39
363364와이에스티선남면 도성2길 198-24
364365미수산업선남면 본성로 490-52
365366㈜하늘담은통나무선남면 명포1길 48
366367신흥산업성주읍 주천로 248-54
367368지에스피㈜월항면 월항농공단지1길 42-15
368369㈜신흥코아텍성주읍 성주산업단지로2길 120-3
369370㈜부강테크선남면 명관로 337-63 주1동