Overview

Dataset statistics

Number of variables5
Number of observations174
Missing cells2
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory41.8 B

Variable types

Numeric1
Text2
Categorical1
DateTime1

Dataset

Description전라남도 광양시의 기타수질오염원설치신고현황에 대한 데이터를 전국민들에게 무료로 제공합니다. (업소명, 소재지, 시설구분등의 데이터)
Author전라남도 광양시
URLhttps://www.data.go.kr/data/15035260/fileData.do

Alerts

데이터기준일 has constant value ""Constant
지번소재지 has 2 (1.1%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:10:33.352320
Analysis finished2024-04-06 08:10:34.351602
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct174
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.5
Minimum1
Maximum174
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-06T17:10:34.526013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.65
Q144.25
median87.5
Q3130.75
95-th percentile165.35
Maximum174
Range173
Interquartile range (IQR)86.5

Descriptive statistics

Standard deviation50.373604
Coefficient of variation (CV)0.57569833
Kurtosis-1.2
Mean87.5
Median Absolute Deviation (MAD)43.5
Skewness0
Sum15225
Variance2537.5
MonotonicityStrictly increasing
2024-04-06T17:10:34.823632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
121 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
116 1
 
0.6%
117 1
 
0.6%
118 1
 
0.6%
119 1
 
0.6%
120 1
 
0.6%
Other values (164) 164
94.3%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
174 1
0.6%
173 1
0.6%
172 1
0.6%
171 1
0.6%
170 1
0.6%
169 1
0.6%
168 1
0.6%
167 1
0.6%
166 1
0.6%
165 1
0.6%

업소명
Text

Distinct173
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-06T17:10:35.314141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.2758621
Min length2

Characters and Unicode

Total characters1266
Distinct characters227
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

Unique172 ?
Unique (%)98.9%

Sample

1st row동안자동차공업사
2nd row(유)메디컬자동차공업사
3rd row섬진강내수면영농조합법인
4th row광양폐차장
5th row대신자동차정비공업사
ValueCountFrequency (%)
주식회사 3
 
1.5%
안경원 3
 
1.5%
주)대원기업 2
 
1.0%
광양마동점 2
 
1.0%
안경나라 2
 
1.0%
광양중동점 2
 
1.0%
광양읍점 2
 
1.0%
안경매니져 2
 
1.0%
봄스튜디오 1
 
0.5%
한국기계검사소이엔씨(주 1
 
0.5%
Other values (180) 180
90.0%
2024-04-06T17:10:36.234068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 46
 
3.6%
원 45
 
3.6%
광 40
 
3.2%
사 36
 
2.8%
업 36
 
2.8%
주 32
 
2.5%
동 31
 
2.4%
안 31
 
2.4%
( 31
 
2.4%
) 31
 
2.4%
Other values (217) 907
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1153
91.1%
Open Punctuation 31
 
2.4%
Close Punctuation 31
 
2.4%
Space Separator 26
 
2.1%
Other Symbol 8
 
0.6%
Decimal Number 7
 
0.6%
Uppercase Letter 5
 
0.4%
Other Punctuation 4
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 46
 
4.0%
원 45
 
3.9%
광 40
 
3.5%
사 36
 
3.1%
업 36
 
3.1%
주 32
 
2.8%
동 31
 
2.7%
안 31
 
2.7%
경 29
 
2.5%
의 28
 
2.4%
Other values (202) 799
69.3%
Uppercase Letter
ValueCountFrequency (%)
G 2
40.0%
K 1
20.0%
L 1
20.0%
F 1
20.0%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
2 2
28.6%
0 2
28.6%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
, 1
25.0%
& 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1161
91.7%
Common 100
 
7.9%
Latin 5
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 46
 
4.0%
원 45
 
3.9%
광 40
 
3.4%
사 36
 
3.1%
업 36
 
3.1%
주 32
 
2.8%
동 31
 
2.7%
안 31
 
2.7%
경 29
 
2.5%
의 28
 
2.4%
Other values (203) 807
69.5%
Common
ValueCountFrequency (%)
( 31
31.0%
) 31
31.0%
26
26.0%
1 3
 
3.0%
. 2
 
2.0%
2 2
 
2.0%
0 2
 
2.0%
, 1
 
1.0%
& 1
 
1.0%
- 1
 
1.0%
Latin
ValueCountFrequency (%)
G 2
40.0%
K 1
20.0%
L 1
20.0%
F 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1153
91.1%
ASCII 105
 
8.3%
None 8
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 46
 
4.0%
원 45
 
3.9%
광 40
 
3.5%
사 36
 
3.1%
업 36
 
3.1%
주 32
 
2.8%
동 31
 
2.7%
안 31
 
2.7%
경 29
 
2.5%
의 28
 
2.4%
Other values (202) 799
69.3%
ASCII
ValueCountFrequency (%)
( 31
29.5%
) 31
29.5%
26
24.8%
1 3
 
2.9%
. 2
 
1.9%
G 2
 
1.9%
2 2
 
1.9%
0 2
 
1.9%
K 1
 
1.0%
, 1
 
1.0%
Other values (4) 4
 
3.8%
None
ValueCountFrequency (%)
㈜ 8
100.0%

지번소재지
Text

MISSING 

Distinct165
Distinct (%)95.9%
Missing2
Missing (%)1.1%
Memory size1.5 KiB
2024-04-06T17:10:36.789058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length22.174419
Min length17

Characters and Unicode

Total characters3814
Distinct characters115
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique158 ?
Unique (%)91.9%

Sample

1st row전라남도 광양시 옥곡면 신금리 1507-85
2nd row전라남도 광양시 광양읍 덕례리 1464
3rd row전라남도 광양시 광양읍 목성리 506-3
4th row전라남도 광양시 광양읍 사곡리 1125-4
5th row전라남도 광양시 옥곡면 신금리 1435-3
ValueCountFrequency (%)
전라남도 172
21.2%
광양시 172
21.2%
광양읍 61
 
7.5%
중동 29
 
3.6%
태인동 21
 
2.6%
광영동 17
 
2.1%
신금리 16
 
2.0%
옥곡면 16
 
2.0%
덕례리 12
 
1.5%
목성리 10
 
1.2%
Other values (211) 284
35.1%
2024-04-06T17:10:37.619132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
813
21.3%
광 254
 
6.7%
양 237
 
6.2%
1 202
 
5.3%
남 178
 
4.7%
도 173
 
4.5%
시 173
 
4.5%
전 172
 
4.5%
라 172
 
4.5%
- 142
 
3.7%
Other values (105) 1298
34.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2057
53.9%
Space Separator 813
 
21.3%
Decimal Number 789
 
20.7%
Dash Punctuation 142
 
3.7%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Other Punctuation 3
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 254
12.3%
양 237
11.5%
남 178
 
8.7%
도 173
 
8.4%
시 173
 
8.4%
전 172
 
8.4%
라 172
 
8.4%
동 91
 
4.4%
리 87
 
4.2%
읍 67
 
3.3%
Other values (88) 453
22.0%
Decimal Number
ValueCountFrequency (%)
1 202
25.6%
6 82
10.4%
5 80
 
10.1%
3 77
 
9.8%
2 71
 
9.0%
7 69
 
8.7%
8 54
 
6.8%
9 54
 
6.8%
4 52
 
6.6%
0 48
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
F 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
813
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2057
53.9%
Common 1755
46.0%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 254
12.3%
양 237
11.5%
남 178
 
8.7%
도 173
 
8.4%
시 173
 
8.4%
전 172
 
8.4%
라 172
 
8.4%
동 91
 
4.4%
리 87
 
4.2%
읍 67
 
3.3%
Other values (88) 453
22.0%
Common
ValueCountFrequency (%)
813
46.3%
1 202
 
11.5%
- 142
 
8.1%
6 82
 
4.7%
5 80
 
4.6%
3 77
 
4.4%
2 71
 
4.0%
7 69
 
3.9%
8 54
 
3.1%
9 54
 
3.1%
Other values (5) 111
 
6.3%
Latin
ValueCountFrequency (%)
F 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2057
53.9%
ASCII 1757
46.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
813
46.3%
1 202
 
11.5%
- 142
 
8.1%
6 82
 
4.7%
5 80
 
4.6%
3 77
 
4.4%
2 71
 
4.0%
7 69
 
3.9%
8 54
 
3.1%
9 54
 
3.1%
Other values (7) 113
 
6.4%
Hangul
ValueCountFrequency (%)
광 254
12.3%
양 237
11.5%
남 178
 
8.7%
도 173
 
8.4%
시 173
 
8.4%
전 172
 
8.4%
라 172
 
8.4%
동 91
 
4.4%
리 87
 
4.2%
읍 67
 
3.3%
Other values (88) 453
22.0%

특정시설구분
Categorical

Distinct12
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
운수장비정비
50 
사진처리시설
50 
안경원
29 
운수장비정비또는폐차장시설
20 
X-RAY 시설
6 
Other values (7)
19 

Length

Max length13
Median length6
Mean length6.4942529
Min length3

Unique

Unique3 ?
Unique (%)1.7%

Sample

1st row운수장비정비
2nd row운수장비정비
3rd row양만장,양어장
4th row폐차장시설
5th row운수장비정비

Common Values

ValueCountFrequency (%)
운수장비정비 50
28.7%
사진처리시설 50
28.7%
안경원 29
16.7%
운수장비정비또는폐차장시설 20
 
11.5%
X-RAY 시설 6
 
3.4%
수조식육상양식어업시설 6
 
3.4%
폐차장시설 4
 
2.3%
양만장,양어장 3
 
1.7%
농수산시설 3
 
1.7%
기타시설 1
 
0.6%
Other values (2) 2
 
1.1%

Length

2024-04-06T17:10:38.003940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
운수장비정비 50
27.8%
사진처리시설 50
27.8%
안경원 29
16.1%
운수장비정비또는폐차장시설 20
 
11.1%
x-ray 6
 
3.3%
시설 6
 
3.3%
수조식육상양식어업시설 6
 
3.3%
폐차장시설 4
 
2.2%
양만장,양어장 3
 
1.7%
농수산시설 3
 
1.7%
Other values (3) 3
 
1.7%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2024-03-25 00:00:00
Maximum2024-03-25 00:00:00
2024-04-06T17:10:38.201747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:38.458774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-06T17:10:33.805794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:10:38.591524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번특정시설구분
연번1.0000.448
특정시설구분0.4481.000
2024-04-06T17:10:38.861614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번특정시설구분
연번1.0000.207
특정시설구분0.2071.000

Missing values

2024-04-06T17:10:34.044064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:10:34.236684image/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

연번업소명지번소재지특정시설구분데이터기준일
01동안자동차공업사전라남도 광양시 옥곡면 신금리 1507-85운수장비정비2024-03-25
12(유)메디컬자동차공업사전라남도 광양시 광양읍 덕례리 1464운수장비정비2024-03-25
23섬진강내수면영농조합법인전라남도 광양시 광양읍 목성리 506-3양만장,양어장2024-03-25
34광양폐차장전라남도 광양시 광양읍 사곡리 1125-4폐차장시설2024-03-25
45대신자동차정비공업사전라남도 광양시 옥곡면 신금리 1435-3운수장비정비2024-03-25
56동양자원(주)광양사업소전라남도 광양시 광양읍 덕례리 1122-1폐차장시설2024-03-25
67대명공업사전라남도 광양시 광양읍 용강리 37-17운수장비정비2024-03-25
78김외과의원전라남도 광양시 중동 1677-5사진처리시설2024-03-25
89천지자동차공업사전라남도 광양시 광양읍 사곡리 991-1 991-25운수장비정비또는폐차장시설2024-03-25
910(주)제철자동차정비전라남도 광양시 옥곡면 신금리 892운수장비정비또는폐차장시설2024-03-25
연번업소명지번소재지특정시설구분데이터기준일
164165민스튜디오전라남도 광양시 광영동 783-7사진처리시설2024-03-25
165166이안경전라남도 광양시 중동 1638-11안경원2024-03-25
166167고려의원전라남도 광양시 광양읍 목성리 938-1사진처리시설2024-03-25
167168우리들연합의원<NA>X-RAY 시설2024-03-25
168169의료법인 백운의료재단전라남도 광양시 광양읍 칠성리 493-1X-RAY 시설2024-03-25
169170K비젼안경전라남도 광양시 광양읍 구산리 831-5안경원2024-03-25
170171진상농업협동조합전라남도 광양시 진상면 섬거리 457농수산시설2024-03-25
171172강진종합정비전라남도 광양시 성황동 73-5운수장비정비또는폐차장시설2024-03-25
172173대하동부공업㈜전라남도 광양시 옥곡면 신금리 1581-1운수장비정비또는폐차장시설2024-03-25
173174가야㈜전라남도 광양시 옥곡면 신금리 384-2 외 3필지운수장비정비2024-03-25