Overview

Dataset statistics

Number of variables10
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory85.7 B

Variable types

Categorical6
Text3
Numeric1

Dataset

Description전라남도 광양시의 자동우량경보시설 정보(지역, 시설명, 지점명, 설치장소, 설치연도 등)에 대한 데이터를 전 국민에게 무료로 제공
Author전라남도 광양시
URLhttps://www.data.go.kr/data/3079569/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
교체연도 has constant value ""Constant
데이터기준일 has constant value ""Constant
읍면동 is highly overall correlated with 종류High correlation
종류 is highly overall correlated with 읍면동High correlation
주소 has unique valuesUnique
시설명 has unique valuesUnique
지점명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:56:14.611392
Analysis finished2023-12-12 03:56:15.480184
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
전라남도
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 36
100.0%

Length

2023-12-12T12:56:15.605853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:56:15.771756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 36
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
광양시
36 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광양시 36
100.0%

Length

2023-12-12T12:56:15.938285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:56:16.134057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광양시 36
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size420.0 B
진상면
10 
봉강면
9 
옥룡면
8 
다압면
8 
중마동
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row중마동
2nd row봉강면
3rd row봉강면
4th row봉강면
5th row봉강면

Common Values

ValueCountFrequency (%)
진상면 10
27.8%
봉강면 9
25.0%
옥룡면 8
22.2%
다압면 8
22.2%
중마동 1
 
2.8%

Length

2023-12-12T12:56:16.319729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:56:16.459085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진상면 10
27.8%
봉강면 9
25.0%
옥룡면 8
22.2%
다압면 8
22.2%
중마동 1
 
2.8%

주소
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T12:56:16.686538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22.5
Mean length21.833333
Min length15

Characters and Unicode

Total characters786
Distinct characters44
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row전라남도 광양시 시청로 33
2nd row전라남도 광양시 봉강면 조령리 산 166-1
3rd row전라남도 광양시 봉강면 신룡리 산 69-1
4th row전라남도 광양시 봉강면 구서리 552-1
5th row전라남도 광양시 봉강면 신룡리 731
ValueCountFrequency (%)
전라남도 36
18.8%
광양시 36
18.8%
산 13
 
6.8%
진상면 10
 
5.2%
어치리 9
 
4.7%
봉강면 9
 
4.7%
옥룡면 8
 
4.2%
금천리 8
 
4.2%
다압면 8
 
4.2%
동곡리 7
 
3.6%
Other values (41) 48
25.0%
2023-12-12T12:56:17.529245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157
20.0%
시 37
 
4.7%
전 36
 
4.6%
남 36
 
4.6%
도 36
 
4.6%
광 36
 
4.6%
양 36
 
4.6%
라 36
 
4.6%
면 35
 
4.5%
리 35
 
4.5%
Other values (34) 306
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 478
60.8%
Space Separator 157
 
20.0%
Decimal Number 132
 
16.8%
Dash Punctuation 19
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 37
 
7.7%
전 36
 
7.5%
남 36
 
7.5%
도 36
 
7.5%
광 36
 
7.5%
양 36
 
7.5%
라 36
 
7.5%
면 35
 
7.3%
리 35
 
7.3%
산 14
 
2.9%
Other values (22) 141
29.5%
Decimal Number
ValueCountFrequency (%)
1 33
25.0%
2 23
17.4%
6 16
12.1%
7 12
 
9.1%
3 11
 
8.3%
9 9
 
6.8%
5 9
 
6.8%
4 9
 
6.8%
8 7
 
5.3%
0 3
 
2.3%
Space Separator
ValueCountFrequency (%)
157
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 478
60.8%
Common 308
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 37
 
7.7%
전 36
 
7.5%
남 36
 
7.5%
도 36
 
7.5%
광 36
 
7.5%
양 36
 
7.5%
라 36
 
7.5%
면 35
 
7.3%
리 35
 
7.3%
산 14
 
2.9%
Other values (22) 141
29.5%
Common
ValueCountFrequency (%)
157
51.0%
1 33
 
10.7%
2 23
 
7.5%
- 19
 
6.2%
6 16
 
5.2%
7 12
 
3.9%
3 11
 
3.6%
9 9
 
2.9%
5 9
 
2.9%
4 9
 
2.9%
Other values (2) 10
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 478
60.8%
ASCII 308
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
157
51.0%
1 33
 
10.7%
2 23
 
7.5%
- 19
 
6.2%
6 16
 
5.2%
7 12
 
3.9%
3 11
 
3.6%
9 9
 
2.9%
5 9
 
2.9%
4 9
 
2.9%
Other values (2) 10
 
3.2%
Hangul
ValueCountFrequency (%)
시 37
 
7.7%
전 36
 
7.5%
남 36
 
7.5%
도 36
 
7.5%
광 36
 
7.5%
양 36
 
7.5%
라 36
 
7.5%
면 35
 
7.3%
리 35
 
7.3%
산 14
 
2.9%
Other values (22) 141
29.5%

종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
경보국
27 
우량국
8 
감시국
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row감시국
2nd row우량국
3rd row우량국
4th row경보국
5th row경보국

Common Values

ValueCountFrequency (%)
경보국 27
75.0%
우량국 8
 
22.2%
감시국 1
 
2.8%

Length

2023-12-12T12:56:17.728846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:56:17.869861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경보국 27
75.0%
우량국 8
 
22.2%
감시국 1
 
2.8%

시설명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T12:56:18.174608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0555556
Min length5

Characters and Unicode

Total characters182
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row시청통합감시국
2nd row봉강1우량
3rd row봉강2우량
4th row봉강1경보
5th row봉강2경보
ValueCountFrequency (%)
시청통합감시국 1
 
2.8%
봉강1우량 1
 
2.8%
진상7경보 1
 
2.8%
진상1경보 1
 
2.8%
진상2경보 1
 
2.8%
진상3경보 1
 
2.8%
진상4경보 1
 
2.8%
진상5경보 1
 
2.8%
진상6경보 1
 
2.8%
진상8경보 1
 
2.8%
Other values (26) 26
72.2%
2023-12-12T12:56:18.830680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 27
14.8%
경 27
14.8%
상 10
 
5.5%
진 10
 
5.5%
봉 9
 
4.9%
강 9
 
4.9%
다 8
 
4.4%
룡 8
 
4.4%
옥 8
 
4.4%
2 8
 
4.4%
Other values (16) 58
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147
80.8%
Decimal Number 35
 
19.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 27
18.4%
경 27
18.4%
상 10
 
6.8%
진 10
 
6.8%
봉 9
 
6.1%
강 9
 
6.1%
다 8
 
5.4%
룡 8
 
5.4%
옥 8
 
5.4%
압 8
 
5.4%
Other values (8) 23
15.6%
Decimal Number
ValueCountFrequency (%)
2 8
22.9%
1 8
22.9%
6 4
11.4%
3 4
11.4%
4 4
11.4%
5 4
11.4%
7 2
 
5.7%
8 1
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147
80.8%
Common 35
 
19.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 27
18.4%
경 27
18.4%
상 10
 
6.8%
진 10
 
6.8%
봉 9
 
6.1%
강 9
 
6.1%
다 8
 
5.4%
룡 8
 
5.4%
옥 8
 
5.4%
압 8
 
5.4%
Other values (8) 23
15.6%
Common
ValueCountFrequency (%)
2 8
22.9%
1 8
22.9%
6 4
11.4%
3 4
11.4%
4 4
11.4%
5 4
11.4%
7 2
 
5.7%
8 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147
80.8%
ASCII 35
 
19.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 27
18.4%
경 27
18.4%
상 10
 
6.8%
진 10
 
6.8%
봉 9
 
6.1%
강 9
 
6.1%
다 8
 
5.4%
룡 8
 
5.4%
옥 8
 
5.4%
압 8
 
5.4%
Other values (8) 23
15.6%
ASCII
ValueCountFrequency (%)
2 8
22.9%
1 8
22.9%
6 4
11.4%
3 4
11.4%
4 4
11.4%
5 4
11.4%
7 2
 
5.7%
8 1
 
2.9%

지점명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T12:56:19.197795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.8611111
Min length4

Characters and Unicode

Total characters175
Distinct characters66
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

Unique36 ?
Unique (%)100.0%

Sample

1st row시청통합감시국
2nd row성불사우량
3rd row안치우량
4th row계룡경보
5th row신천경보
ValueCountFrequency (%)
시청통합감시국 1
 
2.8%
성불사우량 1
 
2.8%
천수암경보 1
 
2.8%
지계리경보 1
 
2.8%
외회경보 1
 
2.8%
내회교경보 1
 
2.8%
백학동경보국 1
 
2.8%
주차장경보국 1
 
2.8%
넷논골경보 1
 
2.8%
장수교경보 1
 
2.8%
Other values (26) 26
72.2%
2023-12-12T12:56:19.790301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 25
 
14.3%
경 25
 
14.3%
동 11
 
6.3%
우 8
 
4.6%
량 8
 
4.6%
사 5
 
2.9%
교 5
 
2.9%
장 5
 
2.9%
서 4
 
2.3%
국 3
 
1.7%
Other values (56) 76
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 175
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 25
 
14.3%
경 25
 
14.3%
동 11
 
6.3%
우 8
 
4.6%
량 8
 
4.6%
사 5
 
2.9%
교 5
 
2.9%
장 5
 
2.9%
서 4
 
2.3%
국 3
 
1.7%
Other values (56) 76
43.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 175
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 25
 
14.3%
경 25
 
14.3%
동 11
 
6.3%
우 8
 
4.6%
량 8
 
4.6%
사 5
 
2.9%
교 5
 
2.9%
장 5
 
2.9%
서 4
 
2.3%
국 3
 
1.7%
Other values (56) 76
43.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 175
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 25
 
14.3%
경 25
 
14.3%
동 11
 
6.3%
우 8
 
4.6%
량 8
 
4.6%
사 5
 
2.9%
교 5
 
2.9%
장 5
 
2.9%
서 4
 
2.3%
국 3
 
1.7%
Other values (56) 76
43.4%

설치연도
Real number (ℝ)

Distinct6
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2004.9167
Minimum2002
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:56:19.968404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2002
Q12002.75
median2004
Q32004
95-th percentile2012.75
Maximum2015
Range13
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation3.7368818
Coefficient of variation (CV)0.0018638589
Kurtosis1.6719377
Mean2004.9167
Median Absolute Deviation (MAD)1
Skewness1.6726483
Sum72177
Variance13.964286
MonotonicityNot monotonic
2023-12-12T12:56:20.157803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2004 15
41.7%
2002 9
25.0%
2003 5
 
13.9%
2010 3
 
8.3%
2015 2
 
5.6%
2012 2
 
5.6%
ValueCountFrequency (%)
2002 9
25.0%
2003 5
 
13.9%
2004 15
41.7%
2010 3
 
8.3%
2012 2
 
5.6%
2015 2
 
5.6%
ValueCountFrequency (%)
2015 2
 
5.6%
2012 2
 
5.6%
2010 3
 
8.3%
2004 15
41.7%
2003 5
 
13.9%
2002 9
25.0%

교체연도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2019
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 36
100.0%

Length

2023-12-12T12:56:20.359033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:56:20.483802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 36
100.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-11-13
36 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-13
2nd row2023-11-13
3rd row2023-11-13
4th row2023-11-13
5th row2023-11-13

Common Values

ValueCountFrequency (%)
2023-11-13 36
100.0%

Length

2023-12-12T12:56:20.602404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:56:20.751598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-13 36
100.0%

Interactions

2023-12-12T12:56:14.964402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:56:20.856154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동주소종류시설명지점명설치연도
읍면동1.0001.0000.6851.0001.0000.510
주소1.0001.0001.0001.0001.0001.000
종류0.6851.0001.0001.0001.0000.000
시설명1.0001.0001.0001.0001.0001.000
지점명1.0001.0001.0001.0001.0001.000
설치연도0.5101.0000.0001.0001.0001.000
2023-12-12T12:56:21.008333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류읍면동
종류1.0000.641
읍면동0.6411.000
2023-12-12T12:56:21.139755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도읍면동종류
설치연도1.0000.3860.000
읍면동0.3861.0000.641
종류0.0000.6411.000

Missing values

2023-12-12T12:56:15.127178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:56:15.385529image/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

시도시군구읍면동주소종류시설명지점명설치연도교체연도데이터기준일
0전라남도광양시중마동전라남도 광양시 시청로 33감시국시청통합감시국시청통합감시국200220192023-11-13
1전라남도광양시봉강면전라남도 광양시 봉강면 조령리 산 166-1우량국봉강1우량성불사우량200420192023-11-13
2전라남도광양시봉강면전라남도 광양시 봉강면 신룡리 산 69-1우량국봉강2우량안치우량200420192023-11-13
3전라남도광양시봉강면전라남도 광양시 봉강면 구서리 552-1경보국봉강1경보계룡경보200420192023-11-13
4전라남도광양시봉강면전라남도 광양시 봉강면 신룡리 731경보국봉강2경보신천경보200420192023-11-13
5전라남도광양시봉강면전라남도 광양시 봉강면 조령리 산 427-1경보국봉강3경보부암경보200420192023-11-13
6전라남도광양시봉강면전라남도 광양시 봉강면 조령리 산 200-1경보국봉강4경보꽃사슴농장경보200420192023-11-13
7전라남도광양시봉강면전라남도 광양시 봉강면 조령리 832경보국봉강5경보성불산장200420192023-11-13
8전라남도광양시봉강면전라남도 광양시 봉강면 조령리 166-1경보국봉강6경보간이중계소200420192023-11-13
9전라남도광양시봉강면전라남도 광양시 봉강면 조령리 산 169경보국봉강7경보성불사경보200420192023-11-13
시도시군구읍면동주소종류시설명지점명설치연도교체연도데이터기준일
26전라남도광양시진상면전라남도 광양시 진상면 어치리 864-3경보국진상7경보천수암경보201220192023-11-13
27전라남도광양시진상면전라남도 광양시 진상면 어치리 226-2경보국진상8경보장수교경보201520192023-11-13
28전라남도광양시다압면전라남도 광양시 다압면 금천리 719우량국다압1우량동동우량200420192023-11-13
29전라남도광양시다압면전라남도 광양시 다압면 금천리 2795우량국다압2우량서동우량200420192023-11-13
30전라남도광양시다압면전라남도 광양시 다압면 금천리 498-1경보국다압1경보장동나무골경보200420192023-11-13
31전라남도광양시다압면전라남도 광양시 다압면 금천리 산 46-1경보국다압2경보동동경보201220192023-11-13
32전라남도광양시다압면전라남도 광양시 다압면 금천리 1169경보국다압3경보서동교경보200420192023-11-13
33전라남도광양시다압면전라남도 광양시 다압면 금천리 743경보국다압4경보서동입구경보200420192023-11-13
34전라남도광양시다압면전라남도 광양시 다압면 금천리 2786경보국다압5경보서동경보200420192023-11-13
35전라남도광양시다압면전라남도 광양시 다압면 금천리 1562경보국다압6경보휴양소경보201020192023-11-13