Overview

Dataset statistics

Number of variables8
Number of observations76
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory69.7 B

Variable types

Text1
Categorical3
Numeric3
DateTime1

Dataset

Description보령시 도로에 설치되어 있는 미끄럼방지시설에 대한 현황 데이터 입니다. (설치 주소, 관리기관, 포장재질, 폭원, 연장, 위경도, 데이터기준일로 구성)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=332&beforeMenuCd=DOM_000000201001001000&publicdatapk=15088217

Alerts

관리기관 has constant value ""Constant
포장재질 has constant value ""Constant
데이터기준일 has constant value ""Constant
주소 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:45:12.198113
Analysis finished2024-01-09 21:45:13.163572
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주소
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2024-01-10T06:45:13.329417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length17.526316
Min length14

Characters and Unicode

Total characters1332
Distinct characters53
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

Unique76 ?
Unique (%)100.0%

Sample

1st row충남 보령시 내항동 336-12
2nd row충남 보령시 명천동 496-2
3rd row충남 보령시 명천동 497-3
4th row충남 보령시 명천동 430-12
5th row충남 보령시 명천동 443-15
ValueCountFrequency (%)
충남 76
22.4%
보령시 76
22.4%
동대동 17
 
5.0%
명천동 13
 
3.8%
웅천읍 10
 
2.9%
미산면 8
 
2.4%
궁촌동 6
 
1.8%
대창리 6
 
1.8%
남포면 6
 
1.8%
성주면 6
 
1.8%
Other values (92) 115
33.9%
2024-01-10T06:45:13.672120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
263
19.7%
남 83
 
6.2%
1 79
 
5.9%
충 76
 
5.7%
보 76
 
5.7%
령 76
 
5.7%
시 76
 
5.7%
동 63
 
4.7%
- 59
 
4.4%
3 41
 
3.1%
Other values (43) 440
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 707
53.1%
Decimal Number 303
22.7%
Space Separator 263
 
19.7%
Dash Punctuation 59
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 83
11.7%
충 76
10.7%
보 76
10.7%
령 76
10.7%
시 76
10.7%
동 63
8.9%
리 32
 
4.5%
천 24
 
3.4%
대 24
 
3.4%
면 22
 
3.1%
Other values (31) 155
21.9%
Decimal Number
ValueCountFrequency (%)
1 79
26.1%
3 41
13.5%
2 41
13.5%
7 32
10.6%
0 25
 
8.3%
4 24
 
7.9%
5 22
 
7.3%
9 15
 
5.0%
8 12
 
4.0%
6 12
 
4.0%
Space Separator
ValueCountFrequency (%)
263
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 707
53.1%
Common 625
46.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 83
11.7%
충 76
10.7%
보 76
10.7%
령 76
10.7%
시 76
10.7%
동 63
8.9%
리 32
 
4.5%
천 24
 
3.4%
대 24
 
3.4%
면 22
 
3.1%
Other values (31) 155
21.9%
Common
ValueCountFrequency (%)
263
42.1%
1 79
 
12.6%
- 59
 
9.4%
3 41
 
6.6%
2 41
 
6.6%
7 32
 
5.1%
0 25
 
4.0%
4 24
 
3.8%
5 22
 
3.5%
9 15
 
2.4%
Other values (2) 24
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 707
53.1%
ASCII 625
46.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
263
42.1%
1 79
 
12.6%
- 59
 
9.4%
3 41
 
6.6%
2 41
 
6.6%
7 32
 
5.1%
0 25
 
4.0%
4 24
 
3.8%
5 22
 
3.5%
9 15
 
2.4%
Other values (2) 24
 
3.8%
Hangul
ValueCountFrequency (%)
남 83
11.7%
충 76
10.7%
보 76
10.7%
령 76
10.7%
시 76
10.7%
동 63
8.9%
리 32
 
4.5%
천 24
 
3.4%
대 24
 
3.4%
면 22
 
3.1%
Other values (31) 155
21.9%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
보령시
76 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보령시 76
100.0%

Length

2024-01-10T06:45:13.796690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:45:13.894237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보령시 76
100.0%

포장재질
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
아스팔트콘크리트
76 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아스팔트콘크리트 76
100.0%

Length

2024-01-10T06:45:13.992967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:45:14.091732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아스팔트콘크리트 76
100.0%

폭원
Categorical

Distinct5
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
3
44 
6
23 
9
7 
5
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st row3
2nd row3
3rd row6
4th row3
5th row6

Common Values

ValueCountFrequency (%)
3 44
57.9%
6 23
30.3%
9 7
 
9.2%
5 1
 
1.3%
4 1
 
1.3%

Length

2024-01-10T06:45:14.194709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:45:14.301918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 44
57.9%
6 23
30.3%
9 7
 
9.2%
5 1
 
1.3%
4 1
 
1.3%

연장
Real number (ℝ)

Distinct53
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.881579
Minimum2
Maximum364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-01-10T06:45:14.425951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile7
Q125.5
median50
Q365
95-th percentile118.25
Maximum364
Range362
Interquartile range (IQR)39.5

Descriptive statistics

Standard deviation54.150892
Coefficient of variation (CV)0.96902939
Kurtosis15.702476
Mean55.881579
Median Absolute Deviation (MAD)19
Skewness3.4553705
Sum4247
Variance2932.3191
MonotonicityNot monotonic
2024-01-10T06:45:14.564869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 4
 
5.3%
40 3
 
3.9%
52 3
 
3.9%
77 3
 
3.9%
51 2
 
2.6%
7 2
 
2.6%
39 2
 
2.6%
53 2
 
2.6%
57 2
 
2.6%
32 2
 
2.6%
Other values (43) 51
67.1%
ValueCountFrequency (%)
2 1
 
1.3%
3 1
 
1.3%
4 1
 
1.3%
7 2
2.6%
10 1
 
1.3%
11 1
 
1.3%
12 1
 
1.3%
15 4
5.3%
16 2
2.6%
17 1
 
1.3%
ValueCountFrequency (%)
364 1
1.3%
242 1
1.3%
226 1
1.3%
146 1
1.3%
109 1
1.3%
95 1
1.3%
94 1
1.3%
91 1
1.3%
87 1
1.3%
85 1
1.3%

경도
Real number (ℝ)

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.308897
Minimum36.199473
Maximum36.355246
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-01-10T06:45:14.706582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.199473
5-th percentile36.204244
Q136.271812
median36.336991
Q336.345671
95-th percentile36.35194
Maximum36.355246
Range0.15577294
Interquartile range (IQR)0.073858782

Descriptive statistics

Standard deviation0.050457603
Coefficient of variation (CV)0.001389676
Kurtosis-0.46954753
Mean36.308897
Median Absolute Deviation (MAD)0.01390066
Skewness-1.0352502
Sum2759.4761
Variance0.0025459697
MonotonicityNot monotonic
2024-01-10T06:45:14.854144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.3418892 1
 
1.3%
36.23127151 1
 
1.3%
36.24646043 1
 
1.3%
36.24646815 1
 
1.3%
36.27127767 1
 
1.3%
36.27197682 1
 
1.3%
36.27131763 1
 
1.3%
36.23114922 1
 
1.3%
36.23100496 1
 
1.3%
36.30646571 1
 
1.3%
Other values (66) 66
86.8%
ValueCountFrequency (%)
36.19947297 1
1.3%
36.19970024 1
1.3%
36.2026171 1
1.3%
36.20357243 1
1.3%
36.20446749 1
1.3%
36.205404 1
1.3%
36.22472428 1
1.3%
36.22476431 1
1.3%
36.22529923 1
1.3%
36.23100496 1
1.3%
ValueCountFrequency (%)
36.35524591 1
1.3%
36.35492232 1
1.3%
36.35292417 1
1.3%
36.35199603 1
1.3%
36.35192159 1
1.3%
36.35182441 1
1.3%
36.35144129 1
1.3%
36.35129464 1
1.3%
36.351267 1
1.3%
36.35102305 1
1.3%

위도
Real number (ℝ)

Distinct75
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.60703
Minimum126.5099
Maximum126.68093
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-01-10T06:45:14.999136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5099
5-th percentile126.53997
Q1126.59662
median126.60477
Q3126.61506
95-th percentile126.67603
Maximum126.68093
Range0.1710316
Interquartile range (IQR)0.018435475

Descriptive statistics

Standard deviation0.03776285
Coefficient of variation (CV)0.0002982682
Kurtosis0.84609118
Mean126.60703
Median Absolute Deviation (MAD)0.0095918
Skewness-0.17072595
Sum9622.1341
Variance0.0014260329
MonotonicityNot monotonic
2024-01-10T06:45:15.119831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6536703 2
 
2.6%
126.6046074 1
 
1.3%
126.5579548 1
 
1.3%
126.5584584 1
 
1.3%
126.5663909 1
 
1.3%
126.5667386 1
 
1.3%
126.5672804 1
 
1.3%
126.6031901 1
 
1.3%
126.6034794 1
 
1.3%
126.5869402 1
 
1.3%
Other values (65) 65
85.5%
ValueCountFrequency (%)
126.5098983 1
1.3%
126.510016 1
1.3%
126.510132 1
1.3%
126.5396934 1
1.3%
126.5400628 1
1.3%
126.5559071 1
1.3%
126.5579548 1
1.3%
126.5584584 1
1.3%
126.5663909 1
1.3%
126.5667386 1
1.3%
ValueCountFrequency (%)
126.6809299 1
1.3%
126.6807369 1
1.3%
126.6805239 1
1.3%
126.680357 1
1.3%
126.6745906 1
1.3%
126.6743884 1
1.3%
126.6742887 1
1.3%
126.6741039 1
1.3%
126.6543111 1
1.3%
126.6536703 2
2.6%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum2021-09-13 00:00:00
Maximum2021-09-13 00:00:00
2024-01-10T06:45:15.204539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:15.271572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T06:45:12.802242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:12.366896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:12.584951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:12.871301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:12.441069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:12.656084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:12.944675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:12.515847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:12.732397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:45:15.553379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소폭원연장경도위도
주소1.0001.0001.0001.0001.000
폭원1.0001.0000.0000.2950.737
연장1.0000.0001.0000.4930.499
경도1.0000.2950.4931.0000.834
위도1.0000.7370.4990.8341.000
2024-01-10T06:45:15.627321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연장경도위도폭원
연장1.0000.017-0.0650.000
경도0.0171.000-0.0000.165
위도-0.065-0.0001.0000.380
폭원0.0000.1650.3801.000

Missing values

2024-01-10T06:45:13.033822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:45:13.126861image/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

주소관리기관포장재질폭원연장경도위도데이터기준일
0충남 보령시 내항동 336-12보령시아스팔트콘크리트35136.341889126.586942021-09-13
1충남 보령시 명천동 496-2보령시아스팔트콘크리트31136.343622126.5997112021-09-13
2충남 보령시 명천동 497-3보령시아스팔트콘크리트62036.343012126.5998832021-09-13
3충남 보령시 명천동 430-12보령시아스팔트콘크리트32136.342641126.6000262021-09-13
4충남 보령시 명천동 443-15보령시아스팔트콘크리트63736.34176126.6002512021-09-13
5충남 보령시 명천동 431보령시아스팔트콘크리트31636.341131126.6004892021-09-13
6충남 보령시 남포면 봉덕리 9-6보령시아스팔트콘크리트67736.326923126.6021212021-09-13
7충남 보령시 남포면 창동리 570-1보령시아스팔트콘크리트67536.326029126.6024322021-09-13
8충남 보령시 남포면 창동리 567-3보령시아스팔트콘크리트61536.3265126.6023072021-09-13
9충남 보령시 신흑동 918-8보령시아스팔트콘크리트96536.325345126.5100162021-09-13
주소관리기관포장재질폭원연장경도위도데이터기준일
66충남 보령시 성주면 성주리 산 37-2보령시아스팔트콘크리트336436.334974126.6400112021-09-13
67충남 보령시 성주면 성주리 산 38-3보령시아스팔트콘크리트31736.336591126.6441032021-09-13
68충남 보령시 미산면 풍계리 산 37-13보령시아스팔트콘크리트35236.272654126.6803572021-09-13
69충남 보령시 미산면 용수리 2-5보령시아스팔트콘크리트35236.272185126.6805242021-09-13
70충남 보령시 미산면 풍계리 1-7보령시아스팔트콘크리트34336.27227126.680932021-09-13
71충남 보령시 미산면 용수리 1-6보령시아스팔트콘크리트35036.27113126.6807372021-09-13
72충남 보령시 미산면 삼계리 230-1보령시아스팔트콘크리트35036.205404126.6745912021-09-13
73충남 보령시 미산면 삼계리 237-1보령시아스팔트콘크리트35736.204467126.6743882021-09-13
74충남 보령시 미산면 삼계리 201-12보령시아스팔트콘크리트35336.203572126.6742892021-09-13
75충남 보령시 미산면 삼계리 202-1보령시아스팔트콘크리트34936.202617126.6741042021-09-13