Overview

Dataset statistics

Number of variables9
Number of observations76
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory78.7 B

Variable types

Numeric4
Text1
Categorical4

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
연번 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
주소 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:45:02.795983
Analysis finished2024-01-09 21:45:04.473622
Duration1.68 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.5
Minimum1
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-01-10T06:45:04.527071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.75
Q119.75
median38.5
Q357.25
95-th percentile72.25
Maximum76
Range75
Interquartile range (IQR)37.5

Descriptive statistics

Standard deviation22.083176
Coefficient of variation (CV)0.57358899
Kurtosis-1.2
Mean38.5
Median Absolute Deviation (MAD)19
Skewness0
Sum2926
Variance487.66667
MonotonicityStrictly increasing
2024-01-10T06:45:04.653459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
50 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
49 1
 
1.3%
Other values (66) 66
86.8%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%
67 1
1.3%

주소
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2024-01-10T06:45:04.903236image/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%
2024-01-10T06:45:05.235851image/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

2024-01-10T06:45:05.358141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:45:05.452332image/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

2024-01-10T06:45:05.783121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:45:05.861543image/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

2024-01-10T06:45:05.937122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:45:06.019282image/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
2024-01-10T06:45:06.111117image/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
2024-01-10T06:45:06.214078image/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)

HIGH CORRELATION  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
2024-01-10T06:45:06.321099image/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
2024-01-10T06:45:06.431647image/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
2024-01-10T06:45:06.539012image/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
2024-01-10T06:45:06.644500image/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
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-08-28
76 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-28
2nd row2023-08-28
3rd row2023-08-28
4th row2023-08-28
5th row2023-08-28

Common Values

ValueCountFrequency (%)
2023-08-28 76
100.0%

Length

2024-01-10T06:45:06.751305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:45:06.822875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-28 76
100.0%

Interactions

2024-01-10T06:45:03.986057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.024688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.311072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.601578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:04.073751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.093122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.380919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.694954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:04.164655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.163528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.449668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.794935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:04.239232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.236802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.522413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:45:03.891912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:45:06.871391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주소폭원연장경도위도
연번1.0001.0000.7090.2000.7850.908
주소1.0001.0001.0001.0001.0001.000
폭원0.7091.0001.0000.0000.2950.737
연장0.2001.0000.0001.0000.4930.499
경도0.7851.0000.2950.4931.0000.834
위도0.9081.0000.7370.4990.8341.000
2024-01-10T06:45:06.948499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연장경도위도폭원
연번1.0000.068-0.5740.4570.352
연장0.0681.0000.017-0.0650.000
경도-0.5740.0171.000-0.0000.165
위도0.457-0.065-0.0001.0000.380
폭원0.3520.0000.1650.3801.000

Missing values

2024-01-10T06:45:04.329670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:45:04.435009image/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

연번주소관리기관포장재질폭원연장경도위도데이터기준일
01충남 보령시 내항동 336-12보령시아스팔트콘크리트35136.341889126.586942023-08-28
12충남 보령시 명천동 496-2보령시아스팔트콘크리트31136.343622126.5997112023-08-28
23충남 보령시 명천동 497-3보령시아스팔트콘크리트62036.343012126.5998832023-08-28
34충남 보령시 명천동 430-12보령시아스팔트콘크리트32136.342641126.6000262023-08-28
45충남 보령시 명천동 443-15보령시아스팔트콘크리트63736.34176126.6002512023-08-28
56충남 보령시 명천동 431보령시아스팔트콘크리트31636.341131126.6004892023-08-28
67충남 보령시 남포면 봉덕리 9-6보령시아스팔트콘크리트67736.326923126.6021212023-08-28
78충남 보령시 남포면 창동리 570-1보령시아스팔트콘크리트67536.326029126.6024322023-08-28
89충남 보령시 남포면 창동리 567-3보령시아스팔트콘크리트61536.3265126.6023072023-08-28
910충남 보령시 신흑동 918-8보령시아스팔트콘크리트96536.325345126.5100162023-08-28
연번주소관리기관포장재질폭원연장경도위도데이터기준일
6667충남 보령시 성주면 성주리 산 37-2보령시아스팔트콘크리트336436.334974126.6400112023-08-28
6768충남 보령시 성주면 성주리 산 38-3보령시아스팔트콘크리트31736.336591126.6441032023-08-28
6869충남 보령시 미산면 풍계리 산 37-13보령시아스팔트콘크리트35236.272654126.6803572023-08-28
6970충남 보령시 미산면 용수리 2-5보령시아스팔트콘크리트35236.272185126.6805242023-08-28
7071충남 보령시 미산면 풍계리 1-7보령시아스팔트콘크리트34336.27227126.680932023-08-28
7172충남 보령시 미산면 용수리 1-6보령시아스팔트콘크리트35036.27113126.6807372023-08-28
7273충남 보령시 미산면 삼계리 230-1보령시아스팔트콘크리트35036.205404126.6745912023-08-28
7374충남 보령시 미산면 삼계리 237-1보령시아스팔트콘크리트35736.204467126.6743882023-08-28
7475충남 보령시 미산면 삼계리 201-12보령시아스팔트콘크리트35336.203572126.6742892023-08-28
7576충남 보령시 미산면 삼계리 202-1보령시아스팔트콘크리트34936.202617126.6741042023-08-28