Overview

Dataset statistics

Number of variables5
Number of observations141
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)1.4%
Total size in memory6.0 KiB
Average record size in memory43.9 B

Variable types

Categorical2
Numeric3

Dataset

Description경상남도 사천시 공간정보시스템의 중앙분리대(DB) 자료입니다.(설치일자, 중앙분리대 종류 ,연장, 폭원 등)
Author경상남도 사천시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15091544

Alerts

Dataset has 2 (1.4%) duplicate rowsDuplicates
폭원 is highly overall correlated with 설치일자 and 1 other fieldsHigh correlation
설치일자 is highly overall correlated with 폭원 and 1 other fieldsHigh correlation
중앙분리대 종류 is highly overall correlated with 폭원 and 1 other fieldsHigh correlation
폭원 has 16 (11.3%) zerosZeros
높이 has 11 (7.8%) zerosZeros

Reproduction

Analysis started2023-12-11 00:33:49.385567
Analysis finished2023-12-11 00:33:50.749408
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치일자
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1960-01-01
82 
2011-01-01
35 
2010-01-01
17 
2008-01-01
 
7

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1960-01-01
2nd row1960-01-01
3rd row1960-01-01
4th row1960-01-01
5th row1960-01-01

Common Values

ValueCountFrequency (%)
1960-01-01 82
58.2%
2011-01-01 35
24.8%
2010-01-01 17
 
12.1%
2008-01-01 7
 
5.0%

Length

2023-12-11T09:33:50.820481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:50.932250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1960-01-01 82
58.2%
2011-01-01 35
24.8%
2010-01-01 17
 
12.1%
2008-01-01 7
 
5.0%

중앙분리대 종류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
가드레일
66 
기타
23 
녹지대
20 
시선유도봉
18 
미분류
13 

Length

Max length6
Median length5
Mean length3.5815603
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row가드레일
2nd row가드레일
3rd row미분류
4th row가드레일
5th row미분류

Common Values

ValueCountFrequency (%)
가드레일 66
46.8%
기타 23
 
16.3%
녹지대 20
 
14.2%
시선유도봉 18
 
12.8%
미분류 13
 
9.2%
충격흡수시설 1
 
0.7%

Length

2023-12-11T09:33:51.127992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:51.279791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가드레일 66
46.8%
기타 23
 
16.3%
녹지대 20
 
14.2%
시선유도봉 18
 
12.8%
미분류 13
 
9.2%
충격흡수시설 1
 
0.7%

연장
Real number (ℝ)

Distinct139
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean248.69702
Minimum9.41
Maximum4939.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:33:51.414328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.41
5-th percentile17.28
Q157.82
median107.8
Q3245.5
95-th percentile899.33
Maximum4939.79
Range4930.38
Interquartile range (IQR)187.68

Descriptive statistics

Standard deviation474.74513
Coefficient of variation (CV)1.9089297
Kurtosis68.537603
Mean248.69702
Median Absolute Deviation (MAD)60.65
Skewness7.2604345
Sum35066.28
Variance225382.94
MonotonicityNot monotonic
2023-12-11T09:33:51.559525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63.1 2
 
1.4%
47.15 2
 
1.4%
400.59 1
 
0.7%
17.28 1
 
0.7%
404.29 1
 
0.7%
80.3 1
 
0.7%
78.63 1
 
0.7%
101.35 1
 
0.7%
97.36 1
 
0.7%
445.49 1
 
0.7%
Other values (129) 129
91.5%
ValueCountFrequency (%)
9.41 1
0.7%
9.43 1
0.7%
12.3 1
0.7%
15.06 1
0.7%
16.87 1
0.7%
16.94 1
0.7%
17.0 1
0.7%
17.28 1
0.7%
19.95 1
0.7%
20.03 1
0.7%
ValueCountFrequency (%)
4939.79 1
0.7%
1253.31 1
0.7%
1120.0 1
0.7%
1102.5 1
0.7%
997.2 1
0.7%
920.7 1
0.7%
909.4 1
0.7%
899.33 1
0.7%
831.35 1
0.7%
827.51 1
0.7%

폭원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.72553191
Minimum0
Maximum3.1
Zeros16
Zeros (%)11.3%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:33:51.701931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.3
median0.5
Q31.1
95-th percentile2.5
Maximum3.1
Range3.1
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.73680917
Coefficient of variation (CV)1.0155434
Kurtosis2.0094549
Mean0.72553191
Median Absolute Deviation (MAD)0.4
Skewness1.5516455
Sum102.3
Variance0.54288775
MonotonicityNot monotonic
2023-12-11T09:33:51.839259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.5 31
22.0%
0.4 22
15.6%
0.1 19
13.5%
0.0 16
11.3%
1.1 10
 
7.1%
1.5 7
 
5.0%
1.0 4
 
2.8%
1.35 4
 
2.8%
3.0 4
 
2.8%
2.0 3
 
2.1%
Other values (15) 21
14.9%
ValueCountFrequency (%)
0.0 16
11.3%
0.1 19
13.5%
0.3 2
 
1.4%
0.4 22
15.6%
0.45 2
 
1.4%
0.46 1
 
0.7%
0.5 31
22.0%
0.52 1
 
0.7%
0.6 2
 
1.4%
0.7 2
 
1.4%
ValueCountFrequency (%)
3.1 1
 
0.7%
3.0 4
2.8%
2.6 1
 
0.7%
2.5 2
 
1.4%
2.1 2
 
1.4%
2.0 3
2.1%
1.9 1
 
0.7%
1.76 1
 
0.7%
1.5 7
5.0%
1.46 1
 
0.7%

높이
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.86028369
Minimum0
Maximum3.1
Zeros11
Zeros (%)7.8%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:33:52.004614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.75
median0.8
Q31.09
95-th percentile1.5
Maximum3.1
Range3.1
Interquartile range (IQR)0.34

Descriptive statistics

Standard deviation0.49202924
Coefficient of variation (CV)0.57193836
Kurtosis2.6650857
Mean0.86028369
Median Absolute Deviation (MAD)0.15
Skewness0.68046062
Sum121.3
Variance0.24209278
MonotonicityNot monotonic
2023-12-11T09:33:52.179501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.8 32
22.7%
1.5 19
13.5%
0.75 13
9.2%
0.2 12
 
8.5%
0.0 11
 
7.8%
0.9 9
 
6.4%
0.77 5
 
3.5%
1.0 5
 
3.5%
1.4 4
 
2.8%
0.78 4
 
2.8%
Other values (18) 27
19.1%
ValueCountFrequency (%)
0.0 11
7.8%
0.2 12
8.5%
0.3 3
 
2.1%
0.5 1
 
0.7%
0.6 1
 
0.7%
0.7 3
 
2.1%
0.72 1
 
0.7%
0.75 13
9.2%
0.77 5
 
3.5%
0.78 4
 
2.8%
ValueCountFrequency (%)
3.1 1
 
0.7%
2.5 1
 
0.7%
1.5 19
13.5%
1.45 2
 
1.4%
1.4 4
 
2.8%
1.34 1
 
0.7%
1.33 1
 
0.7%
1.3 3
 
2.1%
1.26 1
 
0.7%
1.2 1
 
0.7%

Interactions

2023-12-11T09:33:50.258223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:49.606556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:49.967405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:50.374779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:49.750385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:50.060276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:50.482048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:49.862983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:50.167164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:33:52.638873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치일자중앙분리대 종류연장폭원높이
설치일자1.0000.6790.1970.6940.585
중앙분리대 종류0.6791.0000.2410.8020.652
연장0.1970.2411.0000.0760.135
폭원0.6940.8020.0761.0000.705
높이0.5850.6520.1350.7051.000
2023-12-11T09:33:52.768851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치일자중앙분리대 종류
설치일자1.0000.505
중앙분리대 종류0.5051.000
2023-12-11T09:33:52.861286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연장폭원높이설치일자중앙분리대 종류
연장1.000-0.0810.1140.0780.155
폭원-0.0811.000-0.2670.5180.548
높이0.114-0.2671.0000.4400.459
설치일자0.0780.5180.4401.0000.505
중앙분리대 종류0.1550.5480.4590.5051.000

Missing values

2023-12-11T09:33:50.614428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:33:50.710847image/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

설치일자중앙분리대 종류연장폭원높이
01960-01-01가드레일400.591.460.77
11960-01-01가드레일100.881.30.75
21960-01-01미분류518.730.00.0
31960-01-01가드레일47.150.50.93
41960-01-01미분류124.730.00.0
51960-01-01미분류149.20.00.0
61960-01-01미분류831.350.00.0
71960-01-01미분류633.820.00.0
81960-01-01미분류93.390.00.0
91960-01-01미분류4939.790.00.0
설치일자중앙분리대 종류연장폭원높이
1311960-01-01녹지대50.943.00.3
1321960-01-01녹지대158.343.00.3
1331960-01-01녹지대52.23.00.3
1341960-01-01기타82.150.11.0
1351960-01-01기타57.820.11.0
1361960-01-01기타85.460.11.0
1371960-01-01기타141.650.11.0
1381960-01-01기타79.550.10.9
1391960-01-01기타49.210.10.9
1401960-01-01기타141.530.10.9

Duplicate rows

Most frequently occurring

설치일자중앙분리대 종류연장폭원높이# duplicates
01960-01-01가드레일47.150.50.932
12011-01-01기타63.10.00.92