Overview

Dataset statistics

Number of variables5
Number of observations160
Missing cells19
Missing cells (%)2.4%
Duplicate rows2
Duplicate rows (%)1.2%
Total size in memory6.7 KiB
Average record size in memory42.8 B

Variable types

Categorical2
DateTime1
Numeric2

Dataset

Description경상남도 사천시 공간정보시스템의 미끄럽방지시설(DB) 자료입니다.(읍면동 코드, 설치일자, 포장종류 코드 등)
Author경상남도 사천시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15091546

Alerts

Dataset has 2 (1.2%) duplicate rowsDuplicates
폭원 is highly overall correlated with 포장종류High correlation
행정읍/면/동 is highly overall correlated with 포장종류High correlation
포장종류 is highly overall correlated with 폭원 and 1 other fieldsHigh correlation
설치일자 has 19 (11.9%) missing valuesMissing
폭원 has 6 (3.8%) zerosZeros
연장 has 6 (3.8%) zerosZeros

Reproduction

Analysis started2023-12-10 23:14:29.926071
Analysis finished2023-12-10 23:14:31.344959
Duration1.42 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정읍/면/동
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
곤명면
35 
사남면
21 
사천읍
21 
곤양면
18 
용현면
16 
Other values (9)
49 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
곤명면 35
21.9%
사남면 21
13.1%
사천읍 21
13.1%
곤양면 18
11.2%
용현면 16
10.0%
서포면 11
 
6.9%
동서동 11
 
6.9%
향촌동 7
 
4.4%
용강동 6
 
3.8%
선구동 5
 
3.1%
Other values (4) 9
 
5.6%

Length

2023-12-11T08:14:31.407465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
곤명면 35
21.9%
사남면 21
13.1%
사천읍 21
13.1%
곤양면 18
11.2%
용현면 16
10.0%
서포면 11
 
6.9%
동서동 11
 
6.9%
향촌동 7
 
4.4%
용강동 6
 
3.8%
선구동 5
 
3.1%
Other values (4) 9
 
5.6%

설치일자
Date

MISSING 

Distinct7
Distinct (%)5.0%
Missing19
Missing (%)11.9%
Memory size1.4 KiB
Minimum1900-01-01 00:00:00
Maximum2011-01-01 00:00:00
2023-12-11T08:14:31.523588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:14:31.642941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

포장종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
투수콘
107 
아스팔트콘크리트
47 
속성나중입력
 
6

Length

Max length8
Median length3
Mean length4.58125
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
투수콘 107
66.9%
아스팔트콘크리트 47
29.4%
속성나중입력 6
 
3.8%

Length

2023-12-11T08:14:31.792122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:14:31.912785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
투수콘 107
66.9%
아스팔트콘크리트 47
29.4%
속성나중입력 6
 
3.8%

폭원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct90
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1553125
Minimum0
Maximum10
Zeros6
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:14:32.071607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.6
Q12.9075
median3.24
Q35.8775
95-th percentile8.01
Maximum10
Range10
Interquartile range (IQR)2.97

Descriptive statistics

Standard deviation2.051643
Coefficient of variation (CV)0.49373975
Kurtosis0.59432865
Mean4.1553125
Median Absolute Deviation (MAD)0.44
Skewness0.87732303
Sum664.85
Variance4.2092389
MonotonicityNot monotonic
2023-12-11T08:14:32.298055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.9 13
 
8.1%
3.0 12
 
7.5%
2.8 10
 
6.2%
3.2 8
 
5.0%
0.0 6
 
3.8%
3.4 6
 
3.8%
2.7 4
 
2.5%
3.1 4
 
2.5%
6.3 3
 
1.9%
3.9 3
 
1.9%
Other values (80) 91
56.9%
ValueCountFrequency (%)
0.0 6
3.8%
2.4 1
 
0.6%
2.6 2
 
1.2%
2.62 1
 
0.6%
2.7 4
 
2.5%
2.8 10
6.2%
2.82 1
 
0.6%
2.86 2
 
1.2%
2.9 13
8.1%
2.91 1
 
0.6%
ValueCountFrequency (%)
10.0 1
0.6%
9.8 1
0.6%
9.7 1
0.6%
9.68 1
0.6%
9.3 1
0.6%
9.24 1
0.6%
8.83 1
0.6%
8.2 1
0.6%
8.0 2
1.2%
7.6 1
0.6%

연장
Real number (ℝ)

ZEROS 

Distinct143
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.179562
Minimum0
Maximum114.2
Zeros6
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:14:32.433882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.049
Q12.845
median33.485
Q364.8075
95-th percentile89.985
Maximum114.2
Range114.2
Interquartile range (IQR)61.9625

Descriptive statistics

Standard deviation31.695567
Coefficient of variation (CV)0.85249973
Kurtosis-1.0743253
Mean37.179562
Median Absolute Deviation (MAD)31.015
Skewness0.40846894
Sum5948.73
Variance1004.609
MonotonicityNot monotonic
2023-12-11T08:14:32.620518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6
 
3.8%
9.0 3
 
1.9%
1.3 3
 
1.9%
15.0 2
 
1.2%
28.6 2
 
1.2%
1.05 2
 
1.2%
1.84 2
 
1.2%
83.7 2
 
1.2%
49.0 2
 
1.2%
1.45 2
 
1.2%
Other values (133) 134
83.8%
ValueCountFrequency (%)
0.0 6
3.8%
1.0 1
 
0.6%
1.03 1
 
0.6%
1.05 2
 
1.2%
1.07 1
 
0.6%
1.1 1
 
0.6%
1.11 1
 
0.6%
1.13 1
 
0.6%
1.14 1
 
0.6%
1.17 1
 
0.6%
ValueCountFrequency (%)
114.2 1
0.6%
108.55 1
0.6%
98.4 1
0.6%
98.21 1
0.6%
97.02 1
0.6%
96.65 1
0.6%
94.18 1
0.6%
93.5 1
0.6%
89.8 1
0.6%
89.37 1
0.6%

Interactions

2023-12-11T08:14:30.325878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:14:30.116636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:14:30.454982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:14:30.217222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:14:32.732211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정읍/면/동설치일자포장종류폭원연장
행정읍/면/동1.0000.6890.7550.5750.266
설치일자0.6891.0000.5710.3370.475
포장종류0.7550.5711.0000.9370.270
폭원0.5750.3370.9371.0000.262
연장0.2660.4750.2700.2621.000
2023-12-11T08:14:32.841701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정읍/면/동포장종류
행정읍/면/동1.0000.567
포장종류0.5671.000
2023-12-11T08:14:32.927381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폭원연장행정읍/면/동포장종류
폭원1.0000.2210.3070.697
연장0.2211.0000.1060.163
행정읍/면/동0.3070.1061.0000.567
포장종류0.6970.1630.5671.000

Missing values

2023-12-11T08:14:31.187436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:14:31.303659image/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

행정읍/면/동설치일자포장종류폭원연장
0곤명면1960-01-01투수콘3.049.0
1곤명면1960-01-01투수콘3.038.8
2곤명면1960-01-01투수콘2.979.6
3곤명면1960-01-01투수콘3.778.1
4곤명면1960-01-01투수콘3.075.4
5곤명면1960-01-01투수콘2.978.9
6곤명면1960-01-01투수콘7.389.8
7곤명면1960-01-01투수콘3.21.45
8곤명면1960-01-01투수콘3.021.1
9서포면1960-01-01투수콘10.050.22
행정읍/면/동설치일자포장종류폭원연장
150용현면1900-01-01아스팔트콘크리트3.2624.89
151용현면1900-01-01아스팔트콘크리트3.3228.6
152벌용동1900-01-01아스팔트콘크리트2.9424.99
153벌용동1900-01-01아스팔트콘크리트3.0116.89
154벌용동1900-01-01아스팔트콘크리트3.0946.61
155벌용동1900-01-01아스팔트콘크리트2.969.35
156서포면1900-01-01아스팔트콘크리트7.0557.09
157서포면1900-01-01아스팔트콘크리트3.5145.68
158서포면1900-01-01아스팔트콘크리트3.43108.55
159서포면1900-01-01아스팔트콘크리트6.8377.95

Duplicate rows

Most frequently occurring

행정읍/면/동설치일자포장종류폭원연장# duplicates
0용현면<NA>속성나중입력0.00.06
1향촌동1960-01-01투수콘3.483.72