Overview

Dataset statistics

Number of variables21
Number of observations97
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.9 KiB
Average record size in memory178.4 B

Variable types

Text4
Categorical8
Numeric8
DateTime1

Dataset

Description경상남도 진주시의 임도현황에 대한 데이터로 임도명, 조성연도, 거리, 폭, 산주수, 유역면적 등 다양한 정보를 제공합니다
URLhttps://www.data.go.kr/data/15116589/fileData.do

Alerts

기관명 has constant value ""Constant
관리부서 has constant value ""Constant
시도 has constant value ""Constant
시군구 has constant value ""Constant
사업별 has constant value ""Constant
전화번호 has unique valuesUnique
데이터기준일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:44:40.543036
Analysis finished2023-12-12 17:44:40.832060
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대장번호
Text

Distinct96
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-12-13T02:44:41.048718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1164
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)97.9%

Sample

1st row경남-진주-1985-1
2nd row경남-진주-1987-1
3rd row경남-진주-1988-1
4th row경남-진주-1988-2
5th row경남-진주-1989-1
ValueCountFrequency (%)
경남-진주-1995-8 2
 
2.1%
경남-진주-1985-1 1
 
1.0%
경남-진주-1998-1 1
 
1.0%
경남-진주-2007-1 1
 
1.0%
경남-진주-2006-1 1
 
1.0%
경남-진주-2005-1 1
 
1.0%
경남-진주-2003-1 1
 
1.0%
경남-진주-2002-3 1
 
1.0%
경남-진주-2002-2 1
 
1.0%
경남-진주-2002-1 1
 
1.0%
Other values (86) 86
88.7%
2023-12-13T02:44:41.452821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 291
25.0%
1 125
10.7%
9 120
10.3%
경 97
 
8.3%
남 97
 
8.3%
진 97
 
8.3%
주 97
 
8.3%
2 74
 
6.4%
0 63
 
5.4%
3 21
 
1.8%
Other values (5) 82
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 485
41.7%
Other Letter 388
33.3%
Dash Punctuation 291
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 125
25.8%
9 120
24.7%
2 74
15.3%
0 63
13.0%
3 21
 
4.3%
5 19
 
3.9%
4 18
 
3.7%
8 17
 
3.5%
7 14
 
2.9%
6 14
 
2.9%
Other Letter
ValueCountFrequency (%)
경 97
25.0%
남 97
25.0%
진 97
25.0%
주 97
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 291
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 776
66.7%
Hangul 388
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 291
37.5%
1 125
16.1%
9 120
15.5%
2 74
 
9.5%
0 63
 
8.1%
3 21
 
2.7%
5 19
 
2.4%
4 18
 
2.3%
8 17
 
2.2%
7 14
 
1.8%
Hangul
ValueCountFrequency (%)
경 97
25.0%
남 97
25.0%
진 97
25.0%
주 97
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 776
66.7%
Hangul 388
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 291
37.5%
1 125
16.1%
9 120
15.5%
2 74
 
9.5%
0 63
 
8.1%
3 21
 
2.7%
5 19
 
2.4%
4 18
 
2.3%
8 17
 
2.2%
7 14
 
1.8%
Hangul
ValueCountFrequency (%)
경 97
25.0%
남 97
25.0%
진 97
25.0%
주 97
25.0%

기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
경상남도 진주시청
97 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도 진주시청
2nd row경상남도 진주시청
3rd row경상남도 진주시청
4th row경상남도 진주시청
5th row경상남도 진주시청

Common Values

ValueCountFrequency (%)
경상남도 진주시청 97
100.0%

Length

2023-12-13T02:44:41.601301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:41.687160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 97
50.0%
진주시청 97
50.0%

관리부서
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
산림과
97 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
산림과 97
100.0%

Length

2023-12-13T02:44:41.786622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:41.872678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
산림과 97
100.0%

임도명
Text

Distinct68
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-12-13T02:44:42.125380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length11
Mean length12.793814
Min length11

Characters and Unicode

Total characters1241
Distinct characters86
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)52.6%

Sample

1st row진주시 진성면 동산리
2nd row진주시 미천면 향양리~오방
3rd row진주시 진성면 구천리~대사리
4th row진주시 미천면 오방리
5th row진주시 명석면 신기리 ~ 외율리
ValueCountFrequency (%)
진주시 97
31.5%
명석면 14
 
4.5%
미천면 11
 
3.6%
대곡면 9
 
2.9%
정촌면 8
 
2.6%
집현면 8
 
2.6%
대평면 7
 
2.3%
내동면 7
 
2.3%
금곡면 6
 
1.9%
대곡리 6
 
1.9%
Other values (78) 135
43.8%
2023-12-13T02:44:42.574953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
212
17.1%
리 114
 
9.2%
진 104
 
8.4%
면 103
 
8.3%
주 97
 
7.8%
시 97
 
7.8%
곡 38
 
3.1%
대 36
 
2.9%
~ 29
 
2.3%
정 21
 
1.7%
Other values (76) 390
31.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 997
80.3%
Space Separator 212
 
17.1%
Math Symbol 29
 
2.3%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 114
 
11.4%
진 104
 
10.4%
면 103
 
10.3%
주 97
 
9.7%
시 97
 
9.7%
곡 38
 
3.8%
대 36
 
3.6%
정 21
 
2.1%
수 19
 
1.9%
천 15
 
1.5%
Other values (71) 353
35.4%
Space Separator
ValueCountFrequency (%)
212
100.0%
Math Symbol
ValueCountFrequency (%)
~ 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 997
80.3%
Common 244
 
19.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 114
 
11.4%
진 104
 
10.4%
면 103
 
10.3%
주 97
 
9.7%
시 97
 
9.7%
곡 38
 
3.8%
대 36
 
3.6%
정 21
 
2.1%
수 19
 
1.9%
천 15
 
1.5%
Other values (71) 353
35.4%
Common
ValueCountFrequency (%)
212
86.9%
~ 29
 
11.9%
) 1
 
0.4%
, 1
 
0.4%
( 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 997
80.3%
ASCII 244
 
19.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
212
86.9%
~ 29
 
11.9%
) 1
 
0.4%
, 1
 
0.4%
( 1
 
0.4%
Hangul
ValueCountFrequency (%)
리 114
 
11.4%
진 104
 
10.4%
면 103
 
10.3%
주 97
 
9.7%
시 97
 
9.7%
곡 38
 
3.8%
대 36
 
3.6%
정 21
 
2.1%
수 19
 
1.9%
천 15
 
1.5%
Other values (71) 353
35.4%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
경남
97 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경남 97
100.0%

Length

2023-12-13T02:44:42.730328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:42.818439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경남 97
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
진주
97 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진주 97
100.0%

Length

2023-12-13T02:44:42.909391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:42.984961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진주 97
100.0%

읍면
Categorical

Distinct17
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size908.0 B
명석
14 
미천
12 
대곡
10 
정촌
8 
내동
7 
Other values (12)
46 

Length

Max length3
Median length2
Mean length2.0927835
Min length2

Unique

Unique2 ?
Unique (%)2.1%

Sample

1st row진성
2nd row미천
3rd row 진성
4th row미천
5th row명석

Common Values

ValueCountFrequency (%)
명석 14
14.4%
미천 12
12.4%
대곡 10
10.3%
정촌 8
8.2%
내동 7
 
7.2%
대평 7
 
7.2%
금곡 6
 
6.2%
사봉 5
 
5.2%
집현 5
 
5.2%
수곡 5
 
5.2%
Other values (7) 18
18.6%

Length

2023-12-13T02:44:43.070206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
명석 14
14.4%
미천 12
12.4%
대곡 10
10.3%
정촌 8
8.2%
내동 7
 
7.2%
대평 7
 
7.2%
금곡 6
 
6.2%
사봉 5
 
5.2%
집현 5
 
5.2%
수곡 5
 
5.2%
Other values (5) 18
18.6%

리동
Categorical

Distinct47
Distinct (%)48.5%
Missing0
Missing (%)0.0%
Memory size908.0 B
대곡
 
7
향양
 
5
부계
 
5
대축
 
4
신기
 
4
Other values (42)
72 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique24 ?
Unique (%)24.7%

Sample

1st row동산
2nd row향양
3rd row구천
4th row오방
5th row신기

Common Values

ValueCountFrequency (%)
대곡 7
 
7.2%
향양 5
 
5.2%
부계 5
 
5.2%
대축 4
 
4.1%
신기 4
 
4.1%
관봉 4
 
4.1%
외율 4
 
4.1%
안간 4
 
4.1%
청원 3
 
3.1%
남성 3
 
3.1%
Other values (37) 54
55.7%

Length

2023-12-13T02:44:43.175882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대곡 7
 
7.2%
부계 5
 
5.2%
향양 5
 
5.2%
대축 4
 
4.1%
신기 4
 
4.1%
관봉 4
 
4.1%
외율 4
 
4.1%
안간 4
 
4.1%
유수 3
 
3.1%
정수 3
 
3.1%
Other values (37) 54
55.7%

번지
Text

Distinct78
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-12-13T02:44:43.389512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.5979381
Min length2

Characters and Unicode

Total characters349
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)63.9%

Sample

1st row산95
2nd row산124
3rd row산201
4th row산186
5th row164
ValueCountFrequency (%)
산26 4
 
4.1%
산152 3
 
3.1%
산180 2
 
2.1%
산115 2
 
2.1%
산302 2
 
2.1%
산36 2
 
2.1%
산7 2
 
2.1%
산34 2
 
2.1%
산69 2
 
2.1%
산146 2
 
2.1%
Other values (68) 74
76.3%
2023-12-13T02:44:43.755358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 87
24.9%
1 55
15.8%
2 38
10.9%
6 31
 
8.9%
4 26
 
7.4%
3 25
 
7.2%
0 21
 
6.0%
5 17
 
4.9%
8 16
 
4.6%
7 16
 
4.6%
Other values (2) 17
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 255
73.1%
Other Letter 87
 
24.9%
Dash Punctuation 7
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 55
21.6%
2 38
14.9%
6 31
12.2%
4 26
10.2%
3 25
9.8%
0 21
 
8.2%
5 17
 
6.7%
8 16
 
6.3%
7 16
 
6.3%
9 10
 
3.9%
Other Letter
ValueCountFrequency (%)
산 87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 262
75.1%
Hangul 87
 
24.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 55
21.0%
2 38
14.5%
6 31
11.8%
4 26
9.9%
3 25
9.5%
0 21
 
8.0%
5 17
 
6.5%
8 16
 
6.1%
7 16
 
6.1%
9 10
 
3.8%
Hangul
ValueCountFrequency (%)
산 87
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 262
75.1%
Hangul 87
 
24.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 87
100.0%
ASCII
ValueCountFrequency (%)
1 55
21.0%
2 38
14.5%
6 31
11.8%
4 26
9.9%
3 25
9.5%
0 21
 
8.0%
5 17
 
6.5%
8 16
 
6.1%
7 16
 
6.1%
9 10
 
3.8%

사업별
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
간선
97 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
간선 97
100.0%

Length

2023-12-13T02:44:43.891091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:43.971267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
간선 97
100.0%

조성연도
Real number (ℝ)

Distinct35
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2000.3505
Minimum1985
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T02:44:44.054561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1985
5-th percentile1989.8
Q11994
median1997
Q32007
95-th percentile2018.2
Maximum2022
Range37
Interquartile range (IQR)13

Descriptive statistics

Standard deviation8.9186617
Coefficient of variation (CV)0.0044585494
Kurtosis-0.33633637
Mean2000.3505
Median Absolute Deviation (MAD)4
Skewness0.78168767
Sum194034
Variance79.542526
MonotonicityIncreasing
2023-12-13T02:44:44.192992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1995 9
 
9.3%
1996 8
 
8.2%
1997 7
 
7.2%
1994 6
 
6.2%
1998 5
 
5.2%
2011 5
 
5.2%
1993 5
 
5.2%
1991 4
 
4.1%
1992 4
 
4.1%
1999 4
 
4.1%
Other values (25) 40
41.2%
ValueCountFrequency (%)
1985 1
 
1.0%
1987 1
 
1.0%
1988 2
 
2.1%
1989 1
 
1.0%
1990 2
 
2.1%
1991 4
4.1%
1992 4
4.1%
1993 5
5.2%
1994 6
6.2%
1995 9
9.3%
ValueCountFrequency (%)
2022 1
1.0%
2021 2
2.1%
2020 1
1.0%
2019 1
1.0%
2018 1
1.0%
2016 1
1.0%
2015 1
1.0%
2014 2
2.1%
2013 2
2.1%
2012 2
2.1%

거리(km)
Real number (ℝ)

Distinct72
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4410309
Minimum0.24
Maximum4.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T02:44:44.325681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.24
5-th percentile0.39
Q10.86
median1.4
Q31.86
95-th percentile2.878
Maximum4.06
Range3.82
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.80534734
Coefficient of variation (CV)0.55886888
Kurtosis0.83913307
Mean1.4410309
Median Absolute Deviation (MAD)0.5
Skewness0.90113246
Sum139.78
Variance0.64858434
MonotonicityNot monotonic
2023-12-13T02:44:44.460372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 5
 
5.2%
1.64 4
 
4.1%
1.5 4
 
4.1%
0.7 3
 
3.1%
0.92 3
 
3.1%
1.04 3
 
3.1%
0.4 2
 
2.1%
1.3 2
 
2.1%
1.86 2
 
2.1%
1.74 2
 
2.1%
Other values (62) 67
69.1%
ValueCountFrequency (%)
0.24 1
1.0%
0.28 1
1.0%
0.29 1
1.0%
0.34 1
1.0%
0.35 1
1.0%
0.4 2
2.1%
0.44 1
1.0%
0.46 1
1.0%
0.5 1
1.0%
0.52 1
1.0%
ValueCountFrequency (%)
4.06 1
1.0%
3.68 1
1.0%
3.52 1
1.0%
3.37 1
1.0%
3.27 1
1.0%
2.78 1
1.0%
2.74 1
1.0%
2.52 1
1.0%
2.46 1
1.0%
2.36 1
1.0%

폭(m)
Categorical

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
4.0
54 
3.0
37 
3.5
6 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4.0
2nd row4.0
3rd row4.0
4th row4.0
5th row4.0

Common Values

ValueCountFrequency (%)
4.0 54
55.7%
3.0 37
38.1%
3.5 6
 
6.2%

Length

2023-12-13T02:44:44.588337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:44.678785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4.0 54
55.7%
3.0 37
38.1%
3.5 6
 
6.2%

시점(X좌표)
Real number (ℝ)

Distinct93
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120541.47
Minimum100548
Maximum141993
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T02:44:44.805532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100548
5-th percentile104690.6
Q1112630
median117826
Q3127991
95-th percentile138720.4
Maximum141993
Range41445
Interquartile range (IQR)15361

Descriptive statistics

Standard deviation10789.308
Coefficient of variation (CV)0.089507019
Kurtosis-0.91029865
Mean120541.47
Median Absolute Deviation (MAD)7787
Skewness0.29094458
Sum11692523
Variance1.1640917 × 108
MonotonicityNot monotonic
2023-12-13T02:44:44.934515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
113244 2
 
2.1%
123372 2
 
2.1%
126454 2
 
2.1%
111096 2
 
2.1%
128309 1
 
1.0%
136208 1
 
1.0%
110576 1
 
1.0%
111179 1
 
1.0%
127398 1
 
1.0%
128044 1
 
1.0%
Other values (83) 83
85.6%
ValueCountFrequency (%)
100548 1
1.0%
101683 1
1.0%
102634 1
1.0%
104205 1
1.0%
104365 1
1.0%
104772 1
1.0%
104992 1
1.0%
105750 1
1.0%
106086 1
1.0%
107995 1
1.0%
ValueCountFrequency (%)
141993 1
1.0%
141805 1
1.0%
141250 1
1.0%
140991 1
1.0%
138794 1
1.0%
138702 1
1.0%
138462 1
1.0%
137883 1
1.0%
136736 1
1.0%
136311 1
1.0%

시점(Y좌표)
Real number (ℝ)

Distinct94
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290567.38
Minimum194569
Maximum303669
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T02:44:45.057041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum194569
5-th percentile280784.8
Q1283341
median292878
Q3297734
95-th percentile301681.2
Maximum303669
Range109100
Interquartile range (IQR)14393

Descriptive statistics

Standard deviation12270.102
Coefficient of variation (CV)0.042228079
Kurtosis38.684591
Mean290567.38
Median Absolute Deviation (MAD)6875
Skewness-5.0344209
Sum28185036
Variance1.5055541 × 108
MonotonicityNot monotonic
2023-12-13T02:44:45.181424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
278970 2
 
2.1%
282309 2
 
2.1%
301251 2
 
2.1%
288542 1
 
1.0%
299175 1
 
1.0%
282265 1
 
1.0%
297734 1
 
1.0%
297600 1
 
1.0%
297205 1
 
1.0%
294760 1
 
1.0%
Other values (84) 84
86.6%
ValueCountFrequency (%)
194569 1
1.0%
278432 1
1.0%
278970 2
2.1%
280348 1
1.0%
280894 1
1.0%
281200 1
1.0%
281569 1
1.0%
281770 1
1.0%
281778 1
1.0%
281794 1
1.0%
ValueCountFrequency (%)
303669 1
1.0%
302513 1
1.0%
302466 1
1.0%
302151 1
1.0%
301702 1
1.0%
301676 1
1.0%
301251 2
2.1%
301185 1
1.0%
301100 1
1.0%
300816 1
1.0%

종점(X좌표)
Real number (ℝ)

Distinct87
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120497.75
Minimum101368
Maximum142054
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T02:44:45.303033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101368
5-th percentile104160
Q1112706
median117936
Q3128042
95-th percentile138720.4
Maximum142054
Range40686
Interquartile range (IQR)15336

Descriptive statistics

Standard deviation10868.344
Coefficient of variation (CV)0.090195407
Kurtosis-0.89159863
Mean120497.75
Median Absolute Deviation (MAD)7941
Skewness0.28606515
Sum11688282
Variance1.181209 × 108
MonotonicityNot monotonic
2023-12-13T02:44:45.423984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
114881 3
 
3.1%
125521 2
 
2.1%
119114 2
 
2.1%
112706 2
 
2.1%
123372 2
 
2.1%
127063 2
 
2.1%
117936 2
 
2.1%
109509 2
 
2.1%
113244 2
 
2.1%
104205 1
 
1.0%
Other values (77) 77
79.4%
ValueCountFrequency (%)
101368 1
1.0%
101530 1
1.0%
101567 1
1.0%
103259 1
1.0%
103980 1
1.0%
104205 1
1.0%
104365 1
1.0%
105750 1
1.0%
106200 1
1.0%
107488 1
1.0%
ValueCountFrequency (%)
142054 1
1.0%
141993 1
1.0%
141805 1
1.0%
141345 1
1.0%
138794 1
1.0%
138702 1
1.0%
138462 1
1.0%
138269 1
1.0%
136568 1
1.0%
136236 1
1.0%

종점(Y좌표)
Real number (ℝ)

Distinct86
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290512.04
Minimum194022
Maximum304366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T02:44:45.549191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum194022
5-th percentile281138.8
Q1283551
median292036
Q3297940
95-th percentile301331.6
Maximum304366
Range110344
Interquartile range (IQR)14389

Descriptive statistics

Standard deviation12257.679
Coefficient of variation (CV)0.042193361
Kurtosis39.705374
Mean290512.04
Median Absolute Deviation (MAD)7423
Skewness-5.1290746
Sum28179668
Variance1.502507 × 108
MonotonicityNot monotonic
2023-12-13T02:44:45.674301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300301 3
 
3.1%
300630 3
 
3.1%
282781 2
 
2.1%
283551 2
 
2.1%
294783 2
 
2.1%
279336 2
 
2.1%
299459 2
 
2.1%
295964 2
 
2.1%
299803 2
 
2.1%
291745 1
 
1.0%
Other values (76) 76
78.4%
ValueCountFrequency (%)
194022 1
1.0%
277387 1
1.0%
279336 2
2.1%
280894 1
1.0%
281200 1
1.0%
281569 1
1.0%
281602 1
1.0%
281778 1
1.0%
281794 1
1.0%
282009 1
1.0%
ValueCountFrequency (%)
304366 1
 
1.0%
302466 1
 
1.0%
302152 1
 
1.0%
301676 1
 
1.0%
301394 1
 
1.0%
301316 1
 
1.0%
301100 1
 
1.0%
300634 1
 
1.0%
300630 3
3.1%
300306 1
 
1.0%

산주수
Real number (ℝ)

Distinct37
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.505155
Minimum1
Maximum227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T02:44:45.780127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median12
Q324
95-th percentile59.4
Maximum227
Range226
Interquartile range (IQR)19

Descriptive statistics

Standard deviation31.630722
Coefficient of variation (CV)1.5425742
Kurtosis21.935998
Mean20.505155
Median Absolute Deviation (MAD)8
Skewness4.2143196
Sum1989
Variance1000.5026
MonotonicityNot monotonic
2023-12-13T02:44:45.894761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
5 10
 
10.3%
3 7
 
7.2%
4 6
 
6.2%
12 6
 
6.2%
15 6
 
6.2%
1 6
 
6.2%
6 5
 
5.2%
14 4
 
4.1%
25 4
 
4.1%
8 3
 
3.1%
Other values (27) 40
41.2%
ValueCountFrequency (%)
1 6
6.2%
2 2
 
2.1%
3 7
7.2%
4 6
6.2%
5 10
10.3%
6 5
5.2%
7 3
 
3.1%
8 3
 
3.1%
9 1
 
1.0%
10 2
 
2.1%
ValueCountFrequency (%)
227 1
1.0%
155 1
1.0%
102 1
1.0%
101 1
1.0%
89 1
1.0%
52 1
1.0%
51 1
1.0%
44 2
2.1%
43 1
1.0%
37 2
2.1%

유역면적(ha)
Real number (ℝ)

Distinct40
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.113402
Minimum1
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T02:44:46.004194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median12
Q326
95-th percentile59
Maximum85
Range84
Interquartile range (IQR)20

Descriptive statistics

Standard deviation17.397842
Coefficient of variation (CV)0.96049557
Kurtosis3.5039572
Mean18.113402
Median Absolute Deviation (MAD)6
Skewness1.8381316
Sum1757
Variance302.68492
MonotonicityNot monotonic
2023-12-13T02:44:46.365051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
6 9
 
9.3%
7 7
 
7.2%
15 7
 
7.2%
5 6
 
6.2%
1 6
 
6.2%
14 4
 
4.1%
28 4
 
4.1%
12 4
 
4.1%
11 4
 
4.1%
10 4
 
4.1%
Other values (30) 42
43.3%
ValueCountFrequency (%)
1 6
6.2%
2 2
 
2.1%
3 2
 
2.1%
4 1
 
1.0%
5 6
6.2%
6 9
9.3%
7 7
7.2%
8 2
 
2.1%
9 2
 
2.1%
10 4
4.1%
ValueCountFrequency (%)
85 1
1.0%
80 1
1.0%
65 1
1.0%
63 2
2.1%
58 1
1.0%
50 1
1.0%
47 1
1.0%
45 1
1.0%
40 1
1.0%
38 1
1.0%

전화번호
Text

UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-12-13T02:44:46.584207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1164
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)100.0%

Sample

1st row055-749-5352
2nd row055-749-5353
3rd row055-749-5354
4th row055-749-5355
5th row055-749-5356
ValueCountFrequency (%)
055-749-5352 1
 
1.0%
055-749-5401 1
 
1.0%
055-749-5423 1
 
1.0%
055-749-5422 1
 
1.0%
055-749-5421 1
 
1.0%
055-749-5420 1
 
1.0%
055-749-5419 1
 
1.0%
055-749-5418 1
 
1.0%
055-749-5417 1
 
1.0%
055-749-5416 1
 
1.0%
Other values (87) 87
89.7%
2023-12-13T02:44:46.949083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 309
26.5%
- 194
16.7%
4 165
14.2%
7 117
 
10.1%
0 116
 
10.0%
9 116
 
10.0%
3 68
 
5.8%
2 20
 
1.7%
6 20
 
1.7%
8 20
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 970
83.3%
Dash Punctuation 194
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 309
31.9%
4 165
17.0%
7 117
 
12.1%
0 116
 
12.0%
9 116
 
12.0%
3 68
 
7.0%
2 20
 
2.1%
6 20
 
2.1%
8 20
 
2.1%
1 19
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 194
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1164
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 309
26.5%
- 194
16.7%
4 165
14.2%
7 117
 
10.1%
0 116
 
10.0%
9 116
 
10.0%
3 68
 
5.8%
2 20
 
1.7%
6 20
 
1.7%
8 20
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 309
26.5%
- 194
16.7%
4 165
14.2%
7 117
 
10.1%
0 116
 
10.0%
9 116
 
10.0%
3 68
 
5.8%
2 20
 
1.7%
6 20
 
1.7%
8 20
 
1.7%

데이터기준일자
Date

UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
Minimum2023-07-13 00:00:00
Maximum2023-10-17 00:00:00
2023-12-13T02:44:47.086758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:44:47.200736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Sample

대장번호기관명관리부서임도명시도시군구읍면리동번지사업별조성연도거리(km)폭(m)시점(X좌표)시점(Y좌표)종점(X좌표)종점(Y좌표)산주수유역면적(ha)전화번호데이터기준일자
0경남-진주-1985-1경상남도 진주시청산림과진주시 진성면 동산리경남진주진성동산산95간선19851.04.0128309288542128164288109520055-749-53522023-07-13
1경남-진주-1987-1경상남도 진주시청산림과진주시 미천면 향양리~오방경남진주미천향양산124간선19871.04.01186572996231191143003011015055-749-53532023-07-14
2경남-진주-1988-1경상남도 진주시청산림과진주시 진성면 구천리~대사리경남진주진성구천산201간선19881.54.013091428367613147128372010215055-749-53542023-07-15
3경남-진주-1988-2경상남도 진주시청산림과진주시 미천면 오방리경남진주미천오방산186간선19880.524.0119506300562119114300301526055-749-53552023-07-16
4경남-진주-1989-1경상남도 진주시청산림과진주시 명석면 신기리 ~ 외율리경남진주명석신기164간선19892.284.01097712997531108882999698950055-749-53562023-07-17
5경남-진주-1990-1경상남도 진주시청산림과진주시 미천면 어옥리 ~ 덕진경남진주미천어옥산200간선19901.784.01214153006301222873003062510055-749-53572023-07-18
6경남-진주-1990-2경상남도 진주시청산림과진주시 집현면 정평 임도경남진주집현정평865간선19902.244.01144263005261144883013943080055-749-53582023-07-19
7경남-진주-1991-1경상남도 진주시청산림과진주시 정촌면 관봉리~금곡면 인담리경남진주정촌관봉산152간선19912.324.01234362803481233722808945116055-749-53592023-07-20
8경남-진주-1991-2경상남도 진주시청산림과진주시 금곡면 검암임도경남진주금곡검암114간선19910.344.0126454278970126939279336108055-749-53602023-07-21
9경남-진주-1991-3경상남도 진주시청산림과진주시 지수면 청원리경남진주지수청원산26간선19911.044.01361332928781360782930583314055-749-53612023-07-22
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