Overview

Dataset statistics

Number of variables7
Number of observations90
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory60.5 B

Variable types

Text2
Numeric2
Categorical3

Dataset

Description경기도 파주시 "스마트교차로"에 대한 데이터로, 스마트교차로명, 소재주주소, 위도, 경도, 설치연도 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15101659/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
스마트 교차로명 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:26:38.731398
Analysis finished2023-12-12 18:26:40.253665
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

스마트 교차로명
Text

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-13T03:26:40.431406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.3222222
Min length5

Characters and Unicode

Total characters659
Distinct characters147
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)100.0%

Sample

1st row산내마을3단지
2nd row한빛지하차도상부교차로
3rd row금촌사거리
4th row운정이마트앞사거리
5th row아동교차로
ValueCountFrequency (%)
산내마을3단지 1
 
1.1%
산내10단지사거리 1
 
1.1%
해솔2단지사거리 1
 
1.1%
해솔2단지삼거리 1
 
1.1%
해솔3,6단지사거리 1
 
1.1%
가월교차로 1
 
1.1%
청암초삼거리 1
 
1.1%
산남ic교차로 1
 
1.1%
청석교차로 1
 
1.1%
해오름2,13단지사거리 1
 
1.1%
Other values (81) 81
89.0%
2023-12-13T03:26:40.767076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 52
 
7.9%
거 50
 
7.6%
교 45
 
6.8%
사 38
 
5.8%
차 34
 
5.2%
로 34
 
5.2%
지 24
 
3.6%
1 14
 
2.1%
단 14
 
2.1%
삼 13
 
2.0%
Other values (137) 341
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 603
91.5%
Decimal Number 35
 
5.3%
Uppercase Letter 15
 
2.3%
Other Punctuation 5
 
0.8%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 52
 
8.6%
거 50
 
8.3%
교 45
 
7.5%
사 38
 
6.3%
차 34
 
5.6%
로 34
 
5.6%
지 24
 
4.0%
단 14
 
2.3%
삼 13
 
2.2%
산 13
 
2.2%
Other values (119) 286
47.4%
Decimal Number
ValueCountFrequency (%)
1 14
40.0%
3 6
17.1%
2 5
 
14.3%
4 3
 
8.6%
6 2
 
5.7%
8 1
 
2.9%
7 1
 
2.9%
9 1
 
2.9%
0 1
 
2.9%
5 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
C 5
33.3%
I 4
26.7%
G 2
 
13.3%
L 2
 
13.3%
D 1
 
6.7%
S 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 603
91.5%
Common 41
 
6.2%
Latin 15
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 52
 
8.6%
거 50
 
8.3%
교 45
 
7.5%
사 38
 
6.3%
차 34
 
5.6%
로 34
 
5.6%
지 24
 
4.0%
단 14
 
2.3%
삼 13
 
2.2%
산 13
 
2.2%
Other values (119) 286
47.4%
Common
ValueCountFrequency (%)
1 14
34.1%
3 6
14.6%
2 5
 
12.2%
, 5
 
12.2%
4 3
 
7.3%
6 2
 
4.9%
8 1
 
2.4%
7 1
 
2.4%
9 1
 
2.4%
0 1
 
2.4%
Other values (2) 2
 
4.9%
Latin
ValueCountFrequency (%)
C 5
33.3%
I 4
26.7%
G 2
 
13.3%
L 2
 
13.3%
D 1
 
6.7%
S 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 603
91.5%
ASCII 56
 
8.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 52
 
8.6%
거 50
 
8.3%
교 45
 
7.5%
사 38
 
6.3%
차 34
 
5.6%
로 34
 
5.6%
지 24
 
4.0%
단 14
 
2.3%
삼 13
 
2.2%
산 13
 
2.2%
Other values (119) 286
47.4%
ASCII
ValueCountFrequency (%)
1 14
25.0%
3 6
10.7%
2 5
 
8.9%
, 5
 
8.9%
C 5
 
8.9%
I 4
 
7.1%
4 3
 
5.4%
G 2
 
3.6%
L 2
 
3.6%
6 2
 
3.6%
Other values (8) 8
14.3%

소재지주소
Text

Distinct77
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-13T03:26:41.079182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length17.444444
Min length15

Characters and Unicode

Total characters1570
Distinct characters69
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

Unique68 ?
Unique (%)75.6%

Sample

1st row경기도 파주시 목동동 949-1
2nd row경기도 파주시 야당동 1037
3rd row경기도 파주시 금촌동 457-2
4th row경기도 파주시 야당동 1020
5th row경기도 파주시 금촌동 466-58
ValueCountFrequency (%)
파주시 91
24.1%
경기도 90
23.9%
목동동 13
 
3.4%
금촌동 11
 
2.9%
동패동 11
 
2.9%
야당동 9
 
2.4%
와동동 6
 
1.6%
1020 5
 
1.3%
적성면 4
 
1.1%
상지석동 4
 
1.1%
Other values (104) 133
35.3%
2023-12-13T03:26:41.527925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
288
18.3%
동 105
 
6.7%
시 91
 
5.8%
파 91
 
5.8%
주 91
 
5.8%
기 90
 
5.7%
경 90
 
5.7%
도 90
 
5.7%
1 74
 
4.7%
- 55
 
3.5%
Other values (59) 505
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 867
55.2%
Decimal Number 360
22.9%
Space Separator 288
 
18.3%
Dash Punctuation 55
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 105
12.1%
시 91
10.5%
파 91
10.5%
주 91
10.5%
기 90
10.4%
경 90
10.4%
도 90
10.4%
리 23
 
2.7%
금 14
 
1.6%
목 13
 
1.5%
Other values (47) 169
19.5%
Decimal Number
ValueCountFrequency (%)
1 74
20.6%
3 42
11.7%
2 39
10.8%
9 33
9.2%
6 32
8.9%
0 31
8.6%
5 30
8.3%
4 30
8.3%
7 27
 
7.5%
8 22
 
6.1%
Space Separator
ValueCountFrequency (%)
288
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 867
55.2%
Common 703
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 105
12.1%
시 91
10.5%
파 91
10.5%
주 91
10.5%
기 90
10.4%
경 90
10.4%
도 90
10.4%
리 23
 
2.7%
금 14
 
1.6%
목 13
 
1.5%
Other values (47) 169
19.5%
Common
ValueCountFrequency (%)
288
41.0%
1 74
 
10.5%
- 55
 
7.8%
3 42
 
6.0%
2 39
 
5.5%
9 33
 
4.7%
6 32
 
4.6%
0 31
 
4.4%
5 30
 
4.3%
4 30
 
4.3%
Other values (2) 49
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 867
55.2%
ASCII 703
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
288
41.0%
1 74
 
10.5%
- 55
 
7.8%
3 42
 
6.0%
2 39
 
5.5%
9 33
 
4.7%
6 32
 
4.6%
0 31
 
4.4%
5 30
 
4.3%
4 30
 
4.3%
Other values (2) 49
 
7.0%
Hangul
ValueCountFrequency (%)
동 105
12.1%
시 91
10.5%
파 91
10.5%
주 91
10.5%
기 90
10.4%
경 90
10.4%
도 90
10.4%
리 23
 
2.7%
금 14
 
1.6%
목 13
 
1.5%
Other values (47) 169
19.5%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.754215
Minimum37.696652
Maximum37.997455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T03:26:41.681486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.696652
5-th percentile37.708174
Q137.721507
median37.73145
Q337.763218
95-th percentile37.863056
Maximum37.997455
Range0.300803
Interquartile range (IQR)0.0417115

Descriptive statistics

Standard deviation0.059305905
Coefficient of variation (CV)0.001570842
Kurtosis6.32488
Mean37.754215
Median Absolute Deviation (MAD)0.0190238
Skewness2.4457531
Sum3397.8793
Variance0.0035171904
MonotonicityNot monotonic
2023-12-13T03:26:41.824203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.72718 1
 
1.1%
37.719854 1
 
1.1%
37.724009 1
 
1.1%
37.724762 1
 
1.1%
37.724714 1
 
1.1%
37.723869 1
 
1.1%
37.980829 1
 
1.1%
37.73058 1
 
1.1%
37.696652 1
 
1.1%
37.740685 1
 
1.1%
Other values (80) 80
88.9%
ValueCountFrequency (%)
37.696652 1
1.1%
37.705157 1
1.1%
37.705823 1
1.1%
37.706954 1
1.1%
37.707044 1
1.1%
37.709555 1
1.1%
37.709962 1
1.1%
37.710067 1
1.1%
37.710098 1
1.1%
37.711335 1
1.1%
ValueCountFrequency (%)
37.997455 1
1.1%
37.980829 1
1.1%
37.96744 1
1.1%
37.922743 1
1.1%
37.863769 1
1.1%
37.862185 1
1.1%
37.86042 1
1.1%
37.849493 1
1.1%
37.837927 1
1.1%
37.828278 1
1.1%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.76562
Minimum126.7036
Maximum126.98462
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T03:26:41.968577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.7036
5-th percentile126.71432
Q1126.73724
median126.75644
Q3126.7772
95-th percentile126.87305
Maximum126.98462
Range0.281016
Interquartile range (IQR)0.0399605

Descriptive statistics

Standard deviation0.04814929
Coefficient of variation (CV)0.00037982925
Kurtosis7.5852323
Mean126.76562
Median Absolute Deviation (MAD)0.019619
Skewness2.4790519
Sum11408.906
Variance0.0023183541
MonotonicityNot monotonic
2023-12-13T03:26:42.121459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.733812 1
 
1.1%
126.736822 1
 
1.1%
126.739763 1
 
1.1%
126.742805 1
 
1.1%
126.744194 1
 
1.1%
126.74778 1
 
1.1%
126.917827 1
 
1.1%
126.73682 1
 
1.1%
126.703603 1
 
1.1%
126.724177 1
 
1.1%
Other values (80) 80
88.9%
ValueCountFrequency (%)
126.703603 1
1.1%
126.706869 1
1.1%
126.710942 1
1.1%
126.711556 1
1.1%
126.711583 1
1.1%
126.71766 1
1.1%
126.722869 1
1.1%
126.724025 1
1.1%
126.724177 1
1.1%
126.726958 1
1.1%
ValueCountFrequency (%)
126.984619 1
1.1%
126.952763 1
1.1%
126.917827 1
1.1%
126.898756 1
1.1%
126.888572 1
1.1%
126.854083 1
1.1%
126.830842 1
1.1%
126.804019 1
1.1%
126.802626 1
1.1%
126.797849 1
1.1%

설치연도
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
2022
62 
2021
28 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2022 62
68.9%
2021 28
31.1%

Length

2023-12-13T03:26:42.253329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:26:42.350802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 62
68.9%
2021 28
31.1%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
경기도 파주시청
90 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 파주시청
2nd row경기도 파주시청
3rd row경기도 파주시청
4th row경기도 파주시청
5th row경기도 파주시청

Common Values

ValueCountFrequency (%)
경기도 파주시청 90
100.0%

Length

2023-12-13T03:26:42.460612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:26:42.565628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 90
50.0%
파주시청 90
50.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-08-14
90 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-14
2nd row2023-08-14
3rd row2023-08-14
4th row2023-08-14
5th row2023-08-14

Common Values

ValueCountFrequency (%)
2023-08-14 90
100.0%

Length

2023-12-13T03:26:42.675367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:26:42.785039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-14 90
100.0%

Interactions

2023-12-13T03:26:39.373962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:26:39.125977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:26:39.489125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:26:39.245283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:26:42.859607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
스마트 교차로명소재지주소위도경도설치연도
스마트 교차로명1.0001.0001.0001.0001.000
소재지주소1.0001.0000.9990.9990.750
위도1.0000.9991.0000.7850.159
경도1.0000.9990.7851.0000.000
설치연도1.0000.7500.1590.0001.000
2023-12-13T03:26:42.958887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설치연도
위도1.0000.5580.111
경도0.5581.0000.000
설치연도0.1110.0001.000

Missing values

2023-12-13T03:26:40.048059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:26:40.190235image/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

스마트 교차로명소재지주소위도경도설치연도관리기관명데이터기준일
0산내마을3단지경기도 파주시 목동동 949-137.72718126.7338122021경기도 파주시청2023-08-14
1한빛지하차도상부교차로경기도 파주시 야당동 103737.706954126.759252021경기도 파주시청2023-08-14
2금촌사거리경기도 파주시 금촌동 457-237.765644126.7687282021경기도 파주시청2023-08-14
3운정이마트앞사거리경기도 파주시 야당동 102037.712408126.7463742021경기도 파주시청2023-08-14
4아동교차로경기도 파주시 금촌동 466-5837.763716126.765632021경기도 파주시청2023-08-14
5파주스타디움앞교차로경기도 파주시 금릉동 216-337.754449126.7831312021경기도 파주시청2023-08-14
6문산제일고삼거리경기도 파주시 야동동 935-237.769899126.7627972021경기도 파주시청2023-08-14
7갈현사거리경기도 파주시 탄현면 갈현리 1783-937.771619126.7240252021경기도 파주시청2023-08-14
8와동교차로경기도 파주시 당하동 37237.741893126.7527742021경기도 파주시청2023-08-14
9벧엘교회앞교차로경기도 파주시 와동동 155537.735168126.7588292021경기도 파주시청2023-08-14
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