Overview

Dataset statistics

Number of variables7
Number of observations197
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.5 KiB
Average record size in memory59.7 B

Variable types

Numeric1
Categorical4
Text1
DateTime1

Dataset

Description서울특별시 노원구에 설치된 LED바닥횡단보도 및 음성안내횡된보도에 대한 데이터로 연번, 구분, 시군구명, 위치명, 설치개소, 설치년도, 기준일자로 구성되어있다.
Author서울특별시 노원구
URLhttps://www.data.go.kr/data/15125390/fileData.do

Alerts

시군구명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
구분 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
개소 is highly overall correlated with 구분High correlation
설치년도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:22:04.105333
Analysis finished2023-12-12 21:22:04.712098
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct197
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99
Minimum1
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-13T06:22:04.790868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.8
Q150
median99
Q3148
95-th percentile187.2
Maximum197
Range196
Interquartile range (IQR)98

Descriptive statistics

Standard deviation57.013156
Coefficient of variation (CV)0.57589047
Kurtosis-1.2
Mean99
Median Absolute Deviation (MAD)49
Skewness0
Sum19503
Variance3250.5
MonotonicityStrictly increasing
2023-12-13T06:22:04.944652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
125 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
Other values (187) 187
94.9%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
음성안내시설물
108 
LED바닥신호등
89 

Length

Max length8
Median length7
Mean length7.4517766
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
음성안내시설물 108
54.8%
LED바닥신호등 89
45.2%

Length

2023-12-13T06:22:05.096263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:22:05.219618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음성안내시설물 108
54.8%
led바닥신호등 89
45.2%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
서울특별시 노원구
197 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 노원구
2nd row서울특별시 노원구
3rd row서울특별시 노원구
4th row서울특별시 노원구
5th row서울특별시 노원구

Common Values

ValueCountFrequency (%)
서울특별시 노원구 197
100.0%

Length

2023-12-13T06:22:05.343439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:22:05.453394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 197
50.0%
노원구 197
50.0%
Distinct180
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-13T06:22:05.695348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length8.6192893
Min length4

Characters and Unicode

Total characters1698
Distinct characters190
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)82.7%

Sample

1st row은행사거리 교차로
2nd row육사삼거리 앞
3rd row수락산역 교차로
4th row연지초등학교
5th row공연초등학교
ValueCountFrequency (%)
81
 
21.0%
교차로 43
 
11.2%
사거리 13
 
3.4%
후문 5
 
1.3%
삼거리 4
 
1.0%
하계역 3
 
0.8%
공릉 3
 
0.8%
공릉초등학교 3
 
0.8%
원광초등학교 3
 
0.8%
용원초등학교 3
 
0.8%
Other values (181) 224
58.2%
2023-12-13T06:22:06.138140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
193
 
11.4%
150
 
8.8%
101
 
5.9%
94
 
5.5%
71
 
4.2%
62
 
3.7%
51
 
3.0%
49
 
2.9%
48
 
2.8%
41
 
2.4%
Other values (180) 838
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1433
84.4%
Space Separator 193
 
11.4%
Decimal Number 32
 
1.9%
Open Punctuation 16
 
0.9%
Close Punctuation 16
 
0.9%
Other Punctuation 6
 
0.4%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
150
 
10.5%
101
 
7.0%
94
 
6.6%
71
 
5.0%
62
 
4.3%
51
 
3.6%
49
 
3.4%
48
 
3.3%
41
 
2.9%
27
 
1.9%
Other values (168) 739
51.6%
Decimal Number
ValueCountFrequency (%)
1 11
34.4%
6 7
21.9%
3 4
 
12.5%
7 3
 
9.4%
5 3
 
9.4%
4 2
 
6.2%
2 2
 
6.2%
Space Separator
ValueCountFrequency (%)
193
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1433
84.4%
Common 265
 
15.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
150
 
10.5%
101
 
7.0%
94
 
6.6%
71
 
5.0%
62
 
4.3%
51
 
3.6%
49
 
3.4%
48
 
3.3%
41
 
2.9%
27
 
1.9%
Other values (168) 739
51.6%
Common
ValueCountFrequency (%)
193
72.8%
( 16
 
6.0%
) 16
 
6.0%
1 11
 
4.2%
6 7
 
2.6%
, 6
 
2.3%
3 4
 
1.5%
7 3
 
1.1%
5 3
 
1.1%
- 2
 
0.8%
Other values (2) 4
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1433
84.4%
ASCII 265
 
15.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
193
72.8%
( 16
 
6.0%
) 16
 
6.0%
1 11
 
4.2%
6 7
 
2.6%
, 6
 
2.3%
3 4
 
1.5%
7 3
 
1.1%
5 3
 
1.1%
- 2
 
0.8%
Other values (2) 4
 
1.5%
Hangul
ValueCountFrequency (%)
150
 
10.5%
101
 
7.0%
94
 
6.6%
71
 
5.0%
62
 
4.3%
51
 
3.6%
49
 
3.4%
48
 
3.3%
41
 
2.9%
27
 
1.9%
Other values (168) 739
51.6%

개소
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
108 
1
40 
4
20 
3
14 
2
13 

Length

Max length4
Median length4
Mean length2.6446701
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row1
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 108
54.8%
1 40
 
20.3%
4 20
 
10.2%
3 14
 
7.1%
2 13
 
6.6%
6 2
 
1.0%

Length

2023-12-13T06:22:06.283782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:22:06.424351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 108
54.8%
1 40
 
20.3%
4 20
 
10.2%
3 14
 
7.1%
2 13
 
6.6%
6 2
 
1.0%

설치년도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
108 
2022
37 
2021
35 
2023
15 
2020
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
<NA> 108
54.8%
2022 37
 
18.8%
2021 35
 
17.8%
2023 15
 
7.6%
2020 2
 
1.0%

Length

2023-12-13T06:22:06.549446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:22:06.685535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 108
54.8%
2022 37
 
18.8%
2021 35
 
17.8%
2023 15
 
7.6%
2020 2
 
1.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2023-12-06 00:00:00
Maximum2023-12-06 00:00:00
2023-12-13T06:22:06.815003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:22:06.910495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T06:22:04.397037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:22:06.983535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분개소설치년도
연번1.0000.9970.5340.757
구분0.9971.000NaNNaN
개소0.534NaN1.0000.352
설치년도0.757NaN0.3521.000
2023-12-13T06:22:07.095516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분개소설치년도
구분1.0001.0001.000
개소1.0001.0000.292
설치년도1.0000.2921.000
2023-12-13T06:22:07.197780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분개소설치년도
연번1.0000.9250.2230.700
구분0.9251.0001.0001.000
개소0.2231.0001.0000.292
설치년도0.7001.0000.2921.000

Missing values

2023-12-13T06:22:04.533245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:22:04.658762image/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

연번구분시군구명위치명개소설치년도데이터기준일자
01LED바닥신호등서울특별시 노원구은행사거리 교차로420202023-12-06
12LED바닥신호등서울특별시 노원구육사삼거리 앞120202023-12-06
23LED바닥신호등서울특별시 노원구수락산역 교차로320212023-12-06
34LED바닥신호등서울특별시 노원구연지초등학교120212023-12-06
45LED바닥신호등서울특별시 노원구공연초등학교120212023-12-06
56LED바닥신호등서울특별시 노원구중계역 교차로420212023-12-06
67LED바닥신호등서울특별시 노원구공릉초등학교120212023-12-06
78LED바닥신호등서울특별시 노원구15단지 교차로420212023-12-06
89LED바닥신호등서울특별시 노원구상계역 교차로420212023-12-06
910LED바닥신호등서울특별시 노원구공릉 우성아파트 앞 (공릉동 성당)120212023-12-06
연번구분시군구명위치명개소설치년도데이터기준일자
187188음성안내시설물서울특별시 노원구태랑초등학교 앞<NA><NA>2023-12-06
188189음성안내시설물서울특별시 노원구연촌초등학교 앞<NA><NA>2023-12-06
189190음성안내시설물서울특별시 노원구수락산역 교차로<NA><NA>2023-12-06
190191음성안내시설물서울특별시 노원구하계역 교차로<NA><NA>2023-12-06
191192음성안내시설물서울특별시 노원구서울과기대 삼거리<NA><NA>2023-12-06
192193음성안내시설물서울특별시 노원구공릉역 교차로<NA><NA>2023-12-06
193194음성안내시설물서울특별시 노원구하계5,6단지 교차로<NA><NA>2023-12-06
194195음성안내시설물서울특별시 노원구당고개 데이케어센터<NA><NA>2023-12-06
195196음성안내시설물서울특별시 노원구상계6,7동 주민센터<NA><NA>2023-12-06
196197음성안내시설물서울특별시 노원구상계2,6단지 교차로<NA><NA>2023-12-06