Overview

Dataset statistics

Number of variables19
Number of observations380
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory58.8 KiB
Average record size in memory158.3 B

Variable types

Numeric3
Text3
Categorical9
Boolean3
DateTime1

Dataset

Description광주시 과속방지턱 정보로 과속방지턱관리번호, 도로명, 설치장소, 과속방지턱재료, 과속방지턱형태구분 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15091507/fileData.do

Alerts

설치장소 has constant value ""Constant
과속방지턱재료 has constant value ""Constant
과속방지턱연장 has constant value ""Constant
규격여부 has constant value ""Constant
관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
과속방지턱높이 is highly overall correlated with 과속방지턱폭 and 1 other fieldsHigh correlation
과속방지턱폭 is highly overall correlated with 과속방지턱높이 and 1 other fieldsHigh correlation
도로유형구분 is highly overall correlated with 과속방지턱높이 and 1 other fieldsHigh correlation
과속방지턱형태구분 is highly imbalanced (76.0%)Imbalance
과속방지턱높이 is highly imbalanced (67.0%)Imbalance
과속방지턱폭 is highly imbalanced (67.0%)Imbalance
도로유형구분 is highly imbalanced (68.1%)Imbalance
과속방지턱관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:48:13.194378
Analysis finished2023-12-12 04:48:15.804499
Duration2.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

과속방지턱관리번호
Real number (ℝ)

UNIQUE 

Distinct380
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean190.91579
Minimum1
Maximum381
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T13:48:15.910483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.95
Q195.75
median190.5
Q3286.25
95-th percentile362.05
Maximum381
Range380
Interquartile range (IQR)190.5

Descriptive statistics

Standard deviation110.26238
Coefficient of variation (CV)0.57754458
Kurtosis-1.203992
Mean190.91579
Median Absolute Deviation (MAD)95.5
Skewness0.0022384721
Sum72548
Variance12157.792
MonotonicityStrictly increasing
2023-12-12T13:48:16.121466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
253 1
 
0.3%
262 1
 
0.3%
261 1
 
0.3%
260 1
 
0.3%
259 1
 
0.3%
258 1
 
0.3%
257 1
 
0.3%
256 1
 
0.3%
255 1
 
0.3%
Other values (370) 370
97.4%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
381 1
0.3%
380 1
0.3%
379 1
0.3%
378 1
0.3%
377 1
0.3%
376 1
0.3%
375 1
0.3%
374 1
0.3%
373 1
0.3%
372 1
0.3%

도로명
Text

Distinct101
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T13:48:16.457380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.1263158
Min length3

Characters and Unicode

Total characters1568
Distinct characters108
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

Unique50 ?
Unique (%)13.2%

Sample

1st row양벌로
2nd row양벌로
3rd row청석로
4th row오포로
5th row오포로
ValueCountFrequency (%)
신만로 27
 
7.0%
이배재로 25
 
6.5%
해공로 21
 
5.4%
도척윗로 20
 
5.2%
천진암로 18
 
4.7%
현산로 17
 
4.4%
경충대로 17
 
4.4%
곤지암천로 12
 
3.1%
무들로 11
 
2.8%
봉골길 10
 
2.6%
Other values (83) 208
53.9%
2023-12-12T13:48:16.915561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 276
 
17.6%
길 150
 
9.6%
번 46
 
2.9%
암 42
 
2.7%
37
 
2.4%
도 33
 
2.1%
천 33
 
2.1%
대 32
 
2.0%
경 30
 
1.9%
1 30
 
1.9%
Other values (98) 859
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1403
89.5%
Decimal Number 128
 
8.2%
Space Separator 37
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 276
 
19.7%
길 150
 
10.7%
번 46
 
3.3%
암 42
 
3.0%
도 33
 
2.4%
천 33
 
2.4%
대 32
 
2.3%
경 30
 
2.1%
신 30
 
2.1%
이 29
 
2.1%
Other values (87) 702
50.0%
Decimal Number
ValueCountFrequency (%)
1 30
23.4%
2 19
14.8%
7 17
13.3%
4 13
10.2%
8 12
 
9.4%
0 10
 
7.8%
5 9
 
7.0%
6 7
 
5.5%
9 6
 
4.7%
3 5
 
3.9%
Space Separator
ValueCountFrequency (%)
37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1403
89.5%
Common 165
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 276
 
19.7%
길 150
 
10.7%
번 46
 
3.3%
암 42
 
3.0%
도 33
 
2.4%
천 33
 
2.4%
대 32
 
2.3%
경 30
 
2.1%
신 30
 
2.1%
이 29
 
2.1%
Other values (87) 702
50.0%
Common
ValueCountFrequency (%)
37
22.4%
1 30
18.2%
2 19
11.5%
7 17
10.3%
4 13
 
7.9%
8 12
 
7.3%
0 10
 
6.1%
5 9
 
5.5%
6 7
 
4.2%
9 6
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1403
89.5%
ASCII 165
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 276
 
19.7%
길 150
 
10.7%
번 46
 
3.3%
암 42
 
3.0%
도 33
 
2.4%
천 33
 
2.4%
대 32
 
2.3%
경 30
 
2.1%
신 30
 
2.1%
이 29
 
2.1%
Other values (87) 702
50.0%
ASCII
ValueCountFrequency (%)
37
22.4%
1 30
18.2%
2 19
11.5%
7 17
10.3%
4 13
 
7.9%
8 12
 
7.3%
0 10
 
6.1%
5 9
 
5.5%
6 7
 
4.2%
9 6
 
3.6%

소재지도로명주소
Text

Distinct345
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T13:48:17.179809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length16.131579
Min length13

Characters and Unicode

Total characters6130
Distinct characters111
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique319 ?
Unique (%)83.9%

Sample

1st row경기도 광주시 양벌로 307
2nd row경기도 광주시 양벌로 301
3rd row경기도 광주시 청석로 149
4th row경기도 광주시 오포로 914
5th row경기도 광주시 오포로 898
ValueCountFrequency (%)
경기도 380
24.9%
광주시 380
24.9%
신만로 27
 
1.8%
이배재로 25
 
1.6%
해공로 21
 
1.4%
도척윗로 20
 
1.3%
천진암로 18
 
1.2%
경충대로 17
 
1.1%
현산로 17
 
1.1%
곤지암천로 12
 
0.8%
Other values (354) 610
39.9%
2023-12-12T13:48:17.597775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1178
19.2%
도 413
 
6.7%
경 410
 
6.7%
광 385
 
6.3%
주 383
 
6.2%
시 381
 
6.2%
기 380
 
6.2%
로 276
 
4.5%
1 240
 
3.9%
길 151
 
2.5%
Other values (101) 1933
31.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3685
60.1%
Space Separator 1178
 
19.2%
Decimal Number 1170
 
19.1%
Dash Punctuation 51
 
0.8%
Other Punctuation 46
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 413
11.2%
경 410
11.1%
광 385
10.4%
주 383
10.4%
시 381
10.3%
기 380
10.3%
로 276
 
7.5%
길 151
 
4.1%
번 47
 
1.3%
암 42
 
1.1%
Other values (88) 817
22.2%
Decimal Number
ValueCountFrequency (%)
1 240
20.5%
2 138
11.8%
3 120
10.3%
5 111
9.5%
7 106
9.1%
4 101
8.6%
8 92
 
7.9%
9 90
 
7.7%
6 88
 
7.5%
0 84
 
7.2%
Space Separator
ValueCountFrequency (%)
1178
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Other Punctuation
ValueCountFrequency (%)
. 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3685
60.1%
Common 2445
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 413
11.2%
경 410
11.1%
광 385
10.4%
주 383
10.4%
시 381
10.3%
기 380
10.3%
로 276
 
7.5%
길 151
 
4.1%
번 47
 
1.3%
암 42
 
1.1%
Other values (88) 817
22.2%
Common
ValueCountFrequency (%)
1178
48.2%
1 240
 
9.8%
2 138
 
5.6%
3 120
 
4.9%
5 111
 
4.5%
7 106
 
4.3%
4 101
 
4.1%
8 92
 
3.8%
9 90
 
3.7%
6 88
 
3.6%
Other values (3) 181
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3685
60.1%
ASCII 2445
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1178
48.2%
1 240
 
9.8%
2 138
 
5.6%
3 120
 
4.9%
5 111
 
4.5%
7 106
 
4.3%
4 101
 
4.1%
8 92
 
3.8%
9 90
 
3.7%
6 88
 
3.6%
Other values (3) 181
 
7.4%
Hangul
ValueCountFrequency (%)
도 413
11.2%
경 410
11.1%
광 385
10.4%
주 383
10.4%
시 381
10.3%
기 380
10.3%
로 276
 
7.5%
길 151
 
4.1%
번 47
 
1.3%
암 42
 
1.1%
Other values (88) 817
22.2%

소재지지번주소
Text

Distinct360
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T13:48:17.999135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length19.973684
Min length14

Characters and Unicode

Total characters7590
Distinct characters98
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

Unique341 ?
Unique (%)89.7%

Sample

1st row경기도 광주시 양벌동 607-2
2nd row경기도 광주시 양벌동 562-2
3rd row경기도 광주시 양벌동 산54-2
4th row경기도 광주시 고산동 180-2
5th row경기도 광주시 고산동 242-2
ValueCountFrequency (%)
경기도 380
22.1%
광주시 380
22.1%
초월읍 80
 
4.7%
곤지암읍 55
 
3.2%
도척면 30
 
1.7%
퇴촌면 27
 
1.6%
남한산성면 25
 
1.5%
목현동 21
 
1.2%
쌍동리 19
 
1.1%
양벌동 17
 
1.0%
Other values (399) 685
39.8%
2023-12-12T13:48:18.520733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1410
18.6%
도 437
 
5.8%
경 388
 
5.1%
광 380
 
5.0%
주 380
 
5.0%
시 380
 
5.0%
기 380
 
5.0%
- 354
 
4.7%
1 291
 
3.8%
2 266
 
3.5%
Other values (88) 2924
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4242
55.9%
Decimal Number 1555
 
20.5%
Space Separator 1410
 
18.6%
Dash Punctuation 354
 
4.7%
Close Punctuation 14
 
0.2%
Open Punctuation 14
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 437
 
10.3%
경 388
 
9.1%
광 380
 
9.0%
주 380
 
9.0%
시 380
 
9.0%
기 380
 
9.0%
리 217
 
5.1%
동 188
 
4.4%
읍 135
 
3.2%
월 95
 
2.2%
Other values (73) 1262
29.8%
Decimal Number
ValueCountFrequency (%)
1 291
18.7%
2 266
17.1%
3 209
13.4%
4 139
8.9%
5 131
8.4%
7 129
8.3%
6 112
 
7.2%
0 108
 
6.9%
8 88
 
5.7%
9 82
 
5.3%
Space Separator
ValueCountFrequency (%)
1410
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 354
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4242
55.9%
Common 3348
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 437
 
10.3%
경 388
 
9.1%
광 380
 
9.0%
주 380
 
9.0%
시 380
 
9.0%
기 380
 
9.0%
리 217
 
5.1%
동 188
 
4.4%
읍 135
 
3.2%
월 95
 
2.2%
Other values (73) 1262
29.8%
Common
ValueCountFrequency (%)
1410
42.1%
- 354
 
10.6%
1 291
 
8.7%
2 266
 
7.9%
3 209
 
6.2%
4 139
 
4.2%
5 131
 
3.9%
7 129
 
3.9%
6 112
 
3.3%
0 108
 
3.2%
Other values (5) 199
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4242
55.9%
ASCII 3348
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1410
42.1%
- 354
 
10.6%
1 291
 
8.7%
2 266
 
7.9%
3 209
 
6.2%
4 139
 
4.2%
5 131
 
3.9%
7 129
 
3.9%
6 112
 
3.3%
0 108
 
3.2%
Other values (5) 199
 
5.9%
Hangul
ValueCountFrequency (%)
도 437
 
10.3%
경 388
 
9.1%
광 380
 
9.0%
주 380
 
9.0%
시 380
 
9.0%
기 380
 
9.0%
리 217
 
5.1%
동 188
 
4.4%
읍 135
 
3.2%
월 95
 
2.2%
Other values (73) 1262
29.8%

설치장소
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
도로
380 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도로 380
100.0%

Length

2023-12-12T13:48:18.672829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:18.771498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도로 380
100.0%

과속방지턱재료
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
아스팔트 콘크리트
380 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row아스팔트 콘크리트
2nd row아스팔트 콘크리트
3rd row아스팔트 콘크리트
4th row아스팔트 콘크리트
5th row아스팔트 콘크리트

Common Values

ValueCountFrequency (%)
아스팔트 콘크리트 380
100.0%

Length

2023-12-12T13:48:18.882375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:18.992507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아스팔트 380
50.0%
콘크리트 380
50.0%

과속방지턱형태구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
원호형
365 
기타
 
15

Length

Max length3
Median length3
Mean length2.9605263
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원호형 365
96.1%
기타 15
 
3.9%

Length

2023-12-12T13:48:19.123860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:19.286345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원호형 365
96.1%
기타 15
 
3.9%

과속방지턱높이
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
7.5
357 
10.0
 
23

Length

Max length4
Median length3
Mean length3.0605263
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10.0
2nd row10.0
3rd row7.5
4th row7.5
5th row7.5

Common Values

ValueCountFrequency (%)
7.5 357
93.9%
10.0 23
 
6.1%

Length

2023-12-12T13:48:19.434644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:19.604510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7.5 357
93.9%
10.0 23
 
6.1%

과속방지턱폭
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2.0
357 
3.6
 
23

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.6
2nd row3.6
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 357
93.9%
3.6 23
 
6.1%

Length

2023-12-12T13:48:19.752928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:19.878692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2.0 357
93.9%
3.6 23
 
6.1%

과속방지턱연장
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
6
380 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row6
3rd row6
4th row6
5th row6

Common Values

ValueCountFrequency (%)
6 380
100.0%

Length

2023-12-12T13:48:19.987320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:20.086530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6 380
100.0%

도로유형구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
소로
358 
일반
 
22

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row일반
3rd row소로
4th row소로
5th row소로

Common Values

ValueCountFrequency (%)
소로 358
94.2%
일반 22
 
5.8%

Length

2023-12-12T13:48:20.198190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:20.319553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소로 358
94.2%
일반 22
 
5.8%

규격여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size512.0 B
True
380 
ValueCountFrequency (%)
True 380
100.0%
2023-12-12T13:48:20.413248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위도
Real number (ℝ)

Distinct340
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.389188
Minimum37.301165
Maximum37.475584
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T13:48:20.544582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.301165
5-th percentile37.32972
Q137.357124
median37.383466
Q337.418286
95-th percentile37.454074
Maximum37.475584
Range0.17441939
Interquartile range (IQR)0.061162137

Descriptive statistics

Standard deviation0.040338939
Coefficient of variation (CV)0.0010788932
Kurtosis-0.79231972
Mean37.389188
Median Absolute Deviation (MAD)0.03070176
Skewness0.096014332
Sum14207.891
Variance0.00162723
MonotonicityNot monotonic
2023-12-12T13:48:20.739238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.37221267 4
 
1.1%
37.35465966 4
 
1.1%
37.37754662 3
 
0.8%
37.3572443 3
 
0.8%
37.37114297 3
 
0.8%
37.43282869 3
 
0.8%
37.44602884 3
 
0.8%
37.39373152 2
 
0.5%
37.45557484 2
 
0.5%
37.44651597 2
 
0.5%
Other values (330) 351
92.4%
ValueCountFrequency (%)
37.30116468 1
0.3%
37.30188571 1
0.3%
37.30269622 1
0.3%
37.30289496 1
0.3%
37.30495198 1
0.3%
37.30753557 1
0.3%
37.30754649 1
0.3%
37.30760951 1
0.3%
37.3083198 1
0.3%
37.3091435 1
0.3%
ValueCountFrequency (%)
37.47558407 1
0.3%
37.47494051 1
0.3%
37.47464143 1
0.3%
37.47411768 2
0.5%
37.4727704 1
0.3%
37.47117383 1
0.3%
37.47106389 1
0.3%
37.46867468 1
0.3%
37.46811351 1
0.3%
37.46367349 1
0.3%

경도
Real number (ℝ)

Distinct340
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.28203
Minimum127.15771
Maximum127.42395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T13:48:20.963101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.15771
5-th percentile127.19714
Q1127.24354
median127.2869
Q3127.31884
95-th percentile127.39129
Maximum127.42395
Range0.26624
Interquartile range (IQR)0.07529995

Descriptive statistics

Standard deviation0.057813273
Coefficient of variation (CV)0.00045421395
Kurtosis-0.32351762
Mean127.28203
Median Absolute Deviation (MAD)0.03949155
Skewness0.12101028
Sum48367.171
Variance0.0033423745
MonotonicityNot monotonic
2023-12-12T13:48:21.134711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.2991629 4
 
1.1%
127.3351876 4
 
1.1%
127.2975551 3
 
0.8%
127.330119 3
 
0.8%
127.2996018 3
 
0.8%
127.3083509 3
 
0.8%
127.2663118 3
 
0.8%
127.2902216 2
 
0.5%
127.3356084 2
 
0.5%
127.2678554 2
 
0.5%
Other values (330) 351
92.4%
ValueCountFrequency (%)
127.1577082 1
0.3%
127.1598199 1
0.3%
127.1602161 1
0.3%
127.1604945 1
0.3%
127.1608022 2
0.5%
127.1616485 1
0.3%
127.161732 1
0.3%
127.1618356 1
0.3%
127.1618642 1
0.3%
127.1621731 1
0.3%
ValueCountFrequency (%)
127.4239482 1
0.3%
127.4063066 1
0.3%
127.4047009 2
0.5%
127.403733 1
0.3%
127.4036688 1
0.3%
127.3981473 2
0.5%
127.3981382 2
0.5%
127.3963371 2
0.5%
127.396159 1
0.3%
127.3956497 2
0.5%

보차분리여부
Boolean

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size512.0 B
True
223 
False
157 
ValueCountFrequency (%)
True 223
58.7%
False 157
41.3%
2023-12-12T13:48:21.274728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

연속형여부
Boolean

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size512.0 B
False
219 
True
161 
ValueCountFrequency (%)
False 219
57.6%
True 161
42.4%
2023-12-12T13:48:21.381669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
경기도 광주시청
380 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 광주시청 380
100.0%

Length

2023-12-12T13:48:21.505803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:21.630076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 380
50.0%
광주시청 380
50.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
031-760-4867
380 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-760-4867
2nd row031-760-4867
3rd row031-760-4867
4th row031-760-4867
5th row031-760-4867

Common Values

ValueCountFrequency (%)
031-760-4867 380
100.0%

Length

2023-12-12T13:48:21.756533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:21.871442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-760-4867 380
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2023-05-02 00:00:00
Maximum2023-05-02 00:00:00
2023-12-12T13:48:21.967973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:22.085013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T13:48:14.979560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:13.980434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:14.332233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:15.091549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:14.110582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:14.445877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:15.205805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:14.223958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:14.881824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:48:22.168226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과속방지턱관리번호과속방지턱형태구분과속방지턱높이과속방지턱폭도로유형구분위도경도보차분리여부연속형여부
과속방지턱관리번호1.0000.0700.3080.3080.3220.8950.8960.5880.233
과속방지턱형태구분0.0701.0000.2150.2150.1240.1330.1850.2300.000
과속방지턱높이0.3080.2151.0000.9990.9970.0000.1220.2670.221
과속방지턱폭0.3080.2150.9991.0000.9970.0000.1220.2670.221
도로유형구분0.3220.1240.9970.9971.0000.0140.1200.2580.242
위도0.8950.1330.0000.0000.0141.0000.8020.5530.263
경도0.8960.1850.1220.1220.1200.8021.0000.4640.081
보차분리여부0.5880.2300.2670.2670.2580.5530.4641.0000.000
연속형여부0.2330.0000.2210.2210.2420.2630.0810.0001.000
2023-12-12T13:48:22.302719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과속방지턱높이과속방지턱폭과속방지턱형태구분보차분리여부연속형여부도로유형구분
과속방지턱높이1.0000.9770.1380.1720.1420.953
과속방지턱폭0.9771.0000.1380.1720.1420.953
과속방지턱형태구분0.1380.1381.0000.1480.0000.079
보차분리여부0.1720.1720.1481.0000.0000.166
연속형여부0.1420.1420.0000.0001.0000.156
도로유형구분0.9530.9530.0790.1660.1561.000
2023-12-12T13:48:22.438187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과속방지턱관리번호위도경도과속방지턱형태구분과속방지턱높이과속방지턱폭도로유형구분보차분리여부연속형여부
과속방지턱관리번호1.0000.3560.3950.0480.2300.2300.2410.4500.171
위도0.3561.000-0.1960.1010.0000.0000.0070.4220.199
경도0.395-0.1961.0000.1400.0920.0920.0910.3530.061
과속방지턱형태구분0.0480.1010.1401.0000.1380.1380.0790.1480.000
과속방지턱높이0.2300.0000.0920.1381.0000.9770.9530.1720.142
과속방지턱폭0.2300.0000.0920.1380.9771.0000.9530.1720.142
도로유형구분0.2410.0070.0910.0790.9530.9531.0000.1660.156
보차분리여부0.4500.4220.3530.1480.1720.1720.1661.0000.000
연속형여부0.1710.1990.0610.0000.1420.1420.1560.0001.000

Missing values

2023-12-12T13:48:15.376964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:48:15.697464image/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

과속방지턱관리번호도로명소재지도로명주소소재지지번주소설치장소과속방지턱재료과속방지턱형태구분과속방지턱높이과속방지턱폭과속방지턱연장도로유형구분규격여부위도경도보차분리여부연속형여부관리기관명관리기관전화번호데이터기준일자
01양벌로경기도 광주시 양벌로 307경기도 광주시 양벌동 607-2도로아스팔트 콘크리트원호형10.03.66일반Y37.371679127.247412YN경기도 광주시청031-760-48672023-05-02
12양벌로경기도 광주시 양벌로 301경기도 광주시 양벌동 562-2도로아스팔트 콘크리트원호형10.03.66일반Y37.372131127.247713YY경기도 광주시청031-760-48672023-05-02
23청석로경기도 광주시 청석로 149경기도 광주시 양벌동 산54-2도로아스팔트 콘크리트원호형7.52.06소로Y37.399925127.261181NY경기도 광주시청031-760-48672023-05-02
34오포로경기도 광주시 오포로 914경기도 광주시 고산동 180-2도로아스팔트 콘크리트원호형7.52.06소로Y37.371616127.233289NN경기도 광주시청031-760-48672023-05-02
45오포로경기도 광주시 오포로 898경기도 광주시 고산동 242-2도로아스팔트 콘크리트원호형7.52.06소로Y37.349702127.207381YN경기도 광주시청031-760-48672023-05-02
56오포로경기도 광주시 오포로 880경기도 광주시 고산동 234-2도로아스팔트 콘크리트원호형7.52.06소로Y37.368805127.231962YY경기도 광주시청031-760-48672023-05-02
67고산길경기도 광주시 고산길 55경기도 광주시 고산동 301-12도로아스팔트 콘크리트원호형7.52.06소로Y37.371568127.226041NN경기도 광주시청031-760-48672023-05-02
78오포로경기도 광주시 오포로 632경기도 광주시 문형동 328-7도로아스팔트 콘크리트원호형10.03.66일반Y37.353667127.215591YY경기도 광주시청031-760-48672023-05-02
89오포로경기도 광주시 오포로 609경기도 광주시 문형동 산10-6도로아스팔트 콘크리트원호형10.03.66일반Y37.352584127.213898YY경기도 광주시청031-760-48672023-05-02
910능평로경기도 광주시 능평로 203경기도 광주시 능평동 166-3도로아스팔트 콘크리트원호형7.52.06소로Y37.345047127.177487YN경기도 광주시청031-760-48672023-05-02
과속방지턱관리번호도로명소재지도로명주소소재지지번주소설치장소과속방지턱재료과속방지턱형태구분과속방지턱높이과속방지턱폭과속방지턱연장도로유형구분규격여부위도경도보차분리여부연속형여부관리기관명관리기관전화번호데이터기준일자
370372신만로경기도 광주시 신만로 59경기도 광주시 곤지암읍 수양리 46-7도로아스팔트 콘크리트원호형7.52.06소로Y37.333499127.389925NY경기도 광주시청031-760-48672023-05-02
371373신만로경기도 광주시 신만로 85경기도 광주시 곤지암읍 수양리 30-4도로아스팔트 콘크리트원호형7.52.06소로Y37.335706127.389873NN경기도 광주시청031-760-48672023-05-02
372374평촌길경기도 광주시 평촌길 12-27.경기도 광주시 곤지암읍 삼리 126-1도로아스팔트 콘크리트원호형7.52.06소로Y37.357561127.327238YN경기도 광주시청031-760-48672023-05-02
373375신만로경기도 광주시 신만로 395경기도 광주시 곤지암읍 부향리 325-3도로아스팔트 콘크리트원호형7.52.06소로Y37.360907127.398147NY경기도 광주시청031-760-48672023-05-02
374376신만로경기도 광주시 신만로 391경기도 광주시 곤지암읍 부향리 324-3도로아스팔트 콘크리트원호형7.52.06소로Y37.360637127.398138NY경기도 광주시청031-760-48672023-05-02
375377신만로경기도 광주시 신만로 346경기도 광주시 곤지암읍 부향리 295-9도로아스팔트 콘크리트기타7.52.06소로Y37.357167127.396337YN경기도 광주시청031-760-48672023-05-02
376378신만로경기도 광주시 신만로 337경기도 광주시 곤지암읍 부항리 276-7도로아스팔트 콘크리트기타7.52.06소로Y37.356621127.395156YN경기도 광주시청031-760-48672023-05-02
377379신만로경기도 광주시 신만로 480경기도 광주시 곤지암읍 만선리 200-5도로아스팔트 콘크리트원호형7.52.06소로Y37.364446127.404701NN경기도 광주시청031-760-48672023-05-02
378380신만로경기도 광주시 신만로 470경기도 광주시 곤지암읍 만선리 182-3도로아스팔트 콘크리트원호형7.52.06소로Y37.36362127.403669NN경기도 광주시청031-760-48672023-05-02
379381곤지암로경기도 광주시 곤지암로 120경기도 광주시 곤지암읍 곤지암리 453-136도로아스팔트 콘크리트원호형7.52.06소로Y37.345368127.338091YN경기도 광주시청031-760-48672023-05-02