Overview

Dataset statistics

Number of variables15
Number of observations1141
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory142.8 KiB
Average record size in memory128.1 B

Variable types

Numeric8
Categorical5
Text1
DateTime1

Dataset

Description제주특별자치도에서 제공하는어린이보호구역 내 미끄럼방지시설 관련 도로명, 폭(m), 연장(m), 도로차로수, 보차분리여부 등 정보 입니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15075791/fileData.do

Alerts

시도명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시군구명 is highly overall correlated with 관리번호 and 4 other fieldsHigh correlation
관리기관명 is highly overall correlated with 관리번호 and 4 other fieldsHigh correlation
관리번호 is highly overall correlated with 시작점위도 and 4 other fieldsHigh correlation
시작점위도 is highly overall correlated with 관리번호 and 4 other fieldsHigh correlation
시작점경도 is highly overall correlated with 종료점경도High correlation
종료점위도 is highly overall correlated with 관리번호 and 4 other fieldsHigh correlation
종료점경도 is highly overall correlated with 시작점경도High correlation
보차분리여부 is highly overall correlated with 관리번호 and 4 other fieldsHigh correlation
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:24:29.764000
Analysis finished2023-12-12 09:24:39.323499
Duration9.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean571
Minimum1
Maximum1141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-12T18:24:39.449882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile58
Q1286
median571
Q3856
95-th percentile1084
Maximum1141
Range1140
Interquartile range (IQR)570

Descriptive statistics

Standard deviation329.52263
Coefficient of variation (CV)0.57709743
Kurtosis-1.2
Mean571
Median Absolute Deviation (MAD)285
Skewness0
Sum651511
Variance108585.17
MonotonicityStrictly increasing
2023-12-12T18:24:39.637116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
760 1
 
0.1%
766 1
 
0.1%
765 1
 
0.1%
764 1
 
0.1%
763 1
 
0.1%
762 1
 
0.1%
761 1
 
0.1%
759 1
 
0.1%
768 1
 
0.1%
Other values (1131) 1131
99.1%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1141 1
0.1%
1140 1
0.1%
1139 1
0.1%
1138 1
0.1%
1137 1
0.1%
1136 1
0.1%
1135 1
0.1%
1134 1
0.1%
1133 1
0.1%
1132 1
0.1%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
제주특별자치도
1141 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주특별자치도 1141
100.0%

Length

2023-12-12T18:24:39.782696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:24:39.902467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주특별자치도 1141
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
제주시
639 
서귀포시
502 

Length

Max length4
Median length3
Mean length3.4399649
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 639
56.0%
서귀포시 502
44.0%

Length

2023-12-12T18:24:40.013420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:24:40.122076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 639
56.0%
서귀포시 502
44.0%
Distinct429
Distinct (%)37.6%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2023-12-12T18:24:40.385345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length6.0096407
Min length3

Characters and Unicode

Total characters6857
Distinct characters171
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

Unique191 ?
Unique (%)16.7%

Sample

1st row수덕3길
2nd row정존11길
3rd row수덕3길
4th row정존11길
5th row수덕1길
ValueCountFrequency (%)
일주동로 40
 
2.4%
태위로 32
 
1.9%
한림로 24
 
1.5%
중산간서로 22
 
1.3%
중산간동로 22
 
1.3%
효돈로 22
 
1.3%
월평하원로 20
 
1.2%
고성오조로 19
 
1.2%
신례로 19
 
1.2%
시흥상동로 17
 
1.0%
Other values (432) 1406
85.6%
2023-12-12T18:24:40.877706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1002
 
14.6%
502
 
7.3%
404
 
5.9%
1 366
 
5.3%
2 303
 
4.4%
203
 
3.0%
6 187
 
2.7%
5 167
 
2.4%
7 153
 
2.2%
4 144
 
2.1%
Other values (161) 3426
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4473
65.2%
Decimal Number 1820
26.5%
Space Separator 502
 
7.3%
Dash Punctuation 62
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1002
22.4%
404
 
9.0%
203
 
4.5%
115
 
2.6%
112
 
2.5%
102
 
2.3%
101
 
2.3%
99
 
2.2%
91
 
2.0%
79
 
1.8%
Other values (149) 2165
48.4%
Decimal Number
ValueCountFrequency (%)
1 366
20.1%
2 303
16.6%
6 187
10.3%
5 167
9.2%
7 153
8.4%
4 144
 
7.9%
3 135
 
7.4%
8 130
 
7.1%
9 118
 
6.5%
0 117
 
6.4%
Space Separator
ValueCountFrequency (%)
502
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4473
65.2%
Common 2384
34.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1002
22.4%
404
 
9.0%
203
 
4.5%
115
 
2.6%
112
 
2.5%
102
 
2.3%
101
 
2.3%
99
 
2.2%
91
 
2.0%
79
 
1.8%
Other values (149) 2165
48.4%
Common
ValueCountFrequency (%)
502
21.1%
1 366
15.4%
2 303
12.7%
6 187
 
7.8%
5 167
 
7.0%
7 153
 
6.4%
4 144
 
6.0%
3 135
 
5.7%
8 130
 
5.5%
9 118
 
4.9%
Other values (2) 179
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4473
65.2%
ASCII 2384
34.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1002
22.4%
404
 
9.0%
203
 
4.5%
115
 
2.6%
112
 
2.5%
102
 
2.3%
101
 
2.3%
99
 
2.2%
91
 
2.0%
79
 
1.8%
Other values (149) 2165
48.4%
ASCII
ValueCountFrequency (%)
502
21.1%
1 366
15.4%
2 303
12.7%
6 187
 
7.8%
5 167
 
7.0%
7 153
 
6.4%
4 144
 
6.0%
3 135
 
5.7%
8 130
 
5.5%
9 118
 
4.9%
Other values (2) 179
 
7.5%


Real number (ℝ)

Distinct474
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.7858896
Minimum1.8
Maximum80.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-12T18:24:41.057325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.8
5-th percentile3.3
Q14.71
median6.51
Q38.1
95-th percentile10.75
Maximum80.1
Range78.3
Interquartile range (IQR)3.39

Descriptive statistics

Standard deviation3.6118162
Coefficient of variation (CV)0.5322539
Kurtosis161.41856
Mean6.7858896
Median Absolute Deviation (MAD)1.61
Skewness9.1800013
Sum7742.7
Variance13.045216
MonotonicityNot monotonic
2023-12-12T18:24:41.242822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.0 22
 
1.9%
3.9 20
 
1.8%
6.5 19
 
1.7%
4.5 17
 
1.5%
6.0 15
 
1.3%
3.8 14
 
1.2%
4.1 14
 
1.2%
7.5 14
 
1.2%
3.3 14
 
1.2%
5.9 12
 
1.1%
Other values (464) 980
85.9%
ValueCountFrequency (%)
1.8 1
 
0.1%
2.1 3
 
0.3%
2.3 1
 
0.1%
2.4 8
0.7%
2.49 1
 
0.1%
2.5 2
 
0.2%
2.6 2
 
0.2%
2.66 2
 
0.2%
2.7 1
 
0.1%
2.8 2
 
0.2%
ValueCountFrequency (%)
80.1 1
 
0.1%
37.4 3
0.3%
22.4 1
 
0.1%
18.3 1
 
0.1%
16.1 1
 
0.1%
15.98 2
0.2%
15.78 1
 
0.1%
15.5 1
 
0.1%
14.25 1
 
0.1%
14.22 1
 
0.1%

연장
Real number (ℝ)

Distinct768
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.579295
Minimum2.15
Maximum345.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-12T18:24:41.416446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.15
5-th percentile4.97
Q114.42
median24
Q340.72
95-th percentile95.43
Maximum345.7
Range343.55
Interquartile range (IQR)26.3

Descriptive statistics

Standard deviation32.99136
Coefficient of variation (CV)0.98249113
Kurtosis17.084038
Mean33.579295
Median Absolute Deviation (MAD)12
Skewness3.222676
Sum38313.976
Variance1088.4298
MonotonicityNot monotonic
2023-12-12T18:24:41.590734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17.1 23
 
2.0%
17.0 20
 
1.8%
12.0 17
 
1.5%
16.0 15
 
1.3%
4.0 12
 
1.1%
21.0 11
 
1.0%
28.0 11
 
1.0%
13.0 10
 
0.9%
9.0 9
 
0.8%
5.0 9
 
0.8%
Other values (758) 1004
88.0%
ValueCountFrequency (%)
2.15 1
 
0.1%
2.38 1
 
0.1%
2.39 1
 
0.1%
2.4 2
 
0.2%
2.66 1
 
0.1%
3.0 2
 
0.2%
3.1 2
 
0.2%
3.2 1
 
0.1%
3.5 1
 
0.1%
3.6 7
0.6%
ValueCountFrequency (%)
345.7 1
0.1%
275.3 1
0.1%
271.25 1
0.1%
261.87 1
0.1%
223.26 1
0.1%
221.1 1
0.1%
194.48 1
0.1%
178.4 2
0.2%
176.6 1
0.1%
173.66 1
0.1%

도로차로수
Real number (ℝ)

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.115688
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-12T18:24:41.731657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0599277
Coefficient of variation (CV)0.50098487
Kurtosis2.8239518
Mean2.115688
Median Absolute Deviation (MAD)0
Skewness1.6233024
Sum2414
Variance1.1234467
MonotonicityNot monotonic
2023-12-12T18:24:41.872704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 693
60.7%
1 271
 
23.8%
4 125
 
11.0%
6 23
 
2.0%
5 16
 
1.4%
3 13
 
1.1%
ValueCountFrequency (%)
1 271
 
23.8%
2 693
60.7%
3 13
 
1.1%
4 125
 
11.0%
5 16
 
1.4%
6 23
 
2.0%
ValueCountFrequency (%)
6 23
 
2.0%
5 16
 
1.4%
4 125
 
11.0%
3 13
 
1.1%
2 693
60.7%
1 271
 
23.8%

보차분리여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
미분리
753 
분리
388 

Length

Max length3
Median length3
Mean length2.6599474
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row분리
2nd row분리
3rd row미분리
4th row분리
5th row미분리

Common Values

ValueCountFrequency (%)
미분리 753
66.0%
분리 388
34.0%

Length

2023-12-12T18:24:42.015302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:24:42.160403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미분리 753
66.0%
분리 388
34.0%

시작점위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1015
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.395977
Minimum33.223798
Maximum33.555066
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-12T18:24:42.299385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.223798
5-th percentile33.243348
Q133.27356
median33.447233
Q333.492126
95-th percentile33.53318
Maximum33.555066
Range0.331268
Interquartile range (IQR)0.218566

Descriptive statistics

Standard deviation0.10881749
Coefficient of variation (CV)0.0032584012
Kurtosis-1.6056208
Mean33.395977
Median Absolute Deviation (MAD)0.0674
Skewness-0.25906498
Sum38104.81
Variance0.011841247
MonotonicityNot monotonic
2023-12-12T18:24:42.442924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.476606 7
 
0.6%
33.480861 5
 
0.4%
33.263829 5
 
0.4%
33.263595 5
 
0.4%
33.273391 4
 
0.4%
33.284851 4
 
0.4%
33.28396 4
 
0.4%
33.283091 4
 
0.4%
33.252302 4
 
0.4%
33.263567 4
 
0.4%
Other values (1005) 1095
96.0%
ValueCountFrequency (%)
33.223798 1
0.1%
33.223865 1
0.1%
33.223884 1
0.1%
33.224165 1
0.1%
33.224271 2
0.2%
33.224772 1
0.1%
33.225228 1
0.1%
33.22559 1
0.1%
33.225592 1
0.1%
33.225623 1
0.1%
ValueCountFrequency (%)
33.555066 1
0.1%
33.555042 1
0.1%
33.554996 1
0.1%
33.554885 1
0.1%
33.554851 1
0.1%
33.554769 1
0.1%
33.55462 1
0.1%
33.554473 1
0.1%
33.554438 1
0.1%
33.553334 1
0.1%

시작점경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1022
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.53646
Minimum126.17625
Maximum126.91525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-12T18:24:42.631258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.17625
5-th percentile126.2554
Q1126.43337
median126.52919
Q3126.63251
95-th percentile126.88719
Maximum126.91525
Range0.739006
Interquartile range (IQR)0.199141

Descriptive statistics

Standard deviation0.18256582
Coefficient of variation (CV)0.0014427922
Kurtosis-0.47451351
Mean126.53646
Median Absolute Deviation (MAD)0.10332
Skewness0.24765122
Sum144378.1
Variance0.033330278
MonotonicityNot monotonic
2023-12-12T18:24:42.825684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.895889 7
 
0.6%
126.61697 5
 
0.4%
126.896978 5
 
0.4%
126.632507 4
 
0.4%
126.613967 4
 
0.4%
126.617604 4
 
0.4%
126.632396 4
 
0.4%
126.653742 4
 
0.4%
126.633506 4
 
0.4%
126.799517 3
 
0.3%
Other values (1012) 1097
96.1%
ValueCountFrequency (%)
126.176247 1
0.1%
126.176908 1
0.1%
126.177002 1
0.1%
126.178011 1
0.1%
126.178045 1
0.1%
126.178133 1
0.1%
126.178266 1
0.1%
126.178296 1
0.1%
126.182546 1
0.1%
126.182554 1
0.1%
ValueCountFrequency (%)
126.915253 1
 
0.1%
126.914885 3
0.3%
126.914822 3
0.3%
126.914793 3
0.3%
126.914745 1
 
0.1%
126.914736 1
 
0.1%
126.914428 3
0.3%
126.913633 1
 
0.1%
126.91352 1
 
0.1%
126.913476 1
 
0.1%

종료점위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1016
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.396021
Minimum33.223916
Maximum33.555229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-12T18:24:43.008413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.223916
5-th percentile33.243433
Q133.273631
median33.447298
Q333.492012
95-th percentile33.533246
Maximum33.555229
Range0.331313
Interquartile range (IQR)0.218381

Descriptive statistics

Standard deviation0.10875701
Coefficient of variation (CV)0.0032565859
Kurtosis-1.6052223
Mean33.396021
Median Absolute Deviation (MAD)0.067294
Skewness-0.25924773
Sum38104.86
Variance0.011828088
MonotonicityNot monotonic
2023-12-12T18:24:43.180545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.476701 7
 
0.6%
33.480922 5
 
0.4%
33.263668 5
 
0.4%
33.284989 4
 
0.4%
33.284146 4
 
0.4%
33.273463 4
 
0.4%
33.2639 4
 
0.4%
33.263642 4
 
0.4%
33.283154 4
 
0.4%
33.26364 3
 
0.3%
Other values (1006) 1097
96.1%
ValueCountFrequency (%)
33.223916 1
0.1%
33.223975 1
0.1%
33.224011 1
0.1%
33.22427 1
0.1%
33.224375 1
0.1%
33.224395 1
0.1%
33.224892 1
0.1%
33.225289 1
0.1%
33.225742 1
0.1%
33.225785 2
0.2%
ValueCountFrequency (%)
33.555229 1
0.1%
33.555126 1
0.1%
33.555102 1
0.1%
33.554988 1
0.1%
33.554856 1
0.1%
33.554836 1
0.1%
33.554741 1
0.1%
33.554606 1
0.1%
33.55429 1
0.1%
33.55342 1
0.1%

종료점경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1022
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.53681
Minimum126.17665
Maximum126.9155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-12T18:24:43.362691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.17665
5-th percentile126.25633
Q1126.43358
median126.52912
Q3126.63301
95-th percentile126.88773
Maximum126.9155
Range0.738852
Interquartile range (IQR)0.199433

Descriptive statistics

Standard deviation0.18266266
Coefficient of variation (CV)0.0014435535
Kurtosis-0.47416626
Mean126.53681
Median Absolute Deviation (MAD)0.103874
Skewness0.24939257
Sum144378.5
Variance0.033365646
MonotonicityNot monotonic
2023-12-12T18:24:43.514902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.896947 7
 
0.6%
126.897905 5
 
0.4%
126.617337 5
 
0.4%
126.614263 4
 
0.4%
126.634109 4
 
0.4%
126.654268 4
 
0.4%
126.633092 4
 
0.4%
126.618438 4
 
0.4%
126.632997 4
 
0.4%
126.55653 3
 
0.3%
Other values (1012) 1097
96.1%
ValueCountFrequency (%)
126.176646 1
0.1%
126.176957 1
0.1%
126.17784 1
0.1%
126.178091 1
0.1%
126.178128 2
0.2%
126.178223 1
0.1%
126.179346 1
0.1%
126.182536 1
0.1%
126.182603 1
0.1%
126.182648 1
0.1%
ValueCountFrequency (%)
126.915498 1
 
0.1%
126.91537 3
0.3%
126.915353 1
 
0.1%
126.915291 1
 
0.1%
126.915252 3
0.3%
126.915244 3
0.3%
126.915171 3
0.3%
126.914107 1
 
0.1%
126.913805 1
 
0.1%
126.91365 1
 
0.1%

관리기관명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
제주시
639 
서귀포시
502 

Length

Max length4
Median length3
Mean length3.4399649
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 639
56.0%
서귀포시 502
44.0%

Length

2023-12-12T18:24:43.652769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:24:43.744128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 639
56.0%
서귀포시 502
44.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
064-120
1141 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row064-120
2nd row064-120
3rd row064-120
4th row064-120
5th row064-120

Common Values

ValueCountFrequency (%)
064-120 1141
100.0%

Length

2023-12-12T18:24:43.830083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:24:43.912090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
064-120 1141
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
Minimum2020-12-31 00:00:00
Maximum2020-12-31 00:00:00
2023-12-12T18:24:43.976785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:44.055337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T18:24:37.578549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:30.691666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:31.685837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:32.972804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:33.848248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:34.790719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:35.830882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:36.793446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:37.673007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:30.825378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:31.790941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:33.069439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:33.948482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:34.920966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:35.949517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:36.882113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:37.780089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:30.947204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:32.273265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:33.181032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:34.052507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:35.063269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:36.094001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:36.975475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:37.876525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:31.052203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:32.380399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:33.283020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:34.169835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:35.221984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:36.236418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:37.079540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:37.969296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:31.174353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:32.493720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:33.379581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:34.306362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:35.343492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:36.349996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:37.176403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:38.066811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:31.311168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:32.608837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:33.502613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:34.430640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:35.469928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:36.457379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:37.270263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:38.278507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:31.444675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:32.734606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:33.610613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:34.561231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:35.586837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:36.569661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:37.375883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:38.430395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:31.563115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:32.847195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:33.731285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:34.668798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:35.713231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:36.685026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:24:37.466831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:24:44.123649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호시군구명연장도로차로수보차분리여부시작점위도시작점경도종료점위도종료점경도관리기관명
관리번호1.0000.9970.2520.1820.3910.8400.8530.7550.8530.7550.997
시군구명0.9971.0000.0530.1480.3230.8390.9770.5590.9770.5591.000
0.2520.0531.0000.1280.1850.0430.3260.3790.3260.3800.053
연장0.1820.1480.1281.0000.3130.1440.2710.1620.2740.1560.148
도로차로수0.3910.3230.1850.3131.0000.4070.4100.3860.4090.3860.323
보차분리여부0.8400.8390.0430.1440.4071.0000.7950.3810.7920.3820.839
시작점위도0.8530.9770.3260.2710.4100.7951.0000.8431.0000.8430.977
시작점경도0.7550.5590.3790.1620.3860.3810.8431.0000.8431.0000.559
종료점위도0.8530.9770.3260.2740.4090.7921.0000.8431.0000.8430.977
종료점경도0.7550.5590.3800.1560.3860.3820.8431.0000.8431.0000.559
관리기관명0.9971.0000.0530.1480.3230.8390.9770.5590.9770.5591.000
2023-12-12T18:24:44.241703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보차분리여부시군구명관리기관명
보차분리여부1.0000.6340.634
시군구명0.6341.0000.998
관리기관명0.6340.9981.000
2023-12-12T18:24:44.328859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호연장도로차로수시작점위도시작점경도종료점위도종료점경도시군구명보차분리여부관리기관명
관리번호1.000-0.197-0.132-0.125-0.5660.385-0.5650.3870.9460.6700.946
-0.1971.0000.0330.2830.2520.0620.2530.0610.0660.0480.066
연장-0.1320.0331.0000.1280.1900.0530.1890.0570.1480.1440.148
도로차로수-0.1250.2830.1281.000-0.024-0.017-0.025-0.0160.2320.2920.232
시작점위도-0.5660.2520.190-0.0241.0000.1801.0000.1790.8660.6270.866
시작점경도0.3850.0620.053-0.0170.1801.0000.1811.0000.4300.2920.430
종료점위도-0.5650.2530.189-0.0251.0000.1811.0000.1790.8660.6250.866
종료점경도0.3870.0610.057-0.0160.1791.0000.1791.0000.4300.2920.430
시군구명0.9460.0660.1480.2320.8660.4300.8660.4301.0000.6340.998
보차분리여부0.6700.0480.1440.2920.6270.2920.6250.2920.6341.0000.634
관리기관명0.9460.0660.1480.2320.8660.4300.8660.4300.9980.6341.000

Missing values

2023-12-12T18:24:38.636578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:24:39.226778image/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

관리번호시도명시군구명도로명연장도로차로수보차분리여부시작점위도시작점경도종료점위도종료점경도관리기관명관리기관전화번호데이터기준일자
01제주특별자치도제주시수덕3길5.9850.022분리33.485189126.47573733.48483126.475403제주시064-1202020-12-31
12제주특별자치도제주시정존11길9.6828.512분리33.485361126.47569633.485604126.475563제주시064-1202020-12-31
23제주특별자치도제주시수덕3길6.8952.972미분리33.485608126.47626133.485894126.476726제주시064-1202020-12-31
34제주특별자치도제주시정존11길10.0332.392분리33.485234126.47655833.485381126.476243제주시064-1202020-12-31
45제주특별자치도제주시수덕1길8.0753.332미분리33.485237126.47670133.485512126.477166제주시064-1202020-12-31
56제주특별자치도제주시정존11길10.0930.412분리33.484806126.47689933.485065126.476751제주시064-1202020-12-31
67제주특별자치도제주시노형로9.3538.076분리33.484892126.47732633.485024126.47772제주시064-1202020-12-31
78제주특별자치도제주시노형로7.5740.016분리33.484252126.47664233.484457126.477008제주시064-1202020-12-31
89제주특별자치도제주시정존9길10.26136.426분리33.483724126.47581433.484507126.476938제주시064-1202020-12-31
910제주특별자치도제주시노형로9.0435.766분리33.48296126.47507833.483138126.475414제주시064-1202020-12-31
관리번호시도명시군구명도로명연장도로차로수보차분리여부시작점위도시작점경도종료점위도종료점경도관리기관명관리기관전화번호데이터기준일자
11311132제주특별자치도서귀포시고성오조로 6511.343.82미분리33.449452126.91442833.449656126.91537서귀포시064-1202020-12-31
11321133제주특별자치도서귀포시고성오조로 6010.616.22미분리33.448809126.91482233.449001126.915171서귀포시064-1202020-12-31
11331134제주특별자치도서귀포시고성오조로 6010.616.22미분리33.448809126.91482233.449001126.915171서귀포시064-1202020-12-31
11341135제주특별자치도서귀포시고성오조로 6010.616.22미분리33.448809126.91482233.449001126.915171서귀포시064-1202020-12-31
11351136제주특별자치도서귀포시일주동로 509914.1148.04미분리33.3815126.87508833.381758126.878268서귀포시064-1202020-12-31
11361137제주특별자치도서귀포시일주동로 509914.1148.04미분리33.3815126.87508833.381758126.878268서귀포시064-1202020-12-31
11371138제주특별자치도서귀포시일주동로 509914.1148.04미분리33.3815126.87508833.381758126.878268서귀포시064-1202020-12-31
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11401141제주특별자치도서귀포시환해장성로111번길 21-1014.184.04미분리33.381756126.87599133.382012126.877796서귀포시064-1202020-12-31