Overview

Dataset statistics

Number of variables8
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory71.6 B

Variable types

Categorical3
Numeric5

Dataset

Description통영시 도시정보시스템의 교차시설에 대하여 지형지물부호,관리번호,행정읍면동,도엽번호,도로구간번호,구분ID,경도,위도 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15062677/fileData.do

Alerts

지형지물부호 has constant value ""Constant
행정읍면동 is highly overall correlated with 관리번호 and 3 other fieldsHigh correlation
도엽번호 is highly overall correlated with 도로구간번호 and 3 other fieldsHigh correlation
관리번호 is highly overall correlated with 행정읍면동High correlation
도로구간번호 is highly overall correlated with 도엽번호High correlation
경도 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 경도 and 2 other fieldsHigh correlation
관리번호 has unique valuesUnique
구분ID has unique valuesUnique
구분ID has 1 (2.0%) zerosZeros

Reproduction

Analysis started2023-12-12 15:54:59.890345
Analysis finished2023-12-12 15:55:03.460197
Duration3.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지형지물부호
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
도로교차시설
51 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도로교차시설 51
100.0%

Length

2023-12-13T00:55:03.515949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:55:03.596840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도로교차시설 51
100.0%

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30
Minimum5
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-13T00:55:03.692309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.5
Q117.5
median30
Q342.5
95-th percentile52.5
Maximum55
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.49553562
Kurtosis-1.2
Mean30
Median Absolute Deviation (MAD)13
Skewness0
Sum1530
Variance221
MonotonicityNot monotonic
2023-12-13T00:55:03.841010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16 1
 
2.0%
6 1
 
2.0%
46 1
 
2.0%
42 1
 
2.0%
51 1
 
2.0%
17 1
 
2.0%
14 1
 
2.0%
11 1
 
2.0%
35 1
 
2.0%
27 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
11 1
2.0%
12 1
2.0%
13 1
2.0%
14 1
2.0%
ValueCountFrequency (%)
55 1
2.0%
54 1
2.0%
53 1
2.0%
52 1
2.0%
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%

행정읍면동
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
미수동
27 
정량동
14 
도천동
6 
명정동
 
2
산양읍
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미수동
2nd row도천동
3rd row정량동
4th row도천동
5th row미수동

Common Values

ValueCountFrequency (%)
미수동 27
52.9%
정량동 14
27.5%
도천동 6
 
11.8%
명정동 2
 
3.9%
산양읍 2
 
3.9%

Length

2023-12-13T00:55:03.963850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:55:04.064819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미수동 27
52.9%
정량동 14
27.5%
도천동 6
 
11.8%
명정동 2
 
3.9%
산양읍 2
 
3.9%

도엽번호
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size540.0 B
348021860A
24 
348021919A
14 
348021923B
 
2
348021860C
 
2
348021913D
 
2
Other values (7)
7 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique7 ?
Unique (%)13.7%

Sample

1st row348021860A
2nd row348021923B
3rd row348021919A
4th row348021923A
5th row348021860A

Common Values

ValueCountFrequency (%)
348021860A 24
47.1%
348021919A 14
27.5%
348021923B 2
 
3.9%
348021860C 2
 
3.9%
348021913D 2
 
3.9%
348021923A 1
 
2.0%
348021819C 1
 
2.0%
348021850C 1
 
2.0%
348021491D 1
 
2.0%
348021491A 1
 
2.0%
Other values (2) 2
 
3.9%

Length

2023-12-13T00:55:04.190578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
348021860a 24
47.1%
348021919a 14
27.5%
348021923b 2
 
3.9%
348021860c 2
 
3.9%
348021913d 2
 
3.9%
348021923a 1
 
2.0%
348021819c 1
 
2.0%
348021850c 1
 
2.0%
348021491d 1
 
2.0%
348021491a 1
 
2.0%
Other values (2) 2
 
3.9%

도로구간번호
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8092.549
Minimum2403
Maximum9320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-13T00:55:04.308379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2403
5-th percentile3194
Q19127.5
median9311
Q39315
95-th percentile9319
Maximum9320
Range6917
Interquartile range (IQR)187.5

Descriptive statistics

Standard deviation2419.0519
Coefficient of variation (CV)0.29892336
Kurtosis0.643815
Mean8092.549
Median Absolute Deviation (MAD)5
Skewness-1.5923822
Sum412720
Variance5851812.3
MonotonicityNot monotonic
2023-12-13T00:55:04.425230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
9318 4
 
7.8%
9312 4
 
7.8%
9319 4
 
7.8%
9314 4
 
7.8%
9310 4
 
7.8%
9311 3
 
5.9%
3534 3
 
5.9%
9308 2
 
3.9%
8949 2
 
3.9%
3194 2
 
3.9%
Other values (12) 19
37.3%
ValueCountFrequency (%)
2403 2
3.9%
3194 2
3.9%
3468 2
3.9%
3534 3
5.9%
4014 1
 
2.0%
8168 1
 
2.0%
8949 2
3.9%
9306 1
 
2.0%
9307 2
3.9%
9308 2
3.9%
ValueCountFrequency (%)
9320 2
3.9%
9319 4
7.8%
9318 4
7.8%
9317 1
 
2.0%
9316 1
 
2.0%
9315 2
3.9%
9314 4
7.8%
9313 2
3.9%
9312 4
7.8%
9311 3
5.9%

구분ID
Real number (ℝ)

UNIQUE  ZEROS 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25
Minimum0
Maximum50
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-13T00:55:04.575439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.5
Q112.5
median25
Q337.5
95-th percentile47.5
Maximum50
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.59464275
Kurtosis-1.2
Mean25
Median Absolute Deviation (MAD)13
Skewness0
Sum1275
Variance221
MonotonicityStrictly increasing
2023-12-13T00:55:04.705787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
2.0%
1 1
 
2.0%
28 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
0 1
2.0%
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)56.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.40975
Minimum128.37651
Maximum128.44157
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-13T00:55:04.836145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.37651
5-th percentile128.39374
Q1128.39619
median128.39623
Q3128.44143
95-th percentile128.44147
Maximum128.44157
Range0.0650634
Interquartile range (IQR)0.0452414

Descriptive statistics

Standard deviation0.020728573
Coefficient of variation (CV)0.00016142522
Kurtosis-1.1053507
Mean128.40975
Median Absolute Deviation (MAD)0.0003429
Skewness0.7270361
Sum6548.8975
Variance0.00042967373
MonotonicityNot monotonic
2023-12-13T00:55:04.970608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
128.3962028 9
17.6%
128.4414302 7
 
13.7%
128.396234 3
 
5.9%
128.3959343 3
 
5.9%
128.3958916 2
 
3.9%
128.4136126 2
 
3.9%
128.3959621 2
 
3.9%
128.4414273 2
 
3.9%
128.403227 1
 
2.0%
128.3962345 1
 
2.0%
Other values (19) 19
37.3%
ValueCountFrequency (%)
128.3765089 1
 
2.0%
128.3810686 1
 
2.0%
128.3924804 1
 
2.0%
128.3950087 1
 
2.0%
128.3958916 2
 
3.9%
128.3959343 3
 
5.9%
128.3959621 2
 
3.9%
128.3961658 1
 
2.0%
128.396169 1
 
2.0%
128.3962028 9
17.6%
ValueCountFrequency (%)
128.4415723 1
 
2.0%
128.4414735 1
 
2.0%
128.4414699 1
 
2.0%
128.4414647 1
 
2.0%
128.4414302 7
13.7%
128.4414274 1
 
2.0%
128.4414273 2
 
3.9%
128.4136408 1
 
2.0%
128.4136126 2
 
3.9%
128.4136103 1
 
2.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)56.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.830943
Minimum34.795309
Maximum34.85324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-13T00:55:05.091958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.795309
5-th percentile34.822371
Q134.822904
median34.823393
Q334.844132
95-th percentile34.844243
Maximum34.85324
Range0.0579308
Interquartile range (IQR)0.02122785

Descriptive statistics

Standard deviation0.012635572
Coefficient of variation (CV)0.00036276857
Kurtosis0.33073946
Mean34.830943
Median Absolute Deviation (MAD)0.00105952
Skewness-0.42024477
Sum1776.3781
Variance0.00015965767
MonotonicityNot monotonic
2023-12-13T00:55:05.229520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
34.82290447 9
17.6%
34.8441347 7
 
13.7%
34.82284523 3
 
5.9%
34.82339323 3
 
5.9%
34.82338337 2
 
3.9%
34.84049619 2
 
3.9%
34.82334848 2
 
3.9%
34.84424276 2
 
3.9%
34.85244146 1
 
2.0%
34.82284514 1
 
2.0%
Other values (19) 19
37.3%
ValueCountFrequency (%)
34.79530932 1
 
2.0%
34.79691139 1
 
2.0%
34.82233371 1
 
2.0%
34.82240859 1
 
2.0%
34.82284514 1
 
2.0%
34.82284523 3
 
5.9%
34.82290447 9
17.6%
34.82291646 1
 
2.0%
34.82291763 1
 
2.0%
34.82296497 1
 
2.0%
ValueCountFrequency (%)
34.85324012 1
 
2.0%
34.85244146 1
 
2.0%
34.84424276 2
 
3.9%
34.84424051 1
 
2.0%
34.8441347 7
13.7%
34.84413245 1
 
2.0%
34.84413219 1
 
2.0%
34.84359605 1
 
2.0%
34.84308537 1
 
2.0%
34.8410066 1
 
2.0%

Interactions

2023-12-13T00:55:02.330850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:00.246886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:00.785012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:01.291054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:01.776930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:02.454960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:00.354538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:00.876998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:01.387538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:01.862637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:02.561558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:00.470172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:00.965837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:01.489190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:01.961154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:02.662457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:00.571480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:01.071695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:01.586157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:02.075588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:02.775479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:00.693655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:01.188038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:01.676100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:55:02.204870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:55:05.337687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정읍면동도엽번호도로구간번호구분ID경도위도
관리번호1.0000.9610.7370.6110.7360.8180.843
행정읍면동0.9611.0001.0000.5490.7150.9311.000
도엽번호0.7371.0001.0000.9650.0000.9621.000
도로구간번호0.6110.5490.9651.0000.2960.5610.883
구분ID0.7360.7150.0000.2961.0000.2710.540
경도0.8180.9310.9620.5610.2711.0000.983
위도0.8431.0001.0000.8830.5400.9831.000
2023-12-13T00:55:05.445638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정읍면동도엽번호
행정읍면동1.0000.921
도엽번호0.9211.000
2023-12-13T00:55:05.530995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호도로구간번호구분ID경도위도행정읍면동도엽번호
관리번호1.0000.4670.3210.4640.2450.7170.411
도로구간번호0.4671.0000.0320.4220.0890.4330.826
구분ID0.3210.0321.000-0.1080.1320.3820.051
경도0.4640.422-0.1081.0000.6100.8890.830
위도0.2450.0890.1320.6101.0000.9890.931
행정읍면동0.7170.4330.3820.8890.9891.0000.921
도엽번호0.4110.8260.0510.8300.9310.9211.000

Missing values

2023-12-13T00:55:03.265568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:55:03.413048image/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

지형지물부호관리번호행정읍면동도엽번호도로구간번호구분ID경도위도
0도로교차시설16미수동348021860A93080128.39589234.823383
1도로교차시설6도천동348021923B35341128.41364134.839881
2도로교차시설43정량동348021919A34682128.44146534.843085
3도로교차시설9도천동348021923A24033128.41235334.839052
4도로교차시설31미수동348021860A93114128.39620334.822904
5도로교차시설20미수동348021860A93125128.39620334.822904
6도로교차시설37미수동348021860C93156128.3964734.822409
7도로교차시설39정량동348021919A93197128.44147434.844132
8도로교차시설33미수동348021860A93148128.39623434.822845
9도로교차시설24미수동348021860A93099128.39596234.823348
지형지물부호관리번호행정읍면동도엽번호도로구간번호구분ID경도위도
41도로교차시설22미수동348021860A931341128.39623934.822916
42도로교차시설25미수동348021860A931042128.39620334.822904
43도로교차시설21미수동348021860A931243128.39620334.822904
44도로교차시설45정량동348021919A931844128.4414334.844135
45도로교차시설38정량동348021919A931845128.44142734.844241
46도로교차시설12미수동348021860A930646128.39593434.823393
47도로교차시설52명정동348021491D319447128.40322734.852441
48도로교차시설53명정동348021491A319448128.40204134.85324
49도로교차시설54산양읍348022307C894949128.38106934.796911
50도로교차시설55산양읍348022306C894950128.37650934.795309