Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory761.7 KiB
Average record size in memory78.0 B

Variable types

Categorical3
Numeric5

Dataset

Description대전광역시 도로관리시스템에 등재된 가로수 현황입니다. ※ 2022년 공공데이터 기업 매칭 지원사업으로 청년 인턴을 통해 구축·정비된 데이터입니다. 법적 효력이 없으므로 참고 목적으로만 활용하시기 바랍니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15110072/fileData.do

Alerts

지형지물부호 has constant value ""Constant
대장초기화여부 has constant value ""Constant
관리번호 is highly overall correlated with 도엽번호 and 2 other fieldsHigh correlation
도엽번호 is highly overall correlated with 관리번호 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 행정읍면동High correlation
행정읍면동 is highly overall correlated with 관리번호 and 2 other fieldsHigh correlation
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-04-17 16:23:22.501519
Analysis finished2024-04-17 16:23:25.391989
Duration2.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지형지물부호
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가로수
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가로수 10000
100.0%

Length

2024-04-18T01:23:25.438479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:23:25.507413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가로수 10000
100.0%

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50585.5
Minimum2
Maximum101207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T01:23:25.588060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5259.6
Q125327.25
median50891
Q375623
95-th percentile96046.45
Maximum101207
Range101205
Interquartile range (IQR)50295.75

Descriptive statistics

Standard deviation29155.081
Coefficient of variation (CV)0.57635253
Kurtosis-1.1981774
Mean50585.5
Median Absolute Deviation (MAD)25218
Skewness0.0026381675
Sum5.05855 × 108
Variance8.5001874 × 108
MonotonicityNot monotonic
2024-04-18T01:23:25.691218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98994 1
 
< 0.1%
28392 1
 
< 0.1%
50546 1
 
< 0.1%
21365 1
 
< 0.1%
17351 1
 
< 0.1%
43866 1
 
< 0.1%
24642 1
 
< 0.1%
45357 1
 
< 0.1%
15755 1
 
< 0.1%
71496 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
19 1
< 0.1%
22 1
< 0.1%
23 1
< 0.1%
39 1
< 0.1%
46 1
< 0.1%
58 1
< 0.1%
59 1
< 0.1%
ValueCountFrequency (%)
101207 1
< 0.1%
101201 1
< 0.1%
101186 1
< 0.1%
101173 1
< 0.1%
101161 1
< 0.1%
101141 1
< 0.1%
101127 1
< 0.1%
101110 1
< 0.1%
101100 1
< 0.1%
101091 1
< 0.1%

행정읍면동
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대전광역시 유성구
3706 
대전광역시 서구
2571 
대전광역시 중구
1450 
대전광역시 동구
1172 
대전광역시 대덕구
1101 

Length

Max length10
Median length9
Mean length9.4807
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대전광역시 유성구
2nd row대전광역시 대덕구
3rd row대전광역시 서구
4th row대전광역시 유성구
5th row대전광역시 대덕구

Common Values

ValueCountFrequency (%)
대전광역시 유성구 3706
37.1%
대전광역시 서구 2571
25.7%
대전광역시 중구 1450
 
14.5%
대전광역시 동구 1172
 
11.7%
대전광역시 대덕구 1101
 
11.0%

Length

2024-04-18T01:23:25.788141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:23:25.864606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 10000
50.0%
유성구 3706
 
18.5%
서구 2571
 
12.9%
중구 1450
 
7.2%
동구 1172
 
5.9%
대덕구 1101
 
5.5%

도엽번호
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36710061
Minimum36710026
Maximum36710099
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T01:23:25.962810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36710026
5-th percentile36710036
Q136710053
median36710062
Q336710074
95-th percentile36710084
Maximum36710099
Range73
Interquartile range (IQR)21

Descriptive statistics

Standard deviation14.858292
Coefficient of variation (CV)4.0474713 × 10-7
Kurtosis-0.40797696
Mean36710061
Median Absolute Deviation (MAD)9
Skewness-0.098571913
Sum3.6710061 × 1011
Variance220.76884
MonotonicityNot monotonic
2024-04-18T01:23:26.068433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
36710056 656
 
6.6%
36710058 516
 
5.2%
36710066 512
 
5.1%
36710043 482
 
4.8%
36710054 468
 
4.7%
36710068 455
 
4.5%
36710076 451
 
4.5%
36710055 451
 
4.5%
36710064 386
 
3.9%
36710078 378
 
3.8%
Other values (38) 5245
52.4%
ValueCountFrequency (%)
36710026 39
 
0.4%
36710027 141
 
1.4%
36710028 95
 
0.9%
36710029 22
 
0.2%
36710035 55
 
0.5%
36710036 208
2.1%
36710037 289
2.9%
36710038 47
 
0.5%
36710043 482
4.8%
36710044 239
2.4%
ValueCountFrequency (%)
36710099 67
 
0.7%
36710097 12
 
0.1%
36710096 23
 
0.2%
36710094 15
 
0.1%
36710089 114
1.1%
36710087 4
 
< 0.1%
36710086 185
1.8%
36710085 28
 
0.3%
36710084 217
2.2%
36710083 61
 
0.6%

도로구간번호
Real number (ℝ)

Distinct4549
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35778.282
Minimum1759
Maximum134875
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T01:23:26.177577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1759
5-th percentile14493
Q122418.25
median34337
Q343235.75
95-th percentile73437
Maximum134875
Range133116
Interquartile range (IQR)20817.5

Descriptive statistics

Standard deviation19769.928
Coefficient of variation (CV)0.55256785
Kurtosis7.5010776
Mean35778.282
Median Absolute Deviation (MAD)9527
Skewness2.3372597
Sum3.5778282 × 108
Variance3.9085006 × 108
MonotonicityNot monotonic
2024-04-18T01:23:26.503976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46986 41
 
0.4%
46893 27
 
0.3%
43037 25
 
0.2%
42897 23
 
0.2%
43355 22
 
0.2%
17292 22
 
0.2%
17223 21
 
0.2%
42445 21
 
0.2%
43763 20
 
0.2%
41708 19
 
0.2%
Other values (4539) 9759
97.6%
ValueCountFrequency (%)
1759 1
 
< 0.1%
2513 1
 
< 0.1%
3190 3
< 0.1%
5889 3
< 0.1%
6123 2
< 0.1%
6619 1
 
< 0.1%
7317 1
 
< 0.1%
7670 3
< 0.1%
7791 1
 
< 0.1%
7856 3
< 0.1%
ValueCountFrequency (%)
134875 1
 
< 0.1%
134851 3
< 0.1%
134840 2
< 0.1%
134825 2
< 0.1%
134822 3
< 0.1%
134791 1
 
< 0.1%
134765 1
 
< 0.1%
134464 1
 
< 0.1%
132799 2
< 0.1%
132692 1
 
< 0.1%

대장초기화여부
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 10000
100.0%

Length

2024-04-18T01:23:26.600760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:23:26.665942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct9993
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.350324
Minimum36.253764
Maximum36.44989
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T01:23:26.743873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.253764
5-th percentile36.296509
Q136.323087
median36.349909
Q336.371919
95-th percentile36.419952
Maximum36.44989
Range0.19612652
Interquartile range (IQR)0.04883187

Descriptive statistics

Standard deviation0.036378506
Coefficient of variation (CV)0.0010007753
Kurtosis-0.12611958
Mean36.350324
Median Absolute Deviation (MAD)0.024715315
Skewness0.32400497
Sum363503.24
Variance0.0013233957
MonotonicityNot monotonic
2024-04-18T01:23:26.855188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.38255952 2
 
< 0.1%
36.36687274 2
 
< 0.1%
36.35120621 2
 
< 0.1%
36.34834111 2
 
< 0.1%
36.29643319 2
 
< 0.1%
36.36465867 2
 
< 0.1%
36.35399546 2
 
< 0.1%
36.34168411 1
 
< 0.1%
36.34834095 1
 
< 0.1%
36.3304134 1
 
< 0.1%
Other values (9983) 9983
99.8%
ValueCountFrequency (%)
36.25376378 1
< 0.1%
36.25381523 1
< 0.1%
36.25387245 1
< 0.1%
36.2539881 1
< 0.1%
36.25411546 1
< 0.1%
36.25420023 1
< 0.1%
36.25446085 1
< 0.1%
36.25466181 1
< 0.1%
36.25474034 1
< 0.1%
36.25480757 1
< 0.1%
ValueCountFrequency (%)
36.4498903 1
< 0.1%
36.44987144 1
< 0.1%
36.44972667 1
< 0.1%
36.4497165 1
< 0.1%
36.44970337 1
< 0.1%
36.44968207 1
< 0.1%
36.44961617 1
< 0.1%
36.44952726 1
< 0.1%
36.44947284 1
< 0.1%
36.44940478 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct9967
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.38264
Minimum127.28513
Maximum127.47699
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T01:23:26.967633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.28513
5-th percentile127.311
Q1127.34416
median127.3852
Q3127.41941
95-th percentile127.45252
Maximum127.47699
Range0.1918542
Interquartile range (IQR)0.0752492

Descriptive statistics

Standard deviation0.044459381
Coefficient of variation (CV)0.00034902229
Kurtosis-0.98515674
Mean127.38264
Median Absolute Deviation (MAD)0.03780815
Skewness-0.03210552
Sum1273826.4
Variance0.0019766365
MonotonicityNot monotonic
2024-04-18T01:23:27.081365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.3444841 2
 
< 0.1%
127.3445148 2
 
< 0.1%
127.339887 2
 
< 0.1%
127.3382041 2
 
< 0.1%
127.3407079 2
 
< 0.1%
127.3793413 2
 
< 0.1%
127.3893228 2
 
< 0.1%
127.3433749 2
 
< 0.1%
127.3198307 2
 
< 0.1%
127.4276071 2
 
< 0.1%
Other values (9957) 9980
99.8%
ValueCountFrequency (%)
127.2851313 1
< 0.1%
127.2856313 1
< 0.1%
127.2880703 1
< 0.1%
127.2882287 1
< 0.1%
127.288587 1
< 0.1%
127.2889472 1
< 0.1%
127.2894531 1
< 0.1%
127.2900299 1
< 0.1%
127.290125 1
< 0.1%
127.2901817 1
< 0.1%
ValueCountFrequency (%)
127.4769855 1
< 0.1%
127.4759772 1
< 0.1%
127.4750893 1
< 0.1%
127.4748639 1
< 0.1%
127.4748477 1
< 0.1%
127.4748285 1
< 0.1%
127.4747017 1
< 0.1%
127.4746273 1
< 0.1%
127.4745688 1
< 0.1%
127.4742333 1
< 0.1%

Interactions

2024-04-18T01:23:24.792849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.164689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.543861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.972277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.389814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.883147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.235436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.616818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.041905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.464983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.991439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.313762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.709377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.124982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.547951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:25.070113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.386845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.807588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.225828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.628692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:25.154633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.468389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:23.891532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.311312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:23:24.708747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T01:23:27.158510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정읍면동도엽번호도로구간번호위도경도
관리번호1.0000.9310.9350.7590.9240.839
행정읍면동0.9311.0000.8720.7300.8330.909
도엽번호0.9350.8721.0000.7060.9780.736
도로구간번호0.7590.7300.7061.0000.6600.621
위도0.9240.8330.9780.6601.0000.662
경도0.8390.9090.7360.6210.6621.000
2024-04-18T01:23:27.239126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호도엽번호도로구간번호위도경도행정읍면동
관리번호1.000-0.9580.4670.904-0.3750.647
도엽번호-0.9581.000-0.460-0.9590.2780.538
도로구간번호0.467-0.4601.0000.419-0.3510.389
위도0.904-0.9590.4191.000-0.1040.494
경도-0.3750.278-0.351-0.1041.0000.604
행정읍면동0.6470.5380.3890.4940.6041.000

Missing values

2024-04-18T01:23:25.252881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T01:23:25.348778image/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

지형지물부호관리번호행정읍면동도엽번호도로구간번호대장초기화여부위도경도
97785가로수98994대전광역시 유성구3671003517144136.402526127.364077
94315가로수95423대전광역시 대덕구3671003715900136.42108127.419603
37815가로수38112대전광역시 서구3671006621158136.342031127.397485
72940가로수73760대전광역시 유성구36710046107477136.377717127.375067
96476가로수97619대전광역시 대덕구3671002812490136.443763127.44461
8718가로수8847대전광역시 중구3671007919234136.303733127.451631
28277가로수28472대전광역시 서구3671007533706136.30624127.364598
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