Overview

Dataset statistics

Number of variables6
Number of observations70
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory52.9 B

Variable types

Numeric3
Categorical3

Dataset

Description울산광역시 중구에서 설치한 불법주정차 단속용 무인단속기(CCTV)의 위치(위도와 경도)를 제공하는 데이터입니다
Author울산광역시 중구
URLhttps://www.data.go.kr/data/15106754/fileData.do

Alerts

관리부서 소속 has constant value ""Constant
연락번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:20:30.485490
Analysis finished2023-12-12 16:20:31.626216
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.5
Minimum1
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-13T01:20:31.704996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.45
Q118.25
median35.5
Q352.75
95-th percentile66.55
Maximum70
Range69
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation20.351085
Coefficient of variation (CV)0.57327
Kurtosis-1.2
Mean35.5
Median Absolute Deviation (MAD)17.5
Skewness0
Sum2485
Variance414.16667
MonotonicityStrictly increasing
2023-12-13T01:20:31.854433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
46 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
45 1
 
1.4%
54 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%
61 1
1.4%

위도
Real number (ℝ)

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.562235
Minimum35.550881
Maximum35.583778
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-13T01:20:32.046880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.550881
5-th percentile35.552353
Q135.555133
median35.558976
Q335.568589
95-th percentile35.580144
Maximum35.583778
Range0.032897
Interquartile range (IQR)0.013456

Descriptive statistics

Standard deviation0.0087563677
Coefficient of variation (CV)0.00024622659
Kurtosis-0.33985276
Mean35.562235
Median Absolute Deviation (MAD)0.0049195
Skewness0.8275951
Sum2489.3565
Variance7.6673976 × 10-5
MonotonicityNot monotonic
2023-12-13T01:20:32.265024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.557417 1
 
1.4%
35.558589 1
 
1.4%
35.576276 1
 
1.4%
35.553146 1
 
1.4%
35.552089 1
 
1.4%
35.558003 1
 
1.4%
35.556564 1
 
1.4%
35.555298 1
 
1.4%
35.568715 1
 
1.4%
35.569104 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
35.550881 1
1.4%
35.5516056 1
1.4%
35.551895 1
1.4%
35.552089 1
1.4%
35.552676 1
1.4%
35.552776 1
1.4%
35.553018 1
1.4%
35.553146 1
1.4%
35.553235 1
1.4%
35.554036 1
1.4%
ValueCountFrequency (%)
35.583778 1
1.4%
35.581648 1
1.4%
35.581314 1
1.4%
35.580719 1
1.4%
35.579441 1
1.4%
35.577021 1
1.4%
35.576276 1
1.4%
35.575948 1
1.4%
35.575004 1
1.4%
35.574334 1
1.4%

경도
Real number (ℝ)

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.32296
Minimum129.2673
Maximum129.35044
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-13T01:20:32.413948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.2673
5-th percentile129.29263
Q1129.31126
median129.32176
Q3129.3382
95-th percentile129.3457
Maximum129.35044
Range0.083144
Interquartile range (IQR)0.026937

Descriptive statistics

Standard deviation0.018166318
Coefficient of variation (CV)0.00014047249
Kurtosis0.55216483
Mean129.32296
Median Absolute Deviation (MAD)0.013186
Skewness-0.74171008
Sum9052.6071
Variance0.00033001512
MonotonicityNot monotonic
2023-12-13T01:20:32.558746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.32631 1
 
1.4%
129.272002 1
 
1.4%
129.319373 1
 
1.4%
129.318246 1
 
1.4%
129.288478 1
 
1.4%
129.306301 1
 
1.4%
129.306436 1
 
1.4%
129.318032 1
 
1.4%
129.344772 1
 
1.4%
129.337196 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
129.267297 1
1.4%
129.272002 1
1.4%
129.288478 1
1.4%
129.2916095 1
1.4%
129.293882 1
1.4%
129.296267 1
1.4%
129.299453 1
1.4%
129.299729 1
1.4%
129.299995 1
1.4%
129.306301 1
1.4%
ValueCountFrequency (%)
129.350441 1
1.4%
129.348236 1
1.4%
129.346964 1
1.4%
129.346097 1
1.4%
129.345209 1
1.4%
129.345055 1
1.4%
129.344953 1
1.4%
129.344772 1
1.4%
129.344714 1
1.4%
129.344263 1
1.4%

관리부서 소속
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
안전도시국 교통과
70 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row안전도시국 교통과
2nd row안전도시국 교통과
3rd row안전도시국 교통과
4th row안전도시국 교통과
5th row안전도시국 교통과

Common Values

ValueCountFrequency (%)
안전도시국 교통과 70
100.0%

Length

2023-12-13T01:20:32.707422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:20:32.809064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안전도시국 70
50.0%
교통과 70
50.0%

연락번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
052-290-3983
70 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row052-290-3983
2nd row052-290-3983
3rd row052-290-3983
4th row052-290-3983
5th row052-290-3983

Common Values

ValueCountFrequency (%)
052-290-3983 70
100.0%

Length

2023-12-13T01:20:32.916979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:20:33.001750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
052-290-3983 70
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-09-01
70 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-01
2nd row2023-09-01
3rd row2023-09-01
4th row2023-09-01
5th row2023-09-01

Common Values

ValueCountFrequency (%)
2023-09-01 70
100.0%

Length

2023-12-13T01:20:33.094156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:20:33.180931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-01 70
100.0%

Interactions

2023-12-13T01:20:31.120376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:20:30.577106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:20:30.854354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:20:31.208485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:20:30.672227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:20:30.945555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:20:31.320506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:20:30.764927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:20:31.040252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:20:33.236065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.4500.000
위도0.4501.0000.270
경도0.0000.2701.000
2023-12-13T01:20:33.314390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.067-0.202
위도0.0671.0000.311
경도-0.2020.3111.000

Missing values

2023-12-13T01:20:31.422607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:20:31.574178image/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

연번위도경도관리부서 소속연락번호데이터기준일자
0135.557417129.32631안전도시국 교통과052-290-39832023-09-01
1235.562431129.337551안전도시국 교통과052-290-39832023-09-01
2335.568676129.344714안전도시국 교통과052-290-39832023-09-01
3435.555019129.309302안전도시국 교통과052-290-39832023-09-01
4535.565242129.350441안전도시국 교통과052-290-39832023-09-01
5635.577021129.317613안전도시국 교통과052-290-39832023-09-01
6735.556578129.306434안전도시국 교통과052-290-39832023-09-01
7835.563887129.335112안전도시국 교통과052-290-39832023-09-01
8935.580719129.345055안전도시국 교통과052-290-39832023-09-01
91035.569072129.346097안전도시국 교통과052-290-39832023-09-01
연번위도경도관리부서 소속연락번호데이터기준일자
606135.554079129.315832안전도시국 교통과052-290-39832023-09-01
616235.568972129.335873안전도시국 교통과052-290-39832023-09-01
626335.567288129.333315안전도시국 교통과052-290-39832023-09-01
636435.560165129.30874안전도시국 교통과052-290-39832023-09-01
646535.556946129.319543안전도시국 교통과052-290-39832023-09-01
656635.574334129.345209안전도시국 교통과052-290-39832023-09-01
666735.583778129.341692안전도시국 교통과052-290-39832023-09-01
676835.568328129.296267안전도시국 교통과052-290-39832023-09-01
686935.56283129.330894안전도시국 교통과052-290-39832023-09-01
697035.561296129.299995안전도시국 교통과052-290-39832023-09-01