Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory498.0 KiB
Average record size in memory51.0 B

Variable types

Numeric3
Text1
Categorical1

Dataset

Description순번,굴착예정지 일련번호,입력년도,X좌표,Y좌표
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-2775/S/1/datasetView.do

Alerts

입력년도 has constant value ""Constant
순번 has unique valuesUnique
굴착예정지 일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 03:53:52.775523
Analysis finished2023-12-11 03:53:55.292994
Duration2.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24245.991
Minimum2
Maximum102181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:53:55.404019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2485.9
Q111883
median23592
Q336076.25
95-th percentile47961.1
Maximum102181
Range102179
Interquartile range (IQR)24193.25

Descriptive statistics

Standard deviation14462.831
Coefficient of variation (CV)0.59650402
Kurtosis-0.79014463
Mean24245.991
Median Absolute Deviation (MAD)12135.5
Skewness0.17815721
Sum2.4245991 × 108
Variance2.0917349 × 108
MonotonicityNot monotonic
2023-12-11T12:53:56.012872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13877 1
 
< 0.1%
50955 1
 
< 0.1%
2406 1
 
< 0.1%
19224 1
 
< 0.1%
4387 1
 
< 0.1%
48220 1
 
< 0.1%
37089 1
 
< 0.1%
46441 1
 
< 0.1%
18209 1
 
< 0.1%
39601 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
19 1
< 0.1%
23 1
< 0.1%
26 1
< 0.1%
28 1
< 0.1%
ValueCountFrequency (%)
102181 1
< 0.1%
93218 1
< 0.1%
92977 1
< 0.1%
90843 1
< 0.1%
90156 1
< 0.1%
85747 1
< 0.1%
82934 1
< 0.1%
80730 1
< 0.1%
76813 1
< 0.1%
73757 1
< 0.1%

굴착예정지 일련번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:53:56.252333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters180000
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowSVR001200605100087
2nd rowSVR001200504060025
3rd rowSVR001200606230037
4th rowSVR001200607060058
5th rowSVR001200605090011
ValueCountFrequency (%)
svr001200605100087 1
 
< 0.1%
svr001200507280002 1
 
< 0.1%
svr001200506150039 1
 
< 0.1%
svr001200605100088 1
 
< 0.1%
svr001200602200049 1
 
< 0.1%
svr001200606120111 1
 
< 0.1%
svr001200604030072 1
 
< 0.1%
svr001200508040010 1
 
< 0.1%
svr001200505060026 1
 
< 0.1%
svr001200508290104 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-11T12:53:56.721782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71921
40.0%
1 19844
 
11.0%
2 17876
 
9.9%
6 10366
 
5.8%
S 10000
 
5.6%
V 10000
 
5.6%
R 10000
 
5.6%
5 8775
 
4.9%
3 5906
 
3.3%
4 4732
 
2.6%
Other values (3) 10580
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150000
83.3%
Uppercase Letter 30000
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71921
47.9%
1 19844
 
13.2%
2 17876
 
11.9%
6 10366
 
6.9%
5 8775
 
5.9%
3 5906
 
3.9%
4 4732
 
3.2%
7 4072
 
2.7%
8 3808
 
2.5%
9 2700
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
S 10000
33.3%
V 10000
33.3%
R 10000
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 150000
83.3%
Latin 30000
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71921
47.9%
1 19844
 
13.2%
2 17876
 
11.9%
6 10366
 
6.9%
5 8775
 
5.9%
3 5906
 
3.9%
4 4732
 
3.2%
7 4072
 
2.7%
8 3808
 
2.5%
9 2700
 
1.8%
Latin
ValueCountFrequency (%)
S 10000
33.3%
V 10000
33.3%
R 10000
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71921
40.0%
1 19844
 
11.0%
2 17876
 
9.9%
6 10366
 
5.8%
S 10000
 
5.6%
V 10000
 
5.6%
R 10000
 
5.6%
5 8775
 
4.9%
3 5906
 
3.3%
4 4732
 
2.6%
Other values (3) 10580
 
5.9%

입력년도
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10000
100.0%

Length

2023-12-11T12:53:56.912344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:53:57.033217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

X좌표
Real number (ℝ)

Distinct9913
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean198233.84
Minimum182362.2
Maximum215250.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:53:57.158644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182362.2
5-th percentile185961.39
Q1192420.88
median197750.22
Q3204391.06
95-th percentile211163.22
Maximum215250.45
Range32888.25
Interquartile range (IQR)11970.188

Descriptive statistics

Standard deviation7683.6521
Coefficient of variation (CV)0.038760547
Kurtosis-0.95590856
Mean198233.84
Median Absolute Deviation (MAD)5902.625
Skewness0.056592578
Sum1.9823384 × 109
Variance59038510
MonotonicityNot monotonic
2023-12-11T12:53:57.317381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206795.15 2
 
< 0.1%
211297.2 2
 
< 0.1%
196355.9 2
 
< 0.1%
193897.1 2
 
< 0.1%
194776.45 2
 
< 0.1%
191986.9 2
 
< 0.1%
191780.7 2
 
< 0.1%
194037.9 2
 
< 0.1%
193229.15 2
 
< 0.1%
205474.8 2
 
< 0.1%
Other values (9903) 9980
99.8%
ValueCountFrequency (%)
182362.2 1
< 0.1%
182476.15 1
< 0.1%
182501.65 1
< 0.1%
182503.55 1
< 0.1%
182528.6 1
< 0.1%
182548.75 1
< 0.1%
182569.5 1
< 0.1%
182897.6 1
< 0.1%
182912.15 1
< 0.1%
182912.3 1
< 0.1%
ValueCountFrequency (%)
215250.45 1
< 0.1%
215113.0 1
< 0.1%
215095.3 1
< 0.1%
214982.55 1
< 0.1%
214912.35 1
< 0.1%
214901.0 1
< 0.1%
214613.3 1
< 0.1%
214427.7 1
< 0.1%
214358.75 1
< 0.1%
214316.4 1
< 0.1%

Y좌표
Real number (ℝ)

Distinct9856
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean449494.83
Minimum437231.6
Maximum465813.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:53:57.499126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437231.6
5-th percentile441774.75
Q1444810.4
median449458.38
Q3453274.05
95-th percentile458581.81
Maximum465813.6
Range28582
Interquartile range (IQR)8463.65

Descriptive statistics

Standard deviation5472.0966
Coefficient of variation (CV)0.012173881
Kurtosis-0.47712314
Mean449494.83
Median Absolute Deviation (MAD)4273.825
Skewness0.34011461
Sum4.4949483 × 109
Variance29943841
MonotonicityNot monotonic
2023-12-11T12:53:57.658958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443841.8 3
 
< 0.1%
449404.1 2
 
< 0.1%
455383.45 2
 
< 0.1%
453376.05 2
 
< 0.1%
448845.45 2
 
< 0.1%
441999.45 2
 
< 0.1%
443651.05 2
 
< 0.1%
448535.7 2
 
< 0.1%
445210.75 2
 
< 0.1%
458116.8 2
 
< 0.1%
Other values (9846) 9979
99.8%
ValueCountFrequency (%)
437231.6 1
< 0.1%
437358.9 1
< 0.1%
437390.1 1
< 0.1%
437639.1 1
< 0.1%
437745.8 1
< 0.1%
437849.2 1
< 0.1%
437976.95 1
< 0.1%
438123.35 1
< 0.1%
438177.9 1
< 0.1%
438192.75 1
< 0.1%
ValueCountFrequency (%)
465813.6 1
< 0.1%
465534.25 1
< 0.1%
465526.5 1
< 0.1%
465459.2 1
< 0.1%
465361.05 1
< 0.1%
465299.8 1
< 0.1%
465283.05 1
< 0.1%
465217.85 1
< 0.1%
465212.7 1
< 0.1%
464972.8 1
< 0.1%

Interactions

2023-12-11T12:53:54.511196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:53.318876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:53.757012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:54.697093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:53.429396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:54.049876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:54.856231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:53.532441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:54.287943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:53:57.782982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번X좌표Y좌표
순번1.0000.1580.150
X좌표0.1581.0000.646
Y좌표0.1500.6461.000
2023-12-11T12:53:57.895384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번X좌표Y좌표
순번1.000-0.0800.016
X좌표-0.0801.0000.162
Y좌표0.0160.1621.000

Missing values

2023-12-11T12:53:55.060051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:53:55.219220image/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

순번굴착예정지 일련번호입력년도X좌표Y좌표
1636613877SVR001200605100087195065.85442175.3
2859034721SVR001200504060025198243.9453744.35
1518620751SVR001200606230037201698.95452207.25
1633221752SVR001200607060058199656.8451761.4
948813768SVR001200605090011199626.05451103.8
57867382SVR001200603280014204098.85452436.85
2988630058SVR001200503140098188165.7449191.2
3799247756SVR001200506140081194538.15442795.65
1926124856SVR001200607260060190659.9453811.1
3820346672SVR001200507290035186906.6450586.65
순번굴착예정지 일련번호입력년도X좌표Y좌표
3036535815SVR001200505090058203011.4455494.05
2136021222SVR001200606290083192281.8457281.4
84159964SVR001200604140158191418.85451450.75
2825137815SVR001200504150189197477.15448130.05
3847641621SVR001200506130098193951.45444227.35
2245427425SVR001200608090085195385.2443068.35
2717937989SVR001200505230037197176.8451788.95
2717136600SVR001200505090197183357.15452717.6
2926936531SVR001200503060003204704.75456768.75
2396332106SVR001200504110093204459.75451941.95