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,위도,경도
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-2776/S/1/datasetView.do

Alerts

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

Reproduction

Analysis started2023-12-11 09:07:54.333026
Analysis finished2023-12-11 09:07:56.105548
Duration1.77 second
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%
Mean23262.51
Minimum3
Maximum47534
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T18:07:56.200766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile2380.95
Q111605.75
median23334.5
Q334595.5
95-th percentile45162.1
Maximum47534
Range47531
Interquartile range (IQR)22989.75

Descriptive statistics

Standard deviation13430.389
Coefficient of variation (CV)0.57734051
Kurtosis-1.1567348
Mean23262.51
Median Absolute Deviation (MAD)11488.5
Skewness0.019714402
Sum2.326251 × 108
Variance1.8037535 × 108
MonotonicityNot monotonic
2023-12-11T18:07:56.399806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43654 1
 
< 0.1%
3300 1
 
< 0.1%
7169 1
 
< 0.1%
1269 1
 
< 0.1%
39708 1
 
< 0.1%
35132 1
 
< 0.1%
27452 1
 
< 0.1%
5590 1
 
< 0.1%
26861 1
 
< 0.1%
16424 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
36 1
< 0.1%
42 1
< 0.1%
44 1
< 0.1%
50 1
< 0.1%
51 1
< 0.1%
52 1
< 0.1%
59 1
< 0.1%
ValueCountFrequency (%)
47534 1
< 0.1%
47531 1
< 0.1%
47524 1
< 0.1%
47522 1
< 0.1%
47518 1
< 0.1%
47512 1
< 0.1%
47507 1
< 0.1%
47506 1
< 0.1%
47501 1
< 0.1%
47491 1
< 0.1%

굴착예정지 일련번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T18:07:56.954469image/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 rowSVR001200505020092
2nd rowSVR001200504120036
3rd rowSVR001200506210060
4th rowSVR001200505020325
5th rowSVR001200505020417
ValueCountFrequency (%)
svr001200505020092 1
 
< 0.1%
svr001200604190094 1
 
< 0.1%
svr001200505160160 1
 
< 0.1%
svr001200602270196 1
 
< 0.1%
svr001200603240078 1
 
< 0.1%
svr001200602270128 1
 
< 0.1%
svr001200507130025 1
 
< 0.1%
svr001200504070166 1
 
< 0.1%
svr003200606090007 1
 
< 0.1%
svr001200602280119 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-11T18:07:57.355005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71720
39.8%
1 19902
 
11.1%
2 18207
 
10.1%
6 10540
 
5.9%
S 10000
 
5.6%
V 10000
 
5.6%
R 10000
 
5.6%
5 8520
 
4.7%
3 5817
 
3.2%
4 4889
 
2.7%
Other values (3) 10405
 
5.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71720
47.8%
1 19902
 
13.3%
2 18207
 
12.1%
6 10540
 
7.0%
5 8520
 
5.7%
3 5817
 
3.9%
4 4889
 
3.3%
7 4110
 
2.7%
8 3660
 
2.4%
9 2635
 
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 71720
47.8%
1 19902
 
13.3%
2 18207
 
12.1%
6 10540
 
7.0%
5 8520
 
5.7%
3 5817
 
3.9%
4 4889
 
3.3%
7 4110
 
2.7%
8 3660
 
2.4%
9 2635
 
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 71720
39.8%
1 19902
 
11.1%
2 18207
 
10.1%
6 10540
 
5.9%
S 10000
 
5.6%
V 10000
 
5.6%
R 10000
 
5.6%
5 8520
 
4.7%
3 5817
 
3.2%
4 4889
 
2.7%
Other values (3) 10405
 
5.8%

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

2023-12-11T18:07:57.539363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:07:57.673650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

위도
Real number (ℝ)

Distinct9963
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.545734
Minimum37.434345
Maximum37.687916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T18:07:57.799197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.434345
5-th percentile37.475725
Q137.504005
median37.545239
Q337.579416
95-th percentile37.62781
Maximum37.687916
Range0.2535705
Interquartile range (IQR)0.075410325

Descriptive statistics

Standard deviation0.048957807
Coefficient of variation (CV)0.0013039513
Kurtosis-0.51063922
Mean37.545734
Median Absolute Deviation (MAD)0.03810195
Skewness0.32315747
Sum375457.34
Variance0.0023968669
MonotonicityNot monotonic
2023-12-11T18:07:58.004739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5387187 2
 
< 0.1%
37.565593 2
 
< 0.1%
37.5261479 2
 
< 0.1%
37.4777679 2
 
< 0.1%
37.4930376 2
 
< 0.1%
37.5304983 2
 
< 0.1%
37.4761706 2
 
< 0.1%
37.5101011 2
 
< 0.1%
37.4846065 2
 
< 0.1%
37.5724992 2
 
< 0.1%
Other values (9953) 9980
99.8%
ValueCountFrequency (%)
37.4343453 1
< 0.1%
37.4351364 1
< 0.1%
37.4356892 1
< 0.1%
37.438889 1
< 0.1%
37.4392282 1
< 0.1%
37.4393071 1
< 0.1%
37.4405227 1
< 0.1%
37.44115 1
< 0.1%
37.4424638 1
< 0.1%
37.4430644 1
< 0.1%
ValueCountFrequency (%)
37.6879158 1
< 0.1%
37.6865744 1
< 0.1%
37.6862277 1
< 0.1%
37.6858791 1
< 0.1%
37.6830946 1
< 0.1%
37.6807347 1
< 0.1%
37.6804749 1
< 0.1%
37.6804297 1
< 0.1%
37.6801979 1
< 0.1%
37.6800888 1
< 0.1%

경도
Real number (ℝ)

Distinct9966
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98035
Minimum126.80021
Maximum127.17432
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T18:07:58.185233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.80021
5-th percentile126.84148
Q1126.91493
median126.97714
Q3127.04776
95-th percentile127.12667
Maximum127.17432
Range0.3741096
Interquartile range (IQR)0.13282962

Descriptive statistics

Standard deviation0.086526978
Coefficient of variation (CV)0.00068142021
Kurtosis-0.92719216
Mean126.98035
Median Absolute Deviation (MAD)0.06536375
Skewness0.059827709
Sum1269803.5
Variance0.0074869179
MonotonicityNot monotonic
2023-12-11T18:07:58.351783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0229623 2
 
< 0.1%
127.0752362 2
 
< 0.1%
127.0010353 2
 
< 0.1%
126.9146314 2
 
< 0.1%
126.8636348 2
 
< 0.1%
127.0821406 2
 
< 0.1%
126.931113 2
 
< 0.1%
126.9226898 2
 
< 0.1%
126.9268087 2
 
< 0.1%
126.9281611 2
 
< 0.1%
Other values (9956) 9980
99.8%
ValueCountFrequency (%)
126.8002146 1
< 0.1%
126.801291 1
< 0.1%
126.8019341 1
< 0.1%
126.8022296 1
< 0.1%
126.8025869 1
< 0.1%
126.8027765 1
< 0.1%
126.8029461 1
< 0.1%
126.8051267 1
< 0.1%
126.806423 1
< 0.1%
126.8065822 1
< 0.1%
ValueCountFrequency (%)
127.1743242 1
< 0.1%
127.1734866 1
< 0.1%
127.1733051 1
< 0.1%
127.173238 1
< 0.1%
127.1723066 1
< 0.1%
127.1717347 1
< 0.1%
127.1715368 1
< 0.1%
127.1711769 1
< 0.1%
127.1711616 1
< 0.1%
127.1708476 1
< 0.1%

Interactions

2023-12-11T18:07:55.568283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:07:54.830017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:07:55.216645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:07:55.668284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:07:54.973383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:07:55.335310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:07:55.799968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:07:55.103684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:07:55.443107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:07:58.455196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도
순번1.0000.1660.160
위도0.1661.0000.639
경도0.1600.6391.000
2023-12-11T18:07:58.555216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도
순번1.0000.033-0.084
위도0.0331.0000.148
경도-0.0840.1481.000

Missing values

2023-12-11T18:07:55.941898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:07:56.052503image/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 일련번호입력년도위도경도
3616943654SVR00120050502009237.562675126.970216
2319327674SVR00120050412003637.622935126.917697
3135641990SVR00120050621006037.506392127.097553
2532835512SVR00120050502032537.516233126.836429
3262939148SVR00120050502041737.463061126.915328
1932821132SVR00120060710006037.512981126.85339
1885923011SVR00120060714008437.577839126.90455
988514770SVR00120060518000437.541442127.09712
1872224281SVR00120060802013137.490313126.881275
1192110827SVR00120060522010837.556745126.940045
순번굴착예정지 일련번호입력년도위도경도
2779431778SVR00320060227000637.479336126.88402
2731633608SVR00120050418031437.509858127.113941
1861725442SVR00120060721017737.467099126.921387
1283719016SVR00120060621011437.561466126.951365
30253897SVR00120060302014537.496718127.137082
2524936162SVR00120050520025037.482979126.88299
1298319072SVR00120060630012037.511248126.951219
3620844285SVR00120050822002237.492527126.843977
2394627276SVR00120060719007237.603322127.031686
2529836765SVR00120050415009137.55078126.837476