Overview

Dataset statistics

Number of variables11
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory99.4 B

Variable types

Numeric4
Categorical7

Dataset

Description샘플 데이터
Author경기콘텐츠진흥원
URLhttps://bigdata-region.kr/#/dataset/432cdb05-8b23-4dc4-9602-e6b475e03719

Alerts

시도 코드 has constant value ""Constant
시도명 has constant value ""Constant
시군구 코드 has constant value ""Constant
시군구명 has constant value ""Constant
행정동 코드 has constant value ""Constant
행정동명 has constant value ""Constant
블록 ID is highly overall correlated with 중심 X좌표 and 1 other fieldsHigh correlation
중심 X좌표 is highly overall correlated with 블록 IDHigh correlation
경계길이 is highly overall correlated with 블럭면적High correlation
블럭면적 is highly overall correlated with 블록 ID and 1 other fieldsHigh correlation
중심 X좌표 has unique valuesUnique
중심 Y좌표 has unique valuesUnique

Reproduction

Analysis started2023-12-10 14:07:36.562761
Analysis finished2023-12-10 14:07:42.103081
Duration5.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

블록 ID
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.105051 × 1019
Minimum3.105051 × 1019
Maximum3.105051 × 1019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:07:42.218722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.105051 × 1019
5-th percentile3.105051 × 1019
Q13.105051 × 1019
median3.105051 × 1019
Q33.105051 × 1019
95-th percentile3.105051 × 1019
Maximum3.105051 × 1019
Range1.0006 × 1011
Interquartile range (IQR)9.1775017 × 109

Descriptive statistics

Standard deviation4.2774288 × 1010
Coefficient of variation (CV)1.3775712 × 10-9
Kurtosis-0.26790787
Mean3.105051 × 1019
Median Absolute Deviation (MAD)35002368
Skewness1.3200464
Sum9.315153 × 1020
Variance1.8296397 × 1021
MonotonicityIncreasing
2023-12-10T23:07:42.503184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
3.10505101001e+19 12
40.0%
3.105051010001e+19 1
 
3.3%
3.105051011101e+19 1
 
3.3%
3.105051020007e+19 1
 
3.3%
3.105051020006e+19 1
 
3.3%
3.105051020005e+19 1
 
3.3%
3.105051020004e+19 1
 
3.3%
3.105051020003e+19 1
 
3.3%
3.105051020002e+19 1
 
3.3%
3.105051020001e+19 1
 
3.3%
Other values (9) 9
30.0%
ValueCountFrequency (%)
3.105051010001e+19 1
 
3.3%
3.105051010002e+19 1
 
3.3%
3.105051010003e+19 1
 
3.3%
3.105051010004e+19 1
 
3.3%
3.105051010005e+19 1
 
3.3%
3.105051010006e+19 1
 
3.3%
3.105051010007e+19 1
 
3.3%
3.105051010008e+19 1
 
3.3%
3.105051010009e+19 1
 
3.3%
3.10505101001e+19 12
40.0%
ValueCountFrequency (%)
3.105051020007e+19 1
 
3.3%
3.105051020006e+19 1
 
3.3%
3.105051020005e+19 1
 
3.3%
3.105051020004e+19 1
 
3.3%
3.105051020003e+19 1
 
3.3%
3.105051020002e+19 1
 
3.3%
3.105051020001e+19 1
 
3.3%
3.105051011101e+19 1
 
3.3%
3.105051010401e+19 1
 
3.3%
3.10505101001e+19 12
40.0%

중심 X좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.78176
Minimum126.77738
Maximum126.78859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:07:42.877319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.77738
5-th percentile126.77789
Q1126.77901
median126.78129
Q3126.78284
95-th percentile126.78768
Maximum126.78859
Range0.011207022
Interquartile range (IQR)0.0038335577

Descriptive statistics

Standard deviation0.0032733902
Coefficient of variation (CV)2.5819095 × 10-5
Kurtosis-0.51621665
Mean126.78176
Median Absolute Deviation (MAD)0.0021107954
Skewness0.72041684
Sum3803.4528
Variance1.0715084 × 10-5
MonotonicityNot monotonic
2023-12-10T23:07:43.200646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
126.778328283 1
 
3.3%
126.7799110184 1
 
3.3%
126.7870780408 1
 
3.3%
126.7876201162 1
 
3.3%
126.7877338394 1
 
3.3%
126.7866091981 1
 
3.3%
126.7885908072 1
 
3.3%
126.7847217277 1
 
3.3%
126.7854156459 1
 
3.3%
126.7779612391 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
126.7773837851 1
3.3%
126.7778294023 1
3.3%
126.7779612391 1
3.3%
126.778328283 1
3.3%
126.7784151073 1
3.3%
126.778623646 1
3.3%
126.7787141687 1
3.3%
126.778839907 1
3.3%
126.7795168038 1
3.3%
126.7799110184 1
3.3%
ValueCountFrequency (%)
126.7885908072 1
3.3%
126.7877338394 1
3.3%
126.7876201162 1
3.3%
126.7870780408 1
3.3%
126.7866091981 1
3.3%
126.7854156459 1
3.3%
126.7847217277 1
3.3%
126.7828445056 1
3.3%
126.7828372388 1
3.3%
126.7821330607 1
3.3%

중심 Y좌표
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.486248
Minimum37.484693
Maximum37.488659
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:07:43.486981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.484693
5-th percentile37.484725
Q137.485342
median37.486281
Q337.486885
95-th percentile37.488039
Maximum37.488659
Range0.0039663032
Interquartile range (IQR)0.0015433727

Descriptive statistics

Standard deviation0.0011116903
Coefficient of variation (CV)2.9655949 × 10-5
Kurtosis-0.70718164
Mean37.486248
Median Absolute Deviation (MAD)0.00086187635
Skewness0.38508228
Sum1124.5874
Variance1.2358552 × 10-6
MonotonicityNot monotonic
2023-12-10T23:07:43.765982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.4851743298 1
 
3.3%
37.4866403827 1
 
3.3%
37.4857601656 1
 
3.3%
37.4886591084 1
 
3.3%
37.4876805148 1
 
3.3%
37.4846928052 1
 
3.3%
37.485566803 1
 
3.3%
37.4867083482 1
 
3.3%
37.4859447253 1
 
3.3%
37.4868866146 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
37.4846928052 1
3.3%
37.4847037338 1
3.3%
37.4847518149 1
3.3%
37.4848265634 1
3.3%
37.4849789253 1
3.3%
37.4851163161 1
3.3%
37.4851743298 1
3.3%
37.4853116361 1
3.3%
37.4854324842 1
3.3%
37.485566803 1
3.3%
ValueCountFrequency (%)
37.4886591084 1
3.3%
37.4882148648 1
3.3%
37.487823786 1
3.3%
37.4877145625 1
3.3%
37.4876805148 1
3.3%
37.4874404501 1
3.3%
37.4871562369 1
3.3%
37.4868866146 1
3.3%
37.4868810396 1
3.3%
37.4867083482 1
3.3%

시도 코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
41
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41
2nd row41
3rd row41
4th row41
5th row41

Common Values

ValueCountFrequency (%)
41 30
100.0%

Length

2023-12-10T23:07:43.994869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:44.141342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41 30
100.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 30
100.0%

Length

2023-12-10T23:07:44.295716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:44.468480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구 코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
41190
30 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41190
2nd row41190
3rd row41190
4th row41190
5th row41190

Common Values

ValueCountFrequency (%)
41190 30
100.0%

Length

2023-12-10T23:07:44.621712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:44.810177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41190 30
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
부천시
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부천시 30
100.0%

Length

2023-12-10T23:07:45.064972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:45.274656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부천시 30
100.0%

행정동 코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
4119051000
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4119051000
2nd row4119051000
3rd row4119051000
4th row4119051000
5th row4119051000

Common Values

ValueCountFrequency (%)
4119051000 30
100.0%

Length

2023-12-10T23:07:45.450160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:45.677659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4119051000 30
100.0%

행정동명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
심곡2동
30 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row심곡2동
2nd row심곡2동
3rd row심곡2동
4th row심곡2동
5th row심곡2동

Common Values

ValueCountFrequency (%)
심곡2동 30
100.0%

Length

2023-12-10T23:07:45.839736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:46.066206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
심곡2동 30
100.0%

블럭면적
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0.01
15 
0.02
7 
0.0
6 
0.03
2 

Length

Max length4
Median length4
Mean length3.8
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.01
2nd row0.01
3rd row0.02
4th row0.03
5th row0.02

Common Values

ValueCountFrequency (%)
0.01 15
50.0%
0.02 7
23.3%
0.0 6
 
20.0%
0.03 2
 
6.7%

Length

2023-12-10T23:07:46.320885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:07:46.477446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.01 15
50.0%
0.02 7
23.3%
0.0 6
 
20.0%
0.03 2
 
6.7%

경계길이
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.50433333
Minimum0.22
Maximum0.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:07:46.650589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.22
5-th percentile0.239
Q10.33
median0.45
Q30.6775
95-th percentile0.88
Maximum0.89
Range0.67
Interquartile range (IQR)0.3475

Descriptive statistics

Standard deviation0.21258156
Coefficient of variation (CV)0.42151003
Kurtosis-0.99673104
Mean0.50433333
Median Absolute Deviation (MAD)0.16
Skewness0.50857674
Sum15.13
Variance0.04519092
MonotonicityNot monotonic
2023-12-10T23:07:46.866737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.88 2
 
6.7%
0.38 2
 
6.7%
0.33 2
 
6.7%
0.43 2
 
6.7%
0.89 1
 
3.3%
0.3 1
 
3.3%
0.49 1
 
3.3%
0.48 1
 
3.3%
0.77 1
 
3.3%
0.63 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
0.22 1
3.3%
0.23 1
3.3%
0.25 1
3.3%
0.27 1
3.3%
0.29 1
3.3%
0.3 1
3.3%
0.31 1
3.3%
0.33 2
6.7%
0.36 1
3.3%
0.38 2
6.7%
ValueCountFrequency (%)
0.89 1
3.3%
0.88 2
6.7%
0.84 1
3.3%
0.77 1
3.3%
0.72 1
3.3%
0.7 1
3.3%
0.69 1
3.3%
0.64 1
3.3%
0.63 1
3.3%
0.61 1
3.3%

Interactions

2023-12-10T23:07:40.403865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:36.879764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:38.571901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:39.486831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:40.792807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:37.614876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:38.887526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:39.794813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:41.107123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:37.861039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:39.153119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:39.977060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:41.361449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:38.253180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:39.352325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:07:40.213876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:07:47.030408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
블록 ID중심 X좌표중심 Y좌표블럭면적경계길이
블록 ID1.0000.9220.4340.0730.555
중심 X좌표0.9221.0000.3530.0000.677
중심 Y좌표0.4340.3531.0000.6310.547
블럭면적0.0730.0000.6311.0000.858
경계길이0.5550.6770.5470.8581.000
2023-12-10T23:07:47.553406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
블록 ID중심 X좌표중심 Y좌표경계길이블럭면적
블록 ID1.0000.709-0.092-0.1411.000
중심 X좌표0.7091.000-0.0930.2200.000
중심 Y좌표-0.092-0.0931.0000.1750.366
경계길이-0.1410.2200.1751.0000.618
블럭면적1.0000.0000.3660.6181.000

Missing values

2023-12-10T23:07:41.726171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:07:42.009197image/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

블록 ID중심 X좌표중심 Y좌표시도 코드시도명시군구 코드시군구명행정동 코드행정동명블럭면적경계길이
031050510100010000001126.77832837.48517441경기도41190부천시4119051000심곡2동0.010.89
131050510100020000001126.77782937.48771541경기도41190부천시4119051000심곡2동0.010.43
231050510100030000001126.78035437.48782441경기도41190부천시4119051000심곡2동0.020.7
331050510100040000001126.78189137.4874441경기도41190부천시4119051000심곡2동0.030.88
431050510100050000001126.77871437.48628141경기도41190부천시4119051000심곡2동0.020.69
531050510100060000001126.7788437.48715641경기도41190부천시4119051000심곡2동0.010.44
631050510100070000001126.77862437.48821541경기도41190부천시4119051000심곡2동0.020.61
731050510100080000001126.77738437.48628141경기도41190부천시4119051000심곡2동0.020.64
831050510100090000001126.77996537.48584641경기도41190부천시4119051000심곡2동0.020.72
931050510100100000001126.78180237.48470441경기도41190부천시4119051000심곡2동0.010.38
블록 ID중심 X좌표중심 Y좌표시도 코드시도명시군구 코드시군구명행정동 코드행정동명블럭면적경계길이
2031050510100100000012126.78077637.48648641경기도41190부천시4119051000심곡2동0.010.36
2131050510104010000001126.77841537.48497941경기도41190부천시4119051000심곡2동0.00.27
2231050510111010000001126.77796137.48688741경기도41190부천시4119051000심곡2동0.00.23
2331050510200010000001126.78541637.48594541경기도41190부천시4119051000심곡2동0.020.84
2431050510200020000001126.78472237.48670841경기도41190부천시4119051000심곡2동0.010.5
2531050510200030000001126.78859137.48556741경기도41190부천시4119051000심곡2동0.010.63
2631050510200040000001126.78660937.48469341경기도41190부천시4119051000심곡2동0.020.77
2731050510200050000001126.78773437.48768141경기도41190부천시4119051000심곡2동0.010.48
2831050510200060000001126.7876237.48865941경기도41190부천시4119051000심곡2동0.030.88
2931050510200070000001126.78707837.4857641경기도41190부천시4119051000심곡2동0.010.49