Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory673.8 KiB
Average record size in memory69.0 B

Variable types

Numeric4
Categorical3

Dataset

Description인천광역시 강화군 개별공시지가 정보
Author인천광역시 강화군
URLhttps://www.data.go.kr/data/15002749/fileData.do

Alerts

리 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
법정동 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
번호 is highly overall correlated with 법정동 and 1 other fieldsHigh correlation
구분 is highly imbalanced (54.9%)Imbalance
번호 has unique valuesUnique
부번 has 2870 (28.7%) zerosZeros

Reproduction

Analysis started2023-12-12 10:12:51.969668
Analysis finished2023-12-12 10:12:55.000897
Duration3.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49450.406
Minimum2
Maximum100004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:12:55.093637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4749.65
Q124467
median48853.5
Q373900.25
95-th percentile94651.5
Maximum100004
Range100002
Interquartile range (IQR)49433.25

Descriptive statistics

Standard deviation28732.402
Coefficient of variation (CV)0.5810347
Kurtosis-1.1823436
Mean49450.406
Median Absolute Deviation (MAD)24733.5
Skewness0.028331748
Sum4.9450406 × 108
Variance8.2555092 × 108
MonotonicityNot monotonic
2023-12-12T19:12:55.236693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74321 1
 
< 0.1%
22071 1
 
< 0.1%
40953 1
 
< 0.1%
87266 1
 
< 0.1%
20934 1
 
< 0.1%
43025 1
 
< 0.1%
62808 1
 
< 0.1%
39470 1
 
< 0.1%
88470 1
 
< 0.1%
13651 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
9 1
< 0.1%
19 1
< 0.1%
43 1
< 0.1%
58 1
< 0.1%
61 1
< 0.1%
64 1
< 0.1%
80 1
< 0.1%
92 1
< 0.1%
93 1
< 0.1%
ValueCountFrequency (%)
100004 1
< 0.1%
100001 1
< 0.1%
99981 1
< 0.1%
99975 1
< 0.1%
99972 1
< 0.1%
99965 1
< 0.1%
99964 1
< 0.1%
99961 1
< 0.1%
99956 1
< 0.1%
99952 1
< 0.1%

법정동
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
길상면
2523 
강화읍
2493 
불은면
2183 
선원면
1471 
화도면
1330 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row길상면
2nd row화도면
3rd row길상면
4th row선원면
5th row불은면

Common Values

ValueCountFrequency (%)
길상면 2523
25.2%
강화읍 2493
24.9%
불은면 2183
21.8%
선원면 1471
14.7%
화도면 1330
13.3%

Length

2023-12-12T19:12:55.394222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:55.534468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
길상면 2523
25.2%
강화읍 2493
24.9%
불은면 2183
21.8%
선원면 1471
14.7%
화도면 1330
13.3%

리
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
선두리
 
593
온수리
 
518
길직리
 
506
내리
 
419
두운리
 
405
Other values (30)
7559 

Length

Max length4
Median length3
Mean length2.9527
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row초지리
2nd row덕포리
3rd row온수리
4th row창리
5th row삼동암리

Common Values

ValueCountFrequency (%)
선두리 593
 
5.9%
온수리 518
 
5.2%
길직리 506
 
5.1%
내리 419
 
4.2%
두운리 405
 
4.0%
초지리 400
 
4.0%
삼동암리 366
 
3.7%
장흥리 355
 
3.5%
삼성리 352
 
3.5%
관청리 341
 
3.4%
Other values (25) 5745
57.5%

Length

2023-12-12T19:12:55.675486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
선두리 593
 
5.9%
온수리 518
 
5.2%
길직리 506
 
5.1%
내리 419
 
4.2%
두운리 405
 
4.0%
초지리 400
 
4.0%
삼동암리 366
 
3.7%
장흥리 355
 
3.5%
삼성리 352
 
3.5%
관청리 341
 
3.4%
Other values (25) 5745
57.5%

구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9055 
2
945 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 9055
90.5%
2 945
 
9.4%

Length

2023-12-12T19:12:55.833522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:55.934669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9055
90.5%
2 945
 
9.4%

본번
Real number (ℝ)

Distinct1616
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean542.7775
Minimum1
Maximum2599
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:12:56.073967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile31
Q1190
median467
Q3811
95-th percentile1306
Maximum2599
Range2598
Interquartile range (IQR)621

Descriptive statistics

Standard deviation425.885
Coefficient of variation (CV)0.78464012
Kurtosis1.2124926
Mean542.7775
Median Absolute Deviation (MAD)300
Skewness1.0242112
Sum5427775
Variance181378.03
MonotonicityNot monotonic
2023-12-12T19:12:56.583987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 40
 
0.4%
14 28
 
0.3%
161 27
 
0.3%
809 25
 
0.2%
241 24
 
0.2%
687 24
 
0.2%
181 24
 
0.2%
685 23
 
0.2%
449 23
 
0.2%
1251 23
 
0.2%
Other values (1606) 9739
97.4%
ValueCountFrequency (%)
1 18
0.2%
2 13
0.1%
3 18
0.2%
4 18
0.2%
5 20
0.2%
6 14
0.1%
7 21
0.2%
8 9
0.1%
9 15
0.1%
10 21
0.2%
ValueCountFrequency (%)
2599 1
 
< 0.1%
2594 3
< 0.1%
2588 1
 
< 0.1%
2587 1
 
< 0.1%
2579 1
 
< 0.1%
2568 1
 
< 0.1%
2564 1
 
< 0.1%
2561 1
 
< 0.1%
2557 1
 
< 0.1%
2549 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct159
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6038
Minimum0
Maximum644
Zeros2870
Zeros (%)28.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:12:56.767553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q36
95-th percentile29
Maximum644
Range644
Interquartile range (IQR)6

Descriptive statistics

Standard deviation27.354412
Coefficient of variation (CV)3.597466
Kurtosis257.82191
Mean7.6038
Median Absolute Deviation (MAD)2
Skewness14.108411
Sum76038
Variance748.26385
MonotonicityNot monotonic
2023-12-12T19:12:56.930321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2870
28.7%
1 1536
15.4%
2 1147
 
11.5%
3 747
 
7.5%
4 550
 
5.5%
5 428
 
4.3%
6 328
 
3.3%
7 281
 
2.8%
8 210
 
2.1%
10 170
 
1.7%
Other values (149) 1733
17.3%
ValueCountFrequency (%)
0 2870
28.7%
1 1536
15.4%
2 1147
 
11.5%
3 747
 
7.5%
4 550
 
5.5%
5 428
 
4.3%
6 328
 
3.3%
7 281
 
2.8%
8 210
 
2.1%
9 166
 
1.7%
ValueCountFrequency (%)
644 1
< 0.1%
614 1
< 0.1%
609 1
< 0.1%
605 1
< 0.1%
590 1
< 0.1%
575 1
< 0.1%
562 1
< 0.1%
561 1
< 0.1%
536 1
< 0.1%
524 1
< 0.1%

결정지가
Real number (ℝ)

Distinct2226
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80556.763
Minimum693
Maximum2348000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:12:57.083149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum693
5-th percentile8250
Q125100
median56950
Q398300
95-th percentile210500
Maximum2348000
Range2347307
Interquartile range (IQR)73200

Descriptive statistics

Standard deviation121270.17
Coefficient of variation (CV)1.5054003
Kurtosis113.07325
Mean80556.763
Median Absolute Deviation (MAD)33450
Skewness8.4159608
Sum8.0556763 × 108
Variance1.4706455 × 1010
MonotonicityNot monotonic
2023-12-12T19:12:57.251096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26000 171
 
1.7%
8250 136
 
1.4%
25000 133
 
1.3%
8580 102
 
1.0%
26500 77
 
0.8%
25700 75
 
0.8%
26700 53
 
0.5%
19100 52
 
0.5%
24700 51
 
0.5%
25400 49
 
0.5%
Other values (2216) 9101
91.0%
ValueCountFrequency (%)
693 1
 
< 0.1%
719 2
< 0.1%
765 1
 
< 0.1%
772 1
 
< 0.1%
1050 1
 
< 0.1%
1080 1
 
< 0.1%
1130 1
 
< 0.1%
1140 1
 
< 0.1%
1150 4
< 0.1%
1170 1
 
< 0.1%
ValueCountFrequency (%)
2348000 1
< 0.1%
2337000 1
< 0.1%
2300000 1
< 0.1%
2280000 1
< 0.1%
2249000 1
< 0.1%
2231000 1
< 0.1%
2201000 1
< 0.1%
2074000 1
< 0.1%
1836000 1
< 0.1%
1690000 1
< 0.1%

Interactions

2023-12-12T19:12:54.347225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:52.954018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:53.442189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:53.872216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:54.447436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:53.064974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:53.550508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:54.002045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:54.534780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:53.190464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:53.657989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:54.127211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:54.643024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:53.308285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:53.768469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:54.245729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:12:57.351014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호법정동리구분본번부번결정지가
번호1.0000.9960.9950.1240.4290.1850.295
법정동0.9961.0001.0000.0530.3860.1200.235
리0.9951.0001.0000.1570.6110.2440.350
구분0.1240.0530.1571.0000.5290.0200.076
본번0.4290.3860.6110.5291.0000.1830.032
부번0.1850.1200.2440.0200.1831.0000.135
결정지가0.2950.2350.3500.0760.0320.1351.000
2023-12-12T19:12:57.473080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
리법정동구분
리1.0000.9980.132
법정동0.9981.0000.065
구분0.1320.0651.000
2023-12-12T19:12:57.594968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호본번부번결정지가법정동리구분
번호1.0000.160-0.011-0.1380.9110.9370.095
본번0.1601.000-0.0640.0970.1700.2570.407
부번-0.011-0.0641.0000.1440.0500.0860.015
결정지가-0.1380.0970.1441.0000.1000.1270.058
법정동0.9110.1700.0500.1001.0000.9980.065
리0.9370.2570.0860.1270.9981.0000.132
구분0.0950.4070.0150.0580.0650.1321.000

Missing values

2023-12-12T19:12:54.789561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:12:54.938574image/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

번호법정동리구분본번부번결정지가
7431774321길상면초지리1791380200
9683196836화도면덕포리11293091500
6535465358길상면온수리17329649200
3447234474선원면창리2177024700
5263852641불은면삼동암리1884324400
7501675020길상면초지리11134087700
4281842821불은면고능리112399000
2679026792선원면연리13882525900
5552455527불은면삼성리1433323000
6909669100길상면선두리110052152600
번호법정동리구분본번부번결정지가
5781057813불은면삼성리22203770
6769967703길상면선두리182728107100
7424774251길상면초지리1745083800
5963159634불은면덕성리1571059700
3027130273선원면지산리1871472000
9432194326화도면문산리1566081000
8342983433길상면길직리1771595800
4616046163불은면오두리1338159800
4620546208불은면오두리1355151000
7961579619길상면장흥리136424128000