Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory110.0 B

Variable types

Numeric3
Categorical7
Text1
Boolean1

Dataset

Description밀양시 개별공시지가 입니다
Author경상남도 밀양시
URLhttps://www.data.go.kr/data/15002417/fileData.do

Alerts

기준년도 has constant value ""Constant
기준월 has constant value ""Constant
표준지여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
특수지구분코드 is highly overall correlated with 특수지구분명High correlation
특수지구분명 is highly overall correlated with 특수지구분코드High correlation
고유번호 is highly overall correlated with 법정동코드 and 1 other fieldsHigh correlation
법정동코드 is highly overall correlated with 고유번호 and 1 other fieldsHigh correlation
법정동명 is highly overall correlated with 고유번호 and 1 other fieldsHigh correlation
특수지구분코드 is highly imbalanced (76.9%)Imbalance
특수지구분명 is highly imbalanced (76.9%)Imbalance
공시일자 is highly imbalanced (89.6%)Imbalance

Reproduction

Analysis started2023-12-12 08:39:54.219310
Analysis finished2023-12-12 08:39:56.304642
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고유번호
Real number (ℝ)

HIGH CORRELATION 

Distinct9988
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8270211 × 1018
Minimum4.8270101 × 1018
Maximum4.827031 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:39:56.384524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.8270101 × 1018
5-th percentile4.8270102 × 1018
Q14.8270107 × 1018
median4.827025 × 1018
Q34.8270253 × 1018
95-th percentile4.827031 × 1018
Maximum4.827031 × 1018
Range2.0924004 × 1013
Interquartile range (IQR)1.4622 × 1013

Descriptive statistics

Standard deviation7.2164258 × 1012
Coefficient of variation (CV)1.4950061 × 10-6
Kurtosis-1.2262937
Mean4.8270211 × 1018
Median Absolute Deviation (MAD)2.9691515 × 1011
Skewness-0.68288007
Sum-4.918582 × 1018
Variance5.2076801 × 1025
MonotonicityNot monotonic
2023-12-12T17:39:56.541089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4827025025105530000 2
 
< 0.1%
4827010800105670008 2
 
< 0.1%
4827025028200030006 2
 
< 0.1%
4827010300101620001 2
 
< 0.1%
4827025033200370000 2
 
< 0.1%
4827010600103780004 2
 
< 0.1%
4827025029114720001 2
 
< 0.1%
4827031022104220001 2
 
< 0.1%
4827031022103290002 2
 
< 0.1%
4827010400103690018 2
 
< 0.1%
Other values (9978) 9980
99.8%
ValueCountFrequency (%)
4827010100100010002 1
< 0.1%
4827010100100090000 1
< 0.1%
4827010100100180000 1
< 0.1%
4827010100100210003 1
< 0.1%
4827010100100300006 1
< 0.1%
4827010100100320002 1
< 0.1%
4827010100100330004 1
< 0.1%
4827010100100340006 1
< 0.1%
4827010100100350005 1
< 0.1%
4827010100100350007 1
< 0.1%
ValueCountFrequency (%)
4827031024104180005 1
< 0.1%
4827031024103870002 1
< 0.1%
4827031024103810004 1
< 0.1%
4827031024103340000 1
< 0.1%
4827031024103330002 1
< 0.1%
4827031024103300000 1
< 0.1%
4827031024103230001 1
< 0.1%
4827031024102990008 1
< 0.1%
4827031024102990006 1
< 0.1%
4827031024102990004 1
< 0.1%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8270211 × 109
Minimum4.8270101 × 109
Maximum4.827031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:39:56.688761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.8270101 × 109
5-th percentile4.8270102 × 109
Q14.8270107 × 109
median4.827025 × 109
Q34.8270253 × 109
95-th percentile4.827031 × 109
Maximum4.827031 × 109
Range20924
Interquartile range (IQR)14622

Descriptive statistics

Standard deviation7216.4247
Coefficient of variation (CV)1.4950059 × 10-6
Kurtosis-1.2262934
Mean4.8270211 × 109
Median Absolute Deviation (MAD)297
Skewness-0.68287951
Sum4.8270211 × 1013
Variance52076786
MonotonicityNot monotonic
2023-12-12T17:39:56.857270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
4827010200 684
 
6.8%
4827010400 635
 
6.3%
4827025321 611
 
6.1%
4827010300 473
 
4.7%
4827010800 472
 
4.7%
4827025029 451
 
4.5%
4827025021 436
 
4.4%
4827025323 429
 
4.3%
4827025023 378
 
3.8%
4827025322 333
 
3.3%
Other values (23) 5098
51.0%
ValueCountFrequency (%)
4827010100 239
 
2.4%
4827010200 684
6.8%
4827010300 473
4.7%
4827010400 635
6.3%
4827010500 74
 
0.7%
4827010600 324
3.2%
4827010700 152
 
1.5%
4827010800 472
4.7%
4827025021 436
4.4%
4827025022 228
 
2.3%
ValueCountFrequency (%)
4827031024 94
 
0.9%
4827031023 117
 
1.2%
4827031022 281
2.8%
4827031021 219
2.2%
4827025328 136
 
1.4%
4827025327 270
2.7%
4827025326 158
 
1.6%
4827025325 258
2.6%
4827025324 275
2.8%
4827025323 429
4.3%

법정동명
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
내이동
 
684
삼문동
 
635
하남읍수산리
 
611
교동
 
473
가곡동
 
472
Other values (28)
7125 

Length

Max length7
Median length6
Mean length5.4532
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row삼랑진읍우곡리
2nd row삼랑진읍미전리
3rd row삼랑진읍우곡리
4th row삼랑진읍행곡리
5th row교동

Common Values

ValueCountFrequency (%)
내이동 684
 
6.8%
삼문동 635
 
6.3%
하남읍수산리 611
 
6.1%
교동 473
 
4.7%
가곡동 472
 
4.7%
삼랑진읍행곡리 451
 
4.5%
삼랑진읍송지리 436
 
4.4%
하남읍백산리 429
 
4.3%
삼랑진읍미전리 378
 
3.8%
하남읍명례리 333
 
3.3%
Other values (23) 5098
51.0%

Length

2023-12-12T17:39:57.021982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
내이동 684
 
6.8%
삼문동 635
 
6.3%
하남읍수산리 611
 
6.1%
교동 473
 
4.7%
가곡동 472
 
4.7%
삼랑진읍행곡리 451
 
4.5%
삼랑진읍송지리 436
 
4.4%
하남읍백산리 429
 
4.3%
삼랑진읍미전리 378
 
3.8%
하남읍명례리 333
 
3.3%
Other values (23) 5098
51.0%

특수지구분코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9331 
2
 
651
5
 
18

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 9331
93.3%
2 651
 
6.5%
5 18
 
0.2%

Length

2023-12-12T17:39:57.176547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:39:57.290677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9331
93.3%
2 651
 
6.5%
5 18
 
0.2%

특수지구분명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
9331 
산
 
651
가지번
 
18

Length

Max length3
Median length2
Mean length1.9367
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row일반
3rd row산
4th row일반
5th row일반

Common Values

ValueCountFrequency (%)
일반 9331
93.3%
산 651
 
6.5%
가지번 18
 
0.2%

Length

2023-12-12T17:39:57.423324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:39:57.567050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 9331
93.3%
산 651
 
6.5%
가지번 18
 
0.2%

지번
Text

Distinct7445
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T17:39:57.958667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.2614
Min length3

Characters and Unicode

Total characters52614
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5735 ?
Unique (%)57.4%

Sample

1st row647-1
2nd row7-3
3rd row243-5
4th row830-0
5th row815-2
ValueCountFrequency (%)
40-0 8
 
0.1%
24-1 8
 
0.1%
163-0 8
 
0.1%
31-0 7
 
0.1%
460-0 7
 
0.1%
120-0 6
 
0.1%
39-0 6
 
0.1%
261-0 6
 
0.1%
24-0 6
 
0.1%
407-0 6
 
0.1%
Other values (7435) 9932
99.3%
2023-12-12T17:39:58.552718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 10000
19.0%
1 7666
14.6%
0 5246
10.0%
2 4995
9.5%
3 4466
8.5%
4 4193
8.0%
6 3577
 
6.8%
5 3562
 
6.8%
7 3304
 
6.3%
8 3018
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42614
81.0%
Dash Punctuation 10000
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7666
18.0%
0 5246
12.3%
2 4995
11.7%
3 4466
10.5%
4 4193
9.8%
6 3577
8.4%
5 3562
8.4%
7 3304
7.8%
8 3018
 
7.1%
9 2587
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52614
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 10000
19.0%
1 7666
14.6%
0 5246
10.0%
2 4995
9.5%
3 4466
8.5%
4 4193
8.0%
6 3577
 
6.8%
5 3562
 
6.8%
7 3304
 
6.3%
8 3018
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52614
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 10000
19.0%
1 7666
14.6%
0 5246
10.0%
2 4995
9.5%
3 4466
8.5%
4 4193
8.0%
6 3577
 
6.8%
5 3562
 
6.8%
7 3304
 
6.3%
8 3018
 
5.7%

기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2018
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 10000
100.0%

Length

2023-12-12T17:39:58.705637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:39:58.806305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 10000
100.0%

기준월
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 10000
100.0%

Length

2023-12-12T17:39:58.926495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:39:59.054687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

공시지가
Real number (ℝ)

Distinct2793
Distinct (%)27.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117989.51
Minimum135
Maximum2483000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:39:59.182239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum135
5-th percentile2850
Q121100
median50400
Q3119000
95-th percentile460035
Maximum2483000
Range2482865
Interquartile range (IQR)97900

Descriptive statistics

Standard deviation199454.76
Coefficient of variation (CV)1.6904448
Kurtosis36.206782
Mean117989.51
Median Absolute Deviation (MAD)37700
Skewness4.8776372
Sum1.1798951 × 109
Variance3.9782201 × 1010
MonotonicityNot monotonic
2023-12-12T17:39:59.320927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8580 77
 
0.8%
12500 75
 
0.8%
10000 73
 
0.7%
36000 72
 
0.7%
37000 66
 
0.7%
13800 62
 
0.6%
29700 56
 
0.6%
12200 55
 
0.5%
9900 51
 
0.5%
30000 45
 
0.4%
Other values (2783) 9368
93.7%
ValueCountFrequency (%)
135 1
< 0.1%
306 1
< 0.1%
313 2
< 0.1%
393 2
< 0.1%
405 1
< 0.1%
406 1
< 0.1%
411 1
< 0.1%
414 2
< 0.1%
415 1
< 0.1%
420 1
< 0.1%
ValueCountFrequency (%)
2483000 1
< 0.1%
2470000 2
< 0.1%
2454000 1
< 0.1%
2340000 1
< 0.1%
2272000 1
< 0.1%
2263000 1
< 0.1%
2226000 1
< 0.1%
2218000 1
< 0.1%
2207000 2
< 0.1%
2178000 1
< 0.1%

공시일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2018-05-31
9863 
2018-10-31
 
137

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-05-31
2nd row2018-05-31
3rd row2018-10-31
4th row2018-05-31
5th row2018-05-31

Common Values

ValueCountFrequency (%)
2018-05-31 9863
98.6%
2018-10-31 137
 
1.4%

Length

2023-12-12T17:39:59.741322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:39:59.849917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-05-31 9863
98.6%
2018-10-31 137
 
1.4%

표준지여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2023-12-12T17:39:59.932110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2019-03-11
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-03-11
2nd row2019-03-11
3rd row2019-03-11
4th row2019-03-11
5th row2019-03-11

Common Values

ValueCountFrequency (%)
2019-03-11 10000
100.0%

Length

2023-12-12T17:40:00.029933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:40:00.121633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-03-11 10000
100.0%

Interactions

2023-12-12T17:39:55.530869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:54.962842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:55.248022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:55.644433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:55.057451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:55.339600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:55.755265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:55.152408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:55.425684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:40:00.181935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호법정동코드법정동명특수지구분코드특수지구분명공시지가공시일자
고유번호1.0001.0001.0000.2750.2750.4490.023
법정동코드1.0001.0001.0000.2680.2680.3930.025
법정동명1.0001.0001.0000.4710.4710.5490.110
특수지구분코드0.2750.2680.4711.0001.0000.1160.003
특수지구분명0.2750.2680.4711.0001.0000.1160.003
공시지가0.4490.3930.5490.1160.1161.0000.034
공시일자0.0230.0250.1100.0030.0030.0341.000
2023-12-12T17:40:00.325477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특수지구분코드특수지구분명법정동명공시일자
특수지구분코드1.0001.0000.2490.005
특수지구분명1.0001.0000.2490.005
법정동명0.2490.2491.0000.093
공시일자0.0050.0050.0931.000
2023-12-12T17:40:00.428189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호법정동코드공시지가법정동명특수지구분코드특수지구분명공시일자
고유번호1.0000.999-0.3090.9980.0900.0900.037
법정동코드0.9991.000-0.3070.9980.0900.0900.037
공시지가-0.309-0.3071.0000.2270.0690.0690.026
법정동명0.9980.9980.2271.0000.2490.2490.093
특수지구분코드0.0900.0900.0690.2491.0001.0000.005
특수지구분명0.0900.0900.0690.2491.0001.0000.005
공시일자0.0370.0370.0260.0930.0050.0051.000

Missing values

2023-12-12T17:39:55.932988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:39:56.153877image/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

고유번호법정동코드법정동명특수지구분코드특수지구분명지번기준년도기준월공시지가공시일자표준지여부데이터기준일자
4671548270250261064700014827025026삼랑진읍우곡리1일반647-120181764002018-05-31N2019-03-11
3532648270250231000700034827025023삼랑진읍미전리1일반7-320181160002018-05-31N2019-03-11
4794048270250262024300054827025026삼랑진읍우곡리2산243-52018158202018-10-31N2019-03-11
5431148270250291083000004827025029삼랑진읍행곡리1일반830-0201811470002018-05-31N2019-03-11
1087948270103001081500024827010300교동1일반815-2201813666002018-05-31N2019-03-11
5975448270250311029600014827025031삼랑진읍숭진리1일반296-120181300002018-05-31N2019-03-11
2571248270108001044300014827010800가곡동1일반443-120181188002018-05-31N2019-03-11
5938648270250311037600004827025031삼랑진읍숭진리1일반376-020181273002018-05-31N2019-03-11
944948270103001042800004827010300교동1일반428-02018187302018-05-31N2019-03-11
2283148270106001095500004827010600용평동1일반955-020181391002018-05-31N2019-03-11
고유번호법정동코드법정동명특수지구분코드특수지구분명지번기준년도기준월공시지가공시일자표준지여부데이터기준일자
76048270101001034600024827010100내일동1일반346-2201811046002018-05-31N2019-03-11
9364048270310231020800014827031023부북면후사포리1일반208-120181544002018-05-31N2019-03-11
5859248270250301147300004827025030삼랑진읍임천리1일반1473-020181341002018-05-31N2019-03-11
6077548270250311098300004827025031삼랑진읍숭진리1일반983-020181275002018-05-31N2019-03-11
2453048270107001055500074827010700활성동1일반555-720181536002018-05-31N2019-03-11
5194848270250281104300024827025028삼랑진읍안태리1일반1043-220181560002018-05-31N2019-03-11
3380548270250221010700004827025022삼랑진읍용전리1일반107-02018175002018-05-31N2019-03-11
4594948270250261036200004827025026삼랑진읍우곡리1일반362-020181504002018-05-31N2019-03-11
543148270102001102300104827010200내이동1일반1023-10201816422002018-05-31N2019-03-11
2215548270106001074500004827010600용평동1일반745-020181506002018-05-31N2019-03-11