Overview

Dataset statistics

Number of variables20
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows95
Duplicate rows (%)0.9%
Total size in memory1.7 MiB
Average record size in memory182.0 B

Variable types

Numeric9
Categorical11

Dataset

Description지적재조사 사업지구에 포함된 토지현황조사서 사전조사, 현지조사에 들어가는 필지정보, 공시지가, 면적, 건축물 정보, 용도지역지구를 조회할 수 있습니다.
Author국토교통부
URLhttps://www.data.go.kr/data/15122891/fileData.do

Alerts

기준년도 has constant value ""Constant
기준월 has constant value ""Constant
기준점구분 has constant value ""Constant
기준점구분코드 has constant value ""Constant
건축물소유자순번 has constant value ""Constant
Dataset has 95 (0.9%) duplicate rowsDuplicates
기준년도.1 is highly overall correlated with 사업지구일련번호 and 11 other fieldsHigh correlation
용도지역지구명 is highly overall correlated with 사업지구일련번호 and 11 other fieldsHigh correlation
용도지역지구코드 is highly overall correlated with 사업지구일련번호 and 12 other fieldsHigh correlation
사업지구명 is highly overall correlated with 사업지구일련번호 and 13 other fieldsHigh correlation
기준점번호 is highly overall correlated with 사업지구일련번호 and 13 other fieldsHigh correlation
기준점명 is highly overall correlated with 사업지구일련번호 and 13 other fieldsHigh correlation
사업지구일련번호 is highly overall correlated with 건축물일련번호 and 6 other fieldsHigh correlation
필지고유번호 is highly overall correlated with 공시지가 and 9 other fieldsHigh correlation
공시지가 is highly overall correlated with 필지고유번호 and 11 other fieldsHigh correlation
연계기준일시 is highly overall correlated with 필지고유번호 and 10 other fieldsHigh correlation
건축물일련번호 is highly overall correlated with 사업지구일련번호 and 5 other fieldsHigh correlation
대지면적 is highly overall correlated with 사업지구명 and 4 other fieldsHigh correlation
건물면적 is highly overall correlated with 공시지가 and 6 other fieldsHigh correlation
집합건물순번 is highly overall correlated with 필지고유번호 and 9 other fieldsHigh correlation
전년대비공시지가변동률 is highly overall correlated with 필지고유번호 and 10 other fieldsHigh correlation
사업지구명 is highly imbalanced (52.5%)Imbalance
기준점명 is highly imbalanced (52.5%)Imbalance
건축물일련번호 is highly skewed (γ1 = 99.99997309)Skewed
대지면적 has 9808 (98.1%) zerosZeros
건물면적 has 1861 (18.6%) zerosZeros

Reproduction

Analysis started2023-12-12 19:06:43.301460
Analysis finished2023-12-12 19:07:00.624259
Duration17.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업지구일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8297.4337
Minimum7408
Maximum8677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:07:00.704497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7408
5-th percentile8025
Q18025
median8328
Q38328
95-th percentile8677
Maximum8677
Range1269
Interquartile range (IQR)303

Descriptive statistics

Standard deviation205.54243
Coefficient of variation (CV)0.024771808
Kurtosis-0.27063254
Mean8297.4337
Median Absolute Deviation (MAD)0
Skewness0.14611114
Sum82974337
Variance42247.692
MonotonicityNot monotonic
2023-12-13T04:07:00.855977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
8328 5522
55.2%
8025 2535
25.4%
8677 1146
 
11.5%
8609 312
 
3.1%
8472 167
 
1.7%
8125 166
 
1.7%
8605 70
 
0.7%
7857 32
 
0.3%
8124 27
 
0.3%
7563 11
 
0.1%
Other values (4) 12
 
0.1%
ValueCountFrequency (%)
7408 4
 
< 0.1%
7563 11
 
0.1%
7857 32
 
0.3%
7907 6
 
0.1%
8025 2535
25.4%
8124 27
 
0.3%
8125 166
 
1.7%
8328 5522
55.2%
8466 1
 
< 0.1%
8467 1
 
< 0.1%
ValueCountFrequency (%)
8677 1146
 
11.5%
8609 312
 
3.1%
8605 70
 
0.7%
8472 167
 
1.7%
8467 1
 
< 0.1%
8466 1
 
< 0.1%
8328 5522
55.2%
8125 166
 
1.7%
8124 27
 
0.3%
8025 2535
25.4%

사업지구명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
도량2지구
5522 
남중신동 지구
2535 
청북한산2지구
1146 
송천2지구
 
312
비산 6지구
 
167
Other values (9)
 
318

Length

Max length7
Median length5
Mean length5.7536
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row도량2지구
2nd row청북한산2지구
3rd row도량2지구
4th row청북한산2지구
5th row남중신동 지구

Common Values

ValueCountFrequency (%)
도량2지구 5522
55.2%
남중신동 지구 2535
25.4%
청북한산2지구 1146
 
11.5%
송천2지구 312
 
3.1%
비산 6지구 167
 
1.7%
황등 지구 166
 
1.7%
금암1지구 70
 
0.7%
대장2지구 32
 
0.3%
병천1지구 27
 
0.3%
노형동2지구 11
 
0.1%
Other values (4) 12
 
0.1%

Length

2023-12-13T04:07:01.048426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도량2지구 5522
42.9%
지구 2701
21.0%
남중신동 2535
19.7%
청북한산2지구 1146
 
8.9%
송천2지구 312
 
2.4%
비산 167
 
1.3%
6지구 167
 
1.3%
황등 166
 
1.3%
금암1지구 70
 
0.5%
대장2지구 32
 
0.2%
Other values (6) 50
 
0.4%

기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 10000
100.0%

Length

2023-12-13T04:07:01.220071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:07:01.343959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

필지고유번호
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5510151 × 1018
Minimum2.7170102 × 1018
Maximum5.0110122 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:07:01.458898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.7170102 × 1018
5-th percentile4.1220259 × 1018
Q14.5140121 × 1018
median4.7190103 × 1018
Q34.7190103 × 1018
95-th percentile4.7190103 × 1018
Maximum5.0110122 × 1018
Range2.294002 × 1018
Interquartile range (IQR)2.049982 × 1017

Descriptive statistics

Standard deviation3.0700417 × 1017
Coefficient of variation (CV)0.067458394
Kurtosis18.789287
Mean4.5510151 × 1018
Median Absolute Deviation (MAD)0
Skewness-3.7907421
Sum2.0331953 × 1018
Variance9.425156 × 1034
MonotonicityNot monotonic
2023-12-13T04:07:01.628254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4719010300107540000 5521
55.2%
4514012100106200003 2535
25.4%
4122025930105320054 630
 
6.3%
4122025930105320053 516
 
5.2%
4511312100101790028 312
 
3.1%
2717010200104040020 167
 
1.7%
4514032021109210018 166
 
1.7%
4511310700106280001 70
 
0.7%
4113511600105770001 32
 
0.3%
4413136022103080000 27
 
0.3%
Other values (6) 24
 
0.2%
ValueCountFrequency (%)
2717010200104040020 167
 
1.7%
4113511600105770001 32
 
0.3%
4122025930105320053 516
5.2%
4122025930105320054 630
6.3%
4136034021102150001 1
 
< 0.1%
4136034021103670029 1
 
< 0.1%
4315011500101040009 6
 
0.1%
4413136022103080000 27
 
0.3%
4511310700106280001 70
 
0.7%
4511312100101790028 312
3.1%
ValueCountFrequency (%)
5011012200124050000 11
 
0.1%
4719010300107540000 5521
55.2%
4719010300107440002 1
 
< 0.1%
4613025030107020006 4
 
< 0.1%
4514032021109210018 166
 
1.7%
4514012100106200003 2535
25.4%
4511312100101790028 312
 
3.1%
4511310700106280001 70
 
0.7%
4413136022103080000 27
 
0.3%
4315011500101040009 6
 
0.1%

기준년도.1
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022
5567 
2021
4261 
2023
 
172

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2021
3rd row2022
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2022 5567
55.7%
2021 4261
42.6%
2023 172
 
1.7%

Length

2023-12-13T04:07:01.799170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:07:01.928242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 5567
55.7%
2021 4261
42.6%
2023 172
 
1.7%

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

2023-12-13T04:07:02.080730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:07:02.206533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

공시지가
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean565228.84
Minimum84200
Maximum1562000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:07:02.332355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum84200
5-th percentile201400
Q1441000
median709700
Q3709700
95-th percentile709700
Maximum1562000
Range1477800
Interquartile range (IQR)268700

Descriptive statistics

Standard deviation194312.86
Coefficient of variation (CV)0.34377734
Kurtosis1.24989
Mean565228.84
Median Absolute Deviation (MAD)0
Skewness-0.34261763
Sum5.6522884 × 109
Variance3.7757489 × 1010
MonotonicityNot monotonic
2023-12-13T04:07:02.507692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
709700 5521
55.2%
441000 2535
25.4%
201400 630
 
6.3%
203500 516
 
5.2%
454200 312
 
3.1%
681000 167
 
1.7%
137600 166
 
1.7%
452100 70
 
0.7%
1562000 32
 
0.3%
454500 27
 
0.3%
Other values (6) 24
 
0.2%
ValueCountFrequency (%)
84200 6
 
0.1%
137600 166
 
1.7%
201400 630
 
6.3%
203500 516
 
5.2%
244000 4
 
< 0.1%
336300 1
 
< 0.1%
407500 1
 
< 0.1%
423300 1
 
< 0.1%
441000 2535
25.4%
452100 70
 
0.7%
ValueCountFrequency (%)
1562000 32
 
0.3%
852900 11
 
0.1%
709700 5521
55.2%
681000 167
 
1.7%
454500 27
 
0.3%
454200 312
 
3.1%
452100 70
 
0.7%
441000 2535
25.4%
423300 1
 
< 0.1%
407500 1
 
< 0.1%

연계기준일시
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20218434
Minimum20211015
Maximum20230913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:07:02.646998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20211015
5-th percentile20211124
Q120211124
median20221207
Q320221207
95-th percentile20221207
Maximum20230913
Range19898
Interquartile range (IQR)10083

Descriptive statistics

Standard deviation5051.1543
Coefficient of variation (CV)0.00024982915
Kurtosis-0.47900295
Mean20218434
Median Absolute Deviation (MAD)0
Skewness-0.32156673
Sum2.0218434 × 1011
Variance25514160
MonotonicityNot monotonic
2023-12-13T04:07:02.825457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
20221207 5522
55.2%
20211124 2535
25.4%
20220209 1146
 
11.5%
20211015 382
 
3.8%
20230913 167
 
1.7%
20230410 166
 
1.7%
20211217 32
 
0.3%
20221103 27
 
0.3%
20220907 11
 
0.1%
20221108 6
 
0.1%
Other values (3) 6
 
0.1%
ValueCountFrequency (%)
20211015 382
 
3.8%
20211124 2535
25.4%
20211217 32
 
0.3%
20220209 1146
 
11.5%
20220907 11
 
0.1%
20220922 1
 
< 0.1%
20221103 27
 
0.3%
20221108 6
 
0.1%
20221207 5522
55.2%
20230410 166
 
1.7%
ValueCountFrequency (%)
20230913 167
 
1.7%
20230907 1
 
< 0.1%
20230802 4
 
< 0.1%
20230410 166
 
1.7%
20221207 5522
55.2%
20221108 6
 
0.1%
20221103 27
 
0.3%
20220922 1
 
< 0.1%
20220907 11
 
0.1%
20220209 1146
 
11.5%

기준점구분
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지적도근점 10000
100.0%

Length

2023-12-13T04:07:03.023969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:07:03.163184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지적도근점 10000
100.0%

기준점구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 10000
100.0%

Length

2023-12-13T04:07:03.291920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:07:03.440295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 10000
100.0%

기준점번호
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
47190D000008681
5521 
45140D000011442
1311 
45140D000009243
1224 
41220D000016063
630 
41220D000016060
 
516
Other values (13)
798 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row47190D000008681
2nd row41220D000016063
3rd row47190D000008681
4th row41220D000016063
5th row45140D000009243

Common Values

ValueCountFrequency (%)
47190D000008681 5521
55.2%
45140D000011442 1311
 
13.1%
45140D000009243 1224
 
12.2%
41220D000016063 630
 
6.3%
41220D000016060 516
 
5.2%
45113D000015407 312
 
3.1%
45140D000024170 166
 
1.7%
27170D000002222 91
 
0.9%
27170D000002223 76
 
0.8%
45113D000015531 70
 
0.7%
Other values (8) 83
 
0.8%

Length

2023-12-13T04:07:03.583799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
47190d000008681 5521
55.2%
45140d000011442 1311
 
13.1%
45140d000009243 1224
 
12.2%
41220d000016063 630
 
6.3%
41220d000016060 516
 
5.2%
45113d000015407 312
 
3.1%
45140d000024170 166
 
1.7%
27170d000002222 91
 
0.9%
27170d000002223 76
 
0.8%
45113d000015531 70
 
0.7%
Other values (8) 83
 
0.8%

기준점명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4913
5521 
81
2535 
32941
630 
32940
 
516
w4511313599
 
312
Other values (12)
 
486

Length

Max length11
Median length4
Mean length3.8755
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row4913
2nd row32941
3rd row4913
4th row32941
5th row81

Common Values

ValueCountFrequency (%)
4913 5521
55.2%
81 2535
25.4%
32941 630
 
6.3%
32940 516
 
5.2%
w4511313599 312
 
3.1%
8519 166
 
1.7%
1579 91
 
0.9%
1580 76
 
0.8%
w4511313723 70
 
0.7%
3533 32
 
0.3%
Other values (7) 51
 
0.5%

Length

2023-12-13T04:07:03.765647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4913 5521
55.2%
81 2535
25.4%
32941 630
 
6.3%
32940 516
 
5.2%
w4511313599 312
 
3.1%
8519 166
 
1.7%
1579 91
 
0.9%
1580 76
 
0.8%
w4511313723 70
 
0.7%
3533 32
 
0.3%
Other values (7) 51
 
0.5%

건축물소유자순번
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

2023-12-13T04:07:03.924861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:07:04.056306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

건축물일련번호
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct33
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1774471 × 109
Minimum9507
Maximum1.11011 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:07:04.199844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9507
5-th percentile25013
Q125018
median1.0018355 × 108
Q31.001837 × 108
95-th percentile1.0019388 × 108
Maximum1.11011 × 1013
Range1.11011 × 1013
Interquartile range (IQR)1.0015868 × 108

Descriptive statistics

Standard deviation1.1101034 × 1011
Coefficient of variation (CV)94.280527
Kurtosis9999.9964
Mean1.1774471 × 109
Median Absolute Deviation (MAD)214
Skewness99.999973
Sum1.1774471 × 1013
Variance1.2323295 × 1022
MonotonicityNot monotonic
2023-12-13T04:07:04.378654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
100183641 1117
11.2%
100183763 1109
11.1%
100183636 1107
11.1%
100183549 1102
11.0%
100183700 1086
10.9%
25016 440
 
4.4%
25018 437
 
4.4%
25013 434
 
4.3%
25017 415
 
4.2%
25014 406
 
4.1%
Other values (23) 2347
23.5%
ValueCountFrequency (%)
9507 58
 
0.6%
10027 1
 
< 0.1%
17968 46
 
0.5%
17969 63
 
0.6%
25013 434
4.3%
25014 406
4.1%
25015 403
4.0%
25016 440
4.4%
25017 415
4.2%
25018 437
4.4%
ValueCountFrequency (%)
11101100000000 1
 
< 0.1%
100295195 19
 
0.2%
100295188 13
 
0.1%
100268112 6
 
0.1%
100212269 4
 
< 0.1%
100194542 11
 
0.1%
100193893 243
 
2.4%
100193884 273
 
2.7%
100183763 1109
11.1%
100183700 1086
10.9%

대지면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.852011
Minimum0
Maximum2989
Zeros9808
Zeros (%)98.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:07:04.517629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2989
Range2989
Interquartile range (IQR)0

Descriptive statistics

Standard deviation168.7148
Coefficient of variation (CV)9.4507446
Kurtosis181.06076
Mean17.852011
Median Absolute Deviation (MAD)0
Skewness12.754766
Sum178520.11
Variance28464.682
MonotonicityNot monotonic
2023-12-13T04:07:04.654718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 9808
98.1%
405.79 109
 
1.1%
888.0 32
 
0.3%
2539.0 27
 
0.3%
1349.0 11
 
0.1%
1541.0 6
 
0.1%
2989.0 4
 
< 0.1%
320.0 1
 
< 0.1%
516.0 1
 
< 0.1%
443.0 1
 
< 0.1%
ValueCountFrequency (%)
0.0 9808
98.1%
320.0 1
 
< 0.1%
405.79 109
 
1.1%
443.0 1
 
< 0.1%
516.0 1
 
< 0.1%
888.0 32
 
0.3%
1349.0 11
 
0.1%
1541.0 6
 
0.1%
2539.0 27
 
0.3%
2989.0 4
 
< 0.1%
ValueCountFrequency (%)
2989.0 4
 
< 0.1%
2539.0 27
 
0.3%
1541.0 6
 
0.1%
1349.0 11
 
0.1%
888.0 32
 
0.3%
516.0 1
 
< 0.1%
443.0 1
 
< 0.1%
405.79 109
 
1.1%
320.0 1
 
< 0.1%
0.0 9808
98.1%

건물면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean302.25236
Minimum0
Maximum3839.55
Zeros1861
Zeros (%)18.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:07:04.831712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1121.27
median332.384
Q3445.431
95-th percentile519.919
Maximum3839.55
Range3839.55
Interquartile range (IQR)324.161

Descriptive statistics

Standard deviation292.35571
Coefficient of variation (CV)0.96725701
Kurtosis59.254511
Mean302.25236
Median Absolute Deviation (MAD)150.374
Skewness5.3799588
Sum3022523.6
Variance85471.864
MonotonicityNot monotonic
2023-12-13T04:07:05.051689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.0 1861
18.6%
332.384 1117
11.2%
445.431 1109
11.1%
121.27 1107
11.1%
473.862 1102
11.0%
519.919 1086
10.9%
195.02 516
 
5.2%
339.8 434
 
4.3%
443.16 406
 
4.1%
145.52 316
 
3.2%
Other values (16) 946
9.5%
ValueCountFrequency (%)
0.0 1861
18.6%
3.6 42
 
0.4%
121.27 1107
11.1%
145.52 316
 
3.2%
148.72 314
 
3.1%
152.39 13
 
0.1%
170.28 1
 
< 0.1%
178.2 1
 
< 0.1%
182.01 58
 
0.6%
195.02 516
 
5.2%
ValueCountFrequency (%)
3839.55 28
 
0.3%
1263.68 163
 
1.6%
617.52 27
 
0.3%
594.72 4
 
< 0.1%
519.919 1086
10.9%
473.862 1102
11.0%
445.431 1109
11.1%
443.16 406
 
4.1%
428.76 11
 
0.1%
339.8 434
 
4.3%

집합건물순번
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.715
Minimum2
Maximum460
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:07:05.245606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q168
median85
Q385
95-th percentile85
Maximum460
Range458
Interquartile range (IQR)17

Descriptive statistics

Standard deviation47.624254
Coefficient of variation (CV)0.65494402
Kurtosis23.28557
Mean72.715
Median Absolute Deviation (MAD)0
Skewness3.7166855
Sum727150
Variance2268.0696
MonotonicityNot monotonic
2023-12-13T04:07:05.399713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
85 5521
55.2%
68 2535
25.4%
4 630
 
6.3%
6 520
 
5.2%
29 313
 
3.1%
356 167
 
1.7%
18 123
 
1.2%
36 70
 
0.7%
16 38
 
0.4%
21 32
 
0.3%
Other values (6) 51
 
0.5%
ValueCountFrequency (%)
2 27
 
0.3%
4 630
6.3%
5 1
 
< 0.1%
6 520
5.2%
12 6
 
0.1%
16 38
 
0.4%
17 5
 
0.1%
18 123
 
1.2%
21 32
 
0.3%
26 1
 
< 0.1%
ValueCountFrequency (%)
460 11
 
0.1%
356 167
 
1.7%
85 5521
55.2%
68 2535
25.4%
36 70
 
0.7%
29 313
 
3.1%
26 1
 
< 0.1%
21 32
 
0.3%
18 123
 
1.2%
17 5
 
0.1%

전년대비공시지가변동률
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2023775
Minimum0.021
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:07:05.568141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.021
5-th percentile0.04
Q10.04
median0.04
Q30.154
95-th percentile1
Maximum1
Range0.979
Interquartile range (IQR)0.114

Descriptive statistics

Standard deviation0.31878957
Coefficient of variation (CV)1.5752224
Kurtosis2.3314152
Mean0.2023775
Median Absolute Deviation (MAD)0
Skewness2.0394125
Sum2023.775
Variance0.10162679
MonotonicityNot monotonic
2023-12-13T04:07:05.742654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.04 5521
55.2%
0.154 2535
25.4%
1.0 1350
 
13.5%
0.11 312
 
3.1%
0.104 167
 
1.7%
0.122 70
 
0.7%
0.035 27
 
0.3%
0.083 11
 
0.1%
0.051 5
 
0.1%
0.021 1
 
< 0.1%
ValueCountFrequency (%)
0.021 1
 
< 0.1%
0.035 27
 
0.3%
0.04 5521
55.2%
0.051 5
 
0.1%
0.083 11
 
0.1%
0.104 167
 
1.7%
0.11 312
 
3.1%
0.122 70
 
0.7%
0.154 2535
25.4%
0.183 1
 
< 0.1%
ValueCountFrequency (%)
1.0 1350
 
13.5%
0.183 1
 
< 0.1%
0.154 2535
25.4%
0.122 70
 
0.7%
0.11 312
 
3.1%
0.104 167
 
1.7%
0.083 11
 
0.1%
0.051 5
 
0.1%
0.04 5521
55.2%
0.035 27
 
0.3%

용도지역지구코드
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
UQA122
2809 
UQS119
1447 
UQA01X
1429 
UQQ310
1371 
UQS121
1348 
Other values (8)
1596 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQS119
2nd rowUQQ600
3rd rowUQQ310
4th rowUQB100
5th rowUQA01X

Common Values

ValueCountFrequency (%)
UQA122 2809
28.1%
UQS119 1447
14.5%
UQA01X 1429
14.3%
UQQ310 1371
13.7%
UQS121 1348
13.5%
UQB100 586
 
5.9%
UQQ600 560
 
5.6%
UQA121 189
 
1.9%
UQH100 172
 
1.7%
UQO100 33
 
0.3%
Other values (3) 56
 
0.6%

Length

2023-12-13T04:07:05.917980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uqa122 2809
28.1%
uqs119 1447
14.5%
uqa01x 1429
14.3%
uqq310 1371
13.7%
uqs121 1348
13.5%
uqb100 586
 
5.9%
uqq600 560
 
5.6%
uqa121 189
 
1.9%
uqh100 172
 
1.7%
uqo100 33
 
0.3%
Other values (3) 56
 
0.6%

용도지역지구명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제2종일반주거지역
2809 
도시지역
1461 
중로3류(폭 12m~15m)
1447 
제1종지구단위계획구역
1371 
소로2류(폭 8m~10m)
1348 
Other values (7)
1564 

Length

Max length15
Median length13
Mean length10.0376
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중로3류(폭 12m~15m)
2nd row토지거래계약에관한허가구역
3rd row제1종지구단위계획구역
4th row계획관리지역
5th row도시지역

Common Values

ValueCountFrequency (%)
제2종일반주거지역 2809
28.1%
도시지역 1461
14.6%
중로3류(폭 12m~15m) 1447
14.5%
제1종지구단위계획구역 1371
13.7%
소로2류(폭 8m~10m) 1348
13.5%
계획관리지역 586
 
5.9%
토지거래계약에관한허가구역 560
 
5.6%
제1종일반주거지역 189
 
1.9%
고도지구 172
 
1.7%
특정용도제한지구 33
 
0.3%
Other values (2) 24
 
0.2%

Length

2023-12-13T04:07:06.053586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종일반주거지역 2809
22.0%
도시지역 1461
11.4%
중로3류(폭 1447
11.3%
12m~15m 1447
11.3%
제1종지구단위계획구역 1371
10.7%
소로2류(폭 1348
10.5%
8m~10m 1348
10.5%
계획관리지역 586
 
4.6%
토지거래계약에관한허가구역 560
 
4.4%
제1종일반주거지역 189
 
1.5%
Other values (4) 229
 
1.8%

Interactions

2023-12-13T04:06:58.211559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:47.686364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:48.832138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:50.455381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:51.840380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:53.287356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:54.629325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:55.905766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:57.082967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:58.383364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:47.820220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:48.959110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:50.611109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:52.013876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:53.439003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:54.753323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:56.029721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:57.184591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:58.502182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:47.952309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:49.094614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:50.752390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:52.175373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:53.574568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:54.882505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:56.161886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:57.300697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:58.647657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:48.067825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:49.234876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:50.897628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:52.349816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:53.728212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:55.042174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:56.287176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:57.441104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:59.123079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:48.203976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:49.359313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:51.071648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:52.506801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:53.890723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:55.213914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:56.436884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:57.564166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:59.242728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:48.311471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:49.534674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:51.214421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:52.649890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:54.028282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:55.354301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:56.589134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:57.703336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:59.422096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:48.448140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:49.687718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:51.371138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:52.814239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:54.200607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:55.498179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:56.723346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:57.835546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:59.603487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:48.586876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:49.845282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:51.535460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:53.011945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:54.368210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:55.652538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:56.877305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:57.976580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:59.761851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:48.706930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:49.958480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:51.681865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:53.143140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:54.494895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:55.781594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:56.986644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:06:58.104980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:07:06.185714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업지구일련번호사업지구명필지고유번호기준년도.1공시지가연계기준일시기준점번호기준점명건축물일련번호대지면적건물면적집합건물순번전년대비공시지가변동률용도지역지구코드용도지역지구명
사업지구일련번호1.0001.0000.9480.9740.9290.9751.0001.0000.0850.8720.4780.9870.9130.8880.856
사업지구명1.0001.0001.0001.0000.9991.0001.0001.0001.0001.0000.8211.0001.0000.9010.887
필지고유번호0.9481.0001.0000.6720.9980.9791.0001.0000.0320.7170.6630.8440.8420.8800.958
기준년도.10.9741.0000.6721.0000.9440.7991.0001.0000.0550.6660.3850.7390.9230.8210.920
공시지가0.9290.9990.9980.9441.0000.9131.0001.0000.6140.9720.4530.8890.9990.8840.945
연계기준일시0.9751.0000.9790.7990.9131.0001.0001.0000.0850.4650.7150.9420.8950.9860.923
기준점번호1.0001.0001.0001.0001.0001.0001.0001.0001.0000.9920.8331.0001.0000.9080.913
기준점명1.0001.0001.0001.0001.0001.0001.0001.0001.0000.9910.8261.0001.0000.9060.895
건축물일련번호0.0851.0000.0320.0550.6140.0851.0001.0001.0000.0850.0000.0190.0000.1860.000
대지면적0.8721.0000.7170.6660.9720.4650.9920.9910.0851.0000.1030.8310.1890.7720.668
건물면적0.4780.8210.6630.3850.4530.7150.8330.8260.0000.1031.0000.5830.3600.7250.827
집합건물순번0.9871.0000.8440.7390.8890.9421.0001.0000.0190.8310.5831.0000.5940.7880.882
전년대비공시지가변동률0.9131.0000.8420.9230.9990.8951.0001.0000.0000.1890.3600.5941.0000.9180.983
용도지역지구코드0.8880.9010.8800.8210.8840.9860.9080.9060.1860.7720.7250.7880.9181.0001.000
용도지역지구명0.8560.8870.9580.9200.9450.9230.9130.8950.0000.6680.8270.8820.9831.0001.000
2023-12-13T04:07:06.390332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도.1용도지역지구명용도지역지구코드사업지구명기준점번호기준점명
기준년도.11.0000.6850.6870.9990.9990.999
용도지역지구명0.6851.0001.0000.6030.6030.603
용도지역지구코드0.6871.0001.0000.6160.6160.616
사업지구명0.9990.6030.6161.0001.0001.000
기준점번호0.9990.6030.6161.0001.0001.000
기준점명0.9990.6030.6161.0001.0001.000
2023-12-13T04:07:06.565393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업지구일련번호필지고유번호공시지가연계기준일시건축물일련번호대지면적건물면적집합건물순번전년대비공시지가변동률사업지구명기준년도.1기준점번호기준점명용도지역지구코드용도지역지구명
사업지구일련번호1.000-0.0430.1000.3550.5240.0120.3030.035-0.1101.0000.9950.9991.0000.6560.624
필지고유번호-0.0431.0000.9070.7280.497-0.2130.4520.864-0.9211.0000.9890.9990.9990.6850.682
공시지가0.1000.9071.0000.7020.5390.0190.5420.917-0.9681.0000.7120.9990.9990.6920.671
연계기준일시0.3550.7280.7021.0000.5740.1260.3970.787-0.7190.9990.8610.9990.9990.8470.846
건축물일련번호0.5240.4970.5390.5741.000-0.0820.4300.409-0.4940.9990.0740.9990.9990.1730.000
대지면적0.012-0.2130.0190.126-0.0821.0000.0170.0790.0300.9700.5720.9710.9710.5000.405
건물면적0.3030.4520.5420.3970.4300.0171.0000.447-0.5510.6280.3760.6270.6280.5200.520
집합건물순번0.0350.8640.9170.7870.4090.0790.4471.000-0.9160.9990.7860.9990.9990.5980.593
전년대비공시지가변동률-0.110-0.921-0.968-0.719-0.4940.030-0.551-0.9161.0000.9990.6620.9990.9990.8510.846
사업지구명1.0001.0001.0000.9990.9990.9700.6280.9990.9991.0000.9991.0001.0000.6160.603
기준년도.10.9950.9890.7120.8610.0740.5720.3760.7860.6620.9991.0000.9990.9990.6870.685
기준점번호0.9990.9990.9990.9990.9990.9710.6270.9990.9991.0000.9991.0001.0000.6160.603
기준점명1.0000.9990.9990.9990.9990.9710.6280.9990.9991.0000.9991.0001.0000.6160.603
용도지역지구코드0.6560.6850.6920.8470.1730.5000.5200.5980.8510.6160.6870.6160.6161.0001.000
용도지역지구명0.6240.6820.6710.8460.0000.4050.5200.5930.8460.6030.6850.6030.6031.0001.000

Missing values

2023-12-13T04:06:59.991004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:07:00.437636image/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

사업지구일련번호사업지구명기준년도필지고유번호기준년도.1기준월공시지가연계기준일시기준점구분기준점구분코드기준점번호기준점명건축물소유자순번건축물일련번호대지면적건물면적집합건물순번전년대비공시지가변동률용도지역지구코드용도지역지구명
317978328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836410.0332.384850.04UQS119중로3류(폭 12m~15m)
41228677청북한산2지구202241220259301053200542021120140020220209지적도근점341220D0000160633294111001803950.0148.7241.0UQQ600토지거래계약에관한허가구역
243528328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836360.0121.27850.04UQQ310제1종지구단위계획구역
34098677청북한산2지구202241220259301053200542021120140020220209지적도근점341220D0000160633294111001803950.0148.7241.0UQB100계획관리지역
500098025남중신동 지구202245140121001062000032021144100020211124지적도근점345140D000009243811250180.00.0680.154UQA01X도시지역
261928328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836360.0121.27850.04UQQ310제1종지구단위계획구역
343588328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836410.0332.384850.04UQS121소로2류(폭 8m~10m)
26008677청북한산2지구202241220259301053200532021120350020220209지적도근점341220D0000160603294011001938930.0195.0261.0UQQ600토지거래계약에관한허가구역
150808328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001835490.0473.862850.04UQQ310제1종지구단위계획구역
398408609송천2지구202245113121001017900282021145420020211015지적도근점345113D000015407w451131359911471220.01263.68290.11UQH100고도지구
사업지구일련번호사업지구명기준년도필지고유번호기준년도.1기준월공시지가연계기준일시기준점구분기준점구분코드기준점번호기준점명건축물소유자순번건축물일련번호대지면적건물면적집합건물순번전년대비공시지가변동률용도지역지구코드용도지역지구명
492388025남중신동 지구202245140121001062000032021144100020211124지적도근점345140D000009243811250140.0443.16680.154UQA122제2종일반주거지역
252758328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836410.0332.384850.04UQA122제2종일반주거지역
319848328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001837630.0445.431850.04UQQ310제1종지구단위계획구역
308498328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001837000.0519.919850.04UQS119중로3류(폭 12m~15m)
205188328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836410.0332.384850.04UQS121소로2류(폭 8m~10m)
204988328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836410.0332.384850.04UQS121소로2류(폭 8m~10m)
402198025남중신동 지구202245140121001062000032021144100020211124지적도근점345140D000011442811250170.00.0680.154UQA01X도시지역
40138677청북한산2지구202241220259301053200542021120140020220209지적도근점341220D0000160633294111001803860.0145.5241.0UQB100계획관리지역
136668328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001837630.0445.431850.04UQS121소로2류(폭 8m~10m)
187488328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001837000.0519.919850.04UQQ310제1종지구단위계획구역

Duplicate rows

Most frequently occurring

사업지구일련번호사업지구명기준년도필지고유번호기준년도.1기준월공시지가연계기준일시기준점구분기준점구분코드기준점번호기준점명건축물소유자순번건축물일련번호대지면적건물면적집합건물순번전년대비공시지가변동률용도지역지구코드용도지역지구명# duplicates
658328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001837630.0445.431850.04UQS119중로3류(폭 12m~15m)305
538328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836360.0121.27850.04UQS119중로3류(폭 12m~15m)292
558328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836410.0332.384850.04UQA122제2종일반주거지역292
578328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836410.0332.384850.04UQS119중로3류(폭 12m~15m)284
498328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001835490.0473.862850.04UQS119중로3류(폭 12m~15m)283
618328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001837000.0519.919850.04UQS119중로3류(폭 12m~15m)283
488328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001835490.0473.862850.04UQQ310제1종지구단위계획구역278
608328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001837000.0519.919850.04UQQ310제1종지구단위계획구역278
548328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001836360.0121.27850.04UQS121소로2류(폭 8m~10m)276
648328도량2지구202247190103001075400002022170970020221207지적도근점347190D000008681491311001837630.0445.431850.04UQQ310제1종지구단위계획구역276