Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells9486
Missing cells (%)7.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory119.0 B

Variable types

Numeric7
Text2
Categorical3
DateTime1

Dataset

Description개별주택가격은 국토교통부장관이 매년 공시하는 표준주택가격을 기준으로 시장·군수·구청장이 조사한 개별주택의 특성과 비교표준주택의 특성을 비교하여 국토교통부장관이 작성·공급한 「주택가격비준표」 상의 주택특성 차이에 따른 가격배율을 산출하고 이를 표준주택가격에 곱하여 산정한 후 한국부동산원의 검증을 받아 주택소유자 등의 의견수렴과 시·군·구 부동산가격공시위원회 심의 등의 절차를 거쳐 시장·군수 ·구청장이 결정 공시하는 개별주택의 가격
URLhttps://www.data.go.kr/data/15013457/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
전체면적(제곱미터) is highly overall correlated with 대지면적High correlation
공시면적(제곱미터) is highly overall correlated with 건물연면적High correlation
대지면적 is highly overall correlated with 전체면적(제곱미터)High correlation
건물연면적 is highly overall correlated with 공시면적(제곱미터) and 1 other fieldsHigh correlation
가격 is highly overall correlated with 건물연면적High correlation
용도지역 is highly imbalanced (55.3%)Imbalance
건물용도 is highly imbalanced (90.0%)Imbalance
비고 has 9486 (94.9%) missing valuesMissing
동 번호 is highly skewed (γ1 = 57.87697579)Skewed
전체면적(제곱미터) is highly skewed (γ1 = 48.6682651)Skewed
일련 번호 has unique valuesUnique
동 번호 has 175 (1.8%) zerosZeros

Reproduction

Analysis started2023-12-11 22:51:42.805784
Analysis finished2023-12-11 22:51:50.235649
Duration7.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련 번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8266.474
Minimum1
Maximum16668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T07:51:50.317395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile797.95
Q14105.5
median8237.5
Q312417.25
95-th percentile15816.05
Maximum16668
Range16667
Interquartile range (IQR)8311.75

Descriptive statistics

Standard deviation4812.5429
Coefficient of variation (CV)0.58217602
Kurtosis-1.1935278
Mean8266.474
Median Absolute Deviation (MAD)4157
Skewness0.021458468
Sum82664740
Variance23160569
MonotonicityNot monotonic
2023-12-12T07:51:50.446818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1207 1
 
< 0.1%
8057 1
 
< 0.1%
15841 1
 
< 0.1%
11406 1
 
< 0.1%
13243 1
 
< 0.1%
14920 1
 
< 0.1%
10762 1
 
< 0.1%
7386 1
 
< 0.1%
6372 1
 
< 0.1%
4404 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
ValueCountFrequency (%)
16668 1
< 0.1%
16667 1
< 0.1%
16666 1
< 0.1%
16665 1
< 0.1%
16663 1
< 0.1%
16662 1
< 0.1%
16660 1
< 0.1%
16656 1
< 0.1%
16655 1
< 0.1%
16654 1
< 0.1%

소재지
Text

Distinct9890
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T07:51:50.765854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length16.2501
Min length13

Characters and Unicode

Total characters162501
Distinct characters127
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9791 ?
Unique (%)97.9%

Sample

1st row하동군 하동읍 비파리 388
2nd row하동군 횡천면 횡천리 658
3rd row하동군 하동읍 광평리 268-26
4th row하동군 옥종면 청룡리 216-10
5th row하동군 고전면 신월리 1165-1
ValueCountFrequency (%)
하동군 10000
25.0%
하동읍 1360
 
3.4%
악양면 1106
 
2.8%
진교면 1083
 
2.7%
옥종면 998
 
2.5%
금남면 871
 
2.2%
화개면 818
 
2.0%
고전면 620
 
1.5%
적량면 602
 
1.5%
금성면 596
 
1.5%
Other values (5761) 22006
54.9%
2023-12-12T07:51:51.304363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30060
18.5%
동 11715
 
7.2%
하 11440
 
7.0%
군 10000
 
6.2%
리 10000
 
6.2%
면 8640
 
5.3%
1 7222
 
4.4%
- 5756
 
3.5%
2 4675
 
2.9%
3 4141
 
2.5%
Other values (117) 58852
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89580
55.1%
Decimal Number 37105
22.8%
Space Separator 30060
 
18.5%
Dash Punctuation 5756
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 11715
 
13.1%
하 11440
 
12.8%
군 10000
 
11.2%
리 10000
 
11.2%
면 8640
 
9.6%
양 1912
 
2.1%
읍 1899
 
2.1%
금 1546
 
1.7%
천 1473
 
1.6%
진 1430
 
1.6%
Other values (105) 29525
33.0%
Decimal Number
ValueCountFrequency (%)
1 7222
19.5%
2 4675
12.6%
3 4141
11.2%
4 3895
10.5%
5 3315
8.9%
6 3190
8.6%
7 2967
8.0%
8 2649
 
7.1%
9 2600
 
7.0%
0 2451
 
6.6%
Space Separator
ValueCountFrequency (%)
30060
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89580
55.1%
Common 72921
44.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 11715
 
13.1%
하 11440
 
12.8%
군 10000
 
11.2%
리 10000
 
11.2%
면 8640
 
9.6%
양 1912
 
2.1%
읍 1899
 
2.1%
금 1546
 
1.7%
천 1473
 
1.6%
진 1430
 
1.6%
Other values (105) 29525
33.0%
Common
ValueCountFrequency (%)
30060
41.2%
1 7222
 
9.9%
- 5756
 
7.9%
2 4675
 
6.4%
3 4141
 
5.7%
4 3895
 
5.3%
5 3315
 
4.5%
6 3190
 
4.4%
7 2967
 
4.1%
8 2649
 
3.6%
Other values (2) 5051
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89580
55.1%
ASCII 72921
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30060
41.2%
1 7222
 
9.9%
- 5756
 
7.9%
2 4675
 
6.4%
3 4141
 
5.7%
4 3895
 
5.3%
5 3315
 
4.5%
6 3190
 
4.4%
7 2967
 
4.1%
8 2649
 
3.6%
Other values (2) 5051
 
6.9%
Hangul
ValueCountFrequency (%)
동 11715
 
13.1%
하 11440
 
12.8%
군 10000
 
11.2%
리 10000
 
11.2%
면 8640
 
9.6%
양 1912
 
2.1%
읍 1899
 
2.1%
금 1546
 
1.7%
천 1473
 
1.6%
진 1430
 
1.6%
Other values (105) 29525
33.0%

동 번호
Real number (ℝ)

SKEWED  ZEROS 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.4995
Minimum0
Maximum40025
Zeros175
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T07:51:51.502713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum40025
Range40025
Interquartile range (IQR)0

Descriptive statistics

Standard deviation659.12337
Coefficient of variation (CV)52.731979
Kurtosis3354.5206
Mean12.4995
Median Absolute Deviation (MAD)0
Skewness57.876976
Sum124995
Variance434443.61
MonotonicityNot monotonic
2023-12-12T07:51:51.647202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 8956
89.6%
2 740
 
7.4%
0 175
 
1.8%
3 85
 
0.9%
4 22
 
0.2%
5 7
 
0.1%
7 3
 
< 0.1%
6 3
 
< 0.1%
8 2
 
< 0.1%
14 2
 
< 0.1%
Other values (5) 5
 
0.1%
ValueCountFrequency (%)
0 175
 
1.8%
1 8956
89.6%
2 740
 
7.4%
3 85
 
0.9%
4 22
 
0.2%
5 7
 
0.1%
6 3
 
< 0.1%
7 3
 
< 0.1%
8 2
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
40025 1
 
< 0.1%
38023 1
 
< 0.1%
36025 1
 
< 0.1%
14 2
 
< 0.1%
13 1
 
< 0.1%
12 1
 
< 0.1%
8 2
 
< 0.1%
7 3
< 0.1%
6 3
< 0.1%
5 7
0.1%

전체면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1690
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean568.93086
Minimum9
Maximum220752
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T07:51:51.826855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile116
Q1241
median374
Q3570
95-th percentile1008
Maximum220752
Range220743
Interquartile range (IQR)329

Descriptive statistics

Standard deviation3394.2938
Coefficient of variation (CV)5.966092
Kurtosis2813.3346
Mean568.93086
Median Absolute Deviation (MAD)153
Skewness48.668265
Sum5689308.6
Variance11521231
MonotonicityNot monotonic
2023-12-12T07:51:52.048918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
660.0 166
 
1.7%
248.0 57
 
0.6%
268.0 54
 
0.5%
218.0 52
 
0.5%
284.0 50
 
0.5%
357.0 49
 
0.5%
330.0 49
 
0.5%
314.0 49
 
0.5%
496.0 47
 
0.5%
231.0 47
 
0.5%
Other values (1680) 9380
93.8%
ValueCountFrequency (%)
9.0 1
 
< 0.1%
17.0 2
 
< 0.1%
20.0 2
 
< 0.1%
23.0 4
< 0.1%
24.0 2
 
< 0.1%
27.0 1
 
< 0.1%
28.0 1
 
< 0.1%
30.0 5
0.1%
31.0 1
 
< 0.1%
33.0 3
< 0.1%
ValueCountFrequency (%)
220752.0 1
 
< 0.1%
190043.0 1
 
< 0.1%
81620.0 1
 
< 0.1%
69985.0 1
 
< 0.1%
58658.0 1
 
< 0.1%
54753.0 1
 
< 0.1%
39853.0 1
 
< 0.1%
37292.0 1
 
< 0.1%
31739.0 1
 
< 0.1%
31537.0 4
< 0.1%

공시면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct5161
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110.78068
Minimum8.2
Maximum4596.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T07:51:52.193248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.2
5-th percentile32.4
Q162.1
median89.99
Q3127.515
95-th percentile242.241
Maximum4596.26
Range4588.06
Interquartile range (IQR)65.415

Descriptive statistics

Standard deviation114.80986
Coefficient of variation (CV)1.0363708
Kurtosis387.49764
Mean110.78068
Median Absolute Deviation (MAD)30.99
Skewness13.929847
Sum1107806.8
Variance13181.304
MonotonicityNot monotonic
2023-12-12T07:51:52.356103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49.5 57
 
0.6%
60.0 38
 
0.4%
59.5 37
 
0.4%
66.0 36
 
0.4%
50.0 28
 
0.3%
66.1 27
 
0.3%
82.6 26
 
0.3%
52.8 23
 
0.2%
26.4 22
 
0.2%
70.0 21
 
0.2%
Other values (5151) 9685
96.9%
ValueCountFrequency (%)
8.2 1
< 0.1%
8.6 1
< 0.1%
9.9 1
< 0.1%
9.92 1
< 0.1%
10.0 1
< 0.1%
10.2 1
< 0.1%
10.6 1
< 0.1%
10.9 1
< 0.1%
11.9 1
< 0.1%
12.5 1
< 0.1%
ValueCountFrequency (%)
4596.26 1
< 0.1%
3496.65 1
< 0.1%
2966.68 1
< 0.1%
2355.96 1
< 0.1%
2061.96 1
< 0.1%
1551.28 1
< 0.1%
1443.21 1
< 0.1%
1309.73 1
< 0.1%
1286.62 1
< 0.1%
1281.37 1
< 0.1%

대지면적
Real number (ℝ)

HIGH CORRELATION 

Distinct2886
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean385.17907
Minimum3.44
Maximum3389
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T07:51:52.497616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.44
5-th percentile86
Q1207.8025
median334
Q3509
95-th percentile841
Maximum3389
Range3385.56
Interquartile range (IQR)301.1975

Descriptive statistics

Standard deviation250.80228
Coefficient of variation (CV)0.65113165
Kurtosis7.3854106
Mean385.17907
Median Absolute Deviation (MAD)146
Skewness1.7527842
Sum3851790.7
Variance62901.785
MonotonicityNot monotonic
2023-12-12T07:51:52.663844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
660.0 145
 
1.5%
248.0 48
 
0.5%
231.0 46
 
0.5%
268.0 46
 
0.5%
357.0 46
 
0.5%
218.0 45
 
0.4%
314.0 43
 
0.4%
205.0 43
 
0.4%
330.0 42
 
0.4%
271.0 41
 
0.4%
Other values (2876) 9455
94.5%
ValueCountFrequency (%)
3.44 1
< 0.1%
4.92 1
< 0.1%
8.52 1
< 0.1%
9.0 1
< 0.1%
9.4 1
< 0.1%
11.0 1
< 0.1%
11.13 1
< 0.1%
11.3 1
< 0.1%
11.65 1
< 0.1%
12.0 1
< 0.1%
ValueCountFrequency (%)
3389.0 1
< 0.1%
2917.0 1
< 0.1%
2555.0 1
< 0.1%
2257.0 1
< 0.1%
2188.0 1
< 0.1%
2184.0 1
< 0.1%
2161.49 1
< 0.1%
2150.0 1
< 0.1%
2142.14 1
< 0.1%
2070.0 1
< 0.1%

건물연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct4789
Distinct (%)47.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.273088
Minimum8.2
Maximum647.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T07:51:52.800845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.2
5-th percentile31.4
Q159.5
median84.795
Q3111.7
95-th percentile179.232
Maximum647.92
Range639.72
Interquartile range (IQR)52.2

Descriptive statistics

Standard deviation50.531909
Coefficient of variation (CV)0.54763431
Kurtosis16.209489
Mean92.273088
Median Absolute Deviation (MAD)25.69
Skewness2.59572
Sum922730.88
Variance2553.4738
MonotonicityNot monotonic
2023-12-12T07:51:52.937674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49.5 57
 
0.6%
59.5 42
 
0.4%
60.0 36
 
0.4%
66.0 35
 
0.4%
50.0 30
 
0.3%
82.6 30
 
0.3%
66.1 28
 
0.3%
52.8 24
 
0.2%
99.0 23
 
0.2%
70.0 22
 
0.2%
Other values (4779) 9673
96.7%
ValueCountFrequency (%)
8.2 1
< 0.1%
8.6 1
< 0.1%
9.9 1
< 0.1%
9.92 1
< 0.1%
10.0 1
< 0.1%
10.2 1
< 0.1%
10.6 2
< 0.1%
10.9 1
< 0.1%
11.9 1
< 0.1%
12.5 1
< 0.1%
ValueCountFrequency (%)
647.92 1
< 0.1%
636.12 1
< 0.1%
618.1 1
< 0.1%
617.98 1
< 0.1%
610.67 1
< 0.1%
593.2 1
< 0.1%
568.34 1
< 0.1%
566.91 1
< 0.1%
541.71 1
< 0.1%
529.0 1
< 0.1%

용도지역
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
계관
7215 
보관
880 
2주
840 
생관
 
350
농림
 
328
Other values (6)
 
387

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2주
2nd row계관
3rd row2주
4th row계관
5th row계관

Common Values

ValueCountFrequency (%)
계관 7215
72.2%
보관 880
 
8.8%
2주 840
 
8.4%
생관 350
 
3.5%
농림 328
 
3.3%
일상 160
 
1.6%
자연 95
 
0.9%
준주 39
 
0.4%
자보 36
 
0.4%
1주 31
 
0.3%

Length

2023-12-12T07:51:53.044911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계관 7215
72.2%
보관 880
 
8.8%
2주 840
 
8.4%
생관 350
 
3.5%
농림 328
 
3.3%
일상 160
 
1.6%
자연 95
 
0.9%
준주 39
 
0.4%
자보 36
 
0.4%
1주 31
 
0.3%

건물용도
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단독
9489 
주상
 
293
주산
 
130
다가구
 
56
기타복합
 
12
Other values (9)
 
20

Length

Max length4
Median length2
Mean length2.0104
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
단독 9489
94.9%
주상 293
 
2.9%
주산 130
 
1.3%
다가구 56
 
0.6%
기타복합 12
 
0.1%
1종근생 8
 
0.1%
숙박 2
 
< 0.1%
기타 2
 
< 0.1%
종교 2
 
< 0.1%
2종근생 2
 
< 0.1%
Other values (4) 4
 
< 0.1%

Length

2023-12-12T07:51:53.423088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독 9489
94.9%
주상 293
 
2.9%
주산 130
 
1.3%
다가구 56
 
0.6%
기타복합 12
 
0.1%
1종근생 8
 
0.1%
숙박 2
 
< 0.1%
기타 2
 
< 0.1%
종교 2
 
< 0.1%
2종근생 2
 
< 0.1%
Other values (4) 4
 
< 0.1%

건물구조
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
목
3090 
블록
2279 
벽돌
1375 
연와
972 
경철
902 
Other values (19)
1382 

Length

Max length3
Median length2
Mean length1.6942
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row목
2nd row블록
3rd row연와
4th row블록
5th row목

Common Values

ValueCountFrequency (%)
목 3090
30.9%
블록 2279
22.8%
벽돌 1375
13.8%
연와 972
 
9.7%
경철 902
 
9.0%
철근 788
 
7.9%
목구 396
 
4.0%
철골 72
 
0.7%
조판 26
 
0.3%
보블 23
 
0.2%
Other values (14) 77
 
0.8%

Length

2023-12-12T07:51:53.541852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목 3090
30.9%
블록 2279
22.8%
벽돌 1375
13.8%
연와 972
 
9.7%
경철 902
 
9.0%
철근 788
 
7.9%
목구 396
 
4.0%
철골 72
 
0.7%
조판 26
 
0.3%
보블 23
 
0.2%
Other values (14) 77
 
0.8%

가격
Real number (ℝ)

HIGH CORRELATION 

Distinct1618
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39210110
Minimum411000
Maximum6.66 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T07:51:53.698328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum411000
5-th percentile6939000
Q114900000
median27300000
Q349500000
95-th percentile1.08 × 108
Maximum6.66 × 108
Range6.65589 × 108
Interquartile range (IQR)34600000

Descriptive statistics

Standard deviation39586176
Coefficient of variation (CV)1.009591
Kurtosis28.552751
Mean39210110
Median Absolute Deviation (MAD)14900000
Skewness3.8505805
Sum3.921011 × 1011
Variance1.5670653 × 1015
MonotonicityNot monotonic
2023-12-12T07:51:53.827361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11200000 40
 
0.4%
12400000 39
 
0.4%
14000000 36
 
0.4%
10300000 35
 
0.4%
10500000 35
 
0.4%
14600000 33
 
0.3%
11400000 33
 
0.3%
15600000 31
 
0.3%
11300000 31
 
0.3%
14900000 31
 
0.3%
Other values (1608) 9656
96.6%
ValueCountFrequency (%)
411000 1
< 0.1%
551000 1
< 0.1%
564000 1
< 0.1%
610000 1
< 0.1%
630000 1
< 0.1%
876000 1
< 0.1%
882000 1
< 0.1%
893000 1
< 0.1%
1040000 1
< 0.1%
1140000 1
< 0.1%
ValueCountFrequency (%)
666000000 1
< 0.1%
540000000 1
< 0.1%
498000000 1
< 0.1%
480000000 1
< 0.1%
476000000 1
< 0.1%
462000000 1
< 0.1%
431000000 1
< 0.1%
399000000 1
< 0.1%
397000000 1
< 0.1%
395000000 1
< 0.1%

비고
Text

MISSING 

Distinct451
Distinct (%)87.7%
Missing9486
Missing (%)94.9%
Memory size156.2 KiB
2023-12-12T07:51:54.185619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length6.4844358
Min length2

Characters and Unicode

Total characters3333
Distinct characters39
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique440 ?
Unique (%)85.6%

Sample

1st row33-20
2nd row159-23
3rd row302-30
4th row469-2
5th row건물만공시
ValueCountFrequency (%)
건물만공시 38
 
5.9%
외 25
 
3.9%
1 18
 
2.8%
국불미공시 15
 
2.3%
국공유미공시 6
 
0.9%
2 4
 
0.6%
475 2
 
0.3%
3 2
 
0.3%
185 2
 
0.3%
761-4 2
 
0.3%
Other values (525) 535
82.4%
2023-12-12T07:51:54.666773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 448
13.4%
1 432
13.0%
2 306
9.2%
3 280
 
8.4%
4 221
 
6.6%
5 193
 
5.8%
193
 
5.8%
8 181
 
5.4%
7 180
 
5.4%
6 164
 
4.9%
Other values (29) 735
22.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2242
67.3%
Dash Punctuation 448
 
13.4%
Other Letter 328
 
9.8%
Space Separator 193
 
5.8%
Other Punctuation 83
 
2.5%
Lowercase Letter 26
 
0.8%
Uppercase Letter 13
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 65
19.8%
시 59
18.0%
물 38
11.6%
건 38
11.6%
만 38
11.6%
외 25
 
7.6%
국 21
 
6.4%
미 21
 
6.4%
불 15
 
4.6%
유 6
 
1.8%
Other values (2) 2
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 432
19.3%
2 306
13.6%
3 280
12.5%
4 221
9.9%
5 193
8.6%
8 181
8.1%
7 180
8.0%
6 164
 
7.3%
9 147
 
6.6%
0 138
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 6
23.1%
a 6
23.1%
b 5
19.2%
r 3
11.5%
n 2
 
7.7%
p 1
 
3.8%
u 1
 
3.8%
g 1
 
3.8%
y 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
F 5
38.5%
M 4
30.8%
J 2
 
15.4%
S 1
 
7.7%
A 1
 
7.7%
Dash Punctuation
ValueCountFrequency (%)
- 448
100.0%
Space Separator
ValueCountFrequency (%)
193
100.0%
Other Punctuation
ValueCountFrequency (%)
, 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2966
89.0%
Hangul 328
 
9.8%
Latin 39
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6
15.4%
a 6
15.4%
F 5
12.8%
b 5
12.8%
M 4
10.3%
r 3
7.7%
n 2
 
5.1%
J 2
 
5.1%
S 1
 
2.6%
p 1
 
2.6%
Other values (4) 4
10.3%
Common
ValueCountFrequency (%)
- 448
15.1%
1 432
14.6%
2 306
10.3%
3 280
9.4%
4 221
7.5%
5 193
6.5%
193
6.5%
8 181
6.1%
7 180
6.1%
6 164
 
5.5%
Other values (3) 368
12.4%
Hangul
ValueCountFrequency (%)
공 65
19.8%
시 59
18.0%
물 38
11.6%
건 38
11.6%
만 38
11.6%
외 25
 
7.6%
국 21
 
6.4%
미 21
 
6.4%
불 15
 
4.6%
유 6
 
1.8%
Other values (2) 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3005
90.2%
Hangul 328
 
9.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 448
14.9%
1 432
14.4%
2 306
10.2%
3 280
9.3%
4 221
7.4%
5 193
6.4%
193
6.4%
8 181
6.0%
7 180
6.0%
6 164
 
5.5%
Other values (17) 407
13.5%
Hangul
ValueCountFrequency (%)
공 65
19.8%
시 59
18.0%
물 38
11.6%
건 38
11.6%
만 38
11.6%
외 25
 
7.6%
국 21
 
6.4%
미 21
 
6.4%
불 15
 
4.6%
유 6
 
1.8%
Other values (2) 2
 
0.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-06-19 00:00:00
Maximum2023-06-19 00:00:00
2023-12-12T07:51:54.767139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:54.855796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T07:51:49.300871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:44.661099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:45.417442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:46.184059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:46.982572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:47.970175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:48.628698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:49.388281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:44.775696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:45.524211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:46.309452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:47.106717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:48.080272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:48.739570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:49.477881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:44.893014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:45.654708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:46.436221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:47.266145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:48.177750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:48.841991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:49.566824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:44.999860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:45.751218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:46.525754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:47.359414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:48.258594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:48.928483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:49.645457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:45.113018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:45.842825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:46.612356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:47.667787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:48.355417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:49.014966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:49.732993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:45.221994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:45.956651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:46.716127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:47.776500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:48.442945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:49.112077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:49.817091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:45.321843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:46.067312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:46.853037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:47.868686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:48.528857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:49.210217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:51:54.921480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련 번호동 번호전체면적(제곱미터)공시면적(제곱미터)대지면적건물연면적용도지역건물용도건물구조가격
일련 번호1.0000.0000.0250.0620.2350.1170.5790.1690.2760.216
동 번호0.0001.0000.0000.0000.0420.0070.0000.0860.0000.124
전체면적(제곱미터)0.0250.0001.0000.0000.0000.0000.1770.0000.0000.000
공시면적(제곱미터)0.0620.0000.0001.0000.2890.4000.2100.7030.1930.327
대지면적0.2350.0420.0000.2891.0000.4360.2070.3230.1770.477
건물연면적0.1170.0070.0000.4000.4361.0000.1140.4360.4300.870
용도지역0.5790.0000.1770.2100.2070.1141.0000.3250.2620.217
건물용도0.1690.0860.0000.7030.3230.4360.3251.0000.4070.414
건물구조0.2760.0000.0000.1930.1770.4300.2620.4071.0000.487
가격0.2160.1240.0000.3270.4770.8700.2170.4140.4871.000
2023-12-12T07:51:55.061285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물용도건물구조용도지역
건물용도1.0000.1400.133
건물구조0.1401.0000.095
용도지역0.1330.0951.000
2023-12-12T07:51:55.152234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련 번호동 번호전체면적(제곱미터)공시면적(제곱미터)대지면적건물연면적가격용도지역건물용도건물구조
일련 번호1.000-0.0320.116-0.0140.1290.007-0.1180.2910.0690.104
동 번호-0.0321.0000.001-0.051-0.050-0.050-0.0300.0000.0670.000
전체면적(제곱미터)0.1160.0011.0000.3540.8440.3520.4470.0910.0000.000
공시면적(제곱미터)-0.014-0.0510.3541.0000.2160.8810.4870.0960.3900.074
대지면적0.129-0.0500.8440.2161.0000.3910.4960.0890.1360.066
건물연면적0.007-0.0500.3520.8810.3911.0000.5500.0480.1920.172
가격-0.118-0.0300.4470.4870.4960.5501.0000.0940.1810.201
용도지역0.2910.0000.0910.0960.0890.0480.0941.0000.1330.095
건물용도0.0690.0670.0000.3900.1360.1920.1810.1331.0000.140
건물구조0.1040.0000.0000.0740.0660.1720.2010.0950.1401.000

Missing values

2023-12-12T07:51:49.934136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:51:50.147537image/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

일련 번호소재지동 번호전체면적(제곱미터)공시면적(제곱미터)대지면적건물연면적용도지역건물용도건물구조가격비고데이터기준일자
12061207하동군 하동읍 비파리 388197.038.097.038.02주단독목16000000<NA>2023-06-19
67276728하동군 횡천면 횡천리 6581602.787.02602.787.02계관단독블록30900000<NA>2023-06-19
10191020하동군 하동읍 광평리 268-261330.079.8330.079.82주단독연와78600000<NA>2023-06-19
1410114102하동군 옥종면 청룡리 216-101609.0315.9609.0315.9계관단독블록67000000<NA>2023-06-19
77117712하동군 고전면 신월리 1165-11359.050.0359.050.0계관단독목11200000<NA>2023-06-19
1050010501하동군 진교면 양포리 33-162312.074.58312.074.58보관단독목구6320000033-202023-06-19
1466414665하동군 옥종면 안계리 6511322.041.2322.041.2계관단독목9450000<NA>2023-06-19
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