Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows45
Duplicate rows (%)0.4%
Total size in memory1.3 MiB
Average record size in memory138.0 B

Variable types

Categorical6
Numeric6
Text2
DateTime1

Dataset

Description일반건축물에 대한 지방세 부과기준인 시가표준액을 제공하며, 과세년도, 법정동, 법정리, 특수지, 본번, 부번, 동, 호, 물건지, 시가표준액, 연면적 등 항목이 있습니다
URLhttps://www.data.go.kr/data/15080617/fileData.do

Alerts

시도명 has constant value ""Constant
과세년도 has constant value ""Constant
법정리 has constant value ""Constant
기준일자 has constant value ""Constant
Dataset has 45 (0.4%) duplicate rowsDuplicates
자치단체코드 is highly overall correlated with 법정동 and 1 other fieldsHigh correlation
시군구명 is highly overall correlated with 법정동 and 1 other fieldsHigh correlation
법정동 is highly overall correlated with 시군구명 and 2 other fieldsHigh correlation
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
특수지 is highly overall correlated with 법정동High correlation
특수지 is highly imbalanced (87.3%)Imbalance
연면적 is highly skewed (γ1 = 20.56183972)Skewed
부번 has 5337 (53.4%) zerosZeros
동 has 347 (3.5%) zerosZeros

Reproduction

Analysis started2023-12-12 15:24:32.090179
Analysis finished2023-12-12 15:24:39.300291
Duration7.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 10000
100.0%

Length

2023-12-13T00:24:39.414036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:24:39.575094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 10000
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
성남시중원구
4467 
성남시수정구
3291 
성남시분당구
2242 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성남시중원구
2nd row성남시중원구
3rd row성남시수정구
4th row성남시중원구
5th row성남시중원구

Common Values

ValueCountFrequency (%)
성남시중원구 4467
44.7%
성남시수정구 3291
32.9%
성남시분당구 2242
22.4%

Length

2023-12-13T00:24:39.751297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:24:39.909646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시중원구 4467
44.7%
성남시수정구 3291
32.9%
성남시분당구 2242
22.4%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
41133
4467 
41131
3291 
41135
2242 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41133
2nd row41133
3rd row41131
4th row41133
5th row41133

Common Values

ValueCountFrequency (%)
41133 4467
44.7%
41131 3291
32.9%
41135 2242
22.4%

Length

2023-12-13T00:24:40.089797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:24:40.376297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41133 4467
44.7%
41131 3291
32.9%
41135 2242
22.4%

과세년도
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

2023-12-13T00:24:40.634770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:24:40.765656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

법정동
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.1798
Minimum101
Maximum132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:24:40.891151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1102
median103
Q3106
95-th percentile115
Maximum132
Range31
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.6878561
Coefficient of variation (CV)0.054077457
Kurtosis11.486492
Mean105.1798
Median Absolute Deviation (MAD)2
Skewness3.12987
Sum1051798
Variance32.351707
MonotonicityNot monotonic
2023-12-13T00:24:41.032868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
105 2061
20.6%
101 1922
19.2%
103 1828
18.3%
102 1451
14.5%
108 896
9.0%
132 282
 
2.8%
115 280
 
2.8%
106 240
 
2.4%
107 240
 
2.4%
112 240
 
2.4%
Other values (7) 560
 
5.6%
ValueCountFrequency (%)
101 1922
19.2%
102 1451
14.5%
103 1828
18.3%
104 218
 
2.2%
105 2061
20.6%
106 240
 
2.4%
107 240
 
2.4%
108 896
9.0%
109 201
 
2.0%
110 8
 
0.1%
ValueCountFrequency (%)
132 282
 
2.8%
117 30
 
0.3%
116 65
 
0.7%
115 280
 
2.8%
113 32
 
0.3%
112 240
 
2.4%
111 6
 
0.1%
110 8
 
0.1%
109 201
 
2.0%
108 896
9.0%

법정리
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-13T00:24:41.209371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:24:41.338475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

특수지
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9703 
3
 
281
2
 
16

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 9703
97.0%
3 281
 
2.8%
2 16
 
0.2%

Length

2023-12-13T00:24:41.479497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:24:41.599978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9703
97.0%
3 281
 
2.8%
2 16
 
0.2%

본번
Real number (ℝ)

Distinct2057
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1472.2743
Minimum1
Maximum7346
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:24:41.739459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q1138
median513
Q32968
95-th percentile5445
Maximum7346
Range7345
Interquartile range (IQR)2830

Descriptive statistics

Standard deviation1854.4925
Coefficient of variation (CV)1.2596107
Kurtosis0.31502367
Mean1472.2743
Median Absolute Deviation (MAD)489
Skewness1.2209484
Sum14722743
Variance3439142.3
MonotonicityNot monotonic
2023-12-13T00:24:41.917832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3499 369
 
3.7%
16 209
 
2.1%
223 196
 
2.0%
7 190
 
1.9%
509 174
 
1.7%
5460 166
 
1.7%
146 156
 
1.6%
513 152
 
1.5%
17 148
 
1.5%
559 148
 
1.5%
Other values (2047) 8092
80.9%
ValueCountFrequency (%)
1 33
 
0.3%
2 2
 
< 0.1%
3 1
 
< 0.1%
4 44
 
0.4%
5 59
 
0.6%
6 104
1.0%
7 190
1.9%
8 45
 
0.4%
9 50
 
0.5%
10 109
1.1%
ValueCountFrequency (%)
7346 1
 
< 0.1%
7343 1
 
< 0.1%
7340 2
 
< 0.1%
7339 5
0.1%
7338 5
0.1%
7335 1
 
< 0.1%
7331 2
 
< 0.1%
7329 1
 
< 0.1%
7325 1
 
< 0.1%
7317 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct63
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5787
Minimum0
Maximum161
Zeros5337
Zeros (%)53.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:24:42.085587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile12
Maximum161
Range161
Interquartile range (IQR)2

Descriptive statistics

Standard deviation6.643615
Coefficient of variation (CV)2.5763427
Kurtosis141.40016
Mean2.5787
Median Absolute Deviation (MAD)0
Skewness8.8239192
Sum25787
Variance44.13762
MonotonicityNot monotonic
2023-12-13T00:24:42.280135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5337
53.4%
1 1370
 
13.7%
2 913
 
9.1%
3 488
 
4.9%
5 266
 
2.7%
4 253
 
2.5%
6 220
 
2.2%
8 220
 
2.2%
7 212
 
2.1%
27 114
 
1.1%
Other values (53) 607
 
6.1%
ValueCountFrequency (%)
0 5337
53.4%
1 1370
 
13.7%
2 913
 
9.1%
3 488
 
4.9%
4 253
 
2.5%
5 266
 
2.7%
6 220
 
2.2%
7 212
 
2.1%
8 220
 
2.2%
9 85
 
0.9%
ValueCountFrequency (%)
161 1
< 0.1%
155 1
< 0.1%
153 1
< 0.1%
124 1
< 0.1%
119 1
< 0.1%
113 1
< 0.1%
106 1
< 0.1%
103 1
< 0.1%
96 1
< 0.1%
75 1
< 0.1%

동
Real number (ℝ)

ZEROS 

Distinct67
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean662.8427
Minimum0
Maximum9025
Zeros347
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:24:42.466304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile8001
Maximum9025
Range9025
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2208.1893
Coefficient of variation (CV)3.3313927
Kurtosis7.5072632
Mean662.8427
Median Absolute Deviation (MAD)0
Skewness3.0753912
Sum6628427
Variance4876100.1
MonotonicityNot monotonic
2023-12-13T00:24:42.617279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 8268
82.7%
0 347
 
3.5%
8001 326
 
3.3%
2 295
 
2.9%
8002 256
 
2.6%
9001 65
 
0.7%
8003 53
 
0.5%
3 49
 
0.5%
8006 36
 
0.4%
102 29
 
0.3%
Other values (57) 276
 
2.8%
ValueCountFrequency (%)
0 347
 
3.5%
1 8268
82.7%
2 295
 
2.9%
3 49
 
0.5%
4 21
 
0.2%
5 5
 
0.1%
6 14
 
0.1%
7 7
 
0.1%
8 5
 
0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
9025 4
 
< 0.1%
9001 65
 
0.7%
9000 26
 
0.3%
8889 1
 
< 0.1%
8028 1
 
< 0.1%
8006 36
 
0.4%
8005 7
 
0.1%
8004 3
 
< 0.1%
8003 53
 
0.5%
8002 256
2.6%

호
Text

Distinct1835
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T00:24:43.052029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length2.7777
Min length1

Characters and Unicode

Total characters27777
Distinct characters28
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1107 ?
Unique (%)11.1%

Sample

1st row6068
2nd row819
3rd row1
4th row158
5th row311
ValueCountFrequency (%)
1 2297
 
22.9%
2 389
 
3.9%
101 261
 
2.6%
8001 187
 
1.9%
201 134
 
1.3%
8101 123
 
1.2%
102 102
 
1.0%
3 100
 
1.0%
202 86
 
0.9%
103 80
 
0.8%
Other values (1801) 6274
62.5%
2023-12-13T00:24:43.611195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8525
30.7%
0 5744
20.7%
2 3273
 
11.8%
3 1923
 
6.9%
8 1719
 
6.2%
4 1462
 
5.3%
5 1351
 
4.9%
6 1186
 
4.3%
7 1042
 
3.8%
9 826
 
3.0%
Other values (18) 726
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27051
97.4%
Uppercase Letter 429
 
1.5%
Dash Punctuation 222
 
0.8%
Lowercase Letter 36
 
0.1%
Space Separator 33
 
0.1%
Other Letter 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8525
31.5%
0 5744
21.2%
2 3273
 
12.1%
3 1923
 
7.1%
8 1719
 
6.4%
4 1462
 
5.4%
5 1351
 
5.0%
6 1186
 
4.4%
7 1042
 
3.9%
9 826
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
A 193
45.0%
B 88
20.5%
F 78
18.2%
D 24
 
5.6%
C 14
 
3.3%
J 13
 
3.0%
S 11
 
2.6%
R 5
 
1.2%
M 3
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
a 16
44.4%
n 13
36.1%
r 3
 
8.3%
e 2
 
5.6%
b 2
 
5.6%
Other Letter
ValueCountFrequency (%)
가 4
66.7%
나 2
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 222
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27306
98.3%
Latin 465
 
1.7%
Hangul 6
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 193
41.5%
B 88
18.9%
F 78
16.8%
D 24
 
5.2%
a 16
 
3.4%
C 14
 
3.0%
n 13
 
2.8%
J 13
 
2.8%
S 11
 
2.4%
R 5
 
1.1%
Other values (4) 10
 
2.2%
Common
ValueCountFrequency (%)
1 8525
31.2%
0 5744
21.0%
2 3273
 
12.0%
3 1923
 
7.0%
8 1719
 
6.3%
4 1462
 
5.4%
5 1351
 
4.9%
6 1186
 
4.3%
7 1042
 
3.8%
9 826
 
3.0%
Other values (2) 255
 
0.9%
Hangul
ValueCountFrequency (%)
가 4
66.7%
나 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27771
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8525
30.7%
0 5744
20.7%
2 3273
 
11.8%
3 1923
 
6.9%
8 1719
 
6.2%
4 1462
 
5.3%
5 1351
 
4.9%
6 1186
 
4.3%
7 1042
 
3.8%
9 826
 
3.0%
Other values (16) 720
 
2.6%
Hangul
ValueCountFrequency (%)
가 4
66.7%
나 2
33.3%

물건지
Text

Distinct8895
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T00:24:43.926229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length16.8876
Min length5

Characters and Unicode

Total characters168876
Distinct characters358
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8137 ?
Unique (%)81.4%

Sample

1st row성남동 3499 1동 6068호
2nd row상대원동 143-2 성남센트럴비즈타워1차 1동 819호
3rd row시흥동 77-26
4th row금광동 10 1동 158호
5th row성남동 3135 지앤느모란 1동 311호
ValueCountFrequency (%)
1동 5090
 
13.6%
상대원동 1999
 
5.4%
성남동 1234
 
3.3%
정자동 1180
 
3.2%
수내동 981
 
2.6%
창곡동 883
 
2.4%
신흥동 608
 
1.6%
태평동 470
 
1.3%
3499 369
 
1.0%
금광동 345
 
0.9%
Other values (5186) 24194
64.8%
2023-12-13T00:24:44.475594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27353
16.2%
1 17281
 
10.2%
동 16523
 
9.8%
2 8087
 
4.8%
0 7657
 
4.5%
3 6644
 
3.9%
호 6577
 
3.9%
4 5838
 
3.5%
5 5543
 
3.3%
- 4890
 
2.9%
Other values (348) 62483
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69331
41.1%
Decimal Number 64869
38.4%
Space Separator 27353
 
16.2%
Dash Punctuation 4890
 
2.9%
Uppercase Letter 2298
 
1.4%
Open Punctuation 39
 
< 0.1%
Close Punctuation 39
 
< 0.1%
Lowercase Letter 27
 
< 0.1%
Other Punctuation 24
 
< 0.1%
Letter Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 16523
23.8%
호 6577
 
9.5%
대 2450
 
3.5%
성 2265
 
3.3%
원 2246
 
3.2%
상 2107
 
3.0%
남 2083
 
3.0%
수 1486
 
2.1%
정 1350
 
1.9%
자 1336
 
1.9%
Other values (299) 30908
44.6%
Uppercase Letter
ValueCountFrequency (%)
A 618
26.9%
B 349
15.2%
L 152
 
6.6%
F 148
 
6.4%
V 136
 
5.9%
Y 134
 
5.8%
C 114
 
5.0%
I 111
 
4.8%
E 97
 
4.2%
K 67
 
2.9%
Other values (13) 372
16.2%
Decimal Number
ValueCountFrequency (%)
1 17281
26.6%
2 8087
12.5%
0 7657
11.8%
3 6644
 
10.2%
4 5838
 
9.0%
5 5543
 
8.5%
6 4376
 
6.7%
9 3876
 
6.0%
7 3116
 
4.8%
8 2451
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
o 6
22.2%
l 4
14.8%
e 3
11.1%
y 3
11.1%
r 3
11.1%
m 3
11.1%
b 3
11.1%
i 2
 
7.4%
Other Punctuation
ValueCountFrequency (%)
, 12
50.0%
. 9
37.5%
/ 3
 
12.5%
Space Separator
ValueCountFrequency (%)
27353
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4890
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97214
57.6%
Hangul 69326
41.1%
Latin 2331
 
1.4%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 16523
23.8%
호 6577
 
9.5%
대 2450
 
3.5%
성 2265
 
3.3%
원 2246
 
3.2%
상 2107
 
3.0%
남 2083
 
3.0%
수 1486
 
2.1%
정 1350
 
1.9%
자 1336
 
1.9%
Other values (298) 30903
44.6%
Latin
ValueCountFrequency (%)
A 618
26.5%
B 349
15.0%
L 152
 
6.5%
F 148
 
6.3%
V 136
 
5.8%
Y 134
 
5.7%
C 114
 
4.9%
I 111
 
4.8%
E 97
 
4.2%
K 67
 
2.9%
Other values (22) 405
17.4%
Common
ValueCountFrequency (%)
27353
28.1%
1 17281
17.8%
2 8087
 
8.3%
0 7657
 
7.9%
3 6644
 
6.8%
4 5838
 
6.0%
5 5543
 
5.7%
- 4890
 
5.0%
6 4376
 
4.5%
9 3876
 
4.0%
Other values (7) 5669
 
5.8%
Han
ValueCountFrequency (%)
家 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99539
58.9%
Hangul 69326
41.1%
Number Forms 6
 
< 0.1%
CJK 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27353
27.5%
1 17281
17.4%
2 8087
 
8.1%
0 7657
 
7.7%
3 6644
 
6.7%
4 5838
 
5.9%
5 5543
 
5.6%
- 4890
 
4.9%
6 4376
 
4.4%
9 3876
 
3.9%
Other values (38) 7994
 
8.0%
Hangul
ValueCountFrequency (%)
동 16523
23.8%
호 6577
 
9.5%
대 2450
 
3.5%
성 2265
 
3.3%
원 2246
 
3.2%
상 2107
 
3.0%
남 2083
 
3.0%
수 1486
 
2.1%
정 1350
 
1.9%
자 1336
 
1.9%
Other values (298) 30903
44.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
100.0%
CJK
ValueCountFrequency (%)
家 5
100.0%

시가표준액
Real number (ℝ)

HIGH CORRELATION 

Distinct7762
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85477538
Minimum39886
Maximum1.0053093 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:24:44.651093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39886
5-th percentile3676059.2
Q117197290
median47946260
Q394257555
95-th percentile2.2823389 × 108
Maximum1.0053093 × 1010
Range1.0053053 × 1010
Interquartile range (IQR)77060265

Descriptive statistics

Standard deviation2.4060293 × 108
Coefficient of variation (CV)2.8148089
Kurtosis553.33816
Mean85477538
Median Absolute Deviation (MAD)34314393
Skewness19.431067
Sum8.5477538 × 1011
Variance5.7889772 × 1016
MonotonicityNot monotonic
2023-12-13T00:24:45.100091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3449564 63
 
0.6%
10588791 45
 
0.4%
54940853 35
 
0.4%
58403683 34
 
0.3%
48218236 33
 
0.3%
76155897 32
 
0.3%
61293294 31
 
0.3%
49170880 27
 
0.3%
54915909 25
 
0.2%
70392520 24
 
0.2%
Other values (7752) 9651
96.5%
ValueCountFrequency (%)
39886 1
< 0.1%
126500 1
< 0.1%
159870 1
< 0.1%
167700 1
< 0.1%
196020 1
< 0.1%
213840 1
< 0.1%
235400 1
< 0.1%
272000 1
< 0.1%
272280 1
< 0.1%
283500 1
< 0.1%
ValueCountFrequency (%)
10053092756 1
< 0.1%
6865831394 1
< 0.1%
6684369803 1
< 0.1%
6168266280 1
< 0.1%
5606581367 1
< 0.1%
5242417721 1
< 0.1%
4526248311 1
< 0.1%
4198035080 1
< 0.1%
3692068560 1
< 0.1%
3508189680 2
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6829
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.8871
Minimum0.7332
Maximum14746.604
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:24:45.255543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.7332
5-th percentile9.2458
Q139.4295
median71.6018
Q3136.5225
95-th percentile344.4805
Maximum14746.604
Range14745.871
Interquartile range (IQR)97.093

Descriptive statistics

Standard deviation313.40462
Coefficient of variation (CV)2.4316214
Kurtosis696.52851
Mean128.8871
Median Absolute Deviation (MAD)42.2311
Skewness20.56184
Sum1288871
Variance98222.458
MonotonicityNot monotonic
2023-12-13T00:24:45.397910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.893 63
 
0.6%
8.2275 48
 
0.5%
71.89 35
 
0.4%
62.795 34
 
0.3%
59.884 33
 
0.3%
99.39 32
 
0.3%
74.55 31
 
0.3%
112.09 27
 
0.3%
64.34 27
 
0.3%
69.76 25
 
0.2%
Other values (6819) 9645
96.5%
ValueCountFrequency (%)
0.7332 1
< 0.1%
0.855 1
< 0.1%
1.0 1
< 0.1%
1.01 1
< 0.1%
1.0935 1
< 0.1%
1.11 1
< 0.1%
1.17 1
< 0.1%
1.2827 1
< 0.1%
1.34 1
< 0.1%
1.41 2
< 0.1%
ValueCountFrequency (%)
14746.604 1
< 0.1%
10072.89 1
< 0.1%
8246.9998 1
< 0.1%
6506.61 1
< 0.1%
6453.35 1
< 0.1%
6258.1637 1
< 0.1%
5945.36 1
< 0.1%
4057.9735 1
< 0.1%
3685.72 1
< 0.1%
3663.89 1
< 0.1%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-06-14 00:00:00
Maximum2023-06-14 00:00:00
2023-12-13T00:24:45.561765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:45.658102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T00:24:38.086954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:33.811868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:34.618818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:35.490105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:36.390694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:37.335634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:38.221783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:33.918324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:34.786257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:35.642809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:36.826062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:37.458320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:38.344047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:34.037736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:34.936964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:35.781085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:36.937563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:37.570529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:38.473617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:34.196605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:35.087896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:35.973663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:37.042918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:37.708577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:38.569251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:34.309103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:35.220825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:36.122545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:37.132992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:37.805575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:38.682264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:34.437731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:35.360319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:36.262318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:37.233488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:37.924529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:24:45.747702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드법정동특수지본번부번동시가표준액연면적
시군구명1.0001.0000.6520.4550.5140.2280.3580.0790.042
자치단체코드1.0001.0000.6520.4550.5140.2280.3580.0790.042
법정동0.6520.6521.0000.7150.4660.1600.2410.0600.055
특수지0.4550.4550.7151.0000.1500.0000.0960.0890.061
본번0.5140.5140.4660.1501.0000.0690.1730.0000.000
부번0.2280.2280.1600.0000.0691.0000.0380.0000.000
동0.3580.3580.2410.0960.1730.0381.0000.0000.000
시가표준액0.0790.0790.0600.0890.0000.0000.0001.0000.874
연면적0.0420.0420.0550.0610.0000.0000.0000.8741.000
2023-12-13T00:24:45.874490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자치단체코드시군구명특수지
자치단체코드1.0001.0000.176
시군구명1.0001.0000.176
특수지0.1760.1761.000
2023-12-13T00:24:46.013227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액연면적시군구명자치단체코드특수지
법정동1.000-0.1890.158-0.0330.1380.1110.5550.5550.634
본번-0.1891.000-0.400-0.258-0.176-0.1290.3590.3590.090
부번0.158-0.4001.000-0.0400.1420.1690.1020.1020.000
동-0.033-0.258-0.0401.0000.0390.0140.2580.2580.064
시가표준액0.138-0.1760.1420.0391.0000.8820.0500.0500.056
연면적0.111-0.1290.1690.0140.8821.0000.0280.0280.041
시군구명0.5550.3590.1020.2580.0500.0281.0001.0000.176
자치단체코드0.5550.3590.1020.2580.0500.0281.0001.0000.176
특수지0.6340.0900.0000.0640.0560.0410.1760.1761.000

Missing values

2023-12-13T00:24:38.859653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:24:39.141345image/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

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자
39233경기도성남시중원구411332022101013499016068성남동 3499 1동 6068호34495644.8932023-06-14
49930경기도성남시중원구4113320221050114321819상대원동 143-2 성남센트럴비즈타워1차 1동 819호99984360128.682023-06-14
28666경기도성남시수정구41131202211501772611시흥동 77-26135476370176.622023-06-14
43817경기도성남시중원구411332022103011001158금광동 10 1동 158호531300013.82023-06-14
35523경기도성남시중원구41133202210101313501311성남동 3135 지앤느모란 1동 311호5394233754.59692023-06-14
8354경기도성남시수정구41131202210201511391302태평동 5113-9 1동 302호64378720195.682023-06-14
52464경기도성남시중원구41133202210501146821012상대원동 146-8 성남우림라이온스밸리2차 2동 1012호70392520112.092023-06-14
95576경기도성남시분당구41135202210301161002701정자동 16145262483113418.412023-06-14
6449경기도성남시수정구411312022102013180111태평동 3180-128776220103.42023-06-14
28845경기도성남시수정구411312022115012051111시흥동 205-121946701103663.892023-06-14
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자
92864경기도성남시분당구4113520221030110231101정자동 102-3191160613334.462023-06-14
37241경기도성남시중원구411332022101013499011097성남동 3499 1동 1097호34418104.8822023-06-14
22932경기도성남시수정구4113120221080155981807창곡동 559-8 위례성희프라자 1동 807호140222190132.382023-06-14
35390경기도성남시중원구411332022101013123011성남동 3123819467064.782023-06-14
58451경기도성남시중원구41133202210501370511상대원동 370-5 한일문화사491065400825.322023-06-14
36848경기도성남시중원구411332022101013492011성남동 349211117216102.93722023-06-14
34818경기도성남시중원구411332022101012481011성남동 248164831900132.312023-06-14
1162경기도성남시수정구41131202210101246571108신흥동 2465-7 1동 108호3700953028.232023-06-14
34174경기도성남시중원구41133202210101226401912성남동 2264 성남 모란 지웰에스테이트 1동 912호6759310661.17612023-06-14
87796경기도성남시분당구4113520221030116180021010정자동 16-1 AK와이즈플레이스 B동 1010호7719537672.152023-06-14

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자# duplicates
0경기도성남시분당구411352022102019311수내동 9-311856251401178.68272023-06-143
2경기도성남시수정구411312022101012458011신흥동 2458177064800501.62023-06-143
5경기도성남시수정구411312022101015539011신흥동 5539556584390690.982023-06-143
10경기도성남시수정구411312022102016136011태평동 6136110323323141.11092023-06-143
1경기도성남시분당구4113520221020128411수내동 28-4190276800323.62023-06-142
3경기도성남시수정구411312022101013421011신흥동 342181681600185.642023-06-142
4경기도성남시수정구411312022101015471011신흥동 54714946759450.9452023-06-142
6경기도성남시수정구411312022101015542011신흥동 5542393348960815.42023-06-142
7경기도성남시수정구411312022102012705011태평동 270567612500180.32023-06-142
8경기도성남시수정구411312022102013499011태평동 3499162397243192.882023-06-142