Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows9
Duplicate rows (%)0.1%
Total size in memory1.2 MiB
Average record size in memory128.0 B

Variable types

Categorical6
Numeric5
Unsupported1
Text2

Dataset

Description인천광역시(군, 구 포함) 주택외건축물 시가표준액 정보 데이터 자료 제공하며, 2023년 재산세 과세자료 중 물건지와 연면적 정보를 포함하고 있음
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15043085&srcSe=7661IVAWM27C61E190

Alerts

시도 has constant value ""Constant
과세연도 has constant value ""Constant
법정리 has constant value ""Constant
기준일자 has constant value ""Constant
Dataset has 9 (0.1%) duplicate rowsDuplicates
법정동코드 is highly overall correlated with 본번 and 1 other fieldsHigh correlation
본번 is highly overall correlated with 법정동코드High correlation
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
시군구 is highly overall correlated with 법정동코드High correlation
특수지 is highly imbalanced (97.6%)Imbalance
시가표준액 is highly skewed (γ1 = 34.47369938)Skewed
연면적 is highly skewed (γ1 = 25.48239183)Skewed
동 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부번 has 1875 (18.8%) zerosZeros

Reproduction

Analysis started2024-03-18 05:30:22.343350
Analysis finished2024-03-18 05:30:25.964469
Duration3.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 10000
100.0%

Length

2024-03-18T14:30:26.015156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:26.090580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 10000
100.0%

시군구
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
중구
6648 
동구
2492 
미추홀구
860 

Length

Max length4
Median length2
Mean length2.172
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동구
2nd row중구
3rd row중구
4th row중구
5th row동구

Common Values

ValueCountFrequency (%)
중구 6648
66.5%
동구 2492
 
24.9%
미추홀구 860
 
8.6%

Length

2024-03-18T14:30:26.186796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:26.284329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 6648
66.5%
동구 2492
 
24.9%
미추홀구 860
 
8.6%

과세연도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 10000
100.0%

Length

2024-03-18T14:30:26.375500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:26.451035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 10000
100.0%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.8567
Minimum101
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T14:30:26.545596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile102
Q1107
median128
Q3145
95-th percentile148
Maximum152
Range51
Interquartile range (IQR)38

Descriptive statistics

Standard deviation18.704495
Coefficient of variation (CV)0.14744586
Kurtosis-1.6945867
Mean126.8567
Median Absolute Deviation (MAD)19
Skewness-0.15815154
Sum1268567
Variance349.85815
MonotonicityNot monotonic
2024-03-18T14:30:26.670589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147 1546
15.5%
145 1492
14.9%
107 1247
12.5%
103 888
8.9%
118 756
 
7.6%
102 573
 
5.7%
128 390
 
3.9%
101 379
 
3.8%
146 274
 
2.7%
149 248
 
2.5%
Other values (41) 2207
22.1%
ValueCountFrequency (%)
101 379
 
3.8%
102 573
5.7%
103 888
8.9%
104 240
 
2.4%
105 35
 
0.4%
106 96
 
1.0%
107 1247
12.5%
108 2
 
< 0.1%
109 9
 
0.1%
110 7
 
0.1%
ValueCountFrequency (%)
152 67
 
0.7%
151 54
 
0.5%
150 61
 
0.6%
149 248
 
2.5%
148 191
 
1.9%
147 1546
15.5%
146 274
 
2.7%
145 1492
14.9%
144 20
 
0.2%
143 8
 
0.1%

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

2024-03-18T14:30:26.810935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:26.898546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

특수지
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9976 
2
 
24

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 9976
99.8%
2 24
 
0.2%

Length

2024-03-18T14:30:26.978736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:27.055679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9976
99.8%
2 24
 
0.2%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct920
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean874.6418
Minimum1
Maximum3246
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T14:30:27.148194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q150
median291
Q31875
95-th percentile3088
Maximum3246
Range3245
Interquartile range (IQR)1825

Descriptive statistics

Standard deviation1083.8199
Coefficient of variation (CV)1.2391586
Kurtosis-0.65349054
Mean874.6418
Median Absolute Deviation (MAD)280
Skewness0.96917839
Sum8746418
Variance1174665.6
MonotonicityNot monotonic
2024-03-18T14:30:27.274812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129 415
 
4.2%
294 393
 
3.9%
1873 356
 
3.6%
1886 348
 
3.5%
2850 282
 
2.8%
1 260
 
2.6%
27 260
 
2.6%
295 233
 
2.3%
2 207
 
2.1%
7 200
 
2.0%
Other values (910) 7046
70.5%
ValueCountFrequency (%)
1 260
2.6%
2 207
2.1%
3 74
 
0.7%
4 96
 
1.0%
5 43
 
0.4%
6 75
 
0.8%
7 200
2.0%
8 59
 
0.6%
9 53
 
0.5%
10 44
 
0.4%
ValueCountFrequency (%)
3246 3
 
< 0.1%
3243 5
 
0.1%
3238 7
0.1%
3234 4
 
< 0.1%
3233 4
 
< 0.1%
3231 9
0.1%
3202 6
0.1%
3196 1
 
< 0.1%
3195 13
0.1%
3194 9
0.1%

부번
Real number (ℝ)

ZEROS 

Distinct376
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.1934
Minimum0
Maximum884
Zeros1875
Zeros (%)18.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T14:30:27.427422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q320
95-th percentile176.05
Maximum884
Range884
Interquartile range (IQR)19

Descriptive statistics

Standard deviation91.634281
Coefficient of variation (CV)2.7606175
Kurtosis32.391628
Mean33.1934
Median Absolute Deviation (MAD)5
Skewness5.194781
Sum331934
Variance8396.8415
MonotonicityNot monotonic
2024-03-18T14:30:27.555437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1875
18.8%
1 1154
 
11.5%
2 705
 
7.0%
4 624
 
6.2%
3 495
 
5.0%
5 399
 
4.0%
6 308
 
3.1%
7 299
 
3.0%
8 241
 
2.4%
11 230
 
2.3%
Other values (366) 3670
36.7%
ValueCountFrequency (%)
0 1875
18.8%
1 1154
11.5%
2 705
 
7.0%
3 495
 
5.0%
4 624
 
6.2%
5 399
 
4.0%
6 308
 
3.1%
7 299
 
3.0%
8 241
 
2.4%
9 141
 
1.4%
ValueCountFrequency (%)
884 1
< 0.1%
878 1
< 0.1%
875 1
< 0.1%
874 1
< 0.1%
870 1
< 0.1%
869 1
< 0.1%
866 1
< 0.1%
864 1
< 0.1%
863 1
< 0.1%
859 1
< 0.1%

동
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

호수
Text

Distinct1014
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-18T14:30:27.864483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length2.3831
Min length1

Characters and Unicode

Total characters23831
Distinct characters18
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique354 ?
Unique (%)3.5%

Sample

1st row316
2nd row6
3rd row405
4th row12
5th row101
ValueCountFrequency (%)
1 1733
 
17.3%
2 680
 
6.8%
3 389
 
3.9%
101 383
 
3.8%
0 324
 
3.2%
4 264
 
2.6%
201 216
 
2.2%
102 183
 
1.8%
5 153
 
1.5%
301 136
 
1.4%
Other values (1006) 5554
55.5%
2024-03-18T14:30:28.259296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7438
31.2%
0 4575
19.2%
2 3595
15.1%
3 2266
 
9.5%
4 1411
 
5.9%
5 1088
 
4.6%
6 957
 
4.0%
8 923
 
3.9%
7 756
 
3.2%
9 699
 
2.9%
Other values (8) 123
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23708
99.5%
Dash Punctuation 72
 
0.3%
Other Letter 32
 
0.1%
Space Separator 15
 
0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7438
31.4%
0 4575
19.3%
2 3595
15.2%
3 2266
 
9.6%
4 1411
 
6.0%
5 1088
 
4.6%
6 957
 
4.0%
8 923
 
3.9%
7 756
 
3.2%
9 699
 
2.9%
Other Letter
ValueCountFrequency (%)
월 15
46.9%
일 15
46.9%
지 2
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
S 1
25.0%
T 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23795
99.8%
Hangul 32
 
0.1%
Latin 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7438
31.3%
0 4575
19.2%
2 3595
15.1%
3 2266
 
9.5%
4 1411
 
5.9%
5 1088
 
4.6%
6 957
 
4.0%
8 923
 
3.9%
7 756
 
3.2%
9 699
 
2.9%
Other values (2) 87
 
0.4%
Hangul
ValueCountFrequency (%)
월 15
46.9%
일 15
46.9%
지 2
 
6.2%
Latin
ValueCountFrequency (%)
B 2
50.0%
S 1
25.0%
T 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23799
99.9%
Hangul 32
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7438
31.3%
0 4575
19.2%
2 3595
15.1%
3 2266
 
9.5%
4 1411
 
5.9%
5 1088
 
4.6%
6 957
 
4.0%
8 923
 
3.9%
7 756
 
3.2%
9 699
 
2.9%
Other values (5) 91
 
0.4%
Hangul
ValueCountFrequency (%)
월 15
46.9%
일 15
46.9%
지 2
 
6.2%

물건지
Text

Distinct9665
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-18T14:30:28.519930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length25.3122
Min length17

Characters and Unicode

Total characters253122
Distinct characters189
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

Unique9424 ?
Unique (%)94.2%

Sample

1st row인천광역시 동구 송림동 294 25동 316호
2nd row인천광역시 중구 무의동 562 1동 6호
3rd row인천광역시 중구 신흥동2가 54-5 405호
4th row인천광역시 중구 을왕동 857-1 1동 12호
5th row인천광역시 동구 만석동 2-18 1동 101호
ValueCountFrequency (%)
12208
20.6%
인천광역시 3896
 
6.6%
0001동 3060
 
5.2%
0000동 2416
 
4.1%
중구 2077
 
3.5%
동구 1668
 
2.8%
1동 1321
 
2.2%
0001호 926
 
1.6%
송림동 897
 
1.5%
1호 805
 
1.4%
Other values (4101) 30129
50.7%
2024-03-18T14:30:28.897980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49403
19.5%
0 37137
14.7%
1 19974
 
7.9%
동 15125
 
6.0%
2 10407
 
4.1%
호 9871
 
3.9%
3 6494
 
2.6%
] 6104
 
2.4%
[ 6104
 
2.4%
로 6002
 
2.4%
Other values (179) 86501
34.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99443
39.3%
Other Letter 88380
34.9%
Space Separator 49403
19.5%
Close Punctuation 6104
 
2.4%
Open Punctuation 6104
 
2.4%
Dash Punctuation 3684
 
1.5%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 15125
17.1%
호 9871
 
11.2%
로 6002
 
6.8%
인 4420
 
5.0%
시 4106
 
4.6%
광 3985
 
4.5%
천 3924
 
4.4%
구 3902
 
4.4%
역 3900
 
4.4%
길 3047
 
3.4%
Other values (162) 30098
34.1%
Decimal Number
ValueCountFrequency (%)
0 37137
37.3%
1 19974
20.1%
2 10407
 
10.5%
3 6494
 
6.5%
4 4984
 
5.0%
9 4926
 
5.0%
5 4315
 
4.3%
6 3807
 
3.8%
7 3725
 
3.7%
8 3674
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
S 1
25.0%
T 1
25.0%
Space Separator
ValueCountFrequency (%)
49403
100.0%
Close Punctuation
ValueCountFrequency (%)
] 6104
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 6104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3684
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 164738
65.1%
Hangul 88380
34.9%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 15125
17.1%
호 9871
 
11.2%
로 6002
 
6.8%
인 4420
 
5.0%
시 4106
 
4.6%
광 3985
 
4.5%
천 3924
 
4.4%
구 3902
 
4.4%
역 3900
 
4.4%
길 3047
 
3.4%
Other values (162) 30098
34.1%
Common
ValueCountFrequency (%)
49403
30.0%
0 37137
22.5%
1 19974
12.1%
2 10407
 
6.3%
3 6494
 
3.9%
] 6104
 
3.7%
[ 6104
 
3.7%
4 4984
 
3.0%
9 4926
 
3.0%
5 4315
 
2.6%
Other values (4) 14890
 
9.0%
Latin
ValueCountFrequency (%)
B 2
50.0%
S 1
25.0%
T 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 164742
65.1%
Hangul 88380
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49403
30.0%
0 37137
22.5%
1 19974
12.1%
2 10407
 
6.3%
3 6494
 
3.9%
] 6104
 
3.7%
[ 6104
 
3.7%
4 4984
 
3.0%
9 4926
 
3.0%
5 4315
 
2.6%
Other values (7) 14894
 
9.0%
Hangul
ValueCountFrequency (%)
동 15125
17.1%
호 9871
 
11.2%
로 6002
 
6.8%
인 4420
 
5.0%
시 4106
 
4.6%
광 3985
 
4.5%
천 3924
 
4.4%
구 3902
 
4.4%
역 3900
 
4.4%
길 3047
 
3.4%
Other values (162) 30098
34.1%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6537
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95624639
Minimum14100
Maximum3.7799163 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T14:30:29.045673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14100
5-th percentile1136485
Q16430477.5
median30324200
Q364482975
95-th percentile2.485148 × 108
Maximum3.7799163 × 1010
Range3.7799149 × 1010
Interquartile range (IQR)58052498

Descriptive statistics

Standard deviation6.7518428 × 108
Coefficient of variation (CV)7.0607773
Kurtosis1530.2461
Mean95624639
Median Absolute Deviation (MAD)25853965
Skewness34.473699
Sum9.5624639 × 1011
Variance4.5587381 × 1017
MonotonicityNot monotonic
2024-03-18T14:30:29.171418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13791820 223
 
2.2%
2050860 212
 
2.1%
18568530 103
 
1.0%
2361830 95
 
0.9%
39994020 63
 
0.6%
46195110 62
 
0.6%
39951740 54
 
0.5%
57045510 52
 
0.5%
2104830 52
 
0.5%
46161960 52
 
0.5%
Other values (6527) 9032
90.3%
ValueCountFrequency (%)
14100 1
 
< 0.1%
18800 2
 
< 0.1%
26460 1
 
< 0.1%
28200 3
< 0.1%
29100 1
 
< 0.1%
29400 1
 
< 0.1%
37600 1
 
< 0.1%
42600 5
0.1%
47000 2
 
< 0.1%
49840 6
0.1%
ValueCountFrequency (%)
37799162900 1
< 0.1%
29069590550 1
< 0.1%
20439533520 1
< 0.1%
19849834620 1
< 0.1%
16107581560 1
< 0.1%
12503688460 1
< 0.1%
9974902600 1
< 0.1%
9395368030 1
< 0.1%
9130042710 1
< 0.1%
8977981710 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5205
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean190.87512
Minimum0.15
Maximum45635.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T14:30:29.566495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.15
5-th percentile7.98
Q133.732925
median52.86
Q3110.7175
95-th percentile544.714
Maximum45635.15
Range45635
Interquartile range (IQR)76.984575

Descriptive statistics

Standard deviation1066.1426
Coefficient of variation (CV)5.5855501
Kurtosis860.70187
Mean190.87512
Median Absolute Deviation (MAD)32.62
Skewness25.482392
Sum1908751.2
Variance1136660
MonotonicityNot monotonic
2024-03-18T14:30:29.675413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 229
 
2.3%
33.97 223
 
2.2%
7.98 212
 
2.1%
39.09 103
 
1.0%
9.19 95
 
0.9%
27.0 77
 
0.8%
36.4909 63
 
0.6%
39.483 62
 
0.6%
57.9722 58
 
0.6%
40.3553 54
 
0.5%
Other values (5195) 8824
88.2%
ValueCountFrequency (%)
0.15 1
 
< 0.1%
0.2 2
 
< 0.1%
0.27 1
 
< 0.1%
0.3 16
0.2%
0.4 1
 
< 0.1%
0.5 3
 
< 0.1%
0.65 1
 
< 0.1%
0.7 10
0.1%
0.9 2
 
< 0.1%
0.924 1
 
< 0.1%
ValueCountFrequency (%)
45635.15 1
< 0.1%
41753.19 1
< 0.1%
39088.8 1
< 0.1%
26039.4 1
< 0.1%
24036.31 1
< 0.1%
20730.4782 1
< 0.1%
20610.61 1
< 0.1%
18948.1 1
< 0.1%
18589.17 1
< 0.1%
18186.93 1
< 0.1%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-06-01
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-01
2nd row2023-06-01
3rd row2023-06-01
4th row2023-06-01
5th row2023-06-01

Common Values

ValueCountFrequency (%)
2023-06-01 10000
100.0%

Length

2024-03-18T14:30:29.803863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:29.898815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-01 10000
100.0%

Interactions

2024-03-18T14:30:25.275106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:23.341764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:23.978331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.395662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.833781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:25.357266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:23.434134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.054626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.474418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.923854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:25.439428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:23.530888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.138526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.573259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:25.010814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:25.513231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:23.604540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.228453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.665110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:25.092896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:25.614304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:23.909344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.316573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:24.761888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:25.194907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:30:29.961364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구법정동코드특수지본번부번시가표준액연면적
시군구1.0000.8410.0130.6410.2120.0000.000
법정동코드0.8411.0000.0880.8580.3870.0050.036
특수지0.0130.0881.0000.0310.0000.0000.000
본번0.6410.8580.0311.0000.2120.0340.049
부번0.2120.3870.0000.2121.0000.0000.113
시가표준액0.0000.0050.0000.0340.0001.0000.958
연면적0.0000.0360.0000.0490.1130.9581.000
2024-03-18T14:30:30.053715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특수지시군구
특수지1.0000.022
시군구0.0221.000
2024-03-18T14:30:30.128937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드본번부번시가표준액연면적시군구특수지
법정동코드1.0000.584-0.0730.2450.1130.7530.068
본번0.5841.000-0.3050.2950.0150.4880.024
부번-0.073-0.3051.0000.0710.1410.1290.000
시가표준액0.2450.2950.0711.0000.8060.0000.000
연면적0.1130.0150.1410.8061.0000.0000.000
시군구0.7530.4880.1290.0000.0001.0000.022
특수지0.0680.0240.0000.0000.0000.0221.000

Missing values

2024-03-18T14:30:25.728520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:30:25.890840image/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

시도시군구과세연도법정동코드법정리특수지본번부번동호수물건지시가표준액연면적기준일자
79477인천광역시동구202310701294025316인천광역시 동구 송림동 294 25동 316호1379182033.972023-06-01
62232인천광역시중구202315201562016인천광역시 중구 무의동 562 1동 6호20160014.02023-06-01
10828인천광역시중구2023127015450405인천광역시 중구 신흥동2가 54-5 405호239980016.92023-06-01
61860인천광역시중구2023149018571112인천광역시 중구 을왕동 857-1 1동 12호175442960284.812023-06-01
63532인천광역시동구2023101012181101인천광역시 동구 만석동 2-18 1동 101호4654332902141.42023-06-01
32507인천광역시중구2023148011293711[ 미단뉴타운로26번길 7 ] 0001동 0001호8039336079.52812023-06-01
90402인천광역시미추홀구2023102014501920602[ 인주대로 132 ] 0000동 0602호127389090164.87512023-06-01
78074인천광역시동구202310301129033228인천광역시 동구 송현동 129 33동 228호21048308.192023-06-01
12385인천광역시중구20231280136013인천광역시 중구 신흥동3가 36 1동 3호101650500245.02023-06-01
44936인천광역시중구2023146011600111007[ 흰바위로 236 ] 0001동 1007호135308440148.562023-06-01
시도시군구과세연도법정동코드법정리특수지본번부번동호수물건지시가표준액연면적기준일자
86501인천광역시미추홀구202310101129471301인천광역시 미추홀구 숭의동 129-47 1동 301호17110160185.982023-06-01
81576인천광역시동구202310701294031122인천광역시 동구 송림동 294 31동 122호1856853039.092023-06-01
86658인천광역시미추홀구202310101148260605[ 미추로46번길 14 ] 0000동 0605호1382559035.81762023-06-01
11805인천광역시중구20231280117411[ 인중로 44 ] 0001동 0001호107274190151.052023-06-01
4031인천광역시중구202311801491147[ 축항대로69번길 20 ] 0001동 0047호1754298014.282023-06-01
35726인천광역시중구2023145011873210321[ 영종대로 875 ] 0000동 0321호9414054089.06392023-06-01
31350인천광역시중구202315202171180013인천광역시 중구 무의동 산 171-1 8001동 3호10215004.52023-06-01
32692인천광역시중구202314501188112103인천광역시 중구 중산동 1881-1 2동 103호2594055035.5352023-06-01
58055인천광역시중구2023147012850203-109인천광역시 중구 운서동 2850-2 3-109호93861630146.432023-06-01
24470인천광역시중구202314701280313442[ 신도시남로142번길 6 ] 0003동 0442호8686968084.91662023-06-01

Duplicate rows

Most frequently occurring

시도시군구과세연도법정동코드법정리특수지본번부번호수물건지시가표준액연면적기준일자# duplicates
4인천광역시중구202314701285119101인천광역시 중구 운서동 2851-19 1동 101호25634205.5972023-06-013
0인천광역시미추홀구20231020162980[ 아암대로 91 ] 0000동 0000호407779530434.272023-06-012
1인천광역시중구20231280141121인천광역시 중구 신흥동3가 41-12 9001동 1호247680014.42023-06-012
2인천광역시중구20231280143321[ 축항대로296번길 56-24 ] 0001동 0001호175921200327.62023-06-012
3인천광역시중구202313801982121[ 월미로233번길 11 ] 0001동 0001호310934520369.722023-06-012
5인천광역시중구202314801168240[ 논골길 49 ] 0001동 0000호38656805.312023-06-012
6인천광역시중구20231480131541[ 영종순환로 646 ] 0006동 0001호122054660306.672023-06-012
7인천광역시중구202314801933151인천광역시 중구 운북동 933-15 1동 1호70996640306.022023-06-012
8인천광역시중구202315101128171인천광역시 중구 덕교동 128-17 2동 1호149222040205.542023-06-012