Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows12
Duplicate rows (%)0.1%
Total size in memory1.2 MiB
Average record size in memory128.0 B

Variable types

Categorical5
Numeric5
Unsupported1
Text2
DateTime1

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 12 (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 (96.7%)Imbalance
시가표준액 is highly skewed (γ1 = 28.88583401)Skewed
연면적 is highly skewed (γ1 = 24.25821502)Skewed
동 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부번 has 1870 (18.7%) zerosZeros

Reproduction

Analysis started2024-03-18 05:30:00.675206
Analysis finished2024-03-18 05:30:04.380359
Duration3.71 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

2024-03-18T14:30:04.430904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:04.509778image/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
6595 
동구
2493 
미추홀구
912 

Length

Max length4
Median length2
Mean length2.1824
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 6595
66.0%
동구 2493
 
24.9%
미추홀구 912
 
9.1%

Length

2024-03-18T14:30:04.597736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:04.700944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 6595
66.0%
동구 2493
 
24.9%
미추홀구 912
 
9.1%

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

2024-03-18T14:30:04.806981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:04.883906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 10000
100.0%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.7657
Minimum101
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T14:30:04.973849image/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 deviation18.724408
Coefficient of variation (CV)0.14770879
Kurtosis-1.6981768
Mean126.7657
Median Absolute Deviation (MAD)19
Skewness-0.14769941
Sum1267657
Variance350.60346
MonotonicityNot monotonic
2024-03-18T14:30:05.109191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147 1509
15.1%
145 1463
14.6%
107 1279
12.8%
103 881
 
8.8%
118 771
 
7.7%
102 572
 
5.7%
128 399
 
4.0%
101 380
 
3.8%
149 273
 
2.7%
146 264
 
2.6%
Other values (40) 2209
22.1%
ValueCountFrequency (%)
101 380
 
3.8%
102 572
5.7%
103 881
8.8%
104 262
 
2.6%
105 31
 
0.3%
106 90
 
0.9%
107 1279
12.8%
108 3
 
< 0.1%
109 4
 
< 0.1%
110 6
 
0.1%
ValueCountFrequency (%)
152 68
 
0.7%
151 64
 
0.6%
150 58
 
0.6%
149 273
 
2.7%
148 198
 
2.0%
147 1509
15.1%
146 264
 
2.6%
145 1463
14.6%
144 17
 
0.2%
143 10
 
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

2024-03-18T14:30:05.232821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:05.308011image/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
9966 
2
 
34

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 9966
99.7%
2 34
 
0.3%

Length

2024-03-18T14:30:05.389683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:30:05.465215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9966
99.7%
2 34
 
0.3%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct913
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean860.4097
Minimum1
Maximum3246
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T14:30:05.551735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q154
median294
Q31873
95-th percentile3088
Maximum3246
Range3245
Interquartile range (IQR)1819

Descriptive statistics

Standard deviation1073.7226
Coefficient of variation (CV)1.2479202
Kurtosis-0.56211767
Mean860.4097
Median Absolute Deviation (MAD)281
Skewness1.0091187
Sum8604097
Variance1152880.3
MonotonicityNot monotonic
2024-03-18T14:30:05.674512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
294 403
 
4.0%
129 403
 
4.0%
1873 368
 
3.7%
1886 350
 
3.5%
27 262
 
2.6%
2850 262
 
2.6%
295 249
 
2.5%
1 245
 
2.5%
7 202
 
2.0%
2 175
 
1.8%
Other values (903) 7081
70.8%
ValueCountFrequency (%)
1 245
2.5%
2 175
1.8%
3 84
 
0.8%
4 85
 
0.9%
5 44
 
0.4%
6 83
 
0.8%
7 202
2.0%
8 57
 
0.6%
9 45
 
0.4%
10 45
 
0.4%
ValueCountFrequency (%)
3246 2
 
< 0.1%
3244 1
 
< 0.1%
3243 16
0.2%
3238 9
0.1%
3234 5
 
0.1%
3233 3
 
< 0.1%
3231 7
0.1%
3215 1
 
< 0.1%
3202 6
 
0.1%
3195 3
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct369
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.1819
Minimum0
Maximum888
Zeros1870
Zeros (%)18.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T14:30:05.791932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q320
95-th percentile173
Maximum888
Range888
Interquartile range (IQR)19

Descriptive statistics

Standard deviation91.942011
Coefficient of variation (CV)2.7708483
Kurtosis30.912537
Mean33.1819
Median Absolute Deviation (MAD)5
Skewness5.1305518
Sum331819
Variance8453.3333
MonotonicityNot monotonic
2024-03-18T14:30:05.919356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1870
18.7%
1 1134
 
11.3%
2 673
 
6.7%
4 654
 
6.5%
3 488
 
4.9%
5 419
 
4.2%
6 351
 
3.5%
7 340
 
3.4%
11 235
 
2.4%
8 222
 
2.2%
Other values (359) 3614
36.1%
ValueCountFrequency (%)
0 1870
18.7%
1 1134
11.3%
2 673
 
6.7%
3 488
 
4.9%
4 654
 
6.5%
5 419
 
4.2%
6 351
 
3.5%
7 340
 
3.4%
8 222
 
2.2%
9 129
 
1.3%
ValueCountFrequency (%)
888 1
< 0.1%
882 1
< 0.1%
879 1
< 0.1%
868 1
< 0.1%
863 1
< 0.1%
861 1
< 0.1%
859 1
< 0.1%
858 1
< 0.1%
853 1
< 0.1%
849 2
< 0.1%

동
Unsupported

REJECTED  UNSUPPORTED 

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

호수
Text

Distinct1048
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-18T14:30:06.273432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length2.384
Min length1

Characters and Unicode

Total characters23840
Distinct characters22
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

Unique389 ?
Unique (%)3.9%

Sample

1st row0121-1
2nd row404
3rd row1
4th row1
5th row303
ValueCountFrequency (%)
1 1684
 
16.8%
2 712
 
7.1%
101 403
 
4.0%
3 380
 
3.8%
0 340
 
3.4%
4 238
 
2.4%
201 212
 
2.1%
5 165
 
1.6%
102 151
 
1.5%
301 137
 
1.4%
Other values (1041) 5589
55.8%
2024-03-18T14:30:06.687395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7422
31.1%
0 4516
18.9%
2 3595
15.1%
3 2310
 
9.7%
4 1400
 
5.9%
5 1098
 
4.6%
6 976
 
4.1%
8 923
 
3.9%
7 794
 
3.3%
9 681
 
2.9%
Other values (12) 125
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23715
99.5%
Dash Punctuation 76
 
0.3%
Other Letter 24
 
0.1%
Space Separator 11
 
< 0.1%
Uppercase Letter 10
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7422
31.3%
0 4516
19.0%
2 3595
15.2%
3 2310
 
9.7%
4 1400
 
5.9%
5 1098
 
4.6%
6 976
 
4.1%
8 923
 
3.9%
7 794
 
3.3%
9 681
 
2.9%
Other Letter
ValueCountFrequency (%)
월 11
45.8%
일 11
45.8%
지 1
 
4.2%
층 1
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
B 6
60.0%
J 2
 
20.0%
T 1
 
10.0%
S 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
50.0%
n 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23802
99.8%
Hangul 24
 
0.1%
Latin 14
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7422
31.2%
0 4516
19.0%
2 3595
15.1%
3 2310
 
9.7%
4 1400
 
5.9%
5 1098
 
4.6%
6 976
 
4.1%
8 923
 
3.9%
7 794
 
3.3%
9 681
 
2.9%
Other values (2) 87
 
0.4%
Latin
ValueCountFrequency (%)
B 6
42.9%
J 2
 
14.3%
a 2
 
14.3%
n 2
 
14.3%
T 1
 
7.1%
S 1
 
7.1%
Hangul
ValueCountFrequency (%)
월 11
45.8%
일 11
45.8%
지 1
 
4.2%
층 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23816
99.9%
Hangul 24
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7422
31.2%
0 4516
19.0%
2 3595
15.1%
3 2310
 
9.7%
4 1400
 
5.9%
5 1098
 
4.6%
6 976
 
4.1%
8 923
 
3.9%
7 794
 
3.3%
9 681
 
2.9%
Other values (8) 101
 
0.4%
Hangul
ValueCountFrequency (%)
월 11
45.8%
일 11
45.8%
지 1
 
4.2%
층 1
 
4.2%

물건지
Text

Distinct9639
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-18T14:30:06.921233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length25.2993
Min length17

Characters and Unicode

Total characters252993
Distinct characters193
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

Unique9380 ?
Unique (%)93.8%

Sample

1st row인천광역시 중구 송월동1가 10-1 14동 121-1호
2nd row[ 은하수로 35 ] 0001동 0404호
3rd row인천광역시 중구 항동7가 1-58 1동 1호
4th row인천광역시 중구 을왕동 843 1동 1호
5th row[ 경인로142번길 10 ] 0000동 0303호
ValueCountFrequency (%)
12196
20.5%
인천광역시 3902
 
6.6%
0001동 2965
 
5.0%
0000동 2444
 
4.1%
중구 2072
 
3.5%
동구 1683
 
2.8%
1동 1281
 
2.2%
송림동 920
 
1.5%
0001호 897
 
1.5%
1호 787
 
1.3%
Other values (4108) 30260
50.9%
2024-03-18T14:30:07.286340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49407
19.5%
0 37156
14.7%
1 19791
 
7.8%
동 15161
 
6.0%
2 10436
 
4.1%
호 9863
 
3.9%
3 6509
 
2.6%
[ 6098
 
2.4%
] 6098
 
2.4%
로 6000
 
2.4%
Other values (183) 86474
34.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99425
39.3%
Other Letter 88292
34.9%
Space Separator 49407
19.5%
Open Punctuation 6098
 
2.4%
Close Punctuation 6098
 
2.4%
Dash Punctuation 3665
 
1.4%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 15161
17.2%
호 9863
 
11.2%
로 6000
 
6.8%
인 4467
 
5.1%
시 4120
 
4.7%
광 3993
 
4.5%
천 3928
 
4.4%
역 3909
 
4.4%
구 3905
 
4.4%
길 2984
 
3.4%
Other values (166) 29962
33.9%
Decimal Number
ValueCountFrequency (%)
0 37156
37.4%
1 19791
19.9%
2 10436
 
10.5%
3 6509
 
6.5%
9 5058
 
5.1%
4 4934
 
5.0%
5 4243
 
4.3%
7 3828
 
3.9%
6 3806
 
3.8%
8 3664
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 6
75.0%
T 1
 
12.5%
S 1
 
12.5%
Space Separator
ValueCountFrequency (%)
49407
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 6098
100.0%
Close Punctuation
ValueCountFrequency (%)
] 6098
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3665
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 164693
65.1%
Hangul 88292
34.9%
Latin 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 15161
17.2%
호 9863
 
11.2%
로 6000
 
6.8%
인 4467
 
5.1%
시 4120
 
4.7%
광 3993
 
4.5%
천 3928
 
4.4%
역 3909
 
4.4%
구 3905
 
4.4%
길 2984
 
3.4%
Other values (166) 29962
33.9%
Common
ValueCountFrequency (%)
49407
30.0%
0 37156
22.6%
1 19791
12.0%
2 10436
 
6.3%
3 6509
 
4.0%
[ 6098
 
3.7%
] 6098
 
3.7%
9 5058
 
3.1%
4 4934
 
3.0%
5 4243
 
2.6%
Other values (4) 14963
 
9.1%
Latin
ValueCountFrequency (%)
B 6
75.0%
T 1
 
12.5%
S 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 164701
65.1%
Hangul 88292
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49407
30.0%
0 37156
22.6%
1 19791
12.0%
2 10436
 
6.3%
3 6509
 
4.0%
[ 6098
 
3.7%
] 6098
 
3.7%
9 5058
 
3.1%
4 4934
 
3.0%
5 4243
 
2.6%
Other values (7) 14971
 
9.1%
Hangul
ValueCountFrequency (%)
동 15161
17.2%
호 9863
 
11.2%
로 6000
 
6.8%
인 4467
 
5.1%
시 4120
 
4.7%
광 3993
 
4.5%
천 3928
 
4.4%
역 3909
 
4.4%
구 3905
 
4.4%
길 2984
 
3.4%
Other values (166) 29962
33.9%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6537
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89415019
Minimum14100
Maximum2.9069591 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T14:30:07.415724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14100
5-th percentile1152000
Q16143062.5
median29185940
Q361050570
95-th percentile2.4018853 × 108
Maximum2.9069591 × 1010
Range2.9069576 × 1010
Interquartile range (IQR)54907508

Descriptive statistics

Standard deviation5.0878077 × 108
Coefficient of variation (CV)5.6901042
Kurtosis1264.7409
Mean89415019
Median Absolute Deviation (MAD)24754745
Skewness28.885834
Sum8.9415019 × 1011
Variance2.5885787 × 1017
MonotonicityNot monotonic
2024-03-18T14:30:07.530113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2050860 225
 
2.2%
13791820 224
 
2.2%
18568530 107
 
1.1%
2361830 95
 
0.9%
46195110 61
 
0.6%
14165340 58
 
0.6%
46161960 55
 
0.5%
39951740 50
 
0.5%
49009390 47
 
0.5%
2104830 46
 
0.5%
Other values (6527) 9032
90.3%
ValueCountFrequency (%)
14100 1
 
< 0.1%
18800 2
 
< 0.1%
28200 3
 
< 0.1%
31360 1
 
< 0.1%
31950 1
 
< 0.1%
42600 10
0.1%
43200 1
 
< 0.1%
44000 1
 
< 0.1%
47520 1
 
< 0.1%
48000 1
 
< 0.1%
ValueCountFrequency (%)
29069590550 1
< 0.1%
15829183390 1
< 0.1%
11710561190 1
< 0.1%
11075040980 1
< 0.1%
10404596090 1
< 0.1%
9816773980 1
< 0.1%
8336074560 1
< 0.1%
7788399360 1
< 0.1%
7664010900 1
< 0.1%
7440477670 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5136
Distinct (%)51.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.65418
Minimum0.15
Maximum45635.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T14:30:07.645427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.15
5-th percentile7.98
Q133
median51.1
Q3108.30055
95-th percentile517.137
Maximum45635.15
Range45635
Interquartile range (IQR)75.30055

Descriptive statistics

Standard deviation839.35638
Coefficient of variation (CV)4.7514097
Kurtosis990.58337
Mean176.65418
Median Absolute Deviation (MAD)31.295
Skewness24.258215
Sum1766541.8
Variance704519.13
MonotonicityNot monotonic
2024-03-18T14:30:07.755663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 257
 
2.6%
7.98 226
 
2.3%
33.97 224
 
2.2%
39.09 108
 
1.1%
9.19 98
 
1.0%
27.0 83
 
0.8%
39.483 61
 
0.6%
34.89 58
 
0.6%
48.3878 55
 
0.5%
40.3553 50
 
0.5%
Other values (5126) 8780
87.8%
ValueCountFrequency (%)
0.15 1
 
< 0.1%
0.2 2
 
< 0.1%
0.25 1
 
< 0.1%
0.3 18
0.2%
0.32 1
 
< 0.1%
0.44 1
 
< 0.1%
0.68 1
 
< 0.1%
0.69 1
 
< 0.1%
0.7 7
 
0.1%
0.8 1
 
< 0.1%
ValueCountFrequency (%)
45635.15 1
< 0.1%
20372.1794 1
< 0.1%
17883.16 1
< 0.1%
16800.575 1
< 0.1%
15314.78 1
< 0.1%
13684.5588 1
< 0.1%
12423.36 1
< 0.1%
12375.28 1
< 0.1%
12230.32 1
< 0.1%
12150.0 1
< 0.1%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-06-01 00:00:00
Maximum2023-06-01 00:00:00
2024-03-18T14:30:07.841284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:08.228240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-18T14:30:03.653245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:01.706522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:02.173625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:02.605531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:03.247574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:03.756332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:01.787284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:02.257374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:02.685897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:03.327971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:03.859956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:01.895475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:02.336210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:02.762243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:03.415470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:03.943118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:01.992954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:02.422787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:03.095383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:03.490812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:04.030650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:02.097145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:02.524566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:03.177358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:03.579013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:30:08.307547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구법정동코드특수지본번부번시가표준액연면적
시군구1.0000.8470.0210.6360.2140.0220.046
법정동코드0.8471.0000.1230.8580.3900.0520.053
특수지0.0210.1231.0000.0570.0000.0000.000
본번0.6360.8580.0571.0000.2310.0460.052
부번0.2140.3900.0000.2311.0000.0000.000
시가표준액0.0220.0520.0000.0460.0001.0000.946
연면적0.0460.0530.0000.0520.0000.9461.000
2024-03-18T14:30:08.412230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특수지시군구
특수지1.0000.036
시군구0.0361.000
2024-03-18T14:30:08.487946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드본번부번시가표준액연면적시군구특수지
법정동코드1.0000.567-0.0710.2270.1020.7630.094
본번0.5671.000-0.2950.3050.0160.4830.044
부번-0.071-0.2951.0000.0480.1240.1300.000
시가표준액0.2270.3050.0481.0000.7970.0150.000
연면적0.1020.0160.1240.7971.0000.0190.000
시군구0.7630.4830.1300.0150.0191.0000.036
특수지0.0940.0440.0000.0000.0000.0361.000

Missing values

2024-03-18T14:30:04.143723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:30:04.304612image/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
20364인천광역시중구202314201101140121-1인천광역시 중구 송월동1가 10-1 14동 121-1호50972920315.72023-06-01
43053인천광역시중구202314501195141404[ 은하수로 35 ] 0001동 0404호3827881037.41822023-06-01
1607인천광역시중구20231180115811인천광역시 중구 항동7가 1-58 1동 1호7633602.082023-06-01
61838인천광역시중구202314901843011인천광역시 중구 을왕동 843 1동 1호4265352098.282023-06-01
86056인천광역시미추홀구20231010157100303[ 경인로142번길 10 ] 0000동 0303호17105505.262023-06-01
28251인천광역시중구202314901157090011인천광역시 중구 을왕동 157 9001동 1호284400018.02023-06-01
52770인천광역시중구202312801429511[ 축항대로296번길 56-27 ] 0001동 0001호163403730338.12023-06-01
4393인천광역시중구2023118015832202[ 축항대로86번길 38 ] 0002동 0202호721360050.82023-06-01
92456인천광역시미추홀구2023103015223999201[ 노적산로54번길 5 ] 0999동 0201호477900027.02023-06-01
17491인천광역시중구20231380164421인천광역시 중구 북성동1가 6-44 2동 1호391500045.02023-06-01
시도시군구과세연도법정동코드법정리특수지본번부번동호수물건지시가표준액연면적기준일자
91656인천광역시미추홀구202310201630100208[ 아암대로 109 ] 0000동 0208호1456389028.172023-06-01
38352인천광역시중구202314501188591101[ 하늘별빛로65번길 19 ] 0001동 0101호9958819081.262023-06-01
79018인천광역시동구20231030112905230인천광역시 동구 송현동 129 5동 230호20508607.982023-06-01
33134인천광역시중구202314501187331120[ 자연대로 47 ] 0001동 0120호15311123096.342023-06-01
37756인천광역시중구202314501188321104[ 하늘별빛로65번길 8-21 ] 0001동 0104호10797562086.142023-06-01
6384인천광역시중구20231180187210302[ 연안부두로55번길 4-11 ] 0000동 0302호2725538049.37572023-06-01
55200인천광역시중구2023133017314[ 우현로67번길 25 ] 0001동 0004호621784036.42023-06-01
38707인천광역시중구2023145011886401016[ 하늘별빛로65번길 7-11 ] 0000동 1016호4900939044.88042023-06-01
60849인천광역시중구20231470131674100300[ 공항동로296번길 87 ] 0100동 0300호7824950001415.02023-06-01
75036인천광역시동구202310701297361102인천광역시 동구 송림동 297-36 1동 102호3067740069.02023-06-01

Duplicate rows

Most frequently occurring

시도시군구과세연도법정동코드법정리특수지본번부번호수물건지시가표준액연면적기준일자# duplicates
10인천광역시중구20231470131661101[ 공항동로296번길 171 ] 0061동 101호16290009.02023-06-013
0인천광역시동구20231030116701인천광역시 동구 송현동 1-670 1동 1호14787508.752023-06-012
1인천광역시동구202310301298104[ 방축로 10 ] 0000동 0104호847704034.322023-06-012
2인천광역시동구20231070110922인천광역시 동구 송림동 109-2 1동 2호25811340176.792023-06-012
3인천광역시동구2023107012961102인천광역시 동구 송림동 296-1 2동 102호1432620037.82023-06-012
4인천광역시중구20231180193161인천광역시 중구 항동7가 93-16 1동 1호5672073099.722023-06-012
5인천광역시중구202312701545105인천광역시 중구 신흥동2가 54-5 105호1162900.72023-06-012
6인천광역시중구202312701545231인천광역시 중구 신흥동2가 54-5 231호426000.32023-06-012
7인천광역시중구20231280141121인천광역시 중구 신흥동3가 41-12 9001동 1호247680014.42023-06-012
8인천광역시중구202313801983670[ 월미로260번길 12 ] 0000동 0000호553499280623.312023-06-012