Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows10
Duplicate rows (%)0.1%
Total size in memory742.2 KiB
Average record size in memory76.0 B

Variable types

Categorical5
Text1
Numeric2

Dataset

Description2017~2021년도 충청남도 보령시 일반건축물에 대한 지방세 부과기준인 시가표준액 항목을 제공합니다. *물건별 재산가액 비교에 참조
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=348&beforeMenuCd=DOM_000000201001001000&publicdatapk=15079936

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
Dataset has 10 (0.1%) duplicate rowsDuplicates
과세년도 is highly overall correlated with 기준일자High correlation
기준일자 is highly overall correlated with 과세년도High correlation
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation

Reproduction

Analysis started2024-01-09 20:55:30.417720
Analysis finished2024-01-09 20:55:31.518357
Duration1.1 second
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
충청남도
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 10000
100.0%

Length

2024-01-10T05:55:31.572240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:55:31.648321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 10000
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보령시 10000
100.0%

Length

2024-01-10T05:55:31.727961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:55:31.805980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보령시 10000
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
44180
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44180
2nd row44180
3rd row44180
4th row44180
5th row44180

Common Values

ValueCountFrequency (%)
44180 10000
100.0%

Length

2024-01-10T05:55:31.882326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:55:31.955065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44180 10000
100.0%

과세년도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2019
3431 
2018
3293 
2017
3276 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2017
3rd row2017
4th row2017
5th row2018

Common Values

ValueCountFrequency (%)
2019 3431
34.3%
2018 3293
32.9%
2017 3276
32.8%

Length

2024-01-10T05:55:32.031493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:55:32.108684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 3431
34.3%
2018 3293
32.9%
2017 3276
32.8%

물건지
Text

Distinct8411
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T05:55:32.378142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length31
Mean length25.2917
Min length19

Characters and Unicode

Total characters252917
Distinct characters273
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7106 ?
Unique (%)71.1%

Sample

1st row[ 오천해안로 506 ] 0000동 0101호
2nd row[ 해수욕장9길 2-15 ] 0000동 0201호
3rd row충청남도 보령시 대천동 407-9 101호
4th row충청남도 보령시 동대동 339 104호
5th row충청남도 보령시 청소면 죽림리 410 101호
ValueCountFrequency (%)
8106
 
13.6%
충청남도 5947
 
10.0%
보령시 5947
 
10.0%
0000동 3799
 
6.4%
101호 2449
 
4.1%
0101호 1586
 
2.7%
102호 1001
 
1.7%
1동 911
 
1.5%
천북면 863
 
1.4%
대천동 587
 
1.0%
Other values (4421) 28495
47.7%
2024-01-10T05:55:32.806389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49691
19.6%
0 31685
 
12.5%
1 22307
 
8.8%
호 10107
 
4.0%
2 8130
 
3.2%
동 7949
 
3.1%
청 6672
 
2.6%
남 6662
 
2.6%
도 6286
 
2.5%
보 6275
 
2.5%
Other values (263) 97153
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102885
40.7%
Decimal Number 87073
34.4%
Space Separator 49691
19.6%
Dash Punctuation 5162
 
2.0%
Open Punctuation 4053
 
1.6%
Close Punctuation 4053
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 10107
 
9.8%
동 7949
 
7.7%
청 6672
 
6.5%
남 6662
 
6.5%
도 6286
 
6.1%
보 6275
 
6.1%
령 6178
 
6.0%
시 6088
 
5.9%
충 6041
 
5.9%
리 4157
 
4.0%
Other values (249) 36470
35.4%
Decimal Number
ValueCountFrequency (%)
0 31685
36.4%
1 22307
25.6%
2 8130
 
9.3%
3 5118
 
5.9%
4 4354
 
5.0%
6 3371
 
3.9%
7 3292
 
3.8%
8 3258
 
3.7%
5 3183
 
3.7%
9 2375
 
2.7%
Space Separator
ValueCountFrequency (%)
49691
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5162
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 4053
100.0%
Close Punctuation
ValueCountFrequency (%)
] 4053
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 150032
59.3%
Hangul 102885
40.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 10107
 
9.8%
동 7949
 
7.7%
청 6672
 
6.5%
남 6662
 
6.5%
도 6286
 
6.1%
보 6275
 
6.1%
령 6178
 
6.0%
시 6088
 
5.9%
충 6041
 
5.9%
리 4157
 
4.0%
Other values (249) 36470
35.4%
Common
ValueCountFrequency (%)
49691
33.1%
0 31685
21.1%
1 22307
14.9%
2 8130
 
5.4%
- 5162
 
3.4%
3 5118
 
3.4%
4 4354
 
2.9%
[ 4053
 
2.7%
] 4053
 
2.7%
6 3371
 
2.2%
Other values (4) 12108
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 150032
59.3%
Hangul 102885
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49691
33.1%
0 31685
21.1%
1 22307
14.9%
2 8130
 
5.4%
- 5162
 
3.4%
3 5118
 
3.4%
4 4354
 
2.9%
[ 4053
 
2.7%
] 4053
 
2.7%
6 3371
 
2.2%
Other values (4) 12108
 
8.1%
Hangul
ValueCountFrequency (%)
호 10107
 
9.8%
동 7949
 
7.7%
청 6672
 
6.5%
남 6662
 
6.5%
도 6286
 
6.1%
보 6275
 
6.1%
령 6178
 
6.0%
시 6088
 
5.9%
충 6041
 
5.9%
리 4157
 
4.0%
Other values (249) 36470
35.4%

시가표준액
Real number (ℝ)

HIGH CORRELATION 

Distinct8924
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68242707
Minimum12080
Maximum8.7453 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:55:32.934988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12080
5-th percentile529186
Q13652500
median19180915
Q366135068
95-th percentile2.4606662 × 108
Maximum8.7453 × 109
Range8.7452879 × 109
Interquartile range (IQR)62482568

Descriptive statistics

Standard deviation2.4310048 × 108
Coefficient of variation (CV)3.5622924
Kurtosis527.48964
Mean68242707
Median Absolute Deviation (MAD)17792815
Skewness18.981502
Sum6.8242707 × 1011
Variance5.9097843 × 1016
MonotonicityNot monotonic
2024-01-10T05:55:33.054024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98040570 14
 
0.1%
90000 13
 
0.1%
828000 11
 
0.1%
22106700 10
 
0.1%
74057420 9
 
0.1%
29656980 8
 
0.1%
480000 8
 
0.1%
29548940 7
 
0.1%
55770000 7
 
0.1%
1641600 7
 
0.1%
Other values (8914) 9906
99.1%
ValueCountFrequency (%)
12080 1
< 0.1%
18040 1
< 0.1%
20000 1
< 0.1%
26600 1
< 0.1%
45000 2
< 0.1%
47040 1
< 0.1%
49980 1
< 0.1%
50140 1
< 0.1%
51480 1
< 0.1%
52800 1
< 0.1%
ValueCountFrequency (%)
8745300000 1
< 0.1%
8560508880 1
< 0.1%
8114624010 1
< 0.1%
5930761030 1
< 0.1%
4191515100 1
< 0.1%
4170816260 1
< 0.1%
3934323000 1
< 0.1%
3874267550 1
< 0.1%
3632970600 1
< 0.1%
3625024220 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct5879
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean231.34766
Minimum0.6
Maximum24435.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:55:33.190201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile15
Q149.19
median108.73
Q3206.6825
95-th percentile744.53
Maximum24435.62
Range24435.02
Interquartile range (IQR)157.4925

Descriptive statistics

Standard deviation679.77442
Coefficient of variation (CV)2.9383241
Kurtosis508.48373
Mean231.34766
Median Absolute Deviation (MAD)71.27
Skewness18.684804
Sum2313476.6
Variance462093.27
MonotonicityNot monotonic
2024-01-10T05:55:33.305198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 139
 
1.4%
198.0 39
 
0.4%
36.0 38
 
0.4%
27.0 33
 
0.3%
50.0 29
 
0.3%
136.7372 27
 
0.3%
72.0 26
 
0.3%
66.0 25
 
0.2%
330.0 24
 
0.2%
25.41 23
 
0.2%
Other values (5869) 9597
96.0%
ValueCountFrequency (%)
0.6 1
 
< 0.1%
0.84 1
 
< 0.1%
1.0 3
< 0.1%
1.31 1
 
< 0.1%
1.32 2
< 0.1%
1.44 1
 
< 0.1%
1.56 1
 
< 0.1%
1.64 1
 
< 0.1%
1.76 1
 
< 0.1%
1.8 1
 
< 0.1%
ValueCountFrequency (%)
24435.62 2
< 0.1%
19459.53 1
< 0.1%
17775.0 1
< 0.1%
14356.72 1
< 0.1%
13896.93 1
< 0.1%
12027.87 1
< 0.1%
10349.42 2
< 0.1%
9579.2 1
< 0.1%
9258.93 1
< 0.1%
8991.76 1
< 0.1%

기준일자
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2019-12-31
3431 
2018-12-31
3293 
2017-12-31
3276 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-12-31
2nd row2017-12-31
3rd row2017-12-31
4th row2017-12-31
5th row2018-12-31

Common Values

ValueCountFrequency (%)
2019-12-31 3431
34.3%
2018-12-31 3293
32.9%
2017-12-31 3276
32.8%

Length

2024-01-10T05:55:33.410998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:55:33.512273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-12-31 3431
34.3%
2018-12-31 3293
32.9%
2017-12-31 3276
32.8%

Interactions

2024-01-10T05:55:31.156618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:55:30.969240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:55:31.237269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:55:31.070719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:55:33.577069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도시가표준액연면적기준일자
과세년도1.0000.0100.0131.000
시가표준액0.0101.0000.8200.010
연면적0.0130.8201.0000.013
기준일자1.0000.0100.0131.000
2024-01-10T05:55:33.671090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도기준일자
과세년도1.0001.000
기준일자1.0001.000
2024-01-10T05:55:33.758994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시가표준액연면적과세년도기준일자
시가표준액1.0000.5940.0070.007
연면적0.5941.0000.0080.008
과세년도0.0070.0081.0001.000
기준일자0.0070.0081.0001.000

Missing values

2024-01-10T05:55:31.349182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:55:31.463748image/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

시도명시군구명자치단체코드과세년도물건지시가표준액연면적기준일자
48161충청남도보령시441802018[ 오천해안로 506 ] 0000동 0101호5032843073.442018-12-31
75377충청남도보령시441802017[ 해수욕장9길 2-15 ] 0000동 0201호135753870172.49542017-12-31
70160충청남도보령시441802017충청남도 보령시 대천동 407-9 101호2023980047.42017-12-31
54959충청남도보령시441802017충청남도 보령시 동대동 339 104호1456169029.952017-12-31
40183충청남도보령시441802018충청남도 보령시 청소면 죽림리 410 101호68660068.662018-12-31
15075충청남도보령시441802019[ 열린바다1길 51 ] 0000동 0301호286292340474.782019-12-31
66741충청남도보령시441802017[ 터미널길 23-11 ] 0000동 0401호248495010303.04272017-12-31
16380충청남도보령시441802019[ 열린바다로 271 ] 0000동 0116호2851887042.612019-12-31
13071충청남도보령시441802019[ 터미널길 11 ] 0000동 0104호679875026.252019-12-31
60254충청남도보령시441802017충청남도 보령시 미산면 도화담리 307-2 1동 101호550800064.82017-12-31
시도명시군구명자치단체코드과세년도물건지시가표준액연면적기준일자
18294충청남도보령시441802019충청남도 보령시 대천동 378-6 101호212118190348.022019-12-31
69373충청남도보령시441802017충청남도 보령시 대천동 618-421 7동 3호15169609.982017-12-31
13101충청남도보령시441802019[ 성주산로 72 ] 0000동 8101호48952080117.92019-12-31
65164충청남도보령시441802017[ 홍보로 341-7 ] 0000동 0102호6703200176.42017-12-31
47679충청남도보령시441802018충청남도 보령시 천북면 학성리 271-31 101호35644000938.02018-12-31
3220충청남도보령시441802019[ 하학로 767 ] 0000동 0101호76790370125.282019-12-31
1626충청남도보령시441802019충청남도 보령시 오천면 녹도리 3-5 102호14220004.52019-12-31
71821충청남도보령시441802017[ 신설1길 87 ] 0000동 0501호170590050432.752017-12-31
50162충청남도보령시441802018충청남도 보령시 천북면 신죽리 537-5 102호739800018.02018-12-31
29698충청남도보령시441802018충청남도 보령시 오천면 오포리 731 8동 17호3544304009579.22018-12-31

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도물건지시가표준액연면적기준일자# duplicates
0충청남도보령시441802017충청남도 보령시 오천면 교성리 1326-20 101호45520020389.062017-12-312
1충청남도보령시441802017충청남도 보령시 천북면 사호리 326-2 1동 101호12117600448.82017-12-312
2충청남도보령시441802017충청남도 보령시 천북면 사호리 46-3 1동 101호672000224.02017-12-312
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