Overview

Dataset statistics

Number of variables12
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory106.7 B

Variable types

Categorical3
Text3
Numeric5
Boolean1

Dataset

Description전북특별자치도 군산시 읍면동 행정복지센터 현황입니다. 데이터 내용으로는 읍면동 명칭, 소재지 도로명 주소, 소재지 지번주소, 대지면적, 건물연면적, 건폐율, 유휴면적, 사용여부, 위도, 경도 등이 나와있습니다.
Author전북특별자치도 군산시
URLhttps://www.data.go.kr/data/15030367/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
유휴면적 has constant value ""Constant
사용여부 has constant value ""Constant
대지면적 is highly overall correlated with 건폐율High correlation
건폐율 is highly overall correlated with 대지면적High correlation
명칭 has unique valuesUnique
소재지 도로명주소 has unique valuesUnique
소재지 지번주소 has unique valuesUnique
대지면적 has unique valuesUnique
건물연면적 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-03-14 15:56:14.379618
Analysis finished2024-03-14 15:56:22.746499
Duration8.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size344.0 B
전라북도
27 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 27
100.0%

Length

2024-03-15T00:56:22.972436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:56:23.258191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 27
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size344.0 B
군산시
27 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군산시 27
100.0%

Length

2024-03-15T00:56:23.423758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:56:23.658883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군산시 27
100.0%

명칭
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size344.0 B
2024-03-15T00:56:24.341754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.1111111
Min length9

Characters and Unicode

Total characters246
Distinct characters48
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row옥구읍행정복지센터
2nd row옥산면행정복지센터
3rd row회현면행정복지센터
4th row임피면행정복지센터
5th row서수면행정복지센터
ValueCountFrequency (%)
옥구읍행정복지센터 1
 
3.7%
신풍동행정복지센터 1
 
3.7%
소룡동행정복지센터 1
 
3.7%
나운3동행정복지센터 1
 
3.7%
나운2동행정복지센터 1
 
3.7%
나운1동행정복지센터 1
 
3.7%
수송동행정복지센터 1
 
3.7%
개정동행정복지센터 1
 
3.7%
구암동행정복지센터 1
 
3.7%
경암동행정복지센터 1
 
3.7%
Other values (17) 17
63.0%
2024-03-15T00:56:25.381470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 29
11.8%
행 27
11.0%
복 27
11.0%
지 27
11.0%
센 27
11.0%
터 27
11.0%
동 16
 
6.5%
면 10
 
4.1%
옥 4
 
1.6%
나 4
 
1.6%
Other values (38) 48
19.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
98.8%
Decimal Number 3
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 29
11.9%
행 27
11.1%
복 27
11.1%
지 27
11.1%
센 27
11.1%
터 27
11.1%
동 16
 
6.6%
면 10
 
4.1%
옥 4
 
1.6%
나 4
 
1.6%
Other values (35) 45
18.5%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
2 1
33.3%
3 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
98.8%
Common 3
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 29
11.9%
행 27
11.1%
복 27
11.1%
지 27
11.1%
센 27
11.1%
터 27
11.1%
동 16
 
6.6%
면 10
 
4.1%
옥 4
 
1.6%
나 4
 
1.6%
Other values (35) 45
18.5%
Common
ValueCountFrequency (%)
1 1
33.3%
2 1
33.3%
3 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
98.8%
ASCII 3
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 29
11.9%
행 27
11.1%
복 27
11.1%
지 27
11.1%
센 27
11.1%
터 27
11.1%
동 16
 
6.6%
면 10
 
4.1%
옥 4
 
1.6%
나 4
 
1.6%
Other values (35) 45
18.5%
ASCII
ValueCountFrequency (%)
1 1
33.3%
2 1
33.3%
3 1
33.3%

소재지 도로명주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size344.0 B
2024-03-15T00:56:26.398721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length20.222222
Min length18

Characters and Unicode

Total characters546
Distinct characters83
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row전북특별자치도 군산시 옥구읍 옥구로6
2nd row전북특별자치도 군산시 옥산면 산성로200
3rd row전북특별자치도 군산시 회현면 회현로 181
4th row전북특별자치도 군산시 임피면 남상2길1
5th row전북특별자치도 군산시 서수면 항쟁로 193
ValueCountFrequency (%)
전북특별자치도 27
23.9%
군산시 27
23.9%
공항로 1
 
0.9%
63 1
 
0.9%
51 1
 
0.9%
미원로 1
 
0.9%
17 1
 
0.9%
대학로 1
 
0.9%
215 1
 
0.9%
큰샘길 1
 
0.9%
Other values (51) 51
45.1%
2024-03-15T00:56:27.765985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
15.8%
산 30
 
5.5%
전 27
 
4.9%
도 27
 
4.9%
군 27
 
4.9%
시 27
 
4.9%
치 27
 
4.9%
자 27
 
4.9%
별 27
 
4.9%
특 27
 
4.9%
Other values (73) 214
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 387
70.9%
Space Separator 86
 
15.8%
Decimal Number 71
 
13.0%
Dash Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 30
 
7.8%
전 27
 
7.0%
도 27
 
7.0%
군 27
 
7.0%
시 27
 
7.0%
치 27
 
7.0%
자 27
 
7.0%
별 27
 
7.0%
특 27
 
7.0%
북 27
 
7.0%
Other values (60) 114
29.5%
Decimal Number
ValueCountFrequency (%)
1 16
22.5%
2 13
18.3%
3 12
16.9%
5 7
9.9%
7 7
9.9%
0 5
 
7.0%
6 4
 
5.6%
4 3
 
4.2%
9 3
 
4.2%
8 1
 
1.4%
Space Separator
ValueCountFrequency (%)
86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 387
70.9%
Common 159
29.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 30
 
7.8%
전 27
 
7.0%
도 27
 
7.0%
군 27
 
7.0%
시 27
 
7.0%
치 27
 
7.0%
자 27
 
7.0%
별 27
 
7.0%
특 27
 
7.0%
북 27
 
7.0%
Other values (60) 114
29.5%
Common
ValueCountFrequency (%)
86
54.1%
1 16
 
10.1%
2 13
 
8.2%
3 12
 
7.5%
5 7
 
4.4%
7 7
 
4.4%
0 5
 
3.1%
6 4
 
2.5%
4 3
 
1.9%
9 3
 
1.9%
Other values (3) 3
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 387
70.9%
ASCII 159
29.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
54.1%
1 16
 
10.1%
2 13
 
8.2%
3 12
 
7.5%
5 7
 
4.4%
7 7
 
4.4%
0 5
 
3.1%
6 4
 
2.5%
4 3
 
1.9%
9 3
 
1.9%
Other values (3) 3
 
1.9%
Hangul
ValueCountFrequency (%)
산 30
 
7.8%
전 27
 
7.0%
도 27
 
7.0%
군 27
 
7.0%
시 27
 
7.0%
치 27
 
7.0%
자 27
 
7.0%
별 27
 
7.0%
특 27
 
7.0%
북 27
 
7.0%
Other values (60) 114
29.5%

소재지 지번주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size344.0 B
2024-03-15T00:56:28.774667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length24.111111
Min length20

Characters and Unicode

Total characters651
Distinct characters67
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

Unique27 ?
Unique (%)100.0%

Sample

1st row전북특별자치도 군산시 옥구읍 선제리 98-11번지
2nd row전북특별자치도 군산시 옥산면 옥산리 23-39번지
3rd row전북특별자치도 군산시 회현면 대정리 23번지
4th row전북특별자치도 군산시 임피면 읍내리 216-1번지
5th row전북특별자치도 군산시 서수면 서수리 769-1번지
ValueCountFrequency (%)
전북특별자치도 27
22.9%
군산시 27
22.9%
나운동 3
 
2.5%
금동 2
 
1.7%
산북동 1
 
0.8%
조촌동 1
 
0.8%
2-3번지 1
 
0.8%
월명동 1
 
0.8%
2-1번지 1
 
0.8%
오룡동 1
 
0.8%
Other values (53) 53
44.9%
2024-03-15T00:56:30.144045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
 
14.0%
산 32
 
4.9%
지 28
 
4.3%
북 28
 
4.3%
전 27
 
4.1%
번 27
 
4.1%
군 27
 
4.1%
시 27
 
4.1%
도 27
 
4.1%
치 27
 
4.1%
Other values (57) 310
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 433
66.5%
Decimal Number 104
 
16.0%
Space Separator 91
 
14.0%
Dash Punctuation 23
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 32
 
7.4%
지 28
 
6.5%
북 28
 
6.5%
전 27
 
6.2%
번 27
 
6.2%
군 27
 
6.2%
시 27
 
6.2%
도 27
 
6.2%
치 27
 
6.2%
자 27
 
6.2%
Other values (45) 156
36.0%
Decimal Number
ValueCountFrequency (%)
1 22
21.2%
2 15
14.4%
3 13
12.5%
7 11
10.6%
8 10
9.6%
9 8
 
7.7%
5 8
 
7.7%
6 7
 
6.7%
4 6
 
5.8%
0 4
 
3.8%
Space Separator
ValueCountFrequency (%)
91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 433
66.5%
Common 218
33.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 32
 
7.4%
지 28
 
6.5%
북 28
 
6.5%
전 27
 
6.2%
번 27
 
6.2%
군 27
 
6.2%
시 27
 
6.2%
도 27
 
6.2%
치 27
 
6.2%
자 27
 
6.2%
Other values (45) 156
36.0%
Common
ValueCountFrequency (%)
91
41.7%
- 23
 
10.6%
1 22
 
10.1%
2 15
 
6.9%
3 13
 
6.0%
7 11
 
5.0%
8 10
 
4.6%
9 8
 
3.7%
5 8
 
3.7%
6 7
 
3.2%
Other values (2) 10
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 433
66.5%
ASCII 218
33.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
41.7%
- 23
 
10.6%
1 22
 
10.1%
2 15
 
6.9%
3 13
 
6.0%
7 11
 
5.0%
8 10
 
4.6%
9 8
 
3.7%
5 8
 
3.7%
6 7
 
3.2%
Other values (2) 10
 
4.6%
Hangul
ValueCountFrequency (%)
산 32
 
7.4%
지 28
 
6.5%
북 28
 
6.5%
전 27
 
6.2%
번 27
 
6.2%
군 27
 
6.2%
시 27
 
6.2%
도 27
 
6.2%
치 27
 
6.2%
자 27
 
6.2%
Other values (45) 156
36.0%

대지면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2257.4444
Minimum319
Maximum6599
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T00:56:30.517893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum319
5-th percentile431.2
Q11398
median1976
Q33391.5
95-th percentile3995.1
Maximum6599
Range6280
Interquartile range (IQR)1993.5

Descriptive statistics

Standard deviation1441.8114
Coefficient of variation (CV)0.63869189
Kurtosis1.5600133
Mean2257.4444
Median Absolute Deviation (MAD)972
Skewness1.0641875
Sum60951
Variance2078820.3
MonotonicityNot monotonic
2024-03-15T00:56:30.892107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
3486 1
 
3.7%
1004 1
 
3.7%
3641 1
 
3.7%
3844 1
 
3.7%
874 1
 
3.7%
1496 1
 
3.7%
623 1
 
3.7%
3297 1
 
3.7%
1658 1
 
3.7%
1976 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
319 1
3.7%
349 1
3.7%
623 1
3.7%
786 1
3.7%
874 1
3.7%
1004 1
3.7%
1342 1
3.7%
1454 1
3.7%
1496 1
3.7%
1570 1
3.7%
ValueCountFrequency (%)
6599 1
3.7%
3999 1
3.7%
3986 1
3.7%
3844 1
3.7%
3837 1
3.7%
3641 1
3.7%
3486 1
3.7%
3297 1
3.7%
2645 1
3.7%
2480 1
3.7%

건물연면적
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1136.2963
Minimum325
Maximum1987
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T00:56:31.262256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325
5-th percentile536.3
Q1716.5
median1206
Q31461.5
95-th percentile1849.3
Maximum1987
Range1662
Interquartile range (IQR)745

Descriptive statistics

Standard deviation464.46419
Coefficient of variation (CV)0.40875271
Kurtosis-1.1113645
Mean1136.2963
Median Absolute Deviation (MAD)438
Skewness0.053567504
Sum30680
Variance215726.99
MonotonicityNot monotonic
2024-03-15T00:56:31.663283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1495 1
 
3.7%
699 1
 
3.7%
1465 1
 
3.7%
1794 1
 
3.7%
1393 1
 
3.7%
1987 1
 
3.7%
999 1
 
3.7%
1713 1
 
3.7%
551 1
 
3.7%
952 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
325 1
3.7%
530 1
3.7%
551 1
3.7%
582 1
3.7%
663 1
3.7%
669 1
3.7%
699 1
3.7%
734 1
3.7%
744 1
3.7%
768 1
3.7%
ValueCountFrequency (%)
1987 1
3.7%
1873 1
3.7%
1794 1
3.7%
1713 1
3.7%
1495 1
3.7%
1494 1
3.7%
1465 1
3.7%
1458 1
3.7%
1455 1
3.7%
1429 1
3.7%

건폐율
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.33037
Minimum9.9
Maximum60.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T00:56:32.011779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.9
5-th percentile12.32
Q115.7
median24.5
Q339.8
95-th percentile56.58
Maximum60.3
Range50.4
Interquartile range (IQR)24.1

Descriptive statistics

Standard deviation15.26533
Coefficient of variation (CV)0.53883269
Kurtosis-0.67893606
Mean28.33037
Median Absolute Deviation (MAD)10.3
Skewness0.74221702
Sum764.92
Variance233.03029
MonotonicityNot monotonic
2024-03-15T00:56:32.369378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
13.3 2
 
7.4%
18.7 1
 
3.7%
26.12 1
 
3.7%
16.0 1
 
3.7%
14.0 1
 
3.7%
49.3 1
 
3.7%
45.5 1
 
3.7%
52.8 1
 
3.7%
24.6 1
 
3.7%
16.8 1
 
3.7%
Other values (16) 16
59.3%
ValueCountFrequency (%)
9.9 1
3.7%
11.9 1
3.7%
13.3 2
7.4%
14.0 1
3.7%
14.9 1
3.7%
15.4 1
3.7%
16.0 1
3.7%
16.8 1
3.7%
17.9 1
3.7%
18.7 1
3.7%
ValueCountFrequency (%)
60.3 1
3.7%
58.2 1
3.7%
52.8 1
3.7%
49.3 1
3.7%
45.5 1
3.7%
43.0 1
3.7%
40.7 1
3.7%
38.9 1
3.7%
34.8 1
3.7%
34.7 1
3.7%

유휴면적
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size344.0 B
0
27 

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 27
100.0%

Length

2024-03-15T00:56:32.783601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:56:33.080814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
100.0%

사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size155.0 B
True
27 
ValueCountFrequency (%)
True 27
100.0%
2024-03-15T00:56:33.320853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위도
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.969068
Minimum35.91331
Maximum36.030267
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T00:56:33.621548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.91331
5-th percentile35.923127
Q135.958577
median35.973799
Q335.984283
95-th percentile35.991993
Maximum36.030267
Range0.11695745
Interquartile range (IQR)0.025705565

Descriptive statistics

Standard deviation0.024683487
Coefficient of variation (CV)0.00068624205
Kurtosis1.134194
Mean35.969068
Median Absolute Deviation (MAD)0.01206336
Skewness-0.34199479
Sum971.16484
Variance0.00060927453
MonotonicityNot monotonic
2024-03-15T00:56:34.016105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
35.92288663 1
 
3.7%
35.93946632 1
 
3.7%
35.957783 1
 
3.7%
35.97379898 1
 
3.7%
35.95880745 1
 
3.7%
35.96486847 1
 
3.7%
35.96680843 1
 
3.7%
35.9648194 1
 
3.7%
35.96443139 1
 
3.7%
35.98586234 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
35.91330978 1
3.7%
35.92288663 1
3.7%
35.923688 1
3.7%
35.93946632 1
3.7%
35.94647617 1
3.7%
35.957783 1
3.7%
35.95834723 1
3.7%
35.95880745 1
3.7%
35.96443139 1
3.7%
35.9648194 1
3.7%
ValueCountFrequency (%)
36.03026723 1
3.7%
35.99309089 1
3.7%
35.9894302 1
3.7%
35.98938785 1
3.7%
35.98642833 1
3.7%
35.98586234 1
3.7%
35.9854458 1
3.7%
35.98312001 1
3.7%
35.98257891 1
3.7%
35.981597 1
3.7%

경도
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.73552
Minimum126.64342
Maximum126.87563
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T00:56:34.502924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.64342
5-th percentile126.66545
Q1126.70021
median126.717
Q3126.75567
95-th percentile126.84531
Maximum126.87563
Range0.232218
Interquartile range (IQR)0.0554654

Descriptive statistics

Standard deviation0.057350358
Coefficient of variation (CV)0.00045252001
Kurtosis0.3808378
Mean126.73552
Median Absolute Deviation (MAD)0.0277728
Skewness0.91005751
Sum3421.859
Variance0.0032890636
MonotonicityNot monotonic
2024-03-15T00:56:34.857100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
126.6853924 1
 
3.7%
126.7483779 1
 
3.7%
126.657584 1
 
3.7%
126.6838068 1
 
3.7%
126.6892321 1
 
3.7%
126.6996085 1
 
3.7%
126.6948317 1
 
3.7%
126.7176797 1
 
3.7%
126.7544699 1
 
3.7%
126.743998 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
126.643415 1
3.7%
126.657584 1
3.7%
126.6838068 1
3.7%
126.6853924 1
3.7%
126.6892321 1
3.7%
126.6948317 1
3.7%
126.6996085 1
3.7%
126.7008079 1
3.7%
126.7076236 1
3.7%
126.7076374 1
3.7%
ValueCountFrequency (%)
126.875633 1
3.7%
126.8508349 1
3.7%
126.8324239 1
3.7%
126.8112008 1
3.7%
126.796856 1
3.7%
126.7859604 1
3.7%
126.7568773 1
3.7%
126.7544699 1
3.7%
126.7483779 1
3.7%
126.743998 1
3.7%

Interactions

2024-03-15T00:56:19.980593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:14.872677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:16.105586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:17.356981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:18.573569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:20.272871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:15.121985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:16.352288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:17.596135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:18.815751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:20.862079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:15.386520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:16.612304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:17.853594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:19.175726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:21.138630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:15.626674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:16.862546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:18.090291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:19.454949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:21.434410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:15.869563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:17.113267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:18.332277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:19.708553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:56:35.020581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
명칭소재지 도로명주소소재지 지번주소대지면적건물연면적건폐율위도경도
명칭1.0001.0001.0001.0001.0001.0001.0001.000
소재지 도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지 지번주소1.0001.0001.0001.0001.0001.0001.0001.000
대지면적1.0001.0001.0001.0000.4780.4420.0000.663
건물연면적1.0001.0001.0000.4781.0000.0350.0000.000
건폐율1.0001.0001.0000.4420.0351.0000.0000.000
위도1.0001.0001.0000.0000.0000.0001.0000.381
경도1.0001.0001.0000.6630.0000.0000.3811.000
2024-03-15T00:56:35.320876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대지면적건물연면적건폐율위도경도
대지면적1.0000.435-0.7690.0450.327
건물연면적0.4351.0000.0830.058-0.282
건폐율-0.7690.0831.000-0.029-0.412
위도0.0450.058-0.0291.0000.261
경도0.327-0.282-0.4120.2611.000

Missing values

2024-03-15T00:56:21.839074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:56:22.556343image/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

시도시군구명칭소재지 도로명주소소재지 지번주소대지면적건물연면적건폐율유휴면적사용여부위도경도
0전라북도군산시옥구읍행정복지센터전북특별자치도 군산시 옥구읍 옥구로6전북특별자치도 군산시 옥구읍 선제리 98-11번지3486149518.70Y35.922887126.685392
1전라북도군산시옥산면행정복지센터전북특별자치도 군산시 옥산면 산성로200전북특별자치도 군산시 옥산면 옥산리 23-39번지100469934.80Y35.939466126.748378
2전라북도군산시회현면행정복지센터전북특별자치도 군산시 회현면 회현로 181전북특별자치도 군산시 회현면 대정리 23번지264558211.90Y35.91331126.756877
3전라북도군산시임피면행정복지센터전북특별자치도 군산시 임피면 남상2길1전북특별자치도 군산시 임피면 읍내리 216-1번지3999122117.90Y35.982579126.850835
4전라북도군산시서수면행정복지센터전북특별자치도 군산시 서수면 항쟁로 193전북특별자치도 군산시 서수면 서수리 769-1번지6599187319.80Y35.98312126.875633
5전라북도군산시대야면행정복지센터전북특별자치도 군산시 대야면 석화로7전북특별자치도 군산시 대야면 지경리 731-11번지3837142914.90Y35.946476126.811201
6전라북도군산시개정면행정복지센터전북특별자치도 군산시 개정면 바르메길 42전북특별자치도 군산시 개정면 발산리 86-9번지157073427.70Y35.958347126.796856
7전라북도군산시성산면행정복지센터전북특별자치도 군산시 성산면 송호로222전북특별자치도 군산시 성산면 고봉리 283-2번지215553013.30Y35.98943126.78596
8전라북도군산시나포면행정복지센터전북특별자치도 군산시 나포면 나포초교길 9전북특별자치도 군산시 나포면 옥곤리 452번지3986117413.30Y36.030267126.832424
9전라북도군산시옥도면행정복지센터전북특별자치도 군산시 내항2길 125전북특별자치도 군산시 금동 1-18번지34974458.20Y35.993091126.710036
시도시군구명칭소재지 도로명주소소재지 지번주소대지면적건물연면적건폐율유휴면적사용여부위도경도
17전라북도군산시조촌동행정복지센터전북특별자치도 군산시 조촌5길 15전북특별자치도 군산시 조촌동 828-4번지17173259.90Y35.974503126.737306
18전라북도군산시경암동행정복지센터전북특별자치도 군산시 구암3.1로 63전북특별자치도 군산시 경암동 572-132번지31976860.30Y35.981597126.726223
19전라북도군산시구암동행정복지센터전북특별자치도 군산시 세풍길 21전북특별자치도 군산시 구암동 377번지197695215.40Y35.985862126.743998
20전라북도군산시개정동행정복지센터전북특별자치도 군산시 번영로 339-5전북특별자치도 군산시 개정동 507-24번지165855116.80Y35.964431126.75447
21전라북도군산시수송동행정복지센터전북특별자치도 군산시 동수송1길 7전북특별자치도 군산시 수송동 845-1번지3297171324.60Y35.964819126.71768
22전라북도군산시나운1동행정복지센터전북특별자치도 군산시 신설3길 3전북특별자치도 군산시 나운동 790-1번지62399952.80Y35.966808126.694832
23전라북도군산시나운2동행정복지센터전북특별자치도 군산시 나운3길 16전북특별자치도 군산시 나운동 376-1번지1496198745.50Y35.964868126.699608
24전라북도군산시나운3동행정복지센터전북특별자치도 군산시 부곡1길 25전북특별자치도 군산시 나운동 868-4번지874139349.30Y35.958807126.689232
25전라북도군산시소룡동행정복지센터전북특별자치도 군산시 설림안4길 30전북특별자치도 군산시 소룡동 1530-7번지3844179414.00Y35.973799126.683807
26전라북도군산시미성동행정복지센터전북특별자치도 군산시 공항로 371전북특별자치도 군산시 산북동 2479-3번지3641146516.00Y35.957783126.657584