Overview

Dataset statistics

Number of variables10
Number of observations118
Missing cells118
Missing cells (%)10.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory84.1 B

Variable types

Numeric3
Text3
Categorical3
DateTime1

Dataset

Description경상남도 진주시 기계설비유지관리자 선임 대상 건축물(일반건축물, 공동주택) 현황 자료입니다. 건물명, 용도, 연면적, 세대수, 주소 등에 관한 내용을 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15121799/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
관리부서명 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
관리부서 전화번호 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
용도 is highly overall correlated with 관리부서명 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 세대수 and 2 other fieldsHigh correlation
연면적(제곱미터) is highly overall correlated with 세대수 and 2 other fieldsHigh correlation
세대수 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
소재지도로명주소 has 56 (47.5%) missing valuesMissing
소재지지번주소 has 62 (52.5%) missing valuesMissing
연번 has unique valuesUnique
건물명 has unique valuesUnique
연면적(제곱미터) has unique valuesUnique
세대수 has 56 (47.5%) zerosZeros

Reproduction

Analysis started2023-12-12 21:07:21.738629
Analysis finished2023-12-12 21:07:23.491306
Duration1.75 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct118
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.5
Minimum1
Maximum118
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T06:07:23.558012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.85
Q130.25
median59.5
Q388.75
95-th percentile112.15
Maximum118
Range117
Interquartile range (IQR)58.5

Descriptive statistics

Standard deviation34.207699
Coefficient of variation (CV)0.57491931
Kurtosis-1.2
Mean59.5
Median Absolute Deviation (MAD)29.5
Skewness0
Sum7021
Variance1170.1667
MonotonicityStrictly increasing
2023-12-13T06:07:23.703183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
76 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
82 1
 
0.8%
81 1
 
0.8%
Other values (108) 108
91.5%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%
111 1
0.8%
110 1
0.8%
109 1
0.8%

건물명
Text

UNIQUE 

Distinct118
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T06:07:24.003325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length10.449153
Min length4

Characters and Unicode

Total characters1233
Distinct characters264
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)100.0%

Sample

1st row진주옥봉엘에이치아파트
2nd row하대주공아파트
3rd row상대주공아파트
4th row한보은빛마을아파트
5th row신안주공2단지아파트
ValueCountFrequency (%)
경상국립대학교 6
 
3.2%
주1동 4
 
2.1%
가좌캠퍼스 3
 
1.6%
초전 3
 
1.6%
해모로 2
 
1.1%
1동 2
 
1.1%
진주보건대학교 2
 
1.1%
칠암캠퍼스 2
 
1.1%
경상대학교병원 2
 
1.1%
주건축물제1동 2
 
1.1%
Other values (153) 159
85.0%
2023-12-13T06:07:24.472350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70
 
5.7%
주 51
 
4.1%
트 44
 
3.6%
아 42
 
3.4%
파 39
 
3.2%
진 31
 
2.5%
대 29
 
2.4%
지 26
 
2.1%
스 24
 
1.9%
동 22
 
1.8%
Other values (254) 855
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1055
85.6%
Space Separator 70
 
5.7%
Decimal Number 46
 
3.7%
Uppercase Letter 43
 
3.5%
Close Punctuation 7
 
0.6%
Open Punctuation 7
 
0.6%
Dash Punctuation 4
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 51
 
4.8%
트 44
 
4.2%
아 42
 
4.0%
파 39
 
3.7%
진 31
 
2.9%
대 29
 
2.7%
지 26
 
2.5%
스 24
 
2.3%
동 22
 
2.1%
공 20
 
1.9%
Other values (224) 727
68.9%
Uppercase Letter
ValueCountFrequency (%)
L 7
16.3%
H 7
16.3%
B 3
 
7.0%
G 3
 
7.0%
S 3
 
7.0%
A 3
 
7.0%
N 2
 
4.7%
T 2
 
4.7%
C 2
 
4.7%
K 2
 
4.7%
Other values (7) 9
20.9%
Decimal Number
ValueCountFrequency (%)
1 18
39.1%
2 9
19.6%
3 7
 
15.2%
4 5
 
10.9%
9 3
 
6.5%
5 2
 
4.3%
8 1
 
2.2%
7 1
 
2.2%
Space Separator
ValueCountFrequency (%)
70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1055
85.6%
Common 135
 
10.9%
Latin 43
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 51
 
4.8%
트 44
 
4.2%
아 42
 
4.0%
파 39
 
3.7%
진 31
 
2.9%
대 29
 
2.7%
지 26
 
2.5%
스 24
 
2.3%
동 22
 
2.1%
공 20
 
1.9%
Other values (224) 727
68.9%
Latin
ValueCountFrequency (%)
L 7
16.3%
H 7
16.3%
B 3
 
7.0%
G 3
 
7.0%
S 3
 
7.0%
A 3
 
7.0%
N 2
 
4.7%
T 2
 
4.7%
C 2
 
4.7%
K 2
 
4.7%
Other values (7) 9
20.9%
Common
ValueCountFrequency (%)
70
51.9%
1 18
 
13.3%
2 9
 
6.7%
) 7
 
5.2%
( 7
 
5.2%
3 7
 
5.2%
4 5
 
3.7%
- 4
 
3.0%
9 3
 
2.2%
5 2
 
1.5%
Other values (3) 3
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1052
85.3%
ASCII 178
 
14.4%
Compat Jamo 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70
39.3%
1 18
 
10.1%
2 9
 
5.1%
) 7
 
3.9%
L 7
 
3.9%
H 7
 
3.9%
( 7
 
3.9%
3 7
 
3.9%
4 5
 
2.8%
- 4
 
2.2%
Other values (20) 37
20.8%
Hangul
ValueCountFrequency (%)
주 51
 
4.8%
트 44
 
4.2%
아 42
 
4.0%
파 39
 
3.7%
진 31
 
2.9%
대 29
 
2.8%
지 26
 
2.5%
스 24
 
2.3%
동 22
 
2.1%
공 20
 
1.9%
Other values (223) 724
68.8%
Compat Jamo
ValueCountFrequency (%)
ㆍ 3
100.0%

용도
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
아파트
51 
교육연구시설
15 
공장
11 
판매시설
6 
업무시설
6 
Other values (16)
29 

Length

Max length9
Median length7
Mean length3.8983051
Min length2

Unique

Unique7 ?
Unique (%)5.9%

Sample

1st row행복주택
2nd row아파트
3rd row아파트
4th row아파트
5th row아파트

Common Values

ValueCountFrequency (%)
아파트 51
43.2%
교육연구시설 15
 
12.7%
공장 11
 
9.3%
판매시설 6
 
5.1%
업무시설 6
 
5.1%
의료시설 5
 
4.2%
국민임대 3
 
2.5%
주상복합 2
 
1.7%
민간임대 2
 
1.7%
교정및군사시설 2
 
1.7%
Other values (11) 15
 
12.7%

Length

2023-12-13T06:07:24.649005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아파트 51
43.2%
교육연구시설 15
 
12.7%
공장 11
 
9.3%
판매시설 6
 
5.1%
업무시설 6
 
5.1%
의료시설 5
 
4.2%
국민임대 3
 
2.5%
방송통신시설 2
 
1.7%
문화및집회시설 2
 
1.7%
숙박시설 2
 
1.7%
Other values (11) 15
 
12.7%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct118
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68476.837
Minimum3867.45
Maximum302824.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T06:07:24.821503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3867.45
5-th percentile11632.158
Q117884.147
median42374.34
Q3100137.9
95-th percentile178569.94
Maximum302824.4
Range298956.95
Interquartile range (IQR)82253.755

Descriptive statistics

Standard deviation61018.071
Coefficient of variation (CV)0.89107608
Kurtosis1.0844144
Mean68476.837
Median Absolute Deviation (MAD)30819.07
Skewness1.1713238
Sum8080266.7
Variance3.723205 × 109
MonotonicityNot monotonic
2023-12-13T06:07:24.989947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32355.89 1
 
0.8%
14139.05 1
 
0.8%
16607.59 1
 
0.8%
16458.01 1
 
0.8%
15856.8 1
 
0.8%
15539.92 1
 
0.8%
15443.43 1
 
0.8%
15318.37 1
 
0.8%
14771.75 1
 
0.8%
14633.1 1
 
0.8%
Other values (108) 108
91.5%
ValueCountFrequency (%)
3867.45 1
0.8%
10586.34 1
0.8%
10817.43 1
0.8%
10891.06 1
0.8%
11139.19 1
0.8%
11445.43 1
0.8%
11665.11 1
0.8%
11855.91 1
0.8%
11945.35 1
0.8%
11959.59 1
0.8%
ValueCountFrequency (%)
302824.3991 1
0.8%
219327.77 1
0.8%
215468.5585 1
0.8%
214861.81 1
0.8%
207217.1236 1
0.8%
180869.2017 1
0.8%
178164.1896 1
0.8%
177888.448 1
0.8%
171063.0137 1
0.8%
170809.92 1
0.8%

세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct62
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean451.11017
Minimum0
Maximum1813
Zeros56
Zeros (%)47.5%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T06:07:25.121268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median513
Q3790
95-th percentile1317.6
Maximum1813
Range1813
Interquartile range (IQR)790

Descriptive statistics

Standard deviation483.75677
Coefficient of variation (CV)1.0723695
Kurtosis-0.56247795
Mean451.11017
Median Absolute Deviation (MAD)513
Skewness0.62619079
Sum53231
Variance234020.61
MonotonicityNot monotonic
2023-12-13T06:07:25.261898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 56
47.5%
500 2
 
1.7%
1046 1
 
0.8%
805 1
 
0.8%
812 1
 
0.8%
826 1
 
0.8%
830 1
 
0.8%
840 1
 
0.8%
869 1
 
0.8%
883 1
 
0.8%
Other values (52) 52
44.1%
ValueCountFrequency (%)
0 56
47.5%
500 2
 
1.7%
510 1
 
0.8%
516 1
 
0.8%
519 1
 
0.8%
520 1
 
0.8%
543 1
 
0.8%
560 1
 
0.8%
564 1
 
0.8%
586 1
 
0.8%
ValueCountFrequency (%)
1813 1
0.8%
1709 1
0.8%
1530 1
0.8%
1465 1
0.8%
1421 1
0.8%
1372 1
0.8%
1308 1
0.8%
1268 1
0.8%
1256 1
0.8%
1152 1
0.8%

소재지도로명주소
Text

MISSING 

Distinct62
Distinct (%)100.0%
Missing56
Missing (%)47.5%
Memory size1.1 KiB
2023-12-13T06:07:25.502944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length31.612903
Min length15

Characters and Unicode

Total characters1960
Distinct characters171
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)100.0%

Sample

1st row경상남도 진주시 진산로 20
2nd row경상남도 진주시 상대로 125 (하대동, 주공아파트)
3rd row경상남도 진주시 상대로 101 (하대동, 상대아파트)
4th row경상남도 진주시 천수로 30 (주약동, 한보은빛마을아파트)
5th row경상남도 진주시 신안들말길 47 (신안동, 신안주공2단지)
ValueCountFrequency (%)
경상남도 62
 
17.7%
진주시 62
 
17.7%
신안동 5
 
1.4%
평거동 5
 
1.4%
가좌동 5
 
1.4%
사들로 5
 
1.4%
새평거로 5
 
1.4%
주약동 4
 
1.1%
초북로 4
 
1.1%
금산면 3
 
0.9%
Other values (162) 190
54.3%
2023-12-13T06:07:26.193743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
290
 
14.8%
주 93
 
4.7%
진 78
 
4.0%
상 72
 
3.7%
시 71
 
3.6%
도 69
 
3.5%
경 68
 
3.5%
남 65
 
3.3%
로 61
 
3.1%
) 57
 
2.9%
Other values (161) 1036
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1296
66.1%
Space Separator 290
 
14.8%
Decimal Number 196
 
10.0%
Close Punctuation 57
 
2.9%
Open Punctuation 57
 
2.9%
Other Punctuation 55
 
2.8%
Uppercase Letter 4
 
0.2%
Lowercase Letter 3
 
0.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 93
 
7.2%
진 78
 
6.0%
상 72
 
5.6%
시 71
 
5.5%
도 69
 
5.3%
경 68
 
5.2%
남 65
 
5.0%
로 61
 
4.7%
동 53
 
4.1%
아 34
 
2.6%
Other values (140) 632
48.8%
Decimal Number
ValueCountFrequency (%)
1 46
23.5%
2 24
12.2%
5 24
12.2%
3 20
10.2%
4 16
 
8.2%
7 16
 
8.2%
0 15
 
7.7%
9 12
 
6.1%
6 12
 
6.1%
8 11
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
s 1
33.3%
k 1
33.3%
y 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 54
98.2%
? 1
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
L 2
50.0%
H 2
50.0%
Space Separator
ValueCountFrequency (%)
290
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1296
66.1%
Common 657
33.5%
Latin 7
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 93
 
7.2%
진 78
 
6.0%
상 72
 
5.6%
시 71
 
5.5%
도 69
 
5.3%
경 68
 
5.2%
남 65
 
5.0%
로 61
 
4.7%
동 53
 
4.1%
아 34
 
2.6%
Other values (140) 632
48.8%
Common
ValueCountFrequency (%)
290
44.1%
) 57
 
8.7%
( 57
 
8.7%
, 54
 
8.2%
1 46
 
7.0%
2 24
 
3.7%
5 24
 
3.7%
3 20
 
3.0%
4 16
 
2.4%
7 16
 
2.4%
Other values (6) 53
 
8.1%
Latin
ValueCountFrequency (%)
L 2
28.6%
H 2
28.6%
s 1
14.3%
k 1
14.3%
y 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1296
66.1%
ASCII 664
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
290
43.7%
) 57
 
8.6%
( 57
 
8.6%
, 54
 
8.1%
1 46
 
6.9%
2 24
 
3.6%
5 24
 
3.6%
3 20
 
3.0%
4 16
 
2.4%
7 16
 
2.4%
Other values (11) 60
 
9.0%
Hangul
ValueCountFrequency (%)
주 93
 
7.2%
진 78
 
6.0%
상 72
 
5.6%
시 71
 
5.5%
도 69
 
5.3%
경 68
 
5.2%
남 65
 
5.0%
로 61
 
4.7%
동 53
 
4.1%
아 34
 
2.6%
Other values (140) 632
48.8%

소재지지번주소
Text

MISSING 

Distinct49
Distinct (%)87.5%
Missing62
Missing (%)52.5%
Memory size1.1 KiB
2023-12-13T06:07:26.416835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length20.946429
Min length16

Characters and Unicode

Total characters1173
Distinct characters62
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

Unique45 ?
Unique (%)80.4%

Sample

1st row경상남도 진주시 칠암동 0150-0001
2nd row경상남도 진주시 계동 0038
3rd row경상남도 진주시 문산읍 삼곡리 0854
4th row경상남도 진주시 금산면 용아리 1016-0010
5th row경상남도 진주시 정촌면 예하리 1240-0005
ValueCountFrequency (%)
경상남도 56
23.6%
진주시 56
23.6%
충무공동 10
 
4.2%
정촌면 7
 
3.0%
예하리 7
 
3.0%
0900 6
 
2.5%
가좌동 6
 
2.5%
상대동 5
 
2.1%
칠암동 5
 
2.1%
상평동 3
 
1.3%
Other values (69) 76
32.1%
2023-12-13T06:07:26.722055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
181
15.4%
0 179
15.3%
상 66
 
5.6%
경 57
 
4.9%
남 57
 
4.9%
도 56
 
4.8%
진 56
 
4.8%
주 56
 
4.8%
시 56
 
4.8%
1 47
 
4.0%
Other values (52) 362
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 608
51.8%
Decimal Number 352
30.0%
Space Separator 181
 
15.4%
Dash Punctuation 32
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 66
10.9%
경 57
9.4%
남 57
9.4%
도 56
9.2%
진 56
9.2%
주 56
9.2%
시 56
9.2%
동 44
 
7.2%
리 13
 
2.1%
면 12
 
2.0%
Other values (40) 135
22.2%
Decimal Number
ValueCountFrequency (%)
0 179
50.9%
1 47
 
13.4%
2 27
 
7.7%
5 20
 
5.7%
4 16
 
4.5%
8 15
 
4.3%
9 14
 
4.0%
3 13
 
3.7%
7 11
 
3.1%
6 10
 
2.8%
Space Separator
ValueCountFrequency (%)
181
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 608
51.8%
Common 565
48.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 66
10.9%
경 57
9.4%
남 57
9.4%
도 56
9.2%
진 56
9.2%
주 56
9.2%
시 56
9.2%
동 44
 
7.2%
리 13
 
2.1%
면 12
 
2.0%
Other values (40) 135
22.2%
Common
ValueCountFrequency (%)
181
32.0%
0 179
31.7%
1 47
 
8.3%
- 32
 
5.7%
2 27
 
4.8%
5 20
 
3.5%
4 16
 
2.8%
8 15
 
2.7%
9 14
 
2.5%
3 13
 
2.3%
Other values (2) 21
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 608
51.8%
ASCII 565
48.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
181
32.0%
0 179
31.7%
1 47
 
8.3%
- 32
 
5.7%
2 27
 
4.8%
5 20
 
3.5%
4 16
 
2.8%
8 15
 
2.7%
9 14
 
2.5%
3 13
 
2.3%
Other values (2) 21
 
3.7%
Hangul
ValueCountFrequency (%)
상 66
10.9%
경 57
9.4%
남 57
9.4%
도 56
9.2%
진 56
9.2%
주 56
9.2%
시 56
9.2%
동 44
 
7.2%
리 13
 
2.1%
면 12
 
2.0%
Other values (40) 135
22.2%

관리부서명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
주택경관과
62 
건축과
56 

Length

Max length5
Median length5
Mean length4.0508475
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주택경관과 62
52.5%
건축과 56
47.5%

Length

2023-12-13T06:07:26.860664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:07:26.944791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주택경관과 62
52.5%
건축과 56
47.5%

관리부서 전화번호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
055-749-5583
62 
055-749-5584
56 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row055-749-5583
2nd row055-749-5583
3rd row055-749-5583
4th row055-749-5583
5th row055-749-5583

Common Values

ValueCountFrequency (%)
055-749-5583 62
52.5%
055-749-5584 56
47.5%

Length

2023-12-13T06:07:27.024048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:07:27.122912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
055-749-5583 62
52.5%
055-749-5584 56
47.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-08-31 00:00:00
Maximum2023-08-31 00:00:00
2023-12-13T06:07:27.211844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:27.299974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T06:07:22.828655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:22.250571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:22.561787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:22.925014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:22.339463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:22.652084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:23.027950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:22.463429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:22.737399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:07:27.361418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번용도연면적(제곱미터)세대수소재지도로명주소소재지지번주소관리부서명관리부서 전화번호
연번1.0000.6440.7080.8531.0000.7420.9980.998
용도0.6441.0000.1720.1941.0001.0001.0001.000
연면적(제곱미터)0.7080.1721.0000.8691.0000.9810.7850.785
세대수0.8530.1940.8691.0001.000NaN1.0001.000
소재지도로명주소1.0001.0001.0001.0001.000NaNNaNNaN
소재지지번주소0.7421.0000.981NaNNaN1.000NaNNaN
관리부서명0.9981.0000.7851.000NaNNaN1.0001.000
관리부서 전화번호0.9981.0000.7851.000NaNNaN1.0001.000
2023-12-13T06:07:27.463592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리부서명관리부서 전화번호용도
관리부서명1.0000.9830.914
관리부서 전화번호0.9831.0000.914
용도0.9140.9141.000
2023-12-13T06:07:27.562022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적(제곱미터)세대수용도관리부서명관리부서 전화번호
연번1.000-0.396-0.6380.2820.9240.924
연면적(제곱미터)-0.3961.0000.8140.0000.7670.767
세대수-0.6380.8141.0000.0600.9690.969
용도0.2820.0000.0601.0000.9140.914
관리부서명0.9240.7670.9690.9141.0000.983
관리부서 전화번호0.9240.7670.9690.9140.9831.000

Missing values

2023-12-13T06:07:23.163143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:07:23.324414image/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.
2023-12-13T06:07:23.442142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번건물명용도연면적(제곱미터)세대수소재지도로명주소소재지지번주소관리부서명관리부서 전화번호데이터기준일자
01진주옥봉엘에이치아파트행복주택32355.89500경상남도 진주시 진산로 20<NA>주택경관과055-749-55832023-08-31
12하대주공아파트아파트23725.7500경상남도 진주시 상대로 125 (하대동, 주공아파트)<NA>주택경관과055-749-55832023-08-31
23상대주공아파트아파트21687.32510경상남도 진주시 상대로 101 (하대동, 상대아파트)<NA>주택경관과055-749-55832023-08-31
34한보은빛마을아파트아파트87568.05516경상남도 진주시 천수로 30 (주약동, 한보은빛마을아파트)<NA>주택경관과055-749-55832023-08-31
45신안주공2단지아파트아파트32996.63519경상남도 진주시 신안들말길 47 (신안동, 신안주공2단지)<NA>주택경관과055-749-55832023-08-31
56진주문산코아루아파트아파트80099.2986520경상남도 진주시 문산읍 월아산로1117번길 5(진주문산코아루아파트)<NA>주택경관과055-749-55832023-08-31
67진주초장이지더원아파트아파트88530.3519543경상남도 진주시 초장로 120(초전동, 이지더원)<NA>주택경관과055-749-55832023-08-31
78중흥센트럴시티 2단지주상복합147347.6748560경상남도 진주시 에나로 190<NA>주택경관과055-749-55832023-08-31
89초전 해모로 루비채 2단지아파트85633.1282564경상남도 진주시 초북로 88(초전동, 초전해모로루비채2단지)<NA>주택경관과055-749-55832023-08-31
910주약현대2차아파트아파트79416.13586경상남도 진주시 진주대로815번길 11 (주약동, 주약현대아파트)<NA>주택경관과055-749-55832023-08-31
연번건물명용도연면적(제곱미터)세대수소재지도로명주소소재지지번주소관리부서명관리부서 전화번호데이터기준일자
108109청과물도매시장판매및영업시설32482.750<NA>경상남도 진주시 초전동 0260건축과055-749-55842023-08-31
109110경상대학교병원 병원본관동(1동)의료시설38693.430<NA>경상남도 진주시 칠암동 0090건축과055-749-55842023-08-31
110111진주교도소교정및군사시설40491.770<NA>경상남도 진주시 대곡면 광석리 0700건축과055-749-55842023-08-31
111112진주종합경기장 주건축물제1동문화및집회시설41160.750<NA>경상남도 진주시 충무공동 0008건축과055-749-55842023-08-31
112113이마트 진주점판매시설43587.930<NA>경상남도 진주시 인사동 0003건축과055-749-55842023-08-31
113114홈플러스판매시설52054.740<NA>경상남도 진주시 상대동 0181-0001건축과055-749-55842023-08-31
114115한화갤러리아백화점판매시설53775.940<NA>경상남도 진주시 평안동 0195건축과055-749-55842023-08-31
115116진주시청업무시설56421.440<NA>경상남도 진주시 상대동 0284건축과055-749-55842023-08-31
116117무림페이퍼 1동공장93157.640<NA>경상남도 진주시 상평동 0281-0001건축과055-749-55842023-08-31
117118롯데아울렛 진주점판매시설99184.240<NA>경상남도 진주시 충무공동 0035건축과055-749-55842023-08-31