Overview

Dataset statistics

Number of variables12
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory106.4 B

Variable types

Numeric6
Categorical2
Text3
DateTime1

Dataset

Description경상남도 김해동부소방서에서 지정한 관내 중점관리대상 현황 데이터로서, 김해동부소방서에서 주기적으로 해당 대상물에 대한 안전점검을 실시하고 있습니다.
Author경상남도
URLhttps://www.data.go.kr/data/15085941/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 연면적(제곱미터)High correlation
층(지상) is highly overall correlated with 등급High correlation
연면적(제곱미터) is highly overall correlated with 연번 and 1 other fieldsHigh correlation
등급 is highly overall correlated with 층(지상) and 2 other fieldsHigh correlation
구분 is highly overall correlated with 등급High correlation
연번 has unique valuesUnique
대상 has unique valuesUnique
연면적(제곱미터) has unique valuesUnique
층(지하) has 4 (13.3%) zerosZeros

Reproduction

Analysis started2024-03-23 06:34:52.935400
Analysis finished2024-03-23 06:35:07.708574
Duration14.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-23T06:35:08.154874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2024-03-23T06:35:08.669506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

등급
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2급
17 
1급
6 
공공(2급)
5 
특급
2 

Length

Max length6
Median length2
Mean length2.6666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공공(2급)
2nd row2급
3rd row2급
4th row2급
5th row2급

Common Values

ValueCountFrequency (%)
2급 17
56.7%
1급 6
 
20.0%
공공(2급) 5
 
16.7%
특급 2
 
6.7%

Length

2024-03-23T06:35:09.256532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:35:09.748995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2급 17
56.7%
1급 6
 
20.0%
공공(2급 5
 
16.7%
특급 2
 
6.7%

구분
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
의료
12 
노유자
6 
복합
5 
숙박
3 
위락
 
1
Other values (3)
3 

Length

Max length3
Median length2
Mean length2.2
Min length2

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row노유자
2nd row숙박
3rd row숙박
4th row노유자
5th row의료

Common Values

ValueCountFrequency (%)
의료 12
40.0%
노유자 6
20.0%
복합 5
16.7%
숙박 3
 
10.0%
위락 1
 
3.3%
판매 1
 
3.3%
교육 1
 
3.3%
공장 1
 
3.3%

Length

2024-03-23T06:35:10.448839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:35:10.957068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의료 12
40.0%
노유자 6
20.0%
복합 5
16.7%
숙박 3
 
10.0%
위락 1
 
3.3%
판매 1
 
3.3%
교육 1
 
3.3%
공장 1
 
3.3%

대상
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-23T06:35:11.616498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.7666667
Min length2

Characters and Unicode

Total characters233
Distinct characters104
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

Unique30 ?
Unique (%)100.0%

Sample

1st row동부노인종합복지관
2nd row가우디하우스
3rd row시티하우스
4th row은석문화회관
5th row서청솔요양병원
ValueCountFrequency (%)
동부노인종합복지관 1
 
3.3%
가우디하우스 1
 
3.3%
kt김해데이터센터 1
 
3.3%
보경프라자(용천스파랜드 1
 
3.3%
진주빌딩(맘스드림조리원 1
 
3.3%
인제요양병원 1
 
3.3%
조은금강병원 1
 
3.3%
신세계백화점(이마트 1
 
3.3%
휴앤락(cgv프리미어 1
 
3.3%
서원요양병원 1
 
3.3%
Other values (20) 20
66.7%
2024-03-23T06:35:12.601789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 15
 
6.4%
병 12
 
5.2%
양 9
 
3.9%
요 9
 
3.9%
김 7
 
3.0%
해 7
 
3.0%
이 6
 
2.6%
스 6
 
2.6%
복 5
 
2.1%
센 5
 
2.1%
Other values (94) 152
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 219
94.0%
Uppercase Letter 5
 
2.1%
Open Punctuation 4
 
1.7%
Close Punctuation 4
 
1.7%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 15
 
6.8%
병 12
 
5.5%
양 9
 
4.1%
요 9
 
4.1%
김 7
 
3.2%
해 7
 
3.2%
이 6
 
2.7%
스 6
 
2.7%
복 5
 
2.3%
센 5
 
2.3%
Other values (86) 138
63.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
20.0%
V 1
20.0%
G 1
20.0%
C 1
20.0%
T 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 219
94.0%
Common 9
 
3.9%
Latin 5
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 15
 
6.8%
병 12
 
5.5%
양 9
 
4.1%
요 9
 
4.1%
김 7
 
3.2%
해 7
 
3.2%
이 6
 
2.7%
스 6
 
2.7%
복 5
 
2.3%
센 5
 
2.3%
Other values (86) 138
63.0%
Latin
ValueCountFrequency (%)
K 1
20.0%
V 1
20.0%
G 1
20.0%
C 1
20.0%
T 1
20.0%
Common
ValueCountFrequency (%)
( 4
44.4%
) 4
44.4%
1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 219
94.0%
ASCII 14
 
6.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 15
 
6.8%
병 12
 
5.5%
양 9
 
4.1%
요 9
 
4.1%
김 7
 
3.2%
해 7
 
3.2%
이 6
 
2.7%
스 6
 
2.7%
복 5
 
2.3%
센 5
 
2.3%
Other values (86) 138
63.0%
ASCII
ValueCountFrequency (%)
( 4
28.6%
) 4
28.6%
K 1
 
7.1%
V 1
 
7.1%
G 1
 
7.1%
C 1
 
7.1%
T 1
 
7.1%
1
 
7.1%

위치(도로명주소)
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-23T06:35:13.206996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11.5
Mean length8.9
Min length6

Characters and Unicode

Total characters267
Distinct characters45
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

Unique26 ?
Unique (%)86.7%

Sample

1st row신어산길 46
2nd row인제로200번길 24
3rd row인제로200번길 28
4th row활천로 294
5th row금관대로1084번길 15
ValueCountFrequency (%)
김해대로 8
 
13.3%
신어산길 2
 
3.3%
2232 2
 
3.3%
인제로200번길 2
 
3.3%
12 2
 
3.3%
활천로 2
 
3.3%
46 2
 
3.3%
15 2
 
3.3%
83 2
 
3.3%
분성로 2
 
3.3%
Other values (34) 34
56.7%
2024-03-23T06:35:14.546093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
 
12.0%
로 28
 
10.5%
2 27
 
10.1%
3 17
 
6.4%
1 14
 
5.2%
5 11
 
4.1%
길 11
 
4.1%
0 10
 
3.7%
대 10
 
3.7%
4 10
 
3.7%
Other values (35) 97
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122
45.7%
Decimal Number 111
41.6%
Space Separator 32
 
12.0%
Dash Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 28
23.0%
길 11
 
9.0%
대 10
 
8.2%
번 9
 
7.4%
해 9
 
7.4%
김 9
 
7.4%
성 4
 
3.3%
분 4
 
3.3%
가 3
 
2.5%
천 3
 
2.5%
Other values (23) 32
26.2%
Decimal Number
ValueCountFrequency (%)
2 27
24.3%
3 17
15.3%
1 14
12.6%
5 11
9.9%
0 10
 
9.0%
4 10
 
9.0%
9 6
 
5.4%
8 6
 
5.4%
7 5
 
4.5%
6 5
 
4.5%
Space Separator
ValueCountFrequency (%)
32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 145
54.3%
Hangul 122
45.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 28
23.0%
길 11
 
9.0%
대 10
 
8.2%
번 9
 
7.4%
해 9
 
7.4%
김 9
 
7.4%
성 4
 
3.3%
분 4
 
3.3%
가 3
 
2.5%
천 3
 
2.5%
Other values (23) 32
26.2%
Common
ValueCountFrequency (%)
32
22.1%
2 27
18.6%
3 17
11.7%
1 14
9.7%
5 11
 
7.6%
0 10
 
6.9%
4 10
 
6.9%
9 6
 
4.1%
8 6
 
4.1%
7 5
 
3.4%
Other values (2) 7
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 145
54.3%
Hangul 122
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
22.1%
2 27
18.6%
3 17
11.7%
1 14
9.7%
5 11
 
7.6%
0 10
 
6.9%
4 10
 
6.9%
9 6
 
4.1%
8 6
 
4.1%
7 5
 
3.4%
Other values (2) 7
 
4.8%
Hangul
ValueCountFrequency (%)
로 28
23.0%
길 11
 
9.0%
대 10
 
8.2%
번 9
 
7.4%
해 9
 
7.4%
김 9
 
7.4%
성 4
 
3.3%
분 4
 
3.3%
가 3
 
2.5%
천 3
 
2.5%
Other values (23) 32
26.2%

위치(지번주소)
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-23T06:35:15.275822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.3666667
Min length6

Characters and Unicode

Total characters251
Distinct characters32
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

Unique26 ?
Unique (%)86.7%

Sample

1st row삼방동 838
2nd row삼방동 172-8
3rd row삼방동 173-5
4th row삼방동 194-3
5th row흥동 517
ValueCountFrequency (%)
삼방동 5
 
8.3%
내동 4
 
6.7%
부원동 4
 
6.7%
외동 4
 
6.7%
삼계동 3
 
5.0%
구산동 2
 
3.3%
838 2
 
3.3%
삼정동 2
 
3.3%
1264 2
 
3.3%
전하동 1
 
1.7%
Other values (31) 31
51.7%
2024-03-23T06:35:16.505605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 30
12.0%
30
12.0%
1 26
 
10.4%
- 21
 
8.4%
2 17
 
6.8%
3 15
 
6.0%
4 14
 
5.6%
6 12
 
4.8%
삼 10
 
4.0%
7 10
 
4.0%
Other values (22) 66
26.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 120
47.8%
Other Letter 80
31.9%
Space Separator 30
 
12.0%
Dash Punctuation 21
 
8.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 30
37.5%
삼 10
 
12.5%
방 6
 
7.5%
원 4
 
5.0%
외 4
 
5.0%
내 4
 
5.0%
부 4
 
5.0%
계 3
 
3.8%
구 2
 
2.5%
산 2
 
2.5%
Other values (10) 11
 
13.8%
Decimal Number
ValueCountFrequency (%)
1 26
21.7%
2 17
14.2%
3 15
12.5%
4 14
11.7%
6 12
10.0%
7 10
 
8.3%
9 7
 
5.8%
8 7
 
5.8%
0 6
 
5.0%
5 6
 
5.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 171
68.1%
Hangul 80
31.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 30
37.5%
삼 10
 
12.5%
방 6
 
7.5%
원 4
 
5.0%
외 4
 
5.0%
내 4
 
5.0%
부 4
 
5.0%
계 3
 
3.8%
구 2
 
2.5%
산 2
 
2.5%
Other values (10) 11
 
13.8%
Common
ValueCountFrequency (%)
30
17.5%
1 26
15.2%
- 21
12.3%
2 17
9.9%
3 15
8.8%
4 14
8.2%
6 12
 
7.0%
7 10
 
5.8%
9 7
 
4.1%
8 7
 
4.1%
Other values (2) 12
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 171
68.1%
Hangul 80
31.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 30
37.5%
삼 10
 
12.5%
방 6
 
7.5%
원 4
 
5.0%
외 4
 
5.0%
내 4
 
5.0%
부 4
 
5.0%
계 3
 
3.8%
구 2
 
2.5%
산 2
 
2.5%
Other values (10) 11
 
13.8%
ASCII
ValueCountFrequency (%)
30
17.5%
1 26
15.2%
- 21
12.3%
2 17
9.9%
3 15
8.8%
4 14
8.2%
6 12
 
7.0%
7 10
 
5.8%
9 7
 
4.1%
8 7
 
4.1%
Other values (2) 12
 
7.0%

위도
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.239782
Minimum35.223993
Maximum35.263817
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-23T06:35:17.084286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.223993
5-th percentile35.224845
Q135.229131
median35.237253
Q335.24877
95-th percentile35.260704
Maximum35.263817
Range0.0398237
Interquartile range (IQR)0.0196391

Descriptive statistics

Standard deviation0.012747277
Coefficient of variation (CV)0.00036172974
Kurtosis-1.0893333
Mean35.239782
Median Absolute Deviation (MAD)0.0090074
Skewness0.53908932
Sum1057.1935
Variance0.00016249307
MonotonicityNot monotonic
2024-03-23T06:35:17.708278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
35.2576111 2
 
6.7%
35.229131 2
 
6.7%
35.2250721 1
 
3.3%
35.2295055 1
 
3.3%
35.2495991 1
 
3.3%
35.2382244 1
 
3.3%
35.258775 1
 
3.3%
35.2622829 1
 
3.3%
35.2421645 1
 
3.3%
35.2341109 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
35.2239929 1
3.3%
35.2246583 1
3.3%
35.2250721 1
3.3%
35.2260141 1
3.3%
35.2269652 1
3.3%
35.227252 1
3.3%
35.2285204 1
3.3%
35.229131 2
6.7%
35.2295055 1
3.3%
35.2306135 1
3.3%
ValueCountFrequency (%)
35.2638166 1
3.3%
35.2622829 1
3.3%
35.258775 1
3.3%
35.2576111 2
6.7%
35.2563607 1
3.3%
35.2562727 1
3.3%
35.2495991 1
3.3%
35.2462831 1
3.3%
35.2462376 1
3.3%
35.2430858 1
3.3%

경도
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.88146
Minimum128.85073
Maximum128.91132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-23T06:35:18.252856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.85073
5-th percentile128.85814
Q1128.86963
median128.87547
Q3128.89676
95-th percentile128.90894
Maximum128.91132
Range0.0605867
Interquartile range (IQR)0.02712685

Descriptive statistics

Standard deviation0.017649236
Coefficient of variation (CV)0.00013694162
Kurtosis-1.0235507
Mean128.88146
Median Absolute Deviation (MAD)0.0102874
Skewness0.35894876
Sum3866.4439
Variance0.00031149555
MonotonicityNot monotonic
2024-03-23T06:35:18.990266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
128.9068182 2
 
6.7%
128.872148 2
 
6.7%
128.8832573 1
 
3.3%
128.9105106 1
 
3.3%
128.8634641 1
 
3.3%
128.8665949 1
 
3.3%
128.8719879 1
 
3.3%
128.860814 1
 
3.3%
128.8685765 1
 
3.3%
128.8809256 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
128.8507284 1
3.3%
128.855952 1
3.3%
128.860814 1
3.3%
128.8634641 1
3.3%
128.864495 1
3.3%
128.8665949 1
3.3%
128.8685765 1
3.3%
128.8695388 1
3.3%
128.8699098 1
3.3%
128.8710857 1
3.3%
ValueCountFrequency (%)
128.9113151 1
3.3%
128.9105106 1
3.3%
128.9070156 1
3.3%
128.9068182 2
6.7%
128.9065233 1
3.3%
128.9026391 1
3.3%
128.8979442 1
3.3%
128.893201 1
3.3%
128.887173 1
3.3%
128.8850698 1
3.3%

층(지상)
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0333333
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-23T06:35:19.740581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q15
median6
Q37.75
95-th percentile24.8
Maximum39
Range38
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation8.0106969
Coefficient of variation (CV)0.99718218
Kurtosis9.6376314
Mean8.0333333
Median Absolute Deviation (MAD)1.5
Skewness3.0768669
Sum241
Variance64.171264
MonotonicityNot monotonic
2024-03-23T06:35:20.479010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
6 8
26.7%
3 4
13.3%
5 4
13.3%
8 3
 
10.0%
7 3
 
10.0%
10 2
 
6.7%
4 2
 
6.7%
16 1
 
3.3%
32 1
 
3.3%
1 1
 
3.3%
ValueCountFrequency (%)
1 1
 
3.3%
3 4
13.3%
4 2
 
6.7%
5 4
13.3%
6 8
26.7%
7 3
 
10.0%
8 3
 
10.0%
10 2
 
6.7%
16 1
 
3.3%
32 1
 
3.3%
ValueCountFrequency (%)
39 1
 
3.3%
32 1
 
3.3%
16 1
 
3.3%
10 2
 
6.7%
8 3
 
10.0%
7 3
 
10.0%
6 8
26.7%
5 4
13.3%
4 2
 
6.7%
3 4
13.3%

층(지하)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5666667
Minimum0
Maximum5
Zeros4
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-23T06:35:20.900506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3.55
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1651057
Coefficient of variation (CV)0.74368448
Kurtosis1.5519515
Mean1.5666667
Median Absolute Deviation (MAD)1
Skewness1.0889823
Sum47
Variance1.3574713
MonotonicityNot monotonic
2024-03-23T06:35:21.406199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 13
43.3%
2 8
26.7%
0 4
 
13.3%
3 3
 
10.0%
4 1
 
3.3%
5 1
 
3.3%
ValueCountFrequency (%)
0 4
 
13.3%
1 13
43.3%
2 8
26.7%
3 3
 
10.0%
4 1
 
3.3%
5 1
 
3.3%
ValueCountFrequency (%)
5 1
 
3.3%
4 1
 
3.3%
3 3
 
10.0%
2 8
26.7%
1 13
43.3%
0 4
 
13.3%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24288.833
Minimum1343
Maximum202271
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-23T06:35:22.158158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1343
5-th percentile1965
Q14566.5
median7075.5
Q321471.25
95-th percentile116658.2
Maximum202271
Range200928
Interquartile range (IQR)16904.75

Descriptive statistics

Standard deviation44707.727
Coefficient of variation (CV)1.84067
Kurtosis9.9022516
Mean24288.833
Median Absolute Deviation (MAD)4222
Skewness3.1156507
Sum728665
Variance1.9987809 × 109
MonotonicityNot monotonic
2024-03-23T06:35:22.885573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4976 1
 
3.3%
202271 1
 
3.3%
37426 1
 
3.3%
36142 1
 
3.3%
11441 1
 
3.3%
4554 1
 
3.3%
2997 1
 
3.3%
35430 1
 
3.3%
147656 1
 
3.3%
33309 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1343 1
3.3%
1767 1
3.3%
2207 1
3.3%
2632 1
3.3%
2997 1
3.3%
3047 1
3.3%
3049 1
3.3%
4554 1
3.3%
4604 1
3.3%
4693 1
3.3%
ValueCountFrequency (%)
202271 1
3.3%
147656 1
3.3%
78772 1
3.3%
37426 1
3.3%
36142 1
3.3%
35430 1
3.3%
33309 1
3.3%
24052 1
3.3%
13729 1
3.3%
13391 1
3.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2024-01-01 00:00:00
Maximum2024-01-01 00:00:00
2024-03-23T06:35:23.536261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:24.333212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-23T06:35:04.517839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:54.173868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:56.168900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:58.414377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:00.480084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:02.586072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:04.792824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:54.484728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:56.534765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:58.758441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:00.831504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:02.965250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:05.185752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:54.886286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:56.932016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:59.130040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:01.166814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:03.318567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:05.501952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:55.200374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:57.330480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:59.448515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:01.509077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:03.573143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:05.775604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:55.514953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:57.726999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:59.834466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:01.912227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:03.882880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:06.204951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:55.760181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:34:58.030745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:00.110772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:02.203055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:35:04.203140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T06:35:24.762742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번등급구분대상위치(도로명주소)위치(지번주소)위도경도층(지상)층(지하)연면적(제곱미터)
연번1.0000.4620.4251.0000.8490.8490.3710.6830.0520.4880.356
등급0.4621.0000.9181.0000.9650.9650.4970.5010.8590.5150.818
구분0.4250.9181.0001.0000.7220.7220.6660.5180.5160.7160.705
대상1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위치(도로명주소)0.8490.9650.7221.0001.0001.0001.0001.0001.0000.9780.000
위치(지번주소)0.8490.9650.7221.0001.0001.0001.0001.0001.0000.9780.000
위도0.3710.4970.6661.0001.0001.0001.0000.6160.0000.4190.000
경도0.6830.5010.5181.0001.0001.0000.6161.0000.0000.7370.000
층(지상)0.0520.8590.5161.0001.0001.0000.0000.0001.0000.8890.792
층(지하)0.4880.5150.7161.0000.9780.9780.4190.7370.8891.0000.618
연면적(제곱미터)0.3560.8180.7051.0000.0000.0000.0000.0000.7920.6181.000
2024-03-23T06:35:25.200823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등급구분
등급1.0000.578
구분0.5781.000
2024-03-23T06:35:25.567406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도층(지상)층(지하)연면적(제곱미터)등급구분
연번1.000-0.064-0.298-0.0990.1520.5010.2360.174
위도-0.0641.000-0.065-0.312-0.419-0.3810.2920.384
경도-0.298-0.0651.000-0.1110.039-0.1670.2930.272
층(지상)-0.099-0.312-0.1111.0000.2040.1180.6960.290
층(지하)0.152-0.4190.0390.2041.0000.3920.3350.474
연면적(제곱미터)0.501-0.381-0.1670.1180.3921.0000.7680.491
등급0.2360.2920.2930.6960.3350.7681.0000.578
구분0.1740.3840.2720.2900.4740.4910.5781.000

Missing values

2024-03-23T06:35:06.737068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:35:07.472178image/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

연번등급구분대상위치(도로명주소)위치(지번주소)위도경도층(지상)층(지하)연면적(제곱미터)데이터기준일자
01공공(2급)노유자동부노인종합복지관신어산길 46삼방동 83835.257611128.9068183149762024-01-01
122급숙박가우디하우스인제로200번길 24삼방동 172-835.246238128.9065238017672024-01-01
232급숙박시티하우스인제로200번길 28삼방동 173-535.246283128.9070168013432024-01-01
342급노유자은석문화회관활천로 294삼방동 194-335.243086128.9113156366472024-01-01
452급의료서청솔요양병원금관대로1084번길 15흥동 51735.223993128.8507287265052024-01-01
562급의료강남요양병원평전로 83외동 672-535.238339128.8559526130472024-01-01
67공공(2급)노유자김해시여성센터신어산길 46삼방동 83835.257611128.9068183146042024-01-01
782급의료한가족요양병원전하로 234전하동 9-835.224658128.8725966190332024-01-01
892급의료이화수로요양병원분성로261번길 15봉황동 446-435.23415128.8744746247912024-01-01
9102급의료강일병원가락로359구산동 707-1235.256273128.8699181137292024-01-01
연번등급구분대상위치(도로명주소)위치(지번주소)위도경도층(지상)층(지하)연면적(제곱미터)데이터기준일자
2021특급복합부원역그린코아더센텀김해대로 2349부원동 606-335.226965128.883687395787722024-01-01
21222급의료서원요양병원가락로 83서상동 73-435.234111128.8809265275042024-01-01
22231급복합휴앤락(CGV프리미어)내외중앙로 137내동 1131-435.242165128.86857662333092024-01-01
23241급판매신세계백화점(이마트)김해대로 2232외동 126435.229131128.872148511476562024-01-01
24251급의료조은금강병원김해대로 1814-37삼계동 392-135.262283128.86081462354302024-01-01
25262급의료인제요양병원가야로 210삼계동 1509-1235.258775128.8719887129972024-01-01
26272급복합진주빌딩(맘스드림조리원)경원로55번길 12내동 1124-435.238224128.86659510145542024-01-01
27282급복합보경프라자(용천스파랜드)김해대로 2232외동 126435.229131128.87214852114412024-01-01
28291급교육KT김해데이터센터분성로3번길 235-2내동 225-235.249599128.86346451361422024-01-01
29301급공장넥센김해대로 2595안동 642-235.229506128.91051140374262024-01-01