Overview

Dataset statistics

Number of variables14
Number of observations38
Missing cells13
Missing cells (%)2.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory120.5 B

Variable types

Categorical4
Text4
Numeric5
DateTime1

Dataset

Description경기도 수원시 관내에 설치된 빗물을 활용하는 시설인 빗물이용시설에 대한 집수면적,용량,설치연도,설치구분,사용용도 등에 관한 자료를 제공합니다.
URLhttps://www.data.go.kr/data/15040640/fileData.do

Alerts

시도명 has constant value ""Constant
시군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
집수면적(제곱미터) is highly overall correlated with 용량(제곱미터)High correlation
용량(제곱미터) is highly overall correlated with 집수면적(제곱미터)High correlation
사용용도 is highly imbalanced (52.2%)Imbalance
소재지도로명주소 has 1 (2.6%) missing valuesMissing
전화번호 has 12 (31.6%) missing valuesMissing
시설명 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:33:23.243065
Analysis finished2023-12-12 12:33:27.701725
Duration4.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
경기도
38 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 38
100.0%

Length

2023-12-12T21:33:27.793455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:33:27.928903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 38
100.0%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
수원시
38 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수원시 38
100.0%

Length

2023-12-12T21:33:28.049473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:33:28.155625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수원시 38
100.0%

시설명
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T21:33:28.314784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length10.921053
Min length4

Characters and Unicode

Total characters415
Distinct characters137
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

Unique38 ?
Unique (%)100.0%

Sample

1st row한국농수산식품유통공사 농식품유통교육원
2nd row경인지방우정청
3rd row국민체육진흥센터(종합운동장내)
4th row학교법인 경기학원 광교씨름장(광교씨름체육관)
5th row수원시립아이파크미술관
ValueCountFrequency (%)
경기도청 2
 
3.6%
한국농수산식품유통공사 1
 
1.8%
하나로마트 1
 
1.8%
수원센트럴아이파크자이 1
 
1.8%
수원가정법원청사 1
 
1.8%
수원역 1
 
1.8%
푸르지오 1
 
1.8%
자이 1
 
1.8%
영화동 1
 
1.8%
행정복지센터 1
 
1.8%
Other values (45) 45
80.4%
2023-12-12T21:33:28.761129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
4.8%
원 19
 
4.6%
수 14
 
3.4%
이 14
 
3.4%
지 14
 
3.4%
스 12
 
2.9%
교 12
 
2.9%
파 10
 
2.4%
트 9
 
2.2%
크 9
 
2.2%
Other values (127) 282
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 372
89.6%
Space Separator 20
 
4.8%
Decimal Number 10
 
2.4%
Uppercase Letter 7
 
1.7%
Open Punctuation 2
 
0.5%
Close Punctuation 2
 
0.5%
Lowercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 19
 
5.1%
수 14
 
3.8%
이 14
 
3.8%
지 14
 
3.8%
스 12
 
3.2%
교 12
 
3.2%
파 10
 
2.7%
트 9
 
2.4%
크 9
 
2.4%
청 8
 
2.2%
Other values (110) 251
67.5%
Decimal Number
ValueCountFrequency (%)
1 3
30.0%
2 2
20.0%
8 1
 
10.0%
4 1
 
10.0%
7 1
 
10.0%
3 1
 
10.0%
5 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
K 1
14.3%
V 1
14.3%
I 1
14.3%
E 1
14.3%
W 1
14.3%
Space Separator
ValueCountFrequency (%)
20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 372
89.6%
Common 34
 
8.2%
Latin 9
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 19
 
5.1%
수 14
 
3.8%
이 14
 
3.8%
지 14
 
3.8%
스 12
 
3.2%
교 12
 
3.2%
파 10
 
2.7%
트 9
 
2.4%
크 9
 
2.4%
청 8
 
2.2%
Other values (110) 251
67.5%
Common
ValueCountFrequency (%)
20
58.8%
1 3
 
8.8%
2 2
 
5.9%
( 2
 
5.9%
) 2
 
5.9%
8 1
 
2.9%
4 1
 
2.9%
7 1
 
2.9%
3 1
 
2.9%
5 1
 
2.9%
Latin
ValueCountFrequency (%)
S 2
22.2%
e 2
22.2%
K 1
11.1%
V 1
11.1%
I 1
11.1%
E 1
11.1%
W 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 372
89.6%
ASCII 43
 
10.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
46.5%
1 3
 
7.0%
2 2
 
4.7%
S 2
 
4.7%
( 2
 
4.7%
) 2
 
4.7%
e 2
 
4.7%
8 1
 
2.3%
K 1
 
2.3%
V 1
 
2.3%
Other values (7) 7
 
16.3%
Hangul
ValueCountFrequency (%)
원 19
 
5.1%
수 14
 
3.8%
이 14
 
3.8%
지 14
 
3.8%
스 12
 
3.2%
교 12
 
3.2%
파 10
 
2.7%
트 9
 
2.4%
크 9
 
2.4%
청 8
 
2.2%
Other values (110) 251
67.5%

소재지도로명주소
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing1
Missing (%)2.6%
Memory size436.0 B
2023-12-12T21:33:29.059146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length20.72973
Min length18

Characters and Unicode

Total characters767
Distinct characters73
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

Unique37 ?
Unique (%)100.0%

Sample

1st row경기도 수원시 권선구 당진로 43-33
2nd row경기도 수원시 권선구 호매실로 22-55
3rd row경기도 수원시 장안구 경수대로 893
4th row경기도 수원시 영통구 광교산로 154-42
5th row경기도 수원시 팔달구 정조로 833
ValueCountFrequency (%)
경기도 37
19.9%
수원시 37
19.9%
영통구 18
 
9.7%
권선구 10
 
5.4%
팔달구 6
 
3.2%
장안구 3
 
1.6%
덕영대로 3
 
1.6%
곡반정로 3
 
1.6%
도청로 2
 
1.1%
법조로 2
 
1.1%
Other values (64) 65
34.9%
2023-12-12T21:33:29.636291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
19.4%
수 40
 
5.2%
원 40
 
5.2%
도 39
 
5.1%
경 38
 
5.0%
시 37
 
4.8%
기 37
 
4.8%
구 37
 
4.8%
로 35
 
4.6%
영 24
 
3.1%
Other values (63) 291
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 490
63.9%
Space Separator 149
 
19.4%
Decimal Number 123
 
16.0%
Dash Punctuation 5
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 40
 
8.2%
원 40
 
8.2%
도 39
 
8.0%
경 38
 
7.8%
시 37
 
7.6%
기 37
 
7.6%
구 37
 
7.6%
로 35
 
7.1%
영 24
 
4.9%
통 18
 
3.7%
Other values (51) 145
29.6%
Decimal Number
ValueCountFrequency (%)
1 22
17.9%
3 18
14.6%
2 15
12.2%
0 12
9.8%
4 12
9.8%
5 12
9.8%
6 9
7.3%
9 9
7.3%
8 9
7.3%
7 5
 
4.1%
Space Separator
ValueCountFrequency (%)
149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 490
63.9%
Common 277
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 40
 
8.2%
원 40
 
8.2%
도 39
 
8.0%
경 38
 
7.8%
시 37
 
7.6%
기 37
 
7.6%
구 37
 
7.6%
로 35
 
7.1%
영 24
 
4.9%
통 18
 
3.7%
Other values (51) 145
29.6%
Common
ValueCountFrequency (%)
149
53.8%
1 22
 
7.9%
3 18
 
6.5%
2 15
 
5.4%
0 12
 
4.3%
4 12
 
4.3%
5 12
 
4.3%
6 9
 
3.2%
9 9
 
3.2%
8 9
 
3.2%
Other values (2) 10
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 490
63.9%
ASCII 277
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
53.8%
1 22
 
7.9%
3 18
 
6.5%
2 15
 
5.4%
0 12
 
4.3%
4 12
 
4.3%
5 12
 
4.3%
6 9
 
3.2%
9 9
 
3.2%
8 9
 
3.2%
Other values (2) 10
 
3.6%
Hangul
ValueCountFrequency (%)
수 40
 
8.2%
원 40
 
8.2%
도 39
 
8.0%
경 38
 
7.8%
시 37
 
7.6%
기 37
 
7.6%
구 37
 
7.6%
로 35
 
7.1%
영 24
 
4.9%
통 18
 
3.7%
Other values (51) 145
29.6%

소재지지번주소
Text

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T21:33:29.926510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length20.105263
Min length15

Characters and Unicode

Total characters764
Distinct characters56
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

Unique36 ?
Unique (%)94.7%

Sample

1st row경기도 수원시 권선구 당수동 148-1
2nd row경기도 수원시 권선구 탑동 909
3rd row경기도 수원시 권선구 조원동 775
4th row경기도 수원시 영통구 이의동 934-11
5th row경기도 수원시 팔달구 신풍동 238-1
ValueCountFrequency (%)
경기도 38
20.1%
수원시 38
20.1%
영통구 19
 
10.1%
권선구 11
 
5.8%
이의동 8
 
4.2%
팔달구 6
 
3.2%
하동 4
 
2.1%
곡반정동 3
 
1.6%
망포동 3
 
1.6%
장안구 2
 
1.1%
Other values (52) 57
30.2%
2023-12-12T21:33:30.364436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
151
19.8%
원 41
 
5.4%
수 39
 
5.1%
경 38
 
5.0%
도 38
 
5.0%
시 38
 
5.0%
구 38
 
5.0%
기 38
 
5.0%
동 38
 
5.0%
1 37
 
4.8%
Other values (46) 268
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 456
59.7%
Space Separator 151
 
19.8%
Decimal Number 139
 
18.2%
Dash Punctuation 18
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 41
 
9.0%
수 39
 
8.6%
경 38
 
8.3%
도 38
 
8.3%
시 38
 
8.3%
구 38
 
8.3%
기 38
 
8.3%
동 38
 
8.3%
영 22
 
4.8%
통 21
 
4.6%
Other values (34) 105
23.0%
Decimal Number
ValueCountFrequency (%)
1 37
26.6%
9 17
12.2%
2 16
11.5%
6 12
 
8.6%
5 12
 
8.6%
3 11
 
7.9%
7 11
 
7.9%
0 9
 
6.5%
4 8
 
5.8%
8 6
 
4.3%
Space Separator
ValueCountFrequency (%)
151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 456
59.7%
Common 308
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 41
 
9.0%
수 39
 
8.6%
경 38
 
8.3%
도 38
 
8.3%
시 38
 
8.3%
구 38
 
8.3%
기 38
 
8.3%
동 38
 
8.3%
영 22
 
4.8%
통 21
 
4.6%
Other values (34) 105
23.0%
Common
ValueCountFrequency (%)
151
49.0%
1 37
 
12.0%
- 18
 
5.8%
9 17
 
5.5%
2 16
 
5.2%
6 12
 
3.9%
5 12
 
3.9%
3 11
 
3.6%
7 11
 
3.6%
0 9
 
2.9%
Other values (2) 14
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 456
59.7%
ASCII 308
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
151
49.0%
1 37
 
12.0%
- 18
 
5.8%
9 17
 
5.5%
2 16
 
5.2%
6 12
 
3.9%
5 12
 
3.9%
3 11
 
3.6%
7 11
 
3.6%
0 9
 
2.9%
Other values (2) 14
 
4.5%
Hangul
ValueCountFrequency (%)
원 41
 
9.0%
수 39
 
8.6%
경 38
 
8.3%
도 38
 
8.3%
시 38
 
8.3%
구 38
 
8.3%
기 38
 
8.3%
동 38
 
8.3%
영 22
 
4.8%
통 21
 
4.6%
Other values (34) 105
23.0%

위도
Real number (ℝ)

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.273539
Minimum37.238981
Maximum37.309863
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T21:33:30.548485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.238981
5-th percentile37.241382
Q137.2556
median37.276507
Q337.290118
95-th percentile37.309269
Maximum37.309863
Range0.07088189
Interquartile range (IQR)0.034518933

Descriptive statistics

Standard deviation0.022016687
Coefficient of variation (CV)0.00059067874
Kurtosis-1.2339259
Mean37.273539
Median Absolute Deviation (MAD)0.016619375
Skewness-0.086604164
Sum1416.3945
Variance0.00048473451
MonotonicityNot monotonic
2023-12-12T21:33:30.766330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
37.29311234 1
 
2.6%
37.244507 1
 
2.6%
37.27664496 1
 
2.6%
37.29314137 1
 
2.6%
37.29013358 1
 
2.6%
37.290073 1
 
2.6%
37.289316 1
 
2.6%
37.243349 1
 
2.6%
37.23902067 1
 
2.6%
37.267605 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
37.23898114 1
2.6%
37.23902067 1
2.6%
37.2417984 1
2.6%
37.243349 1
2.6%
37.24352856 1
2.6%
37.24386086 1
2.6%
37.244507 1
2.6%
37.24723123 1
2.6%
37.25228895 1
2.6%
37.25470712 1
2.6%
ValueCountFrequency (%)
37.30986303 1
2.6%
37.30959946 1
2.6%
37.30921046 1
2.6%
37.3002178 1
2.6%
37.2992625 1
2.6%
37.29637287 1
2.6%
37.29314137 1
2.6%
37.29311234 1
2.6%
37.29053426 1
2.6%
37.29013358 1
2.6%

경도
Real number (ℝ)

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.03121
Minimum126.94007
Maximum127.07296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T21:33:30.970867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.94007
5-th percentile126.95824
Q1127.0168
median127.03796
Q3127.05342
95-th percentile127.07108
Maximum127.07296
Range0.1328934
Interquartile range (IQR)0.0366194

Descriptive statistics

Standard deviation0.034913241
Coefficient of variation (CV)0.00027483986
Kurtosis0.59029233
Mean127.03121
Median Absolute Deviation (MAD)0.01861145
Skewness-1.0877153
Sum4827.186
Variance0.0012189344
MonotonicityNot monotonic
2023-12-12T21:33:31.149616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
126.9400666 1
 
2.6%
127.037521 1
 
2.6%
126.9985956 1
 
2.6%
127.0139542 1
 
2.6%
126.9889503 1
 
2.6%
127.052978 1
 
2.6%
127.053525 1
 
2.6%
127.035734 1
 
2.6%
127.034497 1
 
2.6%
127.0206993 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
126.9400666 1
2.6%
126.9506006 1
2.6%
126.9595835 1
2.6%
126.9700961 1
2.6%
126.98243 1
2.6%
126.9889503 1
2.6%
126.9985956 1
2.6%
127.0097112 1
2.6%
127.0139542 1
2.6%
127.0157242 1
2.6%
ValueCountFrequency (%)
127.07296 1
2.6%
127.0726704 1
2.6%
127.0708 1
2.6%
127.07031 1
2.6%
127.0692751 1
2.6%
127.0675535 1
2.6%
127.0655995 1
2.6%
127.0575195 1
2.6%
127.0572677 1
2.6%
127.053525 1
2.6%

집수면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7882.3421
Minimum593
Maximum36474
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T21:33:31.311174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum593
5-th percentile714.9
Q11482
median3348.5
Q310614.75
95-th percentile26266.85
Maximum36474
Range35881
Interquartile range (IQR)9132.75

Descriptive statistics

Standard deviation9076.4766
Coefficient of variation (CV)1.1514949
Kurtosis2.9833808
Mean7882.3421
Median Absolute Deviation (MAD)2351.5
Skewness1.7870169
Sum299529
Variance82382428
MonotonicityNot monotonic
2023-12-12T21:33:31.483042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1401 2
 
5.3%
1352 1
 
2.6%
34596 1
 
2.6%
36474 1
 
2.6%
729 1
 
2.6%
17061 1
 
2.6%
1426 1
 
2.6%
8651 1
 
2.6%
16146 1
 
2.6%
20295 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
593 1
2.6%
635 1
2.6%
729 1
2.6%
836 1
2.6%
1158 1
2.6%
1352 1
2.6%
1401 2
5.3%
1426 1
2.6%
1438 1
2.6%
1614 1
2.6%
ValueCountFrequency (%)
36474 1
2.6%
34596 1
2.6%
24797 1
2.6%
20295 1
2.6%
17061 1
2.6%
16702 1
2.6%
16146 1
2.6%
13764 1
2.6%
12618 1
2.6%
10652 1
2.6%

용량(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean571.47368
Minimum50
Maximum2214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T21:33:31.676975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile71.1
Q1137.25
median473.5
Q3871
95-th percentile1375.85
Maximum2214
Range2164
Interquartile range (IQR)733.75

Descriptive statistics

Standard deviation516.867
Coefficient of variation (CV)0.90444585
Kurtosis1.664419
Mean571.47368
Median Absolute Deviation (MAD)364
Skewness1.2890837
Sum21716
Variance267151.5
MonotonicityNot monotonic
2023-12-12T21:33:32.170921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
80 2
 
5.3%
72 1
 
2.6%
1783 1
 
2.6%
2214 1
 
2.6%
900 1
 
2.6%
127 1
 
2.6%
670 1
 
2.6%
859 1
 
2.6%
1161 1
 
2.6%
102 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
50 1
2.6%
66 1
2.6%
72 1
2.6%
80 2
5.3%
84 1
2.6%
90 1
2.6%
102 1
2.6%
117 1
2.6%
127 1
2.6%
168 1
2.6%
ValueCountFrequency (%)
2214 1
2.6%
1783 1
2.6%
1304 1
2.6%
1292 1
2.6%
1231 1
2.6%
1161 1
2.6%
1040 1
2.6%
900 1
2.6%
885 1
2.6%
875 1
2.6%

설치연도
Real number (ℝ)

Distinct11
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.0526
Minimum2013
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T21:33:32.320536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2014
Q12017
median2019.5
Q32021
95-th percentile2023
Maximum2023
Range10
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.8753131
Coefficient of variation (CV)0.0014240902
Kurtosis-0.82592222
Mean2019.0526
Median Absolute Deviation (MAD)2.5
Skewness-0.40840581
Sum76724
Variance8.2674253
MonotonicityIncreasing
2023-12-12T21:33:32.468815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2021 6
15.8%
2019 5
13.2%
2020 5
13.2%
2023 5
13.2%
2017 4
10.5%
2015 3
7.9%
2022 3
7.9%
2014 2
 
5.3%
2016 2
 
5.3%
2018 2
 
5.3%
ValueCountFrequency (%)
2013 1
 
2.6%
2014 2
 
5.3%
2015 3
7.9%
2016 2
 
5.3%
2017 4
10.5%
2018 2
 
5.3%
2019 5
13.2%
2020 5
13.2%
2021 6
15.8%
2022 3
7.9%
ValueCountFrequency (%)
2023 5
13.2%
2022 3
7.9%
2021 6
15.8%
2020 5
13.2%
2019 5
13.2%
2018 2
 
5.3%
2017 4
10.5%
2016 2
 
5.3%
2015 3
7.9%
2014 2
 
5.3%

설치구분
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
민간
25 
공공
13 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row민간
2nd row공공
3rd row공공
4th row공공
5th row공공

Common Values

ValueCountFrequency (%)
민간 25
65.8%
공공 13
34.2%

Length

2023-12-12T21:33:32.655505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:33:32.795441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간 25
65.8%
공공 13
34.2%

사용용도
Categorical

IMBALANCE 

Distinct5
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size436.0 B
조경
30 
조경+화장실
4 
조경+청소
 
2
조경+화장실+청소
 
1
화장실
 
1

Length

Max length9
Median length2
Mean length2.7894737
Min length2

Unique

Unique2 ?
Unique (%)5.3%

Sample

1st row조경
2nd row조경+청소
3rd row조경+화장실
4th row조경
5th row조경+화장실

Common Values

ValueCountFrequency (%)
조경 30
78.9%
조경+화장실 4
 
10.5%
조경+청소 2
 
5.3%
조경+화장실+청소 1
 
2.6%
화장실 1
 
2.6%

Length

2023-12-12T21:33:32.932642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:33:33.066200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조경 30
78.9%
조경+화장실 4
 
10.5%
조경+청소 2
 
5.3%
조경+화장실+청소 1
 
2.6%
화장실 1
 
2.6%

전화번호
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing12
Missing (%)31.6%
Memory size436.0 B
2023-12-12T21:33:33.302763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.153846
Min length11

Characters and Unicode

Total characters316
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row031-400-3512
2nd row031-8020-0794
3rd row031-240-2709
4th row031-8007-3463
5th row031-228-3698
ValueCountFrequency (%)
031-8020-0794 1
 
3.8%
031-240-2709 1
 
3.8%
031-202-4700 1
 
3.8%
031-222-0856 1
 
3.8%
031-8008-5008 1
 
3.8%
031-228-5859 1
 
3.8%
031-679-1136 1
 
3.8%
031-210-1900 1
 
3.8%
031-5174-6004 1
 
3.8%
031-211-1137 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T21:33:33.754307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 59
18.7%
1 52
16.5%
- 52
16.5%
3 39
12.3%
2 32
10.1%
8 16
 
5.1%
9 15
 
4.7%
4 15
 
4.7%
5 14
 
4.4%
7 11
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 264
83.5%
Dash Punctuation 52
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 59
22.3%
1 52
19.7%
3 39
14.8%
2 32
12.1%
8 16
 
6.1%
9 15
 
5.7%
4 15
 
5.7%
5 14
 
5.3%
7 11
 
4.2%
6 11
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 316
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 59
18.7%
1 52
16.5%
- 52
16.5%
3 39
12.3%
2 32
10.1%
8 16
 
5.1%
9 15
 
4.7%
4 15
 
4.7%
5 14
 
4.4%
7 11
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 316
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 59
18.7%
1 52
16.5%
- 52
16.5%
3 39
12.3%
2 32
10.1%
8 16
 
5.1%
9 15
 
4.7%
4 15
 
4.7%
5 14
 
4.4%
7 11
 
3.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
Minimum2023-08-02 00:00:00
Maximum2023-08-02 00:00:00
2023-12-12T21:33:33.913213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:34.041082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T21:33:26.457943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:23.883991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:24.620956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:25.196967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:25.865396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:26.593263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:24.025276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:24.748067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:25.330491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:25.987139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:26.719335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:24.159844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:24.872533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:25.455600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:26.109150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:26.862290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:24.312640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:25.007075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:25.599015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:26.223612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:27.009737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:24.445509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:25.103742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:25.721163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:33:26.352716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:33:34.147612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명소재지도로명주소소재지지번주소위도경도집수면적(제곱미터)용량(제곱미터)설치연도설치구분사용용도전화번호
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0000.9580.9731.0001.0001.0001.000
위도1.0001.0001.0001.0000.8260.3020.4420.8820.5570.4571.000
경도1.0001.0001.0000.8261.0000.1660.4390.6950.5950.6001.000
집수면적(제곱미터)1.0001.0000.9580.3020.1661.0000.9540.0000.1980.0001.000
용량(제곱미터)1.0001.0000.9730.4420.4390.9541.0000.0000.6290.0001.000
설치연도1.0001.0001.0000.8820.6950.0000.0001.0000.3700.6761.000
설치구분1.0001.0001.0000.5570.5950.1980.6290.3701.0000.3361.000
사용용도1.0001.0001.0000.4570.6000.0000.0000.6760.3361.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-12T21:33:34.312557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용용도설치구분
사용용도1.0000.389
설치구분0.3891.000
2023-12-12T21:33:34.440202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도집수면적(제곱미터)용량(제곱미터)설치연도설치구분사용용도
위도1.0000.021-0.184-0.179-0.2910.3720.171
경도0.0211.000-0.0590.1000.2960.3990.256
집수면적(제곱미터)-0.184-0.0591.0000.7710.4580.0000.000
용량(제곱미터)-0.1790.1000.7711.0000.3440.4310.000
설치연도-0.2910.2960.4580.3441.0000.0000.246
설치구분0.3720.3990.0000.4310.0001.0000.389
사용용도0.1710.2560.0000.0000.2460.3891.000

Missing values

2023-12-12T21:33:27.192688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:33:27.482654image/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.
2023-12-12T21:33:27.638494image/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

시도명시군명시설명소재지도로명주소소재지지번주소위도경도집수면적(제곱미터)용량(제곱미터)설치연도설치구분사용용도전화번호데이터기준일자
0경기도수원시한국농수산식품유통공사 농식품유통교육원경기도 수원시 권선구 당진로 43-33경기도 수원시 권선구 당수동 148-137.293112126.9400671352722013민간조경031-400-35122023-08-02
1경기도수원시경인지방우정청경기도 수원시 권선구 호매실로 22-55경기도 수원시 권선구 탑동 90937.258277126.9700968362212014공공조경+청소031-8020-07942023-08-02
2경기도수원시국민체육진흥센터(종합운동장내)경기도 수원시 장안구 경수대로 893경기도 수원시 권선구 조원동 77537.300218127.0097112026502014공공조경+화장실031-240-27092023-08-02
3경기도수원시학교법인 경기학원 광교씨름장(광교씨름체육관)경기도 수원시 영통구 광교산로 154-42경기도 수원시 영통구 이의동 934-1137.299262127.0343041158662015공공조경031-8007-34632023-08-02
4경기도수원시수원시립아이파크미술관경기도 수원시 팔달구 정조로 833경기도 수원시 팔달구 신풍동 238-137.282792127.0157241438802015공공조경+화장실031-228-36982023-08-02
5경기도수원시광교이마트경기도 수원시 영통구 광교로 191경기도 수원시 영통구 이의동 124037.296373127.04690231836002015민간조경+화장실+청소031-328-91702023-08-02
6경기도수원시국립산림과학원 산림유전자원부경기도 수원시 권선구 온정로 39경기도 수원시 권선구 오목천동 96737.252289126.9595831401902016공공조경031-290-10192023-08-02
7경기도수원시아이파크 시티 7단지경기도 수원시 권선구 덕영대로 1190번길 100경기도 수원시 권선구 권선동 133737.247231127.020045167028852016민간조경+청소031-267-29302023-08-02
8경기도수원시e편한세상테라스광교4블럭경기도 수원시 영통구 웰빙타운로36번길 46-23경기도 수원시 영통구 이의동 121437.30921127.04973624321802017민간조경031-214-44022023-08-02
9경기도수원시e편한세상테라스광교3블럭 웨스티힐경기도 수원시 영통구 웰빙타운로56번길 76경기도 수원시 영통구 이의동 119737.309863127.04595228822302017민간조경031-214-33092023-08-02
시도명시군명시설명소재지도로명주소소재지지번주소위도경도집수면적(제곱미터)용량(제곱미터)설치연도설치구분사용용도전화번호데이터기준일자
28경기도수원시수원하늘채더퍼스트2단지경기도 수원시 권선구 곡반정로 158경기도 수원시 권선구 곡반정동 186-237.239021127.0344972029511612021민간조경031-546-58532023-08-02
29경기도수원시수원시홍재복지타운경기도 수원시 권선구 곡반정로194번길 19경기도 수원시 권선구 곡반정동 91-237.244507127.03752114011022021공공조경<NA>2023-08-02
30경기도수원시매교역푸르지오SKVIEW경기도 수원시 팔달구 인계로 20경기도 수원시 팔달구 매교동 209-1437.267605127.0206993459617832022민간조경<NA>2023-08-02
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32경기도수원시영흥체육관<NA>경기도 수원시 영통구 영통동 36-1237.2596127.072961614842022민간조경<NA>2023-08-02
33경기도수원시경기도교육청 남부 신청사경기도 수원시 영통구 도청로 28경기도 수원시 영통구 이의동37.28856127.0531226601942023공공조경<NA>2023-08-02
34경기도수원시힐스테이트수원테라스경기도 수원시 권선구 금호로 285경기도 수원시 권선구 서둔동 45937.27637126.98243106525822023민간조경<NA>2023-08-02
35경기도수원시영흥숲푸르지오파크피엔경기도 수원시 영통구 영흥숲길 50경기도 수원시 영통구 원천동 30937.26278127.07031126186602023민간조경<NA>2023-08-02
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