Overview

Dataset statistics

Number of variables9
Number of observations245
Missing cells164
Missing cells (%)7.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.1 KiB
Average record size in memory75.5 B

Variable types

Numeric3
Text4
Categorical1
DateTime1

Dataset

Description경상남도 밀양시의 와이파이 현황에 대한 데이터로 설치장소명, 상세설치장소, 설치시설구분, 서비스제공사명, 설치년월, 소재지도로명주소, 소재지지번주소, 위경도 등으로 구성되어있습니다.
Author경상남도 밀양시
URLhttps://www.data.go.kr/data/15123794/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 설치시설구분High correlation
설치시설구분 is highly overall correlated with 연번High correlation
소재지도로명주소 has 53 (21.6%) missing valuesMissing
소재지지번주소 has 37 (15.1%) missing valuesMissing
위도 has 37 (15.1%) missing valuesMissing
경도 has 37 (15.1%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 19:25:23.971655
Analysis finished2024-03-14 19:25:27.849662
Duration3.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct245
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123
Minimum1
Maximum245
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-03-15T04:25:28.000243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.2
Q162
median123
Q3184
95-th percentile232.8
Maximum245
Range244
Interquartile range (IQR)122

Descriptive statistics

Standard deviation70.869599
Coefficient of variation (CV)0.5761756
Kurtosis-1.2
Mean123
Median Absolute Deviation (MAD)61
Skewness0
Sum30135
Variance5022.5
MonotonicityStrictly increasing
2024-03-15T04:25:28.461987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
155 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
Other values (235) 235
95.9%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
245 1
0.4%
244 1
0.4%
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%
236 1
0.4%

설치장소명
Text

Distinct76
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-03-15T04:25:29.264354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length13
Mean length7.7795918
Min length3

Characters and Unicode

Total characters1906
Distinct characters179
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)14.3%

Sample

1st row가곡체육공원
2nd row경상남도교육청 경남수학문화관 밀양수학체험센터
3rd row경상남도교육청 경남수학문화관 밀양수학체험센터
4th row경상남도교육청 경남수학문화관 밀양수학체험센터
5th row경상남도교육청 특수교육원
ValueCountFrequency (%)
밀양교통㈜ 36
 
11.6%
밀양시청 21
 
6.8%
밀양전통시장 13
 
4.2%
경상남도밀양교육지원청 12
 
3.9%
별관 12
 
3.9%
경상남도교육청 12
 
3.9%
밀양시립도서관 11
 
3.5%
밀양시 10
 
3.2%
특수교육원 9
 
2.9%
밀양시립박물관 9
 
2.9%
Other values (79) 166
53.4%
2024-03-15T04:25:30.535283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 182
 
9.5%
밀 176
 
9.2%
시 103
 
5.4%
84
 
4.4%
관 75
 
3.9%
교 72
 
3.8%
청 59
 
3.1%
통 51
 
2.7%
도 41
 
2.2%
장 38
 
2.0%
Other values (169) 1025
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1750
91.8%
Space Separator 84
 
4.4%
Other Symbol 37
 
1.9%
Open Punctuation 11
 
0.6%
Close Punctuation 11
 
0.6%
Decimal Number 10
 
0.5%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 182
 
10.4%
밀 176
 
10.1%
시 103
 
5.9%
관 75
 
4.3%
교 72
 
4.1%
청 59
 
3.4%
통 51
 
2.9%
도 41
 
2.3%
장 38
 
2.2%
육 38
 
2.2%
Other values (159) 915
52.3%
Decimal Number
ValueCountFrequency (%)
4 3
30.0%
5 3
30.0%
1 2
20.0%
2 1
 
10.0%
7 1
 
10.0%
Space Separator
ValueCountFrequency (%)
84
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1787
93.8%
Common 119
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 182
 
10.2%
밀 176
 
9.8%
시 103
 
5.8%
관 75
 
4.2%
교 72
 
4.0%
청 59
 
3.3%
통 51
 
2.9%
도 41
 
2.3%
장 38
 
2.1%
육 38
 
2.1%
Other values (160) 952
53.3%
Common
ValueCountFrequency (%)
84
70.6%
( 11
 
9.2%
) 11
 
9.2%
4 3
 
2.5%
. 3
 
2.5%
5 3
 
2.5%
1 2
 
1.7%
2 1
 
0.8%
7 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1750
91.8%
ASCII 119
 
6.2%
None 37
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 182
 
10.4%
밀 176
 
10.1%
시 103
 
5.9%
관 75
 
4.3%
교 72
 
4.1%
청 59
 
3.4%
통 51
 
2.9%
도 41
 
2.3%
장 38
 
2.2%
육 38
 
2.2%
Other values (159) 915
52.3%
ASCII
ValueCountFrequency (%)
84
70.6%
( 11
 
9.2%
) 11
 
9.2%
4 3
 
2.5%
. 3
 
2.5%
5 3
 
2.5%
1 2
 
1.7%
2 1
 
0.8%
7 1
 
0.8%
None
ValueCountFrequency (%)
㈜ 37
100.0%

설치장소상세
Text

Distinct147
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-03-15T04:25:31.757532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length6.5714286
Min length2

Characters and Unicode

Total characters1610
Distinct characters214
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)56.3%

Sample

1st row골프장앞kt전주
2nd row1층 계단
3rd row2층 교육자료실
4th row3층 홍하정마당
5th row수련관 1층 운영관리실
ValueCountFrequency (%)
내부 55
 
12.3%
순환배차 37
 
8.3%
1층 27
 
6.0%
2층 22
 
4.9%
앞 19
 
4.2%
3층 11
 
2.5%
cctv 10
 
2.2%
본관 8
 
1.8%
벽면 7
 
1.6%
지상1층 7
 
1.6%
Other values (174) 245
54.7%
2024-03-15T04:25:33.492048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
204
 
12.7%
층 91
 
5.7%
1 60
 
3.7%
내 59
 
3.7%
부 57
 
3.5%
실 47
 
2.9%
관 43
 
2.7%
2 39
 
2.4%
환 38
 
2.4%
차 38
 
2.4%
Other values (204) 934
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1188
73.8%
Space Separator 204
 
12.7%
Decimal Number 133
 
8.3%
Lowercase Letter 50
 
3.1%
Uppercase Letter 24
 
1.5%
Dash Punctuation 9
 
0.6%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 91
 
7.7%
내 59
 
5.0%
부 57
 
4.8%
실 47
 
4.0%
관 43
 
3.6%
환 38
 
3.2%
차 38
 
3.2%
앞 38
 
3.2%
배 37
 
3.1%
순 37
 
3.1%
Other values (184) 703
59.2%
Decimal Number
ValueCountFrequency (%)
1 60
45.1%
2 39
29.3%
3 18
 
13.5%
5 6
 
4.5%
4 5
 
3.8%
0 3
 
2.3%
6 1
 
0.8%
8 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
c 24
48.0%
t 13
26.0%
v 12
24.0%
k 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
F 16
66.7%
C 4
 
16.7%
V 2
 
8.3%
T 2
 
8.3%
Space Separator
ValueCountFrequency (%)
204
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1188
73.8%
Common 348
 
21.6%
Latin 74
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 91
 
7.7%
내 59
 
5.0%
부 57
 
4.8%
실 47
 
4.0%
관 43
 
3.6%
환 38
 
3.2%
차 38
 
3.2%
앞 38
 
3.2%
배 37
 
3.1%
순 37
 
3.1%
Other values (184) 703
59.2%
Common
ValueCountFrequency (%)
204
58.6%
1 60
 
17.2%
2 39
 
11.2%
3 18
 
5.2%
- 9
 
2.6%
5 6
 
1.7%
4 5
 
1.4%
0 3
 
0.9%
6 1
 
0.3%
) 1
 
0.3%
Other values (2) 2
 
0.6%
Latin
ValueCountFrequency (%)
c 24
32.4%
F 16
21.6%
t 13
17.6%
v 12
16.2%
C 4
 
5.4%
V 2
 
2.7%
T 2
 
2.7%
k 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1188
73.8%
ASCII 422
 
26.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
204
48.3%
1 60
 
14.2%
2 39
 
9.2%
c 24
 
5.7%
3 18
 
4.3%
F 16
 
3.8%
t 13
 
3.1%
v 12
 
2.8%
- 9
 
2.1%
5 6
 
1.4%
Other values (10) 21
 
5.0%
Hangul
ValueCountFrequency (%)
층 91
 
7.7%
내 59
 
5.0%
부 57
 
4.8%
실 47
 
4.0%
관 43
 
3.6%
환 38
 
3.2%
차 38
 
3.2%
앞 38
 
3.2%
배 37
 
3.1%
순 37
 
3.1%
Other values (184) 703
59.2%

설치시설구분
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
지역문화시설
50 
관공서
46 
서민·복지시설
44 
교통시설
41 
관광
20 
Other values (3)
44 

Length

Max length7
Median length4
Mean length4.4571429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서민·복지시설
2nd row교육시설
3rd row교육시설
4th row교육시설
5th row교육시설

Common Values

ValueCountFrequency (%)
지역문화시설 50
20.4%
관공서 46
18.8%
서민·복지시설 44
18.0%
교통시설 41
16.7%
관광 20
 
8.2%
교육시설 17
 
6.9%
기타 17
 
6.9%
편의시설 10
 
4.1%

Length

2024-03-15T04:25:33.909795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:25:34.254477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역문화시설 50
20.4%
관공서 46
18.8%
서민·복지시설 44
18.0%
교통시설 41
16.7%
관광 20
 
8.2%
교육시설 17
 
6.9%
기타 17
 
6.9%
편의시설 10
 
4.1%

소재지도로명주소
Text

MISSING 

Distinct52
Distinct (%)27.1%
Missing53
Missing (%)21.6%
Memory size2.0 KiB
2024-03-15T04:25:35.149893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length18.479167
Min length15

Characters and Unicode

Total characters3548
Distinct characters85
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

Unique19 ?
Unique (%)9.9%

Sample

1st row경상남도 밀양시 가곡13길 24
2nd row경상남도 밀양시 가곡13길 24
3rd row경상남도 밀양시 가곡13길 24
4th row경상남도 밀양시 하남읍 대사길 77
5th row경상남도 밀양시 하남읍 대사길 77
ValueCountFrequency (%)
경상남도 192
23.4%
밀양시 192
23.4%
중앙로 36
 
4.4%
밀양대로 33
 
4.0%
2047 21
 
2.6%
상남면 18
 
2.2%
265 17
 
2.1%
밀양대공원로 15
 
1.8%
상설시장1길 13
 
1.6%
11 13
 
1.6%
Other values (92) 272
33.1%
2024-03-15T04:25:36.239545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
630
17.8%
밀 242
 
6.8%
양 241
 
6.8%
상 239
 
6.7%
남 230
 
6.5%
시 215
 
6.1%
경 192
 
5.4%
도 192
 
5.4%
로 132
 
3.7%
1 132
 
3.7%
Other values (75) 1103
31.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2271
64.0%
Space Separator 630
 
17.8%
Decimal Number 614
 
17.3%
Dash Punctuation 33
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
밀 242
10.7%
양 241
10.6%
상 239
10.5%
남 230
10.1%
시 215
9.5%
경 192
8.5%
도 192
8.5%
로 132
 
5.8%
길 63
 
2.8%
대 59
 
2.6%
Other values (63) 466
20.5%
Decimal Number
ValueCountFrequency (%)
1 132
21.5%
2 121
19.7%
7 62
10.1%
6 59
9.6%
0 56
9.1%
5 49
 
8.0%
4 48
 
7.8%
8 36
 
5.9%
3 31
 
5.0%
9 20
 
3.3%
Space Separator
ValueCountFrequency (%)
630
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2271
64.0%
Common 1277
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
밀 242
10.7%
양 241
10.6%
상 239
10.5%
남 230
10.1%
시 215
9.5%
경 192
8.5%
도 192
8.5%
로 132
 
5.8%
길 63
 
2.8%
대 59
 
2.6%
Other values (63) 466
20.5%
Common
ValueCountFrequency (%)
630
49.3%
1 132
 
10.3%
2 121
 
9.5%
7 62
 
4.9%
6 59
 
4.6%
0 56
 
4.4%
5 49
 
3.8%
4 48
 
3.8%
8 36
 
2.8%
- 33
 
2.6%
Other values (2) 51
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2271
64.0%
ASCII 1277
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
630
49.3%
1 132
 
10.3%
2 121
 
9.5%
7 62
 
4.9%
6 59
 
4.6%
0 56
 
4.4%
5 49
 
3.8%
4 48
 
3.8%
8 36
 
2.8%
- 33
 
2.6%
Other values (2) 51
 
4.0%
Hangul
ValueCountFrequency (%)
밀 242
10.7%
양 241
10.6%
상 239
10.5%
남 230
10.1%
시 215
9.5%
경 192
8.5%
도 192
8.5%
로 132
 
5.8%
길 63
 
2.8%
대 59
 
2.6%
Other values (63) 466
20.5%

소재지지번주소
Text

MISSING 

Distinct64
Distinct (%)30.8%
Missing37
Missing (%)15.1%
Memory size2.0 KiB
2024-03-15T04:25:37.223588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length18.798077
Min length15

Characters and Unicode

Total characters3910
Distinct characters74
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

Unique28 ?
Unique (%)13.5%

Sample

1st row경상남도 밀양시 가곡동 529-2
2nd row경상남도 밀양시 가곡동 744-6
3rd row경상남도 밀양시 가곡동 744-6
4th row경상남도 밀양시 가곡동 744-6
5th row경상남도 밀양시 하남읍 대사리 242-2
ValueCountFrequency (%)
경상남도 208
23.1%
밀양시 208
23.1%
삼문동 56
 
6.2%
교동 43
 
4.8%
내일동 26
 
2.9%
999-1 21
 
2.3%
하남읍 19
 
2.1%
상남면 18
 
2.0%
184-11 17
 
1.9%
583-1 13
 
1.4%
Other values (97) 273
30.3%
2024-03-15T04:25:38.695799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
706
18.1%
남 246
 
6.3%
상 227
 
5.8%
양 210
 
5.4%
경 208
 
5.3%
도 208
 
5.3%
밀 208
 
5.3%
시 208
 
5.3%
1 204
 
5.2%
- 165
 
4.2%
Other values (64) 1320
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2238
57.2%
Decimal Number 801
 
20.5%
Space Separator 706
 
18.1%
Dash Punctuation 165
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 246
11.0%
상 227
10.1%
양 210
9.4%
경 208
9.3%
도 208
9.3%
밀 208
9.3%
시 208
9.3%
동 146
 
6.5%
리 64
 
2.9%
삼 61
 
2.7%
Other values (52) 452
20.2%
Decimal Number
ValueCountFrequency (%)
1 204
25.5%
9 122
15.2%
4 103
12.9%
2 72
 
9.0%
8 71
 
8.9%
3 71
 
8.9%
5 50
 
6.2%
0 38
 
4.7%
7 37
 
4.6%
6 33
 
4.1%
Space Separator
ValueCountFrequency (%)
706
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 165
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2238
57.2%
Common 1672
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 246
11.0%
상 227
10.1%
양 210
9.4%
경 208
9.3%
도 208
9.3%
밀 208
9.3%
시 208
9.3%
동 146
 
6.5%
리 64
 
2.9%
삼 61
 
2.7%
Other values (52) 452
20.2%
Common
ValueCountFrequency (%)
706
42.2%
1 204
 
12.2%
- 165
 
9.9%
9 122
 
7.3%
4 103
 
6.2%
2 72
 
4.3%
8 71
 
4.2%
3 71
 
4.2%
5 50
 
3.0%
0 38
 
2.3%
Other values (2) 70
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2238
57.2%
ASCII 1672
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
706
42.2%
1 204
 
12.2%
- 165
 
9.9%
9 122
 
7.3%
4 103
 
6.2%
2 72
 
4.3%
8 71
 
4.2%
3 71
 
4.2%
5 50
 
3.0%
0 38
 
2.3%
Other values (2) 70
 
4.2%
Hangul
ValueCountFrequency (%)
남 246
11.0%
상 227
10.1%
양 210
9.4%
경 208
9.3%
도 208
9.3%
밀 208
9.3%
시 208
9.3%
동 146
 
6.5%
리 64
 
2.9%
삼 61
 
2.7%
Other values (52) 452
20.2%

위도
Real number (ℝ)

MISSING 

Distinct64
Distinct (%)30.8%
Missing37
Missing (%)15.1%
Infinite0
Infinite (%)0.0%
Mean35.480904
Minimum35.350572
Maximum35.585677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-03-15T04:25:39.310011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.350572
5-th percentile35.392863
Q135.479806
median35.488385
Q335.502965
95-th percentile35.510872
Maximum35.585677
Range0.23510535
Interquartile range (IQR)0.02315933

Descriptive statistics

Standard deviation0.03723369
Coefficient of variation (CV)0.0010494008
Kurtosis3.5022292
Mean35.480904
Median Absolute Deviation (MAD)0.01106866
Skewness-1.6370457
Sum7380.0279
Variance0.0013863477
MonotonicityNot monotonic
2024-03-15T04:25:39.739406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.50344829 21
 
8.6%
35.4867908 17
 
6.9%
35.49305872 13
 
5.3%
35.46637143 12
 
4.9%
35.48838473 11
 
4.5%
35.39286252 9
 
3.7%
35.50296509 8
 
3.3%
35.48720887 7
 
2.9%
35.44692822 6
 
2.4%
35.48567011 6
 
2.4%
Other values (54) 98
40.0%
(Missing) 37
 
15.1%
ValueCountFrequency (%)
35.35057192 1
 
0.4%
35.3573252 3
 
1.2%
35.37168226 1
 
0.4%
35.37651224 3
 
1.2%
35.38265913 2
 
0.8%
35.39286252 9
3.7%
35.42357572 1
 
0.4%
35.44692822 6
2.4%
35.44809957 1
 
0.4%
35.45294269 1
 
0.4%
ValueCountFrequency (%)
35.58567727 1
 
0.4%
35.580304 1
 
0.4%
35.5559805 1
 
0.4%
35.53257302 1
 
0.4%
35.53226072 2
0.8%
35.51949392 3
1.2%
35.51252345 2
0.8%
35.50780521 1
 
0.4%
35.50715701 2
0.8%
35.50660573 1
 
0.4%

경도
Real number (ℝ)

MISSING 

Distinct64
Distinct (%)30.8%
Missing37
Missing (%)15.1%
Infinite0
Infinite (%)0.0%
Mean128.75723
Minimum128.60368
Maximum128.99522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-03-15T04:25:40.169301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.60368
5-th percentile128.71208
Q1128.74742
median128.75485
Q3128.75895
95-th percentile128.79438
Maximum128.99522
Range0.3915363
Interquartile range (IQR)0.0115315

Descriptive statistics

Standard deviation0.046589212
Coefficient of variation (CV)0.00036183764
Kurtosis12.046714
Mean128.75723
Median Absolute Deviation (MAD)0.0058307
Skewness2.4806862
Sum26781.503
Variance0.0021705547
MonotonicityNot monotonic
2024-03-15T04:25:40.636161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.7474192 21
 
8.6%
128.7548535 17
 
6.9%
128.7525543 13
 
5.3%
128.7622276 12
 
4.9%
128.7581071 11
 
4.5%
128.7335386 9
 
3.7%
128.7593643 8
 
3.3%
128.7558685 7
 
2.9%
128.7564666 6
 
2.4%
128.7560608 6
 
2.4%
Other values (54) 98
40.0%
(Missing) 37
 
15.1%
ValueCountFrequency (%)
128.6036801 2
0.8%
128.6520376 1
 
0.4%
128.6590488 2
0.8%
128.688264 2
0.8%
128.7034103 1
 
0.4%
128.7059033 1
 
0.4%
128.7120799 3
1.2%
128.7123488 1
 
0.4%
128.7160037 2
0.8%
128.7260418 3
1.2%
ValueCountFrequency (%)
128.9952164 1
 
0.4%
128.9843986 1
 
0.4%
128.9590442 2
0.8%
128.9433465 1
 
0.4%
128.9302548 2
0.8%
128.8892221 1
 
0.4%
128.8807437 1
 
0.4%
128.8462487 1
 
0.4%
128.7999268 1
 
0.4%
128.7840911 3
1.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2024-01-22 00:00:00
Maximum2024-01-22 00:00:00
2024-03-15T04:25:41.000594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:25:41.302871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T04:25:26.417299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:25:24.941845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:25:25.690905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:25:26.601386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:25:25.184259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:25:25.944067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:25:26.762538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:25:25.424292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:25:26.166601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T04:25:41.516641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치장소명설치시설구분소재지도로명주소소재지지번주소위도경도
연번1.0000.9900.7930.9900.9910.7690.605
설치장소명0.9901.0000.9991.0001.0001.0001.000
설치시설구분0.7930.9991.0000.9991.0000.6390.484
소재지도로명주소0.9901.0000.9991.0001.0001.0001.000
소재지지번주소0.9911.0001.0001.0001.0001.0001.000
위도0.7691.0000.6391.0001.0001.0000.847
경도0.6051.0000.4841.0001.0000.8471.000
2024-03-15T04:25:41.799248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도설치시설구분
연번1.0000.206-0.0600.537
위도0.2061.000-0.1500.379
경도-0.060-0.1501.0000.262
설치시설구분0.5370.3790.2621.000

Missing values

2024-03-15T04:25:27.035810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:25:27.379719image/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.
2024-03-15T04:25:27.625051image/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

연번설치장소명설치장소상세설치시설구분소재지도로명주소소재지지번주소위도경도데이터기준일
01가곡체육공원골프장앞kt전주서민·복지시설<NA>경상남도 밀양시 가곡동 529-235.471435128.7673582024-01-22
12경상남도교육청 경남수학문화관 밀양수학체험센터1층 계단교육시설경상남도 밀양시 가곡13길 24경상남도 밀양시 가곡동 744-635.477316128.7625562024-01-22
23경상남도교육청 경남수학문화관 밀양수학체험센터2층 교육자료실교육시설경상남도 밀양시 가곡13길 24경상남도 밀양시 가곡동 744-635.477316128.7625562024-01-22
34경상남도교육청 경남수학문화관 밀양수학체험센터3층 홍하정마당교육시설경상남도 밀양시 가곡13길 24경상남도 밀양시 가곡동 744-635.477316128.7625562024-01-22
45경상남도교육청 특수교육원수련관 1층 운영관리실교육시설경상남도 밀양시 하남읍 대사길 77경상남도 밀양시 하남읍 대사리 242-235.392863128.7335392024-01-22
56경상남도교육청 특수교육원수련관 1층 운영자 숙소교육시설경상남도 밀양시 하남읍 대사길 77경상남도 밀양시 하남읍 대사리 242-235.392863128.7335392024-01-22
67경상남도교육청 특수교육원수련관 2층 다목적강당교육시설경상남도 밀양시 하남읍 대사길 77경상남도 밀양시 하남읍 대사리 242-235.392863128.7335392024-01-22
78경상남도교육청 특수교육원본관 1층 상상누림터교육시설경상남도 밀양시 하남읍 대사길 77경상남도 밀양시 하남읍 대사리 242-235.392863128.7335392024-01-22
89경상남도교육청 특수교육원본관 1층 안전생활체험관교육시설경상남도 밀양시 하남읍 대사길 77경상남도 밀양시 하남읍 대사리 242-235.392863128.7335392024-01-22
910경상남도교육청 특수교육원본관 2층 정보실교육시설경상남도 밀양시 하남읍 대사길 77경상남도 밀양시 하남읍 대사리 242-235.392863128.7335392024-01-22
연번설치장소명설치장소상세설치시설구분소재지도로명주소소재지지번주소위도경도데이터기준일
235236밀양시 청소년 수련관내부서민·복지시설경상남도 밀양시 삼문송림길 26경상남도 밀양시 삼문동 4-1935.488385128.7581072024-01-22
236237밀양시 청소년 수련관내부서민·복지시설경상남도 밀양시 삼문송림길 26경상남도 밀양시 삼문동 4-1935.488385128.7581072024-01-22
237238밀양시 청소년 수련관내부서민·복지시설경상남도 밀양시 삼문송림길 26경상남도 밀양시 삼문동 4-1935.488385128.7581072024-01-22
238239밀양시 청소년 수련관내부서민·복지시설경상남도 밀양시 삼문송림길 26경상남도 밀양시 삼문동 4-1935.488385128.7581072024-01-22
239240밀양시 청소년 수련관내부서민·복지시설경상남도 밀양시 삼문송림길 26경상남도 밀양시 삼문동 4-1935.488385128.7581072024-01-22
240241밀양시 청소년 수련관내부서민·복지시설경상남도 밀양시 삼문송림길 26경상남도 밀양시 삼문동 4-1935.488385128.7581072024-01-22
241242밀양시 청소년 수련관내부서민·복지시설경상남도 밀양시 삼문송림길 26경상남도 밀양시 삼문동 4-1935.488385128.7581072024-01-22
242243복두레 한마당외부지역문화시설경상남도 밀양시 부북면 부북로 55-11경상남도 밀양시 부북면 운전리 72-335.512523128.7274392024-01-22
243244복두레 한마당내부지역문화시설경상남도 밀양시 부북면 부북로 55-11경상남도 밀양시 부북면 운전리 72-335.512523128.7274392024-01-22
244245수산제역사공원 홍보관내부관광<NA>경상남도 밀양시 하남읍 수산리 92735.382659128.7160042024-01-22