Overview

Dataset statistics

Number of variables15
Number of observations113
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.1 KiB
Average record size in memory128.2 B

Variable types

Numeric7
Text3
Categorical5

Dataset

Description경상북도 경산시 무더위쉼터(실내)별 주소, 좌표, 면적, 이용인원, 운영시간 등의 항목을 제공하는 데이터입니다.
Author경상북도 경산시
URLhttps://www.data.go.kr/data/15123891/fileData.do

Alerts

주말종료시간 is highly overall correlated with 시설면적 and 5 other fieldsHigh correlation
평일시작시간 is highly overall correlated with 에어컨 and 3 other fieldsHigh correlation
주말시작시간 is highly overall correlated with 에어컨 and 3 other fieldsHigh correlation
평일종료시간 is highly overall correlated with 시설면적 and 4 other fieldsHigh correlation
연번 is highly overall correlated with 경도High correlation
시설면적 is highly overall correlated with 이용가능인원(명) and 2 other fieldsHigh correlation
이용가능인원(명) is highly overall correlated with 시설면적 and 2 other fieldsHigh correlation
에어컨 is highly overall correlated with 평일시작시간 and 3 other fieldsHigh correlation
경도 is highly overall correlated with 연번High correlation
시설유형 is highly overall correlated with 이용가능인원(명)High correlation
평일시작시간 is highly imbalanced (72.4%)Imbalance
평일종료시간 is highly imbalanced (83.9%)Imbalance
주말종료시간 is highly imbalanced (51.7%)Imbalance
연번 has unique valuesUnique
쉼터명칭 has unique valuesUnique
경도 has unique valuesUnique
위도 has unique valuesUnique
선풍기 has 4 (3.5%) zerosZeros

Reproduction

Analysis started2023-12-12 07:56:42.753593
Analysis finished2023-12-12 07:56:48.806282
Duration6.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57
Minimum1
Maximum113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:56:48.888109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.6
Q129
median57
Q385
95-th percentile107.4
Maximum113
Range112
Interquartile range (IQR)56

Descriptive statistics

Standard deviation32.76431
Coefficient of variation (CV)0.57481245
Kurtosis-1.2
Mean57
Median Absolute Deviation (MAD)28
Skewness0
Sum6441
Variance1073.5
MonotonicityStrictly increasing
2023-12-12T16:56:49.040985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
86 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
Other values (103) 103
91.2%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%

쉼터명칭
Text

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T16:56:49.314413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length7.1327434
Min length4

Characters and Unicode

Total characters806
Distinct characters133
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)100.0%

Sample

1st row하양 새마을 금고
2nd row하양읍사무소
3rd row경산제일 신협
4th row하양농업협동조합
5th row경산시 문화회관
ValueCountFrequency (%)
경로당 27
 
17.2%
마을회관 6
 
3.8%
아파트 2
 
1.3%
은호아파트 2
 
1.3%
경산경로당 1
 
0.6%
삼북주공경로당 1
 
0.6%
삼북경로당 1
 
0.6%
삼남동경로당 1
 
0.6%
하양 1
 
0.6%
중앙동주민센터 1
 
0.6%
Other values (114) 114
72.6%
2023-12-12T16:56:49.798326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 77
 
9.6%
당 77
 
9.6%
로 71
 
8.8%
44
 
5.5%
리 27
 
3.3%
동 22
 
2.7%
산 20
 
2.5%
관 20
 
2.5%
회 19
 
2.4%
2 19
 
2.4%
Other values (123) 410
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 719
89.2%
Space Separator 44
 
5.5%
Decimal Number 39
 
4.8%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 77
 
10.7%
당 77
 
10.7%
로 71
 
9.9%
리 27
 
3.8%
동 22
 
3.1%
산 20
 
2.8%
관 20
 
2.8%
회 19
 
2.6%
을 15
 
2.1%
마 15
 
2.1%
Other values (116) 356
49.5%
Decimal Number
ValueCountFrequency (%)
2 19
48.7%
1 16
41.0%
3 3
 
7.7%
4 1
 
2.6%
Space Separator
ValueCountFrequency (%)
44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 719
89.2%
Common 87
 
10.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 77
 
10.7%
당 77
 
10.7%
로 71
 
9.9%
리 27
 
3.8%
동 22
 
3.1%
산 20
 
2.8%
관 20
 
2.8%
회 19
 
2.6%
을 15
 
2.1%
마 15
 
2.1%
Other values (116) 356
49.5%
Common
ValueCountFrequency (%)
44
50.6%
2 19
21.8%
1 16
 
18.4%
3 3
 
3.4%
( 2
 
2.3%
) 2
 
2.3%
4 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 719
89.2%
ASCII 87
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 77
 
10.7%
당 77
 
10.7%
로 71
 
9.9%
리 27
 
3.8%
동 22
 
3.1%
산 20
 
2.8%
관 20
 
2.8%
회 19
 
2.6%
을 15
 
2.1%
마 15
 
2.1%
Other values (116) 356
49.5%
ASCII
ValueCountFrequency (%)
44
50.6%
2 19
21.8%
1 16
 
18.4%
3 3
 
3.4%
( 2
 
2.3%
) 2
 
2.3%
4 1
 
1.1%

도로명주소
Text

Distinct112
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T16:56:50.213320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length19.017699
Min length14

Characters and Unicode

Total characters2149
Distinct characters105
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

Unique111 ?
Unique (%)98.2%

Sample

1st row경상북도 경산시 하양읍 하양로 99
2nd row경상북도 경산시 하양읍 문화로 36
3rd row경상북도 경산시 하양읍 하양로 105-1
4th row경상북도 경산시 하양읍 대학로 1523
5th row경상북도 경산시 하양읍 문화로 24
ValueCountFrequency (%)
경상북도 113
21.9%
경산시 113
21.9%
남천면 11
 
2.1%
하양읍 11
 
2.1%
와촌면 9
 
1.7%
진량읍 7
 
1.4%
자인면 7
 
1.4%
1 6
 
1.2%
남산면 6
 
1.2%
용성면 6
 
1.2%
Other values (177) 226
43.9%
2023-12-12T16:56:50.836788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
427
19.9%
경 239
 
11.1%
산 133
 
6.2%
상 115
 
5.4%
도 114
 
5.3%
시 114
 
5.3%
북 113
 
5.3%
1 82
 
3.8%
길 77
 
3.6%
로 65
 
3.0%
Other values (95) 670
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1366
63.6%
Space Separator 427
 
19.9%
Decimal Number 331
 
15.4%
Dash Punctuation 25
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 239
17.5%
산 133
 
9.7%
상 115
 
8.4%
도 114
 
8.3%
시 114
 
8.3%
북 113
 
8.3%
길 77
 
5.6%
로 65
 
4.8%
면 39
 
2.9%
남 24
 
1.8%
Other values (83) 333
24.4%
Decimal Number
ValueCountFrequency (%)
1 82
24.8%
2 44
13.3%
3 39
11.8%
4 38
11.5%
6 29
 
8.8%
5 27
 
8.2%
8 22
 
6.6%
0 20
 
6.0%
9 18
 
5.4%
7 12
 
3.6%
Space Separator
ValueCountFrequency (%)
427
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1366
63.6%
Common 783
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 239
17.5%
산 133
 
9.7%
상 115
 
8.4%
도 114
 
8.3%
시 114
 
8.3%
북 113
 
8.3%
길 77
 
5.6%
로 65
 
4.8%
면 39
 
2.9%
남 24
 
1.8%
Other values (83) 333
24.4%
Common
ValueCountFrequency (%)
427
54.5%
1 82
 
10.5%
2 44
 
5.6%
3 39
 
5.0%
4 38
 
4.9%
6 29
 
3.7%
5 27
 
3.4%
- 25
 
3.2%
8 22
 
2.8%
0 20
 
2.6%
Other values (2) 30
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1366
63.6%
ASCII 783
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
427
54.5%
1 82
 
10.5%
2 44
 
5.6%
3 39
 
5.0%
4 38
 
4.9%
6 29
 
3.7%
5 27
 
3.4%
- 25
 
3.2%
8 22
 
2.8%
0 20
 
2.6%
Other values (2) 30
 
3.8%
Hangul
ValueCountFrequency (%)
경 239
17.5%
산 133
 
9.7%
상 115
 
8.4%
도 114
 
8.3%
시 114
 
8.3%
북 113
 
8.3%
길 77
 
5.6%
로 65
 
4.8%
면 39
 
2.9%
남 24
 
1.8%
Other values (83) 333
24.4%

지번주소
Text

Distinct112
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T16:56:51.265888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.584071
Min length15

Characters and Unicode

Total characters2213
Distinct characters84
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

Unique111 ?
Unique (%)98.2%

Sample

1st row경상북도 경산시 하양읍 금락리 113-20
2nd row경상북도 경산시 하양읍 금락리 123-10
3rd row경상북도 경산시 하양읍 금락리 18-1
4th row경상북도 경산시 하양읍 금락리 135-4
5th row경상북도 경산시 하양읍 금락리 123-8
ValueCountFrequency (%)
경상북도 113
21.9%
경산시 113
21.9%
하양읍 11
 
2.1%
남천면 11
 
2.1%
와촌면 9
 
1.7%
중방동 8
 
1.6%
자인면 7
 
1.4%
진량읍 7
 
1.4%
옥산동 6
 
1.2%
압량읍 6
 
1.2%
Other values (173) 224
43.5%
2023-12-12T16:56:51.860814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
402
18.2%
경 226
 
10.2%
산 133
 
6.0%
북 119
 
5.4%
상 118
 
5.3%
시 115
 
5.2%
도 114
 
5.2%
1 90
 
4.1%
- 81
 
3.7%
리 69
 
3.1%
Other values (74) 746
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1317
59.5%
Decimal Number 413
 
18.7%
Space Separator 402
 
18.2%
Dash Punctuation 81
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 226
17.2%
산 133
10.1%
북 119
 
9.0%
상 118
 
9.0%
시 115
 
8.7%
도 114
 
8.7%
리 69
 
5.2%
동 54
 
4.1%
면 39
 
3.0%
읍 24
 
1.8%
Other values (62) 306
23.2%
Decimal Number
ValueCountFrequency (%)
1 90
21.8%
2 57
13.8%
3 51
12.3%
7 43
10.4%
5 38
9.2%
4 34
 
8.2%
8 32
 
7.7%
6 25
 
6.1%
0 23
 
5.6%
9 20
 
4.8%
Space Separator
ValueCountFrequency (%)
402
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1317
59.5%
Common 896
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 226
17.2%
산 133
10.1%
북 119
 
9.0%
상 118
 
9.0%
시 115
 
8.7%
도 114
 
8.7%
리 69
 
5.2%
동 54
 
4.1%
면 39
 
3.0%
읍 24
 
1.8%
Other values (62) 306
23.2%
Common
ValueCountFrequency (%)
402
44.9%
1 90
 
10.0%
- 81
 
9.0%
2 57
 
6.4%
3 51
 
5.7%
7 43
 
4.8%
5 38
 
4.2%
4 34
 
3.8%
8 32
 
3.6%
6 25
 
2.8%
Other values (2) 43
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1317
59.5%
ASCII 896
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
402
44.9%
1 90
 
10.0%
- 81
 
9.0%
2 57
 
6.4%
3 51
 
5.7%
7 43
 
4.8%
5 38
 
4.2%
4 34
 
3.8%
8 32
 
3.6%
6 25
 
2.8%
Other values (2) 43
 
4.8%
Hangul
ValueCountFrequency (%)
경 226
17.2%
산 133
10.1%
북 119
 
9.0%
상 118
 
9.0%
시 115
 
8.7%
도 114
 
8.7%
리 69
 
5.2%
동 54
 
4.1%
면 39
 
3.0%
읍 24
 
1.8%
Other values (62) 306
23.2%

시설유형
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
노인시설
72 
마을회관
13 
면동사무소
8 
금융기관
 
7
주민센터
 
5
Other values (3)
8 

Length

Max length5
Median length4
Mean length3.9823009
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row금융기관
2nd row면동사무소
3rd row금융기관
4th row금융기관
5th row기타

Common Values

ValueCountFrequency (%)
노인시설 72
63.7%
마을회관 13
 
11.5%
면동사무소 8
 
7.1%
금융기관 7
 
6.2%
주민센터 5
 
4.4%
기타 4
 
3.5%
복지회관 2
 
1.8%
보건소 2
 
1.8%

Length

2023-12-12T16:56:51.998209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:52.135885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인시설 72
63.7%
마을회관 13
 
11.5%
면동사무소 8
 
7.1%
금융기관 7
 
6.2%
주민센터 5
 
4.4%
기타 4
 
3.5%
복지회관 2
 
1.8%
보건소 2
 
1.8%

시설면적
Real number (ℝ)

HIGH CORRELATION 

Distinct79
Distinct (%)69.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean250.25071
Minimum20
Maximum4343
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:56:52.326424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile50
Q194
median120
Q3171
95-th percentile1155.6
Maximum4343
Range4323
Interquartile range (IQR)77

Descriptive statistics

Standard deviation530.65506
Coefficient of variation (CV)2.1204938
Kurtosis34.422525
Mean250.25071
Median Absolute Deviation (MAD)39
Skewness5.4003915
Sum28278.33
Variance281594.8
MonotonicityNot monotonic
2023-12-12T16:56:52.479501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120.0 10
 
8.8%
200.0 5
 
4.4%
80.0 4
 
3.5%
63.0 3
 
2.7%
52.0 3
 
2.7%
100.0 3
 
2.7%
40.0 3
 
2.7%
99.0 3
 
2.7%
196.0 2
 
1.8%
60.0 2
 
1.8%
Other values (69) 75
66.4%
ValueCountFrequency (%)
20.0 1
 
0.9%
40.0 3
2.7%
45.0 1
 
0.9%
50.0 2
1.8%
52.0 3
2.7%
60.0 2
1.8%
61.84 1
 
0.9%
63.0 3
2.7%
70.0 1
 
0.9%
80.0 4
3.5%
ValueCountFrequency (%)
4343.0 1
0.9%
2324.5 1
0.9%
1858.0 1
0.9%
1726.0 1
0.9%
1639.0 1
0.9%
1203.0 1
0.9%
1124.0 1
0.9%
550.0 1
0.9%
425.0 1
0.9%
372.0 1
0.9%

이용가능인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)27.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.522124
Minimum6
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:56:52.619457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile13.8
Q125
median30
Q350
95-th percentile100
Maximum500
Range494
Interquartile range (IQR)25

Descriptive statistics

Standard deviation64.578731
Coefficient of variation (CV)1.418623
Kurtosis43.176976
Mean45.522124
Median Absolute Deviation (MAD)11
Skewness6.3448325
Sum5144
Variance4170.4125
MonotonicityNot monotonic
2023-12-12T16:56:52.757154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
30 25
22.1%
50 23
20.4%
20 9
 
8.0%
15 6
 
5.3%
100 6
 
5.3%
25 4
 
3.5%
40 4
 
3.5%
19 3
 
2.7%
12 3
 
2.7%
42 2
 
1.8%
Other values (21) 28
24.8%
ValueCountFrequency (%)
6 1
 
0.9%
10 2
 
1.8%
12 3
 
2.7%
15 6
5.3%
18 2
 
1.8%
19 3
 
2.7%
20 9
8.0%
23 1
 
0.9%
25 4
3.5%
27 1
 
0.9%
ValueCountFrequency (%)
500 2
 
1.8%
100 6
 
5.3%
96 1
 
0.9%
60 1
 
0.9%
51 2
 
1.8%
50 23
20.4%
49 2
 
1.8%
48 1
 
0.9%
44 1
 
0.9%
43 1
 
0.9%

평일시작시간
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
오전9시
101 
오전10시
 
4
오후2시
 
3
오후1시
 
3
오전8시
 
1

Length

Max length5
Median length4
Mean length4.0442478
Min length4

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st row오전9시
2nd row오전9시
3rd row오전9시
4th row오전9시
5th row오전9시

Common Values

ValueCountFrequency (%)
오전9시 101
89.4%
오전10시 4
 
3.5%
오후2시 3
 
2.7%
오후1시 3
 
2.7%
오전8시 1
 
0.9%
오전11시 1
 
0.9%

Length

2023-12-12T16:56:52.905781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:53.012383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
오전9시 101
89.4%
오전10시 4
 
3.5%
오후2시 3
 
2.7%
오후1시 3
 
2.7%
오전8시 1
 
0.9%
오전11시 1
 
0.9%

평일종료시간
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
오후6시
108 
오후5시반
 
3
오후10시
 
1
오후5시
 
1

Length

Max length5
Median length4
Mean length4.0353982
Min length4

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st row오후6시
2nd row오후6시
3rd row오후6시
4th row오후6시
5th row오후6시

Common Values

ValueCountFrequency (%)
오후6시 108
95.6%
오후5시반 3
 
2.7%
오후10시 1
 
0.9%
오후5시 1
 
0.9%

Length

2023-12-12T16:56:53.129615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:53.236159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
오후6시 108
95.6%
오후5시반 3
 
2.7%
오후10시 1
 
0.9%
오후5시 1
 
0.9%

주말시작시간
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
오전9시
67 
미운영
34 
오전10시
 
4
오후2시
 
3
오후1시
 
3
Other values (2)
 
2

Length

Max length5
Median length4
Mean length3.7433628
Min length3

Unique

Unique2 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
오전9시 67
59.3%
미운영 34
30.1%
오전10시 4
 
3.5%
오후2시 3
 
2.7%
오후1시 3
 
2.7%
오전8시 1
 
0.9%
오전11시 1
 
0.9%

Length

2023-12-12T16:56:53.374606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:53.514366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
오전9시 67
59.3%
미운영 34
30.1%
오전10시 4
 
3.5%
오후2시 3
 
2.7%
오후1시 3
 
2.7%
오전8시 1
 
0.9%
오전11시 1
 
0.9%

주말종료시간
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
오후6시
73 
미운영
34 
오후5시반
 
3
오후10시
 
1
오후8시
 
1

Length

Max length5
Median length4
Mean length3.7345133
Min length3

Unique

Unique3 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
오후6시 73
64.6%
미운영 34
30.1%
오후5시반 3
 
2.7%
오후10시 1
 
0.9%
오후8시 1
 
0.9%
오후5시 1
 
0.9%

Length

2023-12-12T16:56:53.681595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:53.835570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
오후6시 73
64.6%
미운영 34
30.1%
오후5시반 3
 
2.7%
오후10시 1
 
0.9%
오후8시 1
 
0.9%
오후5시 1
 
0.9%

선풍기
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3982301
Minimum0
Maximum12
Zeros4
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:56:53.947634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q35
95-th percentile10
Maximum12
Range12
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.60679
Coefficient of variation (CV)0.76710226
Kurtosis2.3150951
Mean3.3982301
Median Absolute Deviation (MAD)1
Skewness1.5909859
Sum384
Variance6.795354
MonotonicityNot monotonic
2023-12-12T16:56:54.086833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 36
31.9%
3 23
20.4%
1 15
13.3%
5 13
 
11.5%
4 6
 
5.3%
10 5
 
4.4%
0 4
 
3.5%
6 4
 
3.5%
12 2
 
1.8%
8 2
 
1.8%
Other values (2) 3
 
2.7%
ValueCountFrequency (%)
0 4
 
3.5%
1 15
13.3%
2 36
31.9%
3 23
20.4%
4 6
 
5.3%
5 13
 
11.5%
6 4
 
3.5%
7 2
 
1.8%
8 2
 
1.8%
10 5
 
4.4%
ValueCountFrequency (%)
12 2
 
1.8%
11 1
 
0.9%
10 5
 
4.4%
8 2
 
1.8%
7 2
 
1.8%
6 4
 
3.5%
5 13
 
11.5%
4 6
 
5.3%
3 23
20.4%
2 36
31.9%

에어컨
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7610619
Minimum1
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:56:54.228312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile6
Maximum55
Range54
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.1575655
Coefficient of variation (CV)2.2301439
Kurtosis55.833071
Mean2.7610619
Median Absolute Deviation (MAD)1
Skewness7.2570834
Sum312
Variance37.915613
MonotonicityNot monotonic
2023-12-12T16:56:54.383070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 51
45.1%
2 37
32.7%
3 13
 
11.5%
4 4
 
3.5%
6 2
 
1.8%
7 2
 
1.8%
55 1
 
0.9%
8 1
 
0.9%
5 1
 
0.9%
38 1
 
0.9%
ValueCountFrequency (%)
1 51
45.1%
2 37
32.7%
3 13
 
11.5%
4 4
 
3.5%
5 1
 
0.9%
6 2
 
1.8%
7 2
 
1.8%
8 1
 
0.9%
38 1
 
0.9%
55 1
 
0.9%
ValueCountFrequency (%)
55 1
 
0.9%
38 1
 
0.9%
8 1
 
0.9%
7 2
 
1.8%
6 2
 
1.8%
5 1
 
0.9%
4 4
 
3.5%
3 13
 
11.5%
2 37
32.7%
1 51
45.1%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.77682
Minimum128.7147
Maximum128.88218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:56:54.533396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.7147
5-th percentile128.72412
Q1128.73236
median128.75857
Q3128.82191
95-th percentile128.87084
Maximum128.88218
Range0.1674831
Interquartile range (IQR)0.0895456

Descriptive statistics

Standard deviation0.049339207
Coefficient of variation (CV)0.00038313733
Kurtosis-1.1348603
Mean128.77682
Median Absolute Deviation (MAD)0.0309855
Skewness0.53769944
Sum14551.781
Variance0.0024343574
MonotonicityNot monotonic
2023-12-12T16:56:54.670573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.818331 1
 
0.9%
128.718314 1
 
0.9%
128.72706 1
 
0.9%
128.728414 1
 
0.9%
128.732741 1
 
0.9%
128.727839 1
 
0.9%
128.741603 1
 
0.9%
128.7357 1
 
0.9%
128.7421 1
 
0.9%
128.7421345 1
 
0.9%
Other values (103) 103
91.2%
ValueCountFrequency (%)
128.714698 1
0.9%
128.718314 1
0.9%
128.719523 1
0.9%
128.7210479 1
0.9%
128.7211363 1
0.9%
128.7238 1
0.9%
128.724337 1
0.9%
128.725187 1
0.9%
128.725943 1
0.9%
128.7266089 1
0.9%
ValueCountFrequency (%)
128.8821811 1
0.9%
128.875853 1
0.9%
128.8755 1
0.9%
128.8752642 1
0.9%
128.8752245 1
0.9%
128.875182 1
0.9%
128.8679494 1
0.9%
128.8536092 1
0.9%
128.8486436 1
0.9%
128.847591 1
0.9%

위도
Real number (ℝ)

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.8369
Minimum35.724587
Maximum35.959436
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:56:54.856150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.724587
5-th percentile35.766529
Q135.806085
median35.825889
Q335.846576
95-th percentile35.941986
Maximum35.959436
Range0.234849
Interquartile range (IQR)0.040491

Descriptive statistics

Standard deviation0.049779324
Coefficient of variation (CV)0.0013890522
Kurtosis0.24637613
Mean35.8369
Median Absolute Deviation (MAD)0.019858
Skewness0.7437716
Sum4049.5697
Variance0.0024779811
MonotonicityNot monotonic
2023-12-12T16:56:55.035380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.91332 1
 
0.9%
35.823459 1
 
0.9%
35.817719 1
 
0.9%
35.815773 1
 
0.9%
35.806085 1
 
0.9%
35.820671 1
 
0.9%
35.806031 1
 
0.9%
35.8 1
 
0.9%
35.802 1
 
0.9%
35.8120176 1
 
0.9%
Other values (103) 103
91.2%
ValueCountFrequency (%)
35.724587 1
0.9%
35.7489155 1
0.9%
35.751982 1
0.9%
35.757141 1
0.9%
35.766319 1
0.9%
35.7664219 1
0.9%
35.7666 1
0.9%
35.7696039 1
0.9%
35.7739 1
0.9%
35.780811 1
0.9%
ValueCountFrequency (%)
35.959436 1
0.9%
35.958615 1
0.9%
35.9535967 1
0.9%
35.951696 1
0.9%
35.946317 1
0.9%
35.944336 1
0.9%
35.940419 1
0.9%
35.934027 1
0.9%
35.925663 1
0.9%
35.9167 1
0.9%

Interactions

2023-12-12T16:56:47.519386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.545914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.277315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.937528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.587655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.225044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.815202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:47.605395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.655005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.391103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.026092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.669037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.305265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.898037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:47.684157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.766711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.485920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.123929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.757933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.395606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.976838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:47.793577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.867526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.582983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.216319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.856392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.473610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:47.103524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:48.187026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.970954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.675174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.322470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.959528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.559587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:47.236887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:48.277545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.068563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.769474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.412507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.052579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.633365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:47.316446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:48.381501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.183893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.863543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.507650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.140337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.733447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:47.431899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:56:55.148107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설유형시설면적이용가능인원(명)평일시작시간평일종료시간주말시작시간주말종료시간선풍기에어컨경도위도
연번1.0000.4610.2360.0000.5170.2140.5530.3870.4340.0000.8810.895
시설유형0.4611.0000.6840.6500.0000.3580.5320.6500.6310.7620.4010.385
시설면적0.2360.6841.0000.8110.5820.6810.7830.7940.5790.8690.0000.200
이용가능인원(명)0.0000.6500.8111.0000.7870.4810.5750.9370.4380.6690.0000.000
평일시작시간0.5170.0000.5820.7871.0000.9841.0000.9590.0000.7180.1500.223
평일종료시간0.2140.3580.6810.4810.9841.0000.9331.0000.0000.8860.0000.147
주말시작시간0.5530.5320.7830.5751.0000.9331.0000.9180.2290.6990.2070.400
주말종료시간0.3870.6500.7940.9370.9591.0000.9181.0000.3010.9270.0000.370
선풍기0.4340.6310.5790.4380.0000.0000.2290.3011.0000.5020.3770.194
에어컨0.0000.7620.8690.6690.7180.8860.6990.9270.5021.0000.0000.000
경도0.8810.4010.0000.0000.1500.0000.2070.0000.3770.0001.0000.745
위도0.8950.3850.2000.0000.2230.1470.4000.3700.1940.0000.7451.000
2023-12-12T16:56:55.279552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주말종료시간평일시작시간시설유형주말시작시간평일종료시간
주말종료시간1.0000.7010.4290.8270.991
평일시작시간0.7011.0000.0000.9950.908
시설유형0.4290.0001.0000.3180.161
주말시작시간0.8270.9950.3181.0000.903
평일종료시간0.9910.9080.1610.9031.000
2023-12-12T16:56:55.402150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설면적이용가능인원(명)선풍기에어컨경도위도시설유형평일시작시간평일종료시간주말시작시간주말종료시간
연번1.000-0.2110.236-0.423-0.028-0.629-0.3600.2370.2970.1230.3140.209
시설면적-0.2111.0000.6940.1870.136-0.0480.2720.4520.3930.5370.3790.624
이용가능인원(명)0.2360.6941.0000.0780.158-0.2030.0690.5120.4600.4760.4570.687
선풍기-0.4230.1870.0781.0000.2140.3380.1650.3390.0000.0000.1130.149
에어컨-0.0280.1360.1580.2141.0000.1430.0670.4200.5460.5620.5580.813
경도-0.629-0.048-0.2030.3380.1431.0000.2940.2000.0650.0000.1020.000
위도-0.3600.2720.0690.1650.0670.2941.0000.1910.1140.0820.2110.199
시설유형0.2370.4520.5120.3390.4200.2000.1911.0000.0000.1610.3180.429
평일시작시간0.2970.3930.4600.0000.5460.0650.1140.0001.0000.9080.9950.701
평일종료시간0.1230.5370.4760.0000.5620.0000.0820.1610.9081.0000.9030.991
주말시작시간0.3140.3790.4570.1130.5580.1020.2110.3180.9950.9031.0000.827
주말종료시간0.2090.6240.6870.1490.8130.0000.1990.4290.7010.9910.8271.000

Missing values

2023-12-12T16:56:48.496953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:56:48.724245image/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

연번쉼터명칭도로명주소지번주소시설유형시설면적이용가능인원(명)평일시작시간평일종료시간주말시작시간주말종료시간선풍기에어컨경도위도
01하양 새마을 금고경상북도 경산시 하양읍 하양로 99경상북도 경산시 하양읍 금락리 113-20금융기관80.020오전9시오후6시미운영미운영53128.81833135.91332
12하양읍사무소경상북도 경산시 하양읍 문화로 36경상북도 경산시 하양읍 금락리 123-10면동사무소200.050오전9시오후6시미운영미운영121128.8121635.912262
23경산제일 신협경상북도 경산시 하양읍 하양로 105-1경상북도 경산시 하양읍 금락리 18-1금융기관80.020오전9시오후6시미운영미운영52128.81873535.913822
34하양농업협동조합경상북도 경산시 하양읍 대학로 1523경상북도 경산시 하양읍 금락리 135-4금융기관120.030오전9시오후6시미운영미운영102128.82079535.913727
45경산시 문화회관경상북도 경산시 하양읍 문화로 24경상북도 경산시 하양읍 금락리 123-8기타200.050오전9시오후6시미운영미운영102128.81278435.91151
56청구2차 경로당경상북도 경산시 하양읍 하양로 202-8경상북도 경산시 하양읍 동서리 740-1노인시설120.030오전9시오후6시오전9시오후6시41128.826835.9167
67은호1리 경로당경상북도 경산시 하양읍 탑소길 30-4경상북도 경산시 하양읍 은호리 101-1노인시설120.030오전9시오후6시오전9시오후6시31128.78859335.898683
78한사경로당경상북도 경산시 하양읍 한사길4길 2경상북도 경산시 하양읍 한사리 524-8노인시설120.030오전9시오후6시오전9시오후6시31128.82293535.925663
89화성경로당경상북도 경산시 하양읍 환소1길 10경상북도 경산시 하양읍 환상리 234-11노인시설120.030오전9시오후6시오전9시오후6시41128.78996335.882703
910남하2리 경로당경상북도 경산시 하양읍 사열길 21경상북도 경산시 하양읍 남하리 91-4노인시설120.030오전9시오후6시오전9시오후6시31128.777735.8907
연번쉼터명칭도로명주소지번주소시설유형시설면적이용가능인원(명)평일시작시간평일종료시간주말시작시간주말종료시간선풍기에어컨경도위도
103104임당3경로당경상북도 경산시 임당로19길 2-5경상북도 경산시 임당동 274노인시설149.050오전9시오후6시오전9시오후6시32128.74337335.845209
104105대동경로당경상북도 경산시 대동안길 1경상북도 경산시 대동 57-19노인시설111.050오전9시오후6시오전9시오후6시21128.75050235.838125
105106조영1경로당경상북도 경산시 대학로61길 24-4경상북도 경산시 조영동 272노인시설63.050오전9시오후6시오전9시오후6시21128.75392835.83987
106107조영2경로당경상북도 경산시 조영길 24경상북도 경산시 조영동 371-4노인시설114.050오전9시오후6시오전9시오후6시22128.7585735.837985
107108갑제경로당경상북도 경산시 갑제길 5경상북도 경산시 갑제동 296-10노인시설110.050오전9시오후6시오전9시오후6시23128.76334935.829572
108109대평그린빌 경로당경상북도 경산시 경안로69길 12-1경상북도 경산시 대평동 428-1노인시설185.050오전9시오후6시오전9시오후6시32128.73177635.838466
109110강산애아파트경로당경상북도 경산시 둥지로 32경상북도 경산시 조영동 572-2노인시설116.050오전9시오후6시오전9시오후6시32128.75519635.841674
110111동부동주민센터경상북도 경산시 백자로 46경상북도 경산시 사동 189-1주민센터100.0100오전9시오후6시미운영미운영03128.753735.8103
111112유곡동 경로당경상북도 경산시 유곡길 44경상북도 경산시 유곡동 71-1노인시설50.030오전9시오후6시오전9시오후6시31128.78237735.800491
112113점촌동경로당경상북도 경산시 점촌길 1경상북도 경산시 점촌동 161-3노인시설70.030오전9시오후6시오전9시오후6시32128.77194435.802829