Overview

Dataset statistics

Number of variables14
Number of observations309
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.5 KiB
Average record size in memory114.4 B

Variable types

Numeric2
Text9
Categorical2
DateTime1

Dataset

Description경기도 성남시 판교 지역 조명시설현황에 대한 데이터로 분전함번호, 분전함이름,위치,구역,상태, 마그네트별 점등/소등시간 등의 항목을 제공합니다.
Author경기도 성남시
URLhttps://www.data.go.kr/data/3070897/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
설치구역 is highly imbalanced (91.7%)Imbalance
분전함번호 has unique valuesUnique
분전함이름 has unique valuesUnique
분전함상태 has 239 (77.3%) zerosZeros

Reproduction

Analysis started2024-03-14 20:51:02.526580
Analysis finished2024-03-14 20:51:08.278081
Duration5.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분전함번호
Real number (ℝ)

UNIQUE 

Distinct309
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean155.00647
Minimum1
Maximum311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T05:51:08.546528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.4
Q178
median155
Q3232
95-th percentile293.6
Maximum311
Range310
Interquartile range (IQR)154

Descriptive statistics

Standard deviation89.356102
Coefficient of variation (CV)0.57646691
Kurtosis-1.1993754
Mean155.00647
Median Absolute Deviation (MAD)77
Skewness0.00044154361
Sum47897
Variance7984.5129
MonotonicityStrictly increasing
2024-03-15T05:51:09.040766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
205 1
 
0.3%
212 1
 
0.3%
211 1
 
0.3%
210 1
 
0.3%
209 1
 
0.3%
208 1
 
0.3%
207 1
 
0.3%
206 1
 
0.3%
204 1
 
0.3%
Other values (299) 299
96.8%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
311 1
0.3%
308 1
0.3%
307 1
0.3%
306 1
0.3%
305 1
0.3%
304 1
0.3%
303 1
0.3%
302 1
0.3%
301 1
0.3%
300 1
0.3%

분전함이름
Text

UNIQUE 

Distinct309
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:51:10.403937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length6.6213592
Min length3

Characters and Unicode

Total characters2046
Distinct characters144
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

Unique309 ?
Unique (%)100.0%

Sample

1st row운중로11
2nd row운중로1
3rd row운중로10
4th row운중로5
5th row운중로9
ValueCountFrequency (%)
판교로 23
 
6.0%
운중천 11
 
2.9%
봇들로 9
 
2.3%
운중저 6
 
1.6%
세계로 4
 
1.0%
상시주간점등 3
 
0.8%
연성로 3
 
0.8%
운중로 3
 
0.8%
01 3
 
0.8%
대왕판교로 3
 
0.8%
Other values (308) 315
82.2%
2024-03-15T05:51:12.285739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 148
 
7.2%
1 125
 
6.1%
교 124
 
6.1%
2 102
 
5.0%
원 85
 
4.2%
공 77
 
3.8%
74
 
3.6%
판 72
 
3.5%
번 62
 
3.0%
길 62
 
3.0%
Other values (134) 1115
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1317
64.4%
Decimal Number 623
30.4%
Space Separator 74
 
3.6%
Dash Punctuation 30
 
1.5%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 148
 
11.2%
교 124
 
9.4%
원 85
 
6.5%
공 77
 
5.8%
판 72
 
5.5%
번 62
 
4.7%
길 62
 
4.7%
운 55
 
4.2%
중 41
 
3.1%
육 26
 
2.0%
Other values (120) 565
42.9%
Decimal Number
ValueCountFrequency (%)
1 125
20.1%
2 102
16.4%
5 62
10.0%
3 58
9.3%
0 57
9.1%
6 53
8.5%
4 48
 
7.7%
9 43
 
6.9%
7 38
 
6.1%
8 37
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%
Space Separator
ValueCountFrequency (%)
74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1317
64.4%
Common 727
35.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 148
 
11.2%
교 124
 
9.4%
원 85
 
6.5%
공 77
 
5.8%
판 72
 
5.5%
번 62
 
4.7%
길 62
 
4.7%
운 55
 
4.2%
중 41
 
3.1%
육 26
 
2.0%
Other values (120) 565
42.9%
Common
ValueCountFrequency (%)
1 125
17.2%
2 102
14.0%
74
10.2%
5 62
8.5%
3 58
8.0%
0 57
7.8%
6 53
7.3%
4 48
 
6.6%
9 43
 
5.9%
7 38
 
5.2%
Other values (2) 67
9.2%
Latin
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1317
64.4%
ASCII 729
35.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 148
 
11.2%
교 124
 
9.4%
원 85
 
6.5%
공 77
 
5.8%
판 72
 
5.5%
번 62
 
4.7%
길 62
 
4.7%
운 55
 
4.2%
중 41
 
3.1%
육 26
 
2.0%
Other values (120) 565
42.9%
ASCII
ValueCountFrequency (%)
1 125
17.1%
2 102
14.0%
74
10.2%
5 62
8.5%
3 58
8.0%
0 57
7.8%
6 53
7.3%
4 48
 
6.6%
9 43
 
5.9%
7 38
 
5.2%
Other values (4) 69
9.5%

설치위치
Text

Distinct204
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:51:13.834651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length16.867314
Min length4

Characters and Unicode

Total characters5212
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

Unique143 ?
Unique (%)46.3%

Sample

1st row성남시 분당구 운중동 889 공
2nd row성남시 분당구 운중동 900공
3rd row성남시 분당구 운중동 898-4공
4th row성남시 분당구 운중동 954-2공
5th row성남시 분당구 운중동 958-1공
ValueCountFrequency (%)
성남시 294
24.2%
분당구 294
24.2%
삼평동 111
 
9.1%
운중동 86
 
7.1%
판교동 52
 
4.3%
백현동 45
 
3.7%
523공 8
 
0.7%
553공 8
 
0.7%
639공 7
 
0.6%
내 7
 
0.6%
Other values (206) 304
25.0%
2024-03-15T05:51:15.298968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
907
17.4%
구 295
 
5.7%
성 294
 
5.6%
시 294
 
5.6%
분 294
 
5.6%
당 294
 
5.6%
남 294
 
5.6%
동 294
 
5.6%
- 184
 
3.5%
공 173
 
3.3%
Other values (46) 1889
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3028
58.1%
Decimal Number 1093
 
21.0%
Space Separator 907
 
17.4%
Dash Punctuation 184
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 295
9.7%
성 294
9.7%
시 294
9.7%
분 294
9.7%
당 294
9.7%
남 294
9.7%
동 294
9.7%
공 173
 
5.7%
삼 111
 
3.7%
평 111
 
3.7%
Other values (34) 574
19.0%
Decimal Number
ValueCountFrequency (%)
1 173
15.8%
5 132
12.1%
6 130
11.9%
9 117
10.7%
2 114
10.4%
3 104
9.5%
7 94
8.6%
4 93
8.5%
8 76
7.0%
0 60
 
5.5%
Space Separator
ValueCountFrequency (%)
907
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3028
58.1%
Common 2184
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 295
9.7%
성 294
9.7%
시 294
9.7%
분 294
9.7%
당 294
9.7%
남 294
9.7%
동 294
9.7%
공 173
 
5.7%
삼 111
 
3.7%
평 111
 
3.7%
Other values (34) 574
19.0%
Common
ValueCountFrequency (%)
907
41.5%
- 184
 
8.4%
1 173
 
7.9%
5 132
 
6.0%
6 130
 
6.0%
9 117
 
5.4%
2 114
 
5.2%
3 104
 
4.8%
7 94
 
4.3%
4 93
 
4.3%
Other values (2) 136
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3028
58.1%
ASCII 2184
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
907
41.5%
- 184
 
8.4%
1 173
 
7.9%
5 132
 
6.0%
6 130
 
6.0%
9 117
 
5.4%
2 114
 
5.2%
3 104
 
4.8%
7 94
 
4.3%
4 93
 
4.3%
Other values (2) 136
 
6.2%
Hangul
ValueCountFrequency (%)
구 295
9.7%
성 294
9.7%
시 294
9.7%
분 294
9.7%
당 294
9.7%
남 294
9.7%
동 294
9.7%
공 173
 
5.7%
삼 111
 
3.7%
평 111
 
3.7%
Other values (34) 574
19.0%

설치구역
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
운중로
304 
미정
 
4
세계로
 
1

Length

Max length3
Median length3
Mean length2.987055
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
운중로 304
98.4%
미정 4
 
1.3%
세계로 1
 
0.3%

Length

2024-03-15T05:51:15.618961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:51:15.944489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운중로 304
98.4%
미정 4
 
1.3%
세계로 1
 
0.3%

분전함상태
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean230.07443
Minimum0
Maximum1111
Zeros239
Zeros (%)77.3%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T05:51:16.254315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1111
Maximum1111
Range1111
Interquartile range (IQR)0

Descriptive statistics

Standard deviation449.10691
Coefficient of variation (CV)1.952007
Kurtosis0.11438894
Mean230.07443
Median Absolute Deviation (MAD)0
Skewness1.4525098
Sum71093
Variance201697.02
MonotonicityNot monotonic
2024-03-15T05:51:16.544978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 239
77.3%
1111 58
 
18.8%
1 2
 
0.6%
1100 2
 
0.6%
11 2
 
0.6%
1000 2
 
0.6%
110 2
 
0.6%
1101 1
 
0.3%
1110 1
 
0.3%
ValueCountFrequency (%)
0 239
77.3%
1 2
 
0.6%
11 2
 
0.6%
110 2
 
0.6%
1000 2
 
0.6%
1100 2
 
0.6%
1101 1
 
0.3%
1110 1
 
0.3%
1111 58
 
18.8%
ValueCountFrequency (%)
1111 58
 
18.8%
1110 1
 
0.3%
1101 1
 
0.3%
1100 2
 
0.6%
1000 2
 
0.6%
110 2
 
0.6%
11 2
 
0.6%
1 2
 
0.6%
0 239
77.3%

마그네트1점등시간
Text

Distinct70
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:51:17.329564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1545
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

Unique35 ?
Unique (%)11.3%

Sample

1st row17:27
2nd row17:27
3rd row17:27
4th row17:22
5th row17:27
ValueCountFrequency (%)
19:16 74
23.9%
19:09 32
 
10.4%
19:11 22
 
7.1%
18:28 20
 
6.5%
18:29 18
 
5.8%
18:30 13
 
4.2%
17:27 10
 
3.2%
19:25 10
 
3.2%
17:24 6
 
1.9%
17:25 6
 
1.9%
Other values (60) 98
31.7%
2024-03-15T05:51:18.498027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 437
28.3%
: 309
20.0%
9 225
14.6%
2 110
 
7.1%
8 107
 
6.9%
6 88
 
5.7%
0 80
 
5.2%
7 72
 
4.7%
5 46
 
3.0%
3 45
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1236
80.0%
Other Punctuation 309
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 437
35.4%
9 225
18.2%
2 110
 
8.9%
8 107
 
8.7%
6 88
 
7.1%
0 80
 
6.5%
7 72
 
5.8%
5 46
 
3.7%
3 45
 
3.6%
4 26
 
2.1%
Other Punctuation
ValueCountFrequency (%)
: 309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 437
28.3%
: 309
20.0%
9 225
14.6%
2 110
 
7.1%
8 107
 
6.9%
6 88
 
5.7%
0 80
 
5.2%
7 72
 
4.7%
5 46
 
3.0%
3 45
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 437
28.3%
: 309
20.0%
9 225
14.6%
2 110
 
7.1%
8 107
 
6.9%
6 88
 
5.7%
0 80
 
5.2%
7 72
 
4.7%
5 46
 
3.0%
3 45
 
2.9%

마그네트1소등시간
Text

Distinct67
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:51:19.275689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1545
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

Unique32 ?
Unique (%)10.4%

Sample

1st row07:29
2nd row07:29
3rd row07:29
4th row07:13
5th row07:29
ValueCountFrequency (%)
05:47 95
30.7%
05:51 22
 
7.1%
06:54 15
 
4.9%
06:49 13
 
4.2%
06:56 12
 
3.9%
07:27 9
 
2.9%
07:29 9
 
2.9%
06:52 9
 
2.9%
05:37 8
 
2.6%
22:00 8
 
2.6%
Other values (57) 109
35.3%
2024-03-15T05:51:20.299716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 355
23.0%
: 309
20.0%
5 236
15.3%
7 157
10.2%
4 145
9.4%
2 107
 
6.9%
6 106
 
6.9%
3 50
 
3.2%
1 41
 
2.7%
9 26
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1236
80.0%
Other Punctuation 309
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 355
28.7%
5 236
19.1%
7 157
12.7%
4 145
11.7%
2 107
 
8.7%
6 106
 
8.6%
3 50
 
4.0%
1 41
 
3.3%
9 26
 
2.1%
8 13
 
1.1%
Other Punctuation
ValueCountFrequency (%)
: 309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 355
23.0%
: 309
20.0%
5 236
15.3%
7 157
10.2%
4 145
9.4%
2 107
 
6.9%
6 106
 
6.9%
3 50
 
3.2%
1 41
 
2.7%
9 26
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 355
23.0%
: 309
20.0%
5 236
15.3%
7 157
10.2%
4 145
9.4%
2 107
 
6.9%
6 106
 
6.9%
3 50
 
3.2%
1 41
 
2.7%
9 26
 
1.7%

마그네트2점등시간
Text

Distinct70
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:51:21.053513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1545
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

Unique35 ?
Unique (%)11.3%

Sample

1st row17:27
2nd row17:27
3rd row17:27
4th row17:22
5th row17:27
ValueCountFrequency (%)
19:16 74
23.9%
19:09 32
 
10.4%
19:11 22
 
7.1%
18:28 20
 
6.5%
18:29 18
 
5.8%
18:30 13
 
4.2%
17:27 10
 
3.2%
19:25 10
 
3.2%
17:24 6
 
1.9%
17:25 6
 
1.9%
Other values (60) 98
31.7%
2024-03-15T05:51:22.072273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 437
28.3%
: 309
20.0%
9 226
14.6%
2 109
 
7.1%
8 108
 
7.0%
6 88
 
5.7%
0 78
 
5.0%
7 75
 
4.9%
3 46
 
3.0%
5 46
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1236
80.0%
Other Punctuation 309
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 437
35.4%
9 226
18.3%
2 109
 
8.8%
8 108
 
8.7%
6 88
 
7.1%
0 78
 
6.3%
7 75
 
6.1%
3 46
 
3.7%
5 46
 
3.7%
4 23
 
1.9%
Other Punctuation
ValueCountFrequency (%)
: 309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 437
28.3%
: 309
20.0%
9 226
14.6%
2 109
 
7.1%
8 108
 
7.0%
6 88
 
5.7%
0 78
 
5.0%
7 75
 
4.9%
3 46
 
3.0%
5 46
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 437
28.3%
: 309
20.0%
9 226
14.6%
2 109
 
7.1%
8 108
 
7.0%
6 88
 
5.7%
0 78
 
5.0%
7 75
 
4.9%
3 46
 
3.0%
5 46
 
3.0%

마그네트2소등시간
Text

Distinct65
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:51:22.792150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1545
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

Unique28 ?
Unique (%)9.1%

Sample

1st row07:29
2nd row07:29
3rd row07:29
4th row07:13
5th row07:29
ValueCountFrequency (%)
05:47 85
27.5%
05:51 22
 
7.1%
23:30 18
 
5.8%
06:54 14
 
4.5%
06:49 13
 
4.2%
06:56 12
 
3.9%
06:52 9
 
2.9%
07:29 9
 
2.9%
07:27 8
 
2.6%
05:37 8
 
2.6%
Other values (55) 111
35.9%
2024-03-15T05:51:23.955550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 361
23.4%
: 309
20.0%
5 227
14.7%
7 142
 
9.2%
4 133
 
8.6%
2 117
 
7.6%
6 105
 
6.8%
3 77
 
5.0%
1 37
 
2.4%
9 26
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1236
80.0%
Other Punctuation 309
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 361
29.2%
5 227
18.4%
7 142
 
11.5%
4 133
 
10.8%
2 117
 
9.5%
6 105
 
8.5%
3 77
 
6.2%
1 37
 
3.0%
9 26
 
2.1%
8 11
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 361
23.4%
: 309
20.0%
5 227
14.7%
7 142
 
9.2%
4 133
 
8.6%
2 117
 
7.6%
6 105
 
6.8%
3 77
 
5.0%
1 37
 
2.4%
9 26
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 361
23.4%
: 309
20.0%
5 227
14.7%
7 142
 
9.2%
4 133
 
8.6%
2 117
 
7.6%
6 105
 
6.8%
3 77
 
5.0%
1 37
 
2.4%
9 26
 
1.7%

마그네트3점등시간
Text

Distinct70
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:51:24.704846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1545
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

Unique35 ?
Unique (%)11.3%

Sample

1st row17:27
2nd row17:27
3rd row17:27
4th row17:22
5th row17:27
ValueCountFrequency (%)
19:16 74
23.9%
19:09 32
 
10.4%
19:11 22
 
7.1%
18:28 20
 
6.5%
18:29 18
 
5.8%
18:30 13
 
4.2%
17:27 10
 
3.2%
19:25 10
 
3.2%
17:24 6
 
1.9%
17:25 6
 
1.9%
Other values (60) 98
31.7%
2024-03-15T05:51:25.634682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 436
28.2%
: 309
20.0%
9 225
14.6%
8 108
 
7.0%
2 108
 
7.0%
6 88
 
5.7%
0 82
 
5.3%
7 73
 
4.7%
5 47
 
3.0%
3 46
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1236
80.0%
Other Punctuation 309
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 436
35.3%
9 225
18.2%
8 108
 
8.7%
2 108
 
8.7%
6 88
 
7.1%
0 82
 
6.6%
7 73
 
5.9%
5 47
 
3.8%
3 46
 
3.7%
4 23
 
1.9%
Other Punctuation
ValueCountFrequency (%)
: 309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 436
28.2%
: 309
20.0%
9 225
14.6%
8 108
 
7.0%
2 108
 
7.0%
6 88
 
5.7%
0 82
 
5.3%
7 73
 
4.7%
5 47
 
3.0%
3 46
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 436
28.2%
: 309
20.0%
9 225
14.6%
8 108
 
7.0%
2 108
 
7.0%
6 88
 
5.7%
0 82
 
5.3%
7 73
 
4.7%
5 47
 
3.0%
3 46
 
3.0%

마그네트3소등시간
Text

Distinct65
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:51:26.447825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1545
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

Unique29 ?
Unique (%)9.4%

Sample

1st row07:29
2nd row07:29
3rd row07:29
4th row07:13
5th row07:29
ValueCountFrequency (%)
05:47 74
23.9%
23:30 32
 
10.4%
05:51 22
 
7.1%
06:54 14
 
4.5%
06:49 13
 
4.2%
06:56 12
 
3.9%
22:00 10
 
3.2%
07:29 9
 
2.9%
06:52 9
 
2.9%
07:27 8
 
2.6%
Other values (55) 106
34.3%
2024-03-15T05:51:27.466987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 357
23.1%
: 309
20.0%
5 210
13.6%
7 130
 
8.4%
2 130
 
8.4%
4 123
 
8.0%
6 104
 
6.7%
3 103
 
6.7%
1 39
 
2.5%
9 28
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1236
80.0%
Other Punctuation 309
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 357
28.9%
5 210
17.0%
7 130
 
10.5%
2 130
 
10.5%
4 123
 
10.0%
6 104
 
8.4%
3 103
 
8.3%
1 39
 
3.2%
9 28
 
2.3%
8 12
 
1.0%
Other Punctuation
ValueCountFrequency (%)
: 309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 357
23.1%
: 309
20.0%
5 210
13.6%
7 130
 
8.4%
2 130
 
8.4%
4 123
 
8.0%
6 104
 
6.7%
3 103
 
6.7%
1 39
 
2.5%
9 28
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 357
23.1%
: 309
20.0%
5 210
13.6%
7 130
 
8.4%
2 130
 
8.4%
4 123
 
8.0%
6 104
 
6.7%
3 103
 
6.7%
1 39
 
2.5%
9 28
 
1.8%

마그네트4점등시간
Date

Distinct70
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2024-03-15 00:38:00
Maximum2024-03-15 20:17:00
2024-03-15T05:51:27.890498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:51:28.616667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

마그네트4소등시간
Text

Distinct64
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:51:29.431934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1545
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

Unique28 ?
Unique (%)9.1%

Sample

1st row07:29
2nd row07:29
3rd row07:29
4th row07:13
5th row07:29
ValueCountFrequency (%)
05:47 72
23.3%
23:30 32
 
10.4%
05:51 22
 
7.1%
06:54 14
 
4.5%
06:49 13
 
4.2%
06:56 12
 
3.9%
22:00 11
 
3.6%
07:29 9
 
2.9%
06:52 9
 
2.9%
05:37 8
 
2.6%
Other values (54) 107
34.6%
2024-03-15T05:51:30.398430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 362
23.4%
: 309
20.0%
5 211
13.7%
2 130
 
8.4%
7 126
 
8.2%
4 121
 
7.8%
3 105
 
6.8%
6 103
 
6.7%
1 39
 
2.5%
9 28
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1236
80.0%
Other Punctuation 309
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 362
29.3%
5 211
17.1%
2 130
 
10.5%
7 126
 
10.2%
4 121
 
9.8%
3 105
 
8.5%
6 103
 
8.3%
1 39
 
3.2%
9 28
 
2.3%
8 11
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 362
23.4%
: 309
20.0%
5 211
13.7%
2 130
 
8.4%
7 126
 
8.2%
4 121
 
7.8%
3 105
 
6.8%
6 103
 
6.7%
1 39
 
2.5%
9 28
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 362
23.4%
: 309
20.0%
5 211
13.7%
2 130
 
8.4%
7 126
 
8.2%
4 121
 
7.8%
3 105
 
6.8%
6 103
 
6.7%
1 39
 
2.5%
9 28
 
1.8%

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-01-10
309 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-10
2nd row2024-01-10
3rd row2024-01-10
4th row2024-01-10
5th row2024-01-10

Common Values

ValueCountFrequency (%)
2024-01-10 309
100.0%

Length

2024-03-15T05:51:30.642117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:51:30.909909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-10 309
100.0%

Interactions

2024-03-15T05:51:06.559493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:51:05.934368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:51:06.849525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:51:06.258248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:51:31.110260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분전함번호설치구역분전함상태마그네트1점등시간마그네트1소등시간마그네트2점등시간마그네트2소등시간마그네트3점등시간마그네트3소등시간마그네트4점등시간마그네트4소등시간
분전함번호1.0000.1000.3940.8010.7860.8010.7900.8010.7940.8010.796
설치구역0.1001.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
분전함상태0.3940.0001.0000.8540.8310.8540.8090.8540.7960.8540.808
마그네트1점등시간0.8010.0000.8541.0000.9961.0000.9961.0000.9961.0000.996
마그네트1소등시간0.7860.0000.8310.9961.0000.9961.0000.9961.0000.9961.000
마그네트2점등시간0.8010.0000.8541.0000.9961.0000.9961.0000.9961.0000.996
마그네트2소등시간0.7900.0000.8090.9961.0000.9961.0000.9961.0000.9961.000
마그네트3점등시간0.8010.0000.8541.0000.9961.0000.9961.0000.9961.0000.996
마그네트3소등시간0.7940.0000.7960.9961.0000.9961.0000.9961.0000.9961.000
마그네트4점등시간0.8010.0000.8541.0000.9961.0000.9961.0000.9961.0000.996
마그네트4소등시간0.7960.0000.8080.9961.0000.9961.0000.9961.0000.9961.000
2024-03-15T05:51:31.332409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분전함번호분전함상태설치구역
분전함번호1.000-0.2000.054
분전함상태-0.2001.0000.000
설치구역0.0540.0001.000

Missing values

2024-03-15T05:51:07.248473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:51:08.022572image/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

분전함번호분전함이름설치위치설치구역분전함상태마그네트1점등시간마그네트1소등시간마그네트2점등시간마그네트2소등시간마그네트3점등시간마그네트3소등시간마그네트4점등시간마그네트4소등시간데이터 기준일자
01운중로11성남시 분당구 운중동 889 공운중로111117:2707:2917:2707:2917:2707:2917:2707:292024-01-10
12운중로1성남시 분당구 운중동 900공운중로017:2707:2917:2707:2917:2707:2917:2707:292024-01-10
23운중로10성남시 분당구 운중동 898-4공운중로111117:2707:2917:2707:2917:2707:2917:2707:292024-01-10
34운중로5성남시 분당구 운중동 954-2공운중로111117:2207:1317:2207:1317:2207:1317:2207:132024-01-10
45운중로9성남시 분당구 운중동 958-1공운중로111117:2707:2917:2707:2917:2707:2917:2707:292024-01-10
56운중로2성남시 분당구 운중동 949-1공운중로111117:2707:2917:2707:2917:2707:2917:2707:292024-01-10
67운중로8성남시 분당구 운중동 997-17공운중로111117:2707:2917:2707:2917:2707:2917:2707:292024-01-10
78운중로3성남시 분당구 운중동 1019-10공운중로111117:2707:2917:2707:2917:2707:2917:2707:292024-01-10
89산운로39성남시 분당구 운중동 880-10도운중로019:2505:3719:2505:3719:2505:3719:2505:372024-01-10
910산운로40성남시 분당구 운중동 892-8 도운중로111119:2505:3719:2505:3719:2505:3719:2505:372024-01-10
분전함번호분전함이름설치위치설치구역분전함상태마그네트1점등시간마그네트1소등시간마그네트2점등시간마그네트2소등시간마그네트3점등시간마그네트3소등시간마그네트4점등시간마그네트4소등시간데이터 기준일자
299300하-기-자21성남시 분당구 삼평동 731공운중로019:1605:4719:1605:4719:1605:4719:1605:472024-01-10
300301운중저 01성남시 분당구 삼평동 745-1공운중로019:1605:4719:1605:4719:1605:4719:1605:472024-01-10
301302운중저 02성남시 분당구 삼평동 745-1공운중로019:1605:4719:1605:4719:1605:4719:1605:472024-01-10
302303운중저 03성남시 분당구 삼평동 745-1공운중로019:1605:4719:1605:4719:1605:4719:1605:472024-01-10
303304분당수서로59성남시 분당구 삼평동 704수운중로019:0905:5119:0905:5119:0905:5119:0905:512024-01-10
304305분당수서로58성남시 분당구 삼평동 703-3 도운중로017:2607:2417:2607:2417:2607:2417:2607:242024-01-10
305306분당수서로53성남시 분당구 백현동 559-1공운중로019:0905:4719:0905:4719:0905:4719:0905:472024-01-10
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