Overview

Dataset statistics

Number of variables10
Number of observations299
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.7 KiB
Average record size in memory84.4 B

Variable types

Numeric3
Categorical2
Text4
DateTime1

Dataset

Description광주광역시 지역아동센터 현황에 대한 데이터로 센터명, 소재지 도로명주소, 전화번호, 정원, 현원 등의 항목을 제공합니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15043862/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 자치구High correlation
현원 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
정원 is highly overall correlated with 현원 and 1 other fieldsHigh correlation
자치구 is highly overall correlated with 연번High correlation
종사자 is highly overall correlated with 현원 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
소재지도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 20:57:31.467534
Analysis finished2024-03-14 20:57:35.153166
Duration3.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct299
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean150
Minimum1
Maximum299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T05:57:35.328695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.9
Q175.5
median150
Q3224.5
95-th percentile284.1
Maximum299
Range298
Interquartile range (IQR)149

Descriptive statistics

Standard deviation86.458082
Coefficient of variation (CV)0.57638722
Kurtosis-1.2
Mean150
Median Absolute Deviation (MAD)75
Skewness0
Sum44850
Variance7475
MonotonicityStrictly increasing
2024-03-15T05:57:35.688812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
207 1
 
0.3%
205 1
 
0.3%
204 1
 
0.3%
203 1
 
0.3%
202 1
 
0.3%
201 1
 
0.3%
200 1
 
0.3%
199 1
 
0.3%
198 1
 
0.3%
Other values (289) 289
96.7%
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 (%)
299 1
0.3%
298 1
0.3%
297 1
0.3%
296 1
0.3%
295 1
0.3%
294 1
0.3%
293 1
0.3%
292 1
0.3%
291 1
0.3%
290 1
0.3%

자치구
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
북구
116 
광산구
70 
남구
47 
서구
46 
동구
20 

Length

Max length3
Median length2
Mean length2.2341137
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
북구 116
38.8%
광산구 70
23.4%
남구 47
15.7%
서구 46
 
15.4%
동구 20
 
6.7%

Length

2024-03-15T05:57:36.056949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:57:36.316906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북구 116
38.8%
광산구 70
23.4%
남구 47
15.7%
서구 46
 
15.4%
동구 20
 
6.7%

센터명
Text

Distinct287
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:57:37.450457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length13
Mean length6.6287625
Min length2

Characters and Unicode

Total characters1982
Distinct characters275
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique276 ?
Unique (%)92.3%

Sample

1st row계림지역아동센터
2nd row꿈을그리는동명지역아동센터
3rd row늘푸른지역아동센터
4th row드림스쿨지역아동센터
5th row디딤돌지역아동센터
ValueCountFrequency (%)
무지개지역아동센터 3
 
1.0%
디딤돌지역아동센터 2
 
0.7%
파랑새지역아동센터 2
 
0.7%
참사랑지역아동센터 2
 
0.7%
한별지역아동센터 2
 
0.7%
행복한지역아동센터 2
 
0.7%
꿈나무지역아동센터 2
 
0.7%
우등지역아동센터 2
 
0.7%
비젼지역아동센터 2
 
0.7%
미래지역아동센터 2
 
0.7%
Other values (277) 278
93.0%
2024-03-15T05:57:38.815278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 201
 
10.1%
동 198
 
10.0%
지 196
 
9.9%
터 187
 
9.4%
역 183
 
9.2%
센 183
 
9.2%
나 20
 
1.0%
꿈 17
 
0.9%
리 16
 
0.8%
무 15
 
0.8%
Other values (265) 766
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1948
98.3%
Lowercase Letter 16
 
0.8%
Decimal Number 9
 
0.5%
Uppercase Letter 9
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 201
 
10.3%
동 198
 
10.2%
지 196
 
10.1%
터 187
 
9.6%
역 183
 
9.4%
센 183
 
9.4%
나 20
 
1.0%
꿈 17
 
0.9%
리 16
 
0.8%
무 15
 
0.8%
Other values (243) 732
37.6%
Lowercase Letter
ValueCountFrequency (%)
o 4
25.0%
e 2
12.5%
p 2
12.5%
n 1
 
6.2%
z 1
 
6.2%
y 1
 
6.2%
a 1
 
6.2%
l 1
 
6.2%
h 1
 
6.2%
c 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
H 3
33.3%
Y 1
 
11.1%
W 1
 
11.1%
C 1
 
11.1%
A 1
 
11.1%
L 1
 
11.1%
S 1
 
11.1%
Decimal Number
ValueCountFrequency (%)
1 4
44.4%
8 2
22.2%
3 2
22.2%
2 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1948
98.3%
Latin 25
 
1.3%
Common 9
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 201
 
10.3%
동 198
 
10.2%
지 196
 
10.1%
터 187
 
9.6%
역 183
 
9.4%
센 183
 
9.4%
나 20
 
1.0%
꿈 17
 
0.9%
리 16
 
0.8%
무 15
 
0.8%
Other values (243) 732
37.6%
Latin
ValueCountFrequency (%)
o 4
16.0%
H 3
 
12.0%
e 2
 
8.0%
p 2
 
8.0%
Y 1
 
4.0%
n 1
 
4.0%
z 1
 
4.0%
y 1
 
4.0%
a 1
 
4.0%
W 1
 
4.0%
Other values (8) 8
32.0%
Common
ValueCountFrequency (%)
1 4
44.4%
8 2
22.2%
3 2
22.2%
2 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1948
98.3%
ASCII 34
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 201
 
10.3%
동 198
 
10.2%
지 196
 
10.1%
터 187
 
9.6%
역 183
 
9.4%
센 183
 
9.4%
나 20
 
1.0%
꿈 17
 
0.9%
리 16
 
0.8%
무 15
 
0.8%
Other values (243) 732
37.6%
ASCII
ValueCountFrequency (%)
o 4
 
11.8%
1 4
 
11.8%
H 3
 
8.8%
8 2
 
5.9%
e 2
 
5.9%
p 2
 
5.9%
3 2
 
5.9%
2 1
 
2.9%
Y 1
 
2.9%
n 1
 
2.9%
Other values (12) 12
35.3%

소재지도로명주소
Text

UNIQUE 

Distinct299
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:57:40.455054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length27.280936
Min length12

Characters and Unicode

Total characters8157
Distinct characters211
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)100.0%

Sample

1st row광주광역시 중앙로 326, 2층
2nd row광주광역시 무등로 460
3rd row광주광역시 밤실로 76-2, 3층
4th row광주광역시 남문로 620, 2층
5th row광주광역시 학소로86번안길 8
ValueCountFrequency (%)
광주광역시 415
27.2%
북구 116
 
7.6%
2층 74
 
4.8%
3층 27
 
1.8%
1층 14
 
0.9%
두암동 13
 
0.9%
상가동 13
 
0.9%
문흥동 10
 
0.7%
오치동 10
 
0.7%
양산동 9
 
0.6%
Other values (600) 825
54.1%
2024-03-15T05:57:42.241685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1229
 
15.1%
광 839
 
10.3%
시 425
 
5.2%
주 425
 
5.2%
역 415
 
5.1%
1 328
 
4.0%
2 320
 
3.9%
로 279
 
3.4%
동 227
 
2.8%
, 200
 
2.5%
Other values (201) 3470
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4793
58.8%
Decimal Number 1503
 
18.4%
Space Separator 1229
 
15.1%
Other Punctuation 203
 
2.5%
Open Punctuation 167
 
2.0%
Close Punctuation 167
 
2.0%
Dash Punctuation 90
 
1.1%
Uppercase Letter 3
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 839
17.5%
시 425
 
8.9%
주 425
 
8.9%
역 415
 
8.7%
로 279
 
5.8%
동 227
 
4.7%
길 188
 
3.9%
번 164
 
3.4%
층 136
 
2.8%
북 119
 
2.5%
Other values (180) 1576
32.9%
Decimal Number
ValueCountFrequency (%)
1 328
21.8%
2 320
21.3%
3 169
11.2%
0 144
9.6%
4 123
 
8.2%
6 108
 
7.2%
5 106
 
7.1%
8 75
 
5.0%
7 67
 
4.5%
9 63
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 200
98.5%
. 2
 
1.0%
@ 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
P 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
1229
100.0%
Open Punctuation
ValueCountFrequency (%)
( 167
100.0%
Close Punctuation
ValueCountFrequency (%)
) 167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4793
58.8%
Common 3361
41.2%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 839
17.5%
시 425
 
8.9%
주 425
 
8.9%
역 415
 
8.7%
로 279
 
5.8%
동 227
 
4.7%
길 188
 
3.9%
번 164
 
3.4%
층 136
 
2.8%
북 119
 
2.5%
Other values (180) 1576
32.9%
Common
ValueCountFrequency (%)
1229
36.6%
1 328
 
9.8%
2 320
 
9.5%
, 200
 
6.0%
3 169
 
5.0%
( 167
 
5.0%
) 167
 
5.0%
0 144
 
4.3%
4 123
 
3.7%
6 108
 
3.2%
Other values (8) 406
 
12.1%
Latin
ValueCountFrequency (%)
A 1
33.3%
P 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4793
58.8%
ASCII 3364
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1229
36.5%
1 328
 
9.8%
2 320
 
9.5%
, 200
 
5.9%
3 169
 
5.0%
( 167
 
5.0%
) 167
 
5.0%
0 144
 
4.3%
4 123
 
3.7%
6 108
 
3.2%
Other values (11) 409
 
12.2%
Hangul
ValueCountFrequency (%)
광 839
17.5%
시 425
 
8.9%
주 425
 
8.9%
역 415
 
8.7%
로 279
 
5.8%
동 227
 
4.7%
길 188
 
3.9%
번 164
 
3.4%
층 136
 
2.8%
북 119
 
2.5%
Other values (180) 1576
32.9%

센터장
Text

Distinct292
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:57:43.707736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9765886
Min length2

Characters and Unicode

Total characters890
Distinct characters132
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique286 ?
Unique (%)95.7%

Sample

1st row김두정
2nd row김헌희
3rd row박수진
4th row이인희
5th row박인숙
ValueCountFrequency (%)
김정숙 3
 
1.0%
박지영 2
 
0.7%
박성숙 2
 
0.7%
김미란 2
 
0.7%
김미화 2
 
0.7%
김미숙 2
 
0.7%
이선주 1
 
0.3%
김인 1
 
0.3%
최형란 1
 
0.3%
김향숙 1
 
0.3%
Other values (283) 283
94.3%
2024-03-15T05:57:45.384142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 78
 
8.8%
숙 45
 
5.1%
정 44
 
4.9%
박 41
 
4.6%
희 35
 
3.9%
미 34
 
3.8%
이 28
 
3.1%
영 27
 
3.0%
선 22
 
2.5%
경 21
 
2.4%
Other values (122) 515
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 889
99.9%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 78
 
8.8%
숙 45
 
5.1%
정 44
 
4.9%
박 41
 
4.6%
희 35
 
3.9%
미 34
 
3.8%
이 28
 
3.1%
영 27
 
3.0%
선 22
 
2.5%
경 21
 
2.4%
Other values (121) 514
57.8%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 889
99.9%
Common 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 78
 
8.8%
숙 45
 
5.1%
정 44
 
4.9%
박 41
 
4.6%
희 35
 
3.9%
미 34
 
3.8%
이 28
 
3.1%
영 27
 
3.0%
선 22
 
2.5%
경 21
 
2.4%
Other values (121) 514
57.8%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 889
99.9%
ASCII 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 78
 
8.8%
숙 45
 
5.1%
정 44
 
4.9%
박 41
 
4.6%
희 35
 
3.9%
미 34
 
3.8%
이 28
 
3.1%
영 27
 
3.0%
선 22
 
2.5%
경 21
 
2.4%
Other values (121) 514
57.8%
ASCII
ValueCountFrequency (%)
1
100.0%

현원
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.785953
Minimum0
Maximum46
Zeros2
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T05:57:45.775743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q118
median23
Q329
95-th percentile36
Maximum46
Range46
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.3197125
Coefficient of variation (CV)0.30773257
Kurtosis0.060020422
Mean23.785953
Median Absolute Deviation (MAD)5
Skewness0.32352924
Sum7112
Variance53.578191
MonotonicityNot monotonic
2024-03-15T05:57:46.172118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
19 35
 
11.7%
25 32
 
10.7%
18 30
 
10.0%
17 21
 
7.0%
24 13
 
4.3%
29 13
 
4.3%
28 12
 
4.0%
15 11
 
3.7%
23 10
 
3.3%
16 10
 
3.3%
Other values (23) 112
37.5%
ValueCountFrequency (%)
0 2
 
0.7%
10 1
 
0.3%
11 3
 
1.0%
12 1
 
0.3%
14 7
 
2.3%
15 11
 
3.7%
16 10
 
3.3%
17 21
7.0%
18 30
10.0%
19 35
11.7%
ValueCountFrequency (%)
46 1
 
0.3%
43 1
 
0.3%
42 1
 
0.3%
40 4
 
1.3%
39 3
 
1.0%
38 4
 
1.3%
36 5
1.7%
35 7
2.3%
34 7
2.3%
33 10
3.3%

정원
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.782609
Minimum0
Maximum49
Zeros2
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T05:57:46.545700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19
Q119
median25
Q329
95-th percentile40
Maximum49
Range49
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.5504721
Coefficient of variation (CV)0.29285136
Kurtosis0.76319474
Mean25.782609
Median Absolute Deviation (MAD)6
Skewness0.56118375
Sum7709
Variance57.009629
MonotonicityNot monotonic
2024-03-15T05:57:47.054302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
19 120
40.1%
29 57
19.1%
25 30
 
10.0%
40 13
 
4.3%
27 11
 
3.7%
35 10
 
3.3%
31 6
 
2.0%
32 6
 
2.0%
34 5
 
1.7%
26 5
 
1.7%
Other values (16) 36
 
12.0%
ValueCountFrequency (%)
0 2
 
0.7%
16 1
 
0.3%
19 120
40.1%
22 2
 
0.7%
23 3
 
1.0%
24 1
 
0.3%
25 30
 
10.0%
26 5
 
1.7%
27 11
 
3.7%
28 3
 
1.0%
ValueCountFrequency (%)
49 4
 
1.3%
46 1
 
0.3%
45 1
 
0.3%
43 1
 
0.3%
41 1
 
0.3%
40 13
4.3%
39 1
 
0.3%
38 2
 
0.7%
37 5
 
1.7%
36 3
 
1.0%

종사자
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2
231 
3
66 
0
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row3

Common Values

ValueCountFrequency (%)
2 231
77.3%
3 66
 
22.1%
0 2
 
0.7%

Length

2024-03-15T05:57:47.593049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:57:47.935973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 231
77.3%
3 66
 
22.1%
0 2
 
0.7%

전화번호
Text

Distinct292
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T05:57:49.044303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.073579
Min length12

Characters and Unicode

Total characters3610
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

Unique291 ?
Unique (%)97.3%

Sample

1st row062-228-6300
2nd row062-233-5104
3rd row062-224-6488
4th row062-224-9191
5th row062-227-9421
ValueCountFrequency (%)
070-8191-2673 8
 
2.7%
062-576-4183 1
 
0.3%
062-575-0936 1
 
0.3%
062-529-0579 1
 
0.3%
062-531-0982 1
 
0.3%
062-529-3162 1
 
0.3%
062-512-6189 1
 
0.3%
062-263-8877 1
 
0.3%
062-571-5772 1
 
0.3%
062-528-0819 1
 
0.3%
Other values (282) 282
94.3%
2024-03-15T05:57:50.558718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 598
16.6%
2 516
14.3%
6 512
14.2%
0 511
14.2%
5 262
7.3%
3 244
6.8%
1 234
 
6.5%
7 226
 
6.3%
9 190
 
5.3%
4 177
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3012
83.4%
Dash Punctuation 598
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 516
17.1%
6 512
17.0%
0 511
17.0%
5 262
8.7%
3 244
8.1%
1 234
7.8%
7 226
7.5%
9 190
 
6.3%
4 177
 
5.9%
8 140
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 598
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3610
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 598
16.6%
2 516
14.3%
6 512
14.2%
0 511
14.2%
5 262
7.3%
3 244
6.8%
1 234
 
6.5%
7 226
 
6.3%
9 190
 
5.3%
4 177
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 598
16.6%
2 516
14.3%
6 512
14.2%
0 511
14.2%
5 262
7.3%
3 244
6.8%
1 234
 
6.5%
7 226
 
6.3%
9 190
 
5.3%
4 177
 
4.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2024-01-15 00:00:00
Maximum2024-01-15 00:00:00
2024-03-15T05:57:51.047748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:57:51.351826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T05:57:33.974828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:57:32.231972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:57:33.231912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:57:34.162042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:57:32.485437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:57:33.482348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:57:34.380082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:57:32.729712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:57:33.717602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:57:51.577296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번자치구현원정원종사자
연번1.0000.9910.2140.3300.337
자치구0.9911.0000.3230.4320.304
현원0.2140.3231.0000.8880.995
정원0.3300.4320.8881.0000.972
종사자0.3370.3040.9950.9721.000
2024-03-15T05:57:51.858344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종사자자치구
종사자1.0000.240
자치구0.2401.000
2024-03-15T05:57:52.109498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번현원정원자치구종사자
연번1.000-0.053-0.0360.8540.212
현원-0.0531.0000.9280.1970.903
정원-0.0360.9281.0000.2810.982
자치구0.8540.1970.2811.0000.240
종사자0.2120.9030.9820.2401.000

Missing values

2024-03-15T05:57:34.585509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:57:34.968862image/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

연번자치구센터명소재지도로명주소센터장현원정원종사자전화번호데이터기준일자
01동구계림지역아동센터광주광역시 중앙로 326, 2층김두정25272062-228-63002024-01-15
12동구꿈을그리는동명지역아동센터광주광역시 무등로 460김헌희16192062-233-51042024-01-15
23동구늘푸른지역아동센터광주광역시 밤실로 76-2, 3층박수진11192062-224-64882024-01-15
34동구드림스쿨지역아동센터광주광역시 남문로 620, 2층이인희22232062-224-91912024-01-15
45동구디딤돌지역아동센터광주광역시 학소로86번안길 8박인숙42493062-227-94212024-01-15
56동구미래지역아동센터광주광역시 필문대로 142-1서해린25252062-527-01012024-01-15
67동구산수중앙지역아동센터광주광역시 밤실로 132, 2층서윤아31313062-251-64372024-01-15
78동구선지역아동센터광주광역시 소태길 22-3, 2층김현숙15192062-233-44762024-01-15
89동구용산지역아동센터광주광역시 화산로 328-6, 호반상가 2층박선정31313062-465-56672024-01-15
910동구정다운지역아동센터광주광역시 밤실로90번길 11-7박경인23232062-262-59622024-01-15
연번자치구센터명소재지도로명주소센터장현원정원종사자전화번호데이터기준일자
289290광산구하남2지구지역아동센터광주광역시 하남대로 30, 부영사랑으로 309동 401호최보라16192062-417-45612024-01-15
290291광산구하남공립지역아동센터광주광역시 월곡산정로 12, 하남복지관 3층신은철31353062-954-01042024-01-15
291292광산구한별지역아동센터광주광역시 사암로27번길 55, 3층추혜경25292062-946-00302024-01-15
292293광산구한아름지역아동센터광주광역시 신도산길 54심춘남35363062-944-13542024-01-15
293294광산구해돋이지역아동센터광주광역시 수완로11번안길 28이경주33353062-955-84282024-01-15
294295광산구해바라기지역아동센터광주광역시 소촌로152번길 5, 상가동 208-201호유근례30313062-944-80042024-01-15
295296광산구해오름지역아동센터광주광역시 송도로 210, 2층강성자17192062-944-43092024-01-15
296297광산구해피존멘토지역아동센터광주광역시 목련로394번길 40-7, 3층한영석18192070-7736-10442024-01-15
297298광산구행복나눔지역아동센터광주광역시 목련로21번길 45, 다사로움1단지 관리사무소 2층김명옥30323062-962-36712024-01-15
298299광산구희망나눔지역아동센터광주광역시 월곡반월로 26, 2층김영주29292062-413-34252024-01-15