Overview

Dataset statistics

Number of variables11
Number of observations47
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory94.8 B

Variable types

DateTime1
Categorical1
Text5
Numeric4

Alerts

집계일자 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
센터명 has unique valuesUnique
센터전화번호 has unique valuesUnique
센터대표자명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:20:06.986114
Analysis finished2023-12-10 21:20:09.317365
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계일자
Date

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
Minimum2023-06-30 00:00:00
Maximum2023-06-30 00:00:00
2023-12-11T06:20:09.358876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:09.440660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시군명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Memory size508.0 B
수원시
8 
용인시
7 
성남시
7 
안산시
4 
화성시
2 
Other values (12)
19 

Length

Max length4
Median length3
Mean length3.0425532
Min length3

Unique

Unique5 ?
Unique (%)10.6%

Sample

1st row고양시
2nd row고양시
3rd row군포시
4th row남양주시
5th row부천시

Common Values

ValueCountFrequency (%)
수원시 8
17.0%
용인시 7
14.9%
성남시 7
14.9%
안산시 4
8.5%
화성시 2
 
4.3%
부천시 2
 
4.3%
시흥시 2
 
4.3%
안성시 2
 
4.3%
오산시 2
 
4.3%
포천시 2
 
4.3%
Other values (7) 9
19.1%

Length

2023-12-11T06:20:09.549314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 8
17.0%
용인시 7
14.9%
성남시 7
14.9%
안산시 4
8.5%
고양시 2
 
4.3%
안양시 2
 
4.3%
포천시 2
 
4.3%
오산시 2
 
4.3%
안성시 2
 
4.3%
시흥시 2
 
4.3%
Other values (7) 9
19.1%

센터명
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T06:20:09.790378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length6.9148936
Min length4

Characters and Unicode

Total characters325
Distinct characters102
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row동국대학교
2nd row한국항공대학교
3rd row군포산업진흥원
4th row경복대학교
5th row가톨릭대학교
ValueCountFrequency (%)
동국대학교 1
 
2.0%
경기테크노파크안산bi 1
 
2.0%
용인예술과학대학교 1
 
2.0%
한양대학교 1
 
2.0%
중앙대학교 1
 
2.0%
한경대학교 1
 
2.0%
연성대학교 1
 
2.0%
안양대학교 1
 
2.0%
여주대학교 1
 
2.0%
오산대학교 1
 
2.0%
Other values (39) 39
79.6%
2023-12-11T06:20:10.200753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 37
 
11.4%
대 34
 
10.5%
교 33
 
10.2%
기 12
 
3.7%
경 10
 
3.1%
국 9
 
2.8%
한 9
 
2.8%
원 7
 
2.2%
업 7
 
2.2%
터 6
 
1.8%
Other values (92) 161
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 312
96.0%
Uppercase Letter 5
 
1.5%
Lowercase Letter 3
 
0.9%
Space Separator 2
 
0.6%
Dash Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 37
 
11.9%
대 34
 
10.9%
교 33
 
10.6%
기 12
 
3.8%
경 10
 
3.2%
국 9
 
2.9%
한 9
 
2.9%
원 7
 
2.2%
업 7
 
2.2%
터 6
 
1.9%
Other values (82) 148
47.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
I 2
40.0%
P 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
33.3%
s 1
33.3%
t 1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 312
96.0%
Latin 8
 
2.5%
Common 5
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 37
 
11.9%
대 34
 
10.9%
교 33
 
10.6%
기 12
 
3.8%
경 10
 
3.2%
국 9
 
2.9%
한 9
 
2.9%
원 7
 
2.2%
업 7
 
2.2%
터 6
 
1.9%
Other values (82) 148
47.4%
Latin
ValueCountFrequency (%)
B 2
25.0%
I 2
25.0%
P 1
12.5%
o 1
12.5%
s 1
12.5%
t 1
12.5%
Common
ValueCountFrequency (%)
2
40.0%
- 1
20.0%
( 1
20.0%
) 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 312
96.0%
ASCII 13
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 37
 
11.9%
대 34
 
10.9%
교 33
 
10.6%
기 12
 
3.8%
경 10
 
3.2%
국 9
 
2.9%
한 9
 
2.9%
원 7
 
2.2%
업 7
 
2.2%
터 6
 
1.9%
Other values (82) 148
47.4%
ASCII
ValueCountFrequency (%)
2
15.4%
B 2
15.4%
I 2
15.4%
P 1
7.7%
o 1
7.7%
s 1
7.7%
t 1
7.7%
- 1
7.7%
( 1
7.7%
) 1
7.7%

센터전화번호
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T06:20:10.442751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.085106
Min length11

Characters and Unicode

Total characters568
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

Unique47 ?
Unique (%)100.0%

Sample

1st row031-961-5465
2nd row02-300-0393
3rd row031-380-7133
4th row031-570-9831
5th row02-2164-6561
ValueCountFrequency (%)
031-961-5465 1
 
2.1%
031-400-7085 1
 
2.1%
031-400-4975 1
 
2.1%
031-670-4762 1
 
2.1%
031-670-5682 1
 
2.1%
031-441-1474 1
 
2.1%
031-467-0968 1
 
2.1%
031-880-5574 1
 
2.1%
031-370-2631 1
 
2.1%
031-379-0242 1
 
2.1%
Other values (37) 37
78.7%
2023-12-11T06:20:10.876058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 95
16.7%
- 94
16.5%
3 77
13.6%
1 69
12.1%
2 40
7.0%
7 38
 
6.7%
4 34
 
6.0%
6 32
 
5.6%
9 31
 
5.5%
8 30
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 474
83.5%
Dash Punctuation 94
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 95
20.0%
3 77
16.2%
1 69
14.6%
2 40
8.4%
7 38
 
8.0%
4 34
 
7.2%
6 32
 
6.8%
9 31
 
6.5%
8 30
 
6.3%
5 28
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 568
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 95
16.7%
- 94
16.5%
3 77
13.6%
1 69
12.1%
2 40
7.0%
7 38
 
6.7%
4 34
 
6.0%
6 32
 
5.6%
9 31
 
5.5%
8 30
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 95
16.7%
- 94
16.5%
3 77
13.6%
1 69
12.1%
2 40
7.0%
7 38
 
6.7%
4 34
 
6.0%
6 32
 
5.6%
9 31
 
5.5%
8 30
 
5.3%

센터대표자명
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T06:20:11.114918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9787234
Min length2

Characters and Unicode

Total characters140
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row이용규
2nd row황재혁
3rd row곽수환
4th row박주현
5th row성재열
ValueCountFrequency (%)
이용규 1
 
2.1%
양기덕 1
 
2.1%
이성욱 1
 
2.1%
문성권 1
 
2.1%
박성진 1
 
2.1%
강경희 1
 
2.1%
원종율 1
 
2.1%
이정철 1
 
2.1%
배재호 1
 
2.1%
조창석 1
 
2.1%
Other values (37) 37
78.7%
2023-12-11T06:20:11.466604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 8
 
5.7%
성 7
 
5.0%
주 6
 
4.3%
박 6
 
4.3%
이 5
 
3.6%
진 4
 
2.9%
영 4
 
2.9%
정 3
 
2.1%
석 3
 
2.1%
용 3
 
2.1%
Other values (60) 91
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 140
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 8
 
5.7%
성 7
 
5.0%
주 6
 
4.3%
박 6
 
4.3%
이 5
 
3.6%
진 4
 
2.9%
영 4
 
2.9%
정 3
 
2.1%
석 3
 
2.1%
용 3
 
2.1%
Other values (60) 91
65.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 140
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 8
 
5.7%
성 7
 
5.0%
주 6
 
4.3%
박 6
 
4.3%
이 5
 
3.6%
진 4
 
2.9%
영 4
 
2.9%
정 3
 
2.1%
석 3
 
2.1%
용 3
 
2.1%
Other values (60) 91
65.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 140
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 8
 
5.7%
성 7
 
5.0%
주 6
 
4.3%
박 6
 
4.3%
이 5
 
3.6%
진 4
 
2.9%
영 4
 
2.9%
정 3
 
2.1%
석 3
 
2.1%
용 3
 
2.1%
Other values (60) 91
65.0%

보육실수
Real number (ℝ)

Distinct33
Distinct (%)70.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.978723
Minimum9
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-11T06:20:11.636733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile11.3
Q120.5
median26
Q338
95-th percentile83.9
Maximum141
Range132
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation27.662948
Coefficient of variation (CV)0.76886962
Kurtosis5.6429507
Mean35.978723
Median Absolute Deviation (MAD)10
Skewness2.2334094
Sum1691
Variance765.23867
MonotonicityNot monotonic
2023-12-11T06:20:11.807634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
25 4
 
8.5%
21 3
 
6.4%
26 2
 
4.3%
36 2
 
4.3%
38 2
 
4.3%
11 2
 
4.3%
37 2
 
4.3%
27 2
 
4.3%
22 2
 
4.3%
17 2
 
4.3%
Other values (23) 24
51.1%
ValueCountFrequency (%)
9 1
2.1%
11 2
4.3%
12 1
2.1%
13 1
2.1%
14 1
2.1%
15 1
2.1%
16 1
2.1%
17 2
4.3%
18 1
2.1%
20 1
2.1%
ValueCountFrequency (%)
141 1
2.1%
128 1
2.1%
89 1
2.1%
72 1
2.1%
69 1
2.1%
68 1
2.1%
60 1
2.1%
59 1
2.1%
53 1
2.1%
51 1
2.1%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15178.277
Minimum10326
Maximum18330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-11T06:20:11.941474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10326
5-th percentile11159.3
Q113498.5
median15588
Q316950.5
95-th percentile18113.6
Maximum18330
Range8004
Interquartile range (IQR)3452

Descriptive statistics

Standard deviation2207.8058
Coefficient of variation (CV)0.14545827
Kurtosis-0.6409493
Mean15178.277
Median Absolute Deviation (MAD)1557
Skewness-0.58414498
Sum713379
Variance4874406.6
MonotonicityNot monotonic
2023-12-11T06:20:12.099314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
15432 2
 
4.3%
15073 2
 
4.3%
10326 1
 
2.1%
15588 1
 
2.1%
17579 1
 
2.1%
14011 1
 
2.1%
14028 1
 
2.1%
12652 1
 
2.1%
18119 1
 
2.1%
18101 1
 
2.1%
Other values (35) 35
74.5%
ValueCountFrequency (%)
10326 1
2.1%
10540 1
2.1%
11159 1
2.1%
11160 1
2.1%
11618 1
2.1%
12051 1
2.1%
12652 1
2.1%
13117 1
2.1%
13120 1
2.1%
13174 1
2.1%
ValueCountFrequency (%)
18330 1
2.1%
18323 1
2.1%
18119 1
2.1%
18101 1
2.1%
17579 1
2.1%
17546 1
2.1%
17303 1
2.1%
17145 1
2.1%
17058 1
2.1%
17035 1
2.1%

소재지지번주소
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T06:20:12.377935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length21.212766
Min length16

Characters and Unicode

Total characters997
Distinct characters100
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

Unique47 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산동구 식사동 814-9번지
2nd row경기도 고양시 덕양구 화전동 646-6번지
3rd row경기도 군포시 부곡동 1254번지
4th row경기도 남양주시 진접읍 금곡리 383번지
5th row경기도 부천시 역곡동 산43-1번지
ValueCountFrequency (%)
경기도 47
 
20.9%
수원시 8
 
3.6%
성남시 7
 
3.1%
용인시 7
 
3.1%
영통구 4
 
1.8%
안산시 4
 
1.8%
처인구 4
 
1.8%
분당구 3
 
1.3%
상록구 2
 
0.9%
정왕동 2
 
0.9%
Other values (117) 137
60.9%
2023-12-11T06:20:12.791813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
178
17.9%
시 49
 
4.9%
기 49
 
4.9%
지 48
 
4.8%
번 47
 
4.7%
경 47
 
4.7%
도 47
 
4.7%
1 42
 
4.2%
동 42
 
4.2%
구 32
 
3.2%
Other values (90) 416
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 631
63.3%
Space Separator 178
 
17.9%
Decimal Number 161
 
16.1%
Dash Punctuation 27
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 49
 
7.8%
기 49
 
7.8%
지 48
 
7.6%
번 47
 
7.4%
경 47
 
7.4%
도 47
 
7.4%
동 42
 
6.7%
구 32
 
5.1%
원 16
 
2.5%
산 16
 
2.5%
Other values (78) 238
37.7%
Decimal Number
ValueCountFrequency (%)
1 42
26.1%
2 22
13.7%
5 19
11.8%
4 17
10.6%
6 13
 
8.1%
3 13
 
8.1%
9 10
 
6.2%
0 9
 
5.6%
7 9
 
5.6%
8 7
 
4.3%
Space Separator
ValueCountFrequency (%)
178
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 631
63.3%
Common 366
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 49
 
7.8%
기 49
 
7.8%
지 48
 
7.6%
번 47
 
7.4%
경 47
 
7.4%
도 47
 
7.4%
동 42
 
6.7%
구 32
 
5.1%
원 16
 
2.5%
산 16
 
2.5%
Other values (78) 238
37.7%
Common
ValueCountFrequency (%)
178
48.6%
1 42
 
11.5%
- 27
 
7.4%
2 22
 
6.0%
5 19
 
5.2%
4 17
 
4.6%
6 13
 
3.6%
3 13
 
3.6%
9 10
 
2.7%
0 9
 
2.5%
Other values (2) 16
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 631
63.3%
ASCII 366
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
178
48.6%
1 42
 
11.5%
- 27
 
7.4%
2 22
 
6.0%
5 19
 
5.2%
4 17
 
4.6%
6 13
 
3.6%
3 13
 
3.6%
9 10
 
2.7%
0 9
 
2.5%
Other values (2) 16
 
4.4%
Hangul
ValueCountFrequency (%)
시 49
 
7.8%
기 49
 
7.8%
지 48
 
7.6%
번 47
 
7.4%
경 47
 
7.4%
도 47
 
7.4%
동 42
 
6.7%
구 32
 
5.1%
원 16
 
2.5%
산 16
 
2.5%
Other values (78) 238
37.7%

소재지도로명주소
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T06:20:13.119564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length19.06383
Min length14

Characters and Unicode

Total characters896
Distinct characters117
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

Unique47 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산동구 동국로 32
2nd row경기도 고양시 덕양구 항공대학로 76
3rd row경기도 군포시 군포첨단산업2로22번길 5
4th row경기도 남양주시 진접읍 경복대로 425
5th row경기도 부천시 지봉로 43
ValueCountFrequency (%)
경기도 47
 
20.9%
수원시 8
 
3.6%
성남시 7
 
3.1%
용인시 7
 
3.1%
영통구 4
 
1.8%
안산시 4
 
1.8%
처인구 4
 
1.8%
분당구 3
 
1.3%
상록구 2
 
0.9%
권선구 2
 
0.9%
Other values (118) 137
60.9%
2023-12-11T06:20:13.587910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
178
19.9%
기 52
 
5.8%
경 50
 
5.6%
시 49
 
5.5%
도 47
 
5.2%
로 45
 
5.0%
구 31
 
3.5%
2 23
 
2.6%
3 23
 
2.6%
1 22
 
2.5%
Other values (107) 376
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 576
64.3%
Space Separator 178
 
19.9%
Decimal Number 140
 
15.6%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 52
 
9.0%
경 50
 
8.7%
시 49
 
8.5%
도 47
 
8.2%
로 45
 
7.8%
구 31
 
5.4%
대 15
 
2.6%
성 14
 
2.4%
수 14
 
2.4%
원 14
 
2.4%
Other values (95) 245
42.5%
Decimal Number
ValueCountFrequency (%)
2 23
16.4%
3 23
16.4%
1 22
15.7%
7 16
11.4%
4 14
10.0%
5 12
8.6%
6 11
7.9%
0 10
7.1%
8 6
 
4.3%
9 3
 
2.1%
Space Separator
ValueCountFrequency (%)
178
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 576
64.3%
Common 320
35.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 52
 
9.0%
경 50
 
8.7%
시 49
 
8.5%
도 47
 
8.2%
로 45
 
7.8%
구 31
 
5.4%
대 15
 
2.6%
성 14
 
2.4%
수 14
 
2.4%
원 14
 
2.4%
Other values (95) 245
42.5%
Common
ValueCountFrequency (%)
178
55.6%
2 23
 
7.2%
3 23
 
7.2%
1 22
 
6.9%
7 16
 
5.0%
4 14
 
4.4%
5 12
 
3.8%
6 11
 
3.4%
0 10
 
3.1%
8 6
 
1.9%
Other values (2) 5
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 576
64.3%
ASCII 320
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
178
55.6%
2 23
 
7.2%
3 23
 
7.2%
1 22
 
6.9%
7 16
 
5.0%
4 14
 
4.4%
5 12
 
3.8%
6 11
 
3.4%
0 10
 
3.1%
8 6
 
1.9%
Other values (2) 5
 
1.6%
Hangul
ValueCountFrequency (%)
기 52
 
9.0%
경 50
 
8.7%
시 49
 
8.5%
도 47
 
8.2%
로 45
 
7.8%
구 31
 
5.4%
대 15
 
2.6%
성 14
 
2.4%
수 14
 
2.4%
원 14
 
2.4%
Other values (95) 245
42.5%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.364177
Minimum37.002494
Maximum37.870667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-11T06:20:13.733621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.002494
5-th percentile37.167041
Q137.274961
median37.321619
Q337.426221
95-th percentile37.743149
Maximum37.870667
Range0.8681727
Interquartile range (IQR)0.15125985

Descriptive statistics

Standard deviation0.18238535
Coefficient of variation (CV)0.0048812892
Kurtosis1.7903614
Mean37.364177
Median Absolute Deviation (MAD)0.0725488
Skewness1.0905998
Sum1756.1163
Variance0.033264416
MonotonicityNot monotonic
2023-12-11T06:20:13.862410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
37.8706669 2
 
4.3%
37.4486646 2
 
4.3%
37.3092259 2
 
4.3%
37.677656 1
 
2.1%
37.2224997 1
 
2.1%
37.0024942 1
 
2.1%
37.012023 1
 
2.1%
37.3974124 1
 
2.1%
37.3911404 1
 
2.1%
37.2697491 1
 
2.1%
Other values (34) 34
72.3%
ValueCountFrequency (%)
37.0024942 1
2.1%
37.012023 1
2.1%
37.1555006 1
2.1%
37.1939696 1
2.1%
37.2064924 1
2.1%
37.213135 1
2.1%
37.2224997 1
2.1%
37.2287182 1
2.1%
37.2490706 1
2.1%
37.2668184 1
2.1%
ValueCountFrequency (%)
37.8706669 2
4.3%
37.746371 1
2.1%
37.7356307 1
2.1%
37.677656 1
2.1%
37.5991377 1
2.1%
37.4880968 1
2.1%
37.4844799 1
2.1%
37.4594069 1
2.1%
37.4509367 1
2.1%
37.4486646 2
4.3%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.04985
Minimum126.73356
Maximum127.63267
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-11T06:20:14.013561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.73356
5-th percentile126.79959
Q1126.93133
median127.04342
Q3127.15841
95-th percentile127.26485
Maximum127.63267
Range0.8991112
Interquartile range (IQR)0.22708045

Descriptive statistics

Standard deviation0.17953185
Coefficient of variation (CV)0.0014130819
Kurtosis1.1337381
Mean127.04985
Median Absolute Deviation (MAD)0.1173672
Skewness0.50628995
Sum5971.3431
Variance0.032231686
MonotonicityNot monotonic
2023-12-11T06:20:14.218169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
127.1560281 2
 
4.3%
127.1679792 2
 
4.3%
126.8068989 1
 
2.1%
127.186628 1
 
2.1%
127.230991 1
 
2.1%
127.2637951 1
 
2.1%
126.909147 1
 
2.1%
126.9197922 1
 
2.1%
127.6326708 1
 
2.1%
127.0607782 1
 
2.1%
Other values (35) 35
74.5%
ValueCountFrequency (%)
126.7335596 1
2.1%
126.7360591 1
2.1%
126.7989116 1
2.1%
126.8011595 1
2.1%
126.8032325 1
2.1%
126.8068989 1
2.1%
126.8224448 1
2.1%
126.8348257 1
2.1%
126.8651507 1
2.1%
126.8756868 1
2.1%
ValueCountFrequency (%)
127.6326708 1
2.1%
127.3964396 1
2.1%
127.265306 1
2.1%
127.2637951 1
2.1%
127.2463627 1
2.1%
127.230991 1
2.1%
127.2179572 1
2.1%
127.2106344 1
2.1%
127.186628 1
2.1%
127.1679792 2
4.3%

Interactions

2023-12-11T06:20:08.407111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:07.424921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:07.734169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:08.085140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:08.498201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:07.496980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:07.824360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:08.164061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:08.607600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:07.582673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:07.920159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:08.245122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:08.691639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:07.660836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:08.005610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:08.325422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:20:14.315105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명센터명센터전화번호센터대표자명보육실수소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0001.0001.0000.0600.9921.0001.0000.9350.950
센터명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
센터전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
센터대표자명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
보육실수0.0601.0001.0001.0001.0000.1631.0001.0000.0000.000
소재지우편번호0.9921.0001.0001.0000.1631.0001.0001.0000.8630.791
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도0.9351.0001.0001.0000.0000.8631.0001.0001.0000.275
WGS84경도0.9501.0001.0001.0000.0000.7911.0001.0000.2751.000
2023-12-11T06:20:14.432891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보육실수소재지우편번호WGS84위도WGS84경도시군명
보육실수1.000-0.069-0.059-0.2080.000
소재지우편번호-0.0691.000-0.8540.1540.867
WGS84위도-0.059-0.8541.000-0.1180.661
WGS84경도-0.2080.154-0.1181.0000.698
시군명0.0000.8670.6610.6981.000

Missing values

2023-12-11T06:20:09.079333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:20:09.249445image/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

집계일자시군명센터명센터전화번호센터대표자명보육실수소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
02023-06-30고양시동국대학교031-961-5465이용규14110326경기도 고양시 일산동구 식사동 814-9번지경기도 고양시 일산동구 동국로 3237.677656126.806899
12023-06-30고양시한국항공대학교02-300-0393황재혁3810540경기도 고양시 덕양구 화전동 646-6번지경기도 고양시 덕양구 항공대학로 7637.599138126.865151
22023-06-30군포시군포산업진흥원031-380-7133곽수환3215880경기도 군포시 부곡동 1254번지경기도 군포시 군포첨단산업2로22번길 537.325663126.942863
32023-06-30남양주시경복대학교031-570-9831박주현3012051경기도 남양주시 진접읍 금곡리 383번지경기도 남양주시 진접읍 경복대로 42537.735631127.210634
42023-06-30부천시가톨릭대학교02-2164-6561성재열1214662경기도 부천시 역곡동 산43-1번지경기도 부천시 지봉로 4337.48448126.803232
52023-06-30부천시한국세라믹기술원(부천)031-233-2103박주석1714449경기도 부천시 삼정동 36-1번지경기도 부천시 석천로 39737.488097126.822445
62023-06-30성남시동서울대학교031-720-2182장규순2513117경기도 성남시 수정구 복정동 산42번지경기도 성남시 수정구 복정로 7637.459407127.12954
72023-06-30성남시벤처포럼파트너스070-7858-0004이제열1313488경기도 성남시 분당구 삼평동 690번지경기도 성남시 분당구 판교로 32337.403582127.110302
82023-06-30성남시가천대학교031-750-5317박방주2013120경기도 성남시 수정구 복정동 620-2번지경기도 성남시 수정구 성남대로 134237.450937127.130238
92023-06-30성남시신구대학교031-740-1265김용균5913174경기도 성남시 중원구 금광동 2685번지경기도 성남시 중원구 광명로 37737.448665127.167979
집계일자시군명센터명센터전화번호센터대표자명보육실수소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
372023-06-30용인시단국대학교031-8005-2807조혁1716890경기도 용인시 수지구 죽전동 1491번지경기도 용인시 수지구 죽전로 15237.322646127.125993
382023-06-30용인시강남대학교031-283-6178최유진1516979경기도 용인시 기흥구 구갈동 111번지경기도 용인시 기흥구 강남로 4037.275354127.131959
392023-06-30용인시경기도여성능력개발센터031-270-9767김선영2116922경기도 용인시 기흥구 마북동 431번지경기도 용인시 기흥구 용구대로 231137.292623127.108464
402023-06-30용인시한국외국어대학교031-330-4621박기봉2517035경기도 용인시 처인구 모현읍 왕산리 산55-4번지경기도 용인시 처인구 모현읍 외대로 8137.339151127.265306
412023-06-30의정부시경민대학교031-828-7581정동희6811618경기도 의정부시 가능동 562-1번지경기도 의정부시 서부로 54537.746371127.024326
422023-06-30이천시한국세라믹기술원031-645-1407김경자2717303경기도 이천시 신둔면 수광리 595-7번지경기도 이천시 신둔면 경충대로 332137.320957127.39644
432023-06-30포천시차의과대학교031-850-9345김일형2111160경기도 포천시 동교동 198-1번지경기도 포천시 해룡로 12037.870667127.156028
442023-06-30포천시대진대학교031-539-1281김성수2411159경기도 포천시 선단동 산11-1번지경기도 포천시 호국로 100737.870667127.156028
452023-06-30화성시협성대학교031-299-1346황지온1818330경기도 화성시 봉담읍 상리 14번지경기도 화성시 봉담읍 최루백로 7237.213135126.953346
462023-06-30화성시수원대학교031-222-6589안창주3718323경기도 화성시 봉담읍 와우리 1-2번지경기도 화성시 봉담읍 와우안길 1737.206492126.974923