Overview

Dataset statistics

Number of variables17
Number of observations425
Missing cells450
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory59.9 KiB
Average record size in memory144.3 B

Variable types

Text6
Categorical2
Numeric8
DateTime1

Dataset

Description전라북도 전주시 내 어린이집을 제공하며 어린이집명, 어린이집유형구분, 어린이집전화번호, 어린이집팩스번호, 보육실수 등을 제공합니다
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=1&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15011972

Alerts

데이터기준일자 has constant value ""Constant
보육실수 is highly overall correlated with 보육실면적 and 4 other fieldsHigh correlation
보육실면적 is highly overall correlated with 보육실수 and 4 other fieldsHigh correlation
놀이터수 is highly overall correlated with 보육실수 and 4 other fieldsHigh correlation
보육교직원수 is highly overall correlated with 보육실수 and 4 other fieldsHigh correlation
정원수 is highly overall correlated with 보육실수 and 4 other fieldsHigh correlation
현원수 is highly overall correlated with 보육실수 and 4 other fieldsHigh correlation
어린이집팩스번호 has 74 (17.4%) missing valuesMissing
홈페이지주소 has 376 (88.5%) missing valuesMissing
어린이집전화번호 has unique valuesUnique
놀이터수 has 232 (54.6%) zerosZeros

Reproduction

Analysis started2024-03-13 23:49:07.127043
Analysis finished2024-03-13 23:49:13.691412
Duration6.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct424
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-03-14T08:49:13.814575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length7.6658824
Min length6

Characters and Unicode

Total characters3258
Distinct characters328
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique423 ?
Unique (%)99.5%

Sample

1st rowe편한세상어린이집
2nd rowKCC어린이집
3rd rowNPS국민연금어린이집
4th rowSK뷰 생글어린이집
5th row가나어린이집
ValueCountFrequency (%)
어린이집 5
 
1.1%
아이들세상어린이집 2
 
0.5%
숲속어린이집 2
 
0.5%
전북대학교 1
 
0.2%
전주지방법원직장어린이집 1
 
0.2%
전주삼성어린이집 1
 
0.2%
전주물방울어린이집 1
 
0.2%
수퍼스타어린이집 1
 
0.2%
전주대학교 1
 
0.2%
전주기전대학부설어린이집 1
 
0.2%
Other values (420) 420
96.3%
2024-03-14T08:49:14.109568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
471
 
14.5%
434
 
13.3%
426
 
13.1%
426
 
13.1%
54
 
1.7%
32
 
1.0%
30
 
0.9%
27
 
0.8%
27
 
0.8%
25
 
0.8%
Other values (318) 1306
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3224
99.0%
Uppercase Letter 13
 
0.4%
Space Separator 11
 
0.3%
Decimal Number 4
 
0.1%
Dash Punctuation 2
 
0.1%
Lowercase Letter 2
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
471
 
14.6%
434
 
13.5%
426
 
13.2%
426
 
13.2%
54
 
1.7%
32
 
1.0%
30
 
0.9%
27
 
0.8%
27
 
0.8%
25
 
0.8%
Other values (302) 1272
39.5%
Uppercase Letter
ValueCountFrequency (%)
C 3
23.1%
S 3
23.1%
K 2
15.4%
W 1
 
7.7%
A 1
 
7.7%
Y 1
 
7.7%
N 1
 
7.7%
P 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
4 2
50.0%
2 2
50.0%
Lowercase Letter
ValueCountFrequency (%)
i 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3224
99.0%
Common 19
 
0.6%
Latin 15
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
471
 
14.6%
434
 
13.5%
426
 
13.2%
426
 
13.2%
54
 
1.7%
32
 
1.0%
30
 
0.9%
27
 
0.8%
27
 
0.8%
25
 
0.8%
Other values (302) 1272
39.5%
Latin
ValueCountFrequency (%)
C 3
20.0%
S 3
20.0%
K 2
13.3%
W 1
 
6.7%
A 1
 
6.7%
Y 1
 
6.7%
N 1
 
6.7%
i 1
 
6.7%
P 1
 
6.7%
e 1
 
6.7%
Common
ValueCountFrequency (%)
11
57.9%
4 2
 
10.5%
- 2
 
10.5%
2 2
 
10.5%
) 1
 
5.3%
( 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3224
99.0%
ASCII 34
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
471
 
14.6%
434
 
13.5%
426
 
13.2%
426
 
13.2%
54
 
1.7%
32
 
1.0%
30
 
0.9%
27
 
0.8%
27
 
0.8%
25
 
0.8%
Other values (302) 1272
39.5%
ASCII
ValueCountFrequency (%)
11
32.4%
C 3
 
8.8%
S 3
 
8.8%
K 2
 
5.9%
4 2
 
5.9%
- 2
 
5.9%
2 2
 
5.9%
W 1
 
2.9%
A 1
 
2.9%
Y 1
 
2.9%
Other values (6) 6
17.6%
Distinct7
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
가정
172 
민간
156 
사회복지법인
36 
국공립
35 
법인·단체등
 
13
Other values (2)
 
13

Length

Max length6
Median length2
Mean length2.5435294
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row민간
2nd row민간
3rd row직장
4th row민간
5th row민간

Common Values

ValueCountFrequency (%)
가정 172
40.5%
민간 156
36.7%
사회복지법인 36
 
8.5%
국공립 35
 
8.2%
법인·단체등 13
 
3.1%
직장 12
 
2.8%
협동 1
 
0.2%

Length

2024-03-14T08:49:14.227201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:49:14.327864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가정 172
40.5%
민간 156
36.7%
사회복지법인 36
 
8.5%
국공립 35
 
8.2%
법인·단체등 13
 
3.1%
직장 12
 
2.8%
협동 1
 
0.2%
Distinct425
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-03-14T08:49:14.605198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.009412
Min length12

Characters and Unicode

Total characters5104
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

Unique425 ?
Unique (%)100.0%

Sample

1st row063-251-2131
2nd row063-276-6789
3rd row063-222-6880
4th row063-277-4879
5th row063-244-1355
ValueCountFrequency (%)
063-251-2131 1
 
0.2%
063-246-6004 1
 
0.2%
063-277-3007 1
 
0.2%
063-259-5454 1
 
0.2%
063-287-2035 1
 
0.2%
063-274-7732 1
 
0.2%
063-220-4739 1
 
0.2%
063-271-9637 1
 
0.2%
063-224-5503 1
 
0.2%
063-714-3225 1
 
0.2%
Other values (415) 415
97.6%
2024-03-14T08:49:14.957679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 850
16.7%
2 722
14.1%
3 686
13.4%
0 677
13.3%
6 637
12.5%
7 310
 
6.1%
5 288
 
5.6%
1 288
 
5.6%
4 257
 
5.0%
8 212
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4254
83.3%
Dash Punctuation 850
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 722
17.0%
3 686
16.1%
0 677
15.9%
6 637
15.0%
7 310
7.3%
5 288
 
6.8%
1 288
 
6.8%
4 257
 
6.0%
8 212
 
5.0%
9 177
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 850
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5104
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 850
16.7%
2 722
14.1%
3 686
13.4%
0 677
13.3%
6 637
12.5%
7 310
 
6.1%
5 288
 
5.6%
1 288
 
5.6%
4 257
 
5.0%
8 212
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 850
16.7%
2 722
14.1%
3 686
13.4%
0 677
13.3%
6 637
12.5%
7 310
 
6.1%
5 288
 
5.6%
1 288
 
5.6%
4 257
 
5.0%
8 212
 
4.2%
Distinct349
Distinct (%)99.4%
Missing74
Missing (%)17.4%
Memory size3.4 KiB
2024-03-14T08:49:15.158993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.042735
Min length12

Characters and Unicode

Total characters4227
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

Unique347 ?
Unique (%)98.9%

Sample

1st row063-251-2132
2nd row063-715-6597
3rd row0504-224-1679
4th row063-244-1332
5th row063-226-7563
ValueCountFrequency (%)
063-212-9012 2
 
0.6%
063-212-0009 2
 
0.6%
063-221-0887 1
 
0.3%
063-243-5201 1
 
0.3%
063-236-9002 1
 
0.3%
063-212-4311 1
 
0.3%
063-213-8885 1
 
0.3%
063-223-4480 1
 
0.3%
063-214-7211 1
 
0.3%
063-287-2034 1
 
0.3%
Other values (339) 339
96.6%
2024-03-14T08:49:15.470385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 702
16.6%
2 590
14.0%
3 569
13.5%
0 556
13.2%
6 522
12.3%
7 253
 
6.0%
5 247
 
5.8%
1 231
 
5.5%
4 225
 
5.3%
8 181
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3525
83.4%
Dash Punctuation 702
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 590
16.7%
3 569
16.1%
0 556
15.8%
6 522
14.8%
7 253
7.2%
5 247
7.0%
1 231
 
6.6%
4 225
 
6.4%
8 181
 
5.1%
9 151
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 702
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4227
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 702
16.6%
2 590
14.0%
3 569
13.5%
0 556
13.2%
6 522
12.3%
7 253
 
6.0%
5 247
 
5.8%
1 231
 
5.5%
4 225
 
5.3%
8 181
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4227
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 702
16.6%
2 590
14.0%
3 569
13.5%
0 556
13.2%
6 522
12.3%
7 253
 
6.0%
5 247
 
5.8%
1 231
 
5.5%
4 225
 
5.3%
8 181
 
4.3%

보육실수
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.88
Minimum2
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-14T08:49:15.603643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median4
Q36
95-th percentile8
Maximum18
Range16
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3274814
Coefficient of variation (CV)0.47694292
Kurtosis6.8484301
Mean4.88
Median Absolute Deviation (MAD)1
Skewness2.1971578
Sum2074
Variance5.4171698
MonotonicityNot monotonic
2024-03-14T08:49:15.695801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3 138
32.5%
4 101
23.8%
6 63
14.8%
5 46
 
10.8%
7 33
 
7.8%
8 19
 
4.5%
11 4
 
0.9%
15 4
 
0.9%
2 4
 
0.9%
9 4
 
0.9%
Other values (6) 9
 
2.1%
ValueCountFrequency (%)
2 4
 
0.9%
3 138
32.5%
4 101
23.8%
5 46
 
10.8%
6 63
14.8%
7 33
 
7.8%
8 19
 
4.5%
9 4
 
0.9%
10 3
 
0.7%
11 4
 
0.9%
ValueCountFrequency (%)
18 1
 
0.2%
16 1
 
0.2%
15 4
 
0.9%
14 2
 
0.5%
13 1
 
0.2%
12 1
 
0.2%
11 4
 
0.9%
10 3
 
0.7%
9 4
 
0.9%
8 19
4.5%

보육실면적
Real number (ℝ)

HIGH CORRELATION 

Distinct233
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean174.60706
Minimum27
Maximum1896
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-14T08:49:15.810509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile49.4
Q171
median112
Q3230
95-th percentile481.8
Maximum1896
Range1869
Interquartile range (IQR)159

Descriptive statistics

Standard deviation172.07268
Coefficient of variation (CV)0.98548526
Kurtosis26.261934
Mean174.60706
Median Absolute Deviation (MAD)55
Skewness3.8276065
Sum74208
Variance29609.008
MonotonicityNot monotonic
2024-03-14T08:49:15.920152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
85 17
 
4.0%
60 11
 
2.6%
54 9
 
2.1%
82 7
 
1.6%
62 7
 
1.6%
51 6
 
1.4%
53 6
 
1.4%
112 5
 
1.2%
68 5
 
1.2%
52 5
 
1.2%
Other values (223) 347
81.6%
ValueCountFrequency (%)
27 1
 
0.2%
31 1
 
0.2%
32 1
 
0.2%
34 1
 
0.2%
35 3
0.7%
39 1
 
0.2%
40 2
0.5%
42 2
0.5%
43 4
0.9%
44 2
0.5%
ValueCountFrequency (%)
1896 1
0.2%
1045 1
0.2%
822 1
0.2%
792 1
0.2%
761 1
0.2%
754 1
0.2%
741 2
0.5%
704 1
0.2%
695 1
0.2%
680 1
0.2%

놀이터수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.69882353
Minimum0
Maximum7
Zeros232
Zeros (%)54.6%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-14T08:49:16.009020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.97304401
Coefficient of variation (CV)1.392403
Kurtosis6.2230465
Mean0.69882353
Median Absolute Deviation (MAD)0
Skewness1.9607821
Sum297
Variance0.94681465
MonotonicityNot monotonic
2024-03-14T08:49:16.089177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 232
54.6%
1 121
28.5%
2 51
 
12.0%
3 15
 
3.5%
4 4
 
0.9%
6 1
 
0.2%
7 1
 
0.2%
ValueCountFrequency (%)
0 232
54.6%
1 121
28.5%
2 51
 
12.0%
3 15
 
3.5%
4 4
 
0.9%
6 1
 
0.2%
7 1
 
0.2%
ValueCountFrequency (%)
7 1
 
0.2%
6 1
 
0.2%
4 4
 
0.9%
3 15
 
3.5%
2 51
 
12.0%
1 121
28.5%
0 232
54.6%

보육교직원수
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.3388235
Minimum0
Maximum48
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-14T08:49:16.197632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q15
median8
Q313
95-th percentile19
Maximum48
Range48
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.7300123
Coefficient of variation (CV)0.61356897
Kurtosis6.1641489
Mean9.3388235
Median Absolute Deviation (MAD)3
Skewness1.7630321
Sum3969
Variance32.833041
MonotonicityNot monotonic
2024-03-14T08:49:16.310404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
5 54
12.7%
6 50
11.8%
4 40
 
9.4%
7 36
 
8.5%
8 32
 
7.5%
10 28
 
6.6%
13 27
 
6.4%
12 19
 
4.5%
9 18
 
4.2%
3 14
 
3.3%
Other values (20) 107
25.2%
ValueCountFrequency (%)
0 1
 
0.2%
1 3
 
0.7%
2 9
 
2.1%
3 14
 
3.3%
4 40
9.4%
5 54
12.7%
6 50
11.8%
7 36
8.5%
8 32
7.5%
9 18
 
4.2%
ValueCountFrequency (%)
48 1
 
0.2%
36 1
 
0.2%
34 1
 
0.2%
31 1
 
0.2%
28 1
 
0.2%
26 1
 
0.2%
24 2
 
0.5%
22 1
 
0.2%
21 3
0.7%
20 7
1.6%

정원수
Real number (ℝ)

HIGH CORRELATION 

Distinct103
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.976471
Minimum10
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-14T08:49:16.409723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile13
Q119
median35
Q373
95-th percentile118.8
Maximum300
Range290
Interquartile range (IQR)54

Descriptive statistics

Standard deviation44.598359
Coefficient of variation (CV)0.89238712
Kurtosis8.1931825
Mean49.976471
Median Absolute Deviation (MAD)16
Skewness2.4239848
Sum21240
Variance1989.0136
MonotonicityNot monotonic
2024-03-14T08:49:16.538532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 64
 
15.1%
20 60
 
14.1%
99 26
 
6.1%
13 20
 
4.7%
49 15
 
3.5%
39 11
 
2.6%
48 9
 
2.1%
17 7
 
1.6%
25 7
 
1.6%
79 6
 
1.4%
Other values (93) 200
47.1%
ValueCountFrequency (%)
10 1
 
0.2%
11 3
 
0.7%
12 3
 
0.7%
13 20
 
4.7%
14 2
 
0.5%
15 4
 
0.9%
16 4
 
0.9%
17 7
 
1.6%
18 6
 
1.4%
19 64
15.1%
ValueCountFrequency (%)
300 1
0.2%
288 1
0.2%
272 1
0.2%
265 1
0.2%
250 1
0.2%
240 1
0.2%
214 1
0.2%
210 1
0.2%
200 2
0.5%
181 1
0.2%

현원수
Real number (ℝ)

HIGH CORRELATION 

Distinct103
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.376471
Minimum0
Maximum266
Zeros3
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-14T08:49:16.674739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q113
median20
Q347
95-th percentile91.4
Maximum266
Range266
Interquartile range (IQR)34

Descriptive statistics

Standard deviation33.575449
Coefficient of variation (CV)0.97669855
Kurtosis11.459441
Mean34.376471
Median Absolute Deviation (MAD)11
Skewness2.6658087
Sum14610
Variance1127.3108
MonotonicityNot monotonic
2024-03-14T08:49:16.801596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18 21
 
4.9%
17 20
 
4.7%
19 18
 
4.2%
12 17
 
4.0%
14 17
 
4.0%
11 14
 
3.3%
9 14
 
3.3%
15 13
 
3.1%
13 13
 
3.1%
8 10
 
2.4%
Other values (93) 268
63.1%
ValueCountFrequency (%)
0 3
 
0.7%
1 4
 
0.9%
2 3
 
0.7%
3 4
 
0.9%
4 4
 
0.9%
5 5
 
1.2%
6 5
 
1.2%
7 7
1.6%
8 10
2.4%
9 14
3.3%
ValueCountFrequency (%)
266 1
0.2%
247 1
0.2%
208 1
0.2%
196 1
0.2%
169 1
0.2%
149 1
0.2%
138 1
0.2%
122 1
0.2%
120 1
0.2%
112 1
0.2%
Distinct424
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-03-14T08:49:17.091345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length45
Mean length36.329412
Min length20

Characters and Unicode

Total characters15440
Distinct characters304
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique423 ?
Unique (%)99.5%

Sample

1st row전라북도 전주시 완산구 여울로 161, 관리동(서신동, e편한세상)
2nd row전라북도 전주시 덕진구 세병로 184, 에코시티 kcc스위첸아파트 관리동
3rd row전라북도 전주시 덕진구 기지로 180
4th row전라북도 전주시 완산구 태평2길 22, 관리동(태평동, 태평SKVIEW)
5th row전라북도 전주시 덕진구 안덕원1길 41 (우아동3가)
ValueCountFrequency (%)
전라북도 425
 
14.5%
전주시 425
 
14.5%
덕진구 227
 
7.8%
완산구 198
 
6.8%
관리동 54
 
1.8%
101동 23
 
0.8%
102동 19
 
0.6%
세병로 16
 
0.5%
중화산동2가 14
 
0.5%
104동 14
 
0.5%
Other values (853) 1514
51.7%
2024-03-14T08:49:17.467273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2558
 
16.6%
869
 
5.6%
1 818
 
5.3%
588
 
3.8%
473
 
3.1%
454
 
2.9%
, 452
 
2.9%
437
 
2.8%
435
 
2.8%
430
 
2.8%
Other values (294) 7926
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9235
59.8%
Space Separator 2558
 
16.6%
Decimal Number 2476
 
16.0%
Other Punctuation 453
 
2.9%
Close Punctuation 297
 
1.9%
Open Punctuation 297
 
1.9%
Dash Punctuation 98
 
0.6%
Uppercase Letter 18
 
0.1%
Lowercase Letter 7
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
869
 
9.4%
588
 
6.4%
473
 
5.1%
454
 
4.9%
437
 
4.7%
435
 
4.7%
430
 
4.7%
428
 
4.6%
275
 
3.0%
262
 
2.8%
Other values (262) 4584
49.6%
Decimal Number
ValueCountFrequency (%)
1 818
33.0%
0 390
15.8%
2 380
15.3%
3 238
 
9.6%
5 162
 
6.5%
4 159
 
6.4%
6 105
 
4.2%
7 91
 
3.7%
8 68
 
2.7%
9 65
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
C 3
16.7%
K 3
16.7%
S 3
16.7%
H 2
11.1%
L 2
11.1%
A 1
 
5.6%
V 1
 
5.6%
I 1
 
5.6%
E 1
 
5.6%
W 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
c 2
28.6%
k 1
14.3%
h 1
14.3%
l 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 452
99.8%
@ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2558
100.0%
Close Punctuation
ValueCountFrequency (%)
) 297
100.0%
Open Punctuation
ValueCountFrequency (%)
( 297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9235
59.8%
Common 6179
40.0%
Latin 26
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
869
 
9.4%
588
 
6.4%
473
 
5.1%
454
 
4.9%
437
 
4.7%
435
 
4.7%
430
 
4.7%
428
 
4.6%
275
 
3.0%
262
 
2.8%
Other values (262) 4584
49.6%
Common
ValueCountFrequency (%)
2558
41.4%
1 818
 
13.2%
, 452
 
7.3%
0 390
 
6.3%
2 380
 
6.1%
) 297
 
4.8%
( 297
 
4.8%
3 238
 
3.9%
5 162
 
2.6%
4 159
 
2.6%
Other values (6) 428
 
6.9%
Latin
ValueCountFrequency (%)
C 3
11.5%
K 3
11.5%
S 3
11.5%
H 2
 
7.7%
e 2
 
7.7%
c 2
 
7.7%
L 2
 
7.7%
k 1
 
3.8%
h 1
 
3.8%
1
 
3.8%
Other values (6) 6
23.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9235
59.8%
ASCII 6204
40.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2558
41.2%
1 818
 
13.2%
, 452
 
7.3%
0 390
 
6.3%
2 380
 
6.1%
) 297
 
4.8%
( 297
 
4.8%
3 238
 
3.8%
5 162
 
2.6%
4 159
 
2.6%
Other values (21) 453
 
7.3%
Hangul
ValueCountFrequency (%)
869
 
9.4%
588
 
6.4%
473
 
5.1%
454
 
4.9%
437
 
4.7%
435
 
4.7%
430
 
4.7%
428
 
4.6%
275
 
3.0%
262
 
2.8%
Other values (262) 4584
49.6%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct341
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-03-14T08:49:17.647104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length23.162353
Min length19

Characters and Unicode

Total characters9844
Distinct characters62
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

Unique285 ?
Unique (%)67.1%

Sample

1st row전라북도 전주시 완산구 서신동 572
2nd row전라북도 전주시 덕진구 송천동2가 1298
3rd row전라북도 전주시 덕진구 만성동 1165
4th row전라북도 전주시 완산구 태평동 291
5th row전라북도 전주시 덕진구 우아동3가 450
ValueCountFrequency (%)
전라북도 425
20.0%
전주시 425
20.0%
덕진구 227
 
10.7%
완산구 198
 
9.3%
송천동2가 41
 
1.9%
평화동2가 39
 
1.8%
인후동1가 35
 
1.6%
삼천동1가 28
 
1.3%
서신동 28
 
1.3%
송천동1가 27
 
1.3%
Other values (378) 655
30.8%
2024-03-14T08:49:17.922005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1703
17.3%
850
 
8.6%
1 437
 
4.4%
430
 
4.4%
429
 
4.4%
425
 
4.3%
425
 
4.3%
425
 
4.3%
425
 
4.3%
425
 
4.3%
Other values (52) 3870
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5868
59.6%
Decimal Number 2003
 
20.3%
Space Separator 1703
 
17.3%
Dash Punctuation 270
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
850
14.5%
430
 
7.3%
429
 
7.3%
425
 
7.2%
425
 
7.2%
425
 
7.2%
425
 
7.2%
425
 
7.2%
326
 
5.6%
250
 
4.3%
Other values (40) 1458
24.8%
Decimal Number
ValueCountFrequency (%)
1 437
21.8%
2 351
17.5%
3 204
10.2%
6 170
 
8.5%
7 147
 
7.3%
5 145
 
7.2%
9 144
 
7.2%
8 137
 
6.8%
0 136
 
6.8%
4 132
 
6.6%
Space Separator
ValueCountFrequency (%)
1703
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5868
59.6%
Common 3976
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
850
14.5%
430
 
7.3%
429
 
7.3%
425
 
7.2%
425
 
7.2%
425
 
7.2%
425
 
7.2%
425
 
7.2%
326
 
5.6%
250
 
4.3%
Other values (40) 1458
24.8%
Common
ValueCountFrequency (%)
1703
42.8%
1 437
 
11.0%
2 351
 
8.8%
- 270
 
6.8%
3 204
 
5.1%
6 170
 
4.3%
7 147
 
3.7%
5 145
 
3.6%
9 144
 
3.6%
8 137
 
3.4%
Other values (2) 268
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5868
59.6%
ASCII 3976
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1703
42.8%
1 437
 
11.0%
2 351
 
8.8%
- 270
 
6.8%
3 204
 
5.1%
6 170
 
4.3%
7 147
 
3.7%
5 145
 
3.6%
9 144
 
3.6%
8 137
 
3.4%
Other values (2) 268
 
6.7%
Hangul
ValueCountFrequency (%)
850
14.5%
430
 
7.3%
429
 
7.3%
425
 
7.2%
425
 
7.2%
425
 
7.2%
425
 
7.2%
425
 
7.2%
326
 
5.6%
250
 
4.3%
Other values (40) 1458
24.8%

위도
Real number (ℝ)

Distinct352
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.831685
Minimum35.768236
Maximum35.881241
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-14T08:49:18.274666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.768236
5-th percentile35.787393
Q135.807829
median35.833754
Q335.855967
95-th percentile35.872927
Maximum35.881241
Range0.11300449
Interquartile range (IQR)0.04813787

Descriptive statistics

Standard deviation0.027736147
Coefficient of variation (CV)0.00077406761
Kurtosis-1.0652229
Mean35.831685
Median Absolute Deviation (MAD)0.02494586
Skewness-0.1055393
Sum15228.466
Variance0.00076929386
MonotonicityNot monotonic
2024-03-14T08:49:18.389198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.86931383 6
 
1.4%
35.8682208 6
 
1.4%
35.83783767 5
 
1.2%
35.83994842 4
 
0.9%
35.78510176 4
 
0.9%
35.83895266 3
 
0.7%
35.79344236 3
 
0.7%
35.79572647 3
 
0.7%
35.86790491 3
 
0.7%
35.83611797 3
 
0.7%
Other values (342) 385
90.6%
ValueCountFrequency (%)
35.76823649 1
0.2%
35.77876997 1
0.2%
35.78038033 1
0.2%
35.78203212 1
0.2%
35.78237872 2
0.5%
35.78321464 1
0.2%
35.78399198 1
0.2%
35.78426779 1
0.2%
35.78428617 1
0.2%
35.78452294 1
0.2%
ValueCountFrequency (%)
35.88124098 1
0.2%
35.88027422 1
0.2%
35.88012127 1
0.2%
35.87799168 2
0.5%
35.87727093 1
0.2%
35.87661027 1
0.2%
35.87618178 1
0.2%
35.87576527 1
0.2%
35.87540248 1
0.2%
35.87524058 2
0.5%

경도
Real number (ℝ)

Distinct352
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12208
Minimum127.05554
Maximum127.19065
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-14T08:49:18.515536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05554
5-th percentile127.072
Q1127.11016
median127.12349
Q3127.13553
95-th percentile127.16471
Maximum127.19065
Range0.1351101
Interquartile range (IQR)0.0253789

Descriptive statistics

Standard deviation0.025872781
Coefficient of variation (CV)0.00020352705
Kurtosis0.091477789
Mean127.12208
Median Absolute Deviation (MAD)0.0127001
Skewness-0.34631412
Sum54026.882
Variance0.00066940078
MonotonicityNot monotonic
2024-03-14T08:49:18.649229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1244985 6
 
1.4%
127.1283436 6
 
1.4%
127.1537743 5
 
1.2%
127.1548923 4
 
0.9%
127.1331957 4
 
0.9%
127.1133424 3
 
0.7%
127.1151093 3
 
0.7%
127.1152545 3
 
0.7%
127.0771191 3
 
0.7%
127.1192697 3
 
0.7%
Other values (342) 385
90.6%
ValueCountFrequency (%)
127.0555384 1
0.2%
127.0564009 1
0.2%
127.0573225 2
0.5%
127.0576599 1
0.2%
127.0589108 1
0.2%
127.0601163 1
0.2%
127.0604973 1
0.2%
127.0609765 1
0.2%
127.0610976 1
0.2%
127.062305 2
0.5%
ValueCountFrequency (%)
127.1906485 1
0.2%
127.1722289 1
0.2%
127.1721222 1
0.2%
127.1718914 1
0.2%
127.1718202 1
0.2%
127.1709512 1
0.2%
127.170484 1
0.2%
127.169083 1
0.2%
127.1687272 1
0.2%
127.1684262 1
0.2%
Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
운영
303 
미운영
121 
<NA>
 
1

Length

Max length4
Median length2
Mean length2.2894118
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
운영 303
71.3%
미운영 121
 
28.5%
<NA> 1
 
0.2%

Length

2024-03-14T08:49:18.824243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:49:18.936030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영 303
71.3%
미운영 121
 
28.5%
na 1
 
0.2%

홈페이지주소
Text

MISSING 

Distinct49
Distinct (%)100.0%
Missing376
Missing (%)88.5%
Memory size3.4 KiB
2024-03-14T08:49:19.144376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length32
Mean length23.387755
Min length8

Characters and Unicode

Total characters1146
Distinct characters58
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st rowhttp://m.nps.or.kr
2nd rowcafe.daum.net/greenilove
3rd rowhttps://www.comwel.or.kr/kidsㅡjeonju/index.jsp
4th rowhttps://cafe.naver.com/nambok97
5th rowwww.sarang-namoo.com
ValueCountFrequency (%)
http://kids.paulchurch.com 1
 
2.0%
chulmam@hanmail.net 1
 
2.0%
http://www.영생어린이집.com 1
 
2.0%
his7403@naver.com 1
 
2.0%
http://www.yetni.com 1
 
2.0%
cafe.daum.net/kidorange 1
 
2.0%
http://wooa.or.kr 1
 
2.0%
www.n-kid.com 1
 
2.0%
https://hansol-jbpolice.kidsnote.ac/home/main 1
 
2.0%
https://cafe.naver.com/chonbukkindergarten 1
 
2.0%
Other values (41) 41
80.4%
2024-03-14T08:49:19.498604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 89
 
7.8%
a 83
 
7.2%
n 73
 
6.4%
/ 65
 
5.7%
t 65
 
5.7%
e 63
 
5.5%
o 61
 
5.3%
m 57
 
5.0%
w 50
 
4.4%
h 47
 
4.1%
Other values (48) 493
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 866
75.6%
Other Punctuation 187
 
16.3%
Decimal Number 59
 
5.1%
Other Letter 20
 
1.7%
Dash Punctuation 10
 
0.9%
Uppercase Letter 2
 
0.2%
Space Separator 2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 83
 
9.6%
n 73
 
8.4%
t 65
 
7.5%
e 63
 
7.3%
o 61
 
7.0%
m 57
 
6.6%
w 50
 
5.8%
h 47
 
5.4%
c 47
 
5.4%
r 42
 
4.8%
Other values (15) 278
32.1%
Other Letter
ValueCountFrequency (%)
2
 
10.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (6) 6
30.0%
Decimal Number
ValueCountFrequency (%)
0 13
22.0%
1 11
18.6%
2 7
11.9%
7 6
10.2%
3 5
 
8.5%
5 4
 
6.8%
4 4
 
6.8%
9 4
 
6.8%
8 3
 
5.1%
6 2
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 89
47.6%
/ 65
34.8%
: 20
 
10.7%
@ 13
 
7.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
Q 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 868
75.7%
Common 258
 
22.5%
Hangul 20
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 83
 
9.6%
n 73
 
8.4%
t 65
 
7.5%
e 63
 
7.3%
o 61
 
7.0%
m 57
 
6.6%
w 50
 
5.8%
h 47
 
5.4%
c 47
 
5.4%
r 42
 
4.8%
Other values (16) 280
32.3%
Common
ValueCountFrequency (%)
. 89
34.5%
/ 65
25.2%
: 20
 
7.8%
@ 13
 
5.0%
0 13
 
5.0%
1 11
 
4.3%
- 10
 
3.9%
2 7
 
2.7%
7 6
 
2.3%
3 5
 
1.9%
Other values (6) 19
 
7.4%
Hangul
ValueCountFrequency (%)
2
 
10.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (6) 6
30.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1126
98.3%
Hangul 19
 
1.7%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 89
 
7.9%
a 83
 
7.4%
n 73
 
6.5%
/ 65
 
5.8%
t 65
 
5.8%
e 63
 
5.6%
o 61
 
5.4%
m 57
 
5.1%
w 50
 
4.4%
h 47
 
4.2%
Other values (32) 473
42.0%
Hangul
ValueCountFrequency (%)
2
 
10.5%
2
 
10.5%
2
 
10.5%
2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (5) 5
26.3%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum2023-11-16 00:00:00
Maximum2023-11-16 00:00:00
2024-03-14T08:49:19.590265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:19.658923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T08:49:12.695183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:07.813966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.537144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.143197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.790523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.554896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.222147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.792353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:12.787263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:07.933563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.621927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.249261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.895894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.643903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.301021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.877326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:12.876942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.063565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.700029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.331551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.969384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.725436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.376879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.959785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:12.954393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.161817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.785449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.405039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.051934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.808524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.451386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:12.029424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:13.021853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.232263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.854193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.472197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.195102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.885191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.515858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:12.097153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:13.091634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.307658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.926472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.544651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.330961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.967785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.584171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:12.171385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:13.161896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.376594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.993431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.622971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.413088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.057807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.647337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:12.560824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:13.232580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:08.454673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.067848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:09.709370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:10.484056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.148297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:11.715567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:49:12.625594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T08:49:19.732624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
어린이집유형구분보육실수보육실면적놀이터수보육교직원수정원수현원수위도경도통학차량운영여부홈페이지주소
어린이집유형구분1.0000.5270.6270.5750.5190.5860.5120.3050.1840.3061.000
보육실수0.5271.0000.7270.5750.7860.9350.8220.3120.2830.1911.000
보육실면적0.6270.7271.0000.6250.8620.8190.7920.2980.2520.1861.000
놀이터수0.5750.5750.6251.0000.5040.5700.5300.2520.2480.0601.000
보육교직원수0.5190.7860.8620.5041.0000.8230.9670.1570.2170.2261.000
정원수0.5860.9350.8190.5700.8231.0000.8480.2110.2750.1941.000
현원수0.5120.8220.7920.5300.9670.8481.0000.1770.2500.1271.000
위도0.3050.3120.2980.2520.1570.2110.1771.0000.6790.2451.000
경도0.1840.2830.2520.2480.2170.2750.2500.6791.0000.2091.000
통학차량운영여부0.3060.1910.1860.0600.2260.1940.1270.2450.2091.0001.000
홈페이지주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-03-14T08:49:19.844306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통학차량운영여부어린이집유형구분
통학차량운영여부1.0000.325
어린이집유형구분0.3251.000
2024-03-14T08:49:19.924910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보육실수보육실면적놀이터수보육교직원수정원수현원수위도경도어린이집유형구분통학차량운영여부
보육실수1.0000.8580.6730.7660.8410.786-0.045-0.0230.2970.140
보육실면적0.8581.0000.6830.7880.9260.826-0.021-0.0110.2610.198
놀이터수0.6730.6831.0000.6270.6830.6530.0690.0660.2320.064
보육교직원수0.7660.7880.6271.0000.8230.9430.094-0.0470.3050.218
정원수0.8410.9260.6830.8231.0000.8770.0740.0080.3310.139
현원수0.7860.8260.6530.9430.8771.0000.111-0.0300.3000.125
위도-0.045-0.0210.0690.0940.0740.1111.000-0.0280.1580.186
경도-0.023-0.0110.066-0.0470.008-0.030-0.0281.0000.0930.159
어린이집유형구분0.2970.2610.2320.3050.3310.3000.1580.0931.0000.325
통학차량운영여부0.1400.1980.0640.2180.1390.1250.1860.1590.3251.000

Missing values

2024-03-14T08:49:13.347011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T08:49:13.544221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-14T08:49:13.645042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

어린이집명어린이집유형구분어린이집전화번호어린이집팩스번호보육실수보육실면적놀이터수보육교직원수정원수현원수도로명주소지번주소위도경도통학차량운영여부홈페이지주소데이터기준일자
0e편한세상어린이집민간063-251-2131063-251-21324112062616전라북도 전주시 완산구 여울로 161, 관리동(서신동, e편한세상)전라북도 전주시 완산구 서신동 57235.840714127.106499운영<NA>2023-11-16
1KCC어린이집민간063-276-6789<NA>72082157874전라북도 전주시 덕진구 세병로 184, 에코시티 kcc스위첸아파트 관리동전라북도 전주시 덕진구 송천동2가 129835.881241127.131121미운영<NA>2023-11-16
2NPS국민연금어린이집직장063-222-6880063-715-6597837411711063전라북도 전주시 덕진구 기지로 180전라북도 전주시 덕진구 만성동 116535.837317127.071817미운영http://m.nps.or.kr2023-11-16
3SK뷰 생글어린이집민간063-277-48790504-224-167961380144544전라북도 전주시 완산구 태평2길 22, 관리동(태평동, 태평SKVIEW)전라북도 전주시 완산구 태평동 29135.824741127.140032운영<NA>2023-11-16
4가나어린이집민간063-244-1355063-244-13324106073020전라북도 전주시 덕진구 안덕원1길 41 (우아동3가)전라북도 전주시 덕진구 우아동3가 45035.839862127.165852운영<NA>2023-11-16
5가은어린이집가정063-226-7563063-226-756349202203전라북도 전주시 완산구 삼천천변1길 46, 관리동(삼천동1가, 흥건삼천1차)전라북도 전주시 완산구 삼천동1가 300-335.79431127.115279미운영<NA>2023-11-16
6개구쟁이어린이집가정063-226-4352063-226-435234304208전라북도 전주시 완산구 하거마4길 16 (삼천동1가)전라북도 전주시 완산구 삼천동1가 648-535.795315127.118571운영<NA>2023-11-16
7고감도어린이집민간063-222-1837063-228-18371143021810584전라북도 전주시 완산구 양지2길 5 (평화동2가)전라북도 전주시 완산구 평화동2가 570-135.792576127.123491운영<NA>2023-11-16
8고운미래어린이집법인·단체등063-242-4005<NA>4136084824전라북도 전주시 덕진구 진버들5길 21, 더샵인후센트럴아파트 관리동전라북도 전주시 덕진구 인후동1가 104335.836872127.163922미운영<NA>2023-11-16
9고운손가정어린이집가정063-273-0950063-273-095035304199전라북도 전주시 덕진구 솔내로 142, 102동 107호(송천동1가, 송천신일)전라북도 전주시 덕진구 송천동1가 101-335.862608127.128759운영<NA>2023-11-16
어린이집명어린이집유형구분어린이집전화번호어린이집팩스번호보육실수보육실면적놀이터수보육교직원수정원수현원수도로명주소지번주소위도경도통학차량운영여부홈페이지주소데이터기준일자
415휴먼빌사랑어린이집민간063-252-5306<NA>61441144646전라북도 전주시 덕진구 세병로 74, 에코휴먼빌아파트 관리동전라북도 전주시 덕진구 송천동2가 134135.871314127.132089운영<NA>2023-11-16
416휴먼빌어린이집가정063-908-8876063-908-887635704198전라북도 전주시 덕진구 가리내로 216, 501동 103호(덕진동2가, 휴먼빌아파트)전라북도 전주시 덕진구 덕진동2가 69735.838953127.113342미운영<NA>2023-11-16
417휴먼시아맑은샘어린이집국공립063-223-3883063-223-388741570123430전라북도 전주시 완산구 용호로 20, 307동 1층(효자동2가, 휴먼시아3단지아파트)전라북도 전주시 완산구 효자동2가 1201-235.807682127.101649미운영<NA>2023-11-16
418휴먼시아밝은빛어린이집국공립063-223-0103063-223-013241311104725전라북도 전주시 완산구 호암로 88, 관리동1층(효자동2가, 효자휴먼시아6단지)전라북도 전주시 완산구 효자동2가 1320-135.807829127.102713운영<NA>2023-11-16
419휴먼시아숲속어린이집국공립063-223-6543063-223-654241590103730전라북도 전주시 완산구 호암로 2, 1블럭관리동내(효자동2가, 휴먼시아)전라북도 전주시 완산구 효자동2가 1191-135.807484127.096135미운영<NA>2023-11-16
420휴먼시아해오름어린이집국공립063-236-0131063-236-013251270164742전라북도 전주시 완산구 호암로 87, 관리동(효자동2가, 휴먼시아5단지)전라북도 전주시 완산구 효자동2가 1316-135.809231127.103564운영<NA>2023-11-16
421휴플러스어린이집가정063-228-7075<NA>48404199전라북도 전주시 완산구 따박골4길 10, 104동 104호(효자동1가, 한신휴플러스)전라북도 전주시 완산구 효자동1가 79935.806716127.127813미운영<NA>2023-11-16
422희망어린이집가정063-902-1228063-902-1228362042012전라북도 전주시 덕진구 호성로 136, 202동 103호(호성동1가, 진흥더블파크아파트)전라북도 전주시 덕진구 호성동1가 85135.864349127.147526운영<NA>2023-11-16
423희망찬어린이집가정063-246-5406063-246-5406378061914전라북도 전주시 덕진구 호성2길 16, 101동 101호(호성동1가, 동아)전라북도 전주시 덕진구 호성동1가 82635.85942127.15217운영<NA>2023-11-16
424힐스테이트어린이집민간063-221-2550063-221-055041000102929전라북도 전주시 완산구 세내로 291전라북도 전주시 완산구 효자동3가 1540-335.81641127.111519미운영<NA>2023-11-16