Overview

Dataset statistics

Number of variables14
Number of observations143
Missing cells23
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.9 KiB
Average record size in memory120.9 B

Variable types

Text4
Categorical3
Numeric7

Dataset

Description전라북도 군산시에 소재한 어린이집(어린이집명, 어린이집유형, 전화번호, 팩스번호, 보육실수, 보육실면적, 놀이터수, 보육교직원현원, 정원, 아동현원, 주소, 통학차량운영, 위도, 경도)현황을 나타냅니다.
URLhttps://www.data.go.kr/data/15117000/fileData.do

Alerts

보육실수 is highly overall correlated with 보육실면적 and 3 other fieldsHigh correlation
보육실면적 is highly overall correlated with 보육실수 and 3 other fieldsHigh correlation
보육교직원현원 is highly overall correlated with 보육실수 and 3 other fieldsHigh correlation
정원 is highly overall correlated with 보육실수 and 3 other fieldsHigh correlation
아동현원 is highly overall correlated with 보육실수 and 3 other fieldsHigh correlation
팩스번호 has 23 (16.1%) missing valuesMissing
어린이집명 has unique valuesUnique
전화번호 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:56:40.852909
Analysis finished2023-12-12 07:56:46.618757
Duration5.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

어린이집명
Text

UNIQUE 

Distinct143
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T16:56:46.847817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.3986014
Min length6

Characters and Unicode

Total characters1058
Distinct characters207
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

Unique143 ?
Unique (%)100.0%

Sample

1st rowOCI어린이집
2nd rowe편한세상어린이집
3rd row가람어린이집
4th row개정어린이집
5th row군산키즈궁어린이집
ValueCountFrequency (%)
oci어린이집 1
 
0.7%
우리어린이집 1
 
0.7%
월명어린이집 1
 
0.7%
유리바다어린이집 1
 
0.7%
이삭몬테소리어린이집 1
 
0.7%
이화어린이집 1
 
0.7%
재미난어린이집 1
 
0.7%
정다운어린이집 1
 
0.7%
원광어린이집 1
 
0.7%
천사어린이집 1
 
0.7%
Other values (133) 133
93.0%
2023-12-12T16:56:47.290572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 157
 
14.8%
린 145
 
13.7%
어 144
 
13.6%
집 143
 
13.5%
나 15
 
1.4%
키 14
 
1.3%
아 13
 
1.2%
리 12
 
1.1%
즈 12
 
1.1%
한 8
 
0.8%
Other values (197) 395
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1053
99.5%
Uppercase Letter 3
 
0.3%
Decimal Number 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 157
14.9%
린 145
 
13.8%
어 144
 
13.7%
집 143
 
13.6%
나 15
 
1.4%
키 14
 
1.3%
아 13
 
1.2%
리 12
 
1.1%
즈 12
 
1.1%
한 8
 
0.8%
Other values (192) 390
37.0%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
I 1
33.3%
C 1
33.3%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1053
99.5%
Latin 4
 
0.4%
Common 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 157
14.9%
린 145
 
13.8%
어 144
 
13.7%
집 143
 
13.6%
나 15
 
1.4%
키 14
 
1.3%
아 13
 
1.2%
리 12
 
1.1%
즈 12
 
1.1%
한 8
 
0.8%
Other values (192) 390
37.0%
Latin
ValueCountFrequency (%)
O 1
25.0%
e 1
25.0%
I 1
25.0%
C 1
25.0%
Common
ValueCountFrequency (%)
3 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1053
99.5%
ASCII 5
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 157
14.9%
린 145
 
13.8%
어 144
 
13.7%
집 143
 
13.6%
나 15
 
1.4%
키 14
 
1.3%
아 13
 
1.2%
리 12
 
1.1%
즈 12
 
1.1%
한 8
 
0.8%
Other values (192) 390
37.0%
ASCII
ValueCountFrequency (%)
O 1
20.0%
3 1
20.0%
e 1
20.0%
I 1
20.0%
C 1
20.0%

어린이집유형
Categorical

Distinct6
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
민간
47 
가정
40 
국공립
24 
사회복지법인
18 
법인+단체
8 

Length

Max length6
Median length2
Mean length2.8391608
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row직장
2nd row국공립
3rd row가정
4th row사회복지법인
5th row국공립

Common Values

ValueCountFrequency (%)
민간 47
32.9%
가정 40
28.0%
국공립 24
16.8%
사회복지법인 18
 
12.6%
법인+단체 8
 
5.6%
직장 6
 
4.2%

Length

2023-12-12T16:56:47.485735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:47.619403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간 47
32.9%
가정 40
28.0%
국공립 24
16.8%
사회복지법인 18
 
12.6%
법인+단체 8
 
5.6%
직장 6
 
4.2%

전화번호
Text

UNIQUE 

Distinct143
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T16:56:47.913943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.013986
Min length12

Characters and Unicode

Total characters1718
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

Unique143 ?
Unique (%)100.0%

Sample

1st row063-465-7981
2nd row063-442-5400
3rd row063-463-7667
4th row063-451-5132
5th row063-462-2213
ValueCountFrequency (%)
063-465-7981 1
 
0.7%
063-442-6388 1
 
0.7%
063-462-3044 1
 
0.7%
063-463-7787 1
 
0.7%
063-463-4906 1
 
0.7%
063-464-6040 1
 
0.7%
063-467-8333 1
 
0.7%
063-451-7787 1
 
0.7%
063-463-8811 1
 
0.7%
063-465-6462 1
 
0.7%
Other values (133) 133
93.0%
2023-12-12T16:56:48.270185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 292
17.0%
- 286
16.6%
0 242
14.1%
3 213
12.4%
4 201
11.7%
5 100
 
5.8%
1 99
 
5.8%
7 86
 
5.0%
2 80
 
4.7%
9 66
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1432
83.4%
Dash Punctuation 286
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 292
20.4%
0 242
16.9%
3 213
14.9%
4 201
14.0%
5 100
 
7.0%
1 99
 
6.9%
7 86
 
6.0%
2 80
 
5.6%
9 66
 
4.6%
8 53
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 286
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1718
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 292
17.0%
- 286
16.6%
0 242
14.1%
3 213
12.4%
4 201
11.7%
5 100
 
5.8%
1 99
 
5.8%
7 86
 
5.0%
2 80
 
4.7%
9 66
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1718
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 292
17.0%
- 286
16.6%
0 242
14.1%
3 213
12.4%
4 201
11.7%
5 100
 
5.8%
1 99
 
5.8%
7 86
 
5.0%
2 80
 
4.7%
9 66
 
3.8%

팩스번호
Text

MISSING 

Distinct120
Distinct (%)100.0%
Missing23
Missing (%)16.1%
Memory size1.2 KiB
2023-12-12T16:56:48.591576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.016667
Min length12

Characters and Unicode

Total characters1442
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

Unique120 ?
Unique (%)100.0%

Sample

1st row063-465-7982
2nd row0504-228-0062
3rd row063-451-1151
4th row063-445-1636
5th row063-465-1610
ValueCountFrequency (%)
063-451-9984 1
 
0.8%
0504-228-0062 1
 
0.8%
063-465-5311 1
 
0.8%
063-466-5955 1
 
0.8%
063-467-2658 1
 
0.8%
063-442-6220 1
 
0.8%
063-467-3700 1
 
0.8%
063-463-9309 1
 
0.8%
063-462-7641 1
 
0.8%
063-910-2242 1
 
0.8%
Other values (110) 110
91.7%
2023-12-12T16:56:49.009429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 243
16.9%
- 240
16.6%
0 199
13.8%
4 178
12.3%
3 174
12.1%
1 81
 
5.6%
2 77
 
5.3%
5 74
 
5.1%
9 63
 
4.4%
8 57
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1202
83.4%
Dash Punctuation 240
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 243
20.2%
0 199
16.6%
4 178
14.8%
3 174
14.5%
1 81
 
6.7%
2 77
 
6.4%
5 74
 
6.2%
9 63
 
5.2%
8 57
 
4.7%
7 56
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 243
16.9%
- 240
16.6%
0 199
13.8%
4 178
12.3%
3 174
12.1%
1 81
 
5.6%
2 77
 
5.3%
5 74
 
5.1%
9 63
 
4.4%
8 57
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 243
16.9%
- 240
16.6%
0 199
13.8%
4 178
12.3%
3 174
12.1%
1 81
 
5.6%
2 77
 
5.3%
5 74
 
5.1%
9 63
 
4.4%
8 57
 
4.0%

보육실수
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2587413
Minimum2
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:56:49.138564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q14
median5
Q36
95-th percentile8
Maximum17
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.020017
Coefficient of variation (CV)0.38412558
Kurtosis8.4060956
Mean5.2587413
Median Absolute Deviation (MAD)1
Skewness2.1512849
Sum752
Variance4.0804688
MonotonicityNot monotonic
2023-12-12T16:56:49.261600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
4 49
34.3%
5 26
18.2%
6 22
15.4%
7 15
 
10.5%
3 15
 
10.5%
8 8
 
5.6%
9 3
 
2.1%
10 1
 
0.7%
17 1
 
0.7%
11 1
 
0.7%
Other values (2) 2
 
1.4%
ValueCountFrequency (%)
2 1
 
0.7%
3 15
 
10.5%
4 49
34.3%
5 26
18.2%
6 22
15.4%
7 15
 
10.5%
8 8
 
5.6%
9 3
 
2.1%
10 1
 
0.7%
11 1
 
0.7%
ValueCountFrequency (%)
17 1
 
0.7%
13 1
 
0.7%
11 1
 
0.7%
10 1
 
0.7%
9 3
 
2.1%
8 8
 
5.6%
7 15
 
10.5%
6 22
15.4%
5 26
18.2%
4 49
34.3%

보육실면적
Real number (ℝ)

HIGH CORRELATION 

Distinct113
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean179.34266
Minimum42
Maximum927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:56:49.467076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile60
Q185.5
median148
Q3241.5
95-th percentile375.8
Maximum927
Range885
Interquartile range (IQR)156

Descriptive statistics

Standard deviation124.55663
Coefficient of variation (CV)0.69451758
Kurtosis8.7850285
Mean179.34266
Median Absolute Deviation (MAD)71
Skewness2.2042322
Sum25646
Variance15514.354
MonotonicityNot monotonic
2023-12-12T16:56:49.633099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
61 4
 
2.8%
115 4
 
2.8%
148 4
 
2.8%
60 3
 
2.1%
65 3
 
2.1%
96 3
 
2.1%
63 3
 
2.1%
129 2
 
1.4%
196 2
 
1.4%
226 2
 
1.4%
Other values (103) 113
79.0%
ValueCountFrequency (%)
42 1
 
0.7%
48 2
1.4%
54 1
 
0.7%
56 1
 
0.7%
58 1
 
0.7%
59 1
 
0.7%
60 3
2.1%
61 4
2.8%
63 3
2.1%
64 2
1.4%
ValueCountFrequency (%)
927 1
0.7%
562 1
0.7%
518 1
0.7%
503 1
0.7%
466 1
0.7%
445 1
0.7%
385 1
0.7%
376 1
0.7%
374 1
0.7%
363 1
0.7%

놀이터수
Categorical

Distinct5
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
65 
0
57 
2
14 
3
 
5
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row3

Common Values

ValueCountFrequency (%)
1 65
45.5%
0 57
39.9%
2 14
 
9.8%
3 5
 
3.5%
4 2
 
1.4%

Length

2023-12-12T16:56:49.797559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:49.927576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 65
45.5%
0 57
39.9%
2 14
 
9.8%
3 5
 
3.5%
4 2
 
1.4%

보육교직원현원
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.153846
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:56:50.048928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q17
median9
Q313
95-th percentile17.9
Maximum31
Range30
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.5506658
Coefficient of variation (CV)0.44817163
Kurtosis2.1602465
Mean10.153846
Median Absolute Deviation (MAD)3
Skewness1.0833426
Sum1452
Variance20.708559
MonotonicityNot monotonic
2023-12-12T16:56:50.161012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
6 21
14.7%
7 15
10.5%
10 14
9.8%
8 14
9.8%
9 11
7.7%
13 10
 
7.0%
14 9
 
6.3%
15 9
 
6.3%
5 8
 
5.6%
16 6
 
4.2%
Other values (10) 26
18.2%
ValueCountFrequency (%)
1 1
 
0.7%
4 5
 
3.5%
5 8
 
5.6%
6 21
14.7%
7 15
10.5%
8 14
9.8%
9 11
7.7%
10 14
9.8%
11 5
 
3.5%
12 4
 
2.8%
ValueCountFrequency (%)
31 1
 
0.7%
23 1
 
0.7%
21 1
 
0.7%
19 3
 
2.1%
18 2
 
1.4%
17 3
 
2.1%
16 6
4.2%
15 9
6.3%
14 9
6.3%
13 10
7.0%

정원
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.342657
Minimum13
Maximum196
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:56:50.333194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile17.1
Q120
median44
Q365
95-th percentile99
Maximum196
Range183
Interquartile range (IQR)45

Descriptive statistics

Standard deviation33.73887
Coefficient of variation (CV)0.67018452
Kurtosis3.4109821
Mean50.342657
Median Absolute Deviation (MAD)24
Skewness1.5701568
Sum7199
Variance1138.3113
MonotonicityNot monotonic
2023-12-12T16:56:50.552641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 25
 
17.5%
19 8
 
5.6%
99 8
 
5.6%
42 5
 
3.5%
49 4
 
2.8%
65 4
 
2.8%
47 4
 
2.8%
36 4
 
2.8%
48 4
 
2.8%
39 4
 
2.8%
Other values (51) 73
51.0%
ValueCountFrequency (%)
13 2
 
1.4%
14 2
 
1.4%
15 1
 
0.7%
17 3
 
2.1%
18 1
 
0.7%
19 8
 
5.6%
20 25
17.5%
23 1
 
0.7%
25 1
 
0.7%
26 1
 
0.7%
ValueCountFrequency (%)
196 1
 
0.7%
190 1
 
0.7%
139 1
 
0.7%
129 1
 
0.7%
127 1
 
0.7%
125 1
 
0.7%
123 1
 
0.7%
99 8
5.6%
97 1
 
0.7%
94 1
 
0.7%

아동현원
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.573427
Minimum0
Maximum124
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:56:50.721565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q115.5
median24
Q340
95-th percentile83.5
Maximum124
Range124
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation22.029267
Coefficient of variation (CV)0.69771542
Kurtosis2.1013296
Mean31.573427
Median Absolute Deviation (MAD)11
Skewness1.4175007
Sum4515
Variance485.28858
MonotonicityNot monotonic
2023-12-12T16:56:50.886847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 10
 
7.0%
20 8
 
5.6%
16 6
 
4.2%
18 6
 
4.2%
31 5
 
3.5%
14 5
 
3.5%
35 4
 
2.8%
17 4
 
2.8%
15 4
 
2.8%
34 4
 
2.8%
Other values (50) 87
60.8%
ValueCountFrequency (%)
0 1
 
0.7%
6 2
 
1.4%
7 2
 
1.4%
8 1
 
0.7%
9 3
 
2.1%
10 2
 
1.4%
11 4
 
2.8%
12 2
 
1.4%
13 10
7.0%
14 5
3.5%
ValueCountFrequency (%)
124 1
0.7%
91 1
0.7%
90 1
0.7%
88 1
0.7%
85 2
1.4%
84 2
1.4%
79 1
0.7%
73 1
0.7%
69 1
0.7%
67 1
0.7%

주소
Text

UNIQUE 

Distinct143
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T16:56:51.232713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length36
Mean length27.783217
Min length15

Characters and Unicode

Total characters3973
Distinct characters214
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

Unique143 ?
Unique (%)100.0%

Sample

1st row전라북도 군산시 축동로 80 OCI군산공장 기숙사 1층 내
2nd row전라북도 군산시 궁포2로 25
3rd row전라북도 군산시 나운3길 9 나운동삼성아파트 관리동(나운동)
4th row전라북도 군산시 개정면 바르메길 4
5th row전라북도 군산시 진포3길 31
ValueCountFrequency (%)
전라북도 143
 
17.7%
군산시 143
 
17.7%
관리동 19
 
2.3%
103동 7
 
0.9%
102동 6
 
0.7%
수송동 6
 
0.7%
9 6
 
0.7%
백토로 6
 
0.7%
축동로 6
 
0.7%
미룡로 5
 
0.6%
Other values (337) 463
57.2%
2023-12-12T16:56:51.781676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
673
 
16.9%
동 161
 
4.1%
산 161
 
4.1%
1 158
 
4.0%
군 148
 
3.7%
시 147
 
3.7%
라 146
 
3.7%
북 146
 
3.7%
도 145
 
3.6%
전 143
 
3.6%
Other values (204) 1945
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2452
61.7%
Space Separator 673
 
16.9%
Decimal Number 621
 
15.6%
Close Punctuation 78
 
2.0%
Open Punctuation 78
 
2.0%
Other Punctuation 37
 
0.9%
Dash Punctuation 27
 
0.7%
Uppercase Letter 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 161
 
6.6%
산 161
 
6.6%
군 148
 
6.0%
시 147
 
6.0%
라 146
 
6.0%
북 146
 
6.0%
도 145
 
5.9%
전 143
 
5.8%
로 77
 
3.1%
길 70
 
2.9%
Other values (183) 1108
45.2%
Decimal Number
ValueCountFrequency (%)
1 158
25.4%
0 98
15.8%
2 96
15.5%
3 67
10.8%
4 61
 
9.8%
6 33
 
5.3%
5 33
 
5.3%
7 27
 
4.3%
8 24
 
3.9%
9 24
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
28.6%
H 1
14.3%
L 1
14.3%
I 1
14.3%
C 1
14.3%
O 1
14.3%
Space Separator
ValueCountFrequency (%)
673
100.0%
Close Punctuation
ValueCountFrequency (%)
) 78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 78
100.0%
Other Punctuation
ValueCountFrequency (%)
, 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2452
61.7%
Common 1514
38.1%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 161
 
6.6%
산 161
 
6.6%
군 148
 
6.0%
시 147
 
6.0%
라 146
 
6.0%
북 146
 
6.0%
도 145
 
5.9%
전 143
 
5.8%
로 77
 
3.1%
길 70
 
2.9%
Other values (183) 1108
45.2%
Common
ValueCountFrequency (%)
673
44.5%
1 158
 
10.4%
0 98
 
6.5%
2 96
 
6.3%
) 78
 
5.2%
( 78
 
5.2%
3 67
 
4.4%
4 61
 
4.0%
, 37
 
2.4%
6 33
 
2.2%
Other values (5) 135
 
8.9%
Latin
ValueCountFrequency (%)
A 2
28.6%
H 1
14.3%
L 1
14.3%
I 1
14.3%
C 1
14.3%
O 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2452
61.7%
ASCII 1521
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
673
44.2%
1 158
 
10.4%
0 98
 
6.4%
2 96
 
6.3%
) 78
 
5.1%
( 78
 
5.1%
3 67
 
4.4%
4 61
 
4.0%
, 37
 
2.4%
6 33
 
2.2%
Other values (11) 142
 
9.3%
Hangul
ValueCountFrequency (%)
동 161
 
6.6%
산 161
 
6.6%
군 148
 
6.0%
시 147
 
6.0%
라 146
 
6.0%
북 146
 
6.0%
도 145
 
5.9%
전 143
 
5.8%
로 77
 
3.1%
길 70
 
2.9%
Other values (183) 1108
45.2%

통학차량운영
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
운영(신고)
126 
미운영
17 

Length

Max length6
Median length6
Mean length5.6433566
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미운영
2nd row미운영
3rd row운영(신고)
4th row운영(신고)
5th row운영(신고)

Common Values

ValueCountFrequency (%)
운영(신고) 126
88.1%
미운영 17
 
11.9%

Length

2023-12-12T16:56:52.248595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:52.372651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영(신고 126
88.1%
미운영 17
 
11.9%

위도
Real number (ℝ)

Distinct135
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.987592
Minimum35.910868
Maximum37.567357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:56:52.518216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.910868
5-th percentile35.942251
Q135.960062
median35.966881
Q335.974636
95-th percentile35.987099
Maximum37.567357
Range1.6564889
Interquartile range (IQR)0.01457418

Descriptive statistics

Standard deviation0.18927404
Coefficient of variation (CV)0.0052594251
Kurtosis68.158054
Mean35.987592
Median Absolute Deviation (MAD)0.00774101
Skewness8.294468
Sum5146.2256
Variance0.035824664
MonotonicityNot monotonic
2023-12-12T16:56:52.696651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.96471838 4
 
2.8%
35.94241344 2
 
1.4%
35.97333477 2
 
1.4%
35.97960162 2
 
1.4%
35.9653726 2
 
1.4%
35.96309969 2
 
1.4%
35.96626599 1
 
0.7%
35.97552379 1
 
0.7%
35.97406996 1
 
0.7%
35.97970247 1
 
0.7%
Other values (125) 125
87.4%
ValueCountFrequency (%)
35.91086763 1
0.7%
35.92394473 1
0.7%
35.92505501 1
0.7%
35.93217433 1
0.7%
35.94130258 1
0.7%
35.94174468 1
0.7%
35.94216275 1
0.7%
35.94223786 1
0.7%
35.94236456 1
0.7%
35.94239369 1
0.7%
ValueCountFrequency (%)
37.56735651 1
0.7%
37.56647 1
0.7%
35.99625271 1
0.7%
35.99462203 1
0.7%
35.98805941 1
0.7%
35.98751694 1
0.7%
35.98734552 1
0.7%
35.9873311 1
0.7%
35.98501173 1
0.7%
35.98486964 1
0.7%

경도
Real number (ℝ)

Distinct135
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.71831
Minimum126.56527
Maximum126.98309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:56:52.856637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.56527
5-th percentile126.67785
Q1126.69841
median126.71193
Q3126.72455
95-th percentile126.78573
Maximum126.98309
Range0.4178234
Interquartile range (IQR)0.026137

Descriptive statistics

Standard deviation0.047265849
Coefficient of variation (CV)0.00037299935
Kurtosis13.872834
Mean126.71831
Median Absolute Deviation (MAD)0.0128186
Skewness2.4539473
Sum18120.719
Variance0.0022340604
MonotonicityNot monotonic
2023-12-12T16:56:53.022173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7177295 4
 
2.8%
126.6947414 2
 
1.4%
126.7448782 2
 
1.4%
126.7517479 2
 
1.4%
126.7240624 2
 
1.4%
126.7017155 2
 
1.4%
126.7116838 1
 
0.7%
126.7091071 1
 
0.7%
126.7044973 1
 
0.7%
126.6991417 1
 
0.7%
Other values (125) 125
87.4%
ValueCountFrequency (%)
126.5652658 1
0.7%
126.5731462 1
0.7%
126.6425352 1
0.7%
126.6637957 1
0.7%
126.6765837 1
0.7%
126.6767226 1
0.7%
126.6768853 1
0.7%
126.6778442 1
0.7%
126.6779308 1
0.7%
126.6779886 1
0.7%
ValueCountFrequency (%)
126.9830892 1
0.7%
126.977963 1
0.7%
126.8592013 1
0.7%
126.8496949 1
0.7%
126.820268 1
0.7%
126.8148397 1
0.7%
126.7954045 1
0.7%
126.7868564 1
0.7%
126.7756065 1
0.7%
126.7642128 1
0.7%

Interactions

2023-12-12T16:56:45.703676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:41.394161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:41.957201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.470690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.149943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.281127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.031104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.791699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:41.489562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.033380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.565346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.277840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.396693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.140527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.881815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:41.569914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.099264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.638958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.359109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.488421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.228482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.976105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:41.646527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.176340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.718191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.469208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.603918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.326219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.078644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:41.730828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.258548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.813776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.573687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.725631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.418509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.159230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:41.807512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.334670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.909649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.692460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.827904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.516741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:46.237194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:41.886875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:42.403632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.010910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:43.818487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:44.936831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:45.616390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:56:53.122880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
어린이집유형보육실수보육실면적놀이터수보육교직원현원정원아동현원통학차량운영위도경도
어린이집유형1.0000.5970.5280.2760.5640.6030.6050.6870.0000.262
보육실수0.5971.0000.8230.6600.8580.7650.8710.0000.0000.000
보육실면적0.5280.8231.0000.4680.7690.9010.7520.0000.0000.179
놀이터수0.2760.6600.4681.0000.2430.5650.3340.1910.0000.050
보육교직원현원0.5640.8580.7690.2431.0000.6830.9280.1820.0000.000
정원0.6030.7650.9010.5650.6831.0000.7360.1910.0000.152
아동현원0.6050.8710.7520.3340.9280.7361.0000.0000.0000.103
통학차량운영0.6870.0000.0000.1910.1820.1910.0001.0000.0000.286
위도0.0000.0000.0000.0000.0000.0000.0000.0001.0001.000
경도0.2620.0000.1790.0500.0000.1520.1030.2861.0001.000
2023-12-12T16:56:53.246822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
놀이터수어린이집유형통학차량운영
놀이터수1.0000.1890.231
어린이집유형0.1891.0000.497
통학차량운영0.2310.4971.000
2023-12-12T16:56:53.360398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보육실수보육실면적보육교직원현원정원아동현원위도경도어린이집유형놀이터수통학차량운영
보육실수1.0000.7770.6260.7620.6830.1190.0910.2840.4210.000
보육실면적0.7771.0000.6790.9190.7240.1880.1820.3480.3210.000
보육교직원현원0.6260.6791.0000.6910.9140.2370.2670.3010.1730.000
정원0.7620.9190.6911.0000.7770.1130.1850.4120.4050.200
아동현원0.6830.7240.9140.7771.0000.2190.2590.3480.1960.000
위도0.1190.1880.2370.1130.2191.0000.3490.0000.0000.000
경도0.0910.1820.2670.1850.2590.3491.0000.1300.0200.278
어린이집유형0.2840.3480.3010.4120.3480.0000.1301.0000.1890.497
놀이터수0.4210.3210.1730.4050.1960.0000.0200.1891.0000.231
통학차량운영0.0000.0000.0000.2000.0000.0000.2780.4970.2311.000

Missing values

2023-12-12T16:56:46.364223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:56:46.548753image/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

어린이집명어린이집유형전화번호팩스번호보육실수보육실면적놀이터수보육교직원현원정원아동현원주소통학차량운영위도경도
0OCI어린이집직장063-465-7981063-465-798241351102615전라북도 군산시 축동로 80 OCI군산공장 기숙사 1층 내미운영35.966266126.711684
1e편한세상어린이집국공립063-442-5400<NA>51670144240전라북도 군산시 궁포2로 25미운영35.980437126.740814
2가람어린이집가정063-463-76670504-228-0062482172020전라북도 군산시 나운3길 9 나운동삼성아파트 관리동(나운동)운영(신고)35.965313126.700705
3개정어린이집사회복지법인063-451-5132063-451-115151791135938전라북도 군산시 개정면 바르메길 4운영(신고)35.954869126.795405
4군산키즈궁어린이집국공립063-462-2213<NA>10290396531전라북도 군산시 진포3길 31운영(신고)35.97316126.718985
5귀염둥이어린이집가정063-445-1636063-445-1636461081919전라북도 군산시 서당길 9 113동 108호(구암동, 현대)운영(신고)35.979602126.751748
6근로복지공단군산어린이집법인+단체063-465-1606063-465-1610944511712757전라북도 군산시 칠성4길 103 (산북동)운영(신고)35.964108126.676584
7꼬꼬어린이집가정063-466-2129<NA>456161414전라북도 군산시 하나운로 18 105동 104호(나운동, 한울)운영(신고)35.960086126.699837
8꼬마동산어린이집사회복지법인063-453-9199063-453-919863001199988전라북도 군산시 송호로 198운영(신고)35.987517126.786856
9꼬마숲느티나무어린이집민간063-910-9499063-910-94994115083628전라북도 군산시 미룡로 41 관리동 (미룡동,미룡(2)주공아파트)운영(신고)35.944287126.689528
어린이집명어린이집유형전화번호팩스번호보육실수보육실면적놀이터수보육교직원현원정원아동현원주소통학차량운영위도경도
133햇살나무어린이집가정063-910-2020063-910-2020367071918전라북도 군산시 해망로 606 207동 110호(소룡동, 소룡제일아파트)운영(신고)35.980897126.676723
134행복어린이집가정063-468-3011063-910-3016463061917전라북도 군산시 해망로 606 202동 103호(소룡동 제이파크)운영(신고)35.960755126.573146
135행복이가득한수송어린이집민간063-465-9806063-463-9559856212312985전라북도 군산시 동메2길 37 (수송동)운영(신고)35.971235126.714857
136행복한새싹어린이집사회복지법인063-452-0162063-452-29464133175017전라북도 군산시 동안길 24-12 (동안길 24-12)행복한새싹어린이집 (개정동)운영(신고)35.964249126.764213
137행복한진실어린이집사회복지법인063-465-9988063-465-99885115193716전라북도 군산시 부곡안2길 12-5운영(신고)35.960614126.687648
138현대엠코어린이집민간063-471-0279063-471-028241410104425전라북도 군산시 계산로 90 , 관리동(지곡동, 현대엠코아파트)미운영35.950815126.713987
139효성몬테소리어린이집민간063-465-6187063-468-618783501179273전라북도 군산시 의료원로 30 (지곡동)운영(신고)35.955739126.712403
140효승어린이집가정063-452-0369063-452-0369485182020전라북도 군산시 양안로 120 102동 108호(조촌동, 현대)운영(신고)35.973335126.744878
141흥남어린이집국공립063-445-0092063-442-00916230196532전라북도 군산시 흥남2길 7 (서흥남동)운영(신고)35.975222126.716045
142희망루어린이집국공립063-445-0123063-445-51236148162013전라북도 군산시 월명로 584 희망루아파트 관리동운영(신고)35.988059126.697685