Overview

Dataset statistics

Number of variables12
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory103.5 B

Variable types

Numeric5
Categorical3
Text4

Dataset

Description인천광역시 미추홀구 관내 학교 현황에 대한 데이터로 관내 초,중,고 등 교육기관의 학교명,도로명주소,전화번호, 좌표값 등의 데이터를 제공합니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15060792&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 구분High correlation
우편번호 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 우편번호High correlation
구분 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
설립별 is highly overall correlated with 구분High correlation
유형 is highly overall correlated with 구분High correlation
설립별 is highly imbalanced (62.7%)Imbalance
연번 has unique valuesUnique
기관명 has unique valuesUnique
교무실전화번호 has unique valuesUnique
행정실전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:27:01.253256
Analysis finished2024-03-18 04:27:05.683939
Duration4.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.5
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-03-18T13:27:05.752443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q113.75
median26.5
Q339.25
95-th percentile49.45
Maximum52
Range51
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation15.154757
Coefficient of variation (CV)0.57187763
Kurtosis-1.2
Mean26.5
Median Absolute Deviation (MAD)13
Skewness0
Sum1378
Variance229.66667
MonotonicityStrictly increasing
2024-03-18T13:27:05.872975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
28 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%
43 1
1.9%

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size548.0 B
초등학교
23 
고등학교
15 
중학교
12 
특수학교
 
1
평생교육시설
 
1

Length

Max length6
Median length4
Mean length3.8076923
Min length3

Unique

Unique2 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
초등학교 23
44.2%
고등학교 15
28.8%
중학교 12
23.1%
특수학교 1
 
1.9%
평생교육시설 1
 
1.9%

Length

2024-03-18T13:27:05.981486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:27:06.088434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등학교 23
44.2%
고등학교 15
28.8%
중학교 12
23.1%
특수학교 1
 
1.9%
평생교육시설 1
 
1.9%

설립별
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
공립
46 
사립
5 
평교
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
공립 46
88.5%
사립 5
 
9.6%
평교 1
 
1.9%

Length

2024-03-18T13:27:06.187709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:27:06.268702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공립 46
88.5%
사립 5
 
9.6%
평교 1
 
1.9%

유형
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
공학
29 
남
12 
여
11 

Length

Max length2
Median length2
Mean length1.5576923
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공학 29
55.8%
남 12
23.1%
여 11
 
21.2%

Length

2024-03-18T13:27:06.377818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:27:06.508112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공학 29
55.8%
남 12
23.1%
여 11
 
21.2%

기관명
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-03-18T13:27:06.747586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length8
Mean length8.0576923
Min length5

Characters and Unicode

Total characters419
Distinct characters66
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

Unique52 ?
Unique (%)100.0%

Sample

1st row인천경원초등학교
2nd row인천관교초등학교
3rd row인천남부초등학교
4th row인천대화초등학교
5th row인천도화초등학교
ValueCountFrequency (%)
인천경원초등학교 1
 
1.9%
인천관교초등학교 1
 
1.9%
학익고등학교 1
 
1.9%
용현여자중학교 1
 
1.9%
용현중학교 1
 
1.9%
인주중학교 1
 
1.9%
인천남중학교 1
 
1.9%
인화여자중학교 1
 
1.9%
제물포여자중학교 1
 
1.9%
인하대학교사범대학부속중학교 1
 
1.9%
Other values (42) 42
80.8%
2024-03-18T13:27:07.106986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 68
16.2%
교 57
13.6%
인 45
10.7%
등 39
 
9.3%
천 33
 
7.9%
초 23
 
5.5%
고 16
 
3.8%
중 13
 
3.1%
자 10
 
2.4%
여 9
 
2.1%
Other values (56) 106
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 419
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 68
16.2%
교 57
13.6%
인 45
10.7%
등 39
 
9.3%
천 33
 
7.9%
초 23
 
5.5%
고 16
 
3.8%
중 13
 
3.1%
자 10
 
2.4%
여 9
 
2.1%
Other values (56) 106
25.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 419
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 68
16.2%
교 57
13.6%
인 45
10.7%
등 39
 
9.3%
천 33
 
7.9%
초 23
 
5.5%
고 16
 
3.8%
중 13
 
3.1%
자 10
 
2.4%
여 9
 
2.1%
Other values (56) 106
25.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 419
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 68
16.2%
교 57
13.6%
인 45
10.7%
등 39
 
9.3%
천 33
 
7.9%
초 23
 
5.5%
고 16
 
3.8%
중 13
 
3.1%
자 10
 
2.4%
여 9
 
2.1%
Other values (56) 106
25.3%

학생수
Real number (ℝ)

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean651.69231
Minimum237
Maximum1447
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-03-18T13:27:07.235260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum237
5-th percentile250.05
Q1432.5
median576
Q3878
95-th percentile1175.95
Maximum1447
Range1210
Interquartile range (IQR)445.5

Descriptive statistics

Standard deviation298.53522
Coefficient of variation (CV)0.45809228
Kurtosis-0.24769101
Mean651.69231
Median Absolute Deviation (MAD)213
Skewness0.65647143
Sum33888
Variance89123.276
MonotonicityNot monotonic
2024-03-18T13:27:07.634763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
244 2
 
3.8%
1116 1
 
1.9%
801 1
 
1.9%
925 1
 
1.9%
416 1
 
1.9%
876 1
 
1.9%
348 1
 
1.9%
749 1
 
1.9%
808 1
 
1.9%
472 1
 
1.9%
Other values (41) 41
78.8%
ValueCountFrequency (%)
237 1
1.9%
244 2
3.8%
255 1
1.9%
285 1
1.9%
306 1
1.9%
331 1
1.9%
348 1
1.9%
361 1
1.9%
365 1
1.9%
373 1
1.9%
ValueCountFrequency (%)
1447 1
1.9%
1295 1
1.9%
1182 1
1.9%
1171 1
1.9%
1116 1
1.9%
1071 1
1.9%
1005 1
1.9%
975 1
1.9%
950 1
1.9%
928 1
1.9%

도로명주소
Text

Distinct46
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-03-18T13:27:07.861686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27.5
Mean length19.346154
Min length16

Characters and Unicode

Total characters1006
Distinct characters71
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)84.6%

Sample

1st row미추홀구 경인로 511(주안동)
2nd row미추홀구 인하로 414(관교동)
3rd row미추홀구 인주대로 366번길 22(주안동)
4th row미추홀구 석정로 301번길 13(도화동)
5th row미추홀구 경인로242(도화동)
ValueCountFrequency (%)
미추홀구 52
30.2%
석정로 10
 
5.8%
165(도화동 6
 
3.5%
매소홀로 5
 
2.9%
인하로 3
 
1.7%
주승로 3
 
1.7%
경원대로 3
 
1.7%
한나루로 3
 
1.7%
주안동 2
 
1.2%
인천광역시 2
 
1.2%
Other values (78) 83
48.3%
2024-03-18T13:27:08.190784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
12.0%
홀 59
 
5.9%
동 56
 
5.6%
미 52
 
5.2%
( 52
 
5.2%
) 52
 
5.2%
추 52
 
5.2%
구 52
 
5.2%
로 48
 
4.8%
1 35
 
3.5%
Other values (61) 427
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 594
59.0%
Decimal Number 184
 
18.3%
Space Separator 121
 
12.0%
Open Punctuation 52
 
5.2%
Close Punctuation 52
 
5.2%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홀 59
 
9.9%
동 56
 
9.4%
미 52
 
8.8%
추 52
 
8.8%
구 52
 
8.8%
로 48
 
8.1%
길 21
 
3.5%
번 18
 
3.0%
주 18
 
3.0%
화 14
 
2.4%
Other values (47) 204
34.3%
Decimal Number
ValueCountFrequency (%)
1 35
19.0%
5 27
14.7%
2 25
13.6%
3 24
13.0%
6 22
12.0%
4 18
9.8%
0 11
 
6.0%
9 9
 
4.9%
8 7
 
3.8%
7 6
 
3.3%
Space Separator
ValueCountFrequency (%)
121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 594
59.0%
Common 412
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홀 59
 
9.9%
동 56
 
9.4%
미 52
 
8.8%
추 52
 
8.8%
구 52
 
8.8%
로 48
 
8.1%
길 21
 
3.5%
번 18
 
3.0%
주 18
 
3.0%
화 14
 
2.4%
Other values (47) 204
34.3%
Common
ValueCountFrequency (%)
121
29.4%
( 52
12.6%
) 52
12.6%
1 35
 
8.5%
5 27
 
6.6%
2 25
 
6.1%
3 24
 
5.8%
6 22
 
5.3%
4 18
 
4.4%
0 11
 
2.7%
Other values (4) 25
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 594
59.0%
ASCII 412
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
29.4%
( 52
12.6%
) 52
12.6%
1 35
 
8.5%
5 27
 
6.6%
2 25
 
6.1%
3 24
 
5.8%
6 22
 
5.3%
4 18
 
4.4%
0 11
 
2.7%
Other values (4) 25
 
6.1%
Hangul
ValueCountFrequency (%)
홀 59
 
9.9%
동 56
 
9.4%
미 52
 
8.8%
추 52
 
8.8%
구 52
 
8.8%
로 48
 
8.1%
길 21
 
3.5%
번 18
 
3.0%
주 18
 
3.0%
화 14
 
2.4%
Other values (47) 204
34.3%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22178.25
Minimum22100
Maximum22241
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-03-18T13:27:08.299794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22100
5-th percentile22100
Q122132
median22189
Q322222.75
95-th percentile22240
Maximum22241
Range141
Interquartile range (IQR)90.75

Descriptive statistics

Standard deviation50.550644
Coefficient of variation (CV)0.0022792891
Kurtosis-1.325065
Mean22178.25
Median Absolute Deviation (MAD)38
Skewness-0.41302092
Sum1153269
Variance2555.3676
MonotonicityNot monotonic
2024-03-18T13:27:08.401106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
22100 9
17.3%
22189 4
 
7.7%
22240 3
 
5.8%
22211 3
 
5.8%
22222 3
 
5.8%
22163 2
 
3.8%
22241 2
 
3.8%
22228 2
 
3.8%
22225 2
 
3.8%
22232 1
 
1.9%
Other values (21) 21
40.4%
ValueCountFrequency (%)
22100 9
17.3%
22114 1
 
1.9%
22115 1
 
1.9%
22116 1
 
1.9%
22126 1
 
1.9%
22134 1
 
1.9%
22144 1
 
1.9%
22147 1
 
1.9%
22152 1
 
1.9%
22156 1
 
1.9%
ValueCountFrequency (%)
22241 2
3.8%
22240 3
5.8%
22238 1
 
1.9%
22233 1
 
1.9%
22232 1
 
1.9%
22228 2
3.8%
22226 1
 
1.9%
22225 2
3.8%
22222 3
5.8%
22214 1
 
1.9%

교무실전화번호
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-03-18T13:27:08.641622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.019231
Min length12

Characters and Unicode

Total characters625
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row032-438-9321
2nd row032-434-0492
3rd row032-629-1084
4th row032-867-0046
5th row032-874-2585
ValueCountFrequency (%)
032-438-9321 1
 
1.9%
032-434-0492 1
 
1.9%
032-868-4143 1
 
1.9%
032-884-8461 1
 
1.9%
032-629-2694 1
 
1.9%
032-863-9314 1
 
1.9%
032-882-0405 1
 
1.9%
032-766-2015 1
 
1.9%
032-422-2069 1
 
1.9%
032-452-9902 1
 
1.9%
Other values (42) 42
80.8%
2024-03-18T13:27:09.038693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 104
16.6%
2 100
16.0%
0 96
15.4%
3 82
13.1%
6 51
8.2%
4 48
7.7%
8 41
 
6.6%
7 30
 
4.8%
9 28
 
4.5%
5 23
 
3.7%
Other values (2) 22
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 520
83.2%
Dash Punctuation 104
 
16.6%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 100
19.2%
0 96
18.5%
3 82
15.8%
6 51
9.8%
4 48
9.2%
8 41
7.9%
7 30
 
5.8%
9 28
 
5.4%
5 23
 
4.4%
1 21
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 625
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 104
16.6%
2 100
16.0%
0 96
15.4%
3 82
13.1%
6 51
8.2%
4 48
7.7%
8 41
 
6.6%
7 30
 
4.8%
9 28
 
4.5%
5 23
 
3.7%
Other values (2) 22
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 104
16.6%
2 100
16.0%
0 96
15.4%
3 82
13.1%
6 51
8.2%
4 48
7.7%
8 41
 
6.6%
7 30
 
4.8%
9 28
 
4.5%
5 23
 
3.7%
Other values (2) 22
 
3.5%

행정실전화번호
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-03-18T13:27:09.233896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.019231
Min length12

Characters and Unicode

Total characters625
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

Unique52 ?
Unique (%)100.0%

Sample

1st row032-424-1692
2nd row032-434-0491
3rd row032-864-2096
4th row032-867-0047
5th row032-874-2582
ValueCountFrequency (%)
032-424-1692 1
 
1.9%
032-434-0491 1
 
1.9%
032-627-3884 1
 
1.9%
032-884-8462 1
 
1.9%
032-629-2716 1
 
1.9%
032-863-9313 1
 
1.9%
032-8822-2503 1
 
1.9%
032-763-4851 1
 
1.9%
032-423-8079 1
 
1.9%
032-452-9901 1
 
1.9%
Other values (42) 42
80.8%
2024-03-18T13:27:09.568874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 104
16.6%
2 100
16.0%
0 96
15.4%
3 78
12.5%
6 54
8.6%
8 46
7.4%
4 44
7.0%
1 31
 
5.0%
7 29
 
4.6%
9 23
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 521
83.4%
Dash Punctuation 104
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 100
19.2%
0 96
18.4%
3 78
15.0%
6 54
10.4%
8 46
8.8%
4 44
8.4%
1 31
 
6.0%
7 29
 
5.6%
9 23
 
4.4%
5 20
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 625
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 104
16.6%
2 100
16.0%
0 96
15.4%
3 78
12.5%
6 54
8.6%
8 46
7.4%
4 44
7.0%
1 31
 
5.0%
7 29
 
4.6%
9 23
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 104
16.6%
2 100
16.0%
0 96
15.4%
3 78
12.5%
6 54
8.6%
8 46
7.4%
4 44
7.0%
1 31
 
5.0%
7 29
 
4.6%
9 23
 
3.7%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.454584
Minimum37.435491
Maximum37.474048
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-03-18T13:27:09.714196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.435491
5-th percentile37.438982
Q137.444903
median37.449942
Q337.464884
95-th percentile37.47396
Maximum37.474048
Range0.03855648
Interquartile range (IQR)0.01998116

Descriptive statistics

Standard deviation0.012672298
Coefficient of variation (CV)0.00033833771
Kurtosis-1.2765332
Mean37.454584
Median Absolute Deviation (MAD)0.009517135
Skewness0.43049074
Sum1947.6384
Variance0.00016058715
MonotonicityNot monotonic
2024-03-18T13:27:09.843613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
37.47395988 8
 
15.4%
37.45465257 2
 
3.8%
37.4478941 2
 
3.8%
37.44596571 2
 
3.8%
37.44511845 1
 
1.9%
37.44840638 1
 
1.9%
37.44785505 1
 
1.9%
37.442798 1
 
1.9%
37.46379213 1
 
1.9%
37.44914564 1
 
1.9%
Other values (32) 32
61.5%
ValueCountFrequency (%)
37.43549148 1
1.9%
37.43866722 1
1.9%
37.43892166 1
1.9%
37.43903057 1
1.9%
37.43982892 1
1.9%
37.4398904 1
1.9%
37.44037081 1
1.9%
37.44040271 1
1.9%
37.44238998 1
1.9%
37.442798 1
1.9%
ValueCountFrequency (%)
37.47404796 1
 
1.9%
37.47398641 1
 
1.9%
37.47395988 8
15.4%
37.47211645 1
 
1.9%
37.46901872 1
 
1.9%
37.46816063 1
 
1.9%
37.46379213 1
 
1.9%
37.46371972 1
 
1.9%
37.46314321 1
 
1.9%
37.46235 1
 
1.9%

경도
Real number (ℝ)

Distinct42
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.667
Minimum126.63955
Maximum126.69722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-03-18T13:27:09.989510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63955
5-th percentile126.64142
Q1126.652
median126.66498
Q3126.67925
95-th percentile126.69482
Maximum126.69722
Range0.0576756
Interquartile range (IQR)0.02725325

Descriptive statistics

Standard deviation0.016938385
Coefficient of variation (CV)0.00013372375
Kurtosis-1.0222585
Mean126.667
Median Absolute Deviation (MAD)0.01297825
Skewness0.22787157
Sum6586.6838
Variance0.0002869089
MonotonicityNot monotonic
2024-03-18T13:27:10.116748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
126.6519987 8
 
15.4%
126.6738992 2
 
3.8%
126.64196 2
 
3.8%
126.6628662 2
 
3.8%
126.6940513 1
 
1.9%
126.6406704 1
 
1.9%
126.6395478 1
 
1.9%
126.6598715 1
 
1.9%
126.6539999 1
 
1.9%
126.6882045 1
 
1.9%
Other values (32) 32
61.5%
ValueCountFrequency (%)
126.6395478 1
 
1.9%
126.6406704 1
 
1.9%
126.6407581 1
 
1.9%
126.64196 2
 
3.8%
126.6434992 1
 
1.9%
126.6515423 1
 
1.9%
126.6519987 8
15.4%
126.6539999 1
 
1.9%
126.6557067 1
 
1.9%
126.657235 1
 
1.9%
ValueCountFrequency (%)
126.6972234 1
1.9%
126.6965588 1
1.9%
126.6957692 1
1.9%
126.6940513 1
1.9%
126.69278 1
1.9%
126.6917774 1
1.9%
126.6913054 1
1.9%
126.6889705 1
1.9%
126.6882045 1
1.9%
126.6867275 1
1.9%

Interactions

2024-03-18T13:27:05.019967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:03.318989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:03.762297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.135735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.589045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:05.089974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:03.432583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:03.827803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.212569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.672560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:05.173565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:03.520075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:03.898279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.307255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.755462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:05.258595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:03.603087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:03.971751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.400747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.848043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:05.354802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:03.686028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.053349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.495252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:27:04.936072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:27:10.207915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분설립별유형기관명학생수도로명주소우편번호교무실전화번호행정실전화번호위도경도
연번1.0000.9180.6200.6001.0000.0000.8510.0001.0001.0000.0000.189
구분0.9181.0000.7370.6151.0000.3590.9130.0001.0001.0000.3900.332
설립별0.6200.7371.0000.3231.0000.2231.0000.0001.0001.0000.3030.000
유형0.6000.6150.3231.0001.0000.0000.0000.0001.0001.0000.0000.510
기관명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
학생수0.0000.3590.2230.0001.0001.0000.9430.7021.0001.0000.3330.272
도로명주소0.8510.9131.0000.0001.0000.9431.0000.9581.0001.0001.0001.000
우편번호0.0000.0000.0000.0001.0000.7020.9581.0001.0001.0000.8060.815
교무실전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
행정실전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도0.0000.3900.3030.0001.0000.3331.0000.8061.0001.0001.0000.572
경도0.1890.3320.0000.5101.0000.2721.0000.8151.0001.0000.5721.000
2024-03-18T13:27:10.329601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형설립별구분
유형1.0000.1070.558
설립별0.1071.0000.718
구분0.5580.7181.000
2024-03-18T13:27:10.415341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번학생수우편번호위도경도구분설립별유형
연번1.000-0.186-0.1410.035-0.2850.5860.4280.408
학생수-0.1861.0000.165-0.1350.0320.1180.1310.000
우편번호-0.1410.1651.000-0.7560.4820.0000.1550.000
위도0.035-0.135-0.7561.000-0.3740.1510.1660.000
경도-0.2850.0320.482-0.3741.0000.1820.0000.238
구분0.5860.1180.0000.1510.1821.0000.7180.558
설립별0.4280.1310.1550.1660.0000.7181.0000.107
유형0.4080.0000.0000.0000.2380.5580.1071.000

Missing values

2024-03-18T13:27:05.475309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:27:05.626733image/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

연번구분설립별유형기관명학생수도로명주소우편번호교무실전화번호행정실전화번호위도경도
01초등학교공립공학인천경원초등학교1116미추홀구 경인로 511(주안동)22144032-438-9321032-424-169237.461366126.695769
12초등학교공립공학인천관교초등학교575미추홀구 인하로 414(관교동)22240032-434-0492032-434-049137.446257126.69278
23초등학교공립공학인천남부초등학교503미추홀구 인주대로 366번길 22(주안동)22214032-629-1084032-864-209637.45033126.675873
34초등학교공립공학인천대화초등학교453미추홀구 석정로 301번길 13(도화동)22116032-867-0046032-867-004737.469019126.668531
45초등학교공립공학인천도화초등학교928미추홀구 경인로242(도화동)22165032-874-2585032-874-258237.463143126.667845
56초등학교공립공학인천문학초등학교645미추홀구 매소홀로 553(문학동)22233032-629-0102032-629-010137.43989126.682833
67초등학교공립공학인천백학초등학교244미추홀구 매소홀로116 25(학익동)22226032-868-6778032-867-288337.438922126.671948
78초등학교공립공학인천서화초등학교1447미추홀구 송림로 250(도화동)22114032-868-9232032-868-923437.473986126.660814
89초등학교공립공학인천석암초등학교950미추홀구 주안동로 46(주안동)22134032-424-0143032-424-014337.46235126.686728
910초등학교공립공학인천숭의초등학교1295미추홀구 장천로 99(숭의동)22163032-887-9011032-887-901137.46372126.655707
연번구분설립별유형기관명학생수도로명주소우편번호교무실전화번호행정실전화번호위도경도
4243고등학교공립남인천소방고등학교306미추홀구 석정로 165(도화동)22100032-760-0106032-760-010737.47396126.651999
4344고등학교공립여인천비즈니스고등학교383미추홀구 장고개로 31(도화동)22115032-763-3037032-627-048537.472116126.666569
4445고등학교공립여문학정보고등학교255미추홀구 소성로 350번길 29(문학동)22100032-627-0774032-627-080537.435491126.686682
4546고등학교공립공학인천전자마이스터고등학교361미추홀구 석정로 165(도화동)22100032-620-8631032-620-860737.47396126.651999
4647고등학교사립남인하대학교사범대학부속고등학교626미추홀구 재넘이길 123번길 29(학익동)22189032-453-9440032-453-940037.445966126.662866
4748고등학교사립남인항고등학교567미추홀구 매소홀로 135(용현동)22211032-885-3302032-885-330237.446814126.640758
4849고등학교사립여인명여자고등학교871미추홀구 문화로 11(관교동)22241032-439-6083032-439-608437.440371126.697223
4950고등학교사립공학정석항공과학고등학교470미추홀구 인하로 100(용현동)22212032-867-6243032-867-624237.451448126.651542
5051특수학교공립공학인천청인학교331인천광역시 미추홀구 숙골로 135번길 14(도화동)22100032-458-9263032-458-925537.474048126.658844
5152평생교육시설평교공학학력인정남인천고등학교1005인천광역시 미추홀구 매소홀로418번길 14-57(학익동)22225032-863-9941032-864-242137.438667126.66683