Overview

Dataset statistics

Number of variables17
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory152.6 B

Variable types

Numeric10
Categorical4
Text3

Dataset

Description인천광역시 미추홀구 초등학교 현황 데이터입니다.유형, 등록군구, 학교명, 설립유형, 우편번호, 도로명주소, 전화번호, 학년별학급수, 좌표값 등을 제공합니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15087073/fileData.do

Alerts

유형 has constant value ""Constant
등록군구 has constant value ""Constant
설립유형 has constant value ""Constant
우편번호 is highly overall correlated with 사학년학급수 and 1 other fieldsHigh correlation
일학년학급수 is highly overall correlated with 이학년학급수 and 4 other fieldsHigh correlation
이학년학급수 is highly overall correlated with 일학년학급수 and 4 other fieldsHigh correlation
삼학년학급수 is highly overall correlated with 일학년학급수 and 4 other fieldsHigh correlation
사학년학급수 is highly overall correlated with 우편번호 and 5 other fieldsHigh correlation
오학년학급수 is highly overall correlated with 일학년학급수 and 4 other fieldsHigh correlation
육학년학급수 is highly overall correlated with 일학년학급수 and 4 other fieldsHigh correlation
위도 is highly overall correlated with 우편번호High correlation
연번 has unique valuesUnique
학교명 has unique valuesUnique
도로명주소 has unique valuesUnique
전화번호 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-04-21 10:09:00.190830
Analysis finished2024-04-21 10:09:21.034046
Duration20.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-21T19:09:21.211187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2024-04-21T19:09:21.576660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

유형
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size312.0 B
남부
23 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남부 23
100.0%

Length

2024-04-21T19:09:21.951042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:09:22.230937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남부 23
100.0%

등록군구
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size312.0 B
미추홀구
23 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미추홀구 23
100.0%

Length

2024-04-21T19:09:22.520251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:09:22.798624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미추홀구 23
100.0%

학교명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size312.0 B
2024-04-21T19:09:23.383081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length13.130435
Min length13

Characters and Unicode

Total characters302
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row인천광역시 경원 초등학교
2nd row인천광역시 관교 초등학교
3rd row인천광역시 남부 초등학교
4th row인천광역시 대화 초등학교
5th row인천광역시 도화 초등학교
ValueCountFrequency (%)
인천광역시 23
33.3%
초등학교 23
33.3%
연학 1
 
1.4%
학산 1
 
1.4%
주안 1
 
1.4%
주안북 1
 
1.4%
주안남 1
 
1.4%
인주 1
 
1.4%
용현 1
 
1.4%
용현남 1
 
1.4%
Other values (15) 15
21.7%
2024-04-21T19:09:24.416208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
15.2%
30
9.9%
24
7.9%
24
7.9%
23
7.6%
23
7.6%
23
7.6%
23
7.6%
23
7.6%
23
7.6%
Other values (26) 40
13.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 256
84.8%
Space Separator 46
 
15.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
30
11.7%
24
9.4%
24
9.4%
23
9.0%
23
9.0%
23
9.0%
23
9.0%
23
9.0%
23
9.0%
5
 
2.0%
Other values (25) 35
13.7%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 256
84.8%
Common 46
 
15.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
30
11.7%
24
9.4%
24
9.4%
23
9.0%
23
9.0%
23
9.0%
23
9.0%
23
9.0%
23
9.0%
5
 
2.0%
Other values (25) 35
13.7%
Common
ValueCountFrequency (%)
46
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 256
84.8%
ASCII 46
 
15.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
100.0%
Hangul
ValueCountFrequency (%)
30
11.7%
24
9.4%
24
9.4%
23
9.0%
23
9.0%
23
9.0%
23
9.0%
23
9.0%
23
9.0%
5
 
2.0%
Other values (25) 35
13.7%

설립유형
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size312.0 B
공립
23 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공립 23
100.0%

Length

2024-04-21T19:09:24.625527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:09:24.786582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공립 23
100.0%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22186.522
Minimum22114
Maximum22241
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-21T19:09:24.938970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22114
5-th percentile22117
Q122155.5
median22189
Q322222
95-th percentile22239.3
Maximum22241
Range127
Interquartile range (IQR)66.5

Descriptive statistics

Standard deviation41.112782
Coefficient of variation (CV)0.0018530522
Kurtosis-1.1369726
Mean22186.522
Median Absolute Deviation (MAD)33
Skewness-0.41196339
Sum510290
Variance1690.2609
MonotonicityNot monotonic
2024-04-21T19:09:25.175950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
22222 2
 
8.7%
22208 1
 
4.3%
22211 1
 
4.3%
22203 1
 
4.3%
22148 1
 
4.3%
22126 1
 
4.3%
22228 1
 
4.3%
22187 1
 
4.3%
22189 1
 
4.3%
22188 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
22114 1
4.3%
22116 1
4.3%
22126 1
4.3%
22134 1
4.3%
22144 1
4.3%
22148 1
4.3%
22163 1
4.3%
22165 1
4.3%
22168 1
4.3%
22187 1
4.3%
ValueCountFrequency (%)
22241 1
4.3%
22240 1
4.3%
22233 1
4.3%
22228 1
4.3%
22226 1
4.3%
22222 2
8.7%
22214 1
4.3%
22211 1
4.3%
22208 1
4.3%
22203 1
4.3%

도로명주소
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size312.0 B
2024-04-21T19:09:25.844108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length25.043478
Min length22

Characters and Unicode

Total characters576
Distinct characters60
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 경인로 511(주안동)
2nd row인천광역시 미추홀구 인하로 414(관교동)
3rd row인천광역시 미추홀구 인주대로366번길 22(주안동)
4th row인천광역시 미추홀구 석정로301번길 13(도화동)
5th row인천광역시 미추홀구 경인로 242(도화동)
ValueCountFrequency (%)
인천광역시 23
25.0%
미추홀구 23
25.0%
경인로 2
 
2.2%
주승로 2
 
2.2%
매소홀로 2
 
2.2%
53(학익동 1
 
1.1%
26(용현동 1
 
1.1%
용정공원로83번길 1
 
1.1%
9(용현동 1
 
1.1%
133(용현동 1
 
1.1%
Other values (35) 35
38.0%
2024-04-21T19:09:26.742822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69
 
12.0%
29
 
5.0%
27
 
4.7%
25
 
4.3%
24
 
4.2%
23
 
4.0%
( 23
 
4.0%
23
 
4.0%
23
 
4.0%
) 23
 
4.0%
Other values (50) 287
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 379
65.8%
Decimal Number 82
 
14.2%
Space Separator 69
 
12.0%
Open Punctuation 23
 
4.0%
Close Punctuation 23
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
29
 
7.7%
27
 
7.1%
25
 
6.6%
24
 
6.3%
23
 
6.1%
23
 
6.1%
23
 
6.1%
23
 
6.1%
23
 
6.1%
23
 
6.1%
Other values (37) 136
35.9%
Decimal Number
ValueCountFrequency (%)
3 13
15.9%
4 13
15.9%
2 12
14.6%
1 11
13.4%
5 10
12.2%
6 9
11.0%
9 5
 
6.1%
0 4
 
4.9%
7 3
 
3.7%
8 2
 
2.4%
Space Separator
ValueCountFrequency (%)
69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 379
65.8%
Common 197
34.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
29
 
7.7%
27
 
7.1%
25
 
6.6%
24
 
6.3%
23
 
6.1%
23
 
6.1%
23
 
6.1%
23
 
6.1%
23
 
6.1%
23
 
6.1%
Other values (37) 136
35.9%
Common
ValueCountFrequency (%)
69
35.0%
( 23
 
11.7%
) 23
 
11.7%
3 13
 
6.6%
4 13
 
6.6%
2 12
 
6.1%
1 11
 
5.6%
5 10
 
5.1%
6 9
 
4.6%
9 5
 
2.5%
Other values (3) 9
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 379
65.8%
ASCII 197
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
69
35.0%
( 23
 
11.7%
) 23
 
11.7%
3 13
 
6.6%
4 13
 
6.6%
2 12
 
6.1%
1 11
 
5.6%
5 10
 
5.1%
6 9
 
4.6%
9 5
 
2.5%
Other values (3) 9
 
4.6%
Hangul
ValueCountFrequency (%)
29
 
7.7%
27
 
7.1%
25
 
6.6%
24
 
6.3%
23
 
6.1%
23
 
6.1%
23
 
6.1%
23
 
6.1%
23
 
6.1%
23
 
6.1%
Other values (37) 136
35.9%

전화번호
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size312.0 B
2024-04-21T19:09:27.389644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters276
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

Unique23 ?
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
 
4.3%
032-874-0500 1
 
4.3%
032-629-2044 1
 
4.3%
032-629-0186 1
 
4.3%
032-868-5578 1
 
4.3%
032-424-7247 1
 
4.3%
032-875-2607 1
 
4.3%
032-629-0679 1
 
4.3%
032-884-8468 1
 
4.3%
032-627-6300 1
 
4.3%
Other values (13) 13
56.5%
2024-04-21T19:09:28.218544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 46
16.7%
2 45
16.3%
0 43
15.6%
3 32
11.6%
8 25
9.1%
4 21
7.6%
6 20
7.2%
7 15
 
5.4%
9 13
 
4.7%
1 9
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
83.3%
Dash Punctuation 46
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 45
19.6%
0 43
18.7%
3 32
13.9%
8 25
10.9%
4 21
9.1%
6 20
8.7%
7 15
 
6.5%
9 13
 
5.7%
1 9
 
3.9%
5 7
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 276
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 46
16.7%
2 45
16.3%
0 43
15.6%
3 32
11.6%
8 25
9.1%
4 21
7.6%
6 20
7.2%
7 15
 
5.4%
9 13
 
4.7%
1 9
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 46
16.7%
2 45
16.3%
0 43
15.6%
3 32
11.6%
8 25
9.1%
4 21
7.6%
6 20
7.2%
7 15
 
5.4%
9 13
 
4.7%
1 9
 
3.3%

일학년학급수
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6956522
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-21T19:09:28.419982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.1
Q13
median4
Q36.5
95-th percentile7.9
Maximum10
Range8
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.1623805
Coefficient of variation (CV)0.46050695
Kurtosis-0.17313068
Mean4.6956522
Median Absolute Deviation (MAD)1
Skewness0.78568477
Sum108
Variance4.6758893
MonotonicityNot monotonic
2024-04-21T19:09:28.614686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3 8
34.8%
7 4
17.4%
4 3
 
13.0%
6 2
 
8.7%
2 2
 
8.7%
5 2
 
8.7%
10 1
 
4.3%
8 1
 
4.3%
ValueCountFrequency (%)
2 2
 
8.7%
3 8
34.8%
4 3
 
13.0%
5 2
 
8.7%
6 2
 
8.7%
7 4
17.4%
8 1
 
4.3%
10 1
 
4.3%
ValueCountFrequency (%)
10 1
 
4.3%
8 1
 
4.3%
7 4
17.4%
6 2
 
8.7%
5 2
 
8.7%
4 3
 
13.0%
3 8
34.8%
2 2
 
8.7%

이학년학급수
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.173913
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-21T19:09:28.809057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.1
Q14
median4
Q37
95-th percentile9
Maximum10
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3091158
Coefficient of variation (CV)0.44629969
Kurtosis-0.61136171
Mean5.173913
Median Absolute Deviation (MAD)1
Skewness0.64159654
Sum119
Variance5.3320158
MonotonicityNot monotonic
2024-04-21T19:09:29.005362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4 8
34.8%
3 3
 
13.0%
7 3
 
13.0%
6 2
 
8.7%
2 2
 
8.7%
9 2
 
8.7%
10 1
 
4.3%
8 1
 
4.3%
5 1
 
4.3%
ValueCountFrequency (%)
2 2
 
8.7%
3 3
 
13.0%
4 8
34.8%
5 1
 
4.3%
6 2
 
8.7%
7 3
 
13.0%
8 1
 
4.3%
9 2
 
8.7%
10 1
 
4.3%
ValueCountFrequency (%)
10 1
 
4.3%
9 2
 
8.7%
8 1
 
4.3%
7 3
 
13.0%
6 2
 
8.7%
5 1
 
4.3%
4 8
34.8%
3 3
 
13.0%
2 2
 
8.7%

삼학년학급수
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9130435
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-21T19:09:29.410580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.1
Q13
median5
Q36.5
95-th percentile7.9
Maximum10
Range8
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.1513853
Coefficient of variation (CV)0.43789257
Kurtosis-0.44244683
Mean4.9130435
Median Absolute Deviation (MAD)2
Skewness0.51284654
Sum113
Variance4.6284585
MonotonicityNot monotonic
2024-04-21T19:09:29.611291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3 7
30.4%
7 4
17.4%
6 4
17.4%
4 2
 
8.7%
5 2
 
8.7%
2 2
 
8.7%
10 1
 
4.3%
8 1
 
4.3%
ValueCountFrequency (%)
2 2
 
8.7%
3 7
30.4%
4 2
 
8.7%
5 2
 
8.7%
6 4
17.4%
7 4
17.4%
8 1
 
4.3%
10 1
 
4.3%
ValueCountFrequency (%)
10 1
 
4.3%
8 1
 
4.3%
7 4
17.4%
6 4
17.4%
5 2
 
8.7%
4 2
 
8.7%
3 7
30.4%
2 2
 
8.7%

사학년학급수
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5
Minimum2
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-21T19:09:29.806671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.1
Q14
median4
Q36.5
95-th percentile8
Maximum9
Range7
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation2.0449494
Coefficient of variation (CV)0.40898989
Kurtosis-0.88819876
Mean5
Median Absolute Deviation (MAD)1
Skewness0.45408039
Sum115
Variance4.1818182
MonotonicityNot monotonic
2024-04-21T19:09:29.992132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
4 8
34.8%
8 3
 
13.0%
6 3
 
13.0%
3 3
 
13.0%
2 2
 
8.7%
7 2
 
8.7%
9 1
 
4.3%
5 1
 
4.3%
ValueCountFrequency (%)
2 2
 
8.7%
3 3
 
13.0%
4 8
34.8%
5 1
 
4.3%
6 3
 
13.0%
7 2
 
8.7%
8 3
 
13.0%
9 1
 
4.3%
ValueCountFrequency (%)
9 1
 
4.3%
8 3
 
13.0%
7 2
 
8.7%
6 3
 
13.0%
5 1
 
4.3%
4 8
34.8%
3 3
 
13.0%
2 2
 
8.7%

오학년학급수
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4782609
Minimum2
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-21T19:09:30.176191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.1
Q14
median5
Q37
95-th percentile9
Maximum9
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2334149
Coefficient of variation (CV)0.40768685
Kurtosis-1.0949944
Mean5.4782609
Median Absolute Deviation (MAD)2
Skewness0.13867216
Sum126
Variance4.9881423
MonotonicityNot monotonic
2024-04-21T19:09:30.361373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
4 4
17.4%
5 3
13.0%
6 3
13.0%
9 3
13.0%
3 3
13.0%
7 3
13.0%
8 2
8.7%
2 2
8.7%
ValueCountFrequency (%)
2 2
8.7%
3 3
13.0%
4 4
17.4%
5 3
13.0%
6 3
13.0%
7 3
13.0%
8 2
8.7%
9 3
13.0%
ValueCountFrequency (%)
9 3
13.0%
8 2
8.7%
7 3
13.0%
6 3
13.0%
5 3
13.0%
4 4
17.4%
3 3
13.0%
2 2
8.7%

육학년학급수
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4347826
Minimum2
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-21T19:09:30.545989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.1
Q14
median5
Q37
95-th percentile9
Maximum9
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2728854
Coefficient of variation (CV)0.41821091
Kurtosis-0.97809727
Mean5.4347826
Median Absolute Deviation (MAD)1
Skewness0.37254814
Sum125
Variance5.1660079
MonotonicityNot monotonic
2024-04-21T19:09:30.735834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
4 6
26.1%
9 4
17.4%
6 4
17.4%
5 3
13.0%
2 2
 
8.7%
3 2
 
8.7%
8 2
 
8.7%
ValueCountFrequency (%)
2 2
 
8.7%
3 2
 
8.7%
4 6
26.1%
5 3
13.0%
6 4
17.4%
8 2
 
8.7%
9 4
17.4%
ValueCountFrequency (%)
9 4
17.4%
8 2
 
8.7%
6 4
17.4%
5 3
13.0%
4 6
26.1%
3 2
 
8.7%
2 2
 
8.7%

특수학급수
Categorical

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size312.0 B
2
14 
3
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row3

Common Values

ValueCountFrequency (%)
2 14
60.9%
3 6
26.1%
1 3
 
13.0%

Length

2024-04-21T19:09:30.945220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:09:31.109354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 14
60.9%
3 6
26.1%
1 3
 
13.0%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.45276
Minimum37.438922
Maximum37.473986
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-21T19:09:31.279299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.438922
5-th percentile37.439835
Q137.444911
median37.45033
Q337.461858
95-th percentile37.468849
Maximum37.473986
Range0.03506475
Interquartile range (IQR)0.0169474

Descriptive statistics

Standard deviation0.010420493
Coefficient of variation (CV)0.00027823031
Kurtosis-0.93036747
Mean37.45276
Median Absolute Deviation (MAD)0.00910734
Skewness0.42434392
Sum861.41348
Variance0.00010858668
MonotonicityNot monotonic
2024-04-21T19:09:31.512531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
37.46136602 1
 
4.3%
37.44625655 1
 
4.3%
37.44706316 1
 
4.3%
37.43982892 1
 
4.3%
37.45465257 1
 
4.3%
37.4673168 1
 
4.3%
37.44955342 1
 
4.3%
37.44238998 1
 
4.3%
37.45317935 1
 
4.3%
37.4478941 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
37.43892166 1
4.3%
37.43982892 1
4.3%
37.4398904 1
4.3%
37.44040271 1
4.3%
37.44238998 1
4.3%
37.44356467 1
4.3%
37.44625655 1
4.3%
37.44676348 1
4.3%
37.44706316 1
4.3%
37.4478941 1
4.3%
ValueCountFrequency (%)
37.47398641 1
4.3%
37.46901872 1
4.3%
37.4673168 1
4.3%
37.46371972 1
4.3%
37.46314321 1
4.3%
37.46235 1
4.3%
37.46136602 1
4.3%
37.45943698 1
4.3%
37.45465257 1
4.3%
37.45317935 1
4.3%

경도
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.6696
Minimum126.64081
Maximum126.69656
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-21T19:09:31.723593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.64081
5-th percentile126.64211
Q1126.6584
median126.67192
Q3126.68001
95-th percentile126.69547
Maximum126.69656
Range0.0557509
Interquartile range (IQR)0.02161225

Descriptive statistics

Standard deviation0.016222113
Coefficient of variation (CV)0.00012806635
Kurtosis-0.61117102
Mean126.6696
Median Absolute Deviation (MAD)0.013085
Skewness-0.107765
Sum2913.4008
Variance0.00026315694
MonotonicityNot monotonic
2024-04-21T19:09:31.927321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
126.6957692 1
 
4.3%
126.69278 1
 
4.3%
126.6586364 1
 
4.3%
126.65816 1
 
4.3%
126.6738992 1
 
4.3%
126.6771877 1
 
4.3%
126.6850024 1
 
4.3%
126.6737257 1
 
4.3%
126.6408079 1
 
4.3%
126.64196 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
126.6408079 1
4.3%
126.64196 1
4.3%
126.6434992 1
4.3%
126.6557067 1
4.3%
126.657235 1
4.3%
126.65816 1
4.3%
126.6586364 1
4.3%
126.6608141 1
4.3%
126.6633622 1
4.3%
126.667845 1
4.3%
ValueCountFrequency (%)
126.6965588 1
4.3%
126.6957692 1
4.3%
126.69278 1
4.3%
126.6867275 1
4.3%
126.6850024 1
4.3%
126.6828332 1
4.3%
126.6771877 1
4.3%
126.6758729 1
4.3%
126.6738992 1
4.3%
126.6737257 1
4.3%

Interactions

2024-04-21T19:09:17.659897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:01.024705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:02.478790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:04.025775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:05.616941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:07.638129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:09.426726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:11.499914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:13.598135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:15.161682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:17.891929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:01.145987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:02.612650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:04.167641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:05.758258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:07.874496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:09.562225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:11.735297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:13.732837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:15.512108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:18.142108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:01.289061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:02.764355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:04.323698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:05.913687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:08.129720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:09.714985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:11.985891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:13.887223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:15.665465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:18.403455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:01.442839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:02.928028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:04.489038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:06.078901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:08.302239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:09.873595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:12.246537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:14.048785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:15.831192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:18.669524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:01.593787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:03.089482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:04.655876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:06.248280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:08.465166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:10.035553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:12.506607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:14.218349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:16.087818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:18.928178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:01.746547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:03.252713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:04.819324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:06.427022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:08.630246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:10.226648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:12.767427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:14.380539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:16.359628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:19.179971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:01.891350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:03.407895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:04.979537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:06.595818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:08.787385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:10.481645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:12.976935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:14.542005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:16.622585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:19.433316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:02.043569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:03.564912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:05.136724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:06.766464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:08.948670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:10.736490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:13.131349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:14.697786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:16.882505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:19.684123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:02.188951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:03.718360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:05.298113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:07.125720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:09.110171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:10.992037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:13.287813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:14.850803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:17.144692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:19.940942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:02.340605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:03.878340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:05.464146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:07.386733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:09.273870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:11.253110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:13.446690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:15.013244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:09:17.404879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T19:09:32.099027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번학교명우편번호도로명주소전화번호일학년학급수이학년학급수삼학년학급수사학년학급수오학년학급수육학년학급수특수학급수위도경도
연번1.0001.0000.6751.0001.0000.4660.1490.3560.0000.0000.5610.0000.5650.729
학교명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
우편번호0.6751.0001.0001.0001.0000.7200.4880.6180.5040.0000.5850.4660.9000.932
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
일학년학급수0.4661.0000.7201.0001.0001.0000.8840.9650.9460.9120.7740.0000.7410.123
이학년학급수0.1491.0000.4881.0001.0000.8841.0000.8200.8850.7690.7910.4850.7370.000
삼학년학급수0.3561.0000.6181.0001.0000.9650.8201.0000.9280.9250.8180.1250.7650.354
사학년학급수0.0001.0000.5041.0001.0000.9460.8850.9281.0000.9050.7990.3840.7070.430
오학년학급수0.0001.0000.0001.0001.0000.9120.7690.9250.9051.0000.8210.0000.5530.000
육학년학급수0.5611.0000.5851.0001.0000.7740.7910.8180.7990.8211.0000.3770.5970.547
특수학급수0.0001.0000.4661.0001.0000.0000.4850.1250.3840.0000.3771.0000.4500.470
위도0.5651.0000.9001.0001.0000.7410.7370.7650.7070.5530.5970.4501.0000.297
경도0.7291.0000.9321.0001.0000.1230.0000.3540.4300.0000.5470.4700.2971.000
2024-04-21T19:09:32.356122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호일학년학급수이학년학급수삼학년학급수사학년학급수오학년학급수육학년학급수위도경도특수학급수
연번1.0000.016-0.1220.071-0.045-0.0820.021-0.074-0.177-0.3790.000
우편번호0.0161.000-0.484-0.482-0.426-0.575-0.440-0.387-0.8650.2820.215
일학년학급수-0.122-0.4841.0000.9420.9380.9440.9100.9440.385-0.2680.000
이학년학급수0.071-0.4820.9421.0000.9390.9400.9230.9220.386-0.3850.160
삼학년학급수-0.045-0.4260.9380.9391.0000.9420.9310.9540.325-0.2570.000
사학년학급수-0.082-0.5750.9440.9400.9421.0000.9450.9400.466-0.2810.196
오학년학급수0.021-0.4400.9100.9230.9310.9451.0000.9230.285-0.3820.000
육학년학급수-0.074-0.3870.9440.9220.9540.9400.9231.0000.310-0.2530.219
위도-0.177-0.8650.3850.3860.3250.4660.2850.3101.000-0.1200.205
경도-0.3790.282-0.268-0.385-0.257-0.281-0.382-0.253-0.1201.0000.149
특수학급수0.0000.2150.0000.1600.0000.1960.0000.2190.2050.1491.000

Missing values

2024-04-21T19:09:20.314011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T19:09:20.896472image/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

연번유형등록군구학교명설립유형우편번호도로명주소전화번호일학년학급수이학년학급수삼학년학급수사학년학급수오학년학급수육학년학급수특수학급수위도경도
01남부미추홀구인천광역시 경원 초등학교공립22144인천광역시 미추홀구 경인로 511(주안동)032-438-9321767889137.461366126.695769
12남부미추홀구인천광역시 관교 초등학교공립22240인천광역시 미추홀구 인하로 414(관교동)032-434-0492444445237.446257126.69278
23남부미추홀구인천광역시 남부 초등학교공립22214인천광역시 미추홀구 인주대로366번길 22(주안동)032-629-1084343454237.45033126.675873
34남부미추홀구인천광역시 대화 초등학교공립22116인천광역시 미추홀구 석정로301번길 13(도화동)032-867-0046333444237.469019126.668531
45남부미추홀구인천광역시 도화 초등학교공립22165인천광역시 미추홀구 경인로 242(도화동)032-874-2585677666337.463143126.667845
56남부미추홀구인천광역시 문학 초등학교공립22233인천광역시 미추홀구 매소홀로 553(문학동)032-629-0102445455337.43989126.682833
67남부미추홀구인천광역시 백학 초등학교공립22226인천광역시 미추홀구 매소홀로446번길 25(학익동)032-868-6778222222237.438922126.671948
78남부미추홀구인천광역시 서화 초등학교공립22114인천광역시 미추홀구 송림로 250(도화동)032-868-9232101010999237.473986126.660814
89남부미추홀구인천광역시 석암 초등학교공립22134인천광역시 미추홀구 주안동로 46(주안동)032-424-0143776666337.46235126.686728
910남부미추홀구인천광역시 숭의 초등학교공립22163인천광역시 미추홀구 장천로 99(숭의동)032-887-9011898899237.46372126.655707
연번유형등록군구학교명설립유형우편번호도로명주소전화번호일학년학급수이학년학급수삼학년학급수사학년학급수오학년학급수육학년학급수특수학급수위도경도
1314남부미추홀구인천광역시 용정 초등학교공립22168인천광역시 미추홀구 독정안길 26(용현동)032-868-2384222222337.459437126.657235
1415남부미추홀구인천광역시 용학 초등학교공립22188인천광역시 미추홀구 용정공원로83번길 9(용현동)032-627-6300787898137.446763126.643499
1516남부미추홀구인천광역시 용현남 초등학교공립22189인천광역시 미추홀구 매소홀로 133(용현동)032-884-8468676778237.447894126.64196
1617남부미추홀구인천광역시 용현 초등학교공립22187인천광역시 미추홀구 낙섬동로 83(용현동)032-629-0679797789337.453179126.640808
1718남부미추홀구인천광역시 인주 초등학교공립22222인천광역시 미추홀구 매소홀로475번길 53(학익동)032-875-2607345464237.44239126.673726
1819남부미추홀구인천광역시 주안남 초등학교공립22228인천광역시 미추홀구 인주대로434번길 11(주안동)032-424-7247344445337.449553126.685002
1920남부미추홀구인천광역시 주안북 초등학교공립22126인천광역시 미추홀구 석정로 375빈길 14(주안동)032-868-5578343433237.467317126.677188
2021남부미추홀구인천광역시 주안 초등학교공립22148인천광역시 미추홀구 남주길69번길16(주안동)032-629-0186556676237.454653126.673899
2122남부미추홀구인천광역시 학산 초등학교공립22203인천광역시 미추홀구 한나루로357번길 66(학익동)032-629-2044566576237.439829126.65816
2223남부미추홀구인천광역시 학익 초등학교공립22211인천광역시 미추홀구 한나루로403번길 122(학익동)032-629-0430343344237.447063126.658636