Overview

Dataset statistics

Number of variables14
Number of observations31
Missing cells88
Missing cells (%)20.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory125.3 B

Variable types

Unsupported1
Categorical5
Text3
Numeric5

Alerts

소재지우편번호 is highly overall correlated with WGS84위도 and 4 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
완성학급수(개) is highly overall correlated with 일반학급수(개)High correlation
일반학급수(개) is highly overall correlated with 완성학급수(개)High correlation
교육지원청명 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
특수학급수(개) is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
병설유치원학급수(개) is highly overall correlated with 소재지우편번호High correlation
시군명 has 31 (100.0%) missing valuesMissing
소재지도로명주소 has 25 (80.6%) missing valuesMissing
소재지우편번호 has 16 (51.6%) missing valuesMissing
WGS84위도 has 8 (25.8%) missing valuesMissing
WGS84경도 has 8 (25.8%) missing valuesMissing
학교명 has unique valuesUnique
시군명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-20 18:32:12.864035
Analysis finished2024-04-20 18:32:16.720929
Duration3.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

교육지원청명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)35.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
화성오산
6 
김포
4 
고양
4 
광주하남
3 
구리남양주
3 
Other values (6)
11 

Length

Max length5
Median length2
Mean length3.1612903
Min length2

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row광주하남
2nd row김포
3rd row용인
4th row화성오산
5th row화성오산

Common Values

ValueCountFrequency (%)
화성오산 6
19.4%
김포 4
12.9%
고양 4
12.9%
광주하남 3
9.7%
구리남양주 3
9.7%
동두천양주 3
9.7%
시흥 3
9.7%
파주 2
 
6.5%
용인 1
 
3.2%
평택 1
 
3.2%

Length

2024-04-21T03:32:16.778489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성오산 6
19.4%
김포 4
12.9%
고양 4
12.9%
광주하남 3
9.7%
구리남양주 3
9.7%
동두천양주 3
9.7%
시흥 3
9.7%
파주 2
 
6.5%
용인 1
 
3.2%
평택 1
 
3.2%

학교명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-21T03:32:16.941257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.8709677
Min length3

Characters and Unicode

Total characters120
Distinct characters46
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row감일고
2nd row걸포3초
3rd row남사고
4th row동탄10초
5th row동탄1초
ValueCountFrequency (%)
감일고 1
 
3.2%
새터중 1
 
3.2%
향산중 1
 
3.2%
향동고 1
 
3.2%
태전중 1
 
3.2%
진건2초 1
 
3.2%
지축중 1
 
3.2%
장현4초 1
 
3.2%
장현2초 1
 
3.2%
장현2중 1
 
3.2%
Other values (21) 21
67.7%
2024-04-21T03:32:17.208639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
초 17
 
14.2%
2 10
 
8.3%
중 9
 
7.5%
1 7
 
5.8%
동 6
 
5.0%
고 5
 
4.2%
산 5
 
4.2%
봉 4
 
3.3%
탄 4
 
3.3%
현 3
 
2.5%
Other values (36) 50
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94
78.3%
Decimal Number 24
 
20.0%
Dash Punctuation 2
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 17
18.1%
중 9
 
9.6%
동 6
 
6.4%
고 5
 
5.3%
산 5
 
5.3%
봉 4
 
4.3%
탄 4
 
4.3%
현 3
 
3.2%
장 3
 
3.2%
정 3
 
3.2%
Other values (27) 35
37.2%
Decimal Number
ValueCountFrequency (%)
2 10
41.7%
1 7
29.2%
0 2
 
8.3%
8 1
 
4.2%
4 1
 
4.2%
5 1
 
4.2%
3 1
 
4.2%
9 1
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94
78.3%
Common 26
 
21.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 17
18.1%
중 9
 
9.6%
동 6
 
6.4%
고 5
 
5.3%
산 5
 
5.3%
봉 4
 
4.3%
탄 4
 
4.3%
현 3
 
3.2%
장 3
 
3.2%
정 3
 
3.2%
Other values (27) 35
37.2%
Common
ValueCountFrequency (%)
2 10
38.5%
1 7
26.9%
- 2
 
7.7%
0 2
 
7.7%
8 1
 
3.8%
4 1
 
3.8%
5 1
 
3.8%
3 1
 
3.8%
9 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94
78.3%
ASCII 26
 
21.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
초 17
18.1%
중 9
 
9.6%
동 6
 
6.4%
고 5
 
5.3%
산 5
 
5.3%
봉 4
 
4.3%
탄 4
 
4.3%
현 3
 
3.2%
장 3
 
3.2%
정 3
 
3.2%
Other values (27) 35
37.2%
ASCII
ValueCountFrequency (%)
2 10
38.5%
1 7
26.9%
- 2
 
7.7%
0 2
 
7.7%
8 1
 
3.8%
4 1
 
3.8%
5 1
 
3.8%
3 1
 
3.8%
9 1
 
3.8%

소재지지번주소
Text

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-21T03:32:17.392267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length18.870968
Min length14

Characters and Unicode

Total characters585
Distinct characters86
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

Unique27 ?
Unique (%)87.1%

Sample

1st row경기도 하남시 감이동 99-1
2nd row경기도 김포시 걸포동 222-2
3rd row경기도 용인시 처인구 남사면 아곡리 산20-2
4th row경기도 화성시 동탄면 청계리 495-21
5th row경기도 화성시 동탄면 영천리 37-14 일원
ValueCountFrequency (%)
경기도 31
21.8%
화성시 6
 
4.2%
덕양구 4
 
2.8%
김포시 4
 
2.8%
일원 4
 
2.8%
동탄면 4
 
2.8%
고양시 4
 
2.8%
양주시 3
 
2.1%
옥정동 3
 
2.1%
시흥시 3
 
2.1%
Other values (64) 76
53.5%
2024-04-21T03:32:17.681979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111
19.0%
시 34
 
5.8%
경 31
 
5.3%
도 31
 
5.3%
기 31
 
5.3%
동 27
 
4.6%
1 26
 
4.4%
- 18
 
3.1%
2 17
 
2.9%
양 15
 
2.6%
Other values (76) 244
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 347
59.3%
Space Separator 111
 
19.0%
Decimal Number 109
 
18.6%
Dash Punctuation 18
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 34
 
9.8%
경 31
 
8.9%
도 31
 
8.9%
기 31
 
8.9%
동 27
 
7.8%
양 15
 
4.3%
리 10
 
2.9%
주 9
 
2.6%
구 7
 
2.0%
산 7
 
2.0%
Other values (64) 145
41.8%
Decimal Number
ValueCountFrequency (%)
1 26
23.9%
2 17
15.6%
8 15
13.8%
6 11
10.1%
3 11
10.1%
9 9
 
8.3%
4 8
 
7.3%
5 7
 
6.4%
0 3
 
2.8%
7 2
 
1.8%
Space Separator
ValueCountFrequency (%)
111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 347
59.3%
Common 238
40.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 34
 
9.8%
경 31
 
8.9%
도 31
 
8.9%
기 31
 
8.9%
동 27
 
7.8%
양 15
 
4.3%
리 10
 
2.9%
주 9
 
2.6%
구 7
 
2.0%
산 7
 
2.0%
Other values (64) 145
41.8%
Common
ValueCountFrequency (%)
111
46.6%
1 26
 
10.9%
- 18
 
7.6%
2 17
 
7.1%
8 15
 
6.3%
6 11
 
4.6%
3 11
 
4.6%
9 9
 
3.8%
4 8
 
3.4%
5 7
 
2.9%
Other values (2) 5
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 347
59.3%
ASCII 238
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
46.6%
1 26
 
10.9%
- 18
 
7.6%
2 17
 
7.1%
8 15
 
6.3%
6 11
 
4.6%
3 11
 
4.6%
9 9
 
3.8%
4 8
 
3.4%
5 7
 
2.9%
Other values (2) 5
 
2.1%
Hangul
ValueCountFrequency (%)
시 34
 
9.8%
경 31
 
8.9%
도 31
 
8.9%
기 31
 
8.9%
동 27
 
7.8%
양 15
 
4.3%
리 10
 
2.9%
주 9
 
2.6%
구 7
 
2.0%
산 7
 
2.0%
Other values (64) 145
41.8%

소재지도로명주소
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing25
Missing (%)80.6%
Memory size380.0 B
2024-04-21T03:32:17.815389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length17
Min length14

Characters and Unicode

Total characters102
Distinct characters40
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row경기도 파주시 한울로 21
2nd row경기도 김포시 김포한강9로12번길 77
3rd row경기도 고양시 덕양구 원흥1로 26
4th row경기도 파주시 교하로 43
5th row경기도 안산시 상록구 해양5로 10
ValueCountFrequency (%)
경기도 6
23.1%
파주시 2
 
7.7%
태성로 1
 
3.8%
광주시 1
 
3.8%
10 1
 
3.8%
해양5로 1
 
3.8%
상록구 1
 
3.8%
안산시 1
 
3.8%
43 1
 
3.8%
교하로 1
 
3.8%
Other values (10) 10
38.5%
2024-04-21T03:32:18.049349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
19.6%
경 6
 
5.9%
로 6
 
5.9%
도 6
 
5.9%
기 6
 
5.9%
1 6
 
5.9%
시 6
 
5.9%
2 3
 
2.9%
양 3
 
2.9%
주 3
 
2.9%
Other values (30) 37
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64
62.7%
Space Separator 20
 
19.6%
Decimal Number 18
 
17.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 6
 
9.4%
로 6
 
9.4%
도 6
 
9.4%
기 6
 
9.4%
시 6
 
9.4%
양 3
 
4.7%
주 3
 
4.7%
김 2
 
3.1%
포 2
 
3.1%
한 2
 
3.1%
Other values (20) 22
34.4%
Decimal Number
ValueCountFrequency (%)
1 6
33.3%
2 3
16.7%
7 2
 
11.1%
0 2
 
11.1%
4 1
 
5.6%
5 1
 
5.6%
3 1
 
5.6%
6 1
 
5.6%
9 1
 
5.6%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64
62.7%
Common 38
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 6
 
9.4%
로 6
 
9.4%
도 6
 
9.4%
기 6
 
9.4%
시 6
 
9.4%
양 3
 
4.7%
주 3
 
4.7%
김 2
 
3.1%
포 2
 
3.1%
한 2
 
3.1%
Other values (20) 22
34.4%
Common
ValueCountFrequency (%)
20
52.6%
1 6
 
15.8%
2 3
 
7.9%
7 2
 
5.3%
0 2
 
5.3%
4 1
 
2.6%
5 1
 
2.6%
3 1
 
2.6%
6 1
 
2.6%
9 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64
62.7%
ASCII 38
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
52.6%
1 6
 
15.8%
2 3
 
7.9%
7 2
 
5.3%
0 2
 
5.3%
4 1
 
2.6%
5 1
 
2.6%
3 1
 
2.6%
6 1
 
2.6%
9 1
 
2.6%
Hangul
ValueCountFrequency (%)
경 6
 
9.4%
로 6
 
9.4%
도 6
 
9.4%
기 6
 
9.4%
시 6
 
9.4%
양 3
 
4.7%
주 3
 
4.7%
김 2
 
3.1%
포 2
 
3.1%
한 2
 
3.1%
Other values (20) 22
34.4%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)93.3%
Missing16
Missing (%)51.6%
Infinite0
Infinite (%)0.0%
Mean12906.467
Minimum10070
Maximum18295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-21T03:32:18.146027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10070
5-th percentile10105.7
Q110554.5
median10903
Q315296.5
95-th percentile18108.1
Maximum18295
Range8225
Interquartile range (IQR)4742

Descriptive statistics

Standard deviation3079.8817
Coefficient of variation (CV)0.2386309
Kurtosis-1.0511367
Mean12906.467
Median Absolute Deviation (MAD)833
Skewness0.77006342
Sum193597
Variance9485671.3
MonotonicityNot monotonic
2024-04-21T03:32:18.233788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
10121 2
 
6.5%
12997 1
 
3.2%
17117 1
 
3.2%
10903 1
 
3.2%
10070 1
 
3.2%
18028 1
 
3.2%
18295 1
 
3.2%
10563 1
 
3.2%
10872 1
 
3.2%
15596 1
 
3.2%
Other values (4) 4
 
12.9%
(Missing) 16
51.6%
ValueCountFrequency (%)
10070 1
3.2%
10121 2
6.5%
10546 1
3.2%
10563 1
3.2%
10583 1
3.2%
10872 1
3.2%
10903 1
3.2%
12788 1
3.2%
12997 1
3.2%
14997 1
3.2%
ValueCountFrequency (%)
18295 1
3.2%
18028 1
3.2%
17117 1
3.2%
15596 1
3.2%
14997 1
3.2%
12997 1
3.2%
12788 1
3.2%
10903 1
3.2%
10872 1
3.2%
10583 1
3.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)95.7%
Missing8
Missing (%)25.8%
Infinite0
Infinite (%)0.0%
Mean37.504997
Minimum37.019793
Maximum37.815065
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-21T03:32:18.333427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.019793
5-th percentile37.218388
Q137.368988
median37.596419
Q337.651572
95-th percentile37.806155
Maximum37.815065
Range0.79527183
Interquartile range (IQR)0.28258464

Descriptive statistics

Standard deviation0.21521096
Coefficient of variation (CV)0.0057381942
Kurtosis-0.57403327
Mean37.504997
Median Absolute Deviation (MAD)0.13436404
Skewness-0.51163689
Sum862.61493
Variance0.046315756
MonotonicityNot monotonic
2024-04-21T03:32:18.458328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
37.6198542799 2
 
6.5%
37.8150645352 1
 
3.2%
37.5964194072 1
 
3.2%
37.3803412661 1
 
3.2%
37.6521018551 1
 
3.2%
37.3653617865 1
 
3.2%
37.3726136199 1
 
3.2%
37.3736973311 1
 
3.2%
37.4849079092 1
 
3.2%
37.8145294585 1
 
3.2%
Other values (12) 12
38.7%
(Missing) 8
25.8%
ValueCountFrequency (%)
37.0197927006 1
3.2%
37.2174944998 1
3.2%
37.2264330675 1
3.2%
37.2270998831 1
3.2%
37.2813132927 1
3.2%
37.3653617865 1
3.2%
37.3726136199 1
3.2%
37.3736973311 1
3.2%
37.3803412661 1
3.2%
37.4849079092 1
3.2%
ValueCountFrequency (%)
37.8150645352 1
3.2%
37.8145294585 1
3.2%
37.7307834504 1
3.2%
37.7123492129 1
3.2%
37.6687158758 1
3.2%
37.6521018551 1
3.2%
37.65104284 1
3.2%
37.64010189 1
3.2%
37.6357127099 1
3.2%
37.6198542799 2
6.5%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)95.7%
Missing8
Missing (%)25.8%
Infinite0
Infinite (%)0.0%
Mean126.90942
Minimum126.62839
Maximum127.22763
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-21T03:32:18.584229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.62839
5-th percentile126.70548
Q1126.7698
median126.88659
Q3127.09049
95-th percentile127.1599
Maximum127.22763
Range0.59923923
Interquartile range (IQR)0.3206939

Descriptive statistics

Standard deviation0.17216778
Coefficient of variation (CV)0.0013566193
Kurtosis-1.0852979
Mean126.90942
Median Absolute Deviation (MAD)0.14104543
Skewness0.33452124
Sum2918.9167
Variance0.029641743
MonotonicityNot monotonic
2024-04-21T03:32:18.866049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
126.7455460935 2
 
6.5%
127.0909757199 1
 
3.2%
126.8934528531 1
 
3.2%
127.2276322119 1
 
3.2%
126.9181085597 1
 
3.2%
126.8052983266 1
 
3.2%
126.7940461247 1
 
3.2%
126.7954656345 1
 
3.2%
127.1574873291 1
 
3.2%
127.0955631509 1
 
3.2%
Other values (12) 12
38.7%
(Missing) 8
25.8%
ValueCountFrequency (%)
126.6283929805 1
3.2%
126.7025189482 1
3.2%
126.7321658813 1
3.2%
126.7345685109 1
3.2%
126.7455460935 2
6.5%
126.7940461247 1
3.2%
126.7954656345 1
3.2%
126.8052983266 1
3.2%
126.8339142543 1
3.2%
126.868772016 1
3.2%
ValueCountFrequency (%)
127.2276322119 1
3.2%
127.1601729938 1
3.2%
127.1574873291 1
3.2%
127.1094630042 1
3.2%
127.0955631509 1
3.2%
127.0909757199 1
3.2%
127.0900043059 1
3.2%
126.9505650113 1
3.2%
126.9504527938 1
3.2%
126.9181085597 1
3.2%

학교급명
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
초
17 
중
9 
고
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고
2nd row초
3rd row고
4th row초
5th row초

Common Values

ValueCountFrequency (%)
초 17
54.8%
중 9
29.0%
고 5
 
16.1%

Length

2024-04-21T03:32:18.969209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:32:19.050377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초 17
54.8%
중 9
29.0%
고 5
 
16.1%

개교예정년월
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
202103
21 
202009
10 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202103
2nd row202009
3rd row202103
4th row202103
5th row202103

Common Values

ValueCountFrequency (%)
202103 21
67.7%
202009 10
32.3%

Length

2024-04-21T03:32:19.132136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:32:19.211147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202103 21
67.7%
202009 10
32.3%

완성학급수(개)
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.935484
Minimum25
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-21T03:32:19.281731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile26.5
Q131
median39
Q345
95-th percentile49
Maximum49
Range24
Interquartile range (IQR)14

Descriptive statistics

Standard deviation7.8440444
Coefficient of variation (CV)0.20677328
Kurtosis-1.2766001
Mean37.935484
Median Absolute Deviation (MAD)8
Skewness-0.10533264
Sum1176
Variance61.529032
MonotonicityNot monotonic
2024-04-21T03:32:19.368953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
31 5
16.1%
49 5
16.1%
45 4
12.9%
41 3
9.7%
37 3
9.7%
40 2
 
6.5%
27 2
 
6.5%
25 1
 
3.2%
29 1
 
3.2%
43 1
 
3.2%
Other values (4) 4
12.9%
ValueCountFrequency (%)
25 1
 
3.2%
26 1
 
3.2%
27 2
 
6.5%
28 1
 
3.2%
29 1
 
3.2%
31 5
16.1%
37 3
9.7%
38 1
 
3.2%
39 1
 
3.2%
40 2
 
6.5%
ValueCountFrequency (%)
49 5
16.1%
45 4
12.9%
43 1
 
3.2%
41 3
9.7%
40 2
 
6.5%
39 1
 
3.2%
38 1
 
3.2%
37 3
9.7%
31 5
16.1%
29 1
 
3.2%

일반학급수(개)
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.580645
Minimum24
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-21T03:32:19.453125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile24.5
Q129
median36
Q339
95-th percentile45
Maximum48
Range24
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.9415377
Coefficient of variation (CV)0.20073477
Kurtosis-0.96671896
Mean34.580645
Median Absolute Deviation (MAD)6
Skewness0.1414601
Sum1072
Variance48.184946
MonotonicityNot monotonic
2024-04-21T03:32:19.535581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
36 8
25.8%
30 4
12.9%
45 3
 
9.7%
24 2
 
6.5%
41 2
 
6.5%
27 2
 
6.5%
39 2
 
6.5%
26 2
 
6.5%
28 1
 
3.2%
37 1
 
3.2%
Other values (4) 4
12.9%
ValueCountFrequency (%)
24 2
 
6.5%
25 1
 
3.2%
26 2
 
6.5%
27 2
 
6.5%
28 1
 
3.2%
30 4
12.9%
33 1
 
3.2%
36 8
25.8%
37 1
 
3.2%
39 2
 
6.5%
ValueCountFrequency (%)
48 1
 
3.2%
45 3
 
9.7%
44 1
 
3.2%
41 2
 
6.5%
39 2
 
6.5%
37 1
 
3.2%
36 8
25.8%
33 1
 
3.2%
30 4
12.9%
28 1
 
3.2%

특수학급수(개)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
1
24 
2
6 
6
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 24
77.4%
2 6
 
19.4%
6 1
 
3.2%

Length

2024-04-21T03:32:19.624297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:32:19.704152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 24
77.4%
2 6
 
19.4%
6 1
 
3.2%

병설유치원학급수(개)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
0
15 
3
11 
7
3 
4
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row4
3rd row0
4th row3
5th row3

Common Values

ValueCountFrequency (%)
0 15
48.4%
3 11
35.5%
7 3
 
9.7%
4 2
 
6.5%

Length

2024-04-21T03:32:19.785608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:32:19.865229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 15
48.4%
3 11
35.5%
7 3
 
9.7%
4 2
 
6.5%

Interactions

2024-04-21T03:32:16.051413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:14.660452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.033560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.395227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.730548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:16.110420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:14.769470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.100418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.458537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.789570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:16.186317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:14.840555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.183170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.534369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.860902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:16.261410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:14.907457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.259271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.601623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.927435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:16.323657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:14.972427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.328332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.667145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:32:15.992965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T03:32:19.929877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교육지원청명학교명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도학교급명개교예정년월완성학급수(개)일반학급수(개)특수학급수(개)병설유치원학급수(개)
교육지원청명1.0001.0001.0001.0000.9470.9870.9770.0000.5250.5510.7150.7840.581
학교명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0000.5671.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호0.9471.0001.0001.0001.0000.8510.9060.3580.0000.8000.1851.0000.824
WGS84위도0.9871.0001.0001.0000.8511.0000.9300.0000.0000.4130.7160.6600.000
WGS84경도0.9771.0001.0001.0000.9060.9301.0000.0000.2870.5170.3060.8490.000
학교급명0.0001.0000.5671.0000.3580.0000.0001.0000.1780.4320.0000.0000.426
개교예정년월0.5251.0001.0001.0000.0000.0000.2870.1781.0000.5400.6580.0000.666
완성학급수(개)0.5511.0001.0001.0000.8000.4130.5170.4320.5401.0000.8910.6550.675
일반학급수(개)0.7151.0001.0001.0000.1850.7160.3060.0000.6580.8911.0000.0000.647
특수학급수(개)0.7841.0001.0001.0001.0000.6600.8490.0000.0000.6550.0001.0000.460
병설유치원학급수(개)0.5811.0001.0001.0000.8240.0000.0000.4260.6660.6750.6470.4601.000
2024-04-21T03:32:20.046653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교육지원청명병설유치원학급수(개)특수학급수(개)개교예정년월학교급명
교육지원청명1.0000.3220.5460.4100.000
병설유치원학급수(개)0.3221.0000.4440.4490.407
특수학급수(개)0.5460.4441.0000.0000.000
개교예정년월0.4100.4490.0001.0000.285
학교급명0.0000.4070.0000.2851.000
2024-04-21T03:32:20.135959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도완성학급수(개)일반학급수(개)교육지원청명학교급명개교예정년월특수학급수(개)병설유치원학급수(개)
소재지우편번호1.000-0.6700.555-0.229-0.3170.7640.0400.0000.8160.612
WGS84위도-0.6701.000-0.274-0.0710.0620.7970.0000.0000.2870.000
WGS84경도0.555-0.2741.000-0.284-0.1500.7340.0000.1990.4590.000
완성학급수(개)-0.229-0.071-0.2841.0000.9240.2480.1630.4650.3150.449
일반학급수(개)-0.3170.062-0.1500.9241.0000.3780.0000.4270.0000.384
교육지원청명0.7640.7970.7340.2480.3781.0000.0000.4100.5460.322
학교급명0.0400.0000.0000.1630.0000.0001.0000.2850.0000.407
개교예정년월0.0000.0000.1990.4650.4270.4100.2851.0000.0000.449
특수학급수(개)0.8160.2870.4590.3150.0000.5460.0000.0001.0000.444
병설유치원학급수(개)0.6120.0000.0000.4490.3840.3220.4070.4490.4441.000

Missing values

2024-04-21T03:32:16.413510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:32:16.564849image/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.
2024-04-21T03:32:16.669524image/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

시군명교육지원청명학교명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도학교급명개교예정년월완성학급수(개)일반학급수(개)특수학급수(개)병설유치원학급수(개)
0<NA>광주하남감일고경기도 하남시 감이동 99-1<NA>1299737.509348127.160173고202103313010
1<NA>김포걸포3초경기도 김포시 걸포동 222-2<NA><NA>37.635713126.702519초202009413614
2<NA>용인남사고경기도 용인시 처인구 남사면 아곡리 산20-2<NA>17117<NA><NA>고202103252410
3<NA>화성오산동탄10초경기도 화성시 동탄면 청계리 495-21<NA><NA><NA><NA>초202103454113
4<NA>화성오산동탄1초경기도 화성시 동탄면 영천리 37-14 일원<NA><NA>37.217494127.109463초202103312713
5<NA>화성오산동탄28초경기도 화성시 동탄면 송리 21 일원<NA><NA><NA><NA>초202103292810
6<NA>화성오산동탄29초경기도 화성시 동탄면 송리 산4 일원<NA><NA><NA><NA>초202103454113
7<NA>파주동패초경기도 파주시 동패동 1782경기도 파주시 한울로 211090337.712349126.734569초202009494513
8<NA>김포마산서초경기도 김포시 구래동 6891-10경기도 김포시 김포한강9로12번길 771007037.640102126.628393초202009403613
9<NA>평택모산초경기도 평택시 동삭동 366-1번지<NA>1802837.019793127.090004초202009413713
시군명교육지원청명학교명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도학교급명개교예정년월완성학급수(개)일반학급수(개)특수학급수(개)병설유치원학급수(개)
21<NA>광주하남위례1초경기도 하남시 학암동 54<NA><NA>37.484908127.157487초202103494810
22<NA>시흥장현2중경기도 시흥시 장현동 413<NA><NA>37.373697126.795466중202103413920
23<NA>시흥장현2초경기도 시흥시 장현동 428-1<NA><NA>37.372614126.794046초202009494423
24<NA>시흥장현4초경기도 시흥시 군자동 231<NA>1499737.365362126.805298초202103382567
25<NA>고양지축중경기도 고양시 덕양구 지축동 536<NA>1058337.652102126.918109중202103272610
26<NA>구리남양주진건2초경기도 남양주시 진건읍 배양리 951<NA><NA><NA><NA>초202103393324
27<NA>광주하남태전중경기도 광주시 태전동 산22-5경기도 광주시 태성로 1101278837.380341127.227632중202009313010
28<NA>고양향동고경기도 고양시 덕양구 향동동 225-2<NA>1054637.596419126.893453고202103313010
29<NA>김포향산중경기도 김포시 고촌읍 향산리 83-1<NA>1012137.619854126.745546중202009494513
30<NA>김포향산초경기도 김포시 고촌읍 향산리 83-1<NA>1012137.619854126.745546초202009494513