Overview

Dataset statistics

Number of variables5
Number of observations83
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory43.6 B

Variable types

Numeric1
Text1
Categorical3

Dataset

Description인천서구 영어나라(https://isel.seo.incheon.kr/) 이용 회원들 정보에 대한 학력 정보(서구 학교이름, 행정구역(동), 학력코드)입니다.
URLhttps://www.data.go.kr/data/15083700/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
코드명 is highly overall correlated with 일련번호 and 1 other fieldsHigh correlation
코드 is highly overall correlated with 일련번호 and 1 other fieldsHigh correlation
일련번호 is highly overall correlated with 코드 and 1 other fieldsHigh correlation
일련번호 has unique valuesUnique
학교명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:45:14.830843
Analysis finished2023-12-12 18:45:15.506647
Duration0.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42
Minimum1
Maximum83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-13T03:45:15.620749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.1
Q121.5
median42
Q362.5
95-th percentile78.9
Maximum83
Range82
Interquartile range (IQR)41

Descriptive statistics

Standard deviation24.103942
Coefficient of variation (CV)0.57390337
Kurtosis-1.2
Mean42
Median Absolute Deviation (MAD)21
Skewness0
Sum3486
Variance581
MonotonicityStrictly increasing
2023-12-13T03:45:15.837930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
54 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
Other values (73) 73
88.0%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%

학교명
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-13T03:45:16.198799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.0120482
Min length3

Characters and Unicode

Total characters582
Distinct characters75
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

Unique83 ?
Unique (%)100.0%

Sample

1st row인천가림초등학교
2nd row인천가석초등학교
3rd row인천가정초등학교
4th row인천가좌초등학교
5th row인천가현초등학교
ValueCountFrequency (%)
인천가림초등학교 1
 
1.2%
인천당하중학교 1
 
1.2%
서인천고등학교 1
 
1.2%
백석고등학교 1
 
1.2%
대인고등학교 1
 
1.2%
경인여자고등학교 1
 
1.2%
검단고등학교 1
 
1.2%
가좌고등학교 1
 
1.2%
가정고등학교 1
 
1.2%
가림고등학교 1
 
1.2%
Other values (73) 73
88.0%
2023-12-13T03:45:16.779726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 83
14.3%
교 83
14.3%
등 61
10.5%
인 51
 
8.8%
천 49
 
8.4%
초 46
 
7.9%
중 22
 
3.8%
고 18
 
3.1%
가 12
 
2.1%
석 8
 
1.4%
Other values (65) 149
25.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 582
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 83
14.3%
교 83
14.3%
등 61
10.5%
인 51
 
8.8%
천 49
 
8.4%
초 46
 
7.9%
중 22
 
3.8%
고 18
 
3.1%
가 12
 
2.1%
석 8
 
1.4%
Other values (65) 149
25.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 582
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 83
14.3%
교 83
14.3%
등 61
10.5%
인 51
 
8.8%
천 49
 
8.4%
초 46
 
7.9%
중 22
 
3.8%
고 18
 
3.1%
가 12
 
2.1%
석 8
 
1.4%
Other values (65) 149
25.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 582
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 83
14.3%
교 83
14.3%
등 61
10.5%
인 51
 
8.8%
천 49
 
8.4%
초 46
 
7.9%
중 22
 
3.8%
고 18
 
3.1%
가 12
 
2.1%
석 8
 
1.4%
Other values (65) 149
25.6%

코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size796.0 B
1
42 
2
21 
3
17 
4
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 42
50.6%
2 21
25.3%
3 17
20.5%
4 3
 
3.6%

Length

2023-12-13T03:45:16.970978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:45:17.146678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 42
50.6%
2 21
25.3%
3 17
20.5%
4 3
 
3.6%

코드명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size796.0 B
초등학교
42 
중학교
21 
고등학교
17 
일반관리자
 
3

Length

Max length5
Median length4
Mean length3.7831325
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
초등학교 42
50.6%
중학교 21
25.3%
고등학교 17
20.5%
일반관리자 3
 
3.6%

Length

2023-12-13T03:45:17.345434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:45:17.541134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등학교 42
50.6%
중학교 21
25.3%
고등학교 17
20.5%
일반관리자 3
 
3.6%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-07-31
83 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-31
2nd row2023-07-31
3rd row2023-07-31
4th row2023-07-31
5th row2023-07-31

Common Values

ValueCountFrequency (%)
2023-07-31 83
100.0%

Length

2023-12-13T03:45:17.747242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:45:17.908736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-31 83
100.0%

Interactions

2023-12-13T03:45:15.097018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:45:18.024882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호학교명코드코드명
일련번호1.0001.0000.8710.871
학교명1.0001.0001.0001.000
코드0.8711.0001.0001.000
코드명0.8711.0001.0001.000
2023-12-13T03:45:18.170836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
코드명코드
코드명1.0001.000
코드1.0001.000
2023-12-13T03:45:18.873325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호코드코드명
일련번호1.0000.7030.703
코드0.7031.0001.000
코드명0.7031.0001.000

Missing values

2023-12-13T03:45:15.276626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:45:15.445267image/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

일련번호학교명코드코드명데이터기준일자
01인천가림초등학교1초등학교2023-07-31
12인천가석초등학교1초등학교2023-07-31
23인천가정초등학교1초등학교2023-07-31
34인천가좌초등학교1초등학교2023-07-31
45인천가현초등학교1초등학교2023-07-31
56인천간재울초등학교1초등학교2023-07-31
67인천건지초등학교1초등학교2023-07-31
78인천검단초등학교1초등학교2023-07-31
89인천검암초등학교1초등학교2023-07-31
910인천경서초등학교1초등학교2023-07-31
일련번호학교명코드코드명데이터기준일자
7374인천경명초등학교1초등학교2023-07-31
7475인천청일초등학교1초등학교2023-07-31
7576인천공촌초등학교1초등학교2023-07-31
7677초은고등학교3고등학교2023-07-31
7778청라고등학교3고등학교2023-07-31
7879인천체육고등학교3고등학교2023-07-31
7980해원고등학교3고등학교2023-07-31
8081청라중학교2중학교2023-07-31
8182초은중학교2중학교2023-07-31
8283해원중학교2중학교2023-07-31