Overview

Dataset statistics

Number of variables12
Number of observations29
Missing cells29
Missing cells (%)8.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory105.6 B

Variable types

Text5
Numeric4
Categorical1
Unsupported1
DateTime1

Dataset

Description대전광역시 서구 중학교 현황정보에 관한 데이터이며, 학교명, 주소, 행정동, 법정동, 좌표, 전화번호 등을 제공합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15075221/fileData.do

Alerts

기준일자 has constant value ""Constant
행정동코드 is highly overall correlated with 법정동코드 and 1 other fieldsHigh correlation
법정동코드 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
X좌표 is highly overall correlated with 법정동코드 and 1 other fieldsHigh correlation
Y좌표 is highly overall correlated with 법정동High correlation
법정동 is highly overall correlated with 행정동코드 and 3 other fieldsHigh correlation
비고 has 29 (100.0%) missing valuesMissing
학교명 has unique valuesUnique
도로명주소 has unique valuesUnique
지번주소 has unique valuesUnique
X좌표 has unique valuesUnique
Y좌표 has unique valuesUnique
전화번호 has unique valuesUnique
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-06 12:39:10.820547
Analysis finished2024-01-06 12:39:19.230060
Duration8.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

학교명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-01-06T12:39:19.645808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.862069
Min length5

Characters and Unicode

Total characters199
Distinct characters50
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

Unique29 ?
Unique (%)100.0%

Sample

1st row가수원중학교
2nd row갈마중학교
3rd row기성중학교
4th row대전갑천중학교
5th row대전관저중학교
ValueCountFrequency (%)
가수원중학교 1
 
3.4%
대전만년중학교 1
 
3.4%
대전탄방중학교 1
 
3.4%
대전정림중학교 1
 
3.4%
대전월평중학교 1
 
3.4%
대전신계중학교 1
 
3.4%
대전서중학교 1
 
3.4%
대전삼천중학교 1
 
3.4%
대전삼육중학교 1
 
3.4%
대전봉우중학교 1
 
3.4%
Other values (19) 19
65.5%
2024-01-06T12:39:22.150602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
중 29
14.6%
학 29
14.6%
교 29
14.6%
대 26
13.1%
전 25
12.6%
봉 3
 
1.5%
정 3
 
1.5%
동 3
 
1.5%
천 2
 
1.0%
삼 2
 
1.0%
Other values (40) 48
24.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 199
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 29
14.6%
학 29
14.6%
교 29
14.6%
대 26
13.1%
전 25
12.6%
봉 3
 
1.5%
정 3
 
1.5%
동 3
 
1.5%
천 2
 
1.0%
삼 2
 
1.0%
Other values (40) 48
24.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 199
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 29
14.6%
학 29
14.6%
교 29
14.6%
대 26
13.1%
전 25
12.6%
봉 3
 
1.5%
정 3
 
1.5%
동 3
 
1.5%
천 2
 
1.0%
삼 2
 
1.0%
Other values (40) 48
24.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 199
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
중 29
14.6%
학 29
14.6%
교 29
14.6%
대 26
13.1%
전 25
12.6%
봉 3
 
1.5%
정 3
 
1.5%
동 3
 
1.5%
천 2
 
1.0%
삼 2
 
1.0%
Other values (40) 48
24.1%

도로명주소
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-01-06T12:39:23.076518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length22.172414
Min length20

Characters and Unicode

Total characters643
Distinct characters62
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

Unique29 ?
Unique (%)100.0%

Sample

1st row대전광역시 서구 가수원로 26(가수원동)
2nd row대전광역시 서구 계룡로326번길 138(갈마동)
3rd row대전광역시 서구 장안로 54(흑석동)
4th row대전광역시 서구 월평동로 80(월평동)
5th row대전광역시 서구 관저동로 143(관저동)
ValueCountFrequency (%)
대전광역시 29
24.8%
서구 29
24.8%
월평동로 2
 
1.7%
문정로 2
 
1.7%
복수중로 1
 
0.9%
관저로 1
 
0.9%
73(갈마동 1
 
0.9%
만년남로 1
 
0.9%
17(만년동 1
 
0.9%
둔산북로 1
 
0.9%
Other values (49) 49
41.9%
2024-01-06T12:39:25.267414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
88
 
13.7%
동 34
 
5.3%
서 31
 
4.8%
대 30
 
4.7%
역 30
 
4.7%
( 29
 
4.5%
광 29
 
4.5%
시 29
 
4.5%
구 29
 
4.5%
전 29
 
4.5%
Other values (52) 285
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 403
62.7%
Decimal Number 92
 
14.3%
Space Separator 88
 
13.7%
Open Punctuation 29
 
4.5%
Close Punctuation 29
 
4.5%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 34
 
8.4%
서 31
 
7.7%
대 30
 
7.4%
역 30
 
7.4%
광 29
 
7.2%
시 29
 
7.2%
구 29
 
7.2%
전 29
 
7.2%
로 25
 
6.2%
길 11
 
2.7%
Other values (38) 126
31.3%
Decimal Number
ValueCountFrequency (%)
1 20
21.7%
2 16
17.4%
6 8
 
8.7%
7 8
 
8.7%
3 8
 
8.7%
8 8
 
8.7%
0 8
 
8.7%
4 6
 
6.5%
5 6
 
6.5%
9 4
 
4.3%
Space Separator
ValueCountFrequency (%)
88
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 403
62.7%
Common 240
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 34
 
8.4%
서 31
 
7.7%
대 30
 
7.4%
역 30
 
7.4%
광 29
 
7.2%
시 29
 
7.2%
구 29
 
7.2%
전 29
 
7.2%
로 25
 
6.2%
길 11
 
2.7%
Other values (38) 126
31.3%
Common
ValueCountFrequency (%)
88
36.7%
( 29
 
12.1%
) 29
 
12.1%
1 20
 
8.3%
2 16
 
6.7%
6 8
 
3.3%
7 8
 
3.3%
3 8
 
3.3%
8 8
 
3.3%
0 8
 
3.3%
Other values (4) 18
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 403
62.7%
ASCII 240
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
36.7%
( 29
 
12.1%
) 29
 
12.1%
1 20
 
8.3%
2 16
 
6.7%
6 8
 
3.3%
7 8
 
3.3%
3 8
 
3.3%
8 8
 
3.3%
0 8
 
3.3%
Other values (4) 18
 
7.5%
Hangul
ValueCountFrequency (%)
동 34
 
8.4%
서 31
 
7.7%
대 30
 
7.4%
역 30
 
7.4%
광 29
 
7.2%
시 29
 
7.2%
구 29
 
7.2%
전 29
 
7.2%
로 25
 
6.2%
길 11
 
2.7%
Other values (38) 126
31.3%

지번주소
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-01-06T12:39:25.851368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17
Min length16

Characters and Unicode

Total characters493
Distinct characters42
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

Unique29 ?
Unique (%)100.0%

Sample

1st row대전광역시 서구 가수원동 806-18
2nd row대전광역시 서구 갈마동 370-1
3rd row대전광역시 서구 흑석동 295
4th row대전광역시 서구 월평동 306
5th row대전광역시 서구 관저동 993
ValueCountFrequency (%)
대전광역시 29
25.0%
서구 29
25.0%
관저동 4
 
3.4%
둔산동 3
 
2.6%
갈마동 3
 
2.6%
도마동 3
 
2.6%
월평동 3
 
2.6%
복수동 3
 
2.6%
변동 3
 
2.6%
괴정동 2
 
1.7%
Other values (34) 34
29.3%
2024-01-06T12:39:27.069722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
17.6%
대 29
 
5.9%
서 29
 
5.9%
전 29
 
5.9%
동 29
 
5.9%
구 29
 
5.9%
1 29
 
5.9%
시 29
 
5.9%
역 29
 
5.9%
광 29
 
5.9%
Other values (32) 145
29.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 288
58.4%
Decimal Number 107
 
21.7%
Space Separator 87
 
17.6%
Dash Punctuation 11
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 29
10.1%
서 29
10.1%
전 29
10.1%
동 29
10.1%
구 29
10.1%
시 29
10.1%
역 29
10.1%
광 29
10.1%
마 6
 
2.1%
도 4
 
1.4%
Other values (20) 46
16.0%
Decimal Number
ValueCountFrequency (%)
1 29
27.1%
2 14
13.1%
6 14
13.1%
3 12
11.2%
5 8
 
7.5%
0 8
 
7.5%
4 8
 
7.5%
7 5
 
4.7%
8 5
 
4.7%
9 4
 
3.7%
Space Separator
ValueCountFrequency (%)
87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 288
58.4%
Common 205
41.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 29
10.1%
서 29
10.1%
전 29
10.1%
동 29
10.1%
구 29
10.1%
시 29
10.1%
역 29
10.1%
광 29
10.1%
마 6
 
2.1%
도 4
 
1.4%
Other values (20) 46
16.0%
Common
ValueCountFrequency (%)
87
42.4%
1 29
 
14.1%
2 14
 
6.8%
6 14
 
6.8%
3 12
 
5.9%
- 11
 
5.4%
5 8
 
3.9%
0 8
 
3.9%
4 8
 
3.9%
7 5
 
2.4%
Other values (2) 9
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 288
58.4%
ASCII 205
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
42.4%
1 29
 
14.1%
2 14
 
6.8%
6 14
 
6.8%
3 12
 
5.9%
- 11
 
5.4%
5 8
 
3.9%
0 8
 
3.9%
4 8
 
3.9%
7 5
 
2.4%
Other values (2) 9
 
4.4%
Hangul
ValueCountFrequency (%)
대 29
10.1%
서 29
10.1%
전 29
10.1%
동 29
10.1%
구 29
10.1%
시 29
10.1%
역 29
10.1%
광 29
10.1%
마 6
 
2.1%
도 4
 
1.4%
Other values (20) 46
16.0%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170574 × 109
Minimum3.017051 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-06T12:39:27.415615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.017051 × 109
Q13.017054 × 109
median3.0170582 × 109
Q33.0170597 × 109
95-th percentile3.0170646 × 109
Maximum3.017066 × 109
Range15000
Interquartile range (IQR)5700

Descriptive statistics

Standard deviation4185.3574
Coefficient of variation (CV)1.3872316 × 10-6
Kurtosis-0.58401297
Mean3.0170574 × 109
Median Absolute Deviation (MAD)2200
Skewness0.19233909
Sum8.7494664 × 1010
Variance17517217
MonotonicityNot monotonic
2024-01-06T12:39:27.879077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
3017059700 3
 
10.3%
3017051000 3
 
10.3%
3017054000 3
 
10.3%
3017059000 2
 
6.9%
3017058100 2
 
6.9%
3017053000 2
 
6.9%
3017056000 2
 
6.9%
3017058700 1
 
3.4%
3017059600 1
 
3.4%
3017058800 1
 
3.4%
Other values (9) 9
31.0%
ValueCountFrequency (%)
3017051000 3
10.3%
3017052000 1
 
3.4%
3017053000 2
6.9%
3017053500 1
 
3.4%
3017054000 3
10.3%
3017056000 2
6.9%
3017058100 2
6.9%
3017058200 1
 
3.4%
3017058600 1
 
3.4%
3017058700 1
 
3.4%
ValueCountFrequency (%)
3017066000 1
 
3.4%
3017065000 1
 
3.4%
3017064000 1
 
3.4%
3017063000 1
 
3.4%
3017060000 1
 
3.4%
3017059700 3
10.3%
3017059600 1
 
3.4%
3017059000 2
6.9%
3017058800 1
 
3.4%
3017058700 1
 
3.4%

행정동
Text

Distinct19
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-01-06T12:39:28.440019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.5172414
Min length2

Characters and Unicode

Total characters102
Distinct characters25
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

Unique12 ?
Unique (%)41.4%

Sample

1st row가수원동
2nd row갈마1동
3rd row기성동
4th row월평3동
5th row관저1동
ValueCountFrequency (%)
복수동 3
 
10.3%
관저2동 3
 
10.3%
변동 3
 
10.3%
도마2동 2
 
6.9%
갈마1동 2
 
6.9%
가수원동 2
 
6.9%
괴정동 2
 
6.9%
만년동 1
 
3.4%
월평2동 1
 
3.4%
관저1동 1
 
3.4%
Other values (9) 9
31.0%
2024-01-06T12:39:29.608916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 29
28.4%
2 8
 
7.8%
마 6
 
5.9%
1 6
 
5.9%
수 5
 
4.9%
관 4
 
3.9%
저 4
 
3.9%
평 3
 
2.9%
둔 3
 
2.9%
정 3
 
2.9%
Other values (15) 31
30.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86
84.3%
Decimal Number 16
 
15.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 29
33.7%
마 6
 
7.0%
수 5
 
5.8%
관 4
 
4.7%
저 4
 
4.7%
평 3
 
3.5%
둔 3
 
3.5%
정 3
 
3.5%
월 3
 
3.5%
복 3
 
3.5%
Other values (12) 23
26.7%
Decimal Number
ValueCountFrequency (%)
2 8
50.0%
1 6
37.5%
3 2
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86
84.3%
Common 16
 
15.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 29
33.7%
마 6
 
7.0%
수 5
 
5.8%
관 4
 
4.7%
저 4
 
4.7%
평 3
 
3.5%
둔 3
 
3.5%
정 3
 
3.5%
월 3
 
3.5%
복 3
 
3.5%
Other values (12) 23
26.7%
Common
ValueCountFrequency (%)
2 8
50.0%
1 6
37.5%
3 2
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86
84.3%
ASCII 16
 
15.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 29
33.7%
마 6
 
7.0%
수 5
 
5.8%
관 4
 
4.7%
저 4
 
4.7%
평 3
 
3.5%
둔 3
 
3.5%
정 3
 
3.5%
월 3
 
3.5%
복 3
 
3.5%
Other values (12) 23
26.7%
ASCII
ValueCountFrequency (%)
2 8
50.0%
1 6
37.5%
3 2
 
12.5%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)44.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170111 × 109
Minimum3.0170101 × 109
Maximum3.0170128 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-06T12:39:30.038094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0170101 × 109
5-th percentile3.0170101 × 109
Q13.0170103 × 109
median3.0170112 × 109
Q33.0170115 × 109
95-th percentile3.0170123 × 109
Maximum3.0170128 × 109
Range2700
Interquartile range (IQR)1200

Descriptive statistics

Standard deviation724.33084
Coefficient of variation (CV)2.4008226 × 10-7
Kurtosis0.21861683
Mean3.0170111 × 109
Median Absolute Deviation (MAD)400
Skewness0.49376879
Sum8.7493321 × 1010
Variance524655.17
MonotonicityNot monotonic
2024-01-06T12:39:30.480498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3017011600 4
13.8%
3017011100 3
10.3%
3017011300 3
10.3%
3017010200 3
10.3%
3017010100 3
10.3%
3017010300 3
10.3%
3017011200 3
10.3%
3017010800 2
6.9%
3017011400 1
 
3.4%
3017011700 1
 
3.4%
Other values (3) 3
10.3%
ValueCountFrequency (%)
3017010100 3
10.3%
3017010200 3
10.3%
3017010300 3
10.3%
3017010800 2
6.9%
3017011100 3
10.3%
3017011200 3
10.3%
3017011300 3
10.3%
3017011400 1
 
3.4%
3017011500 1
 
3.4%
3017011600 4
13.8%
ValueCountFrequency (%)
3017012800 1
 
3.4%
3017012700 1
 
3.4%
3017011700 1
 
3.4%
3017011600 4
13.8%
3017011500 1
 
3.4%
3017011400 1
 
3.4%
3017011300 3
10.3%
3017011200 3
10.3%
3017011100 3
10.3%
3017010800 2
6.9%

법정동
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)44.8%
Missing0
Missing (%)0.0%
Memory size364.0 B
관저동
4 
갈마동
3 
월평동
3 
변동
3 
복수동
3 
Other values (8)
13 

Length

Max length4
Median length3
Mean length2.9310345
Min length2

Unique

Unique5 ?
Unique (%)17.2%

Sample

1st row가수원동
2nd row갈마동
3rd row흑석동
4th row월평동
5th row관저동

Common Values

ValueCountFrequency (%)
관저동 4
13.8%
갈마동 3
10.3%
월평동 3
10.3%
변동 3
10.3%
복수동 3
10.3%
도마동 3
10.3%
둔산동 3
10.3%
괴정동 2
6.9%
가수원동 1
 
3.4%
흑석동 1
 
3.4%
Other values (3) 3
10.3%

Length

2024-01-06T12:39:31.137960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관저동 4
13.8%
갈마동 3
10.3%
월평동 3
10.3%
변동 3
10.3%
복수동 3
10.3%
도마동 3
10.3%
둔산동 3
10.3%
괴정동 2
6.9%
가수원동 1
 
3.4%
흑석동 1
 
3.4%
Other values (3) 3
10.3%

X좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.36781
Minimum127.32988
Maximum127.40103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-06T12:39:31.915164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.32988
5-th percentile127.33554
Q1127.36129
median127.37225
Q3127.37674
95-th percentile127.39437
Maximum127.40103
Range0.0711517
Interquartile range (IQR)0.0154495

Descriptive statistics

Standard deviation0.018127909
Coefficient of variation (CV)0.00014232724
Kurtosis-0.10514164
Mean127.36781
Median Absolute Deviation (MAD)0.006933
Skewness-0.56888859
Sum3693.6664
Variance0.00032862109
MonotonicityNot monotonic
2024-01-06T12:39:32.666536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
127.3546358 1
 
3.4%
127.3649471 1
 
3.4%
127.3744532 1
 
3.4%
127.3943774 1
 
3.4%
127.3612902 1
 
3.4%
127.3676549 1
 
3.4%
127.3769631 1
 
3.4%
127.3744187 1
 
3.4%
127.3943627 1
 
3.4%
127.3724173 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
127.3298769 1
3.4%
127.3328229 1
3.4%
127.3396235 1
3.4%
127.3398556 1
3.4%
127.3412779 1
3.4%
127.3457868 1
3.4%
127.3546358 1
3.4%
127.3612902 1
3.4%
127.3649471 1
3.4%
127.3676549 1
3.4%
ValueCountFrequency (%)
127.4010286 1
3.4%
127.3943774 1
3.4%
127.3943627 1
3.4%
127.3834392 1
3.4%
127.3807095 1
3.4%
127.3791863 1
3.4%
127.3769631 1
3.4%
127.3767397 1
3.4%
127.3759773 1
3.4%
127.3758931 1
3.4%

Y좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.325696
Minimum36.250082
Maximum36.366772
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-06T12:39:33.597295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.250082
5-th percentile36.295557
Q136.305375
median36.324269
Q336.350681
95-th percentile36.36237
Maximum36.366772
Range0.1166906
Interquartile range (IQR)0.0453059

Descriptive statistics

Standard deviation0.027672778
Coefficient of variation (CV)0.00076179622
Kurtosis0.21117519
Mean36.325696
Median Absolute Deviation (MAD)0.0230683
Skewness-0.48429141
Sum1053.4452
Variance0.00076578263
MonotonicityNot monotonic
2024-01-06T12:39:34.328415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
36.298092 1
 
3.4%
36.3473373 1
 
3.4%
36.3065429 1
 
3.4%
36.3506805 1
 
3.4%
36.2944326 1
 
3.4%
36.3569048 1
 
3.4%
36.3017704 1
 
3.4%
36.3359415 1
 
3.4%
36.358332 1
 
3.4%
36.3118767 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
36.2500815 1
3.4%
36.2944326 1
3.4%
36.297244 1
3.4%
36.298092 1
3.4%
36.2983148 1
3.4%
36.3003982 1
3.4%
36.3017704 1
3.4%
36.3053746 1
3.4%
36.3065429 1
3.4%
36.3095496 1
3.4%
ValueCountFrequency (%)
36.3667721 1
3.4%
36.3628593 1
3.4%
36.3616353 1
3.4%
36.358332 1
3.4%
36.3569048 1
3.4%
36.355058 1
3.4%
36.3534142 1
3.4%
36.3506805 1
3.4%
36.3473373 1
3.4%
36.3424335 1
3.4%

전화번호
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-01-06T12:39:34.987960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters348
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

Unique29 ?
Unique (%)100.0%

Sample

1st row042-541-0145
2nd row042-714-2225
3rd row042-610-0200
4th row042-488-8600
5th row042-545-4762
ValueCountFrequency (%)
042-541-0145 1
 
3.4%
042-480-2851 1
 
3.4%
042-380-3131 1
 
3.4%
042-586-8100 1
 
3.4%
042-600-7800 1
 
3.4%
042-580-8000 1
 
3.4%
042-522-4601 1
 
3.4%
042-483-6733 1
 
3.4%
042-522-0035 1
 
3.4%
042-543-7325 1
 
3.4%
Other values (19) 19
65.5%
2024-01-06T12:39:35.951856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72
20.7%
- 58
16.7%
4 53
15.2%
2 47
13.5%
5 36
10.3%
8 22
 
6.3%
1 17
 
4.9%
3 17
 
4.9%
6 14
 
4.0%
7 9
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
83.3%
Dash Punctuation 58
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72
24.8%
4 53
18.3%
2 47
16.2%
5 36
12.4%
8 22
 
7.6%
1 17
 
5.9%
3 17
 
5.9%
6 14
 
4.8%
7 9
 
3.1%
9 3
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72
20.7%
- 58
16.7%
4 53
15.2%
2 47
13.5%
5 36
10.3%
8 22
 
6.3%
1 17
 
4.9%
3 17
 
4.9%
6 14
 
4.0%
7 9
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72
20.7%
- 58
16.7%
4 53
15.2%
2 47
13.5%
5 36
10.3%
8 22
 
6.3%
1 17
 
4.9%
3 17
 
4.9%
6 14
 
4.0%
7 9
 
2.6%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2023-12-27 00:00:00
Maximum2023-12-27 00:00:00
2024-01-06T12:39:36.343282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:36.749294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-06T12:39:16.373505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:11.873920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:13.497263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:14.836550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:16.639362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:12.211767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:13.861329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:15.280183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:16.965835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:12.535389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:14.163547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:15.634447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:17.400182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:12.898848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:14.509041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:39:16.070282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-06T12:39:36.993019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학교명도로명주소지번주소행정동코드행정동법정동코드법정동X좌표Y좌표전화번호
학교명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
행정동코드1.0001.0001.0001.0001.0000.8840.8850.6070.7041.000
행정동1.0001.0001.0001.0001.0000.9990.9820.7660.9531.000
법정동코드1.0001.0001.0000.8840.9991.0001.0000.6940.7891.000
법정동1.0001.0001.0000.8850.9821.0001.0000.9080.9431.000
X좌표1.0001.0001.0000.6070.7660.6940.9081.0000.6341.000
Y좌표1.0001.0001.0000.7040.9530.7890.9430.6341.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-01-06T12:39:37.368068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드법정동코드X좌표Y좌표법정동
행정동코드1.0000.762-0.2010.2310.626
법정동코드0.7621.000-0.574-0.1050.834
X좌표-0.201-0.5741.0000.4970.621
Y좌표0.231-0.1050.4971.0000.709
법정동0.6260.8340.6210.7091.000

Missing values

2024-01-06T12:39:17.956782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-06T12:39:18.880865image/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

학교명도로명주소지번주소행정동코드행정동법정동코드법정동X좌표Y좌표전화번호비고기준일자
0가수원중학교대전광역시 서구 가수원로 26(가수원동)대전광역시 서구 가수원동 806-183017059000가수원동3017011400가수원동127.35463636.298092042-541-0145<NA>2023-12-27
1갈마중학교대전광역시 서구 계룡로326번길 138(갈마동)대전광역시 서구 갈마동 370-13017058100갈마1동3017011100갈마동127.36494736.347337042-714-2225<NA>2023-12-27
2기성중학교대전광역시 서구 장안로 54(흑석동)대전광역시 서구 흑석동 2953017060000기성동3017011700흑석동127.34127836.250082042-610-0200<NA>2023-12-27
3대전갑천중학교대전광역시 서구 월평동로 80(월평동)대전광역시 서구 월평동 3063017058800월평3동3017011300월평동127.36915436.361635042-488-8600<NA>2023-12-27
4대전관저중학교대전광역시 서구 관저동로 143(관저동)대전광역시 서구 관저동 9933017059600관저1동3017011600관저동127.33985636.305375042-545-4762<NA>2023-12-27
5대전괴정중학교대전광역시 서구 가장로 15(괴정동)대전광역시 서구 괴정동 1203017056000괴정동3017010800괴정동127.37918636.340157042-530-1700<NA>2023-12-27
6대전구봉중학교대전광역시 서구 관저서로 86(관저동)대전광역시 서구 관저동 11323017059700관저2동3017011600관저동127.32987736.300398042-540-7502<NA>2023-12-27
7대전남선중학교대전광역시 서구 월평북로 41(월평동)대전광역시 서구 월평동 2203017058700월평2동3017011300월평동127.37225336.362859042-484-6212<NA>2023-12-27
8대전내동중학교대전광역시 서구 배재로 263(변동)대전광역시 서구 변동 254-4403017054000변동3017010200변동127.37010536.33217042-534-6154<NA>2023-12-27
9대전느리울중학교대전광역시 서구 관저중로64번길 84(관저동)대전광역시 서구 관저동 13753017059700관저2동3017011600관저동127.33962436.297244042-540-4500<NA>2023-12-27
학교명도로명주소지번주소행정동코드행정동법정동코드법정동X좌표Y좌표전화번호비고기준일자
19대전봉산중학교대전광역시 서구 배재로262번길 60(변동)대전광역시 서구 변동 76-13017054000변동3017010200변동127.37283536.330625042-524-4585<NA>2023-12-27
20대전봉우중학교대전광역시 서구 관저로 102(관저동)대전광역시 서구 관저동 11503017059700관저2동3017011600관저동127.33282336.298315042-543-7325<NA>2023-12-27
21대전삼육중학교대전광역시 서구 도림1길 15(도마동)대전광역시 서구 도마동 163-113017053000도마2동3017010300도마동127.37241736.311877042-522-0035<NA>2023-12-27
22대전삼천중학교대전광역시 서구 문정로 271(둔산동)대전광역시 서구 둔산동 9113017064000둔산2동3017011200둔산동127.39436336.358332042-483-6733<NA>2023-12-27
23대전서중학교대전광역시 서구 동서대로997번길 57(괴정동)대전광역시 서구 괴정동 266-43017056000괴정동3017010800괴정동127.37441936.335941042-522-4601<NA>2023-12-27
24대전신계중학교대전광역시 서구 복수동로 40-30(복수동)대전광역시 서구 복수동 4513017051000복수동3017010100복수동127.37696336.30177042-580-8000<NA>2023-12-27
25대전월평중학교대전광역시 서구 월평동로 21(월평동)대전광역시 서구 월평동 6633017058600월평1동3017011300월평동127.36765536.356905042-600-7800<NA>2023-12-27
26대전정림중학교대전광역시 서구 괴곡길 70(괴곡동)대전광역시 서구 괴곡동 361-23017053500정림동3017012700괴곡동127.3612936.294433042-586-8100<NA>2023-12-27
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