Overview

Dataset statistics

Number of variables11
Number of observations75
Missing cells75
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory94.8 B

Variable types

Text4
Numeric4
Categorical2
Unsupported1

Dataset

Description대전광역시 서구 유치원 현황정보에 대한 데이터이며,유치원명, 주소, 행정동, 법정동, 전화번호, 좌표 등을 제공합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15075215/fileData.do

Alerts

행정동코드 is highly overall correlated with 법정동코드 and 2 other fieldsHigh correlation
법정동코드 is highly overall correlated with 행정동코드 and 3 other fieldsHigh correlation
X좌표 is highly overall correlated with 법정동코드 and 3 other fieldsHigh correlation
Y좌표 is highly overall correlated with X좌표 and 2 other fieldsHigh correlation
행정동 is highly overall correlated with 행정동코드 and 4 other fieldsHigh correlation
법정동 is highly overall correlated with 행정동코드 and 4 other fieldsHigh correlation
비고 has 75 (100.0%) missing valuesMissing
유치원명 has unique valuesUnique
새주소 has unique valuesUnique
전화번호 has unique valuesUnique
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 04:18:25.562966
Analysis finished2023-12-12 04:18:28.584592
Duration3.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유치원명
Text

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2023-12-12T13:18:28.832734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length8.16
Min length5

Characters and Unicode

Total characters612
Distinct characters127
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

Unique75 ?
Unique (%)100.0%

Sample

1st row가수원초등학교 병설유치원
2nd row기성초등학교병설유치원
3rd row대전가장초등학교병설유치원
4th row대전갈마유치원
5th row대전관저초등학교병설유치원
ValueCountFrequency (%)
가수원초등학교 1
 
1.3%
비젤유치원 1
 
1.3%
아름유치원 1
 
1.3%
세명유치원 1
 
1.3%
성균관숲유치원 1
 
1.3%
서원유치원 1
 
1.3%
샘머리유치원 1
 
1.3%
상아유치원 1
 
1.3%
산새소리유치원 1
 
1.3%
배재대부속유치원 1
 
1.3%
Other values (66) 66
86.8%
2023-12-12T13:18:29.299281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 79
 
12.9%
유 77
 
12.6%
치 75
 
12.3%
대 26
 
4.2%
교 25
 
4.1%
학 24
 
3.9%
초 23
 
3.8%
등 23
 
3.8%
병 23
 
3.8%
설 23
 
3.8%
Other values (117) 214
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 609
99.5%
Space Separator 1
 
0.2%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 79
 
13.0%
유 77
 
12.6%
치 75
 
12.3%
대 26
 
4.3%
교 25
 
4.1%
학 24
 
3.9%
초 23
 
3.8%
등 23
 
3.8%
병 23
 
3.8%
설 23
 
3.8%
Other values (114) 211
34.6%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 609
99.5%
Common 3
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 79
 
13.0%
유 77
 
12.6%
치 75
 
12.3%
대 26
 
4.3%
교 25
 
4.1%
학 24
 
3.9%
초 23
 
3.8%
등 23
 
3.8%
병 23
 
3.8%
설 23
 
3.8%
Other values (114) 211
34.6%
Common
ValueCountFrequency (%)
1
33.3%
) 1
33.3%
( 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 609
99.5%
ASCII 3
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 79
 
13.0%
유 77
 
12.6%
치 75
 
12.3%
대 26
 
4.3%
교 25
 
4.1%
학 24
 
3.9%
초 23
 
3.8%
등 23
 
3.8%
병 23
 
3.8%
설 23
 
3.8%
Other values (114) 211
34.6%
ASCII
ValueCountFrequency (%)
1
33.3%
) 1
33.3%
( 1
33.3%

새주소
Text

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2023-12-12T13:18:29.604000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length16.506667
Min length12

Characters and Unicode

Total characters1238
Distinct characters86
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

Unique75 ?
Unique (%)100.0%

Sample

1st row서구 벌곡길1359(가수원동)
2nd row서구 기성초교길42(매노동)
3rd row서구 가장로 150(가장동)
4th row서구 월평동로 2 (갈마동)
5th row서구 관저동로161(관저동)
ValueCountFrequency (%)
서구 75
31.5%
둔산동 4
 
1.7%
가수원동 4
 
1.7%
도마동 4
 
1.7%
월평동 4
 
1.7%
갈마동 3
 
1.3%
탄방동 3
 
1.3%
내동 3
 
1.3%
신갈마로 3
 
1.3%
도안동 3
 
1.3%
Other values (119) 132
55.5%
2023-12-12T13:18:30.081161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
163
 
13.2%
동 85
 
6.9%
서 84
 
6.8%
구 76
 
6.1%
( 75
 
6.1%
) 75
 
6.1%
로 69
 
5.6%
1 47
 
3.8%
2 27
 
2.2%
관 26
 
2.1%
Other values (76) 511
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 689
55.7%
Decimal Number 233
 
18.8%
Space Separator 163
 
13.2%
Open Punctuation 75
 
6.1%
Close Punctuation 75
 
6.1%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 85
 
12.3%
서 84
 
12.2%
구 76
 
11.0%
로 69
 
10.0%
관 26
 
3.8%
저 25
 
3.6%
길 22
 
3.2%
마 18
 
2.6%
도 17
 
2.5%
번 16
 
2.3%
Other values (62) 251
36.4%
Decimal Number
ValueCountFrequency (%)
1 47
20.2%
2 27
11.6%
3 25
10.7%
6 24
10.3%
5 24
10.3%
4 23
9.9%
0 22
9.4%
7 21
9.0%
9 12
 
5.2%
8 8
 
3.4%
Space Separator
ValueCountFrequency (%)
163
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 689
55.7%
Common 549
44.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 85
 
12.3%
서 84
 
12.2%
구 76
 
11.0%
로 69
 
10.0%
관 26
 
3.8%
저 25
 
3.6%
길 22
 
3.2%
마 18
 
2.6%
도 17
 
2.5%
번 16
 
2.3%
Other values (62) 251
36.4%
Common
ValueCountFrequency (%)
163
29.7%
( 75
13.7%
) 75
13.7%
1 47
 
8.6%
2 27
 
4.9%
3 25
 
4.6%
6 24
 
4.4%
5 24
 
4.4%
4 23
 
4.2%
0 22
 
4.0%
Other values (4) 44
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 689
55.7%
ASCII 549
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
163
29.7%
( 75
13.7%
) 75
13.7%
1 47
 
8.6%
2 27
 
4.9%
3 25
 
4.6%
6 24
 
4.4%
5 24
 
4.4%
4 23
 
4.2%
0 22
 
4.0%
Other values (4) 44
 
8.0%
Hangul
ValueCountFrequency (%)
동 85
 
12.3%
서 84
 
12.2%
구 76
 
11.0%
로 69
 
10.0%
관 26
 
3.8%
저 25
 
3.6%
길 22
 
3.2%
마 18
 
2.6%
도 17
 
2.5%
번 16
 
2.3%
Other values (62) 251
36.4%

주소
Text

Distinct74
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2023-12-12T13:18:30.465382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length16.666667
Min length13

Characters and Unicode

Total characters1250
Distinct characters47
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

Unique73 ?
Unique (%)97.3%

Sample

1st row대전광역시 서구 가수원동 471
2nd row대전광역시 서구 매노동 163
3rd row대전광역시 서구 가장동 25-1
4th row대전광역시 서구 갈마동 114-26
5th row대전광역시 서구 관저동 992
ValueCountFrequency (%)
대전광역시 75
25.0%
서구 75
25.0%
관저동 13
 
4.3%
월평동 9
 
3.0%
갈마동 6
 
2.0%
둔산동 6
 
2.0%
도안동 6
 
2.0%
내동 5
 
1.7%
도마동 5
 
1.7%
탄방동 4
 
1.3%
Other values (84) 96
32.0%
2023-12-12T13:18:30.970521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
228
18.2%
대 75
 
6.0%
광 75
 
6.0%
역 75
 
6.0%
시 75
 
6.0%
서 75
 
6.0%
구 75
 
6.0%
동 75
 
6.0%
전 75
 
6.0%
1 66
 
5.3%
Other values (37) 356
28.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 747
59.8%
Decimal Number 255
 
20.4%
Space Separator 228
 
18.2%
Dash Punctuation 20
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 75
10.0%
광 75
10.0%
역 75
10.0%
시 75
10.0%
서 75
10.0%
구 75
10.0%
동 75
10.0%
전 75
10.0%
저 13
 
1.7%
관 13
 
1.7%
Other values (25) 121
16.2%
Decimal Number
ValueCountFrequency (%)
1 66
25.9%
3 35
13.7%
2 29
11.4%
4 23
 
9.0%
6 22
 
8.6%
9 22
 
8.6%
8 18
 
7.1%
0 16
 
6.3%
5 14
 
5.5%
7 10
 
3.9%
Space Separator
ValueCountFrequency (%)
228
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 747
59.8%
Common 503
40.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 75
10.0%
광 75
10.0%
역 75
10.0%
시 75
10.0%
서 75
10.0%
구 75
10.0%
동 75
10.0%
전 75
10.0%
저 13
 
1.7%
관 13
 
1.7%
Other values (25) 121
16.2%
Common
ValueCountFrequency (%)
228
45.3%
1 66
 
13.1%
3 35
 
7.0%
2 29
 
5.8%
4 23
 
4.6%
6 22
 
4.4%
9 22
 
4.4%
- 20
 
4.0%
8 18
 
3.6%
0 16
 
3.2%
Other values (2) 24
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 747
59.8%
ASCII 503
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
228
45.3%
1 66
 
13.1%
3 35
 
7.0%
2 29
 
5.8%
4 23
 
4.6%
6 22
 
4.4%
9 22
 
4.4%
- 20
 
4.0%
8 18
 
3.6%
0 16
 
3.2%
Other values (2) 24
 
4.8%
Hangul
ValueCountFrequency (%)
대 75
10.0%
광 75
10.0%
역 75
10.0%
시 75
10.0%
서 75
10.0%
구 75
10.0%
동 75
10.0%
전 75
10.0%
저 13
 
1.7%
관 13
 
1.7%
Other values (25) 121
16.2%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170582 × 109
Minimum3.017051 × 109
Maximum3.017065 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-12T13:18:31.118392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.017052 × 109
Q13.0170565 × 109
median3.0170587 × 109
Q33.0170597 × 109
95-th percentile3.017064 × 109
Maximum3.017065 × 109
Range14000
Interquartile range (IQR)3200

Descriptive statistics

Standard deviation3378.1369
Coefficient of variation (CV)1.1196791 × 10-6
Kurtosis0.01737636
Mean3.0170582 × 109
Median Absolute Deviation (MAD)1000
Skewness-0.061407289
Sum2.2627937 × 1011
Variance11411809
MonotonicityNot monotonic
2023-12-12T13:18:31.234127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3017059000 10
13.3%
3017059700 9
12.0%
3017064000 6
 
8.0%
3017058100 5
 
6.7%
3017057500 5
 
6.7%
3017058600 4
 
5.3%
3017055500 4
 
5.3%
3017059600 4
 
5.3%
3017053500 4
 
5.3%
3017052000 3
 
4.0%
Other values (11) 21
28.0%
ValueCountFrequency (%)
3017051000 2
 
2.7%
3017052000 3
4.0%
3017053000 2
 
2.7%
3017053500 4
5.3%
3017054000 2
 
2.7%
3017055500 4
5.3%
3017056000 2
 
2.7%
3017057000 2
 
2.7%
3017057500 5
6.7%
3017058100 5
6.7%
ValueCountFrequency (%)
3017065000 3
 
4.0%
3017064000 6
8.0%
3017063000 1
 
1.3%
3017060000 1
 
1.3%
3017059700 9
12.0%
3017059600 4
 
5.3%
3017059000 10
13.3%
3017058800 3
 
4.0%
3017058700 2
 
2.7%
3017058600 4
 
5.3%

행정동
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
가수원동
10 
관저2동
9 
둔산2동
6 
갈마1동
5 
내동
5 
Other values (16)
40 

Length

Max length4
Median length4
Mean length3.5733333
Min length2

Unique

Unique3 ?
Unique (%)4.0%

Sample

1st row가수원동
2nd row기성동
3rd row가장동
4th row갈마1동
5th row관저1동

Common Values

ValueCountFrequency (%)
가수원동 10
13.3%
관저2동 9
12.0%
둔산2동 6
 
8.0%
갈마1동 5
 
6.7%
내동 5
 
6.7%
관저1동 4
 
5.3%
탄방동 4
 
5.3%
월평1동 4
 
5.3%
정림동 4
 
5.3%
월평3동 3
 
4.0%
Other values (11) 21
28.0%

Length

2023-12-12T13:18:31.382129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가수원동 10
13.3%
관저2동 9
12.0%
둔산2동 6
 
8.0%
갈마1동 5
 
6.7%
내동 5
 
6.7%
관저1동 4
 
5.3%
탄방동 4
 
5.3%
월평1동 4
 
5.3%
정림동 4
 
5.3%
만년동 3
 
4.0%
Other values (11) 21
28.0%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170112 × 109
Minimum3.0170101 × 109
Maximum3.0170128 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-12T13:18:31.516627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0170101 × 109
5-th percentile3.0170103 × 109
Q13.0170109 × 109
median3.0170112 × 109
Q33.0170115 × 109
95-th percentile3.0170121 × 109
Maximum3.0170128 × 109
Range2700
Interquartile range (IQR)600

Descriptive statistics

Standard deviation589.76862
Coefficient of variation (CV)1.9548109 × 10-7
Kurtosis1.1846594
Mean3.0170112 × 109
Median Absolute Deviation (MAD)300
Skewness0.46738199
Sum2.2627584 × 1011
Variance347827.03
MonotonicityNot monotonic
2023-12-12T13:18:31.641315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3017011600 13
17.3%
3017011300 9
12.0%
3017011200 7
9.3%
3017011100 6
8.0%
3017011500 6
8.0%
3017011000 5
 
6.7%
3017010300 5
 
6.7%
3017011400 4
 
5.3%
3017010600 4
 
5.3%
3017012800 3
 
4.0%
Other values (7) 13
17.3%
ValueCountFrequency (%)
3017010100 2
 
2.7%
3017010200 2
 
2.7%
3017010300 5
6.7%
3017010400 3
4.0%
3017010600 4
5.3%
3017010800 2
 
2.7%
3017010900 2
 
2.7%
3017011000 5
6.7%
3017011100 6
8.0%
3017011200 7
9.3%
ValueCountFrequency (%)
3017012800 3
 
4.0%
3017012700 1
 
1.3%
3017011800 1
 
1.3%
3017011600 13
17.3%
3017011500 6
8.0%
3017011400 4
 
5.3%
3017011300 9
12.0%
3017011200 7
9.3%
3017011100 6
8.0%
3017011000 5
 
6.7%

법정동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
관저동
13 
월평동
9 
둔산동
7 
갈마동
6 
도안동
6 
Other values (12)
34 

Length

Max length4
Median length3
Mean length2.96
Min length2

Unique

Unique2 ?
Unique (%)2.7%

Sample

1st row가수원동
2nd row매노동
3rd row가장동
4th row갈마동
5th row관저동

Common Values

ValueCountFrequency (%)
관저동 13
17.3%
월평동 9
12.0%
둔산동 7
9.3%
갈마동 6
8.0%
도안동 6
8.0%
내동 5
 
6.7%
도마동 5
 
6.7%
탄방동 4
 
5.3%
가수원동 4
 
5.3%
정림동 3
 
4.0%
Other values (7) 13
17.3%

Length

2023-12-12T13:18:31.757046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관저동 13
17.3%
월평동 9
12.0%
둔산동 7
9.3%
갈마동 6
8.0%
도안동 6
8.0%
내동 5
 
6.7%
도마동 5
 
6.7%
가수원동 4
 
5.3%
탄방동 4
 
5.3%
정림동 3
 
4.0%
Other values (7) 13
17.3%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.3652
Minimum127.32628
Maximum127.401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-12T13:18:32.162956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.32628
5-th percentile127.33279
Q1127.34747
median127.36908
Q3127.37869
95-th percentile127.39198
Maximum127.401
Range0.0747259
Interquartile range (IQR)0.03122515

Descriptive statistics

Standard deviation0.019042013
Coefficient of variation (CV)0.00014950719
Kurtosis-0.9480481
Mean127.3652
Median Absolute Deviation (MAD)0.013386
Skewness-0.32127725
Sum9552.3901
Variance0.00036259827
MonotonicityNot monotonic
2023-12-12T13:18:32.299016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.3398808 2
 
2.7%
127.3536182 1
 
1.3%
127.3780768 1
 
1.3%
127.3914356 1
 
1.3%
127.3938196 1
 
1.3%
127.3754612 1
 
1.3%
127.3654966 1
 
1.3%
127.3919524 1
 
1.3%
127.3918713 1
 
1.3%
127.3781372 1
 
1.3%
Other values (64) 64
85.3%
ValueCountFrequency (%)
127.3262776 1
1.3%
127.329642 1
1.3%
127.3296913 1
1.3%
127.3299624 1
1.3%
127.3340007 1
1.3%
127.3368776 1
1.3%
127.3380816 1
1.3%
127.3386154 1
1.3%
127.3388111 1
1.3%
127.3398808 2
2.7%
ValueCountFrequency (%)
127.4010035 1
1.3%
127.3938196 1
1.3%
127.3933666 1
1.3%
127.3920514 1
1.3%
127.3919524 1
1.3%
127.3918713 1
1.3%
127.3914356 1
1.3%
127.3884957 1
1.3%
127.387658 1
1.3%
127.386469 1
1.3%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.328878
Minimum36.249109
Maximum36.369812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-12T13:18:32.432055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.249109
5-th percentile36.296015
Q136.306357
median36.330616
Q336.351736
95-th percentile36.363293
Maximum36.369812
Range0.120703
Interquartile range (IQR)0.04537885

Descriptive statistics

Standard deviation0.025384443
Coefficient of variation (CV)0.00069874006
Kurtosis-0.38556913
Mean36.328878
Median Absolute Deviation (MAD)0.0240364
Skewness-0.34724347
Sum2724.6659
Variance0.00064436993
MonotonicityNot monotonic
2023-12-12T13:18:32.562767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.3063571 2
 
2.7%
36.3026739 1
 
1.3%
36.3395836 1
 
1.3%
36.3478807 1
 
1.3%
36.3479018 1
 
1.3%
36.3588385 1
 
1.3%
36.2891827 1
 
1.3%
36.3587884 1
 
1.3%
36.3634834 1
 
1.3%
36.3698116 1
 
1.3%
Other values (64) 64
85.3%
ValueCountFrequency (%)
36.2491086 1
1.3%
36.2891827 1
1.3%
36.2944326 1
1.3%
36.2946028 1
1.3%
36.2966207 1
1.3%
36.2972849 1
1.3%
36.2981609 1
1.3%
36.2983949 1
1.3%
36.2984864 1
1.3%
36.2986668 1
1.3%
ValueCountFrequency (%)
36.3698116 1
1.3%
36.3667704 1
1.3%
36.3658383 1
1.3%
36.3634834 1
1.3%
36.3632117 1
1.3%
36.3628933 1
1.3%
36.3620717 1
1.3%
36.3607481 1
1.3%
36.3588524 1
1.3%
36.3588385 1
1.3%

전화번호
Text

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2023-12-12T13:18:32.848153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters900
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

Unique75 ?
Unique (%)100.0%

Sample

1st row042-542-3516
2nd row042-585-4611
3rd row042-533-8116
4th row042-477-0664
5th row042-544-2161
ValueCountFrequency (%)
042-542-3516 1
 
1.3%
042-582-8119 1
 
1.3%
042-364-7979 1
 
1.3%
042-489-5673 1
 
1.3%
042-582-8005 1
 
1.3%
042-488-3456 1
 
1.3%
042-472-1198 1
 
1.3%
042-485-6277 1
 
1.3%
042-522-8874 1
 
1.3%
042-541-6064 1
 
1.3%
Other values (65) 65
86.7%
2023-12-12T13:18:33.366720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 152
16.9%
- 150
16.7%
2 125
13.9%
0 120
13.3%
5 83
9.2%
8 60
 
6.7%
3 55
 
6.1%
1 53
 
5.9%
6 45
 
5.0%
7 37
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 750
83.3%
Dash Punctuation 150
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 152
20.3%
2 125
16.7%
0 120
16.0%
5 83
11.1%
8 60
 
8.0%
3 55
 
7.3%
1 53
 
7.1%
6 45
 
6.0%
7 37
 
4.9%
9 20
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 900
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 152
16.9%
- 150
16.7%
2 125
13.9%
0 120
13.3%
5 83
9.2%
8 60
 
6.7%
3 55
 
6.1%
1 53
 
5.9%
6 45
 
5.0%
7 37
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 152
16.9%
- 150
16.7%
2 125
13.9%
0 120
13.3%
5 83
9.2%
8 60
 
6.7%
3 55
 
6.1%
1 53
 
5.9%
6 45
 
5.0%
7 37
 
4.1%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

Interactions

2023-12-12T13:18:27.748710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:26.211945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:26.741425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:27.261552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:27.851572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:26.364612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:26.872254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:27.399085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:27.976236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:26.502292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:26.980627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:27.519803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:28.121400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:26.629817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:27.113027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:27.639763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:18:33.511824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유치원명새주소주소행정동코드행정동법정동코드법정동X좌표Y좌표전화번호
유치원명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
새주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
행정동코드1.0001.0001.0001.0001.0000.8120.9680.6910.6671.000
행정동1.0001.0001.0001.0001.0000.9950.9900.8730.9181.000
법정동코드1.0001.0001.0000.8120.9951.0001.0000.6660.9111.000
법정동1.0001.0001.0000.9680.9901.0001.0000.8630.9101.000
X좌표1.0001.0001.0000.6910.8730.6660.8631.0000.5731.000
Y좌표1.0001.0001.0000.6670.9180.9110.9100.5731.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-12T13:18:33.652326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동행정동
법정동1.0000.878
행정동0.8781.000
2023-12-12T13:18:33.755957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드법정동코드X좌표Y좌표행정동법정동
행정동코드1.0000.804-0.2960.1050.9050.827
법정동코드0.8041.000-0.652-0.1640.8490.930
X좌표-0.296-0.6521.0000.6200.5100.535
Y좌표0.105-0.1640.6201.0000.6320.640
행정동0.9050.8490.5100.6321.0000.878
법정동0.8270.9300.5350.6400.8781.000

Missing values

2023-12-12T13:18:28.287624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:18:28.510095image/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

유치원명새주소주소행정동코드행정동법정동코드법정동X좌표Y좌표전화번호비고
0가수원초등학교 병설유치원서구 벌곡길1359(가수원동)대전광역시 서구 가수원동 4713017059000가수원동3017011400가수원동127.35361836.302674042-542-3516<NA>
1기성초등학교병설유치원서구 기성초교길42(매노동)대전광역시 서구 매노동 1633017060000기성동3017011800매노동127.33808236.249109042-585-4611<NA>
2대전가장초등학교병설유치원서구 가장로 150(가장동)대전광역시 서구 가장동 25-13017057000가장동3017010900가장동127.38849636.330616042-533-8116<NA>
3대전갈마유치원서구 월평동로 2 (갈마동)대전광역시 서구 갈마동 114-263017058100갈마1동3017011100갈마동127.36937536.356409042-477-0664<NA>
4대전관저초등학교병설유치원서구 관저동로161(관저동)대전광역시 서구 관저동 9923017059600관저1동3017011600관저동127.33988136.306357042-544-2161<NA>
5대전구봉초등학교병설유치원서구 관저로75(관저동)대전광역시 서구 관저동 11333017059700관저2동3017011600관저동127.32996236.299515042-542-0169<NA>
6대전금동초등학교병설유치원서구 관저로45(관저동)대전광역시 서구 관저동 11413017059700관저2동3017011600관저동127.32627836.298161042-542-3331<NA>
7대전내동초등학교병설유치원서구 동서대로1063번길13(내동)대전광역시 서구 내동 13-13017057500내동3017011000내동127.37901536.330846042-535-8794<NA>
8대전느리울초등학교병설유치원서구 관저로196(관저동)대전광역시 서구 관저동 13963017059700관저2동3017011600관저동127.34404536.298395042-544-0744<NA>
9대전도마초등학교병설유치원서구 배재로172번길 23 (도마동)대전광역시 서구 도마동 273017052000도마1동3017010300도마동127.37173836.324401042-523-5235<NA>
유치원명새주소주소행정동코드행정동법정동코드법정동X좌표Y좌표전화번호비고
65지니어스유치원서구 월평서로 17 (월평동)대전광역시 서구 월평동 11833017058600월평1동3017011300월평동127.35729736.355083042-487-0033<NA>
66청아유치원서구 동서대로 967 (내동)대전광역시 서구 내동 1513017057500내동3017011000내동127.36997536.335819042-531-6166<NA>
67톰지유치원서구 계룡로536번길 9 (괴정동)대전광역시 서구 괴정동 4183017056000괴정동3017010800괴정동127.38272936.3415042-535-1777<NA>
68펀키즈유치원서구 도안동로 77 (가수원동)대전광역시 서구 도안동 15643017059000가수원동3017011500도안동127.34925936.310122042-542-9114<NA>
69평화유치원서구 월평중로13번길 53 (월평동)대전광역시 서구 월평동 10413017058600월평1동3017011300월평동127.3606836.355498042-486-6015<NA>
70프렌즈유치원서구 원도안로25번길 97(가수원동)대전광역시 서구 가수원동 8453017059000가수원동3017011400가수원동127.34734236.308967042-716-1212<NA>
71피피쿠스유치원서구 동서대로1005번길 106 (내동)대전광역시 서구 도마동 19-13017052000도마1동3017010300도마동127.37365136.326123042-532-6770<NA>
72하이캠유치원서구 계룡로325번길 16 (월평동)대전광역시 서구 월평동 8083017058600월평1동3017011300월평동127.36551936.355136042-489-0116<NA>
73한양유치원서구 계룡로571번길 65 (탄방동)대전광역시 서구 탄방동 6893017055500탄방동3017010600탄방동127.38646936.344755042-488-0082<NA>
74혜천유치원서구 혜천로 100 (복수동)대전광역시 서구 복수동 3333017051000복수동3017010100복수동127.37580936.302747042-582-6767<NA>