Overview

Dataset statistics

Number of variables8
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory70.9 B

Variable types

Categorical2
Text2
Numeric4

Dataset

Description경기도 평택시 내 소재한 수해대피소에 대한 데이터로 구분, 시설명, 주소, 위도, 경도, 면적, 수용(명)을 제공합니다.※ 문의 : 안전총괄과(031-8024-4921)
Author경기도 평택시
URLhttps://www.data.go.kr/data/15113913/fileData.do

Alerts

기준일자 has constant value ""Constant
면적(제곱미터) is highly overall correlated with 수용(명) and 1 other fieldsHigh correlation
수용(명) is highly overall correlated with 면적(제곱미터) and 1 other fieldsHigh correlation
구분 is highly overall correlated with 면적(제곱미터) and 1 other fieldsHigh correlation
구분 is highly imbalanced (84.4%)Imbalance
시설명 has unique valuesUnique
주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2024-03-14 13:20:56.644605
Analysis finished2024-03-14 13:21:01.942344
Duration5.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size480.0 B
학교
43 
기타
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row학교
2nd row학교
3rd row기타
4th row학교
5th row학교

Common Values

ValueCountFrequency (%)
학교 43
97.7%
기타 1
 
2.3%

Length

2024-03-14T22:21:02.139244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:21:02.458890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교 43
97.7%
기타 1
 
2.3%

시설명
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-14T22:21:03.372496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.0681818
Min length5

Characters and Unicode

Total characters267
Distinct characters66
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

Unique44 ?
Unique (%)100.0%

Sample

1st row가사초등학교
2nd row갈곶초등학교
3rd row서부복지타운
4th row경기물류고등학교
5th row도곡중학교
ValueCountFrequency (%)
가사초등학교 1
 
2.3%
갈곶초등학교 1
 
2.3%
청북초등학교 1
 
2.3%
평택이화초등학교 1
 
2.3%
장당중학교 1
 
2.3%
장당초등학교 1
 
2.3%
평택중앙초등학교 1
 
2.3%
지장초등학교 1
 
2.3%
진위고등학교 1
 
2.3%
진위초등학교 1
 
2.3%
Other values (34) 34
77.3%
2024-03-14T22:21:04.696507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 44
16.5%
학 43
16.1%
등 36
13.5%
초 31
 
11.6%
중 9
 
3.4%
고 6
 
2.2%
송 5
 
1.9%
평 5
 
1.9%
지 4
 
1.5%
택 4
 
1.5%
Other values (56) 80
30.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 267
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 44
16.5%
학 43
16.1%
등 36
13.5%
초 31
 
11.6%
중 9
 
3.4%
고 6
 
2.2%
송 5
 
1.9%
평 5
 
1.9%
지 4
 
1.5%
택 4
 
1.5%
Other values (56) 80
30.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 267
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 44
16.5%
학 43
16.1%
등 36
13.5%
초 31
 
11.6%
중 9
 
3.4%
고 6
 
2.2%
송 5
 
1.9%
평 5
 
1.9%
지 4
 
1.5%
택 4
 
1.5%
Other values (56) 80
30.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 267
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 44
16.5%
학 43
16.1%
등 36
13.5%
초 31
 
11.6%
중 9
 
3.4%
고 6
 
2.2%
송 5
 
1.9%
평 5
 
1.9%
지 4
 
1.5%
택 4
 
1.5%
Other values (56) 80
30.0%

주소
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-14T22:21:05.697529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length20.204545
Min length16

Characters and Unicode

Total characters889
Distinct characters88
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

Unique44 ?
Unique (%)100.0%

Sample

1st row경기도 평택시 현덕면 기산2길 16
2nd row경기도 평택시 진위면 엘지로 57
3rd row경기도 평택시 안중읍 서동대로 1557
4th row경기도 평택시 안중읍 안현로 403
5th row경기도 평택시 포승읍 여술로 58
ValueCountFrequency (%)
경기도 44
22.4%
평택시 44
22.4%
포승읍 4
 
2.0%
진위면 3
 
1.5%
안중읍 3
 
1.5%
팽성읍 2
 
1.0%
평남로 2
 
1.0%
서동대로 2
 
1.0%
송탄로 2
 
1.0%
이충로35번길 2
 
1.0%
Other values (87) 88
44.9%
2024-03-14T22:21:07.264847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
152
17.1%
평 50
 
5.6%
택 47
 
5.3%
기 46
 
5.2%
경 45
 
5.1%
시 45
 
5.1%
도 44
 
4.9%
로 34
 
3.8%
동 31
 
3.5%
( 25
 
2.8%
Other values (78) 370
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 560
63.0%
Space Separator 152
 
17.1%
Decimal Number 124
 
13.9%
Open Punctuation 25
 
2.8%
Close Punctuation 25
 
2.8%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 50
 
8.9%
택 47
 
8.4%
기 46
 
8.2%
경 45
 
8.0%
시 45
 
8.0%
도 44
 
7.9%
로 34
 
6.1%
동 31
 
5.5%
길 17
 
3.0%
서 12
 
2.1%
Other values (64) 189
33.8%
Decimal Number
ValueCountFrequency (%)
1 21
16.9%
5 20
16.1%
3 16
12.9%
2 16
12.9%
6 16
12.9%
7 9
7.3%
0 9
7.3%
4 9
7.3%
9 5
 
4.0%
8 3
 
2.4%
Space Separator
ValueCountFrequency (%)
152
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 560
63.0%
Common 329
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 50
 
8.9%
택 47
 
8.4%
기 46
 
8.2%
경 45
 
8.0%
시 45
 
8.0%
도 44
 
7.9%
로 34
 
6.1%
동 31
 
5.5%
길 17
 
3.0%
서 12
 
2.1%
Other values (64) 189
33.8%
Common
ValueCountFrequency (%)
152
46.2%
( 25
 
7.6%
) 25
 
7.6%
1 21
 
6.4%
5 20
 
6.1%
3 16
 
4.9%
2 16
 
4.9%
6 16
 
4.9%
7 9
 
2.7%
0 9
 
2.7%
Other values (4) 20
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 560
63.0%
ASCII 329
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
152
46.2%
( 25
 
7.6%
) 25
 
7.6%
1 21
 
6.4%
5 20
 
6.1%
3 16
 
4.9%
2 16
 
4.9%
6 16
 
4.9%
7 9
 
2.7%
0 9
 
2.7%
Other values (4) 20
 
6.1%
Hangul
ValueCountFrequency (%)
평 50
 
8.9%
택 47
 
8.4%
기 46
 
8.2%
경 45
 
8.0%
시 45
 
8.0%
도 44
 
7.9%
로 34
 
6.1%
동 31
 
5.5%
길 17
 
3.0%
서 12
 
2.1%
Other values (64) 189
33.8%

위도
Real number (ℝ)

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.030063
Minimum36.938062
Maximum37.125431
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T22:21:07.838511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.938062
5-th percentile36.965552
Q136.989842
median37.0299
Q337.063938
95-th percentile37.106045
Maximum37.125431
Range0.1873688
Interquartile range (IQR)0.07409635

Descriptive statistics

Standard deviation0.045332925
Coefficient of variation (CV)0.0012242195
Kurtosis-0.84104407
Mean37.030063
Median Absolute Deviation (MAD)0.0388006
Skewness0.13938803
Sum1629.3228
Variance0.0020550741
MonotonicityNot monotonic
2024-03-14T22:21:08.282037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
36.9380623 1
 
2.3%
37.0594031 1
 
2.3%
37.0514229 1
 
2.3%
37.0499477 1
 
2.3%
37.0020806 1
 
2.3%
37.067879 1
 
2.3%
37.1109979 1
 
2.3%
37.100622 1
 
2.3%
36.9625767 1
 
2.3%
37.0431127 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
36.9380623 1
2.3%
36.9625767 1
2.3%
36.9655432 1
2.3%
36.9656024 1
2.3%
36.9815543 1
2.3%
36.9868192 1
2.3%
36.9868958 1
2.3%
36.9891849 1
2.3%
36.9892524 1
2.3%
36.9892919 1
2.3%
ValueCountFrequency (%)
37.1254311 1
2.3%
37.1109979 1
2.3%
37.1070024 1
2.3%
37.100622 1
2.3%
37.0802559 1
2.3%
37.0770496 1
2.3%
37.0761821 1
2.3%
37.0751893 1
2.3%
37.070937 1
2.3%
37.0695226 1
2.3%

경도
Real number (ℝ)

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.02982
Minimum126.84192
Maximum127.11692
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T22:21:08.688637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.84192
5-th percentile126.88287
Q1127.01651
median127.06076
Q3127.07351
95-th percentile127.1059
Maximum127.11692
Range0.274998
Interquartile range (IQR)0.05700475

Descriptive statistics

Standard deviation0.075810452
Coefficient of variation (CV)0.00059679254
Kurtosis0.1793617
Mean127.02982
Median Absolute Deviation (MAD)0.023254
Skewness-1.2156185
Sum5589.3123
Variance0.0057472246
MonotonicityNot monotonic
2024-03-14T22:21:09.106778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
126.916946 1
 
2.3%
127.068909 1
 
2.3%
127.062989 1
 
2.3%
127.057715 1
 
2.3%
127.077633 1
 
2.3%
127.057593 1
 
2.3%
127.069056 1
 
2.3%
127.089948 1
 
2.3%
127.06322 1
 
2.3%
126.93559 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
126.841923 1
2.3%
126.848964 1
2.3%
126.881709 1
2.3%
126.889456 1
2.3%
126.916946 1
2.3%
126.921329 1
2.3%
126.921843 1
2.3%
126.922542 1
2.3%
126.929731 1
2.3%
126.93559 1
2.3%
ValueCountFrequency (%)
127.116921 1
2.3%
127.108182 1
2.3%
127.107287 1
2.3%
127.098064 1
2.3%
127.097505 1
2.3%
127.093472 1
2.3%
127.089948 1
2.3%
127.08698 1
2.3%
127.082935 1
2.3%
127.081372 1
2.3%

면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1421.5455
Minimum169
Maximum8761
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T22:21:09.512896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169
5-th percentile274.05
Q1597.75
median803.5
Q31313.25
95-th percentile4353.05
Maximum8761
Range8592
Interquartile range (IQR)715.5

Descriptive statistics

Standard deviation1730.0628
Coefficient of variation (CV)1.2170296
Kurtosis9.0732151
Mean1421.5455
Median Absolute Deviation (MAD)215
Skewness2.9154649
Sum62548
Variance2993117.4
MonotonicityNot monotonic
2024-03-14T22:21:09.930351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1786 1
 
2.3%
331 1
 
2.3%
264 1
 
2.3%
2613 1
 
2.3%
585 1
 
2.3%
727 1
 
2.3%
1741 1
 
2.3%
650 1
 
2.3%
4406 1
 
2.3%
372 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
169 1
2.3%
202 1
2.3%
264 1
2.3%
331 1
2.3%
372 1
2.3%
394 1
2.3%
576 1
2.3%
582 1
2.3%
585 1
2.3%
586 1
2.3%
ValueCountFrequency (%)
8761 1
2.3%
7115 1
2.3%
4406 1
2.3%
4053 1
2.3%
3548 1
2.3%
2613 1
2.3%
2193 1
2.3%
2048 1
2.3%
1786 1
2.3%
1741 1
2.3%

수용(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean538.25
Minimum65
Maximum3369
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T22:21:10.320680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile104.9
Q1229.25
median308.5
Q3504.25
95-th percentile1673.6
Maximum3369
Range3304
Interquartile range (IQR)275

Descriptive statistics

Standard deviation662.60845
Coefficient of variation (CV)1.2310422
Kurtosis9.432345
Mean538.25
Median Absolute Deviation (MAD)82.5
Skewness2.9809775
Sum23683
Variance439049.96
MonotonicityNot monotonic
2024-03-14T22:21:10.747351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
279 2
 
4.5%
686 1
 
2.3%
2736 1
 
2.3%
101 1
 
2.3%
700 1
 
2.3%
177 1
 
2.3%
669 1
 
2.3%
250 1
 
2.3%
1694 1
 
2.3%
143 1
 
2.3%
Other values (33) 33
75.0%
ValueCountFrequency (%)
65 1
2.3%
77 1
2.3%
101 1
2.3%
127 1
2.3%
143 1
2.3%
151 1
2.3%
177 1
2.3%
221 1
2.3%
223 1
2.3%
225 1
2.3%
ValueCountFrequency (%)
3369 1
2.3%
2736 1
2.3%
1694 1
2.3%
1558 1
2.3%
1364 1
2.3%
843 1
2.3%
787 1
2.3%
700 1
2.3%
686 1
2.3%
669 1
2.3%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-02-16
44 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-16
2nd row2024-02-16
3rd row2024-02-16
4th row2024-02-16
5th row2024-02-16

Common Values

ValueCountFrequency (%)
2024-02-16 44
100.0%

Length

2024-03-14T22:21:11.155592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:21:11.461937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-16 44
100.0%

Interactions

2024-03-14T22:21:00.336962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:57.119254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:58.279018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:59.369625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:21:00.702734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:57.394562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:58.550791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:59.623965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:21:01.023227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:57.663787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:58.801781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:59.845350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:21:01.221716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:57.936027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:20:59.048572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:21:00.083503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:21:11.652522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시설명주소위도경도면적(제곱미터)수용(명)
구분1.0001.0001.0000.0000.2491.0001.000
시설명1.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.000
위도0.0001.0001.0001.0000.2980.1530.000
경도0.2491.0001.0000.2981.0000.0000.000
면적(제곱미터)1.0001.0001.0000.1530.0001.0000.999
수용(명)1.0001.0001.0000.0000.0000.9991.000
2024-03-14T22:21:11.937254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도면적(제곱미터)수용(명)구분
위도1.0000.233-0.064-0.0720.000
경도0.2331.000-0.199-0.2060.218
면적(제곱미터)-0.064-0.1991.0000.9990.939
수용(명)-0.072-0.2060.9991.0000.939
구분0.0000.2180.9390.9391.000

Missing values

2024-03-14T22:21:01.431516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:21:01.786327image/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

구분시설명주소위도경도면적(제곱미터)수용(명)기준일자
0학교가사초등학교경기도 평택시 현덕면 기산2길 1636.938062126.91694617866862024-02-16
1학교갈곶초등학교경기도 평택시 진위면 엘지로 5737.125431127.0721417782992024-02-16
2기타서부복지타운경기도 평택시 안중읍 서동대로 155736.989526126.921843876133692024-02-16
3학교경기물류고등학교경기도 평택시 안중읍 안현로 40336.986819126.92973120487872024-02-16
4학교도곡중학교경기도 평택시 포승읍 여술로 5836.989185126.8489648463252024-02-16
5학교라온중학교경기도 평택시 경기대로1376번길 38-6 (서정동)37.069523127.0680978033082024-02-16
6학교반지초등학교경기도 평택시 이충로 7(이충동)37.057709127.0696839983832024-02-16
7학교복창초등학교경기도 평택시 서정북로 3(서정동)37.070937127.0500626652552024-02-16
8학교부용초등학교경기도 평택시 팽성읍 동서촌로 6536.965543127.05930413105032024-02-16
9학교비전초등학교경기도 평택시 비전1로57번길 63(비전동)37.001096127.0934727262792024-02-16
구분시설명주소위도경도면적(제곱미터)수용(명)기준일자
34학교평택지산초등학교경기도 평택시 지산2로 57(지산동)37.07705127.062211711527362024-02-16
35학교평택초등학교경기도 평택시 원평2로 4(평택동)36.989292127.0813727462872024-02-16
36학교포승중학교경기도 평택시 포승읍 서동대로 113836.981554126.8817099783762024-02-16
37학교합정초등학교경기도 평택시 평택4로 11(합정동)36.989252127.0980646002302024-02-16
38학교현덕초등학교경기도 평택시 현덕면 현덕로 125436.965602126.92132921938432024-02-16
39학교홍원초등학교경기도 평택시 포승읍 외원길 2637.014145126.8894567212772024-02-16
40학교효덕초등학교경기도 평택시 고덕면 효덕새싹길 6-537.016553127.0359365862252024-02-16
41학교효명고등학교경기도 평택시 송탄로 51(장당동)37.049075127.055185405315582024-02-16
42학교고덕초등학교경기도 평택시 함박산로 16137.041199127.0289227162752024-02-16
43학교동삭초등학교경기도 평택시 동삭로 370(동삭동 332-10)37.018601127.0975053941512024-02-16