Overview

Dataset statistics

Number of variables9
Number of observations72
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory78.8 B

Variable types

Numeric5
Text2
Categorical1
DateTime1

Dataset

Description경상남도 사천시 관내에 있는 풍수해대피소 현황입니다.(시설명, 시설구분, 도로명주소, 위도, 경도, 면적, 수용인원)
Author경상남도 사천시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15113935

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 연번High correlation
면적(제곱미터) is highly overall correlated with 수용인원(명)High correlation
수용인원(명) is highly overall correlated with 면적(제곱미터)High correlation
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-20 16:16:59.736274
Analysis finished2024-04-20 16:17:07.100072
Duration7.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.5
Minimum1
Maximum72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2024-04-21T01:17:07.297947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.55
Q118.75
median36.5
Q354.25
95-th percentile68.45
Maximum72
Range71
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation20.92845
Coefficient of variation (CV)0.57338218
Kurtosis-1.2
Mean36.5
Median Absolute Deviation (MAD)18
Skewness0
Sum2628
Variance438
MonotonicityStrictly increasing
2024-04-21T01:17:07.734293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
38 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
Other values (62) 62
86.1%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%

시설명
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size704.0 B
2024-04-21T01:17:08.585367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length7.8055556
Min length4

Characters and Unicode

Total characters562
Distinct characters103
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row금곡마을회관
2nd row장전1리마을회관
3rd row사천중학교 강당
4th row사천초등학교 강당
5th row수양초등학교 강당
ValueCountFrequency (%)
강당 20
 
18.0%
마을회관 5
 
4.5%
경로당 3
 
2.7%
본관 3
 
2.7%
삼천포공업고등학교 3
 
2.7%
삼천포초등학교 2
 
1.8%
체육관 2
 
1.8%
본관동 2
 
1.8%
한내경로당 1
 
0.9%
노산아파트 1
 
0.9%
Other values (69) 69
62.2%
2024-04-21T01:17:09.828198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
6.9%
당 35
 
6.2%
교 33
 
5.9%
관 32
 
5.7%
학 31
 
5.5%
마 26
 
4.6%
등 26
 
4.6%
회 25
 
4.4%
을 24
 
4.3%
강 20
 
3.6%
Other values (93) 271
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 516
91.8%
Space Separator 39
 
6.9%
Decimal Number 3
 
0.5%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 35
 
6.8%
교 33
 
6.4%
관 32
 
6.2%
학 31
 
6.0%
마 26
 
5.0%
등 26
 
5.0%
회 25
 
4.8%
을 24
 
4.7%
강 20
 
3.9%
초 19
 
3.7%
Other values (86) 245
47.5%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 516
91.8%
Common 45
 
8.0%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 35
 
6.8%
교 33
 
6.4%
관 32
 
6.2%
학 31
 
6.0%
마 26
 
5.0%
등 26
 
5.0%
회 25
 
4.8%
을 24
 
4.7%
강 20
 
3.9%
초 19
 
3.7%
Other values (86) 245
47.5%
Common
ValueCountFrequency (%)
39
86.7%
1 2
 
4.4%
) 1
 
2.2%
2 1
 
2.2%
( 1
 
2.2%
, 1
 
2.2%
Latin
ValueCountFrequency (%)
D 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 516
91.8%
ASCII 46
 
8.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
84.8%
1 2
 
4.3%
) 1
 
2.2%
2 1
 
2.2%
( 1
 
2.2%
, 1
 
2.2%
D 1
 
2.2%
Hangul
ValueCountFrequency (%)
당 35
 
6.8%
교 33
 
6.4%
관 32
 
6.2%
학 31
 
6.0%
마 26
 
5.0%
등 26
 
5.0%
회 25
 
4.8%
을 24
 
4.7%
강 20
 
3.9%
초 19
 
3.7%
Other values (86) 245
47.5%

구분
Categorical

Distinct4
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size704.0 B
학교
31 
마을회관
24 
경로당
16 
기타시설
 
1

Length

Max length4
Median length3
Mean length2.9166667
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
학교 31
43.1%
마을회관 24
33.3%
경로당 16
22.2%
기타시설 1
 
1.4%

Length

2024-04-21T01:17:10.272579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T01:17:10.626058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교 31
43.1%
마을회관 24
33.3%
경로당 16
22.2%
기타시설 1
 
1.4%

도로명주소
Text

Distinct71
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size704.0 B
2024-04-21T01:17:11.777948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length20.722222
Min length18

Characters and Unicode

Total characters1492
Distinct characters114
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)97.2%

Sample

1st row경상남도 사천시 사천읍 거무실안길 3
2nd row경상남도 사천시 사천읍 구암두문로 585
3rd row경상남도 사천시 사천읍 동문로 20
4th row경상남도 사천시 사천읍 읍내로 59
5th row경상남도 사천시 사천읍 옥산로 60
ValueCountFrequency (%)
경상남도 72
21.8%
사천시 72
21.8%
정동면 6
 
1.8%
곤양면 6
 
1.8%
용현면 5
 
1.5%
사천읍 5
 
1.5%
서포면 4
 
1.2%
곤명면 4
 
1.2%
사남면 4
 
1.2%
삼상로 3
 
0.9%
Other values (139) 150
45.3%
2024-04-21T01:17:13.578565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
259
17.4%
사 86
 
5.8%
남 81
 
5.4%
천 79
 
5.3%
상 79
 
5.3%
도 77
 
5.2%
경 72
 
4.8%
시 72
 
4.8%
동 63
 
4.2%
길 51
 
3.4%
Other values (104) 573
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 963
64.5%
Space Separator 259
 
17.4%
Decimal Number 186
 
12.5%
Open Punctuation 36
 
2.4%
Close Punctuation 36
 
2.4%
Dash Punctuation 11
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 86
 
8.9%
남 81
 
8.4%
천 79
 
8.2%
상 79
 
8.2%
도 77
 
8.0%
경 72
 
7.5%
시 72
 
7.5%
동 63
 
6.5%
길 51
 
5.3%
면 31
 
3.2%
Other values (89) 272
28.2%
Decimal Number
ValueCountFrequency (%)
1 39
21.0%
2 32
17.2%
3 20
10.8%
4 19
10.2%
5 19
10.2%
7 14
 
7.5%
6 13
 
7.0%
9 10
 
5.4%
0 10
 
5.4%
8 10
 
5.4%
Space Separator
ValueCountFrequency (%)
259
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 963
64.5%
Common 529
35.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 86
 
8.9%
남 81
 
8.4%
천 79
 
8.2%
상 79
 
8.2%
도 77
 
8.0%
경 72
 
7.5%
시 72
 
7.5%
동 63
 
6.5%
길 51
 
5.3%
면 31
 
3.2%
Other values (89) 272
28.2%
Common
ValueCountFrequency (%)
259
49.0%
1 39
 
7.4%
( 36
 
6.8%
) 36
 
6.8%
2 32
 
6.0%
3 20
 
3.8%
4 19
 
3.6%
5 19
 
3.6%
7 14
 
2.6%
6 13
 
2.5%
Other values (5) 42
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 963
64.5%
ASCII 529
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
259
49.0%
1 39
 
7.4%
( 36
 
6.8%
) 36
 
6.8%
2 32
 
6.0%
3 20
 
3.8%
4 19
 
3.6%
5 19
 
3.6%
7 14
 
2.6%
6 13
 
2.5%
Other values (5) 42
 
7.9%
Hangul
ValueCountFrequency (%)
사 86
 
8.9%
남 81
 
8.4%
천 79
 
8.2%
상 79
 
8.2%
도 77
 
8.0%
경 72
 
7.5%
시 72
 
7.5%
동 63
 
6.5%
길 51
 
5.3%
면 31
 
3.2%
Other values (89) 272
28.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.001994
Minimum34.90392
Maximum35.130344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2024-04-21T01:17:13.996728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.90392
5-th percentile34.929734
Q134.939573
median34.993164
Q335.059599
95-th percentile35.10251
Maximum35.130344
Range0.22642478
Interquartile range (IQR)0.12002589

Descriptive statistics

Standard deviation0.065587908
Coefficient of variation (CV)0.0018738335
Kurtosis-1.3219662
Mean35.001994
Median Absolute Deviation (MAD)0.05871162
Skewness0.34562901
Sum2520.1436
Variance0.0043017737
MonotonicityNot monotonic
2024-04-21T01:17:14.423521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.93467138 2
 
2.8%
35.09818773 1
 
1.4%
34.93428451 1
 
1.4%
34.93002968 1
 
1.4%
34.92950735 1
 
1.4%
34.93271051 1
 
1.4%
34.92991917 1
 
1.4%
34.95366118 1
 
1.4%
34.93317332 1
 
1.4%
34.94128547 1
 
1.4%
Other values (61) 61
84.7%
ValueCountFrequency (%)
34.90391968 1
1.4%
34.92468687 1
1.4%
34.92699038 1
1.4%
34.92950735 1
1.4%
34.92991917 1
1.4%
34.93002968 1
1.4%
34.93030413 1
1.4%
34.93189797 1
1.4%
34.93271051 1
1.4%
34.93317332 1
1.4%
ValueCountFrequency (%)
35.13034446 1
1.4%
35.12999143 1
1.4%
35.12854534 1
1.4%
35.10779369 1
1.4%
35.09818773 1
1.4%
35.09446532 1
1.4%
35.09160756 1
1.4%
35.0906626 1
1.4%
35.08366918 1
1.4%
35.08123658 1
1.4%

경도
Real number (ℝ)

Distinct71
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.06297
Minimum127.93494
Maximum128.15547
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2024-04-21T01:17:14.840516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.93494
5-th percentile127.96075
Q1128.05051
median128.0757
Q3128.09371
95-th percentile128.14242
Maximum128.15547
Range0.2205303
Interquartile range (IQR)0.04320415

Descriptive statistics

Standard deviation0.055185224
Coefficient of variation (CV)0.00043092257
Kurtosis-0.088930695
Mean128.06297
Median Absolute Deviation (MAD)0.0217324
Skewness-0.81325633
Sum9220.5339
Variance0.003045409
MonotonicityNot monotonic
2024-04-21T01:17:15.266861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.0850567 2
 
2.8%
128.1425612 1
 
1.4%
128.0839725 1
 
1.4%
128.0837601 1
 
1.4%
128.0830043 1
 
1.4%
128.0787057 1
 
1.4%
128.073635 1
 
1.4%
128.0781786 1
 
1.4%
128.0739335 1
 
1.4%
128.0757691 1
 
1.4%
Other values (61) 61
84.7%
ValueCountFrequency (%)
127.9349373 1
1.4%
127.9428059 1
1.4%
127.9434339 1
1.4%
127.9593021 1
1.4%
127.9619389 1
1.4%
127.9641095 1
1.4%
127.9673544 1
1.4%
127.9677776 1
1.4%
127.9725762 1
1.4%
127.9732527 1
1.4%
ValueCountFrequency (%)
128.1554676 1
1.4%
128.1501729 1
1.4%
128.1437954 1
1.4%
128.1425612 1
1.4%
128.1422998 1
1.4%
128.132372 1
1.4%
128.1245114 1
1.4%
128.1240504 1
1.4%
128.121834 1
1.4%
128.1119466 1
1.4%

면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean873.75
Minimum43
Maximum9882
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2024-04-21T01:17:15.680191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile63.3
Q192.75
median164
Q3888
95-th percentile3542.35
Maximum9882
Range9839
Interquartile range (IQR)795.25

Descriptive statistics

Standard deviation1722.8777
Coefficient of variation (CV)1.9718199
Kurtosis15.868875
Mean873.75
Median Absolute Deviation (MAD)112
Skewness3.7770436
Sum62910
Variance2968307.5
MonotonicityNot monotonic
2024-04-21T01:17:16.109410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66 5
 
6.9%
132 3
 
4.2%
43 2
 
2.8%
135 2
 
2.8%
86 2
 
2.8%
703 2
 
2.8%
96 2
 
2.8%
1050 1
 
1.4%
1296 1
 
1.4%
75 1
 
1.4%
Other values (51) 51
70.8%
ValueCountFrequency (%)
43 2
 
2.8%
44 1
 
1.4%
60 1
 
1.4%
66 5
6.9%
75 1
 
1.4%
80 1
 
1.4%
82 1
 
1.4%
83 1
 
1.4%
86 2
 
2.8%
87 1
 
1.4%
ValueCountFrequency (%)
9882 1
1.4%
8774 1
1.4%
4758 1
1.4%
4380 1
1.4%
2857 1
1.4%
2806 1
1.4%
2731 1
1.4%
2500 1
1.4%
1625 1
1.4%
1299 1
1.4%

수용인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean336.44444
Minimum17
Maximum3801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2024-04-21T01:17:16.503916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile24.55
Q136
median63.5
Q3342.25
95-th percentile1362.7
Maximum3801
Range3784
Interquartile range (IQR)306.25

Descriptive statistics

Standard deviation662.6413
Coefficient of variation (CV)1.9695415
Kurtosis15.866907
Mean336.44444
Median Absolute Deviation (MAD)43
Skewness3.7766914
Sum24224
Variance439093.49
MonotonicityNot monotonic
2024-04-21T01:17:16.934575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41 3
 
4.2%
34 3
 
4.2%
17 3
 
4.2%
25 3
 
4.2%
48 2
 
2.8%
36 2
 
2.8%
52 2
 
2.8%
37 2
 
2.8%
271 2
 
2.8%
32 2
 
2.8%
Other values (45) 48
66.7%
ValueCountFrequency (%)
17 3
4.2%
24 1
 
1.4%
25 3
4.2%
26 2
2.8%
29 1
 
1.4%
31 1
 
1.4%
32 2
2.8%
34 3
4.2%
35 1
 
1.4%
36 2
2.8%
ValueCountFrequency (%)
3801 1
1.4%
3375 1
1.4%
1830 1
1.4%
1685 1
1.4%
1099 1
1.4%
1080 1
1.4%
1051 1
1.4%
962 1
1.4%
625 1
1.4%
500 1
1.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size704.0 B
Minimum2023-05-19 00:00:00
Maximum2023-05-19 00:00:00
2024-04-21T01:17:17.197534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:17.354989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T01:17:05.143656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:00.285660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:01.524993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:02.725663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:03.926276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:05.401943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:00.537372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:01.774581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:02.973717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:04.179553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:05.646861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:00.778583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:02.002969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:03.208701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:04.414626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:05.888990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:01.018382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:02.238365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:03.438669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:04.653396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:06.137494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:01.266406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:02.473928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:03.676929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:17:04.889283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T01:17:17.564721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명구분도로명주소위도경도면적(제곱미터)수용인원(명)
연번1.0001.0000.5511.0000.8450.7840.1600.160
시설명1.0001.0001.0001.0001.0001.0001.0001.000
구분0.5511.0001.0001.0000.4240.4980.3380.338
도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
위도0.8451.0000.4241.0001.0000.5470.0000.000
경도0.7841.0000.4981.0000.5471.0000.0000.000
면적(제곱미터)0.1601.0000.3381.0000.0000.0001.0001.000
수용인원(명)0.1601.0000.3381.0000.0000.0001.0001.000
2024-04-21T01:17:17.859179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도면적(제곱미터)수용인원(명)구분
연번1.000-0.709-0.008-0.142-0.1410.344
위도-0.7091.000-0.1760.1430.1420.251
경도-0.008-0.1761.0000.1110.1140.327
면적(제곱미터)-0.1420.1430.1111.0001.0000.218
수용인원(명)-0.1410.1420.1141.0001.0000.218
구분0.3440.2510.3270.2180.2181.000

Missing values

2024-04-21T01:17:06.491848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T01:17:06.931820image/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

연번시설명구분도로명주소위도경도면적(제곱미터)수용인원(명)데이터기준일자
01금곡마을회관마을회관경상남도 사천시 사천읍 거무실안길 335.090663128.155468166642023-05-19
12장전1리마을회관마을회관경상남도 사천시 사천읍 구암두문로 58535.098188128.14256199392023-05-19
23사천중학교 강당학교경상남도 사천시 사천읍 동문로 2035.080897128.09808511024242023-05-19
34사천초등학교 강당학교경상남도 사천시 사천읍 읍내로 5935.083669128.09271510754142023-05-19
45수양초등학교 강당학교경상남도 사천시 사천읍 옥산로 6035.078993128.0893657092732023-05-19
56고읍마을회관마을회관경상남도 사천시 정동면 고읍길 22335.067574128.097806132512023-05-19
67복상마을회관마을회관경상남도 사천시 정동면 감곡길 5935.051896128.14379566262023-05-19
78경남자영고등학교 본관학교경상남도 사천시 정동면 옥산로 14335.078444128.100418475818302023-05-19
89동성초등학교 강당학교경상남도 사천시 정동면 동계길 4535.076236128.08731125009622023-05-19
910사천여자중학교 본관동학교경상남도 사천시 정동면 서당길 3235.081237128.102132988238012023-05-19
연번시설명구분도로명주소위도경도면적(제곱미터)수용인원(명)데이터기준일자
6263상궁지경로당경로당경상남도 사천시 상궁지길 71(궁지동)34.939715128.121834105412023-05-19
6364중향마을회관마을회관경상남도 사천시 중향2길 12(향촌동)34.934473128.09669382322023-05-19
6465홀곡경로당경로당경상남도 사천시 홀곡1길 31(이홀동)34.964026128.13237292362023-05-19
6566신향마을회관마을회관경상남도 사천시 신향1길 27(향촌동)34.924687128.091996135522023-05-19
6667용산초등학교학교경상남도 사천시 삼상로 223-31 (봉남동)34.943423128.0987297032712023-05-19
6768배천마을회관마을회관경상남도 사천시 배천길 7-10 (백천동)34.993457128.06966286342023-05-19
6869심포마을회관마을회관경상남도 사천시 노대길 338(대포동)34.990304128.047269116452023-05-19
6970중촌마을회관마을회관경상남도 사천시 해안관광로 488-4 (송포동)34.967837128.054341106412023-05-19
7071남양중학교 강당학교경상남도 사천시 진삼로 147(송포동)34.969537128.0621729713742023-05-19
7172남양초등학교 강당학교경상남도 사천시 문화안길 23(죽림동)34.977504128.06470816256252023-05-19