Overview

Dataset statistics

Number of variables10
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory88.3 B

Variable types

Numeric5
Text2
Categorical3

Dataset

Description전라남도 함평군 이재민수용시설 지정현황에 대한 데이터로 시설명, 상세시설명, 상세주소, 위도, 경도, 수용가능면적, 수용가능인원, 대표전화, 내진설계여부에 대한 데이터를 제공합니다.
Author전라남도 함평군
URLhttps://www.data.go.kr/data/15037397/fileData.do

Alerts

대표전화 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
상세시설명 is highly overall correlated with 대표전화 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 대표전화High correlation
수용가능면적(제곱미터) is highly overall correlated with 수용가능인원(명) and 2 other fieldsHigh correlation
수용가능인원(명) is highly overall correlated with 수용가능면적(제곱미터) and 1 other fieldsHigh correlation
내진설계 is highly overall correlated with 수용가능면적(제곱미터) and 2 other fieldsHigh correlation
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:38:01.454898
Analysis finished2023-12-12 14:38:05.189013
Duration3.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T23:38:05.276072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2023-12-12T23:38:05.446162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

시설명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T23:38:05.734973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length6.725
Min length4

Characters and Unicode

Total characters269
Distinct characters86
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

Unique40 ?
Unique (%)100.0%

Sample

1st row함평엑스포공원 금호관
2nd row함평군민회관
3rd row함평교회
4th row함평중학교
5th row함평학다리고등학교
ValueCountFrequency (%)
함평엑스포공원 1
 
2.4%
월야초등학교 1
 
2.4%
해보초등학교 1
 
2.4%
금적마을회관 1
 
2.4%
아차마을회관 1
 
2.4%
대동향교초등학교 1
 
2.4%
나산면복지회관 1
 
2.4%
월현경로당 1
 
2.4%
해보시장경로당 1
 
2.4%
함평해보중학교 1
 
2.4%
Other values (32) 32
76.2%
2023-12-12T23:38:06.136176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 22
 
8.2%
학 18
 
6.7%
평 13
 
4.8%
함 13
 
4.8%
회 12
 
4.5%
등 11
 
4.1%
관 8
 
3.0%
초 8
 
3.0%
다 7
 
2.6%
면 6
 
2.2%
Other values (76) 151
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 267
99.3%
Space Separator 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 22
 
8.2%
학 18
 
6.7%
평 13
 
4.9%
함 13
 
4.9%
회 12
 
4.5%
등 11
 
4.1%
관 8
 
3.0%
초 8
 
3.0%
다 7
 
2.6%
면 6
 
2.2%
Other values (75) 149
55.8%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 267
99.3%
Common 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 22
 
8.2%
학 18
 
6.7%
평 13
 
4.9%
함 13
 
4.9%
회 12
 
4.5%
등 11
 
4.1%
관 8
 
3.0%
초 8
 
3.0%
다 7
 
2.6%
면 6
 
2.2%
Other values (75) 149
55.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 267
99.3%
ASCII 2
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 22
 
8.2%
학 18
 
6.7%
평 13
 
4.9%
함 13
 
4.9%
회 12
 
4.5%
등 11
 
4.1%
관 8
 
3.0%
초 8
 
3.0%
다 7
 
2.6%
면 6
 
2.2%
Other values (75) 149
55.8%
ASCII
ValueCountFrequency (%)
2
100.0%

상세시설명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
강당
14 
본관
13 
객실
8 
회관
4 
다목적실
 
1

Length

Max length4
Median length2
Mean length2.05
Min length2

Unique

Unique1 ?
Unique (%)2.5%

Sample

1st row다목적실
2nd row본관
3rd row본관
4th row강당
5th row강당

Common Values

ValueCountFrequency (%)
강당 14
35.0%
본관 13
32.5%
객실 8
20.0%
회관 4
 
10.0%
다목적실 1
 
2.5%

Length

2023-12-12T23:38:06.322280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:38:06.461588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강당 14
35.0%
본관 13
32.5%
객실 8
20.0%
회관 4
 
10.0%
다목적실 1
 
2.5%

상세주소
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T23:38:06.727779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22.5
Mean length20.65
Min length19

Characters and Unicode

Total characters826
Distinct characters72
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

Unique38 ?
Unique (%)95.0%

Sample

1st row전라남도 함평군 함평읍 곤재로 27
2nd row전라남도 함평군 함평읍 남일길 52
3rd row전라남도 함평군 함평읍 중앙길 108
4th row전라남도 함평군 함평읍 영수길 275
5th row전라남도 함평군 함평읍 영수길 55
ValueCountFrequency (%)
전라남도 40
20.0%
함평군 40
20.0%
대동면 10
 
5.0%
함평읍 8
 
4.0%
해보면 5
 
2.5%
손불면 5
 
2.5%
학교면 4
 
2.0%
엄다면 3
 
1.5%
엄다길 3
 
1.5%
손불중앙길 3
 
1.5%
Other values (69) 79
39.5%
2023-12-12T23:38:07.155778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
160
19.4%
함 52
 
6.3%
평 49
 
5.9%
남 41
 
5.0%
전 40
 
4.8%
군 40
 
4.8%
라 40
 
4.8%
도 40
 
4.8%
면 32
 
3.9%
길 28
 
3.4%
Other values (62) 304
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 537
65.0%
Space Separator 160
 
19.4%
Decimal Number 118
 
14.3%
Dash Punctuation 11
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
함 52
 
9.7%
평 49
 
9.1%
남 41
 
7.6%
전 40
 
7.4%
군 40
 
7.4%
라 40
 
7.4%
도 40
 
7.4%
면 32
 
6.0%
길 28
 
5.2%
동 17
 
3.2%
Other values (50) 158
29.4%
Decimal Number
ValueCountFrequency (%)
1 23
19.5%
5 17
14.4%
2 15
12.7%
3 13
11.0%
7 11
9.3%
4 9
 
7.6%
8 8
 
6.8%
0 8
 
6.8%
6 8
 
6.8%
9 6
 
5.1%
Space Separator
ValueCountFrequency (%)
160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 537
65.0%
Common 289
35.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
함 52
 
9.7%
평 49
 
9.1%
남 41
 
7.6%
전 40
 
7.4%
군 40
 
7.4%
라 40
 
7.4%
도 40
 
7.4%
면 32
 
6.0%
길 28
 
5.2%
동 17
 
3.2%
Other values (50) 158
29.4%
Common
ValueCountFrequency (%)
160
55.4%
1 23
 
8.0%
5 17
 
5.9%
2 15
 
5.2%
3 13
 
4.5%
7 11
 
3.8%
- 11
 
3.8%
4 9
 
3.1%
8 8
 
2.8%
0 8
 
2.8%
Other values (2) 14
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 537
65.0%
ASCII 289
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
160
55.4%
1 23
 
8.0%
5 17
 
5.9%
2 15
 
5.2%
3 13
 
4.5%
7 11
 
3.8%
- 11
 
3.8%
4 9
 
3.1%
8 8
 
2.8%
0 8
 
2.8%
Other values (2) 14
 
4.8%
Hangul
ValueCountFrequency (%)
함 52
 
9.7%
평 49
 
9.1%
남 41
 
7.6%
전 40
 
7.4%
군 40
 
7.4%
라 40
 
7.4%
도 40
 
7.4%
면 32
 
6.0%
길 28
 
5.2%
동 17
 
3.2%
Other values (50) 158
29.4%

위도
Real number (ℝ)

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.096782
Minimum35.003047
Maximum35.18856
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T23:38:07.336759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.003047
5-th percentile35.010156
Q135.063443
median35.085753
Q335.147875
95-th percentile35.181314
Maximum35.18856
Range0.185513
Interquartile range (IQR)0.084432

Descriptive statistics

Standard deviation0.057529466
Coefficient of variation (CV)0.0016391664
Kurtosis-1.1679229
Mean35.096782
Median Absolute Deviation (MAD)0.05648
Skewness0.081504255
Sum1403.8713
Variance0.0033096394
MonotonicityNot monotonic
2023-12-12T23:38:07.480947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
35.010156 2
 
5.0%
35.056151 1
 
2.5%
35.065644 1
 
2.5%
35.067779 1
 
2.5%
35.112644 1
 
2.5%
35.172981 1
 
2.5%
35.181086 1
 
2.5%
35.175307 1
 
2.5%
35.177559 1
 
2.5%
35.177006 1
 
2.5%
Other values (29) 29
72.5%
ValueCountFrequency (%)
35.003047 1
2.5%
35.010156 2
5.0%
35.011248 1
2.5%
35.01329 1
2.5%
35.019885 1
2.5%
35.026145 1
2.5%
35.056151 1
2.5%
35.060557 1
2.5%
35.063063 1
2.5%
35.06357 1
2.5%
ValueCountFrequency (%)
35.18856 1
2.5%
35.185643 1
2.5%
35.181086 1
2.5%
35.177559 1
2.5%
35.177006 1
2.5%
35.175307 1
2.5%
35.172981 1
2.5%
35.157205 1
2.5%
35.156652 1
2.5%
35.155163 1
2.5%

경도
Real number (ℝ)

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.52778
Minimum126.39628
Maximum126.63269
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T23:38:07.621843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.39628
5-th percentile126.42679
Q1126.51273
median126.52328
Q3126.56441
95-th percentile126.6096
Maximum126.63269
Range0.236408
Interquartile range (IQR)0.05168225

Descriptive statistics

Standard deviation0.057297262
Coefficient of variation (CV)0.00045284333
Kurtosis0.071669464
Mean126.52778
Median Absolute Deviation (MAD)0.020983
Skewness-0.34400115
Sum5061.1113
Variance0.0032829762
MonotonicityNot monotonic
2023-12-12T23:38:07.749700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
126.515875 2
 
5.0%
126.519947 1
 
2.5%
126.589088 1
 
2.5%
126.53232 1
 
2.5%
126.608822 1
 
2.5%
126.580426 1
 
2.5%
126.602551 1
 
2.5%
126.603756 1
 
2.5%
126.603366 1
 
2.5%
126.632686 1
 
2.5%
Other values (29) 29
72.5%
ValueCountFrequency (%)
126.396278 1
2.5%
126.407003 1
2.5%
126.427827 1
2.5%
126.431935 1
2.5%
126.433467 1
2.5%
126.462791 1
2.5%
126.4914 1
2.5%
126.499173 1
2.5%
126.500701 1
2.5%
126.50924 1
2.5%
ValueCountFrequency (%)
126.632686 1
2.5%
126.624303 1
2.5%
126.608822 1
2.5%
126.603756 1
2.5%
126.603366 1
2.5%
126.602551 1
2.5%
126.590654 1
2.5%
126.589088 1
2.5%
126.587073 1
2.5%
126.580426 1
2.5%

수용가능면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean507.736
Minimum58
Maximum2427.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T23:38:07.899865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58
5-th percentile65.85
Q1183
median484.745
Q3691.5
95-th percentile886.4
Maximum2427.15
Range2369.15
Interquartile range (IQR)508.5

Descriptive statistics

Standard deviation436.24114
Coefficient of variation (CV)0.85918891
Kurtosis8.7861568
Mean507.736
Median Absolute Deviation (MAD)232.245
Skewness2.3018821
Sum20309.44
Variance190306.33
MonotonicityNot monotonic
2023-12-12T23:38:08.056073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
108.0 2
 
5.0%
860.0 2
 
5.0%
691.0 2
 
5.0%
307.0 1
 
2.5%
744.0 1
 
2.5%
91.0 1
 
2.5%
257.0 1
 
2.5%
248.0 1
 
2.5%
66.0 1
 
2.5%
63.0 1
 
2.5%
Other values (27) 27
67.5%
ValueCountFrequency (%)
58.0 1
2.5%
63.0 1
2.5%
66.0 1
2.5%
74.0 1
2.5%
91.0 1
2.5%
97.0 1
2.5%
98.0 1
2.5%
108.0 2
5.0%
165.0 1
2.5%
189.0 1
2.5%
ValueCountFrequency (%)
2427.15 1
2.5%
1388.0 1
2.5%
860.0 2
5.0%
803.0 1
2.5%
744.0 1
2.5%
707.92 1
2.5%
706.0 1
2.5%
694.0 1
2.5%
693.0 1
2.5%
691.0 2
5.0%

수용가능인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120.025
Minimum17
Maximum420
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T23:38:08.203459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile19.95
Q132
median80.5
Q3201
95-th percentile244.85
Maximum420
Range403
Interquartile range (IQR)169

Descriptive statistics

Standard deviation94.270611
Coefficient of variation (CV)0.78542479
Kurtosis0.78430229
Mean120.025
Median Absolute Deviation (MAD)59.5
Skewness0.93908438
Sum4801
Variance8886.9481
MonotonicityNot monotonic
2023-12-12T23:38:08.697386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
32 2
 
5.0%
29 2
 
5.0%
72 2
 
5.0%
20 2
 
5.0%
60 2
 
5.0%
210 2
 
5.0%
209 2
 
5.0%
225 1
 
2.5%
77 1
 
2.5%
75 1
 
2.5%
Other values (23) 23
57.5%
ValueCountFrequency (%)
17 1
2.5%
19 1
2.5%
20 2
5.0%
22 1
2.5%
27 1
2.5%
28 1
2.5%
29 2
5.0%
32 2
5.0%
50 1
2.5%
57 1
2.5%
ValueCountFrequency (%)
420 1
2.5%
280 1
2.5%
243 1
2.5%
225 1
2.5%
213 1
2.5%
210 2
5.0%
209 2
5.0%
204 1
2.5%
200 1
2.5%
198 1
2.5%

대표전화
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
061-320-1742
32 
061-320-1472
8 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row061-320-1742
2nd row061-320-1742
3rd row061-320-1742
4th row061-320-1742
5th row061-320-1742

Common Values

ValueCountFrequency (%)
061-320-1742 32
80.0%
061-320-1472 8
 
20.0%

Length

2023-12-12T23:38:08.863339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:38:08.965078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
061-320-1742 32
80.0%
061-320-1472 8
 
20.0%

내진설계
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
미적용
28 
적용
12 

Length

Max length3
Median length3
Mean length2.7
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row적용
2nd row미적용
3rd row미적용
4th row적용
5th row적용

Common Values

ValueCountFrequency (%)
미적용 28
70.0%
적용 12
30.0%

Length

2023-12-12T23:38:09.068625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:38:09.198047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미적용 28
70.0%
적용 12
30.0%

Interactions

2023-12-12T23:38:04.358367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:01.944337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:02.673693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:03.276734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:03.839397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:04.461424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:02.069076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:02.793907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:03.400195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:03.962683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:04.569176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:02.185992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:02.923805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:03.494052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:04.069556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:04.673307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:02.317768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:03.034524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:03.608729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:04.163650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:04.781861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:02.460973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:03.150385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:03.722581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:38:04.252485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:38:09.278153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명상세시설명상세주소위도경도수용가능면적(제곱미터)수용가능인원(명)대표전화내진설계
연번1.0001.0000.8701.0000.6530.6530.6140.5791.0000.622
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상세시설명0.8701.0001.0000.7160.6930.0000.5980.5751.0000.478
상세주소1.0001.0000.7161.0001.0001.0001.0001.0001.0001.000
위도0.6531.0000.6931.0001.0000.8090.3640.1030.0000.246
경도0.6531.0000.0001.0000.8091.0000.5510.0000.4830.000
수용가능면적(제곱미터)0.6141.0000.5981.0000.3640.5511.0000.8950.7460.849
수용가능인원(명)0.5791.0000.5751.0000.1030.0000.8951.0000.5370.836
대표전화1.0001.0001.0001.0000.0000.4830.7460.5371.0000.000
내진설계0.6221.0000.4781.0000.2460.0000.8490.8360.0001.000
2023-12-12T23:38:09.432347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
내진설계대표전화상세시설명
내진설계1.0000.0000.556
대표전화0.0001.0000.960
상세시설명0.5560.9601.000
2023-12-12T23:38:09.603003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도수용가능면적(제곱미터)수용가능인원(명)상세시설명대표전화내진설계
연번1.0000.2110.4890.119-0.2540.4980.8890.423
위도0.2111.0000.1010.0860.0950.4590.0000.210
경도0.4890.1011.000-0.169-0.0930.0000.4320.000
수용가능면적(제곱미터)0.1190.086-0.1691.0000.8290.4490.5220.619
수용가능인원(명)-0.2540.095-0.0930.8291.0000.3770.3660.600
상세시설명0.4980.4590.0000.4490.3771.0000.9600.556
대표전화0.8890.0000.4320.5220.3660.9601.0000.000
내진설계0.4230.2100.0000.6190.6000.5560.0001.000

Missing values

2023-12-12T23:38:04.945892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:38:05.121238image/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

연번시설명상세시설명상세주소위도경도수용가능면적(제곱미터)수용가능인원(명)대표전화내진설계
01함평엑스포공원 금호관다목적실전라남도 함평군 함평읍 곤재로 2735.056151126.519947307.093061-320-1742적용
12함평군민회관본관전라남도 함평군 함평읍 남일길 5235.064947126.515032496.0150061-320-1742미적용
23함평교회본관전라남도 함평군 함평읍 중앙길 10835.108884126.491497.029061-320-1742미적용
34함평중학교강당전라남도 함평군 함평읍 영수길 27535.068104126.522272648.0196061-320-1742적용
45함평학다리고등학교강당전라남도 함평군 함평읍 영수길 5535.060557126.514506618.0187061-320-1742적용
56손불면사무소본관전라남도 함평군 손불면 손불중앙길 76-935.143135126.431935385.0116061-320-1742미적용
67손불서초등학교강당전라남도 함평군 손불면 양재길 1535.156652126.4070031388.0420061-320-1742미적용
78손불초등학교강당전라남도 함평군 손불면 손불중앙길 12135.145446126.433467706.0213061-320-1742적용
89함평손불중학교강당전라남도 함평군 손불면 손불중앙길 7-635.144054126.427827694.0210061-320-1742미적용
910신광초등학교강당전라남도 함평군 신광면 신광중앙길 11835.157205126.499173693.0210061-320-1742적용
연번시설명상세시설명상세주소위도경도수용가능면적(제곱미터)수용가능인원(명)대표전화내진설계
3031월야초등학교강당전라남도 함평군 월야면 금석길 9535.177006126.632686674.0204061-320-1742적용
3132전남보건고등학교강당전라남도 함평군 월야면 문화로 685-1835.18856126.624303691.0209061-320-1742적용
3233모아모텔객실전라남도 함평군 함평읍 함영로 101835.066902126.525579707.92112061-320-1472미적용
3334주포권역다목적복지센터객실전라남도 함평군 함평읍 석성리 312-1835.094846126.462791396.628061-320-1472미적용
3435호텔팰리스객실전라남도 함평군 함평읍 함평천우길 3235.063063126.5239392427.15280061-320-1472미적용
3536해당화권역다목적센터객실전라남도 함평군 손불면 안악길 42-6735.141331126.396278473.4920061-320-1472적용
3637함평엘리체컨트리클럽 골프텔객실전라남도 함평군 학교면 서당매길 24235.003047126.559073659.9184061-320-1472미적용
3738함평베이스타운객실전라남도 함평군 대동면 학동로 93435.102855126.50924860.060061-320-1472미적용
3839함평스포츠텔객실전라남도 함평군 대동면 함장로 137735.06357126.542667860.072061-320-1472미적용
3940힐탑모텔객실전라남도 함평군 해보면 밀재로 1147-535.185643126.590654453.3772061-320-1472미적용