Overview

Dataset statistics

Number of variables13
Number of observations108
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.5 KiB
Average record size in memory109.2 B

Variable types

Numeric4
Categorical4
Text4
DateTime1

Dataset

Description경상남도 장례시설 현황입니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3068678

Alerts

종류 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
연번 is highly overall correlated with 구분High correlation
건물연면적(㎡) is highly overall correlated with 빈소수(개소) and 1 other fieldsHigh correlation
빈소수(개소) is highly overall correlated with 건물연면적(㎡) and 1 other fieldsHigh correlation
안치능력(구) is highly overall correlated with 빈소수(개소) and 1 other fieldsHigh correlation
운영형태 is highly overall correlated with 안치능력(구) and 2 other fieldsHigh correlation
냉장시설안치료(천원) is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly imbalanced (77.1%)Imbalance
연번 has unique valuesUnique
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:39:51.243283
Analysis finished2023-12-10 23:39:53.725636
Duration2.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.5
Minimum1
Maximum108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T08:39:53.803542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.35
Q127.75
median54.5
Q381.25
95-th percentile102.65
Maximum108
Range107
Interquartile range (IQR)53.5

Descriptive statistics

Standard deviation31.32092
Coefficient of variation (CV)0.57469577
Kurtosis-1.2
Mean54.5
Median Absolute Deviation (MAD)27
Skewness0
Sum5886
Variance981
MonotonicityStrictly increasing
2023-12-11T08:39:53.924214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (98) 98
90.7%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size996.0 B
사설
104 
공설
 
4

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공설
2nd row공설
3rd row공설
4th row공설
5th row사설

Common Values

ValueCountFrequency (%)
사설 104
96.3%
공설 4
 
3.7%

Length

2023-12-11T08:39:54.075146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:39:54.165972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사설 104
96.3%
공설 4
 
3.7%

시설명
Text

Distinct107
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-11T08:39:54.349223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.5185185
Min length3

Characters and Unicode

Total characters920
Distinct characters146
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)98.1%

Sample

1st row창원시립상복공원봉안시설
2nd row창녕공설장례식장
3rd row남해추모누리 장례식장
4th row창선공익장례식장
5th row파티마병원 장례식장
ValueCountFrequency (%)
장례식장 8
 
6.8%
영락원장례식장 2
 
1.7%
창원시립상복공원봉안시설 1
 
0.9%
자굴산장례식장 1
 
0.9%
사랑병원장례식장 1
 
0.9%
부성장례식장 1
 
0.9%
의령전문장례식장 1
 
0.9%
웅상병원장례식장 1
 
0.9%
신세계병원장례식장 1
 
0.9%
해인병원장례식장 1
 
0.9%
Other values (99) 99
84.6%
2023-12-11T08:39:54.705207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 196
21.3%
례 98
 
10.7%
식 97
 
10.5%
원 78
 
8.5%
병 65
 
7.1%
해 14
 
1.5%
양 13
 
1.4%
전 12
 
1.3%
성 12
 
1.3%
문 12
 
1.3%
Other values (136) 323
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 896
97.4%
Space Separator 9
 
1.0%
Open Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%
Other Symbol 3
 
0.3%
Decimal Number 2
 
0.2%
Uppercase Letter 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 196
21.9%
례 98
 
10.9%
식 97
 
10.8%
원 78
 
8.7%
병 65
 
7.3%
해 14
 
1.6%
양 13
 
1.5%
전 12
 
1.3%
성 12
 
1.3%
문 12
 
1.3%
Other values (128) 299
33.4%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 899
97.7%
Common 19
 
2.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 196
21.8%
례 98
 
10.9%
식 97
 
10.8%
원 78
 
8.7%
병 65
 
7.2%
해 14
 
1.6%
양 13
 
1.4%
전 12
 
1.3%
성 12
 
1.3%
문 12
 
1.3%
Other values (129) 302
33.6%
Common
ValueCountFrequency (%)
9
47.4%
( 4
21.1%
) 4
21.1%
1 1
 
5.3%
2 1
 
5.3%
Latin
ValueCountFrequency (%)
C 1
50.0%
e 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 896
97.4%
ASCII 21
 
2.3%
None 3
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 196
21.9%
례 98
 
10.9%
식 97
 
10.8%
원 78
 
8.7%
병 65
 
7.3%
해 14
 
1.6%
양 13
 
1.5%
전 12
 
1.3%
성 12
 
1.3%
문 12
 
1.3%
Other values (128) 299
33.4%
ASCII
ValueCountFrequency (%)
9
42.9%
( 4
19.0%
) 4
19.0%
C 1
 
4.8%
1 1
 
4.8%
2 1
 
4.8%
e 1
 
4.8%
None
ValueCountFrequency (%)
㈜ 3
100.0%

위치
Text

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-11T08:39:54.933340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length20.611111
Min length14

Characters and Unicode

Total characters2226
Distinct characters142
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

Unique108 ?
Unique (%)100.0%

Sample

1st row경상남도 창원시 성산구 공단로474번길 160 (상복동)
2nd row경상남도 창녕군 창녕읍 술정리205
3rd row경상남도 남해군 서면 연죽리 산8
4th row경상남도 남해군 창선면 동대리 748
5th row경상남도 창원시 의창구 창이대로 45(명서동)
ValueCountFrequency (%)
경상남도 108
 
22.6%
창원시 20
 
4.2%
김해시 14
 
2.9%
마산회원구 7
 
1.5%
밀양시 7
 
1.5%
창녕군 7
 
1.5%
진주시 7
 
1.5%
사천시 7
 
1.5%
하동군 6
 
1.3%
통영시 6
 
1.3%
Other values (240) 288
60.4%
2023-12-11T08:39:55.287717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
376
 
16.9%
남 130
 
5.8%
상 113
 
5.1%
도 111
 
5.0%
경 109
 
4.9%
시 73
 
3.3%
1 72
 
3.2%
로 68
 
3.1%
5 42
 
1.9%
2 41
 
1.8%
Other values (132) 1091
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1423
63.9%
Space Separator 376
 
16.9%
Decimal Number 364
 
16.4%
Dash Punctuation 30
 
1.3%
Open Punctuation 16
 
0.7%
Close Punctuation 16
 
0.7%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 130
 
9.1%
상 113
 
7.9%
도 111
 
7.8%
경 109
 
7.7%
시 73
 
5.1%
로 68
 
4.8%
동 40
 
2.8%
창 37
 
2.6%
군 35
 
2.5%
해 35
 
2.5%
Other values (117) 672
47.2%
Decimal Number
ValueCountFrequency (%)
1 72
19.8%
5 42
11.5%
2 41
11.3%
4 39
10.7%
3 38
10.4%
7 32
8.8%
6 32
8.8%
8 29
8.0%
9 22
 
6.0%
0 17
 
4.7%
Space Separator
ValueCountFrequency (%)
376
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1423
63.9%
Common 803
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 130
 
9.1%
상 113
 
7.9%
도 111
 
7.8%
경 109
 
7.7%
시 73
 
5.1%
로 68
 
4.8%
동 40
 
2.8%
창 37
 
2.6%
군 35
 
2.5%
해 35
 
2.5%
Other values (117) 672
47.2%
Common
ValueCountFrequency (%)
376
46.8%
1 72
 
9.0%
5 42
 
5.2%
2 41
 
5.1%
4 39
 
4.9%
3 38
 
4.7%
7 32
 
4.0%
6 32
 
4.0%
- 30
 
3.7%
8 29
 
3.6%
Other values (5) 72
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1423
63.9%
ASCII 803
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
376
46.8%
1 72
 
9.0%
5 42
 
5.2%
2 41
 
5.1%
4 39
 
4.9%
3 38
 
4.7%
7 32
 
4.0%
6 32
 
4.0%
- 30
 
3.7%
8 29
 
3.6%
Other values (5) 72
 
9.0%
Hangul
ValueCountFrequency (%)
남 130
 
9.1%
상 113
 
7.9%
도 111
 
7.8%
경 109
 
7.7%
시 73
 
5.1%
로 68
 
4.8%
동 40
 
2.8%
창 37
 
2.6%
군 35
 
2.5%
해 35
 
2.5%
Other values (117) 672
47.2%

설치년월
Date

Distinct89
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size996.0 B
Minimum1994-09-01 00:00:00
Maximum2014-11-01 00:00:00
2023-12-11T08:39:55.429595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:55.547436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size996.0 B
병원
60 
전문
39 
-
 
4
전문병원
 
3
종합병원
 
2

Length

Max length4
Median length2
Mean length2.0555556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row병원

Common Values

ValueCountFrequency (%)
병원 60
55.6%
전문 39
36.1%
- 4
 
3.7%
전문병원 3
 
2.8%
종합병원 2
 
1.9%

Length

2023-12-11T08:39:55.900335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:39:56.008067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
병원 60
55.6%
전문 39
36.1%
4
 
3.7%
전문병원 3
 
2.8%
종합병원 2
 
1.9%

운영형태
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size996.0 B
임대
54 
직영
52 
창원시설관리공단
 
1
위탁
 
1

Length

Max length8
Median length2
Mean length2.0555556
Min length2

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st row창원시설관리공단
2nd row위탁
3rd row임대
4th row임대
5th row직영

Common Values

ValueCountFrequency (%)
임대 54
50.0%
직영 52
48.1%
창원시설관리공단 1
 
0.9%
위탁 1
 
0.9%

Length

2023-12-11T08:39:56.114878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:39:56.248586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 54
50.0%
직영 52
48.1%
창원시설관리공단 1
 
0.9%
위탁 1
 
0.9%

전화번호
Text

Distinct106
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-11T08:39:56.469802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1296
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

Unique104 ?
Unique (%)96.3%

Sample

1st row055-712-0900
2nd row055-533-8510
3rd row055-862-0442
4th row055-867-4141
5th row055-270-1900
ValueCountFrequency (%)
055-863-1024 2
 
1.9%
055-682-2877 2
 
1.9%
055-532-5858 1
 
0.9%
055-389-1024 1
 
0.9%
055-712-0900 1
 
0.9%
055-572-3900 1
 
0.9%
055-573-4500 1
 
0.9%
055-573-0451 1
 
0.9%
055-386-4284 1
 
0.9%
055-367-4411 1
 
0.9%
Other values (96) 96
88.9%
2023-12-11T08:39:56.836451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 295
22.8%
- 216
16.7%
0 209
16.1%
4 151
11.7%
3 92
 
7.1%
2 77
 
5.9%
1 63
 
4.9%
8 55
 
4.2%
6 48
 
3.7%
7 45
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1080
83.3%
Dash Punctuation 216
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 295
27.3%
0 209
19.4%
4 151
14.0%
3 92
 
8.5%
2 77
 
7.1%
1 63
 
5.8%
8 55
 
5.1%
6 48
 
4.4%
7 45
 
4.2%
9 45
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 216
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1296
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 295
22.8%
- 216
16.7%
0 209
16.1%
4 151
11.7%
3 92
 
7.1%
2 77
 
5.9%
1 63
 
4.9%
8 55
 
4.2%
6 48
 
3.7%
7 45
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 295
22.8%
- 216
16.7%
0 209
16.1%
4 151
11.7%
3 92
 
7.1%
2 77
 
5.9%
1 63
 
4.9%
8 55
 
4.2%
6 48
 
3.7%
7 45
 
3.5%

건물연면적(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct103
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1241.1176
Minimum38
Maximum10600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T08:39:57.000957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38
5-th percentile158.1
Q1519
median893
Q31359.425
95-th percentile3886.26
Maximum10600
Range10562
Interquartile range (IQR)840.425

Descriptive statistics

Standard deviation1426.0049
Coefficient of variation (CV)1.1489684
Kurtosis18.797961
Mean1241.1176
Median Absolute Deviation (MAD)425
Skewness3.7549221
Sum134040.7
Variance2033490
MonotonicityNot monotonic
2023-12-11T08:39:57.176941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
621.0 2
 
1.9%
330.0 2
 
1.9%
429.0 2
 
1.9%
574.0 2
 
1.9%
519.0 2
 
1.9%
4200.0 1
 
0.9%
201.0 1
 
0.9%
10600.0 1
 
0.9%
614.0 1
 
0.9%
1700.0 1
 
0.9%
Other values (93) 93
86.1%
ValueCountFrequency (%)
38.0 1
0.9%
67.0 1
0.9%
114.0 1
0.9%
130.0 1
0.9%
140.0 1
0.9%
142.0 1
0.9%
188.0 1
0.9%
198.0 1
0.9%
201.0 1
0.9%
227.0 1
0.9%
ValueCountFrequency (%)
10600.0 1
0.9%
6340.2 1
0.9%
5313.0 1
0.9%
5000.0 1
0.9%
4929.0 1
0.9%
4200.0 1
0.9%
3303.6 1
0.9%
3300.0 1
0.9%
2494.0 1
0.9%
2399.0 1
0.9%

빈소수(개소)
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0740741
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T08:39:57.301968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q35
95-th percentile7.65
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8780767
Coefficient of variation (CV)0.46098246
Kurtosis1.535136
Mean4.0740741
Median Absolute Deviation (MAD)1
Skewness1.210463
Sum440
Variance3.527172
MonotonicityNot monotonic
2023-12-11T08:39:57.401963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3 41
38.0%
4 19
17.6%
5 12
 
11.1%
6 11
 
10.2%
2 11
 
10.2%
7 5
 
4.6%
10 3
 
2.8%
1 3
 
2.8%
8 2
 
1.9%
9 1
 
0.9%
ValueCountFrequency (%)
1 3
 
2.8%
2 11
 
10.2%
3 41
38.0%
4 19
17.6%
5 12
 
11.1%
6 11
 
10.2%
7 5
 
4.6%
8 2
 
1.9%
9 1
 
0.9%
10 3
 
2.8%
ValueCountFrequency (%)
10 3
 
2.8%
9 1
 
0.9%
8 2
 
1.9%
7 5
 
4.6%
6 11
 
10.2%
5 12
 
11.1%
4 19
17.6%
3 41
38.0%
2 11
 
10.2%
1 3
 
2.8%

안치능력(구)
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4074074
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T08:39:57.515184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.35
Q14
median6
Q38
95-th percentile12
Maximum20
Range19
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.1505438
Coefficient of variation (CV)0.49170336
Kurtosis4.4897326
Mean6.4074074
Median Absolute Deviation (MAD)2
Skewness1.7808607
Sum692
Variance9.9259259
MonotonicityNot monotonic
2023-12-11T08:39:57.651708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
6 35
32.4%
4 33
30.6%
8 22
20.4%
12 4
 
3.7%
2 3
 
2.8%
14 2
 
1.9%
10 2
 
1.9%
3 2
 
1.9%
16 1
 
0.9%
20 1
 
0.9%
Other values (3) 3
 
2.8%
ValueCountFrequency (%)
1 1
 
0.9%
2 3
 
2.8%
3 2
 
1.9%
4 33
30.6%
6 35
32.4%
8 22
20.4%
10 2
 
1.9%
11 1
 
0.9%
12 4
 
3.7%
14 2
 
1.9%
ValueCountFrequency (%)
20 1
 
0.9%
18 1
 
0.9%
16 1
 
0.9%
14 2
 
1.9%
12 4
 
3.7%
11 1
 
0.9%
10 2
 
1.9%
8 22
20.4%
6 35
32.4%
4 33
30.6%

빈소임대료(천원)
Text

Distinct56
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-11T08:39:57.867554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length3
Mean length4.6851852
Min length2

Characters and Unicode

Total characters506
Distinct characters34
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)38.0%

Sample

1st row1.8/㎡(2.5)
2nd row50(100)
3rd row240
4th row180
5th row400
ValueCountFrequency (%)
250 11
 
8.7%
600 7
 
5.5%
500 7
 
5.5%
100 6
 
4.7%
6
 
4.7%
240 5
 
3.9%
400 5
 
3.9%
200 5
 
3.9%
360 5
 
3.9%
300 4
 
3.1%
Other values (54) 66
52.0%
2023-12-11T08:39:58.258392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 171
33.8%
2 46
 
9.1%
5 46
 
9.1%
3 38
 
7.5%
4 32
 
6.3%
6 27
 
5.3%
20
 
4.0%
1 18
 
3.6%
8 18
 
3.6%
, 9
 
1.8%
Other values (24) 81
16.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 409
80.8%
Other Letter 29
 
5.7%
Other Punctuation 24
 
4.7%
Space Separator 20
 
4.0%
Dash Punctuation 8
 
1.6%
Close Punctuation 5
 
1.0%
Open Punctuation 5
 
1.0%
Uppercase Letter 3
 
0.6%
Math Symbol 2
 
0.4%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 8
27.6%
호 5
17.2%
평 5
17.2%
무 2
 
6.9%
료 2
 
6.9%
특 2
 
6.9%
차 1
 
3.4%
구 1
 
3.4%
영 1
 
3.4%
만 1
 
3.4%
Decimal Number
ValueCountFrequency (%)
0 171
41.8%
2 46
 
11.2%
5 46
 
11.2%
3 38
 
9.3%
4 32
 
7.8%
6 27
 
6.6%
1 18
 
4.4%
8 18
 
4.4%
9 8
 
2.0%
7 5
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 9
37.5%
: 7
29.2%
/ 6
25.0%
. 2
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
V 1
33.3%
I 1
33.3%
P 1
33.3%
Space Separator
ValueCountFrequency (%)
20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 474
93.7%
Hangul 29
 
5.7%
Latin 3
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 171
36.1%
2 46
 
9.7%
5 46
 
9.7%
3 38
 
8.0%
4 32
 
6.8%
6 27
 
5.7%
20
 
4.2%
1 18
 
3.8%
8 18
 
3.8%
, 9
 
1.9%
Other values (10) 49
 
10.3%
Hangul
ValueCountFrequency (%)
실 8
27.6%
호 5
17.2%
평 5
17.2%
무 2
 
6.9%
료 2
 
6.9%
특 2
 
6.9%
차 1
 
3.4%
구 1
 
3.4%
영 1
 
3.4%
만 1
 
3.4%
Latin
ValueCountFrequency (%)
V 1
33.3%
I 1
33.3%
P 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 476
94.1%
Hangul 29
 
5.7%
CJK Compat 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 171
35.9%
2 46
 
9.7%
5 46
 
9.7%
3 38
 
8.0%
4 32
 
6.7%
6 27
 
5.7%
20
 
4.2%
1 18
 
3.8%
8 18
 
3.8%
, 9
 
1.9%
Other values (12) 51
 
10.7%
Hangul
ValueCountFrequency (%)
실 8
27.6%
호 5
17.2%
평 5
17.2%
무 2
 
6.9%
료 2
 
6.9%
특 2
 
6.9%
차 1
 
3.4%
구 1
 
3.4%
영 1
 
3.4%
만 1
 
3.4%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

냉장시설안치료(천원)
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size996.0 B
60
16 
50
15 
80
14 
100
13 
70
10 
Other values (23)
40 

Length

Max length8
Median length2
Mean length2.712963
Min length2

Unique

Unique12 ?
Unique (%)11.1%

Sample

1st row40/일(70)
2nd row50(100)
3rd row50
4th row60
5th row60

Common Values

ValueCountFrequency (%)
60 16
14.8%
50 15
13.9%
80 14
13.0%
100 13
12.0%
70 10
9.3%
4/시간당 5
 
4.6%
150 4
 
3.7%
250 3
 
2.8%
40 2
 
1.9%
48 2
 
1.9%
Other values (18) 24
22.2%

Length

2023-12-11T08:39:58.447213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
60 16
14.5%
80 15
13.6%
50 15
13.6%
100 13
11.8%
70 10
 
9.1%
4/시간당 5
 
4.5%
150 4
 
3.6%
250 3
 
2.7%
4545 2
 
1.8%
2
 
1.8%
Other values (18) 25
22.7%

Interactions

2023-12-11T08:39:53.091387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.101852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.427877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.777218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:53.163843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.178133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.511216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.867453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:53.265045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.256853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.594969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.945975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:53.347303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.329669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:52.694318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:53.014883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:39:58.532094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분설치년월종류운영형태건물연면적(㎡)빈소수(개소)안치능력(구)빈소임대료(천원)냉장시설안치료(천원)
연번1.0000.6780.7310.6950.2850.2610.4070.4010.7740.799
구분0.6781.0000.6591.0000.8880.4960.0830.6100.8880.729
설치년월0.7310.6591.0000.9510.0000.7390.8680.7840.9530.766
종류0.6951.0000.9511.0000.5610.3310.0000.4250.8730.491
운영형태0.2850.8880.0000.5611.0000.5910.4530.7440.9800.980
건물연면적(㎡)0.2610.4960.7390.3310.5911.0000.6050.6640.8170.000
빈소수(개소)0.4070.0830.8680.0000.4530.6051.0000.9010.8790.541
안치능력(구)0.4010.6100.7840.4250.7440.6640.9011.0000.9170.514
빈소임대료(천원)0.7740.8880.9530.8730.9800.8170.8790.9171.0000.966
냉장시설안치료(천원)0.7990.7290.7660.4910.9800.0000.5410.5140.9661.000
2023-12-11T08:39:58.654073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
냉장시설안치료(천원)종류운영형태구분
냉장시설안치료(천원)1.0000.2250.7310.514
종류0.2251.0000.4860.986
운영형태0.7310.4861.0000.690
구분0.5140.9860.6901.000
2023-12-11T08:39:58.751879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번건물연면적(㎡)빈소수(개소)안치능력(구)구분종류운영형태냉장시설안치료(천원)
연번1.000-0.151-0.327-0.4350.5070.3500.1670.393
건물연면적(㎡)-0.1511.0000.5560.4720.5190.2160.4440.000
빈소수(개소)-0.3270.5561.0000.7600.0550.0000.2770.198
안치능력(구)-0.4350.4720.7601.0000.4540.1830.5350.184
구분0.5070.5190.0550.4541.0000.9860.6900.514
종류0.3500.2160.0000.1830.9861.0000.4860.225
운영형태0.1670.4440.2770.5350.6900.4861.0000.731
냉장시설안치료(천원)0.3930.0000.1980.1840.5140.2250.7311.000

Missing values

2023-12-11T08:39:53.471650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:39:53.632862image/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

연번구분시설명위치설치년월종류운영형태전화번호건물연면적(㎡)빈소수(개소)안치능력(구)빈소임대료(천원)냉장시설안치료(천원)
01공설창원시립상복공원봉안시설경상남도 창원시 성산구 공단로474번길 160 (상복동)2012-02-01-창원시설관리공단055-712-09004929.010161.8/㎡(2.5)40/일(70)
12공설창녕공설장례식장경상남도 창녕군 창녕읍 술정리2052009-05-29-위탁055-533-85105000.04650(100)50(100)
23공설남해추모누리 장례식장경상남도 남해군 서면 연죽리 산82007-05-01-임대055-862-0442895.03624050
34공설창선공익장례식장경상남도 남해군 창선면 동대리 7482012-11-01-임대055-867-4141995.03618060
45사설파티마병원 장례식장경상남도 창원시 의창구 창이대로 45(명서동)2002-01-01병원직영055-270-19002024.071240060
56사설행복한병원 장례식장경상남도 창원시 의창구 북면 천주로 852008-07-01병원임대055-255-0220782.04624060
67사설창원병원장례식장경상남도 창원시 성산구 창원대로 7212012-09-01병원임대055-287-1100984.06843048
78사설마산의료원장례식장경상남도 창원시 마산합포구 중앙동3가 31994-09-01병원직영055-294-14001540.0101419248
89사설시민장례식장경상남도 창원시 마산합포구 해운동 65-112001-04-01전문직영055-245-44441076.06840050
910사설태봉병원장례식장경상남도 창원시 마산합포구 진동면 동전리 1434-52001-10-01전문임대055-271-7990648.03225050
연번구분시설명위치설치년월종류운영형태전화번호건물연면적(㎡)빈소수(개소)안치능력(구)빈소임대료(천원)냉장시설안치료(천원)
9899사설하동병원장례식장경상남도 하동군 하동읍 화심길 51-71999-11-01전문직영055-884-70441340.0561801805050
99100사설하동장례식장경상남도 하동군 적량면공설운동장로 95-72004-04-01전문직영055-883-44841029.0343003005050
100101사설하동전문장례식장경상남도 하동군 금남면섬진강대로 9572000-04-01전문직영055-884-1024384.0342002004545
101102사설산청장례식장경상남도 산청군 신안면지리산대로36572007-12-21전문직영055-974-12341376.044525( - )80( - )
102103사설함양장례식장경상남도 함양군 함양읍 고운로 2842007-12-17전문직영055-964-20001296.046400~600(400~600)6060
103104사설함양성심병원장례식장경상남도 함양군 함양읍 용평1길 52008-01-01병원임대055-962-9999252.0243503506060
104105사설새천년 장례식장경상남도 합천군합천읍 합천리 13592007-02-07전문직영055-934-4444936.04636090
105106사설합천전문장례식장경상남도 합천군 대양면정양리 972007-08-13전문직영055-932-70001225.03436090
106107사설새하늘장례식장경상남도 합천군 적중면 상부리 422-32008-01-08전문직영055-931-1093355.03424050
107108사설고려병원경상남도 합천군 대양면 정양리 587-31998-04-08병원직영055-931-4464997.04436080