Overview

Dataset statistics

Number of variables13
Number of observations304
Missing cells62
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.3 KiB
Average record size in memory105.4 B

Variable types

Text4
Categorical5
DateTime3
Numeric1

Dataset

Description경기도 포천시 경로당 현황에 관한 데이터로 경로당 명칭, 경로당 면적, 경로당 소재지, 경로당 연락처, 건축구조, 난방방식 등의 정보를 제공합니다
Author경기도 포천시
URLhttps://www.data.go.kr/data/15088021/fileData.do

Alerts

데이터기준일 has constant value ""Constant
소유자 is highly overall correlated with 난방방식High correlation
난방방식 is highly overall correlated with 소유자High correlation
경로당 층수 is highly imbalanced (57.6%)Imbalance
난방방식 is highly imbalanced (61.7%)Imbalance
부지면적(제곱미터) has 48 (15.8%) missing valuesMissing
경로당 연락처 has 12 (3.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 10:56:20.819170
Analysis finished2023-12-12 10:56:22.978749
Duration2.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

경로당명
Text

Distinct303
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T19:56:23.317594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.375
Min length2

Characters and Unicode

Total characters1634
Distinct characters199
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

Unique302 ?
Unique (%)99.3%

Sample

1st row한성골(고모1리)
2nd row고뫼(고모2리)
3rd row새터(고모3리)
4th row송정(무림1리)
5th row내누리(무림2리)
ValueCountFrequency (%)
일신아파트 2
 
0.7%
화대3리 2
 
0.7%
노곡4리 1
 
0.3%
연곡2리 1
 
0.3%
수입4리 1
 
0.3%
노곡2리 1
 
0.3%
도평1,4리 1
 
0.3%
도리(도평4리 1
 
0.3%
도평2리 1
 
0.3%
노곡5리 1
 
0.3%
Other values (295) 295
96.1%
2023-12-12T19:56:24.100014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 247
 
15.1%
2 83
 
5.1%
1 81
 
5.0%
( 80
 
4.9%
) 80
 
4.9%
3 50
 
3.1%
동 32
 
2.0%
통 30
 
1.8%
4 27
 
1.7%
산 27
 
1.7%
Other values (189) 897
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1191
72.9%
Decimal Number 273
 
16.7%
Open Punctuation 80
 
4.9%
Close Punctuation 80
 
4.9%
Space Separator 7
 
0.4%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 247
 
20.7%
동 32
 
2.7%
통 30
 
2.5%
산 27
 
2.3%
아 25
 
2.1%
파 24
 
2.0%
신 24
 
2.0%
트 22
 
1.8%
현 20
 
1.7%
정 17
 
1.4%
Other values (175) 723
60.7%
Decimal Number
ValueCountFrequency (%)
2 83
30.4%
1 81
29.7%
3 50
18.3%
4 27
 
9.9%
5 13
 
4.8%
6 8
 
2.9%
7 4
 
1.5%
8 4
 
1.5%
9 2
 
0.7%
0 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1191
72.9%
Common 443
 
27.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 247
 
20.7%
동 32
 
2.7%
통 30
 
2.5%
산 27
 
2.3%
아 25
 
2.1%
파 24
 
2.0%
신 24
 
2.0%
트 22
 
1.8%
현 20
 
1.7%
정 17
 
1.4%
Other values (175) 723
60.7%
Common
ValueCountFrequency (%)
2 83
18.7%
1 81
18.3%
( 80
18.1%
) 80
18.1%
3 50
11.3%
4 27
 
6.1%
5 13
 
2.9%
6 8
 
1.8%
7
 
1.6%
7 4
 
0.9%
Other values (4) 10
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1191
72.9%
ASCII 443
 
27.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 247
 
20.7%
동 32
 
2.7%
통 30
 
2.5%
산 27
 
2.3%
아 25
 
2.1%
파 24
 
2.0%
신 24
 
2.0%
트 22
 
1.8%
현 20
 
1.7%
정 17
 
1.4%
Other values (175) 723
60.7%
ASCII
ValueCountFrequency (%)
2 83
18.7%
1 81
18.3%
( 80
18.1%
) 80
18.1%
3 50
11.3%
4 27
 
6.1%
5 13
 
2.9%
6 8
 
1.8%
7
 
1.6%
7 4
 
0.9%
Other values (4) 10
 
2.3%

읍면동
Categorical

Distinct14
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
소흘읍
38 
신북면
32 
일동면
27 
군내면
25 
가산면
23 
Other values (9)
159 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소흘읍
2nd row소흘읍
3rd row소흘읍
4th row소흘읍
5th row소흘읍

Common Values

ValueCountFrequency (%)
소흘읍 38
12.5%
신북면 32
10.5%
일동면 27
8.9%
군내면 25
8.2%
가산면 23
7.6%
포천동 23
7.6%
내촌면 21
 
6.9%
영북면 21
 
6.9%
이동면 19
 
6.2%
영중면 18
 
5.9%
Other values (4) 57
18.8%

Length

2023-12-12T19:56:24.384771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소흘읍 38
12.5%
신북면 32
10.5%
일동면 27
8.9%
군내면 25
8.2%
가산면 23
7.6%
포천동 23
7.6%
내촌면 21
 
6.9%
영북면 21
 
6.9%
이동면 19
 
6.2%
영중면 18
 
5.9%
Other values (4) 57
18.8%

경로당 주소
Text

Distinct300
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T19:56:24.888353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length55
Mean length46.904605
Min length18

Characters and Unicode

Total characters14259
Distinct characters201
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)97.4%

Sample

1st row경기도 포천시 소흘읍 한성길 91
2nd row경기도 포천시 소흘읍 죽엽산로 296
3rd row경기도 포천시 소흘읍 죽엽산로 419-8
4th row경기도 포천시 소흘읍 무림길 37
5th row경기도 포천시 소흘읍 무림6길 2
ValueCountFrequency (%)
경기도 305
20.0%
포천시 303
19.9%
소흘읍 38
 
2.5%
신북면 32
 
2.1%
일동면 27
 
1.8%
군내면 25
 
1.6%
가산면 23
 
1.5%
내촌면 21
 
1.4%
영북면 20
 
1.3%
이동면 19
 
1.2%
Other values (471) 712
46.7%
2023-12-12T19:56:25.709986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8617
60.4%
천 326
 
2.3%
포 322
 
2.3%
기 307
 
2.2%
시 307
 
2.2%
경 305
 
2.1%
도 305
 
2.1%
1 303
 
2.1%
면 225
 
1.6%
길 224
 
1.6%
Other values (191) 3018
 
21.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 8617
60.4%
Other Letter 4121
28.9%
Decimal Number 1301
 
9.1%
Dash Punctuation 92
 
0.6%
Open Punctuation 58
 
0.4%
Close Punctuation 58
 
0.4%
Other Punctuation 8
 
0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 326
 
7.9%
포 322
 
7.8%
기 307
 
7.4%
시 307
 
7.4%
경 305
 
7.4%
도 305
 
7.4%
면 225
 
5.5%
길 224
 
5.4%
로 210
 
5.1%
동 132
 
3.2%
Other values (173) 1458
35.4%
Decimal Number
ValueCountFrequency (%)
1 303
23.3%
2 182
14.0%
3 161
12.4%
4 110
 
8.5%
5 100
 
7.7%
0 96
 
7.4%
7 93
 
7.1%
6 91
 
7.0%
9 83
 
6.4%
8 82
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
I 2
50.0%
X 1
25.0%
N 1
25.0%
Space Separator
ValueCountFrequency (%)
8617
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10134
71.1%
Hangul 4121
28.9%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 326
 
7.9%
포 322
 
7.8%
기 307
 
7.4%
시 307
 
7.4%
경 305
 
7.4%
도 305
 
7.4%
면 225
 
5.5%
길 224
 
5.4%
로 210
 
5.1%
동 132
 
3.2%
Other values (173) 1458
35.4%
Common
ValueCountFrequency (%)
8617
85.0%
1 303
 
3.0%
2 182
 
1.8%
3 161
 
1.6%
4 110
 
1.1%
5 100
 
1.0%
0 96
 
0.9%
7 93
 
0.9%
- 92
 
0.9%
6 91
 
0.9%
Other values (5) 289
 
2.9%
Latin
ValueCountFrequency (%)
I 2
50.0%
X 1
25.0%
N 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10138
71.1%
Hangul 4121
28.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8617
85.0%
1 303
 
3.0%
2 182
 
1.8%
3 161
 
1.6%
4 110
 
1.1%
5 100
 
1.0%
0 96
 
0.9%
7 93
 
0.9%
- 92
 
0.9%
6 91
 
0.9%
Other values (8) 293
 
2.9%
Hangul
ValueCountFrequency (%)
천 326
 
7.9%
포 322
 
7.8%
기 307
 
7.4%
시 307
 
7.4%
경 305
 
7.4%
도 305
 
7.4%
면 225
 
5.5%
길 224
 
5.4%
로 210
 
5.1%
동 132
 
3.2%
Other values (173) 1458
35.4%

등록일
Date

Distinct236
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum1900-01-01 00:00:00
Maximum2018-10-24 00:00:00
2023-12-12T19:56:25.949886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:56:26.704021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

경로당 면적(제곱미터)
Real number (ℝ)

Distinct244
Distinct (%)80.5%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean119.11208
Minimum42.2
Maximum494.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:56:26.975543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42.2
5-th percentile62.81
Q195.35
median112
Q3135.45
95-th percentile190.37
Maximum494.6
Range452.4
Interquartile range (IQR)40.1

Descriptive statistics

Standard deviation48.425772
Coefficient of variation (CV)0.40655635
Kurtosis16.190382
Mean119.11208
Median Absolute Deviation (MAD)22
Skewness2.885897
Sum36090.96
Variance2345.0554
MonotonicityNot monotonic
2023-12-12T19:56:27.226607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 9
 
3.0%
132.0 6
 
2.0%
98.0 4
 
1.3%
135.0 3
 
1.0%
99.6 3
 
1.0%
98.8 3
 
1.0%
132.7 3
 
1.0%
57.6 3
 
1.0%
104.0 3
 
1.0%
100.0 3
 
1.0%
Other values (234) 263
86.5%
ValueCountFrequency (%)
42.2 1
 
0.3%
43.0 1
 
0.3%
44.9 1
 
0.3%
49.0 1
 
0.3%
55.0 1
 
0.3%
56.0 1
 
0.3%
57.6 3
1.0%
58.1 1
 
0.3%
58.8 1
 
0.3%
59.31 1
 
0.3%
ValueCountFrequency (%)
494.6 1
0.3%
400.0 1
0.3%
335.6 1
0.3%
281.5 1
0.3%
257.4 1
0.3%
252.0 1
0.3%
249.6 1
0.3%
230.0 1
0.3%
224.0 1
0.3%
210.3 1
0.3%

경로당 층수
Categorical

IMBALANCE 

Distinct10
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
1층
215 
1층,2층
48 
2층
26 
1,2층
 
6
<NA>
 
4
Other values (5)
 
5

Length

Max length7
Median length2
Mean length2.5657895
Min length1

Unique

Unique5 ?
Unique (%)1.6%

Sample

1st row1층
2nd row1층
3rd row1층
4th row1,2층
5th row1층

Common Values

ValueCountFrequency (%)
1층 215
70.7%
1층,2층 48
 
15.8%
2층 26
 
8.6%
1,2층 6
 
2.0%
<NA> 4
 
1.3%
3층 1
 
0.3%
1
 
0.3%
1~3층 1
 
0.3%
지하1층.1층 1
 
0.3%
1.2층 1
 
0.3%

Length

2023-12-12T19:56:27.510628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:56:27.753783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1층 215
71.0%
1층,2층 48
 
15.8%
2층 26
 
8.6%
1,2층 6
 
2.0%
na 4
 
1.3%
3층 1
 
0.3%
1~3층 1
 
0.3%
지하1층.1층 1
 
0.3%
1.2층 1
 
0.3%

부지면적(제곱미터)
Text

MISSING 

Distinct203
Distinct (%)79.3%
Missing48
Missing (%)15.8%
Memory size2.5 KiB
2023-12-12T19:56:28.398133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.40625
Min length3

Characters and Unicode

Total characters872
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

Unique172 ?
Unique (%)67.2%

Sample

1st row231
2nd row460
3rd row684
4th row473
5th row165
ValueCountFrequency (%)
330 8
 
3.1%
496 7
 
2.7%
165 6
 
2.3%
331 5
 
2.0%
320 3
 
1.2%
140 3
 
1.2%
350 3
 
1.2%
316 3
 
1.2%
265 2
 
0.8%
278 2
 
0.8%
Other values (193) 214
83.6%
2023-12-12T19:56:29.302128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 121
13.9%
2 108
12.4%
4 106
12.2%
1 99
11.4%
6 85
9.7%
0 72
8.3%
5 71
8.1%
9 61
7.0%
7 61
7.0%
8 44
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 828
95.0%
Other Punctuation 44
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 121
14.6%
2 108
13.0%
4 106
12.8%
1 99
12.0%
6 85
10.3%
0 72
8.7%
5 71
8.6%
9 61
7.4%
7 61
7.4%
8 44
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 872
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 121
13.9%
2 108
12.4%
4 106
12.2%
1 99
11.4%
6 85
9.7%
0 72
8.3%
5 71
8.1%
9 61
7.0%
7 61
7.0%
8 44
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 121
13.9%
2 108
12.4%
4 106
12.2%
1 99
11.4%
6 85
9.7%
0 72
8.3%
5 71
8.1%
9 61
7.0%
7 61
7.0%
8 44
 
5.0%

건축연월일
Date

Distinct274
Distinct (%)90.4%
Missing1
Missing (%)0.3%
Memory size2.5 KiB
Minimum1905-06-01 00:00:00
Maximum2018-08-15 00:00:00
2023-12-12T19:56:29.564766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:56:29.834072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

건축구조
Categorical

Distinct49
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
철근콘크리트
112 
조적조
50 
철근콘크리트
36 
벽돌구조
28 
조적조
 
9
Other values (44)
69 

Length

Max length12
Median length11
Mean length5.6578947
Min length3

Unique

Unique36 ?
Unique (%)11.8%

Sample

1st row벽돌구조
2nd row철근콘크리트
3rd row<NA>
4th row철근콘크리트,경량철골
5th row철근콘크리트

Common Values

ValueCountFrequency (%)
철근콘크리트 112
36.8%
조적조 50
16.4%
철근콘크리트 36
 
11.8%
벽돌구조 28
 
9.2%
조적조 9
 
3.0%
블럭구조 9
 
3.0%
벽돌구조 7
 
2.3%
벽돌구조,경량철골 6
 
2.0%
경량철골구조 3
 
1.0%
시멘트벽돌조 2
 
0.7%
Other values (39) 42
 
13.8%

Length

2023-12-12T19:56:30.132114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철근콘크리트 148
48.7%
조적조 59
 
19.4%
벽돌구조 35
 
11.5%
블럭구조 9
 
3.0%
벽돌구조,경량철골 6
 
2.0%
경량철골구조 4
 
1.3%
블록구조 2
 
0.7%
경량철골조 2
 
0.7%
조적조,경량철골조 2
 
0.7%
조적조,철근콘크리트 2
 
0.7%
Other values (33) 35
 
11.5%

소유자
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
마을회
122 
포천시
94 
포천시
28 
마을회
20 
대한주택공사
 
3
Other values (35)
37 

Length

Max length11
Median length3
Mean length3.7697368
Min length3

Unique

Unique33 ?
Unique (%)10.9%

Sample

1st row마을회
2nd row마을회
3rd row마을회
4th row마을회
5th row마을회

Common Values

ValueCountFrequency (%)
마을회 122
40.1%
포천시 94
30.9%
포천시 28
 
9.2%
마을회 20
 
6.6%
대한주택공사 3
 
1.0%
극동아파트 2
 
0.7%
아이파크 2
 
0.7%
초가팔1리 노인회 1
 
0.3%
㈜신아 1
 
0.3%
승방동경로당 1
 
0.3%
Other values (30) 30
 
9.9%

Length

2023-12-12T19:56:30.399878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
마을회 142
45.4%
포천시 122
39.0%
노인회 6
 
1.9%
대한주택공사 3
 
1.0%
극동아파트 2
 
0.6%
아이파크 2
 
0.6%
주민회 2
 
0.6%
백자아파트 1
 
0.3%
우정아파트 1
 
0.3%
산호건설 1
 
0.3%
Other values (31) 31
 
9.9%

경로당 연락처
Text

MISSING 

Distinct291
Distinct (%)99.7%
Missing12
Missing (%)3.9%
Memory size2.5 KiB
2023-12-12T19:56:30.867206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.003425
Min length12

Characters and Unicode

Total characters3505
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

Unique290 ?
Unique (%)99.3%

Sample

1st row031-543-8488
2nd row031-543-5934
3rd row031-542-4061
4th row031-544-4126
5th row031-544-1092
ValueCountFrequency (%)
031-531-1007 2
 
0.7%
031-534-9474 1
 
0.3%
031-535-0550 1
 
0.3%
031-535-9398 1
 
0.3%
031-535-9400 1
 
0.3%
031-535-0709 1
 
0.3%
031-533-9040 1
 
0.3%
031-535-0667 1
 
0.3%
031-536-0309 1
 
0.3%
031-536-4667 1
 
0.3%
Other values (281) 281
96.2%
2023-12-12T19:56:31.580462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 685
19.5%
- 584
16.7%
1 450
12.8%
5 434
12.4%
0 398
11.4%
4 256
 
7.3%
2 177
 
5.0%
8 136
 
3.9%
6 131
 
3.7%
7 129
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2921
83.3%
Dash Punctuation 584
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 685
23.5%
1 450
15.4%
5 434
14.9%
0 398
13.6%
4 256
 
8.8%
2 177
 
6.1%
8 136
 
4.7%
6 131
 
4.5%
7 129
 
4.4%
9 125
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 584
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3505
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 685
19.5%
- 584
16.7%
1 450
12.8%
5 434
12.4%
0 398
11.4%
4 256
 
7.3%
2 177
 
5.0%
8 136
 
3.9%
6 131
 
3.7%
7 129
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3505
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 685
19.5%
- 584
16.7%
1 450
12.8%
5 434
12.4%
0 398
11.4%
4 256
 
7.3%
2 177
 
5.0%
8 136
 
3.9%
6 131
 
3.7%
7 129
 
3.7%

난방방식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
심야전기보일러
257 
도시가스
37 
LPG가스
 
7
기름보일러
 
3

Length

Max length7
Median length7
Mean length6.5690789
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row심야전기보일러
2nd row심야전기보일러
3rd row심야전기보일러
4th row심야전기보일러
5th row심야전기보일러

Common Values

ValueCountFrequency (%)
심야전기보일러 257
84.5%
도시가스 37
 
12.2%
LPG가스 7
 
2.3%
기름보일러 3
 
1.0%

Length

2023-12-12T19:56:31.904931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:56:32.102029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
심야전기보일러 257
84.5%
도시가스 37
 
12.2%
lpg가스 7
 
2.3%
기름보일러 3
 
1.0%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2021-08-31 00:00:00
Maximum2021-08-31 00:00:00
2023-12-12T19:56:32.252465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:56:32.418122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T19:56:21.945354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:56:32.552184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동경로당 면적(제곱미터)경로당 층수건축구조소유자난방방식
읍면동1.0000.2230.2360.7860.6190.644
경로당 면적(제곱미터)0.2231.0000.3120.5720.0000.231
경로당 층수0.2360.3121.0000.5880.8160.415
건축구조0.7860.5720.5881.0000.0000.489
소유자0.6190.0000.8160.0001.0000.978
난방방식0.6440.2310.4150.4890.9781.000
2023-12-12T19:56:32.755976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축구조소유자난방방식경로당 층수읍면동
건축구조1.0000.0000.2320.2340.332
소유자0.0001.0000.7860.4370.219
난방방식0.2320.7861.0000.2750.416
경로당 층수0.2340.4370.2751.0000.100
읍면동0.3320.2190.4160.1001.000
2023-12-12T19:56:32.933501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경로당 면적(제곱미터)읍면동경로당 층수건축구조소유자난방방식
경로당 면적(제곱미터)1.0000.0940.1040.2250.0000.148
읍면동0.0941.0000.1000.3320.2190.416
경로당 층수0.1040.1001.0000.2340.4370.275
건축구조0.2250.3320.2341.0000.0000.232
소유자0.0000.2190.4370.0001.0000.786
난방방식0.1480.4160.2750.2320.7861.000

Missing values

2023-12-12T19:56:22.180068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:56:22.558909image/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.
2023-12-12T19:56:22.814820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

경로당명읍면동경로당 주소등록일경로당 면적(제곱미터)경로당 층수부지면적(제곱미터)건축연월일건축구조소유자경로당 연락처난방방식데이터기준일
0한성골(고모1리)소흘읍경기도 포천시 소흘읍 한성길 911994-12-15115.01층<NA>1971-01-01벽돌구조마을회031-543-8488심야전기보일러2021-08-31
1고뫼(고모2리)소흘읍경기도 포천시 소흘읍 죽엽산로 2961998-12-04121.11층2311997-04-26철근콘크리트마을회031-543-5934심야전기보일러2021-08-31
2새터(고모3리)소흘읍경기도 포천시 소흘읍 죽엽산로 419-82007-01-09<NA>1층<NA><NA><NA>마을회031-542-4061심야전기보일러2021-08-31
3송정(무림1리)소흘읍경기도 포천시 소흘읍 무림길 371994-06-15494.61,2층<NA>1995-10-18철근콘크리트,경량철골마을회031-544-4126심야전기보일러2021-08-31
4내누리(무림2리)소흘읍경기도 포천시 소흘읍 무림6길 21994-12-05143.91층4602004-05-03철근콘크리트마을회031-544-1092심야전기보일러2021-08-31
5충목단(무봉1리)소흘읍경기도 포천시 소흘읍 소흘로116번길 401997-01-17133.51층6841996-09-25조적조마을회031-543-3465심야전기보일러2021-08-31
6거친봉이(무봉2리)소흘읍경기도 포천시 소흘읍 거친봉이1길 61-132000-08-10257.41층,2층4732000-03-31철근콘크리트마을회031-543-3799심야전기보일러2021-08-31
7막골(무봉3리)소흘읍경기도 포천시 소흘읍 소흘로24번길 10-301996-01-0399.01층1651993-01-19벽돌구조마을회031-543-7856심야전기보일러2021-08-31
8곤당골(송우1리)소흘읍경기도 포천시 소흘읍 송우리 산28-31988-05-19169.61층<NA>1981-01-01벽돌구조송우 노인회031-541-7885심야전기보일러2021-08-31
9아래장터(송우3리)소흘읍경기도 포천시 소흘읍 화합로 387-131998-12-04131.221층<NA>1988-11-20철근콘크리트송우3리 노인회031-542-6883심야전기보일러2021-08-31
경로당명읍면동경로당 주소등록일경로당 면적(제곱미터)경로당 층수부지면적(제곱미터)건축연월일건축구조소유자경로당 연락처난방방식데이터기준일
294장승(선단4통)선단동경기도 포천시 삼육사로2242번길 16-32 (선단동)2001-12-2897.31층1652001-06-28조적조포천시031-543-4186심야전기보일러2021-08-31
295상록(선단5통)선단동경기도 포천시 송선로 301 (선단동)2001-12-28117.21층2701995-06-30철근콘크리트마을회031-542-4889심야전기보일러2021-08-31
296외촌(선단6통)선단동경기도 포천시 건너말1길 31 (선단동)2010-11-2399.91층4632010-11-22경량철골조포천시031-544-1199도시가스2021-08-31
297세창아파트선단동경기도 포천시 선마로 22 (선단동)2001-12-2888.31층28,1112001-05-17철근콘크리트세창아파트031-542-6210도시가스2021-08-31
298해룡(설운2통)선단동경기도 포천시 해룡로16번길 9-13 (설운동)1994-03-02113.01층2551993-09-20철근콘크리트마을회031-541-1622심야전기보일러2021-08-31
299장송(설운3통)선단동경기도 포천시 호국로 899-14 (설운동)1993-12-2466.02층3541998-12-15철근콘크리트,조적조마을회031-541-8613심야전기보일러2021-08-31
300자작(1통)선단동경기도 포천시 자작로3길 19(자작동)1995-02-02184.81층3871992-11-30철근콘크리트마을회031-542-8149심야전기보일러2021-08-31
301파발막(자작2통)선단동경기도 포천시 정자동1길 6 (선단동)1994-03-0781.21층2421993-01-11경량판넬구조마을회031-536-1490심야전기보일러2021-08-31
302설운1통선단동경기도 포천시 호국로883번길 912014-11-12132.2<NA><NA>2014-11-11철근콘크리트포천시<NA>심야전기보일러2021-08-31
303선단7통(성황)선단동경기도 포천시 호국로 982번길 13, 선단동 아띠플러스 103동 201호2017-01-2568.9<NA><NA>2014-11-11철근콘크리트포천시<NA>심야전기보일러2021-08-31