Overview

Dataset statistics

Number of variables14
Number of observations318
Missing cells67
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.1 KiB
Average record size in memory119.4 B

Variable types

Numeric6
Categorical3
Text4
DateTime1

Dataset

Description경상남도 거제시 경로당 정보에 대한 현황을 제공합니다(면동, 경로당명칭, 소재지, 위도, 경도, 등록일자, 기준일자)에 대한 정보를 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15037762

Alerts

개소수 has constant value ""Constant
기준일 has constant value ""Constant
회원수(총계) is highly overall correlated with 회원(남) and 1 other fieldsHigh correlation
회원(남) is highly overall correlated with 회원수(총계)High correlation
회원(여) is highly overall correlated with 회원수(총계)High correlation
위도 is highly overall correlated with 면동High correlation
경도 is highly overall correlated with 면동High correlation
면동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
전화번호 has 51 (16.0%) missing valuesMissing
위도 has 8 (2.5%) missing valuesMissing
경도 has 8 (2.5%) missing valuesMissing
회원(남) has 12 (3.8%) zerosZeros
회원(여) has 5 (1.6%) zerosZeros

Reproduction

Analysis started2023-12-11 00:36:16.661973
Analysis finished2023-12-11 00:36:20.829503
Duration4.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Real number (ℝ)

Distinct317
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean171.68553
Minimum1
Maximum352
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T09:36:20.895445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.85
Q184.25
median167.5
Q3256.75
95-th percentile336.15
Maximum352
Range351
Interquartile range (IQR)172.5

Descriptive statistics

Standard deviation100.81749
Coefficient of variation (CV)0.58722179
Kurtosis-1.1540708
Mean171.68553
Median Absolute Deviation (MAD)86.5
Skewness0.10127071
Sum54596
Variance10164.166
MonotonicityIncreasing
2023-12-11T09:36:21.003850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
278 2
 
0.6%
257 1
 
0.3%
228 1
 
0.3%
227 1
 
0.3%
226 1
 
0.3%
225 1
 
0.3%
224 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
Other values (307) 307
96.5%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
6 1
0.3%
8 1
0.3%
10 1
0.3%
11 1
0.3%
12 1
0.3%
13 1
0.3%
ValueCountFrequency (%)
352 1
0.3%
351 1
0.3%
350 1
0.3%
349 1
0.3%
348 1
0.3%
347 1
0.3%
346 1
0.3%
345 1
0.3%
344 1
0.3%
343 1
0.3%

면동
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
사등면
32 
장목면
29 
연초면
28 
거제면
27 
하청면
27 
Other values (14)
175 

Length

Max length4
Median length3
Mean length3.091195
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row수양동
2nd row고현동
3rd row고현동
4th row상문동
5th row고현동

Common Values

ValueCountFrequency (%)
사등면 32
 
10.1%
장목면 29
 
9.1%
연초면 28
 
8.8%
거제면 27
 
8.5%
하청면 27
 
8.5%
둔덕면 21
 
6.6%
일운면 20
 
6.3%
동부면 20
 
6.3%
고현동 18
 
5.7%
상문동 16
 
5.0%
Other values (9) 80
25.2%

Length

2023-12-11T09:36:21.111189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사등면 32
 
10.1%
장목면 29
 
9.1%
연초면 28
 
8.8%
거제면 27
 
8.5%
하청면 27
 
8.5%
둔덕면 21
 
6.6%
일운면 20
 
6.3%
동부면 20
 
6.3%
고현동 18
 
5.7%
상문동 16
 
5.0%
Other values (8) 80
25.2%

시설명
Text

Distinct313
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T09:36:21.337946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length5
Mean length5.9622642
Min length4

Characters and Unicode

Total characters1896
Distinct characters237
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique308 ?
Unique (%)96.9%

Sample

1st row동산내경로당
2nd row성림마을경로당
3rd row신현경로당
4th row문동경로당
5th row서문경로당
ValueCountFrequency (%)
경로당 5
 
1.5%
죽전경로당 2
 
0.6%
서상경로당 2
 
0.6%
두모경로당 2
 
0.6%
신촌경로당 2
 
0.6%
롯데인벤스경로당 2
 
0.6%
고당경로당 1
 
0.3%
율북경로당 1
 
0.3%
영북경로당 1
 
0.3%
동상경로당 1
 
0.3%
Other values (304) 304
94.1%
2023-12-11T09:36:21.672960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 305
 
16.1%
로 305
 
16.1%
당 304
 
16.0%
동 29
 
1.5%
포 28
 
1.5%
아 28
 
1.5%
산 26
 
1.4%
트 21
 
1.1%
차 19
 
1.0%
파 19
 
1.0%
Other values (227) 812
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1844
97.3%
Decimal Number 34
 
1.8%
Space Separator 5
 
0.3%
Uppercase Letter 5
 
0.3%
Other Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Lowercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 305
16.5%
로 305
16.5%
당 304
 
16.5%
동 29
 
1.6%
포 28
 
1.5%
아 28
 
1.5%
산 26
 
1.4%
트 21
 
1.1%
차 19
 
1.0%
파 19
 
1.0%
Other values (209) 760
41.2%
Decimal Number
ValueCountFrequency (%)
1 11
32.4%
2 8
23.5%
3 7
20.6%
6 3
 
8.8%
4 2
 
5.9%
5 2
 
5.9%
7 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
20.0%
K 1
20.0%
A 1
20.0%
H 1
20.0%
L 1
20.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1844
97.3%
Common 46
 
2.4%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 305
16.5%
로 305
16.5%
당 304
 
16.5%
동 29
 
1.6%
포 28
 
1.5%
아 28
 
1.5%
산 26
 
1.4%
트 21
 
1.1%
차 19
 
1.0%
파 19
 
1.0%
Other values (209) 760
41.2%
Common
ValueCountFrequency (%)
1 11
23.9%
2 8
17.4%
3 7
15.2%
5
10.9%
6 3
 
6.5%
. 2
 
4.3%
) 2
 
4.3%
( 2
 
4.3%
4 2
 
4.3%
5 2
 
4.3%
Other values (2) 2
 
4.3%
Latin
ValueCountFrequency (%)
S 1
16.7%
e 1
16.7%
K 1
16.7%
A 1
16.7%
H 1
16.7%
L 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1844
97.3%
ASCII 52
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 305
16.5%
로 305
16.5%
당 304
 
16.5%
동 29
 
1.6%
포 28
 
1.5%
아 28
 
1.5%
산 26
 
1.4%
트 21
 
1.1%
차 19
 
1.0%
파 19
 
1.0%
Other values (209) 760
41.2%
ASCII
ValueCountFrequency (%)
1 11
21.2%
2 8
15.4%
3 7
13.5%
5
9.6%
6 3
 
5.8%
. 2
 
3.8%
) 2
 
3.8%
( 2
 
3.8%
4 2
 
3.8%
5 2
 
3.8%
Other values (8) 8
15.4%

개소수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
1
318 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 318
100.0%

Length

2023-12-11T09:36:21.799739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:21.895286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 318
100.0%

소 재 지
Text

Distinct314
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T09:36:22.122419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length21.166667
Min length17

Characters and Unicode

Total characters6731
Distinct characters159
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

Unique310 ?
Unique (%)97.5%

Sample

1st row경상남도 거제시 수양동 수양로 382
2nd row경상남도 거제시 고현동 고현로 8길 20
3rd row경상남도 거제시 고현동 고현로8길 6-1
4th row경상남도 거제시 상문동 수양로 24-10
5th row경상남도 거제시 고현동 거제중앙로19길 37
ValueCountFrequency (%)
경상남도 318
19.6%
거제시 318
19.6%
사등면 32
 
2.0%
장목면 29
 
1.8%
연초면 28
 
1.7%
거제면 27
 
1.7%
하청면 27
 
1.7%
둔덕면 21
 
1.3%
일운면 20
 
1.2%
동부면 20
 
1.2%
Other values (445) 783
48.2%
2023-12-11T09:36:22.455727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1306
19.4%
거 381
 
5.7%
제 380
 
5.6%
상 341
 
5.1%
남 339
 
5.0%
도 322
 
4.8%
시 321
 
4.8%
경 318
 
4.7%
1 243
 
3.6%
길 218
 
3.2%
Other values (149) 2562
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4318
64.2%
Space Separator 1306
 
19.4%
Decimal Number 1022
 
15.2%
Dash Punctuation 81
 
1.2%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 381
 
8.8%
제 380
 
8.8%
상 341
 
7.9%
남 339
 
7.9%
도 322
 
7.5%
시 321
 
7.4%
경 318
 
7.4%
길 218
 
5.0%
면 215
 
5.0%
로 157
 
3.6%
Other values (135) 1326
30.7%
Decimal Number
ValueCountFrequency (%)
1 243
23.8%
2 176
17.2%
3 125
12.2%
5 101
9.9%
4 82
 
8.0%
6 73
 
7.1%
7 62
 
6.1%
8 56
 
5.5%
9 52
 
5.1%
0 52
 
5.1%
Space Separator
ValueCountFrequency (%)
1306
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4318
64.2%
Common 2413
35.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 381
 
8.8%
제 380
 
8.8%
상 341
 
7.9%
남 339
 
7.9%
도 322
 
7.5%
시 321
 
7.4%
경 318
 
7.4%
길 218
 
5.0%
면 215
 
5.0%
로 157
 
3.6%
Other values (135) 1326
30.7%
Common
ValueCountFrequency (%)
1306
54.1%
1 243
 
10.1%
2 176
 
7.3%
3 125
 
5.2%
5 101
 
4.2%
4 82
 
3.4%
- 81
 
3.4%
6 73
 
3.0%
7 62
 
2.6%
8 56
 
2.3%
Other values (4) 108
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4318
64.2%
ASCII 2413
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1306
54.1%
1 243
 
10.1%
2 176
 
7.3%
3 125
 
5.2%
5 101
 
4.2%
4 82
 
3.4%
- 81
 
3.4%
6 73
 
3.0%
7 62
 
2.6%
8 56
 
2.3%
Other values (4) 108
 
4.5%
Hangul
ValueCountFrequency (%)
거 381
 
8.8%
제 380
 
8.8%
상 341
 
7.9%
남 339
 
7.9%
도 322
 
7.5%
시 321
 
7.4%
경 318
 
7.4%
길 218
 
5.0%
면 215
 
5.0%
로 157
 
3.6%
Other values (135) 1326
30.7%

성명
Text

Distinct315
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T09:36:22.750568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0031447
Min length2

Characters and Unicode

Total characters955
Distinct characters173
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

Unique312 ?
Unique (%)98.1%

Sample

1st row이종규
2nd row김증자
3rd row손정목
4th row김대곤
5th row윤태근
ValueCountFrequency (%)
김정석 2
 
0.6%
정규오 2
 
0.6%
옥기영 2
 
0.6%
김봉자 1
 
0.3%
이석조 1
 
0.3%
배선각 1
 
0.3%
이부웅 1
 
0.3%
서수찬 1
 
0.3%
최문수 1
 
0.3%
김용조 1
 
0.3%
Other values (305) 305
95.9%
2023-12-11T09:36:23.400722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 77
 
8.1%
정 49
 
5.1%
이 39
 
4.1%
옥 28
 
2.9%
자 21
 
2.2%
박 21
 
2.2%
영 20
 
2.1%
윤 20
 
2.1%
수 17
 
1.8%
상 17
 
1.8%
Other values (163) 646
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 954
99.9%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 77
 
8.1%
정 49
 
5.1%
이 39
 
4.1%
옥 28
 
2.9%
자 21
 
2.2%
박 21
 
2.2%
영 20
 
2.1%
윤 20
 
2.1%
수 17
 
1.8%
상 17
 
1.8%
Other values (162) 645
67.6%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 954
99.9%
Common 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 77
 
8.1%
정 49
 
5.1%
이 39
 
4.1%
옥 28
 
2.9%
자 21
 
2.2%
박 21
 
2.2%
영 20
 
2.1%
윤 20
 
2.1%
수 17
 
1.8%
상 17
 
1.8%
Other values (162) 645
67.6%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 954
99.9%
ASCII 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 77
 
8.1%
정 49
 
5.1%
이 39
 
4.1%
옥 28
 
2.9%
자 21
 
2.2%
박 21
 
2.2%
영 20
 
2.1%
윤 20
 
2.1%
수 17
 
1.8%
상 17
 
1.8%
Other values (162) 645
67.6%
ASCII
ValueCountFrequency (%)
1
100.0%

회원수(총계)
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.509434
Minimum10
Maximum105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T09:36:23.523675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile17
Q122
median29
Q341
95-th percentile60.15
Maximum105
Range95
Interquartile range (IQR)19

Descriptive statistics

Standard deviation15.30793
Coefficient of variation (CV)0.45682449
Kurtosis2.9390489
Mean33.509434
Median Absolute Deviation (MAD)8
Skewness1.5054432
Sum10656
Variance234.33272
MonotonicityNot monotonic
2023-12-11T09:36:23.655497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 27
 
8.5%
22 18
 
5.7%
28 17
 
5.3%
25 15
 
4.7%
30 11
 
3.5%
27 11
 
3.5%
24 11
 
3.5%
23 11
 
3.5%
33 10
 
3.1%
21 10
 
3.1%
Other values (55) 177
55.7%
ValueCountFrequency (%)
10 1
 
0.3%
11 1
 
0.3%
12 2
 
0.6%
13 2
 
0.6%
14 1
 
0.3%
15 4
1.3%
16 2
 
0.6%
17 5
1.6%
18 4
1.3%
19 5
1.6%
ValueCountFrequency (%)
105 1
0.3%
99 1
0.3%
87 1
0.3%
85 1
0.3%
82 1
0.3%
81 1
0.3%
80 1
0.3%
77 2
0.6%
69 1
0.3%
68 1
0.3%

회원(남)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.654088
Minimum0
Maximum58
Zeros12
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T09:36:23.762812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q17
median10
Q315
95-th percentile25
Maximum58
Range58
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.7263835
Coefficient of variation (CV)0.66297624
Kurtosis6.7430561
Mean11.654088
Median Absolute Deviation (MAD)4
Skewness1.8727891
Sum3706
Variance59.697002
MonotonicityNot monotonic
2023-12-11T09:36:23.870941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
10 38
 
11.9%
9 24
 
7.5%
11 20
 
6.3%
8 20
 
6.3%
6 18
 
5.7%
7 18
 
5.7%
13 18
 
5.7%
5 16
 
5.0%
14 15
 
4.7%
4 14
 
4.4%
Other values (24) 117
36.8%
ValueCountFrequency (%)
0 12
3.8%
1 3
 
0.9%
2 3
 
0.9%
3 7
 
2.2%
4 14
4.4%
5 16
5.0%
6 18
5.7%
7 18
5.7%
8 20
6.3%
9 24
7.5%
ValueCountFrequency (%)
58 1
 
0.3%
52 1
 
0.3%
41 2
 
0.6%
34 1
 
0.3%
32 3
0.9%
31 1
 
0.3%
30 1
 
0.3%
28 2
 
0.6%
25 6
1.9%
24 3
0.9%

회원(여)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.855346
Minimum0
Maximum69
Zeros5
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T09:36:24.008965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.85
Q115
median20
Q327
95-th percentile40
Maximum69
Range69
Interquartile range (IQR)12

Descriptive statistics

Standard deviation10.423122
Coefficient of variation (CV)0.47691407
Kurtosis2.3251316
Mean21.855346
Median Absolute Deviation (MAD)6
Skewness1.1114371
Sum6950
Variance108.64147
MonotonicityNot monotonic
2023-12-11T09:36:24.145896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 27
 
8.5%
17 21
 
6.6%
15 19
 
6.0%
14 13
 
4.1%
18 13
 
4.1%
19 13
 
4.1%
12 13
 
4.1%
25 12
 
3.8%
22 12
 
3.8%
23 11
 
3.5%
Other values (40) 164
51.6%
ValueCountFrequency (%)
0 5
 
1.6%
5 2
 
0.6%
7 1
 
0.3%
8 8
2.5%
9 4
 
1.3%
10 7
2.2%
11 9
2.8%
12 13
4.1%
13 11
3.5%
14 13
4.1%
ValueCountFrequency (%)
69 1
0.3%
64 1
0.3%
60 1
0.3%
54 1
0.3%
53 1
0.3%
51 1
0.3%
50 1
0.3%
49 1
0.3%
48 1
0.3%
45 1
0.3%

전화번호
Text

MISSING 

Distinct265
Distinct (%)99.3%
Missing51
Missing (%)16.0%
Memory size2.6 KiB
2023-12-11T09:36:24.370778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters3204
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

Unique263 ?
Unique (%)98.5%

Sample

1st row055-635-7111
2nd row055-636-0023
3rd row055-635-3336
4th row055-636-5105
5th row055-635-8775
ValueCountFrequency (%)
055-635-8874 2
 
0.7%
055-635-0938 2
 
0.7%
055-687-0302 1
 
0.4%
055-633-3733 1
 
0.4%
055-635-4665 1
 
0.4%
055-632-5864 1
 
0.4%
055-635-7111 1
 
0.4%
055-632-4577 1
 
0.4%
055-632-8891 1
 
0.4%
055-632-6766 1
 
0.4%
Other values (255) 255
95.5%
2023-12-11T09:36:24.694635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 724
22.6%
- 534
16.7%
6 420
13.1%
0 397
12.4%
3 349
10.9%
8 159
 
5.0%
1 154
 
4.8%
2 152
 
4.7%
7 130
 
4.1%
4 102
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2670
83.3%
Dash Punctuation 534
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 724
27.1%
6 420
15.7%
0 397
14.9%
3 349
13.1%
8 159
 
6.0%
1 154
 
5.8%
2 152
 
5.7%
7 130
 
4.9%
4 102
 
3.8%
9 83
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 534
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3204
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 724
22.6%
- 534
16.7%
6 420
13.1%
0 397
12.4%
3 349
10.9%
8 159
 
5.0%
1 154
 
4.8%
2 152
 
4.7%
7 130
 
4.1%
4 102
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 724
22.6%
- 534
16.7%
6 420
13.1%
0 397
12.4%
3 349
10.9%
8 159
 
5.0%
1 154
 
4.8%
2 152
 
4.7%
7 130
 
4.1%
4 102
 
3.2%

개소정보(설립일)
Date

Distinct253
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1935-01-01 00:00:00
Maximum2019-09-23 00:00:00
2023-12-11T09:36:24.819464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:24.943904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct306
Distinct (%)98.7%
Missing8
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean34.88687
Minimum34.714529
Maximum35.029753
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T09:36:25.057080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.714529
5-th percentile34.78925
Q134.850499
median34.886468
Q334.920075
95-th percentile34.991576
Maximum35.029753
Range0.31522406
Interquartile range (IQR)0.06957585

Descriptive statistics

Standard deviation0.060998051
Coefficient of variation (CV)0.001748453
Kurtosis0.23643458
Mean34.88687
Median Absolute Deviation (MAD)0.034834155
Skewness-0.096558602
Sum10814.93
Variance0.0037207622
MonotonicityNot monotonic
2023-12-11T09:36:25.177386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.91369475 2
 
0.6%
34.87615028 2
 
0.6%
34.91020488 2
 
0.6%
34.82553033 2
 
0.6%
34.81116798 1
 
0.3%
34.92014953 1
 
0.3%
34.99148777 1
 
0.3%
34.91090185 1
 
0.3%
34.98217703 1
 
0.3%
34.89992649 1
 
0.3%
Other values (296) 296
93.1%
(Missing) 8
 
2.5%
ValueCountFrequency (%)
34.71452921 1
0.3%
34.71485716 1
0.3%
34.72545699 1
0.3%
34.72894983 1
0.3%
34.73274779 1
0.3%
34.73687369 1
0.3%
34.73798293 1
0.3%
34.73975612 1
0.3%
34.74139883 1
0.3%
34.76269195 1
0.3%
ValueCountFrequency (%)
35.02975327 1
0.3%
35.02903987 1
0.3%
35.02745927 1
0.3%
35.02092568 1
0.3%
35.01436784 1
0.3%
35.00954352 1
0.3%
35.00940238 1
0.3%
35.00901896 1
0.3%
35.00662799 1
0.3%
35.00639308 1
0.3%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct306
Distinct (%)98.7%
Missing8
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean128.63021
Minimum128.46506
Maximum128.73866
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T09:36:25.309000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.46506
5-th percentile128.50737
Q1128.58968
median128.63798
Q3128.68623
95-th percentile128.724
Maximum128.73866
Range0.273599
Interquartile range (IQR)0.096541425

Descriptive statistics

Standard deviation0.068269688
Coefficient of variation (CV)0.00053074383
Kurtosis-0.57035635
Mean128.63021
Median Absolute Deviation (MAD)0.04831625
Skewness-0.53447242
Sum39875.364
Variance0.0046607503
MonotonicityNot monotonic
2023-12-11T09:36:25.435161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6543877 2
 
0.6%
128.7348002 2
 
0.6%
128.6440578 2
 
0.6%
128.6055704 2
 
0.6%
128.5990074 1
 
0.3%
128.5312214 1
 
0.3%
128.6451152 1
 
0.3%
128.6182169 1
 
0.3%
128.6631142 1
 
0.3%
128.6861627 1
 
0.3%
Other values (296) 296
93.1%
(Missing) 8
 
2.5%
ValueCountFrequency (%)
128.465064 1
0.3%
128.472862 1
0.3%
128.4764886 1
0.3%
128.4783711 1
0.3%
128.4797251 1
0.3%
128.4797511 1
0.3%
128.4805137 1
0.3%
128.4809108 1
0.3%
128.4815401 1
0.3%
128.4895079 1
0.3%
ValueCountFrequency (%)
128.738663 1
0.3%
128.7362959 1
0.3%
128.7348002 2
0.6%
128.7342142 1
0.3%
128.7341492 1
0.3%
128.7325245 1
0.3%
128.7324638 1
0.3%
128.7313095 1
0.3%
128.7312088 1
0.3%
128.730901 1
0.3%

기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2020-03-12
318 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-03-12
2nd row2020-03-12
3rd row2020-03-12
4th row2020-03-12
5th row2020-03-12

Common Values

ValueCountFrequency (%)
2020-03-12 318
100.0%

Length

2023-12-11T09:36:25.568991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:25.663425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-03-12 318
100.0%

Interactions

2023-12-11T09:36:20.047157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:17.282631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:17.886556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.439242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.992749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.516607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:20.144338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:17.370298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:17.973832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.533085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.074745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.595225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:20.210412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:17.464643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.046411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.641954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.153337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.670846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:20.285797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:17.586056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.151222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.728869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.235219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.746753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:20.364865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:17.693366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.234210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.813287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.320916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.833601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:20.438732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:17.798100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.340626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:18.908946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.410760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:19.953546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:36:25.727104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호면동회원수(총계)회원(남)회원(여)위도경도
등록번호1.0000.6720.4570.2170.5350.5710.640
면동0.6721.0000.3380.3820.2400.8970.872
회원수(총계)0.4570.3381.0000.7360.9410.4810.398
회원(남)0.2170.3820.7361.0000.6650.1410.170
회원(여)0.5350.2400.9410.6651.0000.4080.384
위도0.5710.8970.4810.1410.4081.0000.528
경도0.6400.8720.3980.1700.3840.5281.000
2023-12-11T09:36:25.869225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호회원수(총계)회원(남)회원(여)위도경도면동
등록번호1.000-0.491-0.294-0.4750.0470.1930.320
회원수(총계)-0.4911.0000.7580.868-0.042-0.1540.141
회원(남)-0.2940.7581.0000.404-0.035-0.2420.156
회원(여)-0.4750.8680.4041.000-0.039-0.0910.090
위도0.047-0.042-0.035-0.0391.0000.2210.609
경도0.193-0.154-0.242-0.0910.2211.0000.560
면동0.3200.1410.1560.0900.6090.5601.000

Missing values

2023-12-11T09:36:20.542870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:36:20.683642image/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.
2023-12-11T09:36:20.781280image/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

등록번호면동시설명개소수소 재 지성명회원수(총계)회원(남)회원(여)전화번호개소정보(설립일)위도경도기준일
01수양동동산내경로당1경상남도 거제시 수양동 수양로 382이종규21210055-635-71112000-09-0734.888325128.646742020-03-12
12고현동성림마을경로당1경상남도 거제시 고현동 고현로 8길 20김증자30030055-636-00232001-09-0134.885066128.6237952020-03-12
23고현동신현경로당1경상남도 거제시 고현동 고현로8길 6-1손정목58580055-635-33361999-02-0134.886037128.6231152020-03-12
34상문동문동경로당1경상남도 거제시 상문동 수양로 24-10김대곤27720055-636-51051992-01-0134.861491128.6455612020-03-12
46고현동서문경로당1경상남도 거제시 고현동 거제중앙로19길 37윤태근351025055-635-87751994-07-0134.884069128.6208882020-03-12
58장평동와치경로당1경상남도 거제시 장평동 장평3로 7길 57천경숙22517055-635-55581991-01-0134.892651128.605862020-03-12
610상문동삼거경로당1경상남도 거제시 상문동 거제중앙로 1274윤봉권532132055-637-36631992-01-0134.842942128.6483062020-03-12
711장평동장평4경로당1경상남도 거제시 장평동 장평1로 143황갑연30327055-636-09721992-03-0134.891464128.6045692020-03-12
812장평동장평경로당1경상남도 거제시 장평동 장평로 71김형부281315055-632-43452008-05-0134.890917128.609452020-03-12
913고현동양정고려3차경로당1경상남도 거제시 고현동 중곡로 14김상영221111055-635-99511993-05-0134.894082128.6306152020-03-12
등록번호면동시설명개소수소 재 지성명회원수(총계)회원(남)회원(여)전화번호개소정보(설립일)위도경도기준일
308343장평동덕산아내1차경로당1경상남도 거제시 장평동 장평3로 41정동환20119055-632-38502018-02-0134.891008128.6070932020-03-12
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