Overview

Dataset statistics

Number of variables11
Number of observations440
Missing cells220
Missing cells (%)4.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.2 KiB
Average record size in memory91.3 B

Variable types

Numeric3
Categorical2
Text5
DateTime1

Dataset

Description경상남도 거창군 경로당 및 마을회관 현황 데이터로 연번, 읍면, 마을명, 경로당명, 주소, 연락처 등의 항목을 제공합니다.
Author경상남도 거창군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15044915

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 읍면High correlation
위도 is highly overall correlated with 읍면High correlation
경도 is highly overall correlated with 읍면High correlation
읍면 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
비고 is highly imbalanced (59.9%)Imbalance
지번주소 has 9 (2.0%) missing valuesMissing
위도 has 10 (2.3%) missing valuesMissing
경도 has 10 (2.3%) missing valuesMissing
연락처 has 191 (43.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:37:49.787896
Analysis finished2023-12-11 00:37:51.670741
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct440
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220.5
Minimum1
Maximum440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T09:37:51.741783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.95
Q1110.75
median220.5
Q3330.25
95-th percentile418.05
Maximum440
Range439
Interquartile range (IQR)219.5

Descriptive statistics

Standard deviation127.16131
Coefficient of variation (CV)0.57669531
Kurtosis-1.2
Mean220.5
Median Absolute Deviation (MAD)110
Skewness0
Sum97020
Variance16170
MonotonicityStrictly increasing
2023-12-11T09:37:51.877086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
291 1
 
0.2%
302 1
 
0.2%
301 1
 
0.2%
300 1
 
0.2%
299 1
 
0.2%
298 1
 
0.2%
297 1
 
0.2%
296 1
 
0.2%
295 1
 
0.2%
Other values (430) 430
97.7%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
440 1
0.2%
439 1
0.2%
438 1
0.2%
437 1
0.2%
436 1
0.2%
435 1
0.2%
434 1
0.2%
433 1
0.2%
432 1
0.2%
431 1
0.2%

읍면
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
거창
109 
가조
40 
마리
36 
웅양
33 
남상
33 
Other values (7)
189 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
거창 109
24.8%
가조 40
 
9.1%
마리 36
 
8.2%
웅양 33
 
7.5%
남상 33
 
7.5%
신원 32
 
7.3%
가북 31
 
7.0%
주상 28
 
6.4%
고제 28
 
6.4%
위천 26
 
5.9%
Other values (2) 44
10.0%

Length

2023-12-11T09:37:52.009755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
거창 109
24.8%
가조 40
 
9.1%
마리 36
 
8.2%
웅양 33
 
7.5%
남상 33
 
7.5%
신원 32
 
7.3%
가북 31
 
7.0%
주상 28
 
6.4%
고제 28
 
6.4%
위천 26
 
5.9%
Other values (2) 44
10.0%

마을명
Text

Distinct288
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-11T09:37:52.358958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.1477273
Min length2

Characters and Unicode

Total characters945
Distinct characters180
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

Unique211 ?
Unique (%)48.0%

Sample

1st row하동
2nd row상동
3rd row강양
4th row강양
5th row개봉
ValueCountFrequency (%)
동동 12
 
2.7%
상동 11
 
2.5%
하동 10
 
2.3%
신기 7
 
1.6%
김천리 6
 
1.4%
강양 6
 
1.4%
도평 6
 
1.4%
중동 6
 
1.4%
오산 5
 
1.1%
장팔 5
 
1.1%
Other values (278) 366
83.2%
2023-12-11T09:37:52.915623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 105
 
11.1%
산 40
 
4.2%
상 27
 
2.9%
촌 23
 
2.4%
원 22
 
2.3%
하 19
 
2.0%
중 18
 
1.9%
평 18
 
1.9%
기 18
 
1.9%
곡 18
 
1.9%
Other values (170) 637
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 935
98.9%
Open Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 105
 
11.2%
산 40
 
4.3%
상 27
 
2.9%
촌 23
 
2.5%
원 22
 
2.4%
하 19
 
2.0%
중 18
 
1.9%
평 18
 
1.9%
기 18
 
1.9%
곡 18
 
1.9%
Other values (166) 627
67.1%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 935
98.9%
Common 10
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 105
 
11.2%
산 40
 
4.3%
상 27
 
2.9%
촌 23
 
2.5%
원 22
 
2.4%
하 19
 
2.0%
중 18
 
1.9%
평 18
 
1.9%
기 18
 
1.9%
곡 18
 
1.9%
Other values (166) 627
67.1%
Common
ValueCountFrequency (%)
( 4
40.0%
) 4
40.0%
2 1
 
10.0%
1 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 935
98.9%
ASCII 10
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 105
 
11.2%
산 40
 
4.3%
상 27
 
2.9%
촌 23
 
2.5%
원 22
 
2.4%
하 19
 
2.0%
중 18
 
1.9%
평 18
 
1.9%
기 18
 
1.9%
곡 18
 
1.9%
Other values (166) 627
67.1%
ASCII
ValueCountFrequency (%)
( 4
40.0%
) 4
40.0%
2 1
 
10.0%
1 1
 
10.0%

경로당명
Text

Distinct413
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-11T09:37:53.173519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length5
Mean length5.7227273
Min length5

Characters and Unicode

Total characters2518
Distinct characters220
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique391 ?
Unique (%)88.9%

Sample

1st row77경로당
2nd row강변경로당
3rd row강양경로당
4th row강양할머니경로당
5th row개봉경로당
ValueCountFrequency (%)
신기경로당 4
 
0.9%
창촌경로당 3
 
0.7%
신촌경로당 3
 
0.7%
송정경로당 3
 
0.7%
대현경로당 2
 
0.5%
월포경로당 2
 
0.5%
도동경로당 2
 
0.5%
중산경로당 2
 
0.5%
산포경로당 2
 
0.5%
중촌경로당 2
 
0.5%
Other values (403) 415
94.3%
2023-12-11T09:37:53.643735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 451
17.9%
경 441
17.5%
로 440
17.5%
동 62
 
2.5%
할 42
 
1.7%
산 35
 
1.4%
니 34
 
1.4%
머 34
 
1.4%
상 26
 
1.0%
대 26
 
1.0%
Other values (210) 927
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2490
98.9%
Decimal Number 16
 
0.6%
Other Punctuation 4
 
0.2%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Other Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 451
18.1%
경 441
17.7%
로 440
17.7%
동 62
 
2.5%
할 42
 
1.7%
산 35
 
1.4%
니 34
 
1.4%
머 34
 
1.4%
상 26
 
1.0%
대 26
 
1.0%
Other values (202) 899
36.1%
Decimal Number
ValueCountFrequency (%)
2 8
50.0%
1 5
31.2%
7 2
 
12.5%
3 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
@ 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Symbol
ValueCountFrequency (%)
㉵ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2492
99.0%
Common 26
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 451
18.1%
경 441
17.7%
로 440
17.7%
동 62
 
2.5%
할 42
 
1.7%
산 35
 
1.4%
니 34
 
1.4%
머 34
 
1.4%
상 26
 
1.0%
대 26
 
1.0%
Other values (203) 901
36.2%
Common
ValueCountFrequency (%)
2 8
30.8%
1 5
19.2%
@ 4
15.4%
( 3
 
11.5%
) 3
 
11.5%
7 2
 
7.7%
3 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2490
98.9%
ASCII 26
 
1.0%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 451
18.1%
경 441
17.7%
로 440
17.7%
동 62
 
2.5%
할 42
 
1.7%
산 35
 
1.4%
니 34
 
1.4%
머 34
 
1.4%
상 26
 
1.0%
대 26
 
1.0%
Other values (202) 899
36.1%
ASCII
ValueCountFrequency (%)
2 8
30.8%
1 5
19.2%
@ 4
15.4%
( 3
 
11.5%
) 3
 
11.5%
7 2
 
7.7%
3 1
 
3.8%
None
ValueCountFrequency (%)
㉵ 2
100.0%

도로명주소
Text

Distinct412
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-11T09:37:54.028261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length20.761364
Min length18

Characters and Unicode

Total characters9135
Distinct characters209
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique386 ?
Unique (%)87.7%

Sample

1st row경상남도 거창군 거창읍 아림로2길 69
2nd row경상남도 거창군 거창읍 상동9길 14
3rd row경상남도 거창군 거창읍 중앙로1길 38-6
4th row경상남도 거창군 거창읍 중앙로1길 88-6
5th row경상남도 거창군 거창읍 거열로 234-8
ValueCountFrequency (%)
경상남도 440
20.0%
거창군 440
20.0%
거창읍 109
 
4.9%
가조면 40
 
1.8%
마리면 36
 
1.6%
남상면 33
 
1.5%
웅양면 33
 
1.5%
신원면 32
 
1.5%
가북면 31
 
1.4%
주상면 28
 
1.3%
Other values (651) 981
44.5%
2023-12-11T09:37:54.620467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1763
19.3%
거 569
 
6.2%
창 561
 
6.1%
상 545
 
6.0%
남 510
 
5.6%
도 449
 
4.9%
군 442
 
4.8%
경 441
 
4.8%
길 384
 
4.2%
면 332
 
3.6%
Other values (199) 3139
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5849
64.0%
Space Separator 1763
 
19.3%
Decimal Number 1371
 
15.0%
Dash Punctuation 151
 
1.7%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 569
 
9.7%
창 561
 
9.6%
상 545
 
9.3%
남 510
 
8.7%
도 449
 
7.7%
군 442
 
7.6%
경 441
 
7.5%
길 384
 
6.6%
면 332
 
5.7%
읍 109
 
1.9%
Other values (186) 1507
25.8%
Decimal Number
ValueCountFrequency (%)
1 317
23.1%
2 220
16.0%
3 170
12.4%
4 145
10.6%
5 97
 
7.1%
7 93
 
6.8%
6 93
 
6.8%
8 83
 
6.1%
9 79
 
5.8%
0 74
 
5.4%
Space Separator
ValueCountFrequency (%)
1763
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 151
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5849
64.0%
Common 3286
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 569
 
9.7%
창 561
 
9.6%
상 545
 
9.3%
남 510
 
8.7%
도 449
 
7.7%
군 442
 
7.6%
경 441
 
7.5%
길 384
 
6.6%
면 332
 
5.7%
읍 109
 
1.9%
Other values (186) 1507
25.8%
Common
ValueCountFrequency (%)
1763
53.7%
1 317
 
9.6%
2 220
 
6.7%
3 170
 
5.2%
- 151
 
4.6%
4 145
 
4.4%
5 97
 
3.0%
7 93
 
2.8%
6 93
 
2.8%
8 83
 
2.5%
Other values (3) 154
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5849
64.0%
ASCII 3286
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1763
53.7%
1 317
 
9.6%
2 220
 
6.7%
3 170
 
5.2%
- 151
 
4.6%
4 145
 
4.4%
5 97
 
3.0%
7 93
 
2.8%
6 93
 
2.8%
8 83
 
2.5%
Other values (3) 154
 
4.7%
Hangul
ValueCountFrequency (%)
거 569
 
9.7%
창 561
 
9.6%
상 545
 
9.3%
남 510
 
8.7%
도 449
 
7.7%
군 442
 
7.6%
경 441
 
7.5%
길 384
 
6.6%
면 332
 
5.7%
읍 109
 
1.9%
Other values (186) 1507
25.8%

지번주소
Text

MISSING 

Distinct402
Distinct (%)93.3%
Missing9
Missing (%)2.0%
Memory size3.6 KiB
2023-12-11T09:37:54.933835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length24
Mean length21.62181
Min length19

Characters and Unicode

Total characters9319
Distinct characters125
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique375 ?
Unique (%)87.0%

Sample

1st row경상남도 거창군 거창읍 중앙리 55-8
2nd row경상남도 거창군 거창읍 상림리 155-70
3rd row경상남도 거창군 거창읍 대동리 844-22
4th row경상남도 거창군 거창읍 대동리 753
5th row경상남도 거창군 거창읍 대동리 158-2
ValueCountFrequency (%)
경상남도 431
19.9%
거창군 431
19.9%
거창읍 106
 
4.9%
가조면 40
 
1.8%
마리면 36
 
1.7%
남상면 33
 
1.5%
웅양면 33
 
1.5%
신원면 32
 
1.5%
가북면 31
 
1.4%
고제면 28
 
1.3%
Other values (493) 966
44.6%
2023-12-11T09:37:55.356548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1736
18.6%
거 541
 
5.8%
창 539
 
5.8%
상 529
 
5.7%
남 492
 
5.3%
리 467
 
5.0%
도 439
 
4.7%
군 436
 
4.7%
경 431
 
4.6%
면 325
 
3.5%
Other values (115) 3384
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5603
60.1%
Space Separator 1736
 
18.6%
Decimal Number 1691
 
18.1%
Dash Punctuation 288
 
3.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 541
9.7%
창 539
9.6%
상 529
9.4%
남 492
 
8.8%
리 467
 
8.3%
도 439
 
7.8%
군 436
 
7.8%
경 431
 
7.7%
면 325
 
5.8%
읍 106
 
1.9%
Other values (102) 1298
23.2%
Decimal Number
ValueCountFrequency (%)
1 311
18.4%
2 202
11.9%
3 179
10.6%
5 170
10.1%
4 163
9.6%
7 155
9.2%
6 145
8.6%
8 129
7.6%
0 127
7.5%
9 110
 
6.5%
Space Separator
ValueCountFrequency (%)
1736
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 288
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5603
60.1%
Common 3716
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 541
9.7%
창 539
9.6%
상 529
9.4%
남 492
 
8.8%
리 467
 
8.3%
도 439
 
7.8%
군 436
 
7.8%
경 431
 
7.7%
면 325
 
5.8%
읍 106
 
1.9%
Other values (102) 1298
23.2%
Common
ValueCountFrequency (%)
1736
46.7%
1 311
 
8.4%
- 288
 
7.8%
2 202
 
5.4%
3 179
 
4.8%
5 170
 
4.6%
4 163
 
4.4%
7 155
 
4.2%
6 145
 
3.9%
8 129
 
3.5%
Other values (3) 238
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5603
60.1%
ASCII 3716
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1736
46.7%
1 311
 
8.4%
- 288
 
7.8%
2 202
 
5.4%
3 179
 
4.8%
5 170
 
4.6%
4 163
 
4.4%
7 155
 
4.2%
6 145
 
3.9%
8 129
 
3.5%
Other values (3) 238
 
6.4%
Hangul
ValueCountFrequency (%)
거 541
9.7%
창 539
9.6%
상 529
9.4%
남 492
 
8.8%
리 467
 
8.3%
도 439
 
7.8%
군 436
 
7.8%
경 431
 
7.7%
면 325
 
5.8%
읍 106
 
1.9%
Other values (102) 1298
23.2%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct403
Distinct (%)93.7%
Missing10
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean35.718276
Minimum35.520291
Maximum35.902676
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T09:37:55.524391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.520291
5-th percentile35.574418
Q135.681649
median35.704884
Q335.770546
95-th percentile35.852601
Maximum35.902676
Range0.3823852
Interquartile range (IQR)0.088896875

Descriptive statistics

Standard deviation0.077572363
Coefficient of variation (CV)0.0021717836
Kurtosis-0.15409691
Mean35.718276
Median Absolute Deviation (MAD)0.04543055
Skewness-0.018932124
Sum15358.858
Variance0.0060174716
MonotonicityNot monotonic
2023-12-11T09:37:55.665893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.6845755 3
 
0.7%
35.6853333 3
 
0.7%
35.704195 2
 
0.5%
35.6878116 2
 
0.5%
35.7151552 2
 
0.5%
35.6906743 2
 
0.5%
35.6857728 2
 
0.5%
35.6816487 2
 
0.5%
35.7510229 2
 
0.5%
35.7039755 2
 
0.5%
Other values (393) 408
92.7%
(Missing) 10
 
2.3%
ValueCountFrequency (%)
35.5202911 1
0.2%
35.5255712 1
0.2%
35.5310955 1
0.2%
35.5345706 1
0.2%
35.5351024 1
0.2%
35.5415681 1
0.2%
35.5471921 1
0.2%
35.5492646 1
0.2%
35.5530185 1
0.2%
35.554817 1
0.2%
ValueCountFrequency (%)
35.9026763 1
0.2%
35.8998794 1
0.2%
35.8911399 1
0.2%
35.8838964 1
0.2%
35.8815237 1
0.2%
35.8773546 1
0.2%
35.8763281 1
0.2%
35.8762942 1
0.2%
35.8743383 1
0.2%
35.8734444 1
0.2%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct402
Distinct (%)93.5%
Missing10
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean127.91524
Minimum127.71921
Maximum128.07088
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T09:37:55.803727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.71921
5-th percentile127.8181
Q1127.87519
median127.91331
Q3127.94591
95-th percentile128.02155
Maximum128.07088
Range0.3516661
Interquartile range (IQR)0.070720475

Descriptive statistics

Standard deviation0.061287164
Coefficient of variation (CV)0.00047912322
Kurtosis0.026024991
Mean127.91524
Median Absolute Deviation (MAD)0.03636365
Skewness0.034253592
Sum55003.555
Variance0.0037561165
MonotonicityNot monotonic
2023-12-11T09:37:55.971262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.9119262 3
 
0.7%
127.9061367 3
 
0.7%
127.9092037 2
 
0.5%
127.9054647 2
 
0.5%
127.9091811 2
 
0.5%
127.9170544 2
 
0.5%
127.918491 2
 
0.5%
127.9283584 2
 
0.5%
127.9197216 2
 
0.5%
128.0375962 2
 
0.5%
Other values (392) 408
92.7%
(Missing) 10
 
2.3%
ValueCountFrequency (%)
127.7192105 1
0.2%
127.7426031 1
0.2%
127.7426046 1
0.2%
127.7588673 1
0.2%
127.7606918 1
0.2%
127.7758122 1
0.2%
127.7780508 1
0.2%
127.7854284 1
0.2%
127.7947199 1
0.2%
127.8065915 1
0.2%
ValueCountFrequency (%)
128.0708766 1
0.2%
128.0652613 1
0.2%
128.0618088 1
0.2%
128.0530759 1
0.2%
128.0482168 1
0.2%
128.0464975 1
0.2%
128.0389494 1
0.2%
128.0377615 1
0.2%
128.0375962 2
0.5%
128.0348665 1
0.2%

연락처
Text

MISSING 

Distinct242
Distinct (%)97.2%
Missing191
Missing (%)43.4%
Memory size3.6 KiB
2023-12-11T09:37:56.289497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2988
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

Unique235 ?
Unique (%)94.4%

Sample

1st row055-942-8063
2nd row055-944-3151
3rd row055-944-2672
4th row055-943-5228
5th row055-942-3356
ValueCountFrequency (%)
055-944-9423 2
 
0.8%
055-942-3580 2
 
0.8%
055-944-3597 2
 
0.8%
055-942-3667 2
 
0.8%
055-943-5744 2
 
0.8%
055-944-0082 2
 
0.8%
055-943-0569 2
 
0.8%
055-944-3929 1
 
0.4%
055-945-3357 1
 
0.4%
055-944-3610 1
 
0.4%
Other values (232) 232
93.2%
2023-12-11T09:37:56.746685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 619
20.7%
- 498
16.7%
4 397
13.3%
0 380
12.7%
9 338
11.3%
2 188
 
6.3%
3 174
 
5.8%
1 108
 
3.6%
6 104
 
3.5%
8 101
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2490
83.3%
Dash Punctuation 498
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 619
24.9%
4 397
15.9%
0 380
15.3%
9 338
13.6%
2 188
 
7.6%
3 174
 
7.0%
1 108
 
4.3%
6 104
 
4.2%
8 101
 
4.1%
7 81
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 498
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2988
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 619
20.7%
- 498
16.7%
4 397
13.3%
0 380
12.7%
9 338
11.3%
2 188
 
6.3%
3 174
 
5.8%
1 108
 
3.6%
6 104
 
3.5%
8 101
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2988
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 619
20.7%
- 498
16.7%
4 397
13.3%
0 380
12.7%
9 338
11.3%
2 188
 
6.3%
3 174
 
5.8%
1 108
 
3.6%
6 104
 
3.5%
8 101
 
3.4%

비고
Categorical

IMBALANCE 

Distinct9
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
마을회관겸용
218 
<NA>
206 
분회
 
8
남, 갑계성격
 
2
마을(이용가능)
 
2
Other values (4)
 
4

Length

Max length11
Median length8
Mean length4.9931818
Min length1

Unique

Unique4 ?
Unique (%)0.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
마을회관겸용 218
49.5%
<NA> 206
46.8%
분회 8
 
1.8%
남, 갑계성격 2
 
0.5%
마을(이용가능) 2
 
0.5%
3층, 여, 갑계성격 1
 
0.2%
이용가능 1
 
0.2%
× 1
 
0.2%
면분회 1
 
0.2%

Length

2023-12-11T09:37:57.220549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:37:57.346845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마을회관겸용 218
49.1%
na 206
46.4%
분회 8
 
1.8%
갑계성격 3
 
0.7%
남 2
 
0.5%
마을(이용가능 2
 
0.5%
3층 1
 
0.2%
여 1
 
0.2%
이용가능 1
 
0.2%
× 1
 
0.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum2022-04-28 00:00:00
Maximum2022-04-28 00:00:00
2023-12-11T09:37:57.488791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:57.601057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T09:37:50.986154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:50.428234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:50.692060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:51.069015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:50.504883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:50.774559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:51.182593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:50.605487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:50.866993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:37:57.679777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면위도경도비고
연번1.0000.9410.8500.8700.696
읍면0.9411.0000.8560.8420.655
위도0.8500.8561.0000.5500.438
경도0.8700.8420.5501.0000.000
비고0.6960.6550.4380.0001.000
2023-12-11T09:37:57.769679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면비고
읍면1.0000.342
비고0.3421.000
2023-12-11T09:37:57.852000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도읍면비고
연번1.000-0.1060.3840.7800.424
위도-0.1061.000-0.1560.5840.225
경도0.384-0.1561.0000.5610.000
읍면0.7800.5840.5611.0000.342
비고0.4240.2250.0000.3421.000

Missing values

2023-12-11T09:37:51.307711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:37:51.474643image/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.
2023-12-11T09:37:51.607330image/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

연번읍면마을명경로당명도로명주소지번주소위도경도연락처비고데이터기준일자
01거창하동77경로당경상남도 거창군 거창읍 아림로2길 69경상남도 거창군 거창읍 중앙리 55-835.688867127.91335<NA><NA>2022-04-28
12거창상동강변경로당경상남도 거창군 거창읍 상동9길 14경상남도 거창군 거창읍 상림리 155-7035.684576127.906137<NA><NA>2022-04-28
23거창강양강양경로당경상남도 거창군 거창읍 중앙로1길 38-6경상남도 거창군 거창읍 대동리 844-2235.688173127.914751<NA><NA>2022-04-28
34거창강양강양할머니경로당경상남도 거창군 거창읍 중앙로1길 88-6경상남도 거창군 거창읍 대동리 75335.689855127.916768055-942-8063<NA>2022-04-28
45거창개봉개봉경로당경상남도 거창군 거창읍 거열로 234-8경상남도 거창군 거창읍 대동리 158-235.692622127.918464<NA><NA>2022-04-28
56거창개봉개봉할머니경로당경상남도 거창군 거창읍 거열로 234-8경상남도 거창군 거창읍 대동리 158-235.692622127.918464055-944-3151<NA>2022-04-28
67거창개화개화경로당경상남도 거창군 거창읍 개화1길 31경상남도 거창군 거창읍 가지리 579-435.69834127.905567<NA><NA>2022-04-28
78거창개화개화할머니경로당경상남도 거창군 거창읍 개화1길 31경상남도 거창군 거창읍 가지리 579-435.69834127.905567<NA><NA>2022-04-28
89거창하동거송경로당경상남도 거창군 거창읍 시장길 54경상남도 거창군 거창읍 중앙리 152-1435.686185127.913703055-944-2672<NA>2022-04-28
910거창동동거용경로당경상남도 거창군 거창읍 중앙로1길 38-6경상남도 거창군 거창읍 대동리 844-2235.688173127.914751<NA>남, 갑계성격2022-04-28
연번읍면마을명경로당명도로명주소지번주소위도경도연락처비고데이터기준일자
430431가북회남회남경로당경상남도 거창군 가북면 보해길 963-3경상남도 거창군 가북면 해평리 176035.793558127.971613055-944-0808마을회관겸용2022-04-28
431432가북다전다전경로당경상남도 거창군 가북면 다전길 3경상남도 거창군 가북면 중촌리 2232-135.806081127.971369<NA><NA>2022-04-28
432433가북중촌중촌경로당경상남도 거창군 가북면 동촌길 116-3경상남도 거창군 가북면 중촌리 194335.807816127.973414055-945-1842마을회관겸용2022-04-28
433434가북산수산수경로당경상남도 거창군 가북면 산수마길 45-8경상남도 거창군 가북면 중촌리 238335.81525127.973082055-945-0375<NA>2022-04-28
434435가북심방심방경로당경상남도 거창군 가북면 심방길 36-9경상남도 거창군 가북면 중촌리 240235.826753127.967611055-944-2155마을회관겸용2022-04-28
435436가북수재수재경로당경상남도 거창군 가북면 수재길 242-7경상남도 거창군 가북면 중촌리 46735.83331127.972226<NA><NA>2022-04-28
436437가북용산용산경로당경상남도 거창군 가북면 가북로 310경상남도 거창군 가북면 용산리 120-535.739595127.991621<NA>마을회관겸용2022-04-28
437438가북용산용산할머니경로당경상남도 거창군 가북면 가북로 310경상남도 거창군 가북면 용산리 120-535.739595127.991621055-942-2398<NA>2022-04-28
438439가북율리율리경로당경상남도 거창군 가북면 율리길 328경상남도 거창군 가북면 용산리 513-235.724883127.988849<NA>마을회관겸용2022-04-28
439440가북감월상감월경로당경상남도 거창군 가북면 감월길 872경상남도 거창군 가북면 우혜리 105-235.773858128.033066<NA>마을회관겸용2022-04-28