Overview

Dataset statistics

Number of variables11
Number of observations437
Missing cells188
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.0 KiB
Average record size in memory91.3 B

Variable types

Numeric3
Categorical3
Text5

Dataset

Description경상남도 거창군 경로당 및 마을회관 현황 데이터로 연번, 읍면, 마을명, 경로당명, 주소, 연락처 등의 항목을 제공합니다.
Author경상남도 거창군
URLhttps://www.data.go.kr/data/15044915/fileData.do

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 (60.4%)Imbalance
연락처 has 188 (43.0%) missing valuesMissing
연번 has unique valuesUnique
경로당명 has unique valuesUnique

Reproduction

Analysis started2024-04-29 22:30:49.284497
Analysis finished2024-04-29 22:30:52.297114
Duration3.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct437
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219
Minimum1
Maximum437
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T07:30:52.364108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.8
Q1110
median219
Q3328
95-th percentile415.2
Maximum437
Range436
Interquartile range (IQR)218

Descriptive statistics

Standard deviation126.29529
Coefficient of variation (CV)0.57669082
Kurtosis-1.2
Mean219
Median Absolute Deviation (MAD)109
Skewness0
Sum95703
Variance15950.5
MonotonicityStrictly increasing
2024-04-30T07:30:52.483607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
289 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%
294 1
 
0.2%
293 1
 
0.2%
Other values (427) 427
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 (%)
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%
430 1
0.2%
429 1
0.2%
428 1
0.2%

읍면
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
거창
107 
가조
40 
마리
36 
웅양
33 
남상
33 
Other values (7)
188 

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 107
24.5%
가조 40
 
9.2%
마리 36
 
8.2%
웅양 33
 
7.6%
남상 33
 
7.6%
신원 32
 
7.3%
가북 31
 
7.1%
주상 28
 
6.4%
고제 28
 
6.4%
위천 25
 
5.7%
Other values (2) 44
10.1%

Length

2024-04-30T07:30:52.586759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
거창 107
24.5%
가조 40
 
9.2%
마리 36
 
8.2%
웅양 33
 
7.6%
남상 33
 
7.6%
신원 32
 
7.3%
가북 31
 
7.1%
주상 28
 
6.4%
고제 28
 
6.4%
위천 25
 
5.7%
Other values (2) 44
10.1%

마을명
Text

Distinct256
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-04-30T07:30:52.893717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.1121281
Min length2

Characters and Unicode

Total characters923
Distinct characters169
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)34.8%

Sample

1st row하동
2nd row갈지
3rd row갈지
4th row상동
5th row강양
ValueCountFrequency (%)
하동 10
 
2.3%
상동 10
 
2.3%
동동 9
 
2.1%
신기 8
 
1.8%
김천 6
 
1.4%
강양 6
 
1.4%
중동 6
 
1.4%
장팔 5
 
1.1%
도평 5
 
1.1%
오산 4
 
0.9%
Other values (245) 368
84.2%
2024-04-30T07:30:53.391032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 96
 
10.4%
산 40
 
4.3%
원 24
 
2.6%
상 23
 
2.5%
촌 23
 
2.5%
중 19
 
2.1%
기 18
 
2.0%
평 18
 
2.0%
곡 17
 
1.8%
정 16
 
1.7%
Other values (159) 629
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 914
99.0%
Decimal Number 8
 
0.9%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 96
 
10.5%
산 40
 
4.4%
원 24
 
2.6%
상 23
 
2.5%
촌 23
 
2.5%
중 19
 
2.1%
기 18
 
2.0%
평 18
 
2.0%
곡 17
 
1.9%
정 16
 
1.8%
Other values (156) 620
67.8%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 914
99.0%
Common 9
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 96
 
10.5%
산 40
 
4.4%
원 24
 
2.6%
상 23
 
2.5%
촌 23
 
2.5%
중 19
 
2.1%
기 18
 
2.0%
평 18
 
2.0%
곡 17
 
1.9%
정 16
 
1.8%
Other values (156) 620
67.8%
Common
ValueCountFrequency (%)
2 4
44.4%
1 4
44.4%
1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 914
99.0%
ASCII 9
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 96
 
10.5%
산 40
 
4.4%
원 24
 
2.6%
상 23
 
2.5%
촌 23
 
2.5%
중 19
 
2.1%
기 18
 
2.0%
평 18
 
2.0%
곡 17
 
1.9%
정 16
 
1.8%
Other values (156) 620
67.8%
ASCII
ValueCountFrequency (%)
2 4
44.4%
1 4
44.4%
1
 
11.1%

경로당명
Text

UNIQUE 

Distinct437
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-04-30T07:30:53.633365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length5
Mean length6.3135011
Min length5

Characters and Unicode

Total characters2759
Distinct characters218
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

Unique437 ?
Unique (%)100.0%

Sample

1st row77경로당
2nd row갈지경로당
3rd row갈지할머니경로당
4th row강변경로당
5th row강양경로당
ValueCountFrequency (%)
77경로당 1
 
0.2%
풍계경로당 1
 
0.2%
외춘경로당 1
 
0.2%
외등경로당 1
 
0.2%
오계경로당 1
 
0.2%
신기경로당(남상면 1
 
0.2%
송변경로당 1
 
0.2%
성지경로당 1
 
0.2%
상매경로당 1
 
0.2%
묵동경로당 1
 
0.2%
Other values (427) 427
97.7%
2024-04-30T07:30:53.969224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 449
16.3%
경 439
 
15.9%
로 438
 
15.9%
동 62
 
2.2%
) 53
 
1.9%
( 53
 
1.9%
면 47
 
1.7%
할 39
 
1.4%
상 37
 
1.3%
산 35
 
1.3%
Other values (208) 1107
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2636
95.5%
Close Punctuation 53
 
1.9%
Open Punctuation 53
 
1.9%
Decimal Number 17
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 449
17.0%
경 439
16.7%
로 438
16.6%
동 62
 
2.4%
면 47
 
1.8%
할 39
 
1.5%
상 37
 
1.4%
산 35
 
1.3%
머 33
 
1.3%
니 33
 
1.3%
Other values (202) 1024
38.8%
Decimal Number
ValueCountFrequency (%)
2 8
47.1%
1 6
35.3%
7 2
 
11.8%
3 1
 
5.9%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2636
95.5%
Common 123
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 449
17.0%
경 439
16.7%
로 438
16.6%
동 62
 
2.4%
면 47
 
1.8%
할 39
 
1.5%
상 37
 
1.4%
산 35
 
1.3%
머 33
 
1.3%
니 33
 
1.3%
Other values (202) 1024
38.8%
Common
ValueCountFrequency (%)
) 53
43.1%
( 53
43.1%
2 8
 
6.5%
1 6
 
4.9%
7 2
 
1.6%
3 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2636
95.5%
ASCII 123
 
4.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 449
17.0%
경 439
16.7%
로 438
16.6%
동 62
 
2.4%
면 47
 
1.8%
할 39
 
1.5%
상 37
 
1.4%
산 35
 
1.3%
머 33
 
1.3%
니 33
 
1.3%
Other values (202) 1024
38.8%
ASCII
ValueCountFrequency (%)
) 53
43.1%
( 53
43.1%
2 8
 
6.5%
1 6
 
4.9%
7 2
 
1.6%
3 1
 
0.8%

도로명주소
Text

Distinct409
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-04-30T07:30:54.286734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length20.707094
Min length18

Characters and Unicode

Total characters9049
Distinct characters203
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

Unique383 ?
Unique (%)87.6%

Sample

1st row경상남도 거창군 거창읍 아림로2길 69
2nd row경상남도 거창군 거창읍 갈지길 62
3rd row경상남도 거창군 거창읍 갈지길 62
4th row경상남도 거창군 거창읍 상동9길 14
5th row경상남도 거창군 거창읍 중앙로1길 38-6
ValueCountFrequency (%)
경상남도 437
20.0%
거창군 437
20.0%
거창읍 107
 
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%
고제면 28
 
1.3%
Other values (645) 971
44.4%
2024-04-30T07:30:54.738714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1748
19.3%
거 564
 
6.2%
창 557
 
6.2%
상 541
 
6.0%
남 507
 
5.6%
도 446
 
4.9%
군 439
 
4.9%
경 438
 
4.8%
길 382
 
4.2%
면 331
 
3.7%
Other values (193) 3096
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5795
64.0%
Space Separator 1748
 
19.3%
Decimal Number 1357
 
15.0%
Dash Punctuation 149
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 564
 
9.7%
창 557
 
9.6%
상 541
 
9.3%
남 507
 
8.7%
도 446
 
7.7%
군 439
 
7.6%
경 438
 
7.6%
길 382
 
6.6%
면 331
 
5.7%
읍 107
 
1.8%
Other values (181) 1483
25.6%
Decimal Number
ValueCountFrequency (%)
1 317
23.4%
2 217
16.0%
3 170
12.5%
4 141
10.4%
5 95
 
7.0%
6 92
 
6.8%
7 91
 
6.7%
8 82
 
6.0%
9 79
 
5.8%
0 73
 
5.4%
Space Separator
ValueCountFrequency (%)
1748
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5795
64.0%
Common 3254
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 564
 
9.7%
창 557
 
9.6%
상 541
 
9.3%
남 507
 
8.7%
도 446
 
7.7%
군 439
 
7.6%
경 438
 
7.6%
길 382
 
6.6%
면 331
 
5.7%
읍 107
 
1.8%
Other values (181) 1483
25.6%
Common
ValueCountFrequency (%)
1748
53.7%
1 317
 
9.7%
2 217
 
6.7%
3 170
 
5.2%
- 149
 
4.6%
4 141
 
4.3%
5 95
 
2.9%
6 92
 
2.8%
7 91
 
2.8%
8 82
 
2.5%
Other values (2) 152
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5795
64.0%
ASCII 3254
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1748
53.7%
1 317
 
9.7%
2 217
 
6.7%
3 170
 
5.2%
- 149
 
4.6%
4 141
 
4.3%
5 95
 
2.9%
6 92
 
2.8%
7 91
 
2.8%
8 82
 
2.5%
Other values (2) 152
 
4.7%
Hangul
ValueCountFrequency (%)
거 564
 
9.7%
창 557
 
9.6%
상 541
 
9.3%
남 507
 
8.7%
도 446
 
7.7%
군 439
 
7.6%
경 438
 
7.6%
길 382
 
6.6%
면 331
 
5.7%
읍 107
 
1.8%
Other values (181) 1483
25.6%

지번주소
Text

Distinct407
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-04-30T07:30:54.969988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length21.606407
Min length19

Characters and Unicode

Total characters9442
Distinct characters120
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

Unique379 ?
Unique (%)86.7%

Sample

1st row경상남도 거창군 거창읍 중앙리 55-8
2nd row경상남도 거창군 거창읍 가지리 996-2
3rd row경상남도 거창군 거창읍 가지리 996-2
4th row경상남도 거창군 거창읍 상림리 155-70
5th row경상남도 거창군 거창읍 대동리 844-22
ValueCountFrequency (%)
경상남도 437
19.9%
거창군 437
19.9%
거창읍 107
 
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 30
 
1.4%
Other values (496) 981
44.7%
2024-04-30T07:30:55.307025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1760
18.6%
거 548
 
5.8%
창 546
 
5.8%
상 541
 
5.7%
남 499
 
5.3%
리 473
 
5.0%
도 448
 
4.7%
군 442
 
4.7%
경 437
 
4.6%
면 332
 
3.5%
Other values (110) 3416
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5679
60.1%
Space Separator 1760
 
18.6%
Decimal Number 1710
 
18.1%
Dash Punctuation 293
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 548
9.6%
창 546
9.6%
상 541
9.5%
남 499
 
8.8%
리 473
 
8.3%
도 448
 
7.9%
군 442
 
7.8%
경 437
 
7.7%
면 332
 
5.8%
읍 107
 
1.9%
Other values (98) 1306
23.0%
Decimal Number
ValueCountFrequency (%)
1 314
18.4%
2 201
11.8%
3 182
10.6%
5 172
10.1%
4 162
9.5%
7 159
9.3%
6 148
8.7%
8 133
7.8%
0 125
 
7.3%
9 114
 
6.7%
Space Separator
ValueCountFrequency (%)
1760
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 293
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5679
60.1%
Common 3763
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 548
9.6%
창 546
9.6%
상 541
9.5%
남 499
 
8.8%
리 473
 
8.3%
도 448
 
7.9%
군 442
 
7.8%
경 437
 
7.7%
면 332
 
5.8%
읍 107
 
1.9%
Other values (98) 1306
23.0%
Common
ValueCountFrequency (%)
1760
46.8%
1 314
 
8.3%
- 293
 
7.8%
2 201
 
5.3%
3 182
 
4.8%
5 172
 
4.6%
4 162
 
4.3%
7 159
 
4.2%
6 148
 
3.9%
8 133
 
3.5%
Other values (2) 239
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5679
60.1%
ASCII 3763
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1760
46.8%
1 314
 
8.3%
- 293
 
7.8%
2 201
 
5.3%
3 182
 
4.8%
5 172
 
4.6%
4 162
 
4.3%
7 159
 
4.2%
6 148
 
3.9%
8 133
 
3.5%
Other values (2) 239
 
6.4%
Hangul
ValueCountFrequency (%)
거 548
9.6%
창 546
9.6%
상 541
9.5%
남 499
 
8.8%
리 473
 
8.3%
도 448
 
7.9%
군 442
 
7.8%
경 437
 
7.7%
면 332
 
5.8%
읍 107
 
1.9%
Other values (98) 1306
23.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct409
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.71845
Minimum35.520291
Maximum35.902676
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T07:30:55.444094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.520291
5-th percentile35.575353
Q135.681649
median35.704891
Q335.770116
95-th percentile35.852299
Maximum35.902676
Range0.3823852
Interquartile range (IQR)0.08846725

Descriptive statistics

Standard deviation0.077088623
Coefficient of variation (CV)0.0021582298
Kurtosis-0.1275681
Mean35.71845
Median Absolute Deviation (MAD)0.04562812
Skewness-0.024534511
Sum15608.963
Variance0.0059426558
MonotonicityNot monotonic
2024-04-30T07:30:55.568792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.68533335 3
 
0.7%
35.6845756 3
 
0.7%
35.71534534 2
 
0.5%
35.67546242 2
 
0.5%
35.68948965 2
 
0.5%
35.68164872 2
 
0.5%
35.68335124 2
 
0.5%
35.68781168 2
 
0.5%
35.70419506 2
 
0.5%
35.68075438 2
 
0.5%
Other values (399) 415
95.0%
ValueCountFrequency (%)
35.52029112 1
0.2%
35.52557125 1
0.2%
35.53109555 1
0.2%
35.53457065 1
0.2%
35.53510242 1
0.2%
35.54156811 1
0.2%
35.54719213 1
0.2%
35.54926466 1
0.2%
35.55301853 1
0.2%
35.55481705 1
0.2%
ValueCountFrequency (%)
35.90267632 1
0.2%
35.89987943 1
0.2%
35.89113997 1
0.2%
35.88389643 1
0.2%
35.88152375 1
0.2%
35.87735467 1
0.2%
35.8763281 1
0.2%
35.87629429 1
0.2%
35.87433837 1
0.2%
35.87344448 1
0.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct408
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.91543
Minimum127.71921
Maximum128.07088
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T07:30:55.683357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.71921
5-th percentile127.8184
Q1127.87668
median127.91378
Q3127.94549
95-th percentile128.02151
Maximum128.07088
Range0.3516662
Interquartile range (IQR)0.0688081

Descriptive statistics

Standard deviation0.060691443
Coefficient of variation (CV)0.0004744654
Kurtosis0.087491451
Mean127.91543
Median Absolute Deviation (MAD)0.0344889
Skewness0.031433386
Sum55899.041
Variance0.0036834513
MonotonicityNot monotonic
2024-04-30T07:30:55.804778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.9119262 3
 
0.7%
127.9061368 3
 
0.7%
127.9054648 2
 
0.5%
127.9077794 2
 
0.5%
127.9303425 2
 
0.5%
127.9283585 2
 
0.5%
127.9238715 2
 
0.5%
127.9183179 2
 
0.5%
127.9197217 2
 
0.5%
127.9026876 2
 
0.5%
Other values (398) 415
95.0%
ValueCountFrequency (%)
127.7192105 1
0.2%
127.7426031 1
0.2%
127.7426047 1
0.2%
127.7588674 1
0.2%
127.7606918 1
0.2%
127.7758123 1
0.2%
127.7780508 1
0.2%
127.7854285 1
0.2%
127.7947199 1
0.2%
127.8065915 1
0.2%
ValueCountFrequency (%)
128.0708767 1
0.2%
128.0652613 1
0.2%
128.0618088 1
0.2%
128.053076 1
0.2%
128.0482169 1
0.2%
128.0464976 1
0.2%
128.0389494 1
0.2%
128.0377616 1
0.2%
128.0375963 2
0.5%
128.0348666 1
0.2%

연락처
Text

MISSING 

Distinct242
Distinct (%)97.2%
Missing188
Missing (%)43.0%
Memory size3.5 KiB
2024-04-30T07:30:56.015064image/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 row055-944-3159
2nd row055-942-8063
3rd row055-944-3151
4th row055-944-2672
5th row055-943-5228
ValueCountFrequency (%)
055-942-3667 2
 
0.8%
055-943-5744 2
 
0.8%
055-944-9423 2
 
0.8%
055-944-0082 2
 
0.8%
055-942-3580 2
 
0.8%
055-943-0569 2
 
0.8%
055-944-3597 2
 
0.8%
055-944-5369 1
 
0.4%
055-944-2199 1
 
0.4%
055-942-6132 1
 
0.4%
Other values (232) 232
93.2%
2024-04-30T07:30:56.317240image/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 (%)2.1%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
마을회관겸용
218 
<NA>
204 
분회
 
8
마을(이용가능)
 
2
남, 갑계성격
 
1
Other values (4)
 
4

Length

Max length11
Median length8
Mean length4.993135
Min length1

Unique

Unique5 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
마을회관겸용 218
49.9%
<NA> 204
46.7%
분회 8
 
1.8%
마을(이용가능) 2
 
0.5%
남, 갑계성격 1
 
0.2%
3층, 여, 갑계성격 1
 
0.2%
이용가능 1
 
0.2%
면분회 1
 
0.2%
× 1
 
0.2%

Length

2024-04-30T07:30:56.429017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:30:56.529492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마을회관겸용 218
49.5%
na 204
46.4%
분회 8
 
1.8%
마을(이용가능 2
 
0.5%
갑계성격 2
 
0.5%
남 1
 
0.2%
3층 1
 
0.2%
여 1
 
0.2%
이용가능 1
 
0.2%
면분회 1
 
0.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-04-04
437 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-04-04
2nd row2024-04-04
3rd row2024-04-04
4th row2024-04-04
5th row2024-04-04

Common Values

ValueCountFrequency (%)
2024-04-04 437
100.0%

Length

2024-04-30T07:30:56.656954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:30:56.737685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-04-04 437
100.0%

Interactions

2024-04-30T07:30:51.831671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:30:51.330681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:30:51.596042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:30:51.908259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:30:51.449978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:30:51.669996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:30:51.999074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:30:51.526040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:30:51.749904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:30:56.796220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면위도경도비고
연번1.0000.9420.8540.8640.711
읍면0.9421.0000.8560.8420.648
위도0.8540.8561.0000.5390.394
경도0.8640.8420.5391.0000.000
비고0.7110.6480.3940.0001.000
2024-04-30T07:30:57.069057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고읍면
비고1.0000.336
읍면0.3361.000
2024-04-30T07:30:57.138636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도읍면비고
연번1.000-0.1000.3750.7810.439
위도-0.1001.000-0.1540.5840.199
경도0.375-0.1541.0000.5600.000
읍면0.7810.5840.5601.0000.336
비고0.4390.1990.0000.3361.000

Missing values

2024-04-30T07:30:52.112653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:30:52.246163image/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

연번읍면마을명경로당명도로명주소지번주소위도경도연락처비고데이터기준일자
01거창하동77경로당경상남도 거창군 거창읍 아림로2길 69경상남도 거창군 거창읍 중앙리 55-835.688867127.91335<NA><NA>2024-04-04
12거창갈지갈지경로당경상남도 거창군 거창읍 갈지길 62경상남도 거창군 거창읍 가지리 996-235.703333127.897711<NA><NA>2024-04-04
23거창갈지갈지할머니경로당경상남도 거창군 거창읍 갈지길 62경상남도 거창군 거창읍 가지리 996-235.703333127.897711055-944-3159<NA>2024-04-04
34거창상동강변경로당경상남도 거창군 거창읍 상동9길 14경상남도 거창군 거창읍 상림리 155-7035.684576127.906137<NA><NA>2024-04-04
45거창강양강양경로당경상남도 거창군 거창읍 중앙로1길 38-6경상남도 거창군 거창읍 대동리 844-2235.688174127.914751<NA><NA>2024-04-04
56거창강양강양할머니경로당경상남도 거창군 거창읍 중앙로1길 88-6경상남도 거창군 거창읍 대동리 75335.689855127.916768055-942-8063<NA>2024-04-04
67거창개봉개봉경로당경상남도 거창군 거창읍 거열로 234-8경상남도 거창군 거창읍 대동리 158-235.692622127.918464<NA><NA>2024-04-04
78거창개봉개봉할머니경로당경상남도 거창군 거창읍 거열로 234-8경상남도 거창군 거창읍 대동리 158-235.692622127.918464055-944-3151<NA>2024-04-04
89거창개화개화경로당(거창읍)경상남도 거창군 거창읍 개화1길 31경상남도 거창군 거창읍 가지리 579-435.69834127.905567<NA><NA>2024-04-04
910거창개화개화할머니경로당경상남도 거창군 거창읍 개화1길 31경상남도 거창군 거창읍 가지리 579-435.69834127.905567<NA><NA>2024-04-04
연번읍면마을명경로당명도로명주소지번주소위도경도연락처비고데이터기준일자
427428가북용암용암경로당경상남도 거창군 가북면 용암1길 25-4경상남도 거창군 가북면 용암리 2171-335.815461128.048217055-944-2407마을회관겸용2024-04-04
428429가북우혜우혜경로당경상남도 거창군 가북면 우혜1길 13경상남도 거창군 가북면 우혜리 207435.763271127.993199055-943-6302마을회관겸용2024-04-04
429430가북윤오동윤오동경로당경상남도 거창군 가북면 몽석1길 122경상남도 거창군 가북면 몽석리 194735.789444128.013431<NA><NA>2024-04-04
430431가북율리율리경로당경상남도 거창군 가북면 율리길 328경상남도 거창군 가북면 용산리 513-235.724883127.988849<NA>마을회관겸용2024-04-04
431432가북중촌중촌경로당(가북면)경상남도 거창군 가북면 동촌길 116-3경상남도 거창군 가북면 중촌리 194335.807816127.973415055-945-1842마을회관겸용2024-04-04
432433가북추동추동경로당경상남도 거창군 가북면 추동길 69경상남도 거창군 가북면 해평리 산 180-635.776408127.980326055-943-7966마을회관겸용2024-04-04
433434가북하감월하감월경로당경상남도 거창군 가북면 감월길 261-33경상남도 거창군 가북면 우혜리 2072-235.763375128.00746055-942-2059<NA>2024-04-04
434435가북호암호암경로당경상남도 거창군 가북면 호암길 108경상남도 거창군 가북면 박암리 1007-135.789367127.996946<NA><NA>2024-04-04
435436가북홍감홍감경로당경상남도 거창군 가북면 홍감길 111경상남도 거창군 가북면 용암리 1487-135.811746128.038949<NA><NA>2024-04-04
436437가북회남회남경로당경상남도 거창군 가북면 보해길 963-3경상남도 거창군 가북면 해평리 176035.793558127.971613055-944-0808마을회관겸용2024-04-04