Overview

Dataset statistics

Number of variables11
Number of observations345
Missing cells868
Missing cells (%)22.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.8 KiB
Average record size in memory91.4 B

Variable types

Numeric1
Categorical1
Text5
Unsupported2
DateTime2

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 읍면동High correlation
읍면동 is highly overall correlated with 연번High correlation
지번주소 has 59 (17.1%) missing valuesMissing
위도 has 345 (100.0%) missing valuesMissing
경도 has 345 (100.0%) missing valuesMissing
전화번호 has 25 (7.2%) missing valuesMissing
등 록 일 has 77 (22.3%) missing valuesMissing
시설면적 has 17 (4.9%) missing valuesMissing
연번 has unique valuesUnique
위도 is an unsupported type, check if it needs cleaning or further analysisUnsupported
경도 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-09 23:14:51.096575
Analysis finished2024-01-09 23:14:51.974878
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct345
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173
Minimum1
Maximum345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-10T08:14:52.037544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.2
Q187
median173
Q3259
95-th percentile327.8
Maximum345
Range344
Interquartile range (IQR)172

Descriptive statistics

Standard deviation99.737155
Coefficient of variation (CV)0.57651534
Kurtosis-1.2
Mean173
Median Absolute Deviation (MAD)86
Skewness0
Sum59685
Variance9947.5
MonotonicityStrictly increasing
2024-01-10T08:14:52.160555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
228 1
 
0.3%
236 1
 
0.3%
235 1
 
0.3%
234 1
 
0.3%
233 1
 
0.3%
232 1
 
0.3%
231 1
 
0.3%
230 1
 
0.3%
229 1
 
0.3%
Other values (335) 335
97.1%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
345 1
0.3%
344 1
0.3%
343 1
0.3%
342 1
0.3%
341 1
0.3%
340 1
0.3%
339 1
0.3%
338 1
0.3%
337 1
0.3%
336 1
0.3%

읍면동
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
합덕읍
38 
신평면
31 
당진2동
29 
송악(서)
26 
고대면
24 
Other values (11)
197 

Length

Max length5
Median length3
Mean length3.4956522
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
합덕읍 38
11.0%
신평면 31
 
9.0%
당진2동 29
 
8.4%
송악(서) 26
 
7.5%
고대면 24
 
7.0%
우강면 24
 
7.0%
석문면 23
 
6.7%
당진1동 22
 
6.4%
송산면 21
 
6.1%
순성면 20
 
5.8%
Other values (6) 87
25.2%

Length

2024-01-10T08:14:52.283768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
합덕읍 38
11.0%
신평면 31
 
9.0%
당진2동 29
 
8.4%
송악(서 26
 
7.5%
우강면 25
 
7.2%
고대면 24
 
7.0%
석문면 23
 
6.7%
당진1동 22
 
6.4%
송산면 21
 
6.1%
순성면 20
 
5.8%
Other values (5) 86
24.9%

경로당명
Text

Distinct343
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-01-10T08:14:52.531726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length4.9855072
Min length2

Characters and Unicode

Total characters1720
Distinct characters212
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

Unique341 ?
Unique (%)98.8%

Sample

1st row합덕읍분회
2nd row도곡리
3rd row소소리
4th row회태리
5th row창정리
ValueCountFrequency (%)
신규 4
 
1.1%
신촌리 2
 
0.6%
행정2통 2
 
0.6%
금천2리 2
 
0.6%
상오리 2
 
0.6%
세안아파트 2
 
0.6%
주공그린빌 1
 
0.3%
새마지 1
 
0.3%
내건너 1
 
0.3%
신세대아파트 1
 
0.3%
Other values (342) 342
95.0%
2024-01-10T08:14:52.937780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 241
 
14.0%
1 88
 
5.1%
2 72
 
4.2%
아 49
 
2.8%
통 46
 
2.7%
트 45
 
2.6%
파 44
 
2.6%
) 39
 
2.3%
( 39
 
2.3%
신 37
 
2.2%
Other values (202) 1020
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1407
81.8%
Decimal Number 208
 
12.1%
Close Punctuation 39
 
2.3%
Open Punctuation 39
 
2.3%
Space Separator 16
 
0.9%
Uppercase Letter 9
 
0.5%
Lowercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 241
 
17.1%
아 49
 
3.5%
통 46
 
3.3%
트 45
 
3.2%
파 44
 
3.1%
신 37
 
2.6%
산 30
 
2.1%
당 30
 
2.1%
성 26
 
1.8%
대 25
 
1.8%
Other values (183) 834
59.3%
Decimal Number
ValueCountFrequency (%)
1 88
42.3%
2 72
34.6%
3 18
 
8.7%
7 7
 
3.4%
6 7
 
3.4%
8 5
 
2.4%
4 4
 
1.9%
5 3
 
1.4%
9 3
 
1.4%
0 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
A 4
44.4%
L 2
22.2%
H 2
22.2%
C 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1407
81.8%
Common 303
 
17.6%
Latin 10
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 241
 
17.1%
아 49
 
3.5%
통 46
 
3.3%
트 45
 
3.2%
파 44
 
3.1%
신 37
 
2.6%
산 30
 
2.1%
당 30
 
2.1%
성 26
 
1.8%
대 25
 
1.8%
Other values (183) 834
59.3%
Common
ValueCountFrequency (%)
1 88
29.0%
2 72
23.8%
) 39
12.9%
( 39
12.9%
3 18
 
5.9%
16
 
5.3%
7 7
 
2.3%
6 7
 
2.3%
8 5
 
1.7%
4 4
 
1.3%
Other values (4) 8
 
2.6%
Latin
ValueCountFrequency (%)
A 4
40.0%
L 2
20.0%
H 2
20.0%
e 1
 
10.0%
C 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1407
81.8%
ASCII 313
 
18.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 241
 
17.1%
아 49
 
3.5%
통 46
 
3.3%
트 45
 
3.2%
파 44
 
3.1%
신 37
 
2.6%
산 30
 
2.1%
당 30
 
2.1%
성 26
 
1.8%
대 25
 
1.8%
Other values (183) 834
59.3%
ASCII
ValueCountFrequency (%)
1 88
28.1%
2 72
23.0%
) 39
12.5%
( 39
12.5%
3 18
 
5.8%
16
 
5.1%
7 7
 
2.2%
6 7
 
2.2%
8 5
 
1.6%
4 4
 
1.3%
Other values (9) 18
 
5.8%

도로명주소
Text

Distinct340
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-01-10T08:14:53.249735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length20.565217
Min length14

Characters and Unicode

Total characters7095
Distinct characters218
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

Unique335 ?
Unique (%)97.1%

Sample

1st row충청남도 당진시 합덕읍 버그내2길 128-48
2nd row충청남도 당진시 합덕읍 합덕도곡길 45
3rd row충청남도 당진시 합덕읍 남부로 1623-2
4th row충청남도 당진시 합덕읍 남부로 1458
5th row충청남도 당진시 합덕읍 거섬들1길 92-4
ValueCountFrequency (%)
충청남도 345
20.7%
당진시 343
20.6%
송악읍 44
 
2.6%
합덕읍 38
 
2.3%
신평면 31
 
1.9%
우강면 25
 
1.5%
고대면 24
 
1.4%
석문면 23
 
1.4%
송산면 21
 
1.3%
순성면 20
 
1.2%
Other values (529) 750
45.1%
2024-01-10T08:14:53.664762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1324
18.7%
당 371
 
5.2%
진 357
 
5.0%
남 356
 
5.0%
시 356
 
5.0%
충 350
 
4.9%
도 350
 
4.9%
청 347
 
4.9%
1 253
 
3.6%
면 218
 
3.1%
Other values (208) 2813
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4512
63.6%
Space Separator 1324
 
18.7%
Decimal Number 1118
 
15.8%
Dash Punctuation 124
 
1.7%
Other Punctuation 10
 
0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 371
 
8.2%
진 357
 
7.9%
남 356
 
7.9%
시 356
 
7.9%
충 350
 
7.8%
도 350
 
7.8%
청 347
 
7.7%
면 218
 
4.8%
로 194
 
4.3%
길 156
 
3.5%
Other values (191) 1457
32.3%
Decimal Number
ValueCountFrequency (%)
1 253
22.6%
2 161
14.4%
3 117
10.5%
4 89
 
8.0%
9 86
 
7.7%
6 86
 
7.7%
8 85
 
7.6%
5 82
 
7.3%
0 82
 
7.3%
7 77
 
6.9%
Other Punctuation
ValueCountFrequency (%)
, 7
70.0%
. 3
30.0%
Space Separator
ValueCountFrequency (%)
1324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4512
63.6%
Common 2582
36.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 371
 
8.2%
진 357
 
7.9%
남 356
 
7.9%
시 356
 
7.9%
충 350
 
7.8%
도 350
 
7.8%
청 347
 
7.7%
면 218
 
4.8%
로 194
 
4.3%
길 156
 
3.5%
Other values (191) 1457
32.3%
Common
ValueCountFrequency (%)
1324
51.3%
1 253
 
9.8%
2 161
 
6.2%
- 124
 
4.8%
3 117
 
4.5%
4 89
 
3.4%
9 86
 
3.3%
6 86
 
3.3%
8 85
 
3.3%
5 82
 
3.2%
Other values (6) 175
 
6.8%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4512
63.6%
ASCII 2583
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1324
51.3%
1 253
 
9.8%
2 161
 
6.2%
- 124
 
4.8%
3 117
 
4.5%
4 89
 
3.4%
9 86
 
3.3%
6 86
 
3.3%
8 85
 
3.3%
5 82
 
3.2%
Other values (7) 176
 
6.8%
Hangul
ValueCountFrequency (%)
당 371
 
8.2%
진 357
 
7.9%
남 356
 
7.9%
시 356
 
7.9%
충 350
 
7.8%
도 350
 
7.8%
청 347
 
7.7%
면 218
 
4.8%
로 194
 
4.3%
길 156
 
3.5%
Other values (191) 1457
32.3%

지번주소
Text

MISSING 

Distinct284
Distinct (%)99.3%
Missing59
Missing (%)17.1%
Memory size2.8 KiB
2024-01-10T08:14:54.006902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length20.370629
Min length14

Characters and Unicode

Total characters5826
Distinct characters124
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique282 ?
Unique (%)98.6%

Sample

1st row충청남도 당진시 합덕읍 석우리 586
2nd row충청남도 당진시 합덕읍 운산리 632-3
3rd row충청남도 당진시 합덕읍 운산리 275
4th row충청남도 당진시 합덕읍 운산리 257-58
5th row충청남도 당진시 합덕읍 운산리 378
ValueCountFrequency (%)
충청남도 286
20.7%
당진시 286
20.7%
리 66
 
4.8%
송악읍 35
 
2.5%
합덕읍 28
 
2.0%
신평면 25
 
1.8%
우강면 23
 
1.7%
순성면 20
 
1.4%
고대면 20
 
1.4%
송산면 19
 
1.4%
Other values (409) 573
41.5%
2024-01-10T08:14:54.461900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1098
18.8%
당 300
 
5.1%
도 296
 
5.1%
시 294
 
5.0%
청 289
 
5.0%
충 286
 
4.9%
남 286
 
4.9%
진 286
 
4.9%
리 218
 
3.7%
1 215
 
3.7%
Other values (114) 2258
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3431
58.9%
Space Separator 1098
 
18.8%
Decimal Number 1083
 
18.6%
Dash Punctuation 211
 
3.6%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 300
 
8.7%
도 296
 
8.6%
시 294
 
8.6%
청 289
 
8.4%
충 286
 
8.3%
남 286
 
8.3%
진 286
 
8.3%
리 218
 
6.4%
면 192
 
5.6%
읍 72
 
2.1%
Other values (99) 912
26.6%
Decimal Number
ValueCountFrequency (%)
1 215
19.9%
2 151
13.9%
3 136
12.6%
5 115
10.6%
4 108
10.0%
6 93
8.6%
8 80
 
7.4%
7 68
 
6.3%
9 61
 
5.6%
0 56
 
5.2%
Space Separator
ValueCountFrequency (%)
1098
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 211
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3431
58.9%
Common 2395
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 300
 
8.7%
도 296
 
8.6%
시 294
 
8.6%
청 289
 
8.4%
충 286
 
8.3%
남 286
 
8.3%
진 286
 
8.3%
리 218
 
6.4%
면 192
 
5.6%
읍 72
 
2.1%
Other values (99) 912
26.6%
Common
ValueCountFrequency (%)
1098
45.8%
1 215
 
9.0%
- 211
 
8.8%
2 151
 
6.3%
3 136
 
5.7%
5 115
 
4.8%
4 108
 
4.5%
6 93
 
3.9%
8 80
 
3.3%
7 68
 
2.8%
Other values (5) 120
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3431
58.9%
ASCII 2395
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1098
45.8%
1 215
 
9.0%
- 211
 
8.8%
2 151
 
6.3%
3 136
 
5.7%
5 115
 
4.8%
4 108
 
4.5%
6 93
 
3.9%
8 80
 
3.3%
7 68
 
2.8%
Other values (5) 120
 
5.0%
Hangul
ValueCountFrequency (%)
당 300
 
8.7%
도 296
 
8.6%
시 294
 
8.6%
청 289
 
8.4%
충 286
 
8.3%
남 286
 
8.3%
진 286
 
8.3%
리 218
 
6.4%
면 192
 
5.6%
읍 72
 
2.1%
Other values (99) 912
26.6%

위도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing345
Missing (%)100.0%
Memory size3.2 KiB

경도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing345
Missing (%)100.0%
Memory size3.2 KiB

전화번호
Text

MISSING 

Distinct318
Distinct (%)99.4%
Missing25
Missing (%)7.2%
Memory size2.8 KiB
2024-01-10T08:14:54.704625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters3840
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

Unique316 ?
Unique (%)98.8%

Sample

1st row041-363-2243
2nd row041-363-5115
3rd row041-362-8588
4th row041-363-1910
5th row041-363-1888
ValueCountFrequency (%)
041-352-5755 2
 
0.6%
041-358-2213 2
 
0.6%
041-353-5051 1
 
0.3%
041-362-9506 1
 
0.3%
041-363-2243 1
 
0.3%
041-362-7761 1
 
0.3%
041-363-3893 1
 
0.3%
041-363-0959 1
 
0.3%
041-362-6573 1
 
0.3%
041-363-3109 1
 
0.3%
Other values (308) 308
96.2%
2024-01-10T08:14:55.058840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 640
16.7%
3 540
14.1%
4 462
12.0%
1 451
11.7%
0 445
11.6%
5 416
10.8%
6 260
6.8%
2 233
 
6.1%
7 138
 
3.6%
9 137
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3200
83.3%
Dash Punctuation 640
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 540
16.9%
4 462
14.4%
1 451
14.1%
0 445
13.9%
5 416
13.0%
6 260
8.1%
2 233
7.3%
7 138
 
4.3%
9 137
 
4.3%
8 118
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 640
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 640
16.7%
3 540
14.1%
4 462
12.0%
1 451
11.7%
0 445
11.6%
5 416
10.8%
6 260
6.8%
2 233
 
6.1%
7 138
 
3.6%
9 137
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 640
16.7%
3 540
14.1%
4 462
12.0%
1 451
11.7%
0 445
11.6%
5 416
10.8%
6 260
6.8%
2 233
 
6.1%
7 138
 
3.6%
9 137
 
3.6%

등 록 일
Date

MISSING 

Distinct183
Distinct (%)68.3%
Missing77
Missing (%)22.3%
Memory size2.8 KiB
Minimum1905-05-31 00:00:00
Maximum2021-12-27 00:00:00
2024-01-10T08:14:55.197825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:14:55.349566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시설면적
Text

MISSING 

Distinct294
Distinct (%)89.6%
Missing17
Missing (%)4.9%
Memory size2.8 KiB
2024-01-10T08:14:55.711167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.9481707
Min length2

Characters and Unicode

Total characters1623
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique271 ?
Unique (%)82.6%

Sample

1st row154.44
2nd row86.54
3rd row101.4
4th row163.74
5th row92.43
ValueCountFrequency (%)
81 5
 
1.5%
120 5
 
1.5%
49.5 4
 
1.2%
82.5 3
 
0.9%
49.58 3
 
0.9%
115.5 3
 
0.9%
98.4 2
 
0.6%
59 2
 
0.6%
65.23 2
 
0.6%
86.24 2
 
0.6%
Other values (284) 298
90.6%
2024-01-10T08:14:56.186824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 284
17.5%
. 284
17.5%
9 151
9.3%
4 132
8.1%
8 131
8.1%
5 120
7.4%
2 119
7.3%
6 108
 
6.7%
0 107
 
6.6%
3 105
 
6.5%
Other values (2) 82
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1338
82.4%
Other Punctuation 284
 
17.5%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 284
21.2%
9 151
11.3%
4 132
9.9%
8 131
9.8%
5 120
9.0%
2 119
8.9%
6 108
 
8.1%
0 107
 
8.0%
3 105
 
7.8%
7 81
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 284
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1623
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 284
17.5%
. 284
17.5%
9 151
9.3%
4 132
8.1%
8 131
8.1%
5 120
7.4%
2 119
7.3%
6 108
 
6.7%
0 107
 
6.6%
3 105
 
6.5%
Other values (2) 82
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1623
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 284
17.5%
. 284
17.5%
9 151
9.3%
4 132
8.1%
8 131
8.1%
5 120
7.4%
2 119
7.3%
6 108
 
6.7%
0 107
 
6.6%
3 105
 
6.5%
Other values (2) 82
 
5.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2022-03-04 00:00:00
Maximum2022-03-04 00:00:00
2024-01-10T08:14:56.304084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:14:56.383847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T08:14:51.555017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T08:14:56.447123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동
연번1.0000.973
읍면동0.9731.000
2024-01-10T08:14:56.524935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동
연번1.0000.866
읍면동0.8661.000

Missing values

2024-01-10T08:14:51.668060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T08:14:51.817109image/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.
2024-01-10T08:14:51.922132image/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

연번읍면동경로당명도로명주소지번주소위도경도전화번호등 록 일시설면적데이터기준일
01합덕읍합덕읍분회충청남도 당진시 합덕읍 버그내2길 128-48<NA><NA><NA>041-363-22431975-08-25154.442022-03-04
12합덕읍도곡리충청남도 당진시 합덕읍 합덕도곡길 45<NA><NA><NA>041-363-51151989-05-1086.542022-03-04
23합덕읍소소리충청남도 당진시 합덕읍 남부로 1623-2<NA><NA><NA>041-362-85881989-05-10101.42022-03-04
34합덕읍회태리충청남도 당진시 합덕읍 남부로 1458<NA><NA><NA>041-363-19101989-05-10163.742022-03-04
45합덕읍창정리충청남도 당진시 합덕읍 거섬들1길 92-4충청남도 당진시 합덕읍 석우리 586<NA><NA>041-363-18881989-05-1092.432022-03-04
56합덕읍운곡리충청남도 당진시 합덕읍 미락2길 10충청남도 당진시 합덕읍 운산리 632-3<NA><NA>041-363-25291989-05-1099.892022-03-04
67합덕읍서동리충청남도 당진시 합덕읍 버그내2길 31-18<NA><NA><NA>041-362-56801995-05-0864.262022-03-04
78합덕읍중동리충청남도 당진시 합덕읍 버그내2길 128-48충청남도 당진시 합덕읍 운산리 275<NA><NA>041-363-12381994-07-15145.442022-03-04
89합덕읍교동2리충청남도 당진시 합덕읍 버그내1길 193-19충청남도 당진시 합덕읍 운산리 257-58<NA><NA>041-363-22421993-04-0966.632022-03-04
910합덕읍합덕읍충청남도 당진시 합덕읍 버그내1길 210-7<NA><NA><NA>041-362-24561989-05-101312022-03-04
연번읍면동경로당명도로명주소지번주소위도경도전화번호등 록 일시설면적데이터기준일
335336당진3동시곡3통 상목충청남도 당진시 시곡로 337충청남도 당진시 시곡동 81-15<NA><NA><NA>2003-04-24110.22022-03-04
336337당진3동우두1통충청남도 당진시 원우두실로 121충청남도 당진시 우두동 386-1<NA><NA>041-355-44061999-12-3089.492022-03-04
337338당진3동우두2통충청남도 당진시 어리로 200-40충청남도 당진시 우두동 668-5<NA><NA>041-355-78111995-12-1993.042022-03-04
338339당진3동우두3통충청남도 당진시 태성2길 35충청남도 당진시 우두동 1035<NA><NA><NA>2000-06-2959. 42022-03-04
339340당진3동우민늘사랑아파트충청남도 당진시 서해로 6216충청남도 당진시 시곡동 136-1<NA><NA><NA>2007-12-1349.52022-03-04
340341당진3동원당1통충청남도 당진시 원당로 92충청남도 당진시 원당동 775-1<NA><NA>041-352-17721998-11-11138.452022-03-04
341342당진3동원당2통충청남도 당진시 구봉로 147충청남도 당진시 원당동 179-5<NA><NA>041-355-19221995-07-2874.92022-03-04
342343당진3동원당4통 주공그린빌충청남도 당진시 밤절로 104충청남도 당진시 원당동 1248<NA><NA>041-357-53972005-11-11118.672022-03-04
343344당진3동원당이안아파트충청남도 당진시 원당로 52, 당진원당이안아파트<NA><NA><NA><NA>2016-07-19109.472022-03-04
344345당진3동원당마을아파트충청남도 당진시 밤절로 103충청남도 당진시 원당동 1251<NA><NA>041-357-55102003-12-02922022-03-04