Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells8550
Missing cells (%)9.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory849.6 KiB
Average record size in memory87.0 B

Variable types

Categorical1
Numeric6
Text2

Dataset

Description당진시 공간정보활용시스템에서 관리하는 새주소 정보에 대한 데이터로 시군구번호, 도로명번호, 주건물번호, 부건물번호, 건물명, 도로명주소 등의 항목을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=323&beforeMenuCd=DOM_000000201001001000&publicdatapk=15091588

Alerts

시군구번호 has constant value ""Constant
도로명번호 is highly overall correlated with 경도High correlation
구우편주소 is highly overall correlated with 위도High correlation
경도 is highly overall correlated with 도로명번호High correlation
위도 is highly overall correlated with 구우편주소High correlation
건물명 has 8550 (85.5%) missing valuesMissing
도로명번호 has unique valuesUnique
도로명주소 has unique valuesUnique
부건물번호 has 3730 (37.3%) zerosZeros

Reproduction

Analysis started2024-01-09 19:47:55.596974
Analysis finished2024-01-09 19:47:59.941510
Duration4.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구번호
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
44270
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44270
2nd row44270
3rd row44270
4th row44270
5th row44270

Common Values

ValueCountFrequency (%)
44270 10000
100.0%

Length

2024-01-10T04:47:59.988014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:48:00.057595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44270 10000
100.0%

도로명번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21370.311
Minimum4
Maximum45342
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T04:48:00.137928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile2171.85
Q110223
median21156
Q331845.25
95-th percentile42003.85
Maximum45342
Range45338
Interquartile range (IQR)21622.25

Descriptive statistics

Standard deviation12631.532
Coefficient of variation (CV)0.59107853
Kurtosis-1.1401947
Mean21370.311
Median Absolute Deviation (MAD)10785
Skewness0.075732002
Sum2.1370311 × 108
Variance1.5955561 × 108
MonotonicityNot monotonic
2024-01-10T04:48:00.237466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22884 1
 
< 0.1%
10203 1
 
< 0.1%
19273 1
 
< 0.1%
8065 1
 
< 0.1%
7552 1
 
< 0.1%
33965 1
 
< 0.1%
3167 1
 
< 0.1%
13932 1
 
< 0.1%
28925 1
 
< 0.1%
30143 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
4 1
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
25 1
< 0.1%
28 1
< 0.1%
29 1
< 0.1%
ValueCountFrequency (%)
45342 1
< 0.1%
45340 1
< 0.1%
45339 1
< 0.1%
45330 1
< 0.1%
45326 1
< 0.1%
45321 1
< 0.1%
45318 1
< 0.1%
45315 1
< 0.1%
45313 1
< 0.1%
45303 1
< 0.1%

주건물번호
Real number (ℝ)

Distinct1205
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean289.1075
Minimum1
Maximum7516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T04:48:00.342890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q137
median87
Q3243
95-th percentile1229
Maximum7516
Range7515
Interquartile range (IQR)206

Descriptive statistics

Standard deviation698.28956
Coefficient of variation (CV)2.4153284
Kurtosis55.771217
Mean289.1075
Median Absolute Deviation (MAD)65
Skewness6.7239089
Sum2891075
Variance487608.31
MonotonicityNot monotonic
2024-01-10T04:48:00.450534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41 100
 
1.0%
19 96
 
1.0%
15 89
 
0.9%
20 89
 
0.9%
42 88
 
0.9%
11 87
 
0.9%
10 84
 
0.8%
27 82
 
0.8%
25 81
 
0.8%
30 79
 
0.8%
Other values (1195) 9125
91.2%
ValueCountFrequency (%)
1 39
0.4%
2 35
0.4%
3 59
0.6%
4 71
0.7%
5 49
0.5%
6 50
0.5%
7 74
0.7%
8 70
0.7%
9 68
0.7%
10 84
0.8%
ValueCountFrequency (%)
7516 2
 
< 0.1%
7489 4
< 0.1%
7486 1
 
< 0.1%
7475 1
 
< 0.1%
7463 1
 
< 0.1%
7425 1
 
< 0.1%
7404 5
0.1%
7342 1
 
< 0.1%
7297 3
< 0.1%
7281 1
 
< 0.1%

부건물번호
Real number (ℝ)

ZEROS 

Distinct186
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.3483
Minimum0
Maximum408
Zeros3730
Zeros (%)37.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T04:48:00.559985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q319
95-th percentile66
Maximum408
Range408
Interquartile range (IQR)19

Descriptive statistics

Standard deviation26.441057
Coefficient of variation (CV)1.7227352
Kurtosis22.874938
Mean15.3483
Median Absolute Deviation (MAD)5
Skewness3.7059367
Sum153483
Variance699.1295
MonotonicityNot monotonic
2024-01-10T04:48:00.672307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3730
37.3%
1 369
 
3.7%
5 268
 
2.7%
6 262
 
2.6%
7 262
 
2.6%
8 251
 
2.5%
3 249
 
2.5%
4 244
 
2.4%
9 240
 
2.4%
10 199
 
2.0%
Other values (176) 3926
39.3%
ValueCountFrequency (%)
0 3730
37.3%
1 369
 
3.7%
2 146
 
1.5%
3 249
 
2.5%
4 244
 
2.4%
5 268
 
2.7%
6 262
 
2.6%
7 262
 
2.6%
8 251
 
2.5%
9 240
 
2.4%
ValueCountFrequency (%)
408 1
< 0.1%
373 1
< 0.1%
307 1
< 0.1%
279 1
< 0.1%
265 1
< 0.1%
251 1
< 0.1%
248 1
< 0.1%
247 1
< 0.1%
227 1
< 0.1%
219 1
< 0.1%

건물명
Text

MISSING 

Distinct1258
Distinct (%)86.8%
Missing8550
Missing (%)85.5%
Memory size156.2 KiB
2024-01-10T04:48:00.877998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length5.3317241
Min length1

Characters and Unicode

Total characters7731
Distinct characters566
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

Unique1218 ?
Unique (%)84.0%

Sample

1st row석산레미콘(주)
2nd row명화민박
3rd row기지시택시
4th row구마을회관
5th row차고
ValueCountFrequency (%)
우사 46
 
3.0%
하우스 29
 
1.9%
돈사 23
 
1.5%
견사 15
 
1.0%
원룸 11
 
0.7%
정미소 8
 
0.5%
사무실 8
 
0.5%
마을회관 8
 
0.5%
차고 7
 
0.5%
양계장 7
 
0.5%
Other values (1300) 1349
89.3%
2024-01-10T04:48:01.383937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 205
 
2.7%
리 145
 
1.9%
당 139
 
1.8%
회 132
 
1.7%
우 129
 
1.7%
대 127
 
1.6%
원 121
 
1.6%
장 120
 
1.6%
주 117
 
1.5%
산 98
 
1.3%
Other values (556) 6398
82.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7346
95.0%
Uppercase Letter 82
 
1.1%
Decimal Number 76
 
1.0%
Space Separator 61
 
0.8%
Close Punctuation 52
 
0.7%
Open Punctuation 52
 
0.7%
Other Punctuation 47
 
0.6%
Lowercase Letter 14
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 205
 
2.8%
리 145
 
2.0%
당 139
 
1.9%
회 132
 
1.8%
우 129
 
1.8%
대 127
 
1.7%
원 121
 
1.6%
장 120
 
1.6%
주 117
 
1.6%
산 98
 
1.3%
Other values (511) 6013
81.9%
Uppercase Letter
ValueCountFrequency (%)
S 11
13.4%
T 7
 
8.5%
K 7
 
8.5%
L 6
 
7.3%
B 6
 
7.3%
A 5
 
6.1%
G 5
 
6.1%
C 5
 
6.1%
O 4
 
4.9%
I 4
 
4.9%
Other values (12) 22
26.8%
Decimal Number
ValueCountFrequency (%)
1 34
44.7%
2 22
28.9%
3 7
 
9.2%
6 4
 
5.3%
5 3
 
3.9%
7 2
 
2.6%
4 2
 
2.6%
9 2
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 5
35.7%
p 2
 
14.3%
a 2
 
14.3%
c 1
 
7.1%
s 1
 
7.1%
d 1
 
7.1%
m 1
 
7.1%
t 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 38
80.9%
. 8
 
17.0%
& 1
 
2.1%
Space Separator
ValueCountFrequency (%)
61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7346
95.0%
Common 289
 
3.7%
Latin 96
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 205
 
2.8%
리 145
 
2.0%
당 139
 
1.9%
회 132
 
1.8%
우 129
 
1.8%
대 127
 
1.7%
원 121
 
1.6%
장 120
 
1.6%
주 117
 
1.6%
산 98
 
1.3%
Other values (511) 6013
81.9%
Latin
ValueCountFrequency (%)
S 11
 
11.5%
T 7
 
7.3%
K 7
 
7.3%
L 6
 
6.2%
B 6
 
6.2%
e 5
 
5.2%
A 5
 
5.2%
G 5
 
5.2%
C 5
 
5.2%
O 4
 
4.2%
Other values (20) 35
36.5%
Common
ValueCountFrequency (%)
61
21.1%
) 52
18.0%
( 52
18.0%
, 38
13.1%
1 34
11.8%
2 22
 
7.6%
. 8
 
2.8%
3 7
 
2.4%
6 4
 
1.4%
5 3
 
1.0%
Other values (5) 8
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7346
95.0%
ASCII 385
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 205
 
2.8%
리 145
 
2.0%
당 139
 
1.9%
회 132
 
1.8%
우 129
 
1.8%
대 127
 
1.7%
원 121
 
1.6%
장 120
 
1.6%
주 117
 
1.6%
산 98
 
1.3%
Other values (511) 6013
81.9%
ASCII
ValueCountFrequency (%)
61
15.8%
) 52
13.5%
( 52
13.5%
, 38
9.9%
1 34
 
8.8%
2 22
 
5.7%
S 11
 
2.9%
. 8
 
2.1%
T 7
 
1.8%
3 7
 
1.8%
Other values (35) 93
24.2%

구우편주소
Real number (ℝ)

HIGH CORRELATION 

Distinct117
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31763.095
Minimum31700
Maximum31816
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T04:48:01.499682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31700
5-th percentile31704
Q131732
median31762
Q331797
95-th percentile31813
Maximum31816
Range116
Interquartile range (IQR)65

Descriptive statistics

Standard deviation35.951614
Coefficient of variation (CV)0.0011318675
Kurtosis-1.2816139
Mean31763.095
Median Absolute Deviation (MAD)33
Skewness-0.17115139
Sum3.1763095 × 108
Variance1292.5185
MonotonicityNot monotonic
2024-01-10T04:48:01.608037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31812 281
 
2.8%
31754 232
 
2.3%
31801 228
 
2.3%
31791 220
 
2.2%
31815 201
 
2.0%
31803 195
 
1.9%
31814 191
 
1.9%
31793 187
 
1.9%
31743 178
 
1.8%
31714 175
 
1.8%
Other values (107) 7912
79.1%
ValueCountFrequency (%)
31700 143
1.4%
31701 131
1.3%
31702 8
 
0.1%
31703 121
1.2%
31704 98
1.0%
31705 53
 
0.5%
31706 133
1.3%
31707 81
0.8%
31708 59
0.6%
31709 57
 
0.6%
ValueCountFrequency (%)
31816 90
 
0.9%
31815 201
2.0%
31814 191
1.9%
31813 128
1.3%
31812 281
2.8%
31811 139
1.4%
31810 12
 
0.1%
31809 59
 
0.6%
31808 53
 
0.5%
31807 76
 
0.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct9981
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean926641.35
Minimum904310.26
Maximum941386.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T04:48:01.732770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum904310.26
5-th percentile913237.95
Q1920791.12
median927037.92
Q3934163.88
95-th percentile937961.07
Maximum941386.85
Range37076.59
Interquartile range (IQR)13372.755

Descriptive statistics

Standard deviation7965.9007
Coefficient of variation (CV)0.0085965305
Kurtosis-0.9123607
Mean926641.35
Median Absolute Deviation (MAD)6775.755
Skewness-0.26212964
Sum9.2664135 × 109
Variance63455573
MonotonicityNot monotonic
2024-01-10T04:48:01.876610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
931358.89 2
 
< 0.1%
923466.81 2
 
< 0.1%
923129.06 2
 
< 0.1%
934749.16 2
 
< 0.1%
929483.13 2
 
< 0.1%
934189.86 2
 
< 0.1%
922282.45 2
 
< 0.1%
925229.79 2
 
< 0.1%
934004.11 2
 
< 0.1%
933102.81 2
 
< 0.1%
Other values (9971) 9980
99.8%
ValueCountFrequency (%)
904310.26 1
< 0.1%
904463.25 1
< 0.1%
904656.67 1
< 0.1%
904867.3 1
< 0.1%
904935.87 1
< 0.1%
905048.95 1
< 0.1%
905091.41 1
< 0.1%
905120.52 1
< 0.1%
905154.98 1
< 0.1%
905159.62 1
< 0.1%
ValueCountFrequency (%)
941386.85 1
< 0.1%
941383.98 1
< 0.1%
941369.91 1
< 0.1%
941321.44 1
< 0.1%
941309.04 1
< 0.1%
941305.78 1
< 0.1%
941299.82 1
< 0.1%
941284.39 1
< 0.1%
941283.73 1
< 0.1%
941251.35 1
< 0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct9985
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1877120.8
Minimum1861970.4
Maximum1896016.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T04:48:02.015772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1861970.4
5-th percentile1866814.4
Q11871630
median1877166.4
Q31881808.3
95-th percentile1889481.3
Maximum1896016.2
Range34045.81
Interquartile range (IQR)10178.3

Descriptive statistics

Standard deviation6945.0731
Coefficient of variation (CV)0.0036998541
Kurtosis-0.43141253
Mean1877120.8
Median Absolute Deviation (MAD)5100.88
Skewness0.2730975
Sum1.8771208 × 1010
Variance48234041
MonotonicityNot monotonic
2024-01-10T04:48:02.154982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1880618.95 2
 
< 0.1%
1877982.74 2
 
< 0.1%
1875409.25 2
 
< 0.1%
1875787.42 2
 
< 0.1%
1878938.37 2
 
< 0.1%
1884908.53 2
 
< 0.1%
1870837.75 2
 
< 0.1%
1884924.97 2
 
< 0.1%
1875961.28 2
 
< 0.1%
1868236.28 2
 
< 0.1%
Other values (9975) 9980
99.8%
ValueCountFrequency (%)
1861970.38 1
< 0.1%
1862172.59 1
< 0.1%
1862182.34 1
< 0.1%
1862182.61 1
< 0.1%
1862716.65 1
< 0.1%
1862790.86 1
< 0.1%
1862807.25 1
< 0.1%
1862836.37 1
< 0.1%
1862858.52 1
< 0.1%
1862859.32 1
< 0.1%
ValueCountFrequency (%)
1896016.19 1
< 0.1%
1895865.81 1
< 0.1%
1895848.6 1
< 0.1%
1895550.39 1
< 0.1%
1895537.95 1
< 0.1%
1895509.46 1
< 0.1%
1895507.78 1
< 0.1%
1895503.89 1
< 0.1%
1895482.91 1
< 0.1%
1895476.18 1
< 0.1%

도로명주소
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T04:48:02.407136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length16.3115
Min length9

Characters and Unicode

Total characters163115
Distinct characters313
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row당진시 고대면 세비장길 94-5
2nd row당진시 당진중앙2로 132-21
3rd row당진시 순성면 갈산길 86-1
4th row당진시 송산면 명성길 50-103
5th row당진시 합덕읍 후박마을2길 32
ValueCountFrequency (%)
당진시 10000
26.0%
송악읍 1280
 
3.3%
합덕읍 1082
 
2.8%
신평면 962
 
2.5%
석문면 828
 
2.2%
고대면 760
 
2.0%
송산면 735
 
1.9%
순성면 647
 
1.7%
우강면 602
 
1.6%
면천면 574
 
1.5%
Other values (6763) 20945
54.5%
2024-01-10T04:48:02.734507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28415
17.4%
당 10576
 
6.5%
진 10419
 
6.4%
시 10330
 
6.3%
1 8270
 
5.1%
면 6794
 
4.2%
- 6270
 
3.8%
길 5408
 
3.3%
2 5287
 
3.2%
로 4719
 
2.9%
Other values (303) 66627
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91015
55.8%
Decimal Number 37356
22.9%
Space Separator 28415
 
17.4%
Dash Punctuation 6270
 
3.8%
Other Punctuation 59
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 10576
 
11.6%
진 10419
 
11.4%
시 10330
 
11.3%
면 6794
 
7.5%
길 5408
 
5.9%
로 4719
 
5.2%
읍 2362
 
2.6%
송 2257
 
2.5%
대 1794
 
2.0%
덕 1526
 
1.7%
Other values (290) 34830
38.3%
Decimal Number
ValueCountFrequency (%)
1 8270
22.1%
2 5287
14.2%
3 4220
11.3%
4 3512
9.4%
5 3199
 
8.6%
6 2921
 
7.8%
7 2907
 
7.8%
8 2507
 
6.7%
9 2385
 
6.4%
0 2148
 
5.8%
Space Separator
ValueCountFrequency (%)
28415
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6270
100.0%
Other Punctuation
ValueCountFrequency (%)
. 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91015
55.8%
Common 72100
44.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 10576
 
11.6%
진 10419
 
11.4%
시 10330
 
11.3%
면 6794
 
7.5%
길 5408
 
5.9%
로 4719
 
5.2%
읍 2362
 
2.6%
송 2257
 
2.5%
대 1794
 
2.0%
덕 1526
 
1.7%
Other values (290) 34830
38.3%
Common
ValueCountFrequency (%)
28415
39.4%
1 8270
 
11.5%
- 6270
 
8.7%
2 5287
 
7.3%
3 4220
 
5.9%
4 3512
 
4.9%
5 3199
 
4.4%
6 2921
 
4.1%
7 2907
 
4.0%
8 2507
 
3.5%
Other values (3) 4592
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91015
55.8%
ASCII 72100
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28415
39.4%
1 8270
 
11.5%
- 6270
 
8.7%
2 5287
 
7.3%
3 4220
 
5.9%
4 3512
 
4.9%
5 3199
 
4.4%
6 2921
 
4.1%
7 2907
 
4.0%
8 2507
 
3.5%
Other values (3) 4592
 
6.4%
Hangul
ValueCountFrequency (%)
당 10576
 
11.6%
진 10419
 
11.4%
시 10330
 
11.3%
면 6794
 
7.5%
길 5408
 
5.9%
로 4719
 
5.2%
읍 2362
 
2.6%
송 2257
 
2.5%
대 1794
 
2.0%
덕 1526
 
1.7%
Other values (290) 34830
38.3%

Interactions

2024-01-10T04:47:59.299039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:56.959768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.421498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.892372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.362160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.823332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:59.367004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.032001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.491096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.961958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.430736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.892982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:59.444695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.113189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.569199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.039782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.504862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.970640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:59.526216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.201421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.654280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.124720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.587017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:59.051013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:59.604333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.273683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.730171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.201841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.668024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:59.130342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:59.689246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.349688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:57.815523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.281930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:58.748124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:47:59.213098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T04:48:02.829669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로명번호주건물번호부건물번호구우편주소경도위도
도로명번호1.0000.2070.0930.8060.8690.686
주건물번호0.2071.0000.0240.3200.2780.449
부건물번호0.0930.0241.0000.0720.1040.055
구우편주소0.8060.3200.0721.0000.8350.901
경도0.8690.2780.1040.8351.0000.714
위도0.6860.4490.0550.9010.7141.000
2024-01-10T04:48:02.936200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로명번호주건물번호부건물번호구우편주소경도위도
도로명번호1.0000.0470.0490.069-0.6480.248
주건물번호0.0471.0000.081-0.038-0.1220.092
부건물번호0.0490.0811.000-0.037-0.0620.040
구우편주소0.069-0.038-0.0371.000-0.034-0.702
경도-0.648-0.122-0.062-0.0341.000-0.447
위도0.2480.0920.040-0.702-0.4471.000

Missing values

2024-01-10T04:47:59.787990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T04:47:59.891917image/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

시군구번호도로명번호주건물번호부건물번호건물명구우편주소경도위도도로명주소
174324427022884945<NA>31791916868.651887854.44당진시 고대면 세비장길 94-5
464442702457313221<NA>31776922732.141877723.83당진시 당진중앙2로 132-21
291574427034793861<NA>31755926188.271875178.45당진시 순성면 갈산길 86-1
37713442701457150103<NA>31714928832.321881077.73당진시 송산면 명성길 50-103
10256442705926320<NA>31813935723.841867728.94당진시 합덕읍 후박마을2길 32
10921442703736520160<NA>31723935160.331882192.11당진시 송악읍 복운로 201-60
2462244270288751712<NA>31801918139.891871301.11당진시 정미면 가지막길 17-12
224544270381621956<NA>31769922179.351877677.7당진시 서문2길 19-56
293504427018509260석산레미콘(주)31761927166.951868642.21당진시 순성면 대촌2길 26
3307344270418825044<NA>31743938141.991877974.62당진시 신평면 샛터로 250-44
시군구번호도로명번호주건물번호부건물번호건물명구우편주소경도위도도로명주소
18614442702978415548<NA>31706914254.731890831.53당진시 석문면 대호로 1554-8
633344270104523240<NA>31811934088.121867639.89당진시 합덕읍 예덕로 324
111764427014306829하우스31722937149.121882934.33당진시 송악읍 부곡공단로 68-29
2999644270136857021돈사31758930225.681874204.13당진시 순성면 중상골길 70-21
660044270159179612<NA>31816930886.091867101.97당진시 합덕읍 재오지로 96-12
1700544270229024391정미소31791917027.621887178.1당진시 고대면 황토마을로 439-1
35105442701020829529<NA>31730932604.641879159.98당진시 신평면 새내큰말길 295-29
11108442703779226527<NA>31735932092.221876174.06당진시 송악읍 봉학로 265-27
2563444270187385210<NA>31804924664.051869281.83당진시 면천면 면천로 521
2502442702702810911<NA>31784921649.521876994.12당진시 백암로 109-11