Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells18261
Missing cells (%)12.2%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory1.3 MiB
Average record size in memory133.0 B

Variable types

Numeric5
Categorical6
Text3
DateTime1

Dataset

Description전라북도 정읍시 도로명주소 정보(건물번호, 도로구간시군구코드, 상세건물명, 건물분류코드, 건물종속구분, 지상층수, 지하층수, 건물, 건물명, 읍면동코드, 리코드, 산여부, 지번본번, 지번부번, 건물일련번호, 시군구코드, 도로명코드, 도로구간일련번호, 기초구간일련번호, 건물군일련번호, 건물구분코드, 건물본번, 건물부번)등 자료제공
URLhttps://www.data.go.kr/data/15085011/fileData.do

Alerts

행정구역 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
행정동 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
법정동 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 법정동 and 1 other fieldsHigh correlation
출입구일련번호 is highly overall correlated with 건물일련번호 and 2 other fieldsHigh correlation
건물일련번호 is highly overall correlated with 출입구일련번호 and 1 other fieldsHigh correlation
본번 is highly overall correlated with 광역도로구분High correlation
광역도로구분 is highly overall correlated with 본번High correlation
도로종속구분 is highly overall correlated with 건물일련번호High correlation
도로위계구분 is highly imbalanced (52.5%)Imbalance
광역도로구분 is highly imbalanced (89.0%)Imbalance
연번 has 9467 (94.7%) missing valuesMissing
건물명 has 8794 (87.9%) missing valuesMissing
부번 has 4721 (47.2%) zerosZeros

Reproduction

Analysis started2023-12-12 17:55:38.643485
Analysis finished2023-12-12 17:55:45.349479
Duration6.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct533
Distinct (%)100.0%
Missing9467
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean1171.4559
Minimum1
Maximum2388
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:55:45.455239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile148
Q1561
median1163
Q31762
95-th percentile2227.2
Maximum2388
Range2387
Interquartile range (IQR)1201

Descriptive statistics

Standard deviation678.36891
Coefficient of variation (CV)0.57908189
Kurtosis-1.2039151
Mean1171.4559
Median Absolute Deviation (MAD)601
Skewness0.032770162
Sum624386
Variance460184.37
MonotonicityNot monotonic
2023-12-13T02:55:45.645371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1360 1
 
< 0.1%
1820 1
 
< 0.1%
758 1
 
< 0.1%
1314 1
 
< 0.1%
170 1
 
< 0.1%
1864 1
 
< 0.1%
1740 1
 
< 0.1%
1644 1
 
< 0.1%
1759 1
 
< 0.1%
1592 1
 
< 0.1%
Other values (523) 523
 
5.2%
(Missing) 9467
94.7%
ValueCountFrequency (%)
1 1
< 0.1%
3 1
< 0.1%
6 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
21 1
< 0.1%
28 1
< 0.1%
40 1
< 0.1%
45 1
< 0.1%
46 1
< 0.1%
ValueCountFrequency (%)
2388 1
< 0.1%
2387 1
< 0.1%
2383 1
< 0.1%
2378 1
< 0.1%
2376 1
< 0.1%
2374 1
< 0.1%
2371 1
< 0.1%
2360 1
< 0.1%
2358 1
< 0.1%
2348 1
< 0.1%

행정구역
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정읍시 10000
100.0%

Length

2023-12-13T02:55:45.823628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:55:45.939939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정읍시 10000
100.0%

법정동
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
신태인읍
723 
북면
 
613
태인면
 
582
감곡면
 
533
고부면
 
526
Other values (37)
7023 

Length

Max length4
Median length3
Mean length2.9689
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row교암동
2nd row산외면
3rd row하북동
4th row옹동면
5th row영원면

Common Values

ValueCountFrequency (%)
신태인읍 723
 
7.2%
북면 613
 
6.1%
태인면 582
 
5.8%
감곡면 533
 
5.3%
고부면 526
 
5.3%
입암면 517
 
5.2%
정우면 506
 
5.1%
시기동 481
 
4.8%
칠보면 435
 
4.3%
산외면 431
 
4.3%
Other values (32) 4653
46.5%

Length

2023-12-13T02:55:46.079919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신태인읍 723
 
7.2%
북면 613
 
6.1%
태인면 582
 
5.8%
감곡면 533
 
5.3%
고부면 526
 
5.3%
입암면 517
 
5.2%
정우면 506
 
5.1%
시기동 481
 
4.8%
칠보면 435
 
4.3%
산외면 431
 
4.3%
Other values (32) 4653
46.5%

행정동
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
신태인읍
723 
내장상동
700 
북면
 
613
태인면
 
582
감곡면
 
533
Other values (18)
6849 

Length

Max length4
Median length3
Mean length3.081
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상교동
2nd row산외면
3rd row수성동
4th row옹동면
5th row영원면

Common Values

ValueCountFrequency (%)
신태인읍 723
 
7.2%
내장상동 700
 
7.0%
북면 613
 
6.1%
태인면 582
 
5.8%
감곡면 533
 
5.3%
고부면 526
 
5.3%
입암면 517
 
5.2%
정우면 506
 
5.1%
수성동 501
 
5.0%
칠보면 435
 
4.3%
Other values (13) 4364
43.6%

Length

2023-12-13T02:55:46.248669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신태인읍 723
 
7.2%
내장상동 700
 
7.0%
북면 613
 
6.1%
태인면 582
 
5.8%
감곡면 533
 
5.3%
고부면 526
 
5.3%
입암면 517
 
5.2%
정우면 506
 
5.1%
수성동 501
 
5.0%
칠보면 435
 
4.3%
Other values (13) 4364
43.6%

출입구일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24148.127
Minimum4
Maximum56577
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:55:46.417145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile2652.85
Q112691
median24145.5
Q335220.25
95-th percentile46365.1
Maximum56577
Range56573
Interquartile range (IQR)22529.25

Descriptive statistics

Standard deviation13802.763
Coefficient of variation (CV)0.57158733
Kurtosis-0.98165634
Mean24148.127
Median Absolute Deviation (MAD)11273
Skewness0.084737414
Sum2.4148127 × 108
Variance1.9051627 × 108
MonotonicityNot monotonic
2023-12-13T02:55:46.613444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25148 2
 
< 0.1%
9752 1
 
< 0.1%
6730 1
 
< 0.1%
42418 1
 
< 0.1%
27998 1
 
< 0.1%
17093 1
 
< 0.1%
20268 1
 
< 0.1%
17639 1
 
< 0.1%
3865 1
 
< 0.1%
9256 1
 
< 0.1%
Other values (9989) 9989
99.9%
ValueCountFrequency (%)
4 1
< 0.1%
5 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
14 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
24 1
< 0.1%
27 1
< 0.1%
28 1
< 0.1%
ValueCountFrequency (%)
56577 1
< 0.1%
56541 1
< 0.1%
56539 1
< 0.1%
56538 1
< 0.1%
56517 1
< 0.1%
56459 1
< 0.1%
56441 1
< 0.1%
56397 1
< 0.1%
56357 1
< 0.1%
56317 1
< 0.1%

건물일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51856.645
Minimum42
Maximum107376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:55:46.824220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile5164.6
Q126284.5
median52637.5
Q377879.5
95-th percentile96461.1
Maximum107376
Range107334
Interquartile range (IQR)51595

Descriptive statistics

Standard deviation29673.075
Coefficient of variation (CV)0.57221355
Kurtosis-1.2003967
Mean51856.645
Median Absolute Deviation (MAD)25756
Skewness-0.032815062
Sum5.1856645 × 108
Variance8.8049139 × 108
MonotonicityNot monotonic
2023-12-13T02:55:47.020332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38709 2
 
< 0.1%
80277 1
 
< 0.1%
46236 1
 
< 0.1%
92315 1
 
< 0.1%
62725 1
 
< 0.1%
47034 1
 
< 0.1%
6989 1
 
< 0.1%
2719 1
 
< 0.1%
19905 1
 
< 0.1%
5316 1
 
< 0.1%
Other values (9989) 9989
99.9%
ValueCountFrequency (%)
42 1
< 0.1%
44 1
< 0.1%
48 1
< 0.1%
76 1
< 0.1%
89 1
< 0.1%
93 1
< 0.1%
135 1
< 0.1%
161 1
< 0.1%
176 1
< 0.1%
196 1
< 0.1%
ValueCountFrequency (%)
107376 1
< 0.1%
107340 1
< 0.1%
107338 1
< 0.1%
107337 1
< 0.1%
107318 1
< 0.1%
107278 1
< 0.1%
107260 1
< 0.1%
107216 1
< 0.1%
107176 1
< 0.1%
107136 1
< 0.1%

건물명
Text

MISSING 

Distinct1170
Distinct (%)97.0%
Missing8794
Missing (%)87.9%
Memory size156.2 KiB
2023-12-13T02:55:47.395362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length20
Mean length5.8233831
Min length1

Characters and Unicode

Total characters7023
Distinct characters569
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1150 ?
Unique (%)95.4%

Sample

1st row현보하이텍㈜
2nd row사랑슈퍼
3rd row비비큐치킨수성점
4th row농산물간이집하장
5th row영원상회
ValueCountFrequency (%)
모정 8
 
0.6%
우사 8
 
0.6%
주택 5
 
0.4%
경로당 5
 
0.4%
소성 4
 
0.3%
정읍 4
 
0.3%
온누리교회 2
 
0.1%
대흥 2
 
0.1%
신태인 2
 
0.1%
과학나라 2
 
0.1%
Other values (1272) 1299
96.9%
2023-12-13T02:55:47.960099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 154
 
2.2%
사 141
 
2.0%
135
 
1.9%
회 131
 
1.9%
장 119
 
1.7%
원 111
 
1.6%
당 105
 
1.5%
대 94
 
1.3%
농 93
 
1.3%
인 91
 
1.3%
Other values (559) 5849
83.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6637
94.5%
Space Separator 135
 
1.9%
Uppercase Letter 95
 
1.4%
Decimal Number 50
 
0.7%
Lowercase Letter 33
 
0.5%
Other Symbol 28
 
0.4%
Other Punctuation 15
 
0.2%
Open Punctuation 12
 
0.2%
Close Punctuation 11
 
0.2%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 154
 
2.3%
사 141
 
2.1%
회 131
 
2.0%
장 119
 
1.8%
원 111
 
1.7%
당 105
 
1.6%
대 94
 
1.4%
농 93
 
1.4%
인 91
 
1.4%
동 89
 
1.3%
Other values (503) 5509
83.0%
Uppercase Letter
ValueCountFrequency (%)
G 12
12.6%
K 11
11.6%
S 10
10.5%
A 9
 
9.5%
T 8
 
8.4%
N 5
 
5.3%
L 5
 
5.3%
P 4
 
4.2%
B 4
 
4.2%
D 3
 
3.2%
Other values (12) 24
25.3%
Lowercase Letter
ValueCountFrequency (%)
o 6
18.2%
a 4
12.1%
e 3
9.1%
m 3
9.1%
r 3
9.1%
l 2
 
6.1%
s 2
 
6.1%
y 2
 
6.1%
k 2
 
6.1%
t 2
 
6.1%
Other values (4) 4
12.1%
Decimal Number
ValueCountFrequency (%)
1 10
20.0%
3 9
18.0%
0 7
14.0%
2 7
14.0%
8 6
12.0%
4 4
 
8.0%
5 3
 
6.0%
9 2
 
4.0%
6 2
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 7
46.7%
& 5
33.3%
/ 2
 
13.3%
. 1
 
6.7%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
135
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6665
94.9%
Common 230
 
3.3%
Latin 128
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 154
 
2.3%
사 141
 
2.1%
회 131
 
2.0%
장 119
 
1.8%
원 111
 
1.7%
당 105
 
1.6%
대 94
 
1.4%
농 93
 
1.4%
인 91
 
1.4%
동 89
 
1.3%
Other values (504) 5537
83.1%
Latin
ValueCountFrequency (%)
G 12
 
9.4%
K 11
 
8.6%
S 10
 
7.8%
A 9
 
7.0%
T 8
 
6.2%
o 6
 
4.7%
N 5
 
3.9%
L 5
 
3.9%
P 4
 
3.1%
a 4
 
3.1%
Other values (26) 54
42.2%
Common
ValueCountFrequency (%)
135
58.7%
( 12
 
5.2%
) 11
 
4.8%
1 10
 
4.3%
3 9
 
3.9%
0 7
 
3.0%
, 7
 
3.0%
2 7
 
3.0%
8 6
 
2.6%
- 5
 
2.2%
Other values (9) 21
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6637
94.5%
ASCII 358
 
5.1%
None 28
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 154
 
2.3%
사 141
 
2.1%
회 131
 
2.0%
장 119
 
1.8%
원 111
 
1.7%
당 105
 
1.6%
대 94
 
1.4%
농 93
 
1.4%
인 91
 
1.4%
동 89
 
1.3%
Other values (503) 5509
83.0%
ASCII
ValueCountFrequency (%)
135
37.7%
G 12
 
3.4%
( 12
 
3.4%
) 11
 
3.1%
K 11
 
3.1%
1 10
 
2.8%
S 10
 
2.8%
3 9
 
2.5%
A 9
 
2.5%
T 8
 
2.2%
Other values (45) 131
36.6%
None
ValueCountFrequency (%)
㈜ 28
100.0%

도로위계구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
길
7849 
로
2150 
대로
 
1

Length

Max length2
Median length1
Mean length1.0001
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
길 7849
78.5%
로 2150
 
21.5%
대로 1
 
< 0.1%

Length

2023-12-13T02:55:48.128350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:55:48.253646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
길 7849
78.5%
로 2150
 
21.5%
대로 1
 
< 0.1%

광역도로구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
시군구도로
9747 
광역도로
 
246
행안부도로
 
7

Length

Max length5
Median length5
Mean length4.9754
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시군구도로 9747
97.5%
광역도로 246
 
2.5%
행안부도로 7
 
0.1%

Length

2023-12-13T02:55:48.388065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:55:48.531399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시군구도로 9747
97.5%
광역도로 246
 
2.5%
행안부도로 7
 
0.1%

도로종속구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주도로
5067 
1차 종속도로
4465 
2차 종속도로
 
468

Length

Max length7
Median length3
Mean length4.9732
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1차 종속도로
2nd row1차 종속도로
3rd row1차 종속도로
4th row2차 종속도로
5th row주도로

Common Values

ValueCountFrequency (%)
주도로 5067
50.7%
1차 종속도로 4465
44.6%
2차 종속도로 468
 
4.7%

Length

2023-12-13T02:55:48.686858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:55:48.854054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주도로 5067
33.9%
종속도로 4933
33.0%
1차 4465
29.9%
2차 468
 
3.1%

건물용도
Text

Distinct159
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T02:55:49.518862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.0371
Min length2

Characters and Unicode

Total characters40371
Distinct characters178
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

Unique47 ?
Unique (%)0.5%

Sample

1st row창고
2nd row기타가축시설
3rd row단독주택
4th row축사
5th row단독주택
ValueCountFrequency (%)
단독주택 6848
68.4%
창고 666
 
6.7%
축사 391
 
3.9%
제2종근린생활시설 196
 
2.0%
일반음식점 161
 
1.6%
상점 134
 
1.3%
노인복지시설 106
 
1.1%
기타동식물관련시설 102
 
1.0%
기타창고시설 80
 
0.8%
제1종근린생활시설 75
 
0.7%
Other values (153) 1248
 
12.5%
2023-12-13T02:55:50.047123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 6972
17.3%
택 6936
17.2%
단 6850
17.0%
독 6848
17.0%
시 798
 
2.0%
설 788
 
2.0%
고 751
 
1.9%
창 748
 
1.9%
사 566
 
1.4%
제 424
 
1.1%
Other values (168) 8690
21.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39924
98.9%
Decimal Number 335
 
0.8%
Close Punctuation 51
 
0.1%
Open Punctuation 51
 
0.1%
Space Separator 7
 
< 0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 6972
17.5%
택 6936
17.4%
단 6850
17.2%
독 6848
17.2%
시 798
 
2.0%
설 788
 
2.0%
고 751
 
1.9%
창 748
 
1.9%
사 566
 
1.4%
제 424
 
1.1%
Other values (162) 8243
20.6%
Decimal Number
ValueCountFrequency (%)
2 234
69.9%
1 101
30.1%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39924
98.9%
Common 447
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 6972
17.5%
택 6936
17.4%
단 6850
17.2%
독 6848
17.2%
시 798
 
2.0%
설 788
 
2.0%
고 751
 
1.9%
창 748
 
1.9%
사 566
 
1.4%
제 424
 
1.1%
Other values (162) 8243
20.6%
Common
ValueCountFrequency (%)
2 234
52.3%
1 101
22.6%
) 51
 
11.4%
( 51
 
11.4%
7
 
1.6%
. 3
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39924
98.9%
ASCII 447
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 6972
17.5%
택 6936
17.4%
단 6850
17.2%
독 6848
17.2%
시 798
 
2.0%
설 788
 
2.0%
고 751
 
1.9%
창 748
 
1.9%
사 566
 
1.4%
제 424
 
1.1%
Other values (162) 8243
20.6%
ASCII
ValueCountFrequency (%)
2 234
52.3%
1 101
22.6%
) 51
 
11.4%
( 51
 
11.4%
7
 
1.6%
. 3
 
0.7%

도로명
Text

Distinct1198
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T02:55:50.407484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.7523
Min length2

Characters and Unicode

Total characters37523
Distinct characters270
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

Unique62 ?
Unique (%)0.6%

Sample

1st row석고길
2nd row상두3길
3rd row군대길
4th row시목길
5th row발립길
ValueCountFrequency (%)
충정로 136
 
1.4%
정읍북로 110
 
1.1%
정신로 97
 
1.0%
정읍남로 91
 
0.9%
황토현로 75
 
0.8%
서부산업도로 74
 
0.7%
중앙로 72
 
0.7%
태고로 69
 
0.7%
벚꽃로 68
 
0.7%
영원로 67
 
0.7%
Other values (1188) 9141
91.4%
2023-12-13T02:55:50.939232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 7849
 
20.9%
로 2151
 
5.7%
1 1744
 
4.6%
2 1224
 
3.3%
산 1037
 
2.8%
정 957
 
2.6%
신 740
 
2.0%
동 721
 
1.9%
지 548
 
1.5%
3 511
 
1.4%
Other values (260) 20041
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33507
89.3%
Decimal Number 4016
 
10.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 7849
23.4%
로 2151
 
6.4%
산 1037
 
3.1%
정 957
 
2.9%
신 740
 
2.2%
동 721
 
2.2%
지 548
 
1.6%
성 496
 
1.5%
태 483
 
1.4%
원 465
 
1.4%
Other values (250) 18060
53.9%
Decimal Number
ValueCountFrequency (%)
1 1744
43.4%
2 1224
30.5%
3 511
 
12.7%
4 197
 
4.9%
5 139
 
3.5%
6 101
 
2.5%
7 52
 
1.3%
8 25
 
0.6%
9 21
 
0.5%
0 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33507
89.3%
Common 4016
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 7849
23.4%
로 2151
 
6.4%
산 1037
 
3.1%
정 957
 
2.9%
신 740
 
2.2%
동 721
 
2.2%
지 548
 
1.6%
성 496
 
1.5%
태 483
 
1.4%
원 465
 
1.4%
Other values (250) 18060
53.9%
Common
ValueCountFrequency (%)
1 1744
43.4%
2 1224
30.5%
3 511
 
12.7%
4 197
 
4.9%
5 139
 
3.5%
6 101
 
2.5%
7 52
 
1.3%
8 25
 
0.6%
9 21
 
0.5%
0 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33507
89.3%
ASCII 4016
 
10.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 7849
23.4%
로 2151
 
6.4%
산 1037
 
3.1%
정 957
 
2.9%
신 740
 
2.2%
동 721
 
2.2%
지 548
 
1.6%
성 496
 
1.5%
태 483
 
1.4%
원 465
 
1.4%
Other values (250) 18060
53.9%
ASCII
ValueCountFrequency (%)
1 1744
43.4%
2 1224
30.5%
3 511
 
12.7%
4 197
 
4.9%
5 139
 
3.5%
6 101
 
2.5%
7 52
 
1.3%
8 25
 
0.6%
9 21
 
0.5%
0 2
 
< 0.1%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct929
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean142.8356
Minimum1
Maximum2952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:55:51.102527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q117
median40
Q399.25
95-th percentile753.1
Maximum2952
Range2951
Interquartile range (IQR)82.25

Descriptive statistics

Standard deviation305.9444
Coefficient of variation (CV)2.1419338
Kurtosis24.663747
Mean142.8356
Median Absolute Deviation (MAD)27
Skewness4.375216
Sum1428356
Variance93601.976
MonotonicityNot monotonic
2023-12-13T02:55:51.266218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 234
 
2.3%
7 174
 
1.7%
10 171
 
1.7%
16 169
 
1.7%
15 167
 
1.7%
6 167
 
1.7%
11 164
 
1.6%
9 164
 
1.6%
20 160
 
1.6%
8 156
 
1.6%
Other values (919) 8274
82.7%
ValueCountFrequency (%)
1 63
 
0.6%
2 61
 
0.6%
3 117
1.2%
4 119
1.2%
5 153
1.5%
6 167
1.7%
7 174
1.7%
8 156
1.6%
9 164
1.6%
10 171
1.7%
ValueCountFrequency (%)
2952 1
 
< 0.1%
2951 1
 
< 0.1%
2945 1
 
< 0.1%
2936 3
< 0.1%
2935 3
< 0.1%
2919 1
 
< 0.1%
2918 1
 
< 0.1%
2915 1
 
< 0.1%
2912 1
 
< 0.1%
2858 3
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct123
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3286
Minimum0
Maximum405
Zeros4721
Zeros (%)47.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:55:51.449152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q38
95-th percentile35.05
Maximum405
Range405
Interquartile range (IQR)8

Descriptive statistics

Standard deviation15.105782
Coefficient of variation (CV)2.0612097
Kurtosis63.486751
Mean7.3286
Median Absolute Deviation (MAD)1
Skewness5.1328118
Sum73286
Variance228.18464
MonotonicityNot monotonic
2023-12-13T02:55:51.627728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4721
47.2%
1 619
 
6.2%
3 442
 
4.4%
4 382
 
3.8%
5 345
 
3.5%
6 330
 
3.3%
2 298
 
3.0%
7 248
 
2.5%
8 234
 
2.3%
10 197
 
2.0%
Other values (113) 2184
21.8%
ValueCountFrequency (%)
0 4721
47.2%
1 619
 
6.2%
2 298
 
3.0%
3 442
 
4.4%
4 382
 
3.8%
5 345
 
3.5%
6 330
 
3.3%
7 248
 
2.5%
8 234
 
2.3%
9 170
 
1.7%
ValueCountFrequency (%)
405 1
< 0.1%
191 1
< 0.1%
139 1
< 0.1%
135 1
< 0.1%
134 1
< 0.1%
130 1
< 0.1%
127 1
< 0.1%
125 2
< 0.1%
122 1
< 0.1%
121 1
< 0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-19 00:00:00
Maximum2023-01-19 00:00:00
2023-12-13T02:55:51.759490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:51.868872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T02:55:44.100230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:41.345356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:42.072301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:42.762624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:43.438372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:44.236327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:41.509866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:42.201605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:42.882758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:43.567652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:44.361421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:41.656856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:42.338590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:43.025918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:43.694648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:44.497190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:41.785734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:42.488288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:43.154504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:43.807290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:44.631155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:41.944610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:42.626048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:43.291920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:55:43.936290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:55:51.962627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번법정동행정동출입구일련번호건물일련번호도로위계구분광역도로구분도로종속구분본번부번
연번1.000NaNNaN0.3310.3110.5550.4150.1270.3880.155
법정동NaN1.0000.9990.8910.7410.3770.5900.2140.5220.152
행정동NaN0.9991.0000.8660.7010.3070.3660.1830.4050.095
출입구일련번호0.3310.8910.8661.0000.8930.2630.1820.0650.2360.107
건물일련번호0.3110.7410.7010.8931.0000.5430.2190.7700.3840.160
도로위계구분0.5550.3770.3070.2630.5431.0000.5220.0710.6310.121
광역도로구분0.4150.5900.3660.1820.2190.5221.0000.0460.7630.052
도로종속구분0.1270.2140.1830.0650.7700.0710.0461.0000.0490.387
본번0.3880.5220.4050.2360.3840.6310.7630.0491.0000.095
부번0.1550.1520.0950.1070.1600.1210.0520.3870.0951.000
2023-12-13T02:55:52.135958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로종속구분광역도로구분도로위계구분행정동법정동
도로종속구분1.0000.0140.0210.0950.100
광역도로구분0.0141.0000.2170.2040.339
도로위계구분0.0210.2171.0000.1670.189
행정동0.0950.2040.1671.0000.968
법정동0.1000.3390.1890.9681.000
2023-12-13T02:55:52.246692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번출입구일련번호건물일련번호본번부번법정동행정동도로위계구분광역도로구분도로종속구분
연번1.0000.129-0.0870.0590.0721.0001.0000.4250.3160.075
출입구일련번호0.1291.0000.5140.0000.0280.5680.5520.1620.1100.038
건물일련번호-0.0870.5141.0000.130-0.4670.3600.3460.3870.1330.647
본번0.0590.0000.1301.0000.0810.2070.1610.4770.6390.029
부번0.0720.028-0.4670.0811.0000.0610.0430.0500.0210.174
법정동1.0000.5680.3600.2070.0611.0000.9680.1890.3390.100
행정동1.0000.5520.3460.1610.0430.9681.0000.1670.2040.095
도로위계구분0.4250.1620.3870.4770.0500.1890.1671.0000.2170.021
광역도로구분0.3160.1100.1330.6390.0210.3390.2040.2171.0000.014
도로종속구분0.0750.0380.6470.0290.1740.1000.0950.0210.0141.000

Missing values

2023-12-13T02:55:44.822977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:55:45.093744image/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.
2023-12-13T02:55:45.271145image/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

연번행정구역법정동행정동출입구일련번호건물일련번호건물명도로위계구분광역도로구분도로종속구분건물용도도로명본번부번데이터기준일자
17179<NA>정읍시교암동상교동644213101<NA>길시군구도로1차 종속도로창고석고길96482023-01-19
15256<NA>정읍시산외면산외면4801298591<NA>길시군구도로1차 종속도로기타가축시설상두3길7532023-01-19
20381<NA>정읍시하북동수성동73121204<NA>길시군구도로1차 종속도로단독주택군대길8962023-01-19
30883<NA>정읍시옹동면옹동면2688734558<NA>길시군구도로2차 종속도로축사시목길25232023-01-19
28886<NA>정읍시영원면영원면1908247590<NA>길시군구도로주도로단독주택발립길7802023-01-19
25953<NA>정읍시신태인읍신태인읍3721973209<NA>길시군구도로주도로교회인교3길1502023-01-19
22403<NA>정읍시하북동수성동3889577599<NA>길시군구도로주도로단독주택하북1길7802023-01-19
3500<NA>정읍시고부면고부면171633306<NA>길시군구도로1차 종속도로창고상만1길21212023-01-19
13860<NA>정읍시산내면산내면4293792792<NA>길시군구도로주도로단독주택이화동길29202023-01-19
3478<NA>정읍시고부면고부면1763547396<NA>길시군구도로주도로단독주택만화길9502023-01-19
연번행정구역법정동행정동출입구일련번호건물일련번호건물명도로위계구분광역도로구분도로종속구분건물용도도로명본번부번데이터기준일자
29335<NA>정읍시영원면영원면2951569538<NA>길시군구도로주도로축사영원북길19502023-01-19
42637<NA>정읍시태인면태인면2419238599<NA>길시군구도로1차 종속도로단독주택외칠길33102023-01-19
3374<NA>정읍시고부면고부면1748153928<NA>길시군구도로주도로단독주택마정길2702023-01-19
28963<NA>정읍시영원면영원면2909173465<NA>길시군구도로주도로양수장(공개제한)부월길20102023-01-19
15740<NA>정읍시산외면산외면4258992505<NA>길시군구도로주도로단독주택운전3길1002023-01-19
27754<NA>정읍시연지동연지동1262055108성도24시 편의점길시군구도로주도로제1종근린생활시설연지3길7912023-01-19
7531<NA>정읍시상동내장상동52196103078<NA>로시군구도로1차 종속도로생활편익시설학산로89232023-01-19
36202<NA>정읍시장명동장명동335181477정읍제일교회로시군구도로주도로교회우암로8402023-01-19
7165<NA>정읍시상동내장상동1028784318<NA>로시군구도로주도로단독주택충정로11012023-01-19
28645<NA>정읍시영원면영원면186181724<NA>로시군구도로1차 종속도로단독주택구파로10352023-01-19

Duplicate rows

Most frequently occurring

연번행정구역법정동행정동출입구일련번호건물일련번호건물명도로위계구분광역도로구분도로종속구분건물용도도로명본번부번데이터기준일자# duplicates
0<NA>정읍시태인면태인면2514838709<NA>로시군구도로2차 종속도로단독주택정읍북로1331242023-01-192