Overview

Dataset statistics

Number of variables7
Number of observations8457
Missing cells331
Missing cells (%)0.6%
Duplicate rows6
Duplicate rows (%)0.1%
Total size in memory487.4 KiB
Average record size in memory59.0 B

Variable types

Text4
Numeric3

Dataset

Description전북특별자치도 전주시 내 다세대주택 및 오피스텔 현황으로 건물위치, 주택유형, 세대수, 건축연도 등을 제공합니다.항목 : 건물위치, 주택유형, 세대수, 건축연도담당부서: 건축과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15077153/fileData.do

Alerts

Dataset has 6 (0.1%) duplicate rowsDuplicates
도로명 주소 has 165 (2.0%) missing valuesMissing
세대수(객실수) is highly skewed (γ1 = 39.81112971)Skewed

Reproduction

Analysis started2024-03-14 18:46:39.180593
Analysis finished2024-03-14 18:46:44.183479
Duration5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도로명 주소
Text

MISSING 

Distinct8272
Distinct (%)99.8%
Missing165
Missing (%)2.0%
Memory size66.2 KiB
2024-03-15T03:46:45.588389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length24.460926
Min length21

Characters and Unicode

Total characters202830
Distinct characters212
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

Unique8252 ?
Unique (%)99.5%

Sample

1st row전북특별자치도 전주시 완산구 자만동3길 10
2nd row전북특별자치도 전주시 완산구 태진로 4
3rd row전북특별자치도 전주시 덕진구 모래내5길 14
4th row전북특별자치도 전주시 완산구 인봉1길 13-14
5th row전북특별자치도 전주시 완산구 서학로 39-3
ValueCountFrequency (%)
전북특별자치도 8292
20.0%
전주시 8292
20.0%
완산구 5046
 
12.2%
덕진구 3246
 
7.8%
10 134
 
0.3%
12 132
 
0.3%
9 130
 
0.3%
8 125
 
0.3%
13 122
 
0.3%
7 114
 
0.3%
Other values (2356) 15827
38.2%
2024-03-15T03:46:47.999972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33168
 
16.4%
전 16804
 
8.3%
구 8442
 
4.2%
주 8371
 
4.1%
도 8366
 
4.1%
북 8364
 
4.1%
자 8337
 
4.1%
시 8301
 
4.1%
특 8292
 
4.1%
별 8292
 
4.1%
Other values (202) 86093
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137054
67.6%
Space Separator 33168
 
16.4%
Decimal Number 27746
 
13.7%
Dash Punctuation 4862
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 16804
 
12.3%
구 8442
 
6.2%
주 8371
 
6.1%
도 8366
 
6.1%
북 8364
 
6.1%
자 8337
 
6.1%
시 8301
 
6.1%
특 8292
 
6.1%
별 8292
 
6.1%
치 8292
 
6.1%
Other values (190) 45193
33.0%
Decimal Number
ValueCountFrequency (%)
1 6776
24.4%
2 4299
15.5%
3 3740
13.5%
4 2927
10.5%
5 2346
 
8.5%
6 2112
 
7.6%
7 1597
 
5.8%
8 1494
 
5.4%
9 1266
 
4.6%
0 1189
 
4.3%
Space Separator
ValueCountFrequency (%)
33168
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4862
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137054
67.6%
Common 65776
32.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 16804
 
12.3%
구 8442
 
6.2%
주 8371
 
6.1%
도 8366
 
6.1%
북 8364
 
6.1%
자 8337
 
6.1%
시 8301
 
6.1%
특 8292
 
6.1%
별 8292
 
6.1%
치 8292
 
6.1%
Other values (190) 45193
33.0%
Common
ValueCountFrequency (%)
33168
50.4%
1 6776
 
10.3%
- 4862
 
7.4%
2 4299
 
6.5%
3 3740
 
5.7%
4 2927
 
4.4%
5 2346
 
3.6%
6 2112
 
3.2%
7 1597
 
2.4%
8 1494
 
2.3%
Other values (2) 2455
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137054
67.6%
ASCII 65776
32.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33168
50.4%
1 6776
 
10.3%
- 4862
 
7.4%
2 4299
 
6.5%
3 3740
 
5.7%
4 2927
 
4.4%
5 2346
 
3.6%
6 2112
 
3.2%
7 1597
 
2.4%
8 1494
 
2.3%
Other values (2) 2455
 
3.7%
Hangul
ValueCountFrequency (%)
전 16804
 
12.3%
구 8442
 
6.2%
주 8371
 
6.1%
도 8366
 
6.1%
북 8364
 
6.1%
자 8337
 
6.1%
시 8301
 
6.1%
특 8292
 
6.1%
별 8292
 
6.1%
치 8292
 
6.1%
Other values (190) 45193
33.0%

지번 주소
Text

Distinct8441
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
2024-03-15T03:46:49.405970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length33
Mean length27.318907
Min length22

Characters and Unicode

Total characters231036
Distinct characters77
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

Unique8426 ?
Unique (%)99.6%

Sample

1st row전북특별자치도 전주시 완산구 교동 54-22
2nd row전북특별자치도 전주시 완산구 태평동 83-36
3rd row전북특별자치도 전주시 덕진구 인후동2가 236-97
4th row전북특별자치도 전주시 완산구 중노송동 253-102
5th row전북특별자치도 전주시 완산구 동서학동 95
ValueCountFrequency (%)
전북특별자치도 8457
20.0%
전주시 8457
20.0%
완산구 5085
12.0%
덕진구 3372
 
8.0%
효자동3가 1642
 
3.9%
서신동 750
 
1.8%
인후동1가 686
 
1.6%
삼천동1가 677
 
1.6%
중화산동2가 599
 
1.4%
금암동 510
 
1.2%
Other values (7680) 12062
28.5%
2024-03-15T03:46:51.157332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34076
 
14.7%
전 16921
 
7.3%
1 11262
 
4.9%
자 10849
 
4.7%
북 8550
 
3.7%
동 8510
 
3.7%
구 8459
 
3.7%
치 8457
 
3.7%
도 8457
 
3.7%
특 8457
 
3.7%
Other values (67) 107038
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142566
61.7%
Decimal Number 46214
 
20.0%
Space Separator 34076
 
14.7%
Dash Punctuation 8180
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 16921
 
11.9%
자 10849
 
7.6%
북 8550
 
6.0%
동 8510
 
6.0%
구 8459
 
5.9%
치 8457
 
5.9%
도 8457
 
5.9%
특 8457
 
5.9%
시 8457
 
5.9%
주 8457
 
5.9%
Other values (55) 46992
33.0%
Decimal Number
ValueCountFrequency (%)
1 11262
24.4%
2 6296
13.6%
3 5094
11.0%
6 4852
10.5%
5 3840
 
8.3%
7 3360
 
7.3%
4 3290
 
7.1%
8 3039
 
6.6%
9 2694
 
5.8%
0 2487
 
5.4%
Space Separator
ValueCountFrequency (%)
34076
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8180
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142566
61.7%
Common 88470
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 16921
 
11.9%
자 10849
 
7.6%
북 8550
 
6.0%
동 8510
 
6.0%
구 8459
 
5.9%
치 8457
 
5.9%
도 8457
 
5.9%
특 8457
 
5.9%
시 8457
 
5.9%
주 8457
 
5.9%
Other values (55) 46992
33.0%
Common
ValueCountFrequency (%)
34076
38.5%
1 11262
 
12.7%
- 8180
 
9.2%
2 6296
 
7.1%
3 5094
 
5.8%
6 4852
 
5.5%
5 3840
 
4.3%
7 3360
 
3.8%
4 3290
 
3.7%
8 3039
 
3.4%
Other values (2) 5181
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142566
61.7%
ASCII 88470
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34076
38.5%
1 11262
 
12.7%
- 8180
 
9.2%
2 6296
 
7.1%
3 5094
 
5.8%
6 4852
 
5.5%
5 3840
 
4.3%
7 3360
 
3.8%
4 3290
 
3.7%
8 3039
 
3.4%
Other values (2) 5181
 
5.9%
Hangul
ValueCountFrequency (%)
전 16921
 
11.9%
자 10849
 
7.6%
북 8550
 
6.0%
동 8510
 
6.0%
구 8459
 
5.9%
치 8457
 
5.9%
도 8457
 
5.9%
특 8457
 
5.9%
시 8457
 
5.9%
주 8457
 
5.9%
Other values (55) 46992
33.0%

위도
Real number (ℝ)

Distinct8340
Distinct (%)99.6%
Missing83
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean35.825874
Minimum35.760948
Maximum35.893731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.5 KiB
2024-03-15T03:46:51.406579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.760948
5-th percentile35.794692
Q135.8136
median35.827542
Q335.837003
95-th percentile35.85186
Maximum35.893731
Range0.13278323
Interquartile range (IQR)0.02340333

Descriptive statistics

Standard deviation0.017608922
Coefficient of variation (CV)0.0004915141
Kurtosis0.014574823
Mean35.825874
Median Absolute Deviation (MAD)0.01115882
Skewness-0.17235505
Sum300005.87
Variance0.00031007414
MonotonicityNot monotonic
2024-03-15T03:46:51.699326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.83880502 3
 
< 0.1%
35.83222578 2
 
< 0.1%
35.81227299 2
 
< 0.1%
35.82752582 2
 
< 0.1%
35.81010678 2
 
< 0.1%
35.82176366 2
 
< 0.1%
35.8107252 2
 
< 0.1%
35.80119382 2
 
< 0.1%
35.80308812 2
 
< 0.1%
35.83685927 2
 
< 0.1%
Other values (8330) 8353
98.8%
(Missing) 83
 
1.0%
ValueCountFrequency (%)
35.76094814 1
< 0.1%
35.76260666 1
< 0.1%
35.76289012 1
< 0.1%
35.7634404 1
< 0.1%
35.76383222 1
< 0.1%
35.7644343 1
< 0.1%
35.77044409 1
< 0.1%
35.77261815 1
< 0.1%
35.77330877 1
< 0.1%
35.77515938 1
< 0.1%
ValueCountFrequency (%)
35.89373137 1
< 0.1%
35.88823894 1
< 0.1%
35.88804533 1
< 0.1%
35.88755244 1
< 0.1%
35.88252604 1
< 0.1%
35.88227154 1
< 0.1%
35.87798923 1
< 0.1%
35.87660545 1
< 0.1%
35.87655668 1
< 0.1%
35.8761457 1
< 0.1%

경도
Real number (ℝ)

Distinct8256
Distinct (%)98.6%
Missing83
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean127.12166
Minimum127.03898
Maximum127.20082
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.5 KiB
2024-03-15T03:46:52.080728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.03898
5-th percentile127.08638
Q1127.10333
median127.11873
Q3127.13673
95-th percentile127.16702
Maximum127.20082
Range0.1618407
Interquartile range (IQR)0.033402175

Descriptive statistics

Standard deviation0.024468644
Coefficient of variation (CV)0.0001924821
Kurtosis-0.27905689
Mean127.12166
Median Absolute Deviation (MAD)0.0162879
Skewness0.27056416
Sum1064516.8
Variance0.00059871455
MonotonicityNot monotonic
2024-03-15T03:46:52.539674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.059285 3
 
< 0.1%
127.1178434 3
 
< 0.1%
127.1030717 3
 
< 0.1%
127.1036289 3
 
< 0.1%
127.1189116 2
 
< 0.1%
127.1206557 2
 
< 0.1%
127.1334392 2
 
< 0.1%
127.1013502 2
 
< 0.1%
127.1343996 2
 
< 0.1%
127.1187013 2
 
< 0.1%
Other values (8246) 8350
98.7%
(Missing) 83
 
1.0%
ValueCountFrequency (%)
127.0389813 1
 
< 0.1%
127.059285 3
< 0.1%
127.0592943 1
 
< 0.1%
127.0596511 1
 
< 0.1%
127.0596678 1
 
< 0.1%
127.0597236 1
 
< 0.1%
127.0597786 1
 
< 0.1%
127.0598525 1
 
< 0.1%
127.0598836 1
 
< 0.1%
127.0599174 1
 
< 0.1%
ValueCountFrequency (%)
127.200822 1
< 0.1%
127.1776892 1
< 0.1%
127.176867 1
< 0.1%
127.1761612 1
< 0.1%
127.1760464 1
< 0.1%
127.1759108 1
< 0.1%
127.17583 1
< 0.1%
127.1757711 1
< 0.1%
127.1757476 1
< 0.1%
127.1756918 1
< 0.1%

주택유형구분
Text

Distinct719
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
2024-03-15T03:46:53.460025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length8.3258839
Min length2

Characters and Unicode

Total characters70412
Distinct characters122
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique491 ?
Unique (%)5.8%

Sample

1st row단독주택
2nd row단독주택,제1종근린생활시설
3rd row주택, 소매점, 화장실
4th row주택, 물치
5th row다세대주택, 독서실, 사무실, 창고
ValueCountFrequency (%)
단독주택 4264
41.2%
다가구주택 699
 
6.8%
근린생활시설 689
 
6.7%
단독주택,제1종근린생활시설 678
 
6.6%
단독주택(다가구주택 437
 
4.2%
제1종근린생활시설 312
 
3.0%
주택 272
 
2.6%
단독주택(3가구 250
 
2.4%
다세대주택 248
 
2.4%
제2종근린생활시설 214
 
2.1%
Other values (419) 2280
22.0%
2024-03-15T03:46:54.722104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 8820
 
12.5%
택 8819
 
12.5%
단 6652
 
9.4%
독 6651
 
9.4%
구 2721
 
3.9%
가 2720
 
3.9%
, 2602
 
3.7%
생 2464
 
3.5%
근 2462
 
3.5%
시 2438
 
3.5%
Other values (112) 24063
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59005
83.8%
Decimal Number 3071
 
4.4%
Other Punctuation 2652
 
3.8%
Open Punctuation 1887
 
2.7%
Space Separator 1887
 
2.7%
Close Punctuation 1885
 
2.7%
Dash Punctuation 24
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 8820
14.9%
택 8819
14.9%
단 6652
11.3%
독 6651
11.3%
구 2721
 
4.6%
가 2720
 
4.6%
생 2464
 
4.2%
근 2462
 
4.2%
시 2438
 
4.1%
설 2434
 
4.1%
Other values (90) 12824
21.7%
Decimal Number
ValueCountFrequency (%)
1 1466
47.7%
2 656
21.4%
3 438
 
14.3%
5 150
 
4.9%
4 147
 
4.8%
9 52
 
1.7%
8 52
 
1.7%
6 48
 
1.6%
0 32
 
1.0%
7 30
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 2602
98.1%
. 17
 
0.6%
& 14
 
0.5%
/ 8
 
0.3%
: 6
 
0.2%
· 3
 
0.1%
' 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1887
100.0%
Space Separator
ValueCountFrequency (%)
1887
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1885
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59005
83.8%
Common 11407
 
16.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 8820
14.9%
택 8819
14.9%
단 6652
11.3%
독 6651
11.3%
구 2721
 
4.6%
가 2720
 
4.6%
생 2464
 
4.2%
근 2462
 
4.2%
시 2438
 
4.1%
설 2434
 
4.1%
Other values (90) 12824
21.7%
Common
ValueCountFrequency (%)
, 2602
22.8%
( 1887
16.5%
1887
16.5%
) 1885
16.5%
1 1466
12.9%
2 656
 
5.8%
3 438
 
3.8%
5 150
 
1.3%
4 147
 
1.3%
9 52
 
0.5%
Other values (12) 237
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59004
83.8%
ASCII 11404
 
16.2%
None 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 8820
14.9%
택 8819
14.9%
단 6652
11.3%
독 6651
11.3%
구 2721
 
4.6%
가 2720
 
4.6%
생 2464
 
4.2%
근 2462
 
4.2%
시 2438
 
4.1%
설 2434
 
4.1%
Other values (89) 12823
21.7%
ASCII
ValueCountFrequency (%)
, 2602
22.8%
( 1887
16.5%
1887
16.5%
) 1885
16.5%
1 1466
12.9%
2 656
 
5.8%
3 438
 
3.8%
5 150
 
1.3%
4 147
 
1.3%
9 52
 
0.5%
Other values (11) 234
 
2.1%
None
ValueCountFrequency (%)
· 3
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
100.0%

세대수(객실수)
Real number (ℝ)

SKEWED 

Distinct42
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5083363
Minimum2
Maximum826
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.5 KiB
2024-03-15T03:46:55.011946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median8
Q311
95-th percentile17
Maximum826
Range824
Interquartile range (IQR)7

Descriptive statistics

Standard deviation13.035138
Coefficient of variation (CV)1.5320431
Kurtosis2160.051
Mean8.5083363
Median Absolute Deviation (MAD)3
Skewness39.81113
Sum71955
Variance169.91481
MonotonicityNot monotonic
2024-03-15T03:46:55.303213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
3 1365
16.1%
10 1069
12.6%
11 794
9.4%
9 650
7.7%
4 617
 
7.3%
5 581
 
6.9%
8 546
 
6.5%
2 504
 
6.0%
6 425
 
5.0%
12 349
 
4.1%
Other values (32) 1557
18.4%
ValueCountFrequency (%)
2 504
 
6.0%
3 1365
16.1%
4 617
7.3%
5 581
6.9%
6 425
 
5.0%
7 305
 
3.6%
8 546
 
6.5%
9 650
7.7%
10 1069
12.6%
11 794
9.4%
ValueCountFrequency (%)
826 1
< 0.1%
514 1
< 0.1%
288 1
< 0.1%
276 1
< 0.1%
191 1
< 0.1%
182 1
< 0.1%
172 1
< 0.1%
167 1
< 0.1%
159 2
< 0.1%
110 1
< 0.1%

건축연도
Text

Distinct4595
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
2024-03-15T03:46:56.593451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9929053
Min length4

Characters and Unicode

Total characters84510
Distinct characters15
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

Unique2515 ?
Unique (%)29.7%

Sample

1st row1948-04-18
2nd row1969-11-04
3rd row1972-07-20
4th row1973-10-10
5th row1974-02-01
ValueCountFrequency (%)
2011-01-04 13
 
0.2%
2012-06-11 11
 
0.1%
2011-12-29 11
 
0.1%
2011-01-05 11
 
0.1%
확인불가 10
 
0.1%
2011-02-23 10
 
0.1%
2011-11-25 10
 
0.1%
2012-02-29 10
 
0.1%
2011-12-26 9
 
0.1%
2011-11-02 9
 
0.1%
Other values (4585) 8353
98.8%
2024-03-15T03:46:58.275734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19502
23.1%
- 16894
20.0%
1 14900
17.6%
2 13180
15.6%
9 5647
 
6.7%
8 2727
 
3.2%
3 2586
 
3.1%
7 2381
 
2.8%
4 2350
 
2.8%
6 2207
 
2.6%
Other values (5) 2136
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67576
80.0%
Dash Punctuation 16894
 
20.0%
Other Letter 40
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19502
28.9%
1 14900
22.0%
2 13180
19.5%
9 5647
 
8.4%
8 2727
 
4.0%
3 2586
 
3.8%
7 2381
 
3.5%
4 2350
 
3.5%
6 2207
 
3.3%
5 2096
 
3.1%
Other Letter
ValueCountFrequency (%)
확 10
25.0%
인 10
25.0%
불 10
25.0%
가 10
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 16894
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84470
> 99.9%
Hangul 40
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19502
23.1%
- 16894
20.0%
1 14900
17.6%
2 13180
15.6%
9 5647
 
6.7%
8 2727
 
3.2%
3 2586
 
3.1%
7 2381
 
2.8%
4 2350
 
2.8%
6 2207
 
2.6%
Hangul
ValueCountFrequency (%)
확 10
25.0%
인 10
25.0%
불 10
25.0%
가 10
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84470
> 99.9%
Hangul 40
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19502
23.1%
- 16894
20.0%
1 14900
17.6%
2 13180
15.6%
9 5647
 
6.7%
8 2727
 
3.2%
3 2586
 
3.1%
7 2381
 
2.8%
4 2350
 
2.8%
6 2207
 
2.6%
Hangul
ValueCountFrequency (%)
확 10
25.0%
인 10
25.0%
불 10
25.0%
가 10
25.0%

Interactions

2024-03-15T03:46:42.051559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:46:40.169873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:46:41.071371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:46:42.334883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:46:40.455682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:46:41.372185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:46:42.890808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:46:40.756942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:46:41.756788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T03:46:58.539037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도세대수(객실수)
위도1.0000.5980.000
경도0.5981.0000.095
세대수(객실수)0.0000.0951.000
2024-03-15T03:46:58.716272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도세대수(객실수)
위도1.0000.0820.098
경도0.0821.0000.124
세대수(객실수)0.0980.1241.000

Missing values

2024-03-15T03:46:43.244063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T03:46:43.659775image/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.
2024-03-15T03:46:43.999581image/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

도로명 주소지번 주소위도경도주택유형구분세대수(객실수)건축연도
0전북특별자치도 전주시 완산구 자만동3길 10전북특별자치도 전주시 완산구 교동 54-2235.814567127.156228단독주택21948-04-18
1전북특별자치도 전주시 완산구 태진로 4전북특별자치도 전주시 완산구 태평동 83-3635.821337127.137944단독주택,제1종근린생활시설21969-11-04
2전북특별자치도 전주시 덕진구 모래내5길 14전북특별자치도 전주시 덕진구 인후동2가 236-9735.833756127.14445주택, 소매점, 화장실41972-07-20
3전북특별자치도 전주시 완산구 인봉1길 13-14전북특별자치도 전주시 완산구 중노송동 253-10235.82498127.154747주택, 물치21973-10-10
4전북특별자치도 전주시 완산구 서학로 39-3전북특별자치도 전주시 완산구 동서학동 9535.809835127.15387다세대주택, 독서실, 사무실, 창고61974-02-01
5전북특별자치도 전주시 완산구 경기전길 10-10전북특별자치도 전주시 완산구 경원동2가 2-335.818936127.149629단독주택41976-05-19
6전북특별자치도 전주시 덕진구 건산로 122전북특별자치도 전주시 덕진구 인후동1가 655-635.832904127.150494단독주택, 제1종근린생활시설21976-06-28
7전북특별자치도 전주시 덕진구 건산로 122전북특별자치도 전주시 덕진구 인후동1가 655-635.832904127.150494단독주택21976-06-28
8전북특별자치도 전주시 덕진구 숲정이1길 7전북특별자치도 전주시 덕진구 진북동 834-9835.83033127.129296다세대주택51978-06-09
9전북특별자치도 전주시 덕진구 태진로 133-2전북특별자치도 전주시 덕진구 금암동 456-635.83288127.135103단독주택(다가구주택)101978-08-10
도로명 주소지번 주소위도경도주택유형구분세대수(객실수)건축연도
8447전북특별자치도 전주시 덕진구 도당산4길 62전북특별자치도 전주시 덕진구 우아동3가 748-7835.846225127.154869단독주택7확인불가
8448전북특별자치도 전주시 덕진구 도당산2길 24전북특별자치도 전주시 덕진구 우아동3가 750-3435.845368127.155465단독주택(3가구)3확인불가
8449전북특별자치도 전주시 덕진구 진버들2길 12-12전북특별자치도 전주시 덕진구 인후동1가 457-435.835653127.158758단독주택(3가구)3확인불가
8450전북특별자치도 전주시 완산구 마당재2길 78전북특별자치도 전주시 완산구 남노송동 159-4335.819894127.157459근린생활시설, 주택2확인불가
8451전북특별자치도 전주시 완산구 송정2길 16-11전북특별자치도 전주시 완산구 삼천동1가 581-1235.800393127.118326다세대주택4확인불가
8452전북특별자치도 전주시 완산구 안행5길 5-3전북특별자치도 전주시 완산구 삼천동1가 742-1335.801502127.132316근린생활시설, 단독다가구주택3확인불가
8453전북특별자치도 전주시 완산구 서신천변15길 7-1전북특별자치도 전주시 완산구 서신동 801-1935.831613127.113493근린생활시설, 다가구주택3확인불가
8454전북특별자치도 전주시 완산구 서신천변4길 7전북특별자치도 전주시 완산구 서신동 840-1135.827956127.114888단독주택(5가구)5확인불가
8455전북특별자치도 전주시 완산구 따박골로 57-10전북특별자치도 전주시 완산구 중화산동2가 535-1035.811526127.125841근린생활시설, 주택(3가구)4확인불가
8456전북특별자치도 전주시 완산구 맏내4길 16-5전북특별자치도 전주시 완산구 평화동1가 702-235.794122127.130234단독주택,제2종근린생활시설6확인불가

Duplicate rows

Most frequently occurring

도로명 주소지번 주소위도경도주택유형구분세대수(객실수)건축연도# duplicates
0전북특별자치도 전주시 덕진구 솔내로 19전북특별자치도 전주시 덕진구 송천동1가 25135.852803127.122363단독주택(다가구주택)92020-02-112
1전북특별자치도 전주시 완산구 강당1길 26전북특별자치도 전주시 완산구 서완산동2가 334-435.810557127.133439단독주택(다가구주택)92019-12-042
2전북특별자치도 전주시 완산구 곤지산1길 17-1전북특별자치도 전주시 완산구 동완산동 20-435.810725127.146832단독주택22014-03-212
3전북특별자치도 전주시 완산구 만지길 22전북특별자치도 전주시 완산구 효자동3가 111635.821227127.090558단독주택41999-04-122
4전북특별자치도 전주시 완산구 백마산길 72-1전북특별자치도 전주시 완산구 효자동3가 132935.817642127.087088단독주택(다가구주택)82002-02-212
5<NA>전북특별자치도 전주시 덕진구 장동 111135.838805127.059285오피스텔1592020-07-242