Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory125.0 B

Variable types

Numeric6
Categorical4
Text4

Dataset

Description경기도 수원시의 우편번호 정보 데이터 (수원시의 도로명 주소(영문명 포함) 및 건물명, 법정동 등의 우편번호 관련 정보를 제공함)
Author과학기술정보통신부 우정사업본부
URLhttps://www.data.go.kr/data/15104404/fileData.do

Alerts

시도 has constant value ""Constant
시도영문 has constant value ""Constant
시군구영문 is highly overall correlated with 우편번호 and 4 other fieldsHigh correlation
시군구 is highly overall correlated with 우편번호 and 4 other fieldsHigh correlation
우편번호 is highly overall correlated with 시군구 and 1 other fieldsHigh correlation
도로명코드 is highly overall correlated with 건물관리번호 and 3 other fieldsHigh correlation
건물관리번호 is highly overall correlated with 도로명코드 and 3 other fieldsHigh correlation
법정동코드 is highly overall correlated with 도로명코드 and 3 other fieldsHigh correlation
건물관리번호 is highly skewed (γ1 = 23.27127939)Skewed
건물번호부번 has 5255 (52.5%) zerosZeros

Reproduction

Analysis started2023-12-12 00:35:01.985219
Analysis finished2023-12-12 00:35:55.449053
Duration53.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct456
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16438.234
Minimum16200
Maximum16714
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:35:55.532328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16200
5-th percentile16221
Q116282
median16443
Q316578
95-th percentile16671
Maximum16714
Range514
Interquartile range (IQR)296

Descriptive statistics

Standard deviation153.99689
Coefficient of variation (CV)0.0093682141
Kurtosis-1.3875327
Mean16438.234
Median Absolute Deviation (MAD)146
Skewness0.067765026
Sum1.6438234 × 108
Variance23715.043
MonotonicityNot monotonic
2023-12-12T09:35:55.698862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16439 149
 
1.5%
16443 113
 
1.1%
16577 110
 
1.1%
16649 101
 
1.0%
16243 97
 
1.0%
16619 96
 
1.0%
16705 96
 
1.0%
16245 90
 
0.9%
16273 86
 
0.9%
16213 82
 
0.8%
Other values (446) 8980
89.8%
ValueCountFrequency (%)
16200 6
 
0.1%
16201 23
0.2%
16202 5
 
0.1%
16203 32
0.3%
16204 15
 
0.1%
16205 51
0.5%
16206 1
 
< 0.1%
16208 7
 
0.1%
16209 8
 
0.1%
16210 20
 
0.2%
ValueCountFrequency (%)
16714 1
 
< 0.1%
16713 2
 
< 0.1%
16712 2
 
< 0.1%
16710 4
 
< 0.1%
16709 2
 
< 0.1%
16708 1
 
< 0.1%
16706 19
 
0.2%
16705 96
1.0%
16704 9
 
0.1%
16703 3
 
< 0.1%

시도
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 10000
100.0%

Length

2023-12-12T09:35:55.828131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:35:55.913908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 10000
100.0%

시도영문
Categorical

CONSTANT 

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

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGyeonggi-do
2nd rowGyeonggi-do
3rd rowGyeonggi-do
4th rowGyeonggi-do
5th rowGyeonggi-do

Common Values

ValueCountFrequency (%)
Gyeonggi-do 10000
100.0%

Length

2023-12-12T09:35:56.013315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:35:56.098388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
gyeonggi-do 10000
100.0%

시군구
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시 권선구
3281 
수원시 팔달구
2783 
수원시 장안구
2706 
수원시 영통구
1230 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수원시 권선구
2nd row수원시 장안구
3rd row수원시 영통구
4th row수원시 영통구
5th row수원시 권선구

Common Values

ValueCountFrequency (%)
수원시 권선구 3281
32.8%
수원시 팔달구 2783
27.8%
수원시 장안구 2706
27.1%
수원시 영통구 1230
 
12.3%

Length

2023-12-12T09:35:56.200996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:35:56.294453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수원시 10000
50.0%
권선구 3281
 
16.4%
팔달구 2783
 
13.9%
장안구 2706
 
13.5%
영통구 1230
 
6.2%

시군구영문
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Gwonseon-gu, Suwon-si
3281 
Paldal-gu, Suwon-si
2783 
Jangan-gu, Suwon-si
2706 
Yeongtong-gu, Suwon-si
1230 

Length

Max length22
Median length19
Mean length20.0252
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGwonseon-gu, Suwon-si
2nd rowJangan-gu, Suwon-si
3rd rowYeongtong-gu, Suwon-si
4th rowYeongtong-gu, Suwon-si
5th rowGwonseon-gu, Suwon-si

Common Values

ValueCountFrequency (%)
Gwonseon-gu, Suwon-si 3281
32.8%
Paldal-gu, Suwon-si 2783
27.8%
Jangan-gu, Suwon-si 2706
27.1%
Yeongtong-gu, Suwon-si 1230
 
12.3%

Length

2023-12-12T09:35:56.414217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:35:56.534120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
suwon-si 10000
50.0%
gwonseon-gu 3281
 
16.4%
paldal-gu 2783
 
13.9%
jangan-gu 2706
 
13.5%
yeongtong-gu 1230
 
6.2%

도로명코드
Real number (ℝ)

HIGH CORRELATION 

Distinct1503
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1113908 × 1011
Minimum4.11111 × 1011
Maximum4.1117485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:35:56.667924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.11111 × 1011
5-th percentile4.1111318 × 1011
Q14.1111432 × 1011
median4.1113433 × 1011
Q34.1115433 × 1011
95-th percentile4.1117433 × 1011
Maximum4.1117485 × 1011
Range63848205
Interquartile range (IQR)40005773

Descriptive statistics

Standard deviation19752814
Coefficient of variation (CV)4.8044118 × 10-5
Kurtosis-1.0009614
Mean4.1113908 × 1011
Median Absolute Deviation (MAD)20002881
Skewness0.24335402
Sum4.1113908 × 1015
Variance3.9017367 × 1014
MonotonicityNot monotonic
2023-12-12T09:35:56.819059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
411113176011 76
 
0.8%
411134325192 74
 
0.7%
411133012006 66
 
0.7%
411153176013 56
 
0.6%
411152012001 54
 
0.5%
411153175031 54
 
0.5%
411153012006 51
 
0.5%
411112012008 51
 
0.5%
411153176018 50
 
0.5%
411133175010 48
 
0.5%
Other values (1493) 9420
94.2%
ValueCountFrequency (%)
411111000022 1
 
< 0.1%
411112012001 14
 
0.1%
411112012008 51
0.5%
411113012001 8
 
0.1%
411113012005 15
 
0.1%
411113012006 22
0.2%
411113174001 28
0.3%
411113174002 27
0.3%
411113174003 23
0.2%
411113174004 1
 
< 0.1%
ValueCountFrequency (%)
411174848227 25
0.2%
411174430291 8
 
0.1%
411174430283 1
 
< 0.1%
411174331259 2
 
< 0.1%
411174331258 1
 
< 0.1%
411174331257 1
 
< 0.1%
411174331256 16
0.2%
411174331255 2
 
< 0.1%
411174331254 5
 
0.1%
411174331250 5
 
0.1%

도로명
Text

Distinct1464
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T09:35:57.092757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.7549
Min length3

Characters and Unicode

Total characters67549
Distinct characters137
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

Unique216 ?
Unique (%)2.2%

Sample

1st row평동로58번길
2nd row수성로289번길
3rd row중부대로256번길
4th row동수원로537번길
5th row정조로378번길
ValueCountFrequency (%)
정조로 139
 
1.4%
경수대로 110
 
1.1%
수원천로 85
 
0.9%
세지로 83
 
0.8%
장안로 76
 
0.8%
동수원로146번길 74
 
0.7%
창룡대로 70
 
0.7%
덕영대로 60
 
0.6%
권선로 58
 
0.6%
창룡문로 56
 
0.6%
Other values (1454) 9189
91.9%
2023-12-12T09:35:57.538101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 10000
 
14.8%
번 7452
 
11.0%
길 7452
 
11.0%
1 3320
 
4.9%
2 2290
 
3.4%
3 2062
 
3.1%
5 1952
 
2.9%
4 1927
 
2.9%
6 1754
 
2.6%
7 1510
 
2.2%
Other values (127) 27830
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48524
71.8%
Decimal Number 19025
 
28.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 10000
20.6%
번 7452
15.4%
길 7452
15.4%
수 1479
 
3.0%
대 1375
 
2.8%
세 850
 
1.8%
원 813
 
1.7%
정 786
 
1.6%
조 653
 
1.3%
경 645
 
1.3%
Other values (117) 17019
35.1%
Decimal Number
ValueCountFrequency (%)
1 3320
17.5%
2 2290
12.0%
3 2062
10.8%
5 1952
10.3%
4 1927
10.1%
6 1754
9.2%
7 1510
7.9%
9 1485
7.8%
8 1424
7.5%
0 1301
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48524
71.8%
Common 19025
 
28.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 10000
20.6%
번 7452
15.4%
길 7452
15.4%
수 1479
 
3.0%
대 1375
 
2.8%
세 850
 
1.8%
원 813
 
1.7%
정 786
 
1.6%
조 653
 
1.3%
경 645
 
1.3%
Other values (117) 17019
35.1%
Common
ValueCountFrequency (%)
1 3320
17.5%
2 2290
12.0%
3 2062
10.8%
5 1952
10.3%
4 1927
10.1%
6 1754
9.2%
7 1510
7.9%
9 1485
7.8%
8 1424
7.5%
0 1301
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48524
71.8%
ASCII 19025
 
28.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 10000
20.6%
번 7452
15.4%
길 7452
15.4%
수 1479
 
3.0%
대 1375
 
2.8%
세 850
 
1.8%
원 813
 
1.7%
정 786
 
1.6%
조 653
 
1.3%
경 645
 
1.3%
Other values (117) 17019
35.1%
ASCII
ValueCountFrequency (%)
1 3320
17.5%
2 2290
12.0%
3 2062
10.8%
5 1952
10.3%
4 1927
10.1%
6 1754
9.2%
7 1510
7.9%
9 1485
7.8%
8 1424
7.5%
0 1301
 
6.8%

도로명영문
Text

Distinct1464
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T09:35:57.824494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length19.3998
Min length6

Characters and Unicode

Total characters193998
Distinct characters51
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique216 ?
Unique (%)2.2%

Sample

1st rowPyeongdong-ro 58beon-gil
2nd rowSuseong-ro 289beon-gil
3rd rowJungbu-daero 256beon-gil
4th rowDongsuwon-ro 537beon-gil
5th rowJeongjo-ro 378beon-gil
ValueCountFrequency (%)
gyeongsu-daero 645
 
3.6%
jeongjo-ro 514
 
2.9%
seji-ro 496
 
2.8%
deogyeong-daero 339
 
1.9%
jangan-ro 272
 
1.5%
suseong-ro 262
 
1.5%
paldalmun-ro 255
 
1.4%
gwonseon-ro 239
 
1.3%
paldal-ro 232
 
1.3%
segwon-ro 194
 
1.1%
Other values (711) 14289
80.6%
2023-12-12T09:35:58.262053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 26954
13.9%
n 18352
 
9.5%
- 17450
 
9.0%
e 15732
 
8.1%
g 14657
 
7.6%
r 10505
 
5.4%
l 9262
 
4.8%
i 8458
 
4.4%
b 7981
 
4.1%
7737
 
4.0%
Other values (41) 56910
29.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 139784
72.1%
Decimal Number 19025
 
9.8%
Dash Punctuation 17450
 
9.0%
Uppercase Letter 10002
 
5.2%
Space Separator 7737
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 26954
19.3%
n 18352
13.1%
e 15732
11.3%
g 14657
10.5%
r 10505
 
7.5%
l 9262
 
6.6%
i 8458
 
6.1%
b 7981
 
5.7%
a 7589
 
5.4%
u 3991
 
2.9%
Other values (12) 16303
11.7%
Uppercase Letter
ValueCountFrequency (%)
S 2415
24.1%
G 2010
20.1%
J 1223
12.2%
D 827
 
8.3%
P 802
 
8.0%
M 596
 
6.0%
H 589
 
5.9%
C 510
 
5.1%
Y 349
 
3.5%
W 221
 
2.2%
Other values (7) 460
 
4.6%
Decimal Number
ValueCountFrequency (%)
1 3320
17.5%
2 2290
12.0%
3 2062
10.8%
5 1952
10.3%
4 1927
10.1%
6 1754
9.2%
7 1510
7.9%
9 1485
7.8%
8 1424
7.5%
0 1301
 
6.8%
Dash Punctuation
ValueCountFrequency (%)
- 17450
100.0%
Space Separator
ValueCountFrequency (%)
7737
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 149786
77.2%
Common 44212
 
22.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 26954
18.0%
n 18352
12.3%
e 15732
10.5%
g 14657
9.8%
r 10505
 
7.0%
l 9262
 
6.2%
i 8458
 
5.6%
b 7981
 
5.3%
a 7589
 
5.1%
u 3991
 
2.7%
Other values (29) 26305
17.6%
Common
ValueCountFrequency (%)
- 17450
39.5%
7737
17.5%
1 3320
 
7.5%
2 2290
 
5.2%
3 2062
 
4.7%
5 1952
 
4.4%
4 1927
 
4.4%
6 1754
 
4.0%
7 1510
 
3.4%
9 1485
 
3.4%
Other values (2) 2725
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193998
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 26954
13.9%
n 18352
 
9.5%
- 17450
 
9.0%
e 15732
 
8.1%
g 14657
 
7.6%
r 10505
 
5.4%
l 9262
 
4.8%
i 8458
 
4.4%
b 7981
 
4.1%
7737
 
4.0%
Other values (41) 56910
29.3%

건물번호본번
Real number (ℝ)

Distinct741
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.4621
Minimum1
Maximum2388
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:35:58.407584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q116
median31
Q363
95-th percentile418
Maximum2388
Range2387
Interquartile range (IQR)47

Descriptive statistics

Standard deviation211.65356
Coefficient of variation (CV)2.3141122
Kurtosis35.425958
Mean91.4621
Median Absolute Deviation (MAD)19
Skewness5.3446176
Sum914621
Variance44797.23
MonotonicityNot monotonic
2023-12-12T09:35:58.551171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 224
 
2.2%
14 222
 
2.2%
10 212
 
2.1%
12 210
 
2.1%
9 206
 
2.1%
17 204
 
2.0%
6 191
 
1.9%
18 191
 
1.9%
11 191
 
1.9%
23 189
 
1.9%
Other values (731) 7960
79.6%
ValueCountFrequency (%)
1 73
 
0.7%
2 78
 
0.8%
3 100
1.0%
4 88
 
0.9%
5 162
1.6%
6 191
1.9%
7 224
2.2%
8 173
1.7%
9 206
2.1%
10 212
2.1%
ValueCountFrequency (%)
2388 1
< 0.1%
2303 1
< 0.1%
2287 1
< 0.1%
2201 1
< 0.1%
2193 1
< 0.1%
2189 1
< 0.1%
2187 1
< 0.1%
2185 1
< 0.1%
2175 1
< 0.1%
2161 1
< 0.1%

건물번호부번
Real number (ℝ)

ZEROS 

Distinct96
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0075
Minimum0
Maximum220
Zeros5255
Zeros (%)52.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:35:58.665663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile21
Maximum220
Range220
Interquartile range (IQR)7

Descriptive statistics

Standard deviation10.18767
Coefficient of variation (CV)2.0344823
Kurtosis72.963152
Mean5.0075
Median Absolute Deviation (MAD)0
Skewness6.1242525
Sum50075
Variance103.78862
MonotonicityNot monotonic
2023-12-12T09:35:58.777572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5255
52.5%
1 605
 
6.0%
3 323
 
3.2%
6 310
 
3.1%
4 299
 
3.0%
5 298
 
3.0%
2 297
 
3.0%
7 258
 
2.6%
8 240
 
2.4%
9 204
 
2.0%
Other values (86) 1911
 
19.1%
ValueCountFrequency (%)
0 5255
52.5%
1 605
 
6.0%
2 297
 
3.0%
3 323
 
3.2%
4 299
 
3.0%
5 298
 
3.0%
6 310
 
3.1%
7 258
 
2.6%
8 240
 
2.4%
9 204
 
2.0%
ValueCountFrequency (%)
220 1
< 0.1%
216 1
< 0.1%
149 1
< 0.1%
145 1
< 0.1%
143 1
< 0.1%
134 1
< 0.1%
130 1
< 0.1%
120 1
< 0.1%
117 1
< 0.1%
115 1
< 0.1%

건물관리번호
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct4114
Distinct (%)41.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1114383 × 1024
Minimum4.1111129 × 1024
Maximum4.1590121 × 1024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:35:58.896082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.1111129 × 1024
5-th percentile4.111113 × 1024
Q14.1111137 × 1024
median4.1113133 × 1024
Q34.1115138 × 1024
95-th percentile4.1117102 × 1024
Maximum4.1590121 × 1024
Range4.78992 × 1022
Interquartile range (IQR)4.001 × 1020

Descriptive statistics

Standard deviation1.7573232 × 1021
Coefficient of variation (CV)0.00042742297
Kurtosis559.45921
Mean4.1114383 × 1024
Median Absolute Deviation (MAD)1.999 × 1020
Skewness23.271279
Sum4.1114383 × 1028
Variance3.0881848 × 1042
MonotonicityNot monotonic
2023-12-12T09:35:59.013164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.1113131001001696e+24 49
 
0.5%
4.1113128001089e+24 42
 
0.4%
4.1117101001011104e+24 40
 
0.4%
4.11151380010184e+24 38
 
0.4%
4.1111137001006097e+24 35
 
0.4%
4.1111134001003695e+24 34
 
0.3%
4.1115127001001103e+24 28
 
0.3%
4.1117101001015297e+24 26
 
0.3%
4.1113126001009693e+24 26
 
0.3%
4.11111370010193e+24 25
 
0.2%
Other values (4104) 9657
96.6%
ValueCountFrequency (%)
4.1111129001002303e+24 1
 
< 0.1%
4.1111129001004305e+24 2
< 0.1%
4.11111290010076e+24 1
 
< 0.1%
4.11111290010087e+24 1
 
< 0.1%
4.1111129001008896e+24 1
 
< 0.1%
4.11111290010095e+24 2
< 0.1%
4.11111290010101e+24 1
 
< 0.1%
4.11111290010102e+24 1
 
< 0.1%
4.1111129001010496e+24 1
 
< 0.1%
4.1111129001020304e+24 3
< 0.1%
ValueCountFrequency (%)
4.1590121001061e+24 1
 
< 0.1%
4.1590121001060895e+24 1
 
< 0.1%
4.1590121001060497e+24 1
 
< 0.1%
4.15901210010604e+24 2
 
< 0.1%
4.1590121001003e+24 1
 
< 0.1%
4.1590121000002497e+24 1
 
< 0.1%
4.14631110010513e+24 1
 
< 0.1%
4.1463111001045295e+24 10
0.1%
4.1463111001045e+24 1
 
< 0.1%
4.11171070010722e+24 1
 
< 0.1%

시군구용건물명
Text

Distinct1700
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T09:35:59.214363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length1
Mean length1.8466
Min length1

Characters and Unicode

Total characters18466
Distinct characters553
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1519 ?
Unique (%)15.2%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
8003
79.5%
업타운코트 9
 
0.1%
현대빌라 8
 
0.1%
가림주택 8
 
0.1%
성원주택 7
 
0.1%
조은빌 7
 
0.1%
다세대주택 7
 
0.1%
진주맨션 6
 
0.1%
목화빌라 6
 
0.1%
삼호빌라 5
 
< 0.1%
Other values (1727) 1996
 
19.8%
2023-12-12T09:35:59.564815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 8014
43.4%
빌 754
 
4.1%
라 458
 
2.5%
원 258
 
1.4%
주 234
 
1.3%
아 223
 
1.2%
트 213
 
1.2%
동 182
 
1.0%
성 167
 
0.9%
파 156
 
0.8%
Other values (543) 7807
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9906
53.6%
Dash Punctuation 8014
43.4%
Decimal Number 174
 
0.9%
Uppercase Letter 165
 
0.9%
Lowercase Letter 68
 
0.4%
Space Separator 62
 
0.3%
Close Punctuation 29
 
0.2%
Open Punctuation 29
 
0.2%
Other Punctuation 13
 
0.1%
Letter Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 754
 
7.6%
라 458
 
4.6%
원 258
 
2.6%
주 234
 
2.4%
아 223
 
2.3%
트 213
 
2.2%
동 182
 
1.8%
성 167
 
1.7%
파 156
 
1.6%
대 153
 
1.5%
Other values (476) 7108
71.8%
Uppercase Letter
ValueCountFrequency (%)
K 16
 
9.7%
S 15
 
9.1%
B 13
 
7.9%
A 11
 
6.7%
T 11
 
6.7%
I 9
 
5.5%
G 9
 
5.5%
M 8
 
4.8%
L 8
 
4.8%
C 7
 
4.2%
Other values (15) 58
35.2%
Lowercase Letter
ValueCountFrequency (%)
e 8
11.8%
a 8
11.8%
l 7
10.3%
o 6
 
8.8%
m 5
 
7.4%
w 4
 
5.9%
u 4
 
5.9%
r 4
 
5.9%
s 3
 
4.4%
t 3
 
4.4%
Other values (10) 16
23.5%
Decimal Number
ValueCountFrequency (%)
1 56
32.2%
2 36
20.7%
3 18
 
10.3%
5 16
 
9.2%
8 9
 
5.2%
4 8
 
4.6%
9 8
 
4.6%
7 8
 
4.6%
6 8
 
4.6%
0 7
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 6
46.2%
. 5
38.5%
& 1
 
7.7%
' 1
 
7.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
50.0%
Ⅰ 1
 
16.7%
Ⅳ 1
 
16.7%
Ⅸ 1
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 8014
100.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9906
53.6%
Common 8321
45.1%
Latin 239
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 754
 
7.6%
라 458
 
4.6%
원 258
 
2.6%
주 234
 
2.4%
아 223
 
2.3%
트 213
 
2.2%
동 182
 
1.8%
성 167
 
1.7%
파 156
 
1.6%
대 153
 
1.5%
Other values (476) 7108
71.8%
Latin
ValueCountFrequency (%)
K 16
 
6.7%
S 15
 
6.3%
B 13
 
5.4%
A 11
 
4.6%
T 11
 
4.6%
I 9
 
3.8%
G 9
 
3.8%
M 8
 
3.3%
L 8
 
3.3%
e 8
 
3.3%
Other values (39) 131
54.8%
Common
ValueCountFrequency (%)
- 8014
96.3%
62
 
0.7%
1 56
 
0.7%
2 36
 
0.4%
) 29
 
0.3%
( 29
 
0.3%
3 18
 
0.2%
5 16
 
0.2%
8 9
 
0.1%
4 8
 
0.1%
Other values (8) 44
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9906
53.6%
ASCII 8554
46.3%
Number Forms 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 8014
93.7%
62
 
0.7%
1 56
 
0.7%
2 36
 
0.4%
) 29
 
0.3%
( 29
 
0.3%
3 18
 
0.2%
K 16
 
0.2%
5 16
 
0.2%
S 15
 
0.2%
Other values (53) 263
 
3.1%
Hangul
ValueCountFrequency (%)
빌 754
 
7.6%
라 458
 
4.6%
원 258
 
2.6%
주 234
 
2.4%
아 223
 
2.3%
트 213
 
2.2%
동 182
 
1.8%
성 167
 
1.7%
파 156
 
1.6%
대 153
 
1.5%
Other values (476) 7108
71.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
50.0%
Ⅰ 1
 
16.7%
Ⅳ 1
 
16.7%
Ⅸ 1
 
16.7%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1113637 × 109
Minimum4.1111129 × 109
Maximum4.1117107 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:35:59.679487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.1111129 × 109
5-th percentile4.111113 × 109
Q14.1111137 × 109
median4.1113133 × 109
Q34.1115138 × 109
95-th percentile4.1117102 × 109
Maximum4.1117107 × 109
Range597800
Interquartile range (IQR)400100

Descriptive statistics

Standard deviation197065.44
Coefficient of variation (CV)4.7931891 × 10-5
Kurtosis-1.0233486
Mean4.1113637 × 109
Median Absolute Deviation (MAD)199900
Skewness0.23125992
Sum4.1113637 × 1013
Variance3.8834787 × 1010
MonotonicityNot monotonic
2023-12-12T09:35:59.795935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4111312600 988
 
9.9%
4111710100 544
 
5.4%
4111113400 501
 
5.0%
4111513900 443
 
4.4%
4111513800 441
 
4.4%
4111113600 410
 
4.1%
4111514100 407
 
4.1%
4111313700 402
 
4.0%
4111113700 392
 
3.9%
4111113000 383
 
3.8%
Other values (46) 5089
50.9%
ValueCountFrequency (%)
4111112900 325
3.2%
4111113000 383
3.8%
4111113100 62
 
0.6%
4111113200 225
2.2%
4111113300 102
 
1.0%
4111113400 501
5.0%
4111113500 264
2.6%
4111113600 410
4.1%
4111113700 392
3.9%
4111113800 18
 
0.2%
ValueCountFrequency (%)
4111710700 80
 
0.8%
4111710600 62
 
0.6%
4111710500 203
 
2.0%
4111710400 36
 
0.4%
4111710300 111
 
1.1%
4111710200 194
 
1.9%
4111710100 544
5.4%
4111514100 407
4.1%
4111514000 378
3.8%
4111513900 443
4.4%

법정동명
Text

Distinct56
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T09:36:00.004128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0151
Min length2

Characters and Unicode

Total characters30151
Distinct characters74
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row평동
2nd row정자동
3rd row매탄동
4th row원천동
5th row세류동
ValueCountFrequency (%)
세류동 988
 
9.9%
매탄동 544
 
5.4%
영화동 501
 
5.0%
지동 443
 
4.4%
화서동 441
 
4.4%
조원동 410
 
4.1%
인계동 407
 
4.1%
권선동 402
 
4.0%
연무동 392
 
3.9%
정자동 383
 
3.8%
Other values (46) 5089
50.9%
2023-12-12T09:36:00.286480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 9675
32.1%
매 1032
 
3.4%
세 988
 
3.3%
류 988
 
3.3%
화 942
 
3.1%
서 758
 
2.5%
영 728
 
2.4%
고 617
 
2.0%
원 604
 
2.0%
정 591
 
2.0%
Other values (64) 13228
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29826
98.9%
Decimal Number 325
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9675
32.4%
매 1032
 
3.5%
세 988
 
3.3%
류 988
 
3.3%
화 942
 
3.2%
서 758
 
2.5%
영 728
 
2.4%
고 617
 
2.1%
원 604
 
2.0%
정 591
 
2.0%
Other values (61) 12903
43.3%
Decimal Number
ValueCountFrequency (%)
3 153
47.1%
1 88
27.1%
2 84
25.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29826
98.9%
Common 325
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9675
32.4%
매 1032
 
3.5%
세 988
 
3.3%
류 988
 
3.3%
화 942
 
3.2%
서 758
 
2.5%
영 728
 
2.4%
고 617
 
2.1%
원 604
 
2.0%
정 591
 
2.0%
Other values (61) 12903
43.3%
Common
ValueCountFrequency (%)
3 153
47.1%
1 88
27.1%
2 84
25.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29826
98.9%
ASCII 325
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 9675
32.4%
매 1032
 
3.5%
세 988
 
3.3%
류 988
 
3.3%
화 942
 
3.2%
서 758
 
2.5%
영 728
 
2.4%
고 617
 
2.1%
원 604
 
2.0%
정 591
 
2.0%
Other values (61) 12903
43.3%
ASCII
ValueCountFrequency (%)
3 153
47.1%
1 88
27.1%
2 84
25.8%

Interactions

2023-12-12T09:35:49.769395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:03.337630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.464813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:12.518365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:17.257787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:21.748781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:49.846034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:03.408669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.568679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:12.590021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:17.342902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:25.548338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:49.926264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:03.484509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.674438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:12.670798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:17.426154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:29.313545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:50.003365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:03.559714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.788379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:12.746810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:17.503880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:32.933840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:50.093220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:03.634887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.901446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:12.838016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:17.585324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:36.889651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:54.248287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.375499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:12.439353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:17.155484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:21.645994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:45.125022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:36:00.369322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호시군구시군구영문도로명코드건물번호본번건물번호부번건물관리번호법정동코드법정동명
우편번호1.0000.9030.9030.9030.2880.1150.1870.9030.985
시군구0.9031.0001.0001.0000.1380.1090.0851.0001.000
시군구영문0.9031.0001.0001.0000.1380.1090.0851.0001.000
도로명코드0.9031.0001.0001.0000.1380.1090.0851.0001.000
건물번호본번0.2880.1380.1380.1381.0000.0310.0000.1350.521
건물번호부번0.1150.1090.1090.1090.0311.0000.2220.1080.309
건물관리번호0.1870.0850.0850.0850.0000.2221.0000.0850.464
법정동코드0.9031.0001.0001.0000.1350.1080.0851.0001.000
법정동명0.9851.0001.0001.0000.5210.3090.4641.0001.000
2023-12-12T09:36:00.460883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구영문시군구
시군구영문1.0001.000
시군구1.0001.000
2023-12-12T09:36:00.533223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호도로명코드건물번호본번건물번호부번건물관리번호법정동코드시군구시군구영문
우편번호1.0000.2560.0010.0150.2450.2440.7870.787
도로명코드0.2561.000-0.1000.0220.9210.9221.0001.000
건물번호본번0.001-0.1001.000-0.0570.0230.0240.0830.083
건물번호부번0.0150.022-0.0571.0000.0100.0100.0510.051
건물관리번호0.2450.9210.0230.0101.0000.9990.7670.767
법정동코드0.2440.9220.0240.0100.9991.0001.0001.000
시군구0.7871.0000.0830.0510.7671.0001.0001.000
시군구영문0.7871.0000.0830.0510.7671.0001.0001.000

Missing values

2023-12-12T09:35:55.160669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:35:55.344304image/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

우편번호시도시도영문시군구시군구영문도로명코드도로명도로명영문건물번호본번건물번호부번건물관리번호시군구용건물명법정동코드법정동명
1635416599경기도Gyeonggi-do수원시 권선구Gwonseon-gu, Suwon-si411134325470평동로58번길Pyeongdong-ro 58beon-gil3814111312700100470000000000-4111312700평동
3146716313경기도Gyeonggi-do수원시 장안구Jangan-gu, Suwon-si411114322148수성로289번길Suseong-ro 289beon-gil5744111113000100480000000000-4111113000정자동
1920816531경기도Gyeonggi-do수원시 영통구Yeongtong-gu, Suwon-si411174328317중부대로256번길Jungbu-daero 256beon-gil5404111710100101940000000000-4111710100매탄동
2233416503경기도Gyeonggi-do수원시 영통구Yeongtong-gu, Suwon-si411174331023동수원로537번길Dongsuwon-ro 537beon-gil28154111710200100770000000000-4111710200원천동
1088916660경기도Gyeonggi-do수원시 권선구Gwonseon-gu, Suwon-si411134325413정조로378번길Jeongjo-ro 378beon-gil1134111312600111660000000000-4111312600세류동
2791616276경기도Gyeonggi-do수원시 장안구Jangan-gu, Suwon-si411113175035수원천로Suwoncheon-ro45304111113400100370000000000-4111113400영화동
3121216312경기도Gyeonggi-do수원시 장안구Jangan-gu, Suwon-si411114322244장안로116번길Jangan-ro 116beon-gil304111113000100320000000000-4111113000정자동
23116649경기도Gyeonggi-do수원시 권선구Gwonseon-gu, Suwon-si411134325038고산로16번길Gosan-ro 16beon-gil2314111312800100790000000000-4111312800고색동
561616565경기도Gyeonggi-do수원시 권선구Gwonseon-gu, Suwon-si411134325023경수대로335번길Gyeongsu-daero 335beon-gil14204111313700109910000000000-4111313700권선동
2068416703경기도Gyeonggi-do수원시 영통구Yeongtong-gu, Suwon-si411173177007봉영로Bongyeong-ro157904111710500109600000000000롯데마트영통점4111710500영통동
우편번호시도시도영문시군구시군구영문도로명코드도로명도로명영문건물번호본번건물번호부번건물관리번호시군구용건물명법정동코드법정동명
1793716541경기도Gyeonggi-do수원시 영통구Yeongtong-gu, Suwon-si411173177008산남로Sannam-ro2604111710100108450000000000-4111710100매탄동
744416609경기도Gyeonggi-do수원시 권선구Gwonseon-gu, Suwon-si411134325282서호서로15번길Seohoseo-ro 15beon-gil2494111313100101500000000000-4111313100서둔동
1840116525경기도Gyeonggi-do수원시 영통구Yeongtong-gu, Suwon-si411174331035매봉로35번길Maebong-ro 35beon-gil3294111710100101110000000000-4111710100매탄동
2497416303경기도Gyeonggi-do수원시 장안구Jangan-gu, Suwon-si411114322043경수대로995번길Gyeongsu-daero 995beon-gil1504111113500104500000000000-4111113500송죽동
3801916447경기도Gyeonggi-do수원시 팔달구Paldal-gu, Suwon-si411154328076고화로61번길Gohwa-ro 61beon-gil3414111513700100520000000000-4111513700고등동
2225816521경기도Gyeonggi-do수원시 영통구Yeongtong-gu, Suwon-si411173177009삼성로Samsung-ro25704111710200102510000000000-4111710200원천동
3554816349경기도Gyeonggi-do수원시 장안구Jangan-gu, Suwon-si411113174015파장로Pajang-ro8804111112900105720000000000다이소4111112900파장동
472816562경기도Gyeonggi-do수원시 권선구Gwonseon-gu, Suwon-si411133175016동수원로Dongsuwon-ro29504111313700111710000000000-4111313700권선동
905716655경기도Gyeonggi-do수원시 권선구Gwonseon-gu, Suwon-si411133012001덕영대로Deogyeong-daero108604111312600105440000000000-4111312600세류동
5052316443경기도Gyeonggi-do수원시 팔달구Paldal-gu, Suwon-si411154328444화양로35번길Hwayang-ro 35beon-gil2144111513800102020000000000-4111513800화서동