Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells7129
Missing cells (%)5.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory108.0 B

Variable types

Numeric4
Categorical4
Text4

Dataset

Description옥외광고물 주소 및 우편코드 현황에 대한 데이터로 순번,시도, 시군구, 읍면동, 도로명, 건물번호, 건물명, 지번, 신우편코드,구우편코드 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15086956&srcSe=7661IVAWM27C61E190

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 읍면동High correlation
신우편코드 is highly overall correlated with 읍면동High correlation
읍면동 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
건물명 has 6808 (68.1%) missing valuesMissing
신우편코드 has 151 (1.5%) missing valuesMissing
건물번호2 has 6641 (66.4%) zerosZeros

Reproduction

Analysis started2024-01-28 09:18:17.992802
Analysis finished2024-01-28 09:18:20.521449
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION 

Distinct9036
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9423.0735
Minimum2
Maximum22655
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-28T18:18:20.816752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile862.55
Q14187.75
median8344
Q314409.25
95-th percentile20877.4
Maximum22655
Range22653
Interquartile range (IQR)10221.5

Descriptive statistics

Standard deviation6288.6211
Coefficient of variation (CV)0.66736412
Kurtosis-0.92808594
Mean9423.0735
Median Absolute Deviation (MAD)4757
Skewness0.43926994
Sum94230735
Variance39546755
MonotonicityNot monotonic
2024-01-28T18:18:20.932529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
539 2
 
< 0.1%
536 2
 
< 0.1%
3231 2
 
< 0.1%
7449 2
 
< 0.1%
1970 2
 
< 0.1%
9655 2
 
< 0.1%
3274 2
 
< 0.1%
870 2
 
< 0.1%
1181 2
 
< 0.1%
5151 2
 
< 0.1%
Other values (9026) 9980
99.8%
ValueCountFrequency (%)
2 1
< 0.1%
4 2
< 0.1%
6 1
< 0.1%
10 1
< 0.1%
12 2
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
19 1
< 0.1%
22 1
< 0.1%
24 1
< 0.1%
ValueCountFrequency (%)
22655 1
< 0.1%
22650 1
< 0.1%
22648 1
< 0.1%
22642 1
< 0.1%
22640 1
< 0.1%
22638 1
< 0.1%
22637 1
< 0.1%
22634 1
< 0.1%
22630 1
< 0.1%
22625 1
< 0.1%

시도
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 10000
100.0%

Length

2024-01-28T18:18:21.035473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:18:21.107677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 10000
100.0%

시군구
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남동구 10000
100.0%

Length

2024-01-28T18:18:21.188857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:18:21.259116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 10000
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
간석동
2267 
구월동
2154 
만수동
1824 
고잔동
1738 
논현동
730 
Other values (6)
1287 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고잔동
2nd row간석동
3rd row운연동
4th row고잔동
5th row간석동

Common Values

ValueCountFrequency (%)
간석동 2267
22.7%
구월동 2154
21.5%
만수동 1824
18.2%
고잔동 1738
17.4%
논현동 730
 
7.3%
남촌동 533
 
5.3%
도림동 186
 
1.9%
장수동 178
 
1.8%
서창동 144
 
1.4%
운연동 126
 
1.3%

Length

2024-01-28T18:18:21.327032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
간석동 2267
22.7%
구월동 2154
21.5%
만수동 1824
18.2%
고잔동 1738
17.4%
논현동 730
 
7.3%
남촌동 533
 
5.3%
도림동 186
 
1.9%
장수동 178
 
1.8%
서창동 144
 
1.4%
운연동 126
 
1.3%

도로명
Text

Distinct810
Distinct (%)8.1%
Missing43
Missing (%)0.4%
Memory size156.2 KiB
2024-01-28T18:18:21.542589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.5476549
Min length3

Characters and Unicode

Total characters65195
Distinct characters130
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

Unique43 ?
Unique (%)0.4%

Sample

1st row앵고개로
2nd row간석로25번길
3rd row음실로
4th row남동동로183번길
5th row주안로241번길
ValueCountFrequency (%)
남동대로 168
 
1.7%
호구포로 159
 
1.6%
백범로 144
 
1.4%
인주대로 116
 
1.2%
남동서로 111
 
1.1%
문화서로4번길 92
 
0.9%
앵고개로 90
 
0.9%
구월남로 88
 
0.9%
남동동로 85
 
0.9%
석산로 80
 
0.8%
Other values (800) 8824
88.6%
2024-01-28T18:18:21.871657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 9948
 
15.3%
길 6653
 
10.2%
번 6644
 
10.2%
1 2555
 
3.9%
2 2090
 
3.2%
4 1936
 
3.0%
5 1860
 
2.9%
3 1700
 
2.6%
남 1663
 
2.6%
6 1620
 
2.5%
Other values (120) 28526
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48657
74.6%
Decimal Number 16538
 
25.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 9948
20.4%
길 6653
13.7%
번 6644
13.7%
남 1663
 
3.4%
동 1565
 
3.2%
대 1419
 
2.9%
구 1346
 
2.8%
월 1115
 
2.3%
서 1030
 
2.1%
석 775
 
1.6%
Other values (110) 16499
33.9%
Decimal Number
ValueCountFrequency (%)
1 2555
15.4%
2 2090
12.6%
4 1936
11.7%
5 1860
11.2%
3 1700
10.3%
6 1620
9.8%
7 1483
9.0%
8 1178
7.1%
9 1064
6.4%
0 1052
6.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48657
74.6%
Common 16538
 
25.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 9948
20.4%
길 6653
13.7%
번 6644
13.7%
남 1663
 
3.4%
동 1565
 
3.2%
대 1419
 
2.9%
구 1346
 
2.8%
월 1115
 
2.3%
서 1030
 
2.1%
석 775
 
1.6%
Other values (110) 16499
33.9%
Common
ValueCountFrequency (%)
1 2555
15.4%
2 2090
12.6%
4 1936
11.7%
5 1860
11.2%
3 1700
10.3%
6 1620
9.8%
7 1483
9.0%
8 1178
7.1%
9 1064
6.4%
0 1052
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48657
74.6%
ASCII 16538
 
25.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 9948
20.4%
길 6653
13.7%
번 6644
13.7%
남 1663
 
3.4%
동 1565
 
3.2%
대 1419
 
2.9%
구 1346
 
2.8%
월 1115
 
2.3%
서 1030
 
2.1%
석 775
 
1.6%
Other values (110) 16499
33.9%
ASCII
ValueCountFrequency (%)
1 2555
15.4%
2 2090
12.6%
4 1936
11.7%
5 1860
11.2%
3 1700
10.3%
6 1620
9.8%
7 1483
9.0%
8 1178
7.1%
9 1064
6.4%
0 1052
6.4%

건물번호
Real number (ℝ)

Distinct736
Distinct (%)7.4%
Missing29
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean105.50707
Minimum0
Maximum3731
Zeros9
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-28T18:18:21.984214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q116
median35
Q377
95-th percentile558
Maximum3731
Range3731
Interquartile range (IQR)61

Descriptive statistics

Standard deviation225.27329
Coefficient of variation (CV)2.1351488
Kurtosis86.346104
Mean105.50707
Median Absolute Deviation (MAD)23
Skewness6.9494487
Sum1052011
Variance50748.057
MonotonicityNot monotonic
2024-01-28T18:18:22.108179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 224
 
2.2%
13 203
 
2.0%
8 202
 
2.0%
15 199
 
2.0%
10 198
 
2.0%
20 191
 
1.9%
16 186
 
1.9%
18 184
 
1.8%
5 177
 
1.8%
11 170
 
1.7%
Other values (726) 8037
80.4%
ValueCountFrequency (%)
0 9
 
0.1%
1 64
 
0.6%
2 63
 
0.6%
3 100
1.0%
4 135
1.4%
5 177
1.8%
6 137
1.4%
7 154
1.5%
8 202
2.0%
9 224
2.2%
ValueCountFrequency (%)
3731 1
 
< 0.1%
3726 3
< 0.1%
3724 1
 
< 0.1%
3722 1
 
< 0.1%
3718 1
 
< 0.1%
3714 1
 
< 0.1%
3669 2
< 0.1%
3659 1
 
< 0.1%
3587 1
 
< 0.1%
3538 1
 
< 0.1%

건물번호2
Real number (ℝ)

ZEROS 

Distinct85
Distinct (%)0.9%
Missing29
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean3.4837027
Minimum0
Maximum111
Zeros6641
Zeros (%)66.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-28T18:18:22.217507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile19
Maximum111
Range111
Interquartile range (IQR)2

Descriptive statistics

Standard deviation8.5741798
Coefficient of variation (CV)2.461226
Kurtosis27.748818
Mean3.4837027
Median Absolute Deviation (MAD)0
Skewness4.3688002
Sum34736
Variance73.51656
MonotonicityNot monotonic
2024-01-28T18:18:22.321344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6641
66.4%
1 776
 
7.8%
2 198
 
2.0%
6 179
 
1.8%
3 173
 
1.7%
5 170
 
1.7%
8 153
 
1.5%
7 153
 
1.5%
4 136
 
1.4%
12 104
 
1.0%
Other values (75) 1288
 
12.9%
ValueCountFrequency (%)
0 6641
66.4%
1 776
 
7.8%
2 198
 
2.0%
3 173
 
1.7%
4 136
 
1.4%
5 170
 
1.7%
6 179
 
1.8%
7 153
 
1.5%
8 153
 
1.5%
9 104
 
1.0%
ValueCountFrequency (%)
111 1
< 0.1%
105 1
< 0.1%
99 2
< 0.1%
96 1
< 0.1%
94 1
< 0.1%
90 1
< 0.1%
88 1
< 0.1%
85 1
< 0.1%
83 2
< 0.1%
80 1
< 0.1%

건물명
Text

MISSING 

Distinct2418
Distinct (%)75.8%
Missing6808
Missing (%)68.1%
Memory size156.2 KiB
2024-01-28T18:18:22.524968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length23
Mean length5.8399123
Min length1

Characters and Unicode

Total characters18641
Distinct characters557
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1934 ?
Unique (%)60.6%

Sample

1st row(주)대경특수공업
2nd row성은감리교회
3rd row문일여자고등학교
4th row(주)동방이엔지
5th row우현정밀
ValueCountFrequency (%)
에코메트로 19
 
0.5%
만수주공아파트 16
 
0.5%
논현휴먼시아 14
 
0.4%
주공아파트 14
 
0.4%
강남빌라 12
 
0.3%
무궁화빌라 11
 
0.3%
휴먼시아 11
 
0.3%
아파트 11
 
0.3%
세일빌라 10
 
0.3%
대양빌라 9
 
0.3%
Other values (2484) 3343
96.3%
2024-01-28T18:18:22.843915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 746
 
4.0%
주 738
 
4.0%
) 542
 
2.9%
( 540
 
2.9%
라 485
 
2.6%
아 424
 
2.3%
동 389
 
2.1%
트 384
 
2.1%
성 340
 
1.8%
업 289
 
1.6%
Other values (547) 13764
73.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16683
89.5%
Close Punctuation 542
 
2.9%
Open Punctuation 540
 
2.9%
Space Separator 278
 
1.5%
Decimal Number 273
 
1.5%
Uppercase Letter 270
 
1.4%
Other Punctuation 17
 
0.1%
Lowercase Letter 16
 
0.1%
Dash Punctuation 12
 
0.1%
Other Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 746
 
4.5%
주 738
 
4.4%
라 485
 
2.9%
아 424
 
2.5%
동 389
 
2.3%
트 384
 
2.3%
성 340
 
2.0%
업 289
 
1.7%
이 285
 
1.7%
파 271
 
1.6%
Other values (493) 12332
73.9%
Uppercase Letter
ValueCountFrequency (%)
A 25
 
9.3%
G 22
 
8.1%
S 22
 
8.1%
C 21
 
7.8%
M 19
 
7.0%
E 18
 
6.7%
T 17
 
6.3%
N 15
 
5.6%
L 14
 
5.2%
B 13
 
4.8%
Other values (14) 84
31.1%
Lowercase Letter
ValueCountFrequency (%)
a 2
12.5%
r 2
12.5%
t 2
12.5%
s 2
12.5%
o 2
12.5%
y 1
6.2%
g 1
6.2%
d 1
6.2%
j 1
6.2%
n 1
6.2%
Decimal Number
ValueCountFrequency (%)
1 105
38.5%
2 47
17.2%
0 36
 
13.2%
3 31
 
11.4%
7 11
 
4.0%
9 10
 
3.7%
5 9
 
3.3%
4 9
 
3.3%
8 8
 
2.9%
6 7
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 7
41.2%
. 7
41.2%
& 3
17.6%
Close Punctuation
ValueCountFrequency (%)
) 542
100.0%
Open Punctuation
ValueCountFrequency (%)
( 540
100.0%
Space Separator
ValueCountFrequency (%)
278
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16688
89.5%
Common 1662
 
8.9%
Latin 289
 
1.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 746
 
4.5%
주 738
 
4.4%
라 485
 
2.9%
아 424
 
2.5%
동 389
 
2.3%
트 384
 
2.3%
성 340
 
2.0%
업 289
 
1.7%
이 285
 
1.7%
파 271
 
1.6%
Other values (492) 12337
73.9%
Latin
ValueCountFrequency (%)
A 25
 
8.7%
G 22
 
7.6%
S 22
 
7.6%
C 21
 
7.3%
M 19
 
6.6%
E 18
 
6.2%
T 17
 
5.9%
N 15
 
5.2%
L 14
 
4.8%
B 13
 
4.5%
Other values (26) 103
35.6%
Common
ValueCountFrequency (%)
) 542
32.6%
( 540
32.5%
278
16.7%
1 105
 
6.3%
2 47
 
2.8%
0 36
 
2.2%
3 31
 
1.9%
- 12
 
0.7%
7 11
 
0.7%
9 10
 
0.6%
Other values (7) 50
 
3.0%
Han
ValueCountFrequency (%)
名 1
50.0%
品 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16681
89.5%
ASCII 1948
 
10.5%
None 7
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 746
 
4.5%
주 738
 
4.4%
라 485
 
2.9%
아 424
 
2.5%
동 389
 
2.3%
트 384
 
2.3%
성 340
 
2.0%
업 289
 
1.7%
이 285
 
1.7%
파 271
 
1.6%
Other values (491) 12330
73.9%
ASCII
ValueCountFrequency (%)
) 542
27.8%
( 540
27.7%
278
14.3%
1 105
 
5.4%
2 47
 
2.4%
0 36
 
1.8%
3 31
 
1.6%
A 25
 
1.3%
G 22
 
1.1%
S 22
 
1.1%
Other values (42) 300
15.4%
None
ValueCountFrequency (%)
㈜ 7
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%
CJK
ValueCountFrequency (%)
名 1
50.0%
品 1
50.0%

지번
Text

Distinct8398
Distinct (%)84.2%
Missing29
Missing (%)0.3%
Memory size156.2 KiB
2024-01-28T18:18:23.174018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.3670645
Min length5

Characters and Unicode

Total characters93399
Distinct characters33
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

Unique7200 ?
Unique (%)72.2%

Sample

1st row고잔동 678-9
2nd row간석동 85-16
3rd row운연동 50
4th row고잔동 644-2
5th row간석동 391-20
ValueCountFrequency (%)
간석동 2264
 
11.4%
구월동 2151
 
10.8%
만수동 1822
 
9.1%
고잔동 1730
 
8.7%
논현동 718
 
3.6%
남촌동 533
 
2.7%
도림동 186
 
0.9%
장수동 178
 
0.9%
서창동 144
 
0.7%
운연동 125
 
0.6%
Other values (7883) 10091
50.6%
2024-01-28T18:18:23.586953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 9971
 
10.7%
9971
 
10.7%
1 9645
 
10.3%
- 9198
 
9.8%
2 5197
 
5.6%
3 4626
 
5.0%
6 4470
 
4.8%
4 3789
 
4.1%
7 3671
 
3.9%
5 3505
 
3.8%
Other values (23) 29356
31.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44281
47.4%
Other Letter 29949
32.1%
Space Separator 9971
 
10.7%
Dash Punctuation 9198
 
9.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9971
33.3%
간 2264
 
7.6%
석 2264
 
7.6%
구 2151
 
7.2%
월 2151
 
7.2%
수 2120
 
7.1%
만 1822
 
6.1%
고 1730
 
5.8%
잔 1730
 
5.8%
논 718
 
2.4%
Other values (11) 3028
 
10.1%
Decimal Number
ValueCountFrequency (%)
1 9645
21.8%
2 5197
11.7%
3 4626
10.4%
6 4470
10.1%
4 3789
 
8.6%
7 3671
 
8.3%
5 3505
 
7.9%
9 3302
 
7.5%
8 3107
 
7.0%
0 2969
 
6.7%
Space Separator
ValueCountFrequency (%)
9971
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9198
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63450
67.9%
Hangul 29949
32.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9971
33.3%
간 2264
 
7.6%
석 2264
 
7.6%
구 2151
 
7.2%
월 2151
 
7.2%
수 2120
 
7.1%
만 1822
 
6.1%
고 1730
 
5.8%
잔 1730
 
5.8%
논 718
 
2.4%
Other values (11) 3028
 
10.1%
Common
ValueCountFrequency (%)
9971
15.7%
1 9645
15.2%
- 9198
14.5%
2 5197
8.2%
3 4626
7.3%
6 4470
7.0%
4 3789
 
6.0%
7 3671
 
5.8%
5 3505
 
5.5%
9 3302
 
5.2%
Other values (2) 6076
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63450
67.9%
Hangul 29949
32.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 9971
33.3%
간 2264
 
7.6%
석 2264
 
7.6%
구 2151
 
7.2%
월 2151
 
7.2%
수 2120
 
7.1%
만 1822
 
6.1%
고 1730
 
5.8%
잔 1730
 
5.8%
논 718
 
2.4%
Other values (11) 3028
 
10.1%
ASCII
ValueCountFrequency (%)
9971
15.7%
1 9645
15.2%
- 9198
14.5%
2 5197
8.2%
3 4626
7.3%
6 4470
7.0%
4 3789
 
6.0%
7 3671
 
5.8%
5 3505
 
5.5%
9 3302
 
5.2%
Other values (2) 6076
9.6%

신우편코드
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct184
Distinct (%)1.9%
Missing151
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean21582.192
Minimum21500
Maximum21700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-28T18:18:23.698865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21500
5-th percentile21508
Q121534
median21559
Q321635
95-th percentile21694
Maximum21700
Range200
Interquartile range (IQR)101

Descriptive statistics

Standard deviation62.881951
Coefficient of variation (CV)0.0029136035
Kurtosis-1.0429221
Mean21582.192
Median Absolute Deviation (MAD)39
Skewness0.61192428
Sum2.1256301 × 108
Variance3954.1397
MonotonicityNot monotonic
2024-01-28T18:18:23.809532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21550 269
 
2.7%
21515 231
 
2.3%
21510 210
 
2.1%
21534 203
 
2.0%
21547 200
 
2.0%
21536 196
 
2.0%
21511 192
 
1.9%
21543 186
 
1.9%
21535 169
 
1.7%
21521 166
 
1.7%
Other values (174) 7827
78.3%
ValueCountFrequency (%)
21500 19
 
0.2%
21501 19
 
0.2%
21502 50
0.5%
21503 48
0.5%
21504 94
0.9%
21505 10
 
0.1%
21506 100
1.0%
21507 101
1.0%
21508 85
0.9%
21509 66
0.7%
ValueCountFrequency (%)
21700 78
0.8%
21699 119
1.2%
21698 80
0.8%
21697 55
0.5%
21696 75
0.8%
21695 65
0.7%
21694 115
1.1%
21693 79
0.8%
21692 53
0.5%
21691 104
1.0%

구우편코드
Text

Distinct149
Distinct (%)1.5%
Missing40
Missing (%)0.4%
Memory size156.2 KiB
2024-01-28T18:18:24.023834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters69720
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.2%

Sample

1st row405-819
2nd row405-801
3rd row405-270
4th row405-817
5th row405-806
ValueCountFrequency (%)
405-800 535
 
5.4%
405-839 459
 
4.6%
405-862 397
 
4.0%
405-835 355
 
3.6%
405-840 344
 
3.5%
405-816 302
 
3.0%
405-809 265
 
2.7%
405-825 255
 
2.6%
405-822 252
 
2.5%
405-806 250
 
2.5%
Other values (139) 6546
65.7%
2024-01-28T18:18:24.323741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14436
20.7%
5 11814
16.9%
4 11701
16.8%
- 9960
14.3%
8 9671
13.9%
2 3543
 
5.1%
6 2232
 
3.2%
1 2101
 
3.0%
3 1722
 
2.5%
9 1355
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59760
85.7%
Dash Punctuation 9960
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14436
24.2%
5 11814
19.8%
4 11701
19.6%
8 9671
16.2%
2 3543
 
5.9%
6 2232
 
3.7%
1 2101
 
3.5%
3 1722
 
2.9%
9 1355
 
2.3%
7 1185
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 9960
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69720
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14436
20.7%
5 11814
16.9%
4 11701
16.8%
- 9960
14.3%
8 9671
13.9%
2 3543
 
5.1%
6 2232
 
3.2%
1 2101
 
3.0%
3 1722
 
2.5%
9 1355
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14436
20.7%
5 11814
16.9%
4 11701
16.8%
- 9960
14.3%
8 9671
13.9%
2 3543
 
5.1%
6 2232
 
3.2%
1 2101
 
3.0%
3 1722
 
2.5%
9 1355
 
1.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-05-17
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-17
2nd row2023-05-17
3rd row2023-05-17
4th row2023-05-17
5th row2023-05-17

Common Values

ValueCountFrequency (%)
2023-05-17 10000
100.0%

Length

2024-01-28T18:18:24.433384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:18:24.506754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-17 10000
100.0%

Interactions

2024-01-28T18:18:19.851571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:18.908364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.204975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.523416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.924028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:18.979310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.284046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.590043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:20.004962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.053558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.362724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.665097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:20.080498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.126937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.440310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:19.770794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T18:18:24.563210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번읍면동건물번호건물번호2신우편코드
순번1.0000.8490.2610.1440.869
읍면동0.8491.0000.2500.1090.886
건물번호0.2610.2501.0000.0380.187
건물번호20.1440.1090.0381.0000.167
신우편코드0.8690.8860.1870.1671.000
2024-01-28T18:18:24.650921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번건물번호건물번호2신우편코드읍면동
순번1.0000.081-0.0210.3300.578
건물번호0.0811.000-0.1460.1670.131
건물번호2-0.021-0.1461.000-0.1320.046
신우편코드0.3300.167-0.1321.0000.646
읍면동0.5780.1310.0460.6461.000

Missing values

2024-01-28T18:18:20.201559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:18:20.336244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-01-28T18:18:20.456626image/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

순번시도시군구읍면동도로명건물번호건물번호2건물명지번신우편코드구우편코드데이터기준일자
1107311074인천광역시남동구고잔동앵고개로4450<NA>고잔동 678-921696405-8192023-05-17
314315인천광역시남동구간석동간석로25번길321<NA>간석동 85-1621510405-8012023-05-17
322029545인천광역시남동구운연동음실로30<NA>운연동 5021601405-2702023-05-17
85988599인천광역시남동구고잔동남동동로183번길370(주)대경특수공업고잔동 644-221643405-8172023-05-17
68786879인천광역시남동구간석동주안로241번길210<NA>간석동 391-2021506405-8062023-05-17
1287812879인천광역시남동구고잔동호구포로670<NA>고잔동 723-1021692405-8222023-05-17
1338913390인천광역시남동구구월동구월남로2560성은감리교회구월동 1239-521563405-8372023-05-17
917918인천광역시남동구간석동경인로6520<NA>간석동 109-421510405-8012023-05-17
267724115인천광역시남동구만수동만부로12<NA>만수동 1-4321521405-8522023-05-17
256693012인천광역시남동구만수동구월로372번길980문일여자고등학교만수동 977-2521539405-8652023-05-17
순번시도시군구읍면동도로명건물번호건물번호2건물명지번신우편코드구우편코드데이터기준일자
284165759인천광역시남동구만수동백범로169번길1911<NA>만수동 882-1821543405-8622023-05-17
2078120782인천광역시남동구남촌동남촌동로180<NA>남촌동 360-921624405-8442023-05-17
313968739인천광역시남동구서창동매소홀로11140<NA>서창동 554-421604405-2602023-05-17
3289810241인천광역시남동구장수동장자로6번길821장수동 공동주택 (손영길)장수동 791-121532405-2502023-05-17
259260인천광역시남동구간석동간석로15번길460<NA>간석동 62-521509405-8002023-05-17
238891232인천광역시남동구논현동은봉로419번길111<NA>논현동 51-121657405-8472023-05-17
2026220263인천광역시남동구남촌동남동대로4620<NA>남촌동 510-10921627405-8452023-05-17
51975198인천광역시남동구간석동석정로551번길410인천남고등학교간석동 614-1221503405-8102023-05-17
1657616577인천광역시남동구구월동백범로2550수인주유소구월동 1249-321542405-8282023-05-17
2051520516인천광역시남동구남촌동남동서로3120와이엠테크남촌동 62121630405-8462023-05-17