Overview

Dataset statistics

Number of variables10
Number of observations72
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory83.8 B

Variable types

Text6
Categorical1
Numeric2
DateTime1

Dataset

Description경기도 안성시 공동주택 현황 테이터, 단지, 위치, 사업승인일, 층수, 동수, 관리사무소 연락처 등의 항목을 제공합니다.
Author경기도 안성시
URLhttps://www.data.go.kr/data/15116730/fileData.do

Alerts

데이터기준일 has constant value ""Constant
동수 is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 동수High correlation
분양형태 is highly imbalanced (54.6%)Imbalance
단지명 has unique valuesUnique
지번주소 has unique valuesUnique
도로명주소 has unique valuesUnique
관리사무소연락처 has unique valuesUnique
관리사무소팩스 has unique valuesUnique

Reproduction

Analysis started2024-03-14 21:00:49.867204
Analysis finished2024-03-14 21:00:52.489010
Duration2.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단지명
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size704.0 B
2024-03-15T06:00:53.338565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length232
Median length29
Mean length16.569444
Min length2

Characters and Unicode

Total characters1193
Distinct characters156
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row금산주공
2nd row아양주공1차
3rd row아양주공2차
4th row옥산주공
5th row삼부
ValueCountFrequency (%)
경기도시공사 2
 
2.4%
nhf 2
 
2.4%
금호어울림[3단지 1
 
1.2%
시티프라디움 1
 
1.2%
푸르지오 1
 
1.2%
안성 1
 
1.2%
서희스타힐스 1
 
1.2%
아양lh1단지 1
 
1.2%
센트럴시티 1
 
1.2%
롯데캐슬 1
 
1.2%
Other values (71) 71
85.5%
2024-03-15T06:00:54.785442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
745
62.4%
아 17
 
1.4%
공 12
 
1.0%
지 12
 
1.0%
트 10
 
0.8%
스 10
 
0.8%
단 10
 
0.8%
도 9
 
0.8%
림 8
 
0.7%
우 8
 
0.7%
Other values (146) 352
29.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 745
62.4%
Other Letter 397
33.3%
Uppercase Letter 24
 
2.0%
Decimal Number 15
 
1.3%
Open Punctuation 5
 
0.4%
Close Punctuation 5
 
0.4%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 17
 
4.3%
공 12
 
3.0%
지 12
 
3.0%
트 10
 
2.5%
스 10
 
2.5%
단 10
 
2.5%
도 9
 
2.3%
림 8
 
2.0%
우 8
 
2.0%
안 8
 
2.0%
Other values (124) 293
73.8%
Uppercase Letter
ValueCountFrequency (%)
H 5
20.8%
F 3
12.5%
I 3
12.5%
L 3
12.5%
N 3
12.5%
T 2
 
8.3%
Y 1
 
4.2%
R 1
 
4.2%
E 1
 
4.2%
G 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 6
40.0%
2 5
33.3%
5 2
 
13.3%
6 1
 
6.7%
3 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
[ 3
60.0%
( 2
40.0%
Close Punctuation
ValueCountFrequency (%)
] 3
60.0%
) 2
40.0%
Space Separator
ValueCountFrequency (%)
745
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 772
64.7%
Hangul 397
33.3%
Latin 24
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 17
 
4.3%
공 12
 
3.0%
지 12
 
3.0%
트 10
 
2.5%
스 10
 
2.5%
단 10
 
2.5%
도 9
 
2.3%
림 8
 
2.0%
우 8
 
2.0%
안 8
 
2.0%
Other values (124) 293
73.8%
Common
ValueCountFrequency (%)
745
96.5%
1 6
 
0.8%
2 5
 
0.6%
[ 3
 
0.4%
] 3
 
0.4%
) 2
 
0.3%
5 2
 
0.3%
( 2
 
0.3%
. 2
 
0.3%
6 1
 
0.1%
Latin
ValueCountFrequency (%)
H 5
20.8%
F 3
12.5%
I 3
12.5%
L 3
12.5%
N 3
12.5%
T 2
 
8.3%
Y 1
 
4.2%
R 1
 
4.2%
E 1
 
4.2%
G 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 796
66.7%
Hangul 397
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
745
93.6%
1 6
 
0.8%
H 5
 
0.6%
2 5
 
0.6%
[ 3
 
0.4%
F 3
 
0.4%
I 3
 
0.4%
] 3
 
0.4%
L 3
 
0.4%
N 3
 
0.4%
Other values (12) 17
 
2.1%
Hangul
ValueCountFrequency (%)
아 17
 
4.3%
공 12
 
3.0%
지 12
 
3.0%
트 10
 
2.5%
스 10
 
2.5%
단 10
 
2.5%
도 9
 
2.3%
림 8
 
2.0%
우 8
 
2.0%
안 8
 
2.0%
Other values (124) 293
73.8%

지번주소
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size704.0 B
2024-03-15T06:00:56.216979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length18.125
Min length14

Characters and Unicode

Total characters1305
Distinct characters74
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row경기도 안성시 금산동 100
2nd row경기도 안성시 아양동 300
3rd row경기도 안성시 아양동 384
4th row경기도 안성시 옥산동 10
5th row경기도 안성시 금산동 50-1
ValueCountFrequency (%)
경기도 72
21.8%
안성시 72
21.8%
공도읍 30
 
9.1%
만정리 11
 
3.3%
당왕동 6
 
1.8%
아양동 6
 
1.8%
진사리 6
 
1.8%
용두리 5
 
1.5%
마정리 4
 
1.2%
금산동 3
 
0.9%
Other values (102) 115
34.8%
2024-03-15T06:00:58.012604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270
20.7%
도 102
 
7.8%
기 76
 
5.8%
경 72
 
5.5%
안 72
 
5.5%
성 72
 
5.5%
시 72
 
5.5%
리 43
 
3.3%
1 34
 
2.6%
5 33
 
2.5%
Other values (64) 459
35.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 781
59.8%
Space Separator 270
 
20.7%
Decimal Number 233
 
17.9%
Dash Punctuation 20
 
1.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 102
13.1%
기 76
9.7%
경 72
 
9.2%
안 72
 
9.2%
성 72
 
9.2%
시 72
 
9.2%
리 43
 
5.5%
동 30
 
3.8%
공 30
 
3.8%
읍 30
 
3.8%
Other values (51) 182
23.3%
Decimal Number
ValueCountFrequency (%)
1 34
14.6%
5 33
14.2%
7 29
12.4%
4 26
11.2%
6 24
10.3%
3 23
9.9%
8 23
9.9%
0 18
7.7%
2 13
 
5.6%
9 10
 
4.3%
Space Separator
ValueCountFrequency (%)
270
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 781
59.8%
Common 524
40.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 102
13.1%
기 76
9.7%
경 72
 
9.2%
안 72
 
9.2%
성 72
 
9.2%
시 72
 
9.2%
리 43
 
5.5%
동 30
 
3.8%
공 30
 
3.8%
읍 30
 
3.8%
Other values (51) 182
23.3%
Common
ValueCountFrequency (%)
270
51.5%
1 34
 
6.5%
5 33
 
6.3%
7 29
 
5.5%
4 26
 
5.0%
6 24
 
4.6%
3 23
 
4.4%
8 23
 
4.4%
- 20
 
3.8%
0 18
 
3.4%
Other values (3) 24
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 781
59.8%
ASCII 524
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
270
51.5%
1 34
 
6.5%
5 33
 
6.3%
7 29
 
5.5%
4 26
 
5.0%
6 24
 
4.6%
3 23
 
4.4%
8 23
 
4.4%
- 20
 
3.8%
0 18
 
3.4%
Other values (3) 24
 
4.6%
Hangul
ValueCountFrequency (%)
도 102
13.1%
기 76
9.7%
경 72
 
9.2%
안 72
 
9.2%
성 72
 
9.2%
시 72
 
9.2%
리 43
 
5.5%
동 30
 
3.8%
공 30
 
3.8%
읍 30
 
3.8%
Other values (51) 182
23.3%

도로명주소
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size704.0 B
2024-03-15T06:00:59.312028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length18.194444
Min length13

Characters and Unicode

Total characters1310
Distinct characters89
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

Unique72 ?
Unique (%)100.0%

Sample

1st row경기도 안성시 안성맞춤대로 1127
2nd row경기도 안성시 아양로 23
3rd row경기도 안성시 석정2길 5
4th row경기도 안성시 중앙로 212
5th row경기도 안성시 금산1길 13
ValueCountFrequency (%)
경기도 72
22.6%
안성시 72
22.6%
공도읍 28
 
8.8%
공도로 6
 
1.9%
아양로 6
 
1.9%
서동대로 4
 
1.3%
안성맞춤대로 4
 
1.3%
진건중길 3
 
0.9%
대덕면 3
 
0.9%
고수2로 3
 
0.9%
Other values (101) 118
37.0%
2024-03-15T06:01:00.601655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
248
18.9%
도 111
 
8.5%
안 77
 
5.9%
성 77
 
5.9%
기 74
 
5.6%
경 72
 
5.5%
시 72
 
5.5%
로 44
 
3.4%
1 41
 
3.1%
공 39
 
3.0%
Other values (79) 455
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 818
62.4%
Space Separator 248
 
18.9%
Decimal Number 215
 
16.4%
Dash Punctuation 19
 
1.5%
Close Punctuation 5
 
0.4%
Open Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 111
13.6%
안 77
 
9.4%
성 77
 
9.4%
기 74
 
9.0%
경 72
 
8.8%
시 72
 
8.8%
로 44
 
5.4%
공 39
 
4.8%
읍 29
 
3.5%
길 26
 
3.2%
Other values (65) 197
24.1%
Decimal Number
ValueCountFrequency (%)
1 41
19.1%
2 33
15.3%
3 27
12.6%
7 23
10.7%
4 21
9.8%
6 19
8.8%
5 16
 
7.4%
9 15
 
7.0%
0 14
 
6.5%
8 6
 
2.8%
Space Separator
ValueCountFrequency (%)
248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 818
62.4%
Common 492
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 111
13.6%
안 77
 
9.4%
성 77
 
9.4%
기 74
 
9.0%
경 72
 
8.8%
시 72
 
8.8%
로 44
 
5.4%
공 39
 
4.8%
읍 29
 
3.5%
길 26
 
3.2%
Other values (65) 197
24.1%
Common
ValueCountFrequency (%)
248
50.4%
1 41
 
8.3%
2 33
 
6.7%
3 27
 
5.5%
7 23
 
4.7%
4 21
 
4.3%
6 19
 
3.9%
- 19
 
3.9%
5 16
 
3.3%
9 15
 
3.0%
Other values (4) 30
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 818
62.4%
ASCII 492
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
248
50.4%
1 41
 
8.3%
2 33
 
6.7%
3 27
 
5.5%
7 23
 
4.7%
4 21
 
4.3%
6 19
 
3.9%
- 19
 
3.9%
5 16
 
3.3%
9 15
 
3.0%
Other values (4) 30
 
6.1%
Hangul
ValueCountFrequency (%)
도 111
13.6%
안 77
 
9.4%
성 77
 
9.4%
기 74
 
9.0%
경 72
 
8.8%
시 72
 
8.8%
로 44
 
5.4%
공 39
 
4.8%
읍 29
 
3.5%
길 26
 
3.2%
Other values (65) 197
24.1%

분양형태
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size704.0 B
분양
60 
임대
11 
분양
 
1

Length

Max length3
Median length2
Mean length2.0138889
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
분양 60
83.3%
임대 11
 
15.3%
분양 1
 
1.4%

Length

2024-03-15T06:01:00.837302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:01:01.087288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분양 61
84.7%
임대 11
 
15.3%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6944444
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2024-03-15T06:01:01.410795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median6
Q311
95-th percentile17
Maximum30
Range29
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.3593117
Coefficient of variation (CV)0.69651705
Kurtosis3.0788782
Mean7.6944444
Median Absolute Deviation (MAD)3
Skewness1.36665
Sum554
Variance28.722222
MonotonicityNot monotonic
2024-03-15T06:01:01.789822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
5 9
12.5%
6 7
9.7%
1 6
 
8.3%
4 6
 
8.3%
8 6
 
8.3%
2 5
 
6.9%
10 5
 
6.9%
12 5
 
6.9%
7 4
 
5.6%
11 4
 
5.6%
Other values (8) 15
20.8%
ValueCountFrequency (%)
1 6
8.3%
2 5
6.9%
3 4
5.6%
4 6
8.3%
5 9
12.5%
6 7
9.7%
7 4
5.6%
8 6
8.3%
9 1
 
1.4%
10 5
6.9%
ValueCountFrequency (%)
30 1
 
1.4%
20 1
 
1.4%
18 1
 
1.4%
17 2
 
2.8%
16 2
 
2.8%
14 3
4.2%
12 5
6.9%
11 4
5.6%
10 5
6.9%
9 1
 
1.4%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct69
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean710.48611
Minimum192
Maximum2615
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2024-03-15T06:01:02.161484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192
5-th percentile220.2
Q1435
median547.5
Q3836.75
95-th percentile1706.35
Maximum2615
Range2423
Interquartile range (IQR)401.75

Descriptive statistics

Standard deviation503.86724
Coefficient of variation (CV)0.70918662
Kurtosis4.0697696
Mean710.48611
Median Absolute Deviation (MAD)221.5
Skewness1.9165299
Sum51155
Variance253882.2
MonotonicityNot monotonic
2024-03-15T06:01:02.591250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
299 2
 
2.8%
474 2
 
2.8%
499 2
 
2.8%
1378 1
 
1.4%
688 1
 
1.4%
759 1
 
1.4%
963 1
 
1.4%
540 1
 
1.4%
2320 1
 
1.4%
390 1
 
1.4%
Other values (59) 59
81.9%
ValueCountFrequency (%)
192 1
1.4%
194 1
1.4%
213 1
1.4%
218 1
1.4%
222 1
1.4%
224 1
1.4%
226 1
1.4%
232 1
1.4%
234 1
1.4%
250 1
1.4%
ValueCountFrequency (%)
2615 1
1.4%
2320 1
1.4%
2295 1
1.4%
1719 1
1.4%
1696 1
1.4%
1657 1
1.4%
1378 1
1.4%
1358 1
1.4%
1240 1
1.4%
1101 1
1.4%

관리사무소연락처
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size704.0 B
2024-03-15T06:01:03.618433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.111111
Min length12

Characters and Unicode

Total characters872
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row031-675-9029
2nd row031-674-2790
3rd row031-675-1903
4th row031-672-1785
5th row031-676-1966
ValueCountFrequency (%)
031-675-9029 1
 
1.4%
031-674-2790 1
 
1.4%
031-677-0661 1
 
1.4%
031-677-7205 1
 
1.4%
031-675-7273 1
 
1.4%
031-671-0540 1
 
1.4%
031-677-8172 1
 
1.4%
031-618-8106 1
 
1.4%
031-692-3162 1
 
1.4%
031-675-2760 1
 
1.4%
Other values (62) 62
86.1%
2024-03-15T06:01:05.090985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 144
16.5%
1 136
15.6%
0 114
13.1%
6 114
13.1%
3 99
11.4%
7 74
8.5%
5 57
 
6.5%
2 51
 
5.8%
8 34
 
3.9%
9 27
 
3.1%
Other values (2) 22
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 725
83.1%
Dash Punctuation 144
 
16.5%
Math Symbol 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 136
18.8%
0 114
15.7%
6 114
15.7%
3 99
13.7%
7 74
10.2%
5 57
7.9%
2 51
 
7.0%
8 34
 
4.7%
9 27
 
3.7%
4 19
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 872
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 144
16.5%
1 136
15.6%
0 114
13.1%
6 114
13.1%
3 99
11.4%
7 74
8.5%
5 57
 
6.5%
2 51
 
5.8%
8 34
 
3.9%
9 27
 
3.1%
Other values (2) 22
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 144
16.5%
1 136
15.6%
0 114
13.1%
6 114
13.1%
3 99
11.4%
7 74
8.5%
5 57
 
6.5%
2 51
 
5.8%
8 34
 
3.9%
9 27
 
3.1%
Other values (2) 22
 
2.5%

관리사무소팩스
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size704.0 B
2024-03-15T06:01:06.035352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.083333
Min length12

Characters and Unicode

Total characters870
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row031-673-8800
2nd row031-674-2797
3rd row031-672-2185
4th row031-675-1428
5th row031-675-1966
ValueCountFrequency (%)
031-673-8800 1
 
1.4%
031-654-6638 1
 
1.4%
031-677-0665 1
 
1.4%
031-677-7206 1
 
1.4%
031-676-7273 1
 
1.4%
031-671-0541 1
 
1.4%
031-671-3981 1
 
1.4%
031-618-8108 1
 
1.4%
031-692-3163 1
 
1.4%
031-675-2761 1
 
1.4%
Other values (63) 63
86.3%
2024-03-15T06:01:07.930122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 144
16.6%
1 131
15.1%
3 113
13.0%
6 107
12.3%
0 102
11.7%
7 82
9.4%
5 60
6.9%
2 41
 
4.7%
8 34
 
3.9%
9 27
 
3.1%
Other values (2) 29
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 722
83.0%
Dash Punctuation 144
 
16.6%
Space Separator 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 131
18.1%
3 113
15.7%
6 107
14.8%
0 102
14.1%
7 82
11.4%
5 60
8.3%
2 41
 
5.7%
8 34
 
4.7%
9 27
 
3.7%
4 25
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 870
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 144
16.6%
1 131
15.1%
3 113
13.0%
6 107
12.3%
0 102
11.7%
7 82
9.4%
5 60
6.9%
2 41
 
4.7%
8 34
 
3.9%
9 27
 
3.1%
Other values (2) 29
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 870
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 144
16.6%
1 131
15.1%
3 113
13.0%
6 107
12.3%
0 102
11.7%
7 82
9.4%
5 60
6.9%
2 41
 
4.7%
8 34
 
3.9%
9 27
 
3.1%
Other values (2) 29
 
3.3%

사용승인일
Text

Distinct70
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size704.0 B
2024-03-15T06:01:09.032673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length10
Mean length10.111111
Min length10

Characters and Unicode

Total characters728
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)94.4%

Sample

1st row1987-03-31
2nd row1991-09-14
3rd row1995-10-26
4th row1988-04-21
5th row1991-10-04
ValueCountFrequency (%)
2007-04-12 2
 
2.8%
2020-08-07 2
 
2.8%
2010-05-28 1
 
1.4%
2007-12-07 1
 
1.4%
2008-01-31 1
 
1.4%
2008-05-23 1
 
1.4%
2008-07-14 1
 
1.4%
2009-04-15 1
 
1.4%
2009-11-27 1
 
1.4%
2007-11-29 1
 
1.4%
Other values (60) 60
83.3%
2024-03-15T06:01:10.797095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 174
23.9%
- 144
19.8%
2 116
15.9%
1 105
14.4%
9 51
 
7.0%
8 30
 
4.1%
3 28
 
3.8%
7 23
 
3.2%
4 21
 
2.9%
5 16
 
2.2%
Other values (9) 20
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 576
79.1%
Dash Punctuation 144
 
19.8%
Other Letter 6
 
0.8%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 174
30.2%
2 116
20.1%
1 105
18.2%
9 51
 
8.9%
8 30
 
5.2%
3 28
 
4.9%
7 23
 
4.0%
4 21
 
3.6%
5 16
 
2.8%
6 12
 
2.1%
Other Letter
ValueCountFrequency (%)
임 1
16.7%
시 1
16.7%
사 1
16.7%
용 1
16.7%
승 1
16.7%
인 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 722
99.2%
Hangul 6
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 174
24.1%
- 144
19.9%
2 116
16.1%
1 105
14.5%
9 51
 
7.1%
8 30
 
4.2%
3 28
 
3.9%
7 23
 
3.2%
4 21
 
2.9%
5 16
 
2.2%
Other values (3) 14
 
1.9%
Hangul
ValueCountFrequency (%)
임 1
16.7%
시 1
16.7%
사 1
16.7%
용 1
16.7%
승 1
16.7%
인 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 722
99.2%
Hangul 6
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 174
24.1%
- 144
19.9%
2 116
16.1%
1 105
14.5%
9 51
 
7.1%
8 30
 
4.2%
3 28
 
3.9%
7 23
 
3.2%
4 21
 
2.9%
5 16
 
2.2%
Other values (3) 14
 
1.9%
Hangul
ValueCountFrequency (%)
임 1
16.7%
시 1
16.7%
사 1
16.7%
용 1
16.7%
승 1
16.7%
인 1
16.7%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size704.0 B
Minimum2024-01-30 00:00:00
Maximum2024-01-30 00:00:00
2024-03-15T06:01:11.150407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:01:11.457939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T06:00:51.219434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:00:50.722871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:00:51.465616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:00:50.979306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T06:01:11.688372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단지명지번주소도로명주소분양형태동수세대수관리사무소연락처관리사무소팩스사용승인일
단지명1.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
분양형태1.0001.0001.0001.0000.0000.0001.0001.0001.000
동수1.0001.0001.0000.0001.0000.8661.0001.0000.989
세대수1.0001.0001.0000.0000.8661.0001.0001.0000.988
관리사무소연락처1.0001.0001.0001.0001.0001.0001.0001.0001.000
관리사무소팩스1.0001.0001.0001.0001.0001.0001.0001.0001.000
사용승인일1.0001.0001.0001.0000.9890.9881.0001.0001.000
2024-03-15T06:01:11.986702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동수세대수분양형태
동수1.0000.7890.000
세대수0.7891.0000.000
분양형태0.0000.0001.000

Missing values

2024-03-15T06:00:51.800942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T06:00:52.293470image/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

단지명지번주소도로명주소분양형태동수세대수관리사무소연락처관리사무소팩스사용승인일데이터기준일
0금산주공경기도 안성시 금산동 100경기도 안성시 안성맞춤대로 1127분양11390031-675-9029031-673-88001987-03-312024-01-30
1아양주공1차경기도 안성시 아양동 300경기도 안성시 아양로 23분양17936031-674-2790031-674-27971991-09-142024-01-30
2아양주공2차경기도 안성시 아양동 384경기도 안성시 석정2길 5분양5712031-675-1903031-672-21851995-10-262024-01-30
3옥산주공경기도 안성시 옥산동 10경기도 안성시 중앙로 212분양11440031-672-1785031-675-14281988-04-212024-01-30
4삼부경기도 안성시 금산동 50-1경기도 안성시 금산1길 13분양2226031-676-1966031-675-19661991-10-042024-01-30
5한주경기도 안성시 봉산동 42경기도 안성시 월덕천길 17분양4420031-672-2482031-677-23531992-12-312024-01-30
6대우경기도 안성시 당왕동 534경기도 안성시 고수1로 19분양8762031-671-0295031-671-03351993-11-102024-01-30
7쌍용경기도 안성시 당왕동 536경기도 안성시 남파로 130분양5498031-675-1653031-676-02491993-10-142024-01-30
8동신경기도 안성시 숭인동 88경기도 안성시 혜산로37-24분양5496031-676-0181031-677-50521994-06-282024-01-30
9대우경남경기도 안성시 당왕동 535경기도 안성시 고수2로 20분양10984031-672-0226031-672-02271997-04-212024-01-30
단지명지번주소도로명주소분양형태동수세대수관리사무소연락처관리사무소팩스사용승인일데이터기준일
62아양LH6단지(행복)경기도 안성시 아양동 414경기도 안성시 아양로 72임대2699031-676-1983031-676-19842020-08-072024-01-30
63골든캐슬타워경기도 안성시 장기로 37경기도 안성시 인지동 7분양1299031-671-8494031-671-84952016-04-142024-01-30
64엘리시아경기도 안성시 중앙로 360경기도 안성시 석정동 29-2분양1192031-677-7841031-677-78402019-07-052024-01-30
65안성센트럴파밀리에경기도 안성시 석정동 368경기도 안성시 아양4로 46분양5644031-673-1102~3031-673-11062021-10-212024-01-30
66골든스테이경기도 안성시 신소현동 184경기도 안성시 공단2로 60분양1299031-671-0994031-671-09962023-03-242024-01-30
67E.TRINITY 공도센트럴파크경기도 안성시 공도읍 만정리 881경기도 안성시 공도읍 도화길 67-21분양7680031-692-3560031-692-35612023-04-102024-01-30
68수에르떼경기도 안성시 공도읍 만정리 424-97경기도 안성시 공도읍 승두길 35분양1224031-8054-8085031-8054-80862023-05-222024-01-30
69안성공도센트럴카운티아아파경기도 안성시 공도읍 용두리 757경기도 안성시 공도읍 서동대로 4057임대7533031-652-5551031-618-55532023-09-262024-01-30
70공도쌍용더플래티넘프리미어경기도 안성시 공도읍 승두리 73경기도 안성시 공도로 42-71분양141696031-651-1136031-618-11362023-12-292024-01-30
71안성금호어울림더프라임경기도 안성시 당왕동 157-10경기도 안성시 당목길 19임대121240031-677-7588031-677-75892024-01-30(임시사용승인)2024-01-30