Overview

Dataset statistics

Number of variables4
Number of observations83
Missing cells37
Missing cells (%)11.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory34.6 B

Variable types

Numeric1
Text3

Dataset

Description경기도 안양시 관내 대부 및 대부중개업체 등록현황(관내 대부 및 대부중개업체상호, 관내 대부 및 대부중개업체 소재지, 관내 대부 및 대부중개업체 전화번호 제공) 데이터 정보입니다.
URLhttps://www.data.go.kr/data/3045135/fileData.do

Alerts

전화번호 has 37 (44.6%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:29:52.009306
Analysis finished2023-12-12 01:29:52.841255
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42
Minimum1
Maximum83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-12T10:29:52.949035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.1
Q121.5
median42
Q362.5
95-th percentile78.9
Maximum83
Range82
Interquartile range (IQR)41

Descriptive statistics

Standard deviation24.103942
Coefficient of variation (CV)0.57390337
Kurtosis-1.2
Mean42
Median Absolute Deviation (MAD)21
Skewness0
Sum3486
Variance581
MonotonicityStrictly increasing
2023-12-12T10:29:53.137412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
54 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
Other values (73) 73
88.0%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%

상호
Text

Distinct71
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-12T10:29:53.435282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length8.6024096
Min length4

Characters and Unicode

Total characters714
Distinct characters152
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

Unique59 ?
Unique (%)71.1%

Sample

1st row함께하는대부
2nd row엔젤대부
3rd row주식회사 제이비파트너스대부
4th row미래119대부
5th row드림뱅크대부
ValueCountFrequency (%)
주식회사 24
 
20.7%
대부중개 4
 
3.4%
빅중개대부 2
 
1.7%
재운캐피탈대부 2
 
1.7%
드림뱅크대부 2
 
1.7%
엘앤케이자산운용대부 2
 
1.7%
나우파이낸스대부 2
 
1.7%
몽키대부 2
 
1.7%
고려사대부 2
 
1.7%
한오름대부 2
 
1.7%
Other values (68) 72
62.1%
2023-12-12T10:29:53.932638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 83
 
11.6%
부 82
 
11.5%
주 33
 
4.6%
33
 
4.6%
사 30
 
4.2%
회 24
 
3.4%
식 24
 
3.4%
이 22
 
3.1%
개 16
 
2.2%
중 16
 
2.2%
Other values (142) 351
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 636
89.1%
Space Separator 33
 
4.6%
Uppercase Letter 20
 
2.8%
Close Punctuation 9
 
1.3%
Open Punctuation 9
 
1.3%
Decimal Number 5
 
0.7%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 83
 
13.1%
부 82
 
12.9%
주 33
 
5.2%
사 30
 
4.7%
회 24
 
3.8%
식 24
 
3.8%
이 22
 
3.5%
개 16
 
2.5%
중 16
 
2.5%
스 12
 
1.9%
Other values (122) 294
46.2%
Uppercase Letter
ValueCountFrequency (%)
N 4
20.0%
A 2
10.0%
I 2
10.0%
C 2
10.0%
L 2
10.0%
R 2
10.0%
F 1
 
5.0%
H 1
 
5.0%
K 1
 
5.0%
J 1
 
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
2 1
20.0%
4 1
20.0%
9 1
20.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 636
89.1%
Common 58
 
8.1%
Latin 20
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 83
 
13.1%
부 82
 
12.9%
주 33
 
5.2%
사 30
 
4.7%
회 24
 
3.8%
식 24
 
3.8%
이 22
 
3.5%
개 16
 
2.5%
중 16
 
2.5%
스 12
 
1.9%
Other values (122) 294
46.2%
Latin
ValueCountFrequency (%)
N 4
20.0%
A 2
10.0%
I 2
10.0%
C 2
10.0%
L 2
10.0%
R 2
10.0%
F 1
 
5.0%
H 1
 
5.0%
K 1
 
5.0%
J 1
 
5.0%
Other values (2) 2
10.0%
Common
ValueCountFrequency (%)
33
56.9%
) 9
 
15.5%
( 9
 
15.5%
& 2
 
3.4%
1 2
 
3.4%
2 1
 
1.7%
4 1
 
1.7%
9 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 636
89.1%
ASCII 78
 
10.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 83
 
13.1%
부 82
 
12.9%
주 33
 
5.2%
사 30
 
4.7%
회 24
 
3.8%
식 24
 
3.8%
이 22
 
3.5%
개 16
 
2.5%
중 16
 
2.5%
스 12
 
1.9%
Other values (122) 294
46.2%
ASCII
ValueCountFrequency (%)
33
42.3%
) 9
 
11.5%
( 9
 
11.5%
N 4
 
5.1%
& 2
 
2.6%
A 2
 
2.6%
I 2
 
2.6%
C 2
 
2.6%
1 2
 
2.6%
L 2
 
2.6%
Other values (10) 11
 
14.1%

소재지(도로명)
Text

Distinct65
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-12T10:29:54.345744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length39.819277
Min length24

Characters and Unicode

Total characters3305
Distinct characters130
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)59.0%

Sample

1st row경기도 안양시 만안구 예술공원로 196(안양동)
2nd row경기도 안양시 동안구 안양판교로 20, 신한데뷰오피스텔 306-C30호 (관양동)
3rd row경기도 안양시 동안구 엘에스로 92, 국제유통단지 14동 228호 (호계동)
4th row경기도 안양시 동안구 안양판교로 20, 신한데뷰오피스텔 1118호 (관양동)
5th row경기도 안양시 동안구 흥안대로 519, 아이퍼스트타워 ES601-12호 (관양동)
ValueCountFrequency (%)
경기도 83
 
12.5%
안양시 83
 
12.5%
동안구 53
 
8.0%
관양동 42
 
6.3%
만안구 30
 
4.5%
안양동 26
 
3.9%
시민대로 15
 
2.3%
안양로 15
 
2.3%
흥안대로 14
 
2.1%
277 9
 
1.4%
Other values (155) 296
44.4%
2023-12-12T10:29:54.994383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
583
 
17.6%
안 240
 
7.3%
양 180
 
5.4%
1 144
 
4.4%
동 144
 
4.4%
시 110
 
3.3%
로 95
 
2.9%
도 87
 
2.6%
, 87
 
2.6%
경 83
 
2.5%
Other values (120) 1552
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1861
56.3%
Space Separator 583
 
17.6%
Decimal Number 557
 
16.9%
Other Punctuation 87
 
2.6%
Close Punctuation 83
 
2.5%
Open Punctuation 83
 
2.5%
Uppercase Letter 32
 
1.0%
Dash Punctuation 19
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 240
 
12.9%
양 180
 
9.7%
동 144
 
7.7%
시 110
 
5.9%
로 95
 
5.1%
도 87
 
4.7%
경 83
 
4.5%
호 83
 
4.5%
구 83
 
4.5%
기 83
 
4.5%
Other values (94) 673
36.2%
Uppercase Letter
ValueCountFrequency (%)
E 10
31.2%
S 8
25.0%
C 3
 
9.4%
R 2
 
6.2%
O 2
 
6.2%
T 2
 
6.2%
A 1
 
3.1%
W 1
 
3.1%
J 1
 
3.1%
P 1
 
3.1%
Decimal Number
ValueCountFrequency (%)
1 144
25.9%
2 83
14.9%
0 79
14.2%
3 50
 
9.0%
5 40
 
7.2%
4 38
 
6.8%
9 34
 
6.1%
6 31
 
5.6%
7 30
 
5.4%
8 28
 
5.0%
Space Separator
ValueCountFrequency (%)
583
100.0%
Other Punctuation
ValueCountFrequency (%)
, 87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1861
56.3%
Common 1412
42.7%
Latin 32
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 240
 
12.9%
양 180
 
9.7%
동 144
 
7.7%
시 110
 
5.9%
로 95
 
5.1%
도 87
 
4.7%
경 83
 
4.5%
호 83
 
4.5%
구 83
 
4.5%
기 83
 
4.5%
Other values (94) 673
36.2%
Common
ValueCountFrequency (%)
583
41.3%
1 144
 
10.2%
, 87
 
6.2%
) 83
 
5.9%
( 83
 
5.9%
2 83
 
5.9%
0 79
 
5.6%
3 50
 
3.5%
5 40
 
2.8%
4 38
 
2.7%
Other values (5) 142
 
10.1%
Latin
ValueCountFrequency (%)
E 10
31.2%
S 8
25.0%
C 3
 
9.4%
R 2
 
6.2%
O 2
 
6.2%
T 2
 
6.2%
A 1
 
3.1%
W 1
 
3.1%
J 1
 
3.1%
P 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1861
56.3%
ASCII 1444
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
583
40.4%
1 144
 
10.0%
, 87
 
6.0%
) 83
 
5.7%
( 83
 
5.7%
2 83
 
5.7%
0 79
 
5.5%
3 50
 
3.5%
5 40
 
2.8%
4 38
 
2.6%
Other values (16) 174
 
12.0%
Hangul
ValueCountFrequency (%)
안 240
 
12.9%
양 180
 
9.7%
동 144
 
7.7%
시 110
 
5.9%
로 95
 
5.1%
도 87
 
4.7%
경 83
 
4.5%
호 83
 
4.5%
구 83
 
4.5%
기 83
 
4.5%
Other values (94) 673
36.2%

전화번호
Text

MISSING 

Distinct35
Distinct (%)76.1%
Missing37
Missing (%)44.6%
Memory size796.0 B
2023-12-12T10:29:55.311137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.021739
Min length9

Characters and Unicode

Total characters553
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

Unique24 ?
Unique (%)52.2%

Sample

1st row031-473-5595
2nd row031-466-6964
3rd row031-388-8998
4th row070-8153-2514
5th row070-4045-6408
ValueCountFrequency (%)
031-360-8185 2
 
4.3%
070-7593-3868 2
 
4.3%
070-4415-9240 2
 
4.3%
031-340-7886 2
 
4.3%
031-466-6964 2
 
4.3%
031-500-5401 2
 
4.3%
1833-8084 2
 
4.3%
031-468-5111 2
 
4.3%
031-469-9656 2
 
4.3%
031-385-3898 2
 
4.3%
Other values (25) 26
56.5%
2023-12-12T10:29:55.718042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 90
16.3%
0 83
15.0%
3 74
13.4%
1 66
11.9%
4 57
10.3%
8 42
7.6%
6 36
 
6.5%
5 34
 
6.1%
9 31
 
5.6%
7 25
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 463
83.7%
Dash Punctuation 90
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 83
17.9%
3 74
16.0%
1 66
14.3%
4 57
12.3%
8 42
9.1%
6 36
7.8%
5 34
7.3%
9 31
 
6.7%
7 25
 
5.4%
2 15
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 553
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 90
16.3%
0 83
15.0%
3 74
13.4%
1 66
11.9%
4 57
10.3%
8 42
7.6%
6 36
 
6.5%
5 34
 
6.1%
9 31
 
5.6%
7 25
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 553
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 90
16.3%
0 83
15.0%
3 74
13.4%
1 66
11.9%
4 57
10.3%
8 42
7.6%
6 36
 
6.5%
5 34
 
6.1%
9 31
 
5.6%
7 25
 
4.5%

Interactions

2023-12-12T10:29:52.515992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:29:55.825164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번상호소재지(도로명)전화번호
순번1.0000.0000.0000.612
상호0.0001.0001.0001.000
소재지(도로명)0.0001.0001.0001.000
전화번호0.6121.0001.0001.000

Missing values

2023-12-12T10:29:52.679436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:29:52.793869image/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

순번상호소재지(도로명)전화번호
01함께하는대부경기도 안양시 만안구 예술공원로 196(안양동)031-473-5595
12엔젤대부경기도 안양시 동안구 안양판교로 20, 신한데뷰오피스텔 306-C30호 (관양동)<NA>
23주식회사 제이비파트너스대부경기도 안양시 동안구 엘에스로 92, 국제유통단지 14동 228호 (호계동)<NA>
34미래119대부경기도 안양시 동안구 안양판교로 20, 신한데뷰오피스텔 1118호 (관양동)<NA>
45드림뱅크대부경기도 안양시 동안구 흥안대로 519, 아이퍼스트타워 ES601-12호 (관양동)031-466-6964
56정직한 대부경기도 안양시 동안구 흥안대로 528, 타워빌딩 702-2호 (관양동)<NA>
67몽키대부경기도 안양시 만안구 안양로 110, 엘리제빌리지 219호 (안양동)<NA>
78나우파이낸스대부경기도 안양시 만안구 안양로 110, 엘리제빌리지 327호 (안양동)<NA>
89주식회사 비엔피엘대부경기도 안양시 동안구 시민대로 272, 평촌동양트레벨파크 1024호 (관양동)031-388-8998
910주식회사 서울파이낸스대부경기도 안양시 동안구 인덕원로30번길 8, 301호 (관양동)070-8153-2514
순번상호소재지(도로명)전화번호
7374주식회사 세종이앤시경기도 안양시 만안구 안양로 115, 도정오피스텔 1114호 (안양동)031-344-9200
7475한솔 대부중개경기도 안양시 만안구 문예로 50, 203-3호 (안양동, 한림시티빌아파트)<NA>
7576완소대부중개경기도 안양시 만안구 문예로 50, 2층 203-5호 (안양동, 한림시티빌아파트)<NA>
7677주식회사 그리핀자산관리대부경기도 안양시 동안구 시민대로 277, 세방글로벌시티 1906호 (관양동)031-387-6512
7778(주)정목대부중개경기도 안양시 만안구 장내로149번길 30 (안양동)<NA>
7879(주)엠제이캐피탈대부중개경기도 안양시 동안구 흥안대로 519, 아이퍼스트타워 ES601-195호 (관양동)<NA>
7980주식회사 금새자산관리대부경기도 안양시 동안구 시민대로 277, 세방글로벌시티 1608호 (관양동)031-469-9656
8081세움대부중개경기도 안양시 만안구 만안로 11, 브레인빌딩 302호 (안양동)1833-8084
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