Overview

Dataset statistics

Number of variables5
Number of observations295
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.9 KiB
Average record size in memory41.4 B

Variable types

Numeric1
Text2
Categorical2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15194/F/1/datasetView.do

Alerts

담당자 전화번호 is highly overall correlated with 관할관청High correlation
관할관청 is highly overall correlated with 담당자 전화번호High correlation
연번 has unique valuesUnique
업체명 has unique valuesUnique

Reproduction

Analysis started2024-03-23 03:18:32.731180
Analysis finished2024-03-23 03:18:34.010805
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct295
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148
Minimum1
Maximum295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-23T12:18:34.172549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.7
Q174.5
median148
Q3221.5
95-th percentile280.3
Maximum295
Range294
Interquartile range (IQR)147

Descriptive statistics

Standard deviation85.30338
Coefficient of variation (CV)0.57637419
Kurtosis-1.2
Mean148
Median Absolute Deviation (MAD)74
Skewness0
Sum43660
Variance7276.6667
MonotonicityStrictly increasing
2024-03-23T12:18:34.439292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
204 1
 
0.3%
202 1
 
0.3%
201 1
 
0.3%
200 1
 
0.3%
199 1
 
0.3%
198 1
 
0.3%
197 1
 
0.3%
196 1
 
0.3%
195 1
 
0.3%
Other values (285) 285
96.6%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
295 1
0.3%
294 1
0.3%
293 1
0.3%
292 1
0.3%
291 1
0.3%
290 1
0.3%
289 1
0.3%
288 1
0.3%
287 1
0.3%
286 1
0.3%

업체명
Text

UNIQUE 

Distinct295
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-23T12:18:34.837950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length8.5559322
Min length5

Characters and Unicode

Total characters2524
Distinct characters231
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique295 ?
Unique (%)100.0%

Sample

1st row(주)26렌트카
2nd row345렌트카(주)
3rd row(주)OK모터스
4th rowSK네트웍스(주)SK렌터카
5th row(주)가야렌트카
ValueCountFrequency (%)
주)26렌트카 1
 
0.3%
주)카렌디피티 1
 
0.3%
인지카(주 1
 
0.3%
주)인모션 1
 
0.3%
주)인렌트카 1
 
0.3%
이케이에프알(주 1
 
0.3%
이카모빌리티(주 1
 
0.3%
주)이지웨이렌트카 1
 
0.3%
주)이지원카 1
 
0.3%
주)이지런렌터카 1
 
0.3%
Other values (285) 285
96.6%
2024-03-23T12:18:35.406536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 295
 
11.7%
) 295
 
11.7%
주 290
 
11.5%
카 211
 
8.4%
렌 193
 
7.6%
트 145
 
5.7%
이 91
 
3.6%
스 72
 
2.9%
터 54
 
2.1%
리 32
 
1.3%
Other values (221) 846
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1923
76.2%
Open Punctuation 295
 
11.7%
Close Punctuation 295
 
11.7%
Uppercase Letter 6
 
0.2%
Decimal Number 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 290
 
15.1%
카 211
 
11.0%
렌 193
 
10.0%
트 145
 
7.5%
이 91
 
4.7%
스 72
 
3.7%
터 54
 
2.8%
리 32
 
1.7%
에 32
 
1.7%
아 29
 
1.5%
Other values (211) 774
40.2%
Decimal Number
ValueCountFrequency (%)
6 1
20.0%
2 1
20.0%
3 1
20.0%
4 1
20.0%
5 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
K 3
50.0%
S 2
33.3%
O 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 295
100.0%
Close Punctuation
ValueCountFrequency (%)
) 295
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1923
76.2%
Common 595
 
23.6%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 290
 
15.1%
카 211
 
11.0%
렌 193
 
10.0%
트 145
 
7.5%
이 91
 
4.7%
스 72
 
3.7%
터 54
 
2.8%
리 32
 
1.7%
에 32
 
1.7%
아 29
 
1.5%
Other values (211) 774
40.2%
Common
ValueCountFrequency (%)
( 295
49.6%
) 295
49.6%
6 1
 
0.2%
2 1
 
0.2%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
Latin
ValueCountFrequency (%)
K 3
50.0%
S 2
33.3%
O 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1923
76.2%
ASCII 601
 
23.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 295
49.1%
) 295
49.1%
K 3
 
0.5%
S 2
 
0.3%
O 1
 
0.2%
6 1
 
0.2%
2 1
 
0.2%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
Hangul
ValueCountFrequency (%)
주 290
 
15.1%
카 211
 
11.0%
렌 193
 
10.0%
트 145
 
7.5%
이 91
 
4.7%
스 72
 
3.7%
터 54
 
2.8%
리 32
 
1.7%
에 32
 
1.7%
아 29
 
1.5%
Other values (211) 774
40.2%

주사무소 주소
Text

Distinct291
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-23T12:18:35.949196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length41
Mean length31.135593
Min length15

Characters and Unicode

Total characters9185
Distinct characters332
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique287 ?
Unique (%)97.3%

Sample

1st row서울시 중랑구 동일로 604 2층
2nd row서울시 강남구 헌릉로745길 37 비동 203호(율현동,강남자동차매매장)
3rd row서울시 강남구 자곡로 201 , 강남라르고빌딩 116호
4th row서울시 종로구 청계천로 85 , 20층(관철동, 삼일빌딩)
5th row서울시 은평구 연서로 110 , 403호(역촌동)
ValueCountFrequency (%)
서울시 289
 
15.3%
160
 
8.5%
강남구 40
 
2.1%
서초구 27
 
1.4%
성동구 23
 
1.2%
송파구 23
 
1.2%
강서구 22
 
1.2%
2층 17
 
0.9%
강동구 16
 
0.8%
광진구 16
 
0.8%
Other values (845) 1260
66.6%
2024-03-23T12:18:37.098188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1615
 
17.6%
1 419
 
4.6%
서 386
 
4.2%
시 330
 
3.6%
구 328
 
3.6%
동 326
 
3.5%
로 311
 
3.4%
울 297
 
3.2%
, 277
 
3.0%
2 270
 
2.9%
Other values (322) 4626
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4982
54.2%
Decimal Number 1775
 
19.3%
Space Separator 1615
 
17.6%
Other Punctuation 278
 
3.0%
Close Punctuation 214
 
2.3%
Open Punctuation 214
 
2.3%
Dash Punctuation 58
 
0.6%
Uppercase Letter 47
 
0.5%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 386
 
7.7%
시 330
 
6.6%
구 328
 
6.6%
동 326
 
6.5%
로 311
 
6.2%
울 297
 
6.0%
호 207
 
4.2%
길 122
 
2.4%
층 120
 
2.4%
강 97
 
1.9%
Other values (287) 2458
49.3%
Uppercase Letter
ValueCountFrequency (%)
B 10
21.3%
A 9
19.1%
C 5
10.6%
K 3
 
6.4%
T 3
 
6.4%
S 3
 
6.4%
L 2
 
4.3%
H 2
 
4.3%
N 2
 
4.3%
D 1
 
2.1%
Other values (7) 7
14.9%
Decimal Number
ValueCountFrequency (%)
1 419
23.6%
2 270
15.2%
0 224
12.6%
3 184
10.4%
4 137
 
7.7%
6 132
 
7.4%
9 109
 
6.1%
7 107
 
6.0%
5 106
 
6.0%
8 87
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 277
99.6%
. 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
1615
100.0%
Close Punctuation
ValueCountFrequency (%)
) 214
100.0%
Open Punctuation
ValueCountFrequency (%)
( 214
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4982
54.2%
Common 4154
45.2%
Latin 49
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 386
 
7.7%
시 330
 
6.6%
구 328
 
6.6%
동 326
 
6.5%
로 311
 
6.2%
울 297
 
6.0%
호 207
 
4.2%
길 122
 
2.4%
층 120
 
2.4%
강 97
 
1.9%
Other values (287) 2458
49.3%
Latin
ValueCountFrequency (%)
B 10
20.4%
A 9
18.4%
C 5
10.2%
K 3
 
6.1%
T 3
 
6.1%
S 3
 
6.1%
L 2
 
4.1%
H 2
 
4.1%
N 2
 
4.1%
D 1
 
2.0%
Other values (9) 9
18.4%
Common
ValueCountFrequency (%)
1615
38.9%
1 419
 
10.1%
, 277
 
6.7%
2 270
 
6.5%
0 224
 
5.4%
) 214
 
5.2%
( 214
 
5.2%
3 184
 
4.4%
4 137
 
3.3%
6 132
 
3.2%
Other values (6) 468
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4982
54.2%
ASCII 4203
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1615
38.4%
1 419
 
10.0%
, 277
 
6.6%
2 270
 
6.4%
0 224
 
5.3%
) 214
 
5.1%
( 214
 
5.1%
3 184
 
4.4%
4 137
 
3.3%
6 132
 
3.1%
Other values (25) 517
 
12.3%
Hangul
ValueCountFrequency (%)
서 386
 
7.7%
시 330
 
6.6%
구 328
 
6.6%
동 326
 
6.5%
로 311
 
6.2%
울 297
 
6.0%
호 207
 
4.2%
길 122
 
2.4%
층 120
 
2.4%
강 97
 
1.9%
Other values (287) 2458
49.3%

관할관청
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
강남구
34 
서초구
26 
송파구
23 
성동구
23 
강서구
20 
Other values (24)
169 

Length

Max length4
Median length4
Mean length3.9525424
Min length3

Unique

Unique3 ?
Unique (%)1.0%

Sample

1st row 중랑구
2nd row 강남구
3rd row 강남구
4th row서울시시
5th row 은평구

Common Values

ValueCountFrequency (%)
강남구 34
 
11.5%
서초구 26
 
8.8%
송파구 23
 
7.8%
성동구 23
 
7.8%
강서구 20
 
6.8%
광진구 16
 
5.4%
강동구 16
 
5.4%
구로구 13
 
4.4%
서울시 12
 
4.1%
중구 12
 
4.1%
Other values (19) 100
33.9%

Length

2024-03-23T12:18:37.324890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남구 35
 
11.9%
서초구 26
 
8.8%
송파구 23
 
7.8%
성동구 23
 
7.8%
강서구 20
 
6.8%
광진구 16
 
5.4%
강동구 16
 
5.4%
구로구 13
 
4.4%
서울시 12
 
4.1%
중구 12
 
4.1%
Other values (17) 99
33.6%

담당자 전화번호
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3423-6503
35 
2155-7179
26 
2147-3151
23 
2286-5679
23 
2600-4123
20 
Other values (19)
168 

Length

Max length9
Median length9
Mean length8.8610169
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2094-2578
2nd row3423-6503
3rd row3423-6503
4th row2133-2339
5th row351-7755

Common Values

ValueCountFrequency (%)
3423-6503 35
 
11.9%
2155-7179 26
 
8.8%
2147-3151 23
 
7.8%
2286-5679 23
 
7.8%
2600-4123 20
 
6.8%
2133-2339 18
 
6.1%
450-7916 16
 
5.4%
3425-6247 16
 
5.4%
860-3194 13
 
4.4%
3396-6226 12
 
4.1%
Other values (14) 93
31.5%

Length

2024-03-23T12:18:37.491807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3423-6503 35
 
11.9%
2155-7179 26
 
8.8%
2147-3151 23
 
7.8%
2286-5679 23
 
7.8%
2600-4123 20
 
6.8%
2133-2339 18
 
6.1%
450-7916 16
 
5.4%
3425-6247 16
 
5.4%
860-3194 13
 
4.4%
3396-6226 12
 
4.1%
Other values (14) 93
31.5%

Interactions

2024-03-23T12:18:33.383832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T12:18:37.604437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관할관청담당자 전화번호
연번1.0000.2380.152
관할관청0.2381.0001.000
담당자 전화번호0.1521.0001.000
2024-03-23T12:18:37.745172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
담당자 전화번호관할관청
담당자 전화번호1.0000.991
관할관청0.9911.000
2024-03-23T12:18:37.905849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관할관청담당자 전화번호
연번1.0000.0820.052
관할관청0.0821.0000.991
담당자 전화번호0.0520.9911.000

Missing values

2024-03-23T12:18:33.729311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T12:18:33.928414image/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

연번업체명주사무소 주소관할관청담당자 전화번호
01(주)26렌트카서울시 중랑구 동일로 604 2층중랑구2094-2578
12345렌트카(주)서울시 강남구 헌릉로745길 37 비동 203호(율현동,강남자동차매매장)강남구3423-6503
23(주)OK모터스서울시 강남구 자곡로 201 , 강남라르고빌딩 116호강남구3423-6503
34SK네트웍스(주)SK렌터카서울시 종로구 청계천로 85 , 20층(관철동, 삼일빌딩)서울시시2133-2339
45(주)가야렌트카서울시 은평구 연서로 110 , 403호(역촌동)은평구351-7755
56(주)가을렌트카서울시 강서구 양천로 400-12 , 더리브골드타워 311호강서구2600-4123
67(주)가인렌트카서울시 송파구 중대로38길 12 , 4층 402호(오금동)송파구2147-3151
78강남렌트카(주)서울시 서초구 바우뫼로41길 72 - 2 화인빌딩 301호 3층서초구2155-7179
89(주)거성렌트카서울시 서초구 청계산로 217 자연누리오피스텔 2층, 254호서초구2155-7179
910건아렌트카(주)서울시 용산구 독서당로 23 402호(한남동,전국빌딩)용산구2199-7748
연번업체명주사무소 주소관할관청담당자 전화번호
285286(주)해동렌트카서울시 강서구 양천로 410, 2층 (가양동)강서구2600-4123
286287(주)해피네트웍스서울시 성동구 자동차시장1길 94-47 ,701호(용답동,장안모터프라자)성동구2286-5679
287288(주)햇살렌트카서울시 중랑구 망우로 316 1층 112호(상봉동, 이지팰리스)중랑구2094-2578
288289향우렌트카(주)서울시 강서구 강서로56길 102 2층(등촌동, 세진빌딩)강서구2600-4123
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