Overview

Dataset statistics

Number of variables5
Number of observations1538
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory61.7 KiB
Average record size in memory41.1 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description인천광역시 서구 중개업소등록현황에 대한 데이터로 연번, 사무소명, 사무소전화번호, 사무소주소 등의 정보가 포함되어 있습니다.
URLhttps://www.data.go.kr/data/15090884/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:21:57.310134
Analysis finished2023-12-12 07:21:58.050021
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct1538
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean769.5
Minimum1
Maximum1538
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.6 KiB
2023-12-12T16:21:58.521755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile77.85
Q1385.25
median769.5
Q31153.75
95-th percentile1461.15
Maximum1538
Range1537
Interquartile range (IQR)768.5

Descriptive statistics

Standard deviation444.12667
Coefficient of variation (CV)0.57716267
Kurtosis-1.2
Mean769.5
Median Absolute Deviation (MAD)384.5
Skewness0
Sum1183491
Variance197248.5
MonotonicityStrictly increasing
2023-12-12T16:21:58.820052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1155 1
 
0.1%
1033 1
 
0.1%
1032 1
 
0.1%
1031 1
 
0.1%
1030 1
 
0.1%
1029 1
 
0.1%
1028 1
 
0.1%
1027 1
 
0.1%
1026 1
 
0.1%
Other values (1528) 1528
99.3%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1538 1
0.1%
1537 1
0.1%
1536 1
0.1%
1535 1
0.1%
1534 1
0.1%
1533 1
0.1%
1532 1
0.1%
1531 1
0.1%
1530 1
0.1%
1529 1
0.1%

등록번호
Text

UNIQUE 

Distinct1538
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
2023-12-12T16:21:59.121437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length14.178804
Min length8

Characters and Unicode

Total characters21807
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

Unique1538 ?
Unique (%)100.0%

Sample

1st row3380-2349
2nd row3380-2340
3rd row3380-2329
4th row3380-2326
5th row3380-2308
ValueCountFrequency (%)
3380-2349 1
 
0.1%
28260-2021-00262 1
 
0.1%
28260-2021-00083 1
 
0.1%
28260-2021-00082 1
 
0.1%
28260-2021-00081 1
 
0.1%
28260-2021-00078 1
 
0.1%
28260-2021-00076 1
 
0.1%
28260-2021-00073 1
 
0.1%
28260-2021-00072 1
 
0.1%
28260-2021-00071 1
 
0.1%
Other values (1528) 1528
99.3%
2023-12-12T16:21:59.522464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5864
26.9%
2 5111
23.4%
- 2676
12.3%
8 1984
 
9.1%
6 1519
 
7.0%
1 1475
 
6.8%
3 1360
 
6.2%
4 484
 
2.2%
5 447
 
2.0%
7 447
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19131
87.7%
Dash Punctuation 2676
 
12.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5864
30.7%
2 5111
26.7%
8 1984
 
10.4%
6 1519
 
7.9%
1 1475
 
7.7%
3 1360
 
7.1%
4 484
 
2.5%
5 447
 
2.3%
7 447
 
2.3%
9 440
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 2676
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21807
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5864
26.9%
2 5111
23.4%
- 2676
12.3%
8 1984
 
9.1%
6 1519
 
7.0%
1 1475
 
6.8%
3 1360
 
6.2%
4 484
 
2.2%
5 447
 
2.0%
7 447
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21807
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5864
26.9%
2 5111
23.4%
- 2676
12.3%
8 1984
 
9.1%
6 1519
 
7.0%
1 1475
 
6.8%
3 1360
 
6.2%
4 484
 
2.2%
5 447
 
2.0%
7 447
 
2.0%

사무소명
Text

Distinct1313
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
2023-12-12T16:21:59.760301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length12.13394
Min length6

Characters and Unicode

Total characters18662
Distinct characters433
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1189 ?
Unique (%)77.3%

Sample

1st rowLG부동산공인중개사사무소
2nd row조은 공인중개사사무소
3rd row뉴신명럭키공인중개사사무소
4th row라인부동산공인중개사사무소
5th row행복공인중개사사무소
ValueCountFrequency (%)
공인중개사사무소 34
 
2.1%
삼성공인중개사사무소 10
 
0.6%
미래공인중개사사무소 7
 
0.4%
굿모닝공인중개사사무소 7
 
0.4%
태양공인중개사사무소 6
 
0.4%
에이스공인중개사사무소 6
 
0.4%
우리공인중개사사무소 5
 
0.3%
현대공인중개사사무소 5
 
0.3%
탑공인중개사사무소 5
 
0.3%
참조은공인중개사사무소 5
 
0.3%
Other values (1308) 1492
94.3%
2023-12-12T16:22:00.136291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 3028
16.2%
인 1562
 
8.4%
중 1545
 
8.3%
개 1542
 
8.3%
소 1524
 
8.2%
공 1523
 
8.2%
무 1517
 
8.1%
동 474
 
2.5%
부 455
 
2.4%
산 453
 
2.4%
Other values (423) 5039
27.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18324
98.2%
Uppercase Letter 120
 
0.6%
Decimal Number 110
 
0.6%
Space Separator 44
 
0.2%
Open Punctuation 21
 
0.1%
Close Punctuation 21
 
0.1%
Lowercase Letter 16
 
0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 3028
16.5%
인 1562
 
8.5%
중 1545
 
8.4%
개 1542
 
8.4%
소 1524
 
8.3%
공 1523
 
8.3%
무 1517
 
8.3%
동 474
 
2.6%
부 455
 
2.5%
산 453
 
2.5%
Other values (384) 4701
25.7%
Uppercase Letter
ValueCountFrequency (%)
K 39
32.5%
S 28
23.3%
O 9
 
7.5%
L 6
 
5.0%
T 6
 
5.0%
H 5
 
4.2%
G 5
 
4.2%
A 3
 
2.5%
E 3
 
2.5%
C 3
 
2.5%
Other values (10) 13
 
10.8%
Decimal Number
ValueCountFrequency (%)
1 58
52.7%
2 18
 
16.4%
4 14
 
12.7%
0 8
 
7.3%
3 4
 
3.6%
7 4
 
3.6%
6 2
 
1.8%
5 2
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
e 9
56.2%
h 3
 
18.8%
c 2
 
12.5%
d 1
 
6.2%
k 1
 
6.2%
Space Separator
ValueCountFrequency (%)
44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18323
98.2%
Common 201
 
1.1%
Latin 137
 
0.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 3028
16.5%
인 1562
 
8.5%
중 1545
 
8.4%
개 1542
 
8.4%
소 1524
 
8.3%
공 1523
 
8.3%
무 1517
 
8.3%
동 474
 
2.6%
부 455
 
2.5%
산 453
 
2.5%
Other values (383) 4700
25.7%
Latin
ValueCountFrequency (%)
K 39
28.5%
S 28
20.4%
O 9
 
6.6%
e 9
 
6.6%
L 6
 
4.4%
T 6
 
4.4%
H 5
 
3.6%
G 5
 
3.6%
h 3
 
2.2%
A 3
 
2.2%
Other values (16) 24
17.5%
Common
ValueCountFrequency (%)
1 58
28.9%
44
21.9%
( 21
 
10.4%
) 21
 
10.4%
2 18
 
9.0%
4 14
 
7.0%
0 8
 
4.0%
3 4
 
2.0%
7 4
 
2.0%
- 3
 
1.5%
Other values (3) 6
 
3.0%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18323
98.2%
ASCII 337
 
1.8%
Number Forms 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 3028
16.5%
인 1562
 
8.5%
중 1545
 
8.4%
개 1542
 
8.4%
소 1524
 
8.3%
공 1523
 
8.3%
무 1517
 
8.3%
동 474
 
2.6%
부 455
 
2.5%
산 453
 
2.5%
Other values (383) 4700
25.7%
ASCII
ValueCountFrequency (%)
1 58
17.2%
44
13.1%
K 39
11.6%
S 28
 
8.3%
( 21
 
6.2%
) 21
 
6.2%
2 18
 
5.3%
4 14
 
4.2%
O 9
 
2.7%
e 9
 
2.7%
Other values (28) 76
22.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%
CJK
ValueCountFrequency (%)
愛 1
100.0%

사무소주소
Text

Distinct1459
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
2023-12-12T16:22:00.428579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length46
Mean length35.308843
Min length15

Characters and Unicode

Total characters54305
Distinct characters380
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

Unique1385 ?
Unique (%)90.1%

Sample

1st row인천광역시 서구 가정로394번길 14(가정동)
2nd row인천광역시 서구 고래울로 6-1(가좌동)
3rd row인천광역시 서구 승학로 447, 상가101호(검암동, 신명아파트)
4th row인천광역시 서구 새오개로78번길 6(신현동)
5th row인천광역시 서구 검단로 489(마전동)
ValueCountFrequency (%)
인천광역시 1536
 
17.2%
서구 1536
 
17.2%
이음5로 131
 
1.5%
상가동 106
 
1.2%
가정로 67
 
0.7%
단지내상가 66
 
0.7%
1층 63
 
0.7%
상가 58
 
0.6%
청라커낼로 55
 
0.6%
이음2로 42
 
0.5%
Other values (2085) 5282
59.1%
2023-12-12T16:22:00.839406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7404
 
13.6%
1 2796
 
5.1%
, 2207
 
4.1%
동 2006
 
3.7%
서 1663
 
3.1%
시 1648
 
3.0%
로 1601
 
2.9%
인 1557
 
2.9%
광 1552
 
2.9%
천 1545
 
2.8%
Other values (370) 30326
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31599
58.2%
Decimal Number 9661
 
17.8%
Space Separator 7404
 
13.6%
Other Punctuation 2227
 
4.1%
Open Punctuation 1482
 
2.7%
Close Punctuation 1481
 
2.7%
Uppercase Letter 247
 
0.5%
Dash Punctuation 184
 
0.3%
Lowercase Letter 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2006
 
6.3%
서 1663
 
5.3%
시 1648
 
5.2%
로 1601
 
5.1%
인 1557
 
4.9%
광 1552
 
4.9%
천 1545
 
4.9%
역 1541
 
4.9%
구 1536
 
4.9%
호 1246
 
3.9%
Other values (324) 15704
49.7%
Uppercase Letter
ValueCountFrequency (%)
B 110
44.5%
S 32
 
13.0%
A 24
 
9.7%
J 20
 
8.1%
K 16
 
6.5%
C 10
 
4.0%
D 7
 
2.8%
I 4
 
1.6%
M 4
 
1.6%
V 3
 
1.2%
Other values (9) 17
 
6.9%
Decimal Number
ValueCountFrequency (%)
1 2796
28.9%
0 1431
14.8%
2 1193
12.3%
3 926
 
9.6%
5 699
 
7.2%
4 669
 
6.9%
6 586
 
6.1%
7 515
 
5.3%
8 458
 
4.7%
9 388
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
e 9
45.0%
s 3
 
15.0%
d 2
 
10.0%
w 1
 
5.0%
h 1
 
5.0%
i 1
 
5.0%
a 1
 
5.0%
l 1
 
5.0%
r 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 2207
99.1%
@ 16
 
0.7%
. 3
 
0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
7404
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1482
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1481
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31599
58.2%
Common 22439
41.3%
Latin 267
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2006
 
6.3%
서 1663
 
5.3%
시 1648
 
5.2%
로 1601
 
5.1%
인 1557
 
4.9%
광 1552
 
4.9%
천 1545
 
4.9%
역 1541
 
4.9%
구 1536
 
4.9%
호 1246
 
3.9%
Other values (324) 15704
49.7%
Latin
ValueCountFrequency (%)
B 110
41.2%
S 32
 
12.0%
A 24
 
9.0%
J 20
 
7.5%
K 16
 
6.0%
C 10
 
3.7%
e 9
 
3.4%
D 7
 
2.6%
I 4
 
1.5%
M 4
 
1.5%
Other values (18) 31
 
11.6%
Common
ValueCountFrequency (%)
7404
33.0%
1 2796
 
12.5%
, 2207
 
9.8%
( 1482
 
6.6%
) 1481
 
6.6%
0 1431
 
6.4%
2 1193
 
5.3%
3 926
 
4.1%
5 699
 
3.1%
4 669
 
3.0%
Other values (8) 2151
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31599
58.2%
ASCII 22706
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7404
32.6%
1 2796
 
12.3%
, 2207
 
9.7%
( 1482
 
6.5%
) 1481
 
6.5%
0 1431
 
6.3%
2 1193
 
5.3%
3 926
 
4.1%
5 699
 
3.1%
4 669
 
2.9%
Other values (36) 2418
 
10.6%
Hangul
ValueCountFrequency (%)
동 2006
 
6.3%
서 1663
 
5.3%
시 1648
 
5.2%
로 1601
 
5.1%
인 1557
 
4.9%
광 1552
 
4.9%
천 1545
 
4.9%
역 1541
 
4.9%
구 1536
 
4.9%
호 1246
 
3.9%
Other values (324) 15704
49.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
2022-09-07
1538 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-07
2nd row2022-09-07
3rd row2022-09-07
4th row2022-09-07
5th row2022-09-07

Common Values

ValueCountFrequency (%)
2022-09-07 1538
100.0%

Length

2023-12-12T16:22:00.959804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:22:01.054333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-07 1538
100.0%

Interactions

2023-12-12T16:21:57.772318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T16:21:57.913301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:21:58.012804image/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

연번등록번호사무소명사무소주소데이터기준일자
013380-2349LG부동산공인중개사사무소인천광역시 서구 가정로394번길 14(가정동)2022-09-07
123380-2340조은 공인중개사사무소인천광역시 서구 고래울로 6-1(가좌동)2022-09-07
233380-2329뉴신명럭키공인중개사사무소인천광역시 서구 승학로 447, 상가101호(검암동, 신명아파트)2022-09-07
343380-2326라인부동산공인중개사사무소인천광역시 서구 새오개로78번길 6(신현동)2022-09-07
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1532153328260-2022-00319뱅크부동산공인중개사사무소인천광역시 서구 서곶로 816, 상가동 103호 (당하동, 당하탑스빌)2022-09-07
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1536153728260-2022-00323루원SK몽땅부동산공인중개사사무소인천광역시 서구 가정로 437, 304동 B263호(가정동, 루원시티SK리더스뷰)2022-09-07
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