Overview

Dataset statistics

Number of variables10
Number of observations502
Missing cells158
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.8 KiB
Average record size in memory83.3 B

Variable types

Numeric3
Text5
Categorical2

Dataset

Description대구광역시 달성군 내에 부동산과 관련된 중개업을 하는 업소 현황을 나타낸 데이터로 업소명, 소재지(도로명주소), 연락처, 위도, 경도 등을 데이터를 제공하고 있습니다.
Author대구광역시 달성군
URLhttps://www.data.go.kr/data/3075531/fileData.do

Alerts

업소상태 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
전화번호 has 158 (31.5%) missing valuesMissing
연번 has unique valuesUnique
등록번호 has unique valuesUnique

Reproduction

Analysis started2024-03-23 05:39:48.608821
Analysis finished2024-03-23 05:39:51.789982
Duration3.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct502
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean251.5
Minimum1
Maximum502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-23T14:39:51.940923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26.05
Q1126.25
median251.5
Q3376.75
95-th percentile476.95
Maximum502
Range501
Interquartile range (IQR)250.5

Descriptive statistics

Standard deviation145.05918
Coefficient of variation (CV)0.57677608
Kurtosis-1.2
Mean251.5
Median Absolute Deviation (MAD)125.5
Skewness0
Sum126253
Variance21042.167
MonotonicityStrictly increasing
2024-03-23T14:39:52.400513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
332 1
 
0.2%
345 1
 
0.2%
344 1
 
0.2%
343 1
 
0.2%
342 1
 
0.2%
341 1
 
0.2%
340 1
 
0.2%
339 1
 
0.2%
338 1
 
0.2%
Other values (492) 492
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
502 1
0.2%
501 1
0.2%
500 1
0.2%
499 1
0.2%
498 1
0.2%
497 1
0.2%
496 1
0.2%
495 1
0.2%
494 1
0.2%
493 1
0.2%

사무소명
Text

Distinct499
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-03-23T14:39:52.742226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length11.492032
Min length6

Characters and Unicode

Total characters5769
Distinct characters281
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique496 ?
Unique (%)98.8%

Sample

1st row현풍부동산중개인영업소
2nd row황금부동산중개사무소
3rd row다사부동산중개인영업소
4th row삼삼부동산중개소
5th row달창공인중개사사무소
ValueCountFrequency (%)
미래공인중개사사무소 2
 
0.4%
대경공인중개사사무소 2
 
0.4%
한솔공인중개사사무소 2
 
0.4%
봄공인중개사사무소 1
 
0.2%
윈윈부동산중개 1
 
0.2%
에이스1등예미지공인중개사사무소 1
 
0.2%
공인중개사사무소 1
 
0.2%
가는길 1
 
0.2%
부자로 1
 
0.2%
반도2차대구공인중개사사무소 1
 
0.2%
Other values (493) 493
97.4%
2024-03-23T14:39:53.770213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 960
16.6%
중 507
 
8.8%
개 505
 
8.8%
소 485
 
8.4%
무 481
 
8.3%
인 467
 
8.1%
공 466
 
8.1%
동 97
 
1.7%
부 88
 
1.5%
산 85
 
1.5%
Other values (271) 1628
28.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5701
98.8%
Uppercase Letter 32
 
0.6%
Decimal Number 19
 
0.3%
Lowercase Letter 9
 
0.2%
Space Separator 4
 
0.1%
Other Punctuation 2
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 960
16.8%
중 507
 
8.9%
개 505
 
8.9%
소 485
 
8.5%
무 481
 
8.4%
인 467
 
8.2%
공 466
 
8.2%
동 97
 
1.7%
부 88
 
1.5%
산 85
 
1.5%
Other values (243) 1560
27.4%
Uppercase Letter
ValueCountFrequency (%)
T 5
15.6%
H 5
15.6%
E 4
12.5%
O 4
12.5%
C 3
9.4%
K 3
9.4%
I 1
 
3.1%
S 1
 
3.1%
A 1
 
3.1%
B 1
 
3.1%
Other values (4) 4
12.5%
Decimal Number
ValueCountFrequency (%)
1 6
31.6%
5 3
15.8%
3 3
15.8%
2 3
15.8%
6 2
 
10.5%
9 1
 
5.3%
4 1
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 6
66.7%
h 1
 
11.1%
n 1
 
11.1%
w 1
 
11.1%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5699
98.8%
Latin 41
 
0.7%
Common 27
 
0.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 960
16.8%
중 507
 
8.9%
개 505
 
8.9%
소 485
 
8.5%
무 481
 
8.4%
인 467
 
8.2%
공 466
 
8.2%
동 97
 
1.7%
부 88
 
1.5%
산 85
 
1.5%
Other values (241) 1558
27.3%
Latin
ValueCountFrequency (%)
e 6
14.6%
T 5
12.2%
H 5
12.2%
E 4
9.8%
O 4
9.8%
C 3
 
7.3%
K 3
 
7.3%
h 1
 
2.4%
I 1
 
2.4%
n 1
 
2.4%
Other values (8) 8
19.5%
Common
ValueCountFrequency (%)
1 6
22.2%
4
14.8%
5 3
11.1%
3 3
11.1%
2 3
11.1%
. 2
 
7.4%
6 2
 
7.4%
- 2
 
7.4%
9 1
 
3.7%
4 1
 
3.7%
Han
ValueCountFrequency (%)
地 1
50.0%
天 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5699
98.8%
ASCII 68
 
1.2%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 960
16.8%
중 507
 
8.9%
개 505
 
8.9%
소 485
 
8.5%
무 481
 
8.4%
인 467
 
8.2%
공 466
 
8.2%
동 97
 
1.7%
부 88
 
1.5%
산 85
 
1.5%
Other values (241) 1558
27.3%
ASCII
ValueCountFrequency (%)
1 6
 
8.8%
e 6
 
8.8%
T 5
 
7.4%
H 5
 
7.4%
E 4
 
5.9%
O 4
 
5.9%
4
 
5.9%
5 3
 
4.4%
C 3
 
4.4%
3 3
 
4.4%
Other values (18) 25
36.8%
CJK
ValueCountFrequency (%)
地 1
50.0%
天 1
50.0%

등록번호
Text

UNIQUE 

Distinct502
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-03-23T14:39:54.157642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length13.63745
Min length7

Characters and Unicode

Total characters6846
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique502 ?
Unique (%)100.0%

Sample

1st row나-18-16
2nd row나-18-43
3rd row나-18-44
4th row나-18-80
5th row가-18-98
ValueCountFrequency (%)
나-18-16 1
 
0.2%
27710-2020-00023 1
 
0.2%
27710-2020-00055 1
 
0.2%
27710-2020-00054 1
 
0.2%
27710-2020-00053 1
 
0.2%
27710-2020-00051 1
 
0.2%
27710-2020-00048 1
 
0.2%
27710-2020-00045 1
 
0.2%
27710-2020-00035 1
 
0.2%
27710-2020-00034 1
 
0.2%
Other values (492) 492
98.0%
2024-03-23T14:39:54.946458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1832
26.8%
2 1039
15.2%
- 1004
14.7%
1 974
14.2%
7 821
12.0%
8 289
 
4.2%
3 198
 
2.9%
5 155
 
2.3%
가 154
 
2.2%
6 144
 
2.1%
Other values (3) 236
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5683
83.0%
Dash Punctuation 1004
 
14.7%
Other Letter 159
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1832
32.2%
2 1039
18.3%
1 974
17.1%
7 821
14.4%
8 289
 
5.1%
3 198
 
3.5%
5 155
 
2.7%
6 144
 
2.5%
4 121
 
2.1%
9 110
 
1.9%
Other Letter
ValueCountFrequency (%)
가 154
96.9%
나 5
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 1004
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6687
97.7%
Hangul 159
 
2.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1832
27.4%
2 1039
15.5%
- 1004
15.0%
1 974
14.6%
7 821
12.3%
8 289
 
4.3%
3 198
 
3.0%
5 155
 
2.3%
6 144
 
2.2%
4 121
 
1.8%
Hangul
ValueCountFrequency (%)
가 154
96.9%
나 5
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6687
97.7%
Hangul 159
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1832
27.4%
2 1039
15.5%
- 1004
15.0%
1 974
14.6%
7 821
12.3%
8 289
 
4.3%
3 198
 
3.0%
5 155
 
2.3%
6 144
 
2.2%
4 121
 
1.8%
Hangul
ValueCountFrequency (%)
가 154
96.9%
나 5
 
3.1%

업소상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
영업중
502 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 502
100.0%

Length

2024-03-23T14:39:55.170470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T14:39:55.326397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 502
100.0%

도로명 주소
Text

Distinct469
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-03-23T14:39:55.720074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length47
Mean length31.366534
Min length19

Characters and Unicode

Total characters15746
Distinct characters225
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

Unique438 ?
Unique (%)87.3%

Sample

1st row대구광역시 달성군 현풍읍 현풍중앙로 41
2nd row대구광역시 달성군 현풍읍 비슬로 561-1
3rd row대구광역시 달성군 다사읍 달구벌대로 846
4th row대구광역시 달성군 논공읍 금강로 20
5th row대구광역시 달성군 현풍읍 비슬로64길 57
ValueCountFrequency (%)
대구광역시 502
 
16.4%
달성군 502
 
16.4%
다사읍 151
 
4.9%
화원읍 74
 
2.4%
비슬로 62
 
2.0%
현풍읍 54
 
1.8%
유가읍 53
 
1.7%
구지면 50
 
1.6%
옥포읍 48
 
1.6%
논공읍 43
 
1.4%
Other values (642) 1526
49.8%
2024-03-23T14:39:56.441707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2571
 
16.3%
1 774
 
4.9%
대 640
 
4.1%
구 601
 
3.8%
역 570
 
3.6%
달 535
 
3.4%
성 525
 
3.3%
시 520
 
3.3%
광 506
 
3.2%
군 503
 
3.2%
Other values (215) 8001
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9712
61.7%
Decimal Number 2802
 
17.8%
Space Separator 2571
 
16.3%
Other Punctuation 286
 
1.8%
Open Punctuation 138
 
0.9%
Close Punctuation 138
 
0.9%
Dash Punctuation 72
 
0.5%
Uppercase Letter 20
 
0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 640
 
6.6%
구 601
 
6.2%
역 570
 
5.9%
달 535
 
5.5%
성 525
 
5.4%
시 520
 
5.4%
광 506
 
5.2%
군 503
 
5.2%
로 471
 
4.8%
읍 423
 
4.4%
Other values (190) 4418
45.5%
Decimal Number
ValueCountFrequency (%)
1 774
27.6%
0 427
15.2%
2 363
13.0%
3 266
 
9.5%
4 227
 
8.1%
5 221
 
7.9%
6 184
 
6.6%
7 151
 
5.4%
8 98
 
3.5%
9 91
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 11
55.0%
A 4
 
20.0%
S 2
 
10.0%
D 1
 
5.0%
L 1
 
5.0%
H 1
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
42.9%
l 2
28.6%
m 1
 
14.3%
a 1
 
14.3%
Space Separator
ValueCountFrequency (%)
2571
100.0%
Other Punctuation
ValueCountFrequency (%)
, 286
100.0%
Open Punctuation
ValueCountFrequency (%)
( 138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 138
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9712
61.7%
Common 6007
38.1%
Latin 27
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 640
 
6.6%
구 601
 
6.2%
역 570
 
5.9%
달 535
 
5.5%
성 525
 
5.4%
시 520
 
5.4%
광 506
 
5.2%
군 503
 
5.2%
로 471
 
4.8%
읍 423
 
4.4%
Other values (190) 4418
45.5%
Common
ValueCountFrequency (%)
2571
42.8%
1 774
 
12.9%
0 427
 
7.1%
2 363
 
6.0%
, 286
 
4.8%
3 266
 
4.4%
4 227
 
3.8%
5 221
 
3.7%
6 184
 
3.1%
7 151
 
2.5%
Other values (5) 537
 
8.9%
Latin
ValueCountFrequency (%)
B 11
40.7%
A 4
 
14.8%
e 3
 
11.1%
l 2
 
7.4%
S 2
 
7.4%
D 1
 
3.7%
m 1
 
3.7%
a 1
 
3.7%
L 1
 
3.7%
H 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9712
61.7%
ASCII 6034
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2571
42.6%
1 774
 
12.8%
0 427
 
7.1%
2 363
 
6.0%
, 286
 
4.7%
3 266
 
4.4%
4 227
 
3.8%
5 221
 
3.7%
6 184
 
3.0%
7 151
 
2.5%
Other values (15) 564
 
9.3%
Hangul
ValueCountFrequency (%)
대 640
 
6.6%
구 601
 
6.2%
역 570
 
5.9%
달 535
 
5.5%
성 525
 
5.4%
시 520
 
5.4%
광 506
 
5.2%
군 503
 
5.2%
로 471
 
4.8%
읍 423
 
4.4%
Other values (190) 4418
45.5%

전화번호
Text

MISSING 

Distinct337
Distinct (%)98.0%
Missing158
Missing (%)31.5%
Memory size4.1 KiB
2024-03-23T14:39:56.984789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length12
Mean length14.94186
Min length12

Characters and Unicode

Total characters5140
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

Unique330 ?
Unique (%)95.9%

Sample

1st row053-614-2116
2nd row053-611-0070
3rd row053-591-3900
4th row053-615-7005
5th row053-614-2566
ValueCountFrequency (%)
053-559-8899 2
 
0.6%
053-616-8989 2
 
0.6%
053-615-4848 2
 
0.6%
053-585-0026 2
 
0.6%
053-636-7500 2
 
0.6%
053-615-8500 2
 
0.6%
053-614-5400 2
 
0.6%
053-614-8880 1
 
0.3%
053-767-1616 1
 
0.3%
053-616-8009 1
 
0.3%
Other values (326) 326
95.0%
2024-03-23T14:39:57.652872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1024
19.9%
- 686
13.3%
0 671
13.1%
5 639
12.4%
3 500
9.7%
6 352
 
6.8%
1 349
 
6.8%
8 290
 
5.6%
9 170
 
3.3%
4 167
 
3.2%
Other values (2) 292
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3430
66.7%
Space Separator 1024
 
19.9%
Dash Punctuation 686
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 671
19.6%
5 639
18.6%
3 500
14.6%
6 352
10.3%
1 349
10.2%
8 290
8.5%
9 170
 
5.0%
4 167
 
4.9%
7 166
 
4.8%
2 126
 
3.7%
Space Separator
ValueCountFrequency (%)
1024
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 686
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5140
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1024
19.9%
- 686
13.3%
0 671
13.1%
5 639
12.4%
3 500
9.7%
6 352
 
6.8%
1 349
 
6.8%
8 290
 
5.6%
9 170
 
3.3%
4 167
 
3.2%
Other values (2) 292
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1024
19.9%
- 686
13.3%
0 671
13.1%
5 639
12.4%
3 500
9.7%
6 352
 
6.8%
1 349
 
6.8%
8 290
 
5.6%
9 170
 
3.3%
4 167
 
3.2%
Other values (2) 292
 
5.7%

대표자명
Text

Distinct57
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-03-23T14:39:57.984476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1506
Distinct characters58
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

Unique9 ?
Unique (%)1.8%

Sample

1st row기OO
2nd row윤OO
3rd row추OO
4th row김OO
5th row조OO
ValueCountFrequency (%)
김oo 106
21.1%
이oo 59
 
11.8%
박oo 51
 
10.2%
정oo 24
 
4.8%
최oo 18
 
3.6%
조oo 14
 
2.8%
권oo 13
 
2.6%
전oo 13
 
2.6%
신oo 13
 
2.6%
서oo 12
 
2.4%
Other values (47) 179
35.7%
2024-03-23T14:39:58.655401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 1004
66.7%
김 106
 
7.0%
이 59
 
3.9%
박 51
 
3.4%
정 24
 
1.6%
최 18
 
1.2%
조 14
 
0.9%
권 13
 
0.9%
전 13
 
0.9%
신 13
 
0.9%
Other values (48) 191
 
12.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1004
66.7%
Other Letter 502
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 106
21.1%
이 59
 
11.8%
박 51
 
10.2%
정 24
 
4.8%
최 18
 
3.6%
조 14
 
2.8%
권 13
 
2.6%
전 13
 
2.6%
신 13
 
2.6%
서 12
 
2.4%
Other values (47) 179
35.7%
Uppercase Letter
ValueCountFrequency (%)
O 1004
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1004
66.7%
Hangul 502
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 106
21.1%
이 59
 
11.8%
박 51
 
10.2%
정 24
 
4.8%
최 18
 
3.6%
조 14
 
2.8%
권 13
 
2.6%
전 13
 
2.6%
신 13
 
2.6%
서 12
 
2.4%
Other values (47) 179
35.7%
Latin
ValueCountFrequency (%)
O 1004
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1004
66.7%
Hangul 502
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 1004
100.0%
Hangul
ValueCountFrequency (%)
김 106
21.1%
이 59
 
11.8%
박 51
 
10.2%
정 24
 
4.8%
최 18
 
3.6%
조 14
 
2.8%
권 13
 
2.6%
전 13
 
2.6%
신 13
 
2.6%
서 12
 
2.4%
Other values (47) 179
35.7%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct354
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.778955
Minimum35.640567
Maximum35.901513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-23T14:39:58.912151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.640567
5-th percentile35.660751
Q135.694965
median35.790509
Q335.859578
95-th percentile35.875734
Maximum35.901513
Range0.26094547
Interquartile range (IQR)0.1646127

Descriptive statistics

Standard deviation0.076357837
Coefficient of variation (CV)0.0021341551
Kurtosis-1.3997763
Mean35.778955
Median Absolute Deviation (MAD)0.073394375
Skewness-0.19954297
Sum17961.035
Variance0.0058305193
MonotonicityNot monotonic
2024-03-23T14:39:59.225113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.87441892 6
 
1.2%
35.69045928 6
 
1.2%
35.87211968 5
 
1.0%
35.85944957 5
 
1.0%
35.87081141 5
 
1.0%
35.86809454 5
 
1.0%
35.69132888 5
 
1.0%
35.80391061 5
 
1.0%
35.85957779 5
 
1.0%
35.66248748 5
 
1.0%
Other values (344) 450
89.6%
ValueCountFrequency (%)
35.64056743 1
0.2%
35.65205611 1
0.2%
35.65377515 1
0.2%
35.6555873 1
0.2%
35.65561954 1
0.2%
35.6556789 2
0.4%
35.65574043 1
0.2%
35.65596254 1
0.2%
35.65596656 1
0.2%
35.65680296 1
0.2%
ValueCountFrequency (%)
35.9015129 1
0.2%
35.9012479 1
0.2%
35.90067836 1
0.2%
35.90007689 1
0.2%
35.87974774 1
0.2%
35.87945709 1
0.2%
35.87928744 1
0.2%
35.87832303 1
0.2%
35.87811089 1
0.2%
35.87801568 1
0.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct354
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.46459
Minimum128.39398
Maximum128.66371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-23T14:39:59.717501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.39398
5-th percentile128.41684
Q1128.44436
median128.46081
Q3128.48014
95-th percentile128.50687
Maximum128.66371
Range0.2697311
Interquartile range (IQR)0.03578605

Descriptive statistics

Standard deviation0.038982523
Coefficient of variation (CV)0.00030344956
Kurtosis9.0286296
Mean128.46459
Median Absolute Deviation (MAD)0.017398
Skewness2.3257012
Sum64489.224
Variance0.0015196371
MonotonicityNot monotonic
2024-03-23T14:40:00.126157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.4802486 6
 
1.2%
128.4608101 6
 
1.2%
128.4782081 5
 
1.0%
128.4591208 5
 
1.0%
128.4896949 5
 
1.0%
128.4906415 5
 
1.0%
128.4643729 5
 
1.0%
128.4950363 5
 
1.0%
128.4679129 5
 
1.0%
128.4093227 5
 
1.0%
Other values (344) 450
89.6%
ValueCountFrequency (%)
128.3939763 1
 
0.2%
128.3992059 1
 
0.2%
128.3993316 1
 
0.2%
128.4013598 1
 
0.2%
128.4015457 1
 
0.2%
128.4023393 1
 
0.2%
128.4085705 3
0.6%
128.4093227 5
1.0%
128.4100047 1
 
0.2%
128.4100865 1
 
0.2%
ValueCountFrequency (%)
128.6637074 1
0.2%
128.6480563 1
0.2%
128.6479107 2
0.4%
128.6442372 1
0.2%
128.6438533 1
0.2%
128.6436164 1
0.2%
128.6392509 1
0.2%
128.6382308 1
0.2%
128.6266747 2
0.4%
128.6237082 1
0.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-03-14
502 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-14
2nd row2024-03-14
3rd row2024-03-14
4th row2024-03-14
5th row2024-03-14

Common Values

ValueCountFrequency (%)
2024-03-14 502
100.0%

Length

2024-03-23T14:40:00.383230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T14:40:00.599030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-14 502
100.0%

Interactions

2024-03-23T14:39:50.783310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:39:49.550609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:39:50.192398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:39:50.942898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:39:49.796513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:39:50.422925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:39:51.109334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:39:49.997028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:39:50.621912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T14:40:00.750804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대표자명위도경도
연번1.0000.2110.0000.000
대표자명0.2111.0000.1820.000
위도0.0000.1821.0000.764
경도0.0000.0000.7641.000
2024-03-23T14:40:00.970281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.000-0.0420.001
위도-0.0421.0000.519
경도0.0010.5191.000

Missing values

2024-03-23T14:39:51.348923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T14:39:51.663018image/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

연번사무소명등록번호업소상태도로명 주소전화번호대표자명위도경도데이터기준일자
01현풍부동산중개인영업소나-18-16영업중대구광역시 달성군 현풍읍 현풍중앙로 41053-614-2116기OO35.693202128.4458982024-03-14
12황금부동산중개사무소나-18-43영업중대구광역시 달성군 현풍읍 비슬로 561-1053-611-0070윤OO35.689558128.446432024-03-14
23다사부동산중개인영업소나-18-44영업중대구광역시 달성군 다사읍 달구벌대로 846053-591-3900추OO35.859968128.4625232024-03-14
34삼삼부동산중개소나-18-80영업중대구광역시 달성군 논공읍 금강로 20053-615-7005김OO35.773849128.4275472024-03-14
45달창공인중개사사무소가-18-98영업중대구광역시 달성군 현풍읍 비슬로64길 57053-614-2566조OO35.673344128.4484722024-03-14
56장원부동산공인중개사사무소가-18-99영업중대구광역시 달성군 다사읍 달구벌대로 835053-585-1490류OO35.860915128.4623512024-03-14
67쌍공공인중개사사무소가-18-106영업중대구광역시 달성군 구지면 과학남로61길 179053-615-7711송OO35.652056128.4100872024-03-14
78태화공인중개사사무소가-18-131영업중대구광역시 달성군 유가읍 비슬로64길 36-4053-615-1455김OO35.67162128.4492242024-03-14
89대진공인중개사사무소가-18-251영업중대구광역시 달성군 논공읍 비슬로306길 1-6053-615-8881허OO35.759751128.3992062024-03-14
910해강공인중개사사무소가-18-279영업중대구광역시 달성군 현풍읍 비슬로 64길 73, 105호053-643-0777김OO35.674798128.4478722024-03-14
연번사무소명등록번호업소상태도로명 주소전화번호대표자명위도경도데이터기준일자
492493길공인중개사사무소27710-2023-00062영업중대구광역시 달성군 유가읍 현풍로 201-12053-614-8289김OO35.698901128.4617982024-03-14
493494라움부동산중개27710-2023-00063영업중대구광역시 달성군 다사읍 죽곡1길 13-3053-591-0078한OO35.85705128.4643882024-03-14
494495노블공인중개사사무소27710-2023-00064영업중대구광역시 달성군 유가읍 테크노북로 260, 201동 B117호(애비뉴스완)<NA>김OO35.690459128.460812024-03-14
495496가창전원공인중개사사무소27710-2024-00001영업중대구광역시 달성군 가창면 가창로 771-1053-767-1241박OO35.781411128.6436162024-03-14
496497강정보부동산중개27710-2024-00002영업중대구광역시 달성군 다사읍 달구벌대로 852<NA>김OO35.859579128.4629412024-03-14
497498The복드림공인중개사사무소27710-2024-00003영업중대구광역시 달성군 논공읍 남리길 7<NA>이OO35.726168128.4497972024-03-14
498499맹호공인중개사사무소27710-2024-00004영업중대구광역시 달성군 논공읍 금포새터길 22-26 101호<NA>이OO35.770062128.4280462024-03-14
499500황금공인중개사사무소27710-2024-00005영업중대구광역시 달성군 유가읍 테크노중앙대로1길 60-5<NA>장OO35.674738128.4542132024-03-14
500501대황금부동산공인중개사사무소27710-2024-00006영업중대구광역시 달성군 유가읍 테크노중앙대로1길 60-5<NA>박OO35.674738128.4542132024-03-14
501502우수공인중개사사무소27710-2024-00007영업중대구광역시 달성군 다사읍 달구벌대로 846<NA>권OO35.859968128.4625232024-03-14