Overview

Dataset statistics

Number of variables7
Number of observations965
Missing cells230
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory53.8 KiB
Average record size in memory57.1 B

Variable types

Numeric1
Text5
Categorical1

Dataset

Description대구광역시 수성구 부동산중개사무소 현황_20180801
Author대구광역시 수성구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15054722&dataSetDetailId=150547221c8a29a701156&provdMethod=FILE

Alerts

행정처분상태 has constant value ""Constant
전화 has 225 (23.3%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-20 21:00:05.169101
Analysis finished2024-04-20 21:00:06.877034
Duration1.71 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct965
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean483
Minimum1
Maximum965
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2024-04-21T06:00:07.118032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile49.2
Q1242
median483
Q3724
95-th percentile916.8
Maximum965
Range964
Interquartile range (IQR)482

Descriptive statistics

Standard deviation278.71581
Coefficient of variation (CV)0.57705136
Kurtosis-1.2
Mean483
Median Absolute Deviation (MAD)241
Skewness0
Sum466095
Variance77682.5
MonotonicityStrictly increasing
2024-04-21T06:00:07.561102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
605 1
 
0.1%
637 1
 
0.1%
638 1
 
0.1%
639 1
 
0.1%
640 1
 
0.1%
641 1
 
0.1%
642 1
 
0.1%
643 1
 
0.1%
644 1
 
0.1%
Other values (955) 955
99.0%
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 (%)
965 1
0.1%
964 1
0.1%
963 1
0.1%
962 1
0.1%
961 1
0.1%
960 1
0.1%
959 1
0.1%
958 1
0.1%
957 1
0.1%
956 1
0.1%

등록번호
Text

Distinct964
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-04-21T06:00:08.401700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length12.691192
Min length8

Characters and Unicode

Total characters12247
Distinct characters12
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

Unique963 ?
Unique (%)99.8%

Sample

1st row가-16-0513
2nd row가-16-0597
3rd row가-16-0682
4th row가-16-0786
5th row가-16-0797
ValueCountFrequency (%)
가-16-2616 2
 
0.2%
27260-2017-00199 1
 
0.1%
27260-2016-00127 1
 
0.1%
27260-2016-00098 1
 
0.1%
27260-2016-00099 1
 
0.1%
27260-2016-00101 1
 
0.1%
27260-2016-00106 1
 
0.1%
27260-2016-00108 1
 
0.1%
27260-2016-00110 1
 
0.1%
27260-2016-00114 1
 
0.1%
Other values (954) 954
98.9%
2024-04-21T06:00:09.657162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2528
20.6%
- 1930
15.8%
2 1892
15.4%
1 1470
12.0%
6 1331
10.9%
7 947
 
7.7%
가 456
 
3.7%
4 404
 
3.3%
8 358
 
2.9%
3 353
 
2.9%
Other values (2) 578
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9861
80.5%
Dash Punctuation 1930
 
15.8%
Other Letter 456
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2528
25.6%
2 1892
19.2%
1 1470
14.9%
6 1331
13.5%
7 947
 
9.6%
4 404
 
4.1%
8 358
 
3.6%
3 353
 
3.6%
5 345
 
3.5%
9 233
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1930
100.0%
Other Letter
ValueCountFrequency (%)
가 456
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11791
96.3%
Hangul 456
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2528
21.4%
- 1930
16.4%
2 1892
16.0%
1 1470
12.5%
6 1331
11.3%
7 947
 
8.0%
4 404
 
3.4%
8 358
 
3.0%
3 353
 
3.0%
5 345
 
2.9%
Hangul
ValueCountFrequency (%)
가 456
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11791
96.3%
Hangul 456
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2528
21.4%
- 1930
16.4%
2 1892
16.0%
1 1470
12.5%
6 1331
11.3%
7 947
 
8.0%
4 404
 
3.4%
8 358
 
3.0%
3 353
 
3.0%
5 345
 
2.9%
Hangul
ValueCountFrequency (%)
가 456
100.0%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
영업중
965 

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 965
100.0%

Length

2024-04-21T06:00:09.920008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:00:10.107474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 965
100.0%

상호명
Text

Distinct960
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-04-21T06:00:10.737398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length11.119171
Min length6

Characters and Unicode

Total characters10730
Distinct characters398
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

Unique956 ?
Unique (%)99.1%

Sample

1st row상영공인중개사사무소
2nd row달구벌공인중개사사무소
3rd row장원공인중개사사무소
4th row앞집공인중개사사무소
5th row동양공인중개사사무소
ValueCountFrequency (%)
강남공인중개사사무소 3
 
0.3%
주식회사 3
 
0.3%
청락부동산중개 2
 
0.2%
궁전공인중개사사무소 2
 
0.2%
상가마당공인중개사사무소 2
 
0.2%
수성못광장부동산중개 1
 
0.1%
유명공인중개사사무소 1
 
0.1%
고모로공인중개사사무소 1
 
0.1%
예원부동산중개 1
 
0.1%
범어제니스부동산중개 1
 
0.1%
Other values (952) 952
98.2%
2024-04-21T06:00:11.666641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 1762
16.4%
중 969
 
9.0%
개 967
 
9.0%
소 894
 
8.3%
무 890
 
8.3%
인 874
 
8.1%
공 865
 
8.1%
동 194
 
1.8%
산 185
 
1.7%
부 166
 
1.5%
Other values (388) 2964
27.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10555
98.4%
Uppercase Letter 82
 
0.8%
Decimal Number 39
 
0.4%
Lowercase Letter 36
 
0.3%
Dash Punctuation 7
 
0.1%
Space Separator 4
 
< 0.1%
Other Punctuation 3
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1762
16.7%
중 969
 
9.2%
개 967
 
9.2%
소 894
 
8.5%
무 890
 
8.4%
인 874
 
8.3%
공 865
 
8.2%
동 194
 
1.8%
산 185
 
1.8%
부 166
 
1.6%
Other values (344) 2789
26.4%
Uppercase Letter
ValueCountFrequency (%)
S 15
18.3%
K 15
18.3%
A 7
8.5%
L 6
 
7.3%
B 5
 
6.1%
J 5
 
6.1%
O 5
 
6.1%
D 4
 
4.9%
T 4
 
4.9%
C 4
 
4.9%
Other values (10) 12
14.6%
Lowercase Letter
ValueCountFrequency (%)
e 24
66.7%
u 2
 
5.6%
a 2
 
5.6%
c 1
 
2.8%
l 1
 
2.8%
r 1
 
2.8%
t 1
 
2.8%
v 1
 
2.8%
i 1
 
2.8%
w 1
 
2.8%
Decimal Number
ValueCountFrequency (%)
1 22
56.4%
4 8
 
20.5%
2 3
 
7.7%
7 2
 
5.1%
5 2
 
5.1%
6 1
 
2.6%
3 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10555
98.4%
Latin 118
 
1.1%
Common 57
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1762
16.7%
중 969
 
9.2%
개 967
 
9.2%
소 894
 
8.5%
무 890
 
8.4%
인 874
 
8.3%
공 865
 
8.2%
동 194
 
1.8%
산 185
 
1.8%
부 166
 
1.6%
Other values (344) 2789
26.4%
Latin
ValueCountFrequency (%)
e 24
20.3%
S 15
12.7%
K 15
12.7%
A 7
 
5.9%
L 6
 
5.1%
B 5
 
4.2%
J 5
 
4.2%
O 5
 
4.2%
D 4
 
3.4%
T 4
 
3.4%
Other values (21) 28
23.7%
Common
ValueCountFrequency (%)
1 22
38.6%
4 8
 
14.0%
- 7
 
12.3%
4
 
7.0%
2 3
 
5.3%
) 2
 
3.5%
( 2
 
3.5%
& 2
 
3.5%
7 2
 
3.5%
5 2
 
3.5%
Other values (3) 3
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10555
98.4%
ASCII 175
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 1762
16.7%
중 969
 
9.2%
개 967
 
9.2%
소 894
 
8.5%
무 890
 
8.4%
인 874
 
8.3%
공 865
 
8.2%
동 194
 
1.8%
산 185
 
1.8%
부 166
 
1.6%
Other values (344) 2789
26.4%
ASCII
ValueCountFrequency (%)
e 24
 
13.7%
1 22
 
12.6%
S 15
 
8.6%
K 15
 
8.6%
4 8
 
4.6%
- 7
 
4.0%
A 7
 
4.0%
L 6
 
3.4%
B 5
 
2.9%
J 5
 
2.9%
Other values (34) 61
34.9%

대 표 자
Text

Distinct910
Distinct (%)94.8%
Missing5
Missing (%)0.5%
Memory size7.7 KiB
2024-04-21T06:00:12.795038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9958333
Min length2

Characters and Unicode

Total characters2876
Distinct characters199
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique867 ?
Unique (%)90.3%

Sample

1st row장찬희
2nd row임재환
3rd row장원태
4th row최근영
5th row김창수
ValueCountFrequency (%)
김정희 4
 
0.4%
서현주 3
 
0.3%
김미정 3
 
0.3%
김명희 3
 
0.3%
김명자 3
 
0.3%
박정민 3
 
0.3%
권영철 2
 
0.2%
문진숙 2
 
0.2%
이영주 2
 
0.2%
김시은 2
 
0.2%
Other values (900) 933
97.2%
2024-04-21T06:00:14.273717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 218
 
7.6%
이 158
 
5.5%
정 137
 
4.8%
영 108
 
3.8%
희 95
 
3.3%
박 87
 
3.0%
경 67
 
2.3%
숙 65
 
2.3%
미 57
 
2.0%
윤 49
 
1.7%
Other values (189) 1835
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2876
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 218
 
7.6%
이 158
 
5.5%
정 137
 
4.8%
영 108
 
3.8%
희 95
 
3.3%
박 87
 
3.0%
경 67
 
2.3%
숙 65
 
2.3%
미 57
 
2.0%
윤 49
 
1.7%
Other values (189) 1835
63.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2876
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 218
 
7.6%
이 158
 
5.5%
정 137
 
4.8%
영 108
 
3.8%
희 95
 
3.3%
박 87
 
3.0%
경 67
 
2.3%
숙 65
 
2.3%
미 57
 
2.0%
윤 49
 
1.7%
Other values (189) 1835
63.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2876
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 218
 
7.6%
이 158
 
5.5%
정 137
 
4.8%
영 108
 
3.8%
희 95
 
3.3%
박 87
 
3.0%
경 67
 
2.3%
숙 65
 
2.3%
미 57
 
2.0%
윤 49
 
1.7%
Other values (189) 1835
63.8%

소재지
Text

Distinct927
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-04-21T06:00:15.410462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length46
Mean length32.094301
Min length15

Characters and Unicode

Total characters30971
Distinct characters255
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique895 ?
Unique (%)92.7%

Sample

1st row대구광역시 수성구 무학로37길 42(지산동)
2nd row대구광역시 수성구 달구벌대로 3188(신매동,아레나스포츠타운)
3rd row대구광역시 수성구 지범로 256, 1층(범물동)
4th row대구광역시 수성구 수성로 294(수성동2가)
5th row대구광역시 수성구 수성로 56(상동)
ValueCountFrequency (%)
대구광역시 963
 
18.7%
수성구 962
 
18.7%
동대구로 104
 
2.0%
범어동 84
 
1.6%
달구벌대로 71
 
1.4%
상가 45
 
0.9%
청수로 41
 
0.8%
수성로 36
 
0.7%
301동 32
 
0.6%
1층 31
 
0.6%
Other values (1325) 2768
53.9%
2024-04-21T06:00:17.228917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4212
 
13.6%
구 2235
 
7.2%
1 1438
 
4.6%
동 1433
 
4.6%
대 1283
 
4.1%
수 1255
 
4.1%
성 1254
 
4.0%
시 1090
 
3.5%
로 976
 
3.2%
역 969
 
3.1%
Other values (245) 14826
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18474
59.6%
Decimal Number 5350
 
17.3%
Space Separator 4212
 
13.6%
Other Punctuation 927
 
3.0%
Open Punctuation 906
 
2.9%
Close Punctuation 906
 
2.9%
Dash Punctuation 95
 
0.3%
Uppercase Letter 89
 
0.3%
Lowercase Letter 10
 
< 0.1%
Control 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2235
 
12.1%
동 1433
 
7.8%
대 1283
 
6.9%
수 1255
 
6.8%
성 1254
 
6.8%
시 1090
 
5.9%
로 976
 
5.3%
역 969
 
5.2%
광 965
 
5.2%
호 528
 
2.9%
Other values (215) 6486
35.1%
Decimal Number
ValueCountFrequency (%)
1 1438
26.9%
0 746
13.9%
2 678
12.7%
3 580
10.8%
4 460
 
8.6%
5 410
 
7.7%
6 355
 
6.6%
7 302
 
5.6%
8 216
 
4.0%
9 165
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 21
23.6%
S 18
20.2%
K 11
12.4%
A 11
12.4%
T 6
 
6.7%
X 6
 
6.7%
N 5
 
5.6%
C 5
 
5.6%
F 4
 
4.5%
D 2
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
e 8
80.0%
s 1
 
10.0%
k 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 925
99.8%
/ 2
 
0.2%
Space Separator
ValueCountFrequency (%)
4212
100.0%
Open Punctuation
ValueCountFrequency (%)
( 906
100.0%
Close Punctuation
ValueCountFrequency (%)
) 906
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 95
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18474
59.6%
Common 12398
40.0%
Latin 99
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2235
 
12.1%
동 1433
 
7.8%
대 1283
 
6.9%
수 1255
 
6.8%
성 1254
 
6.8%
시 1090
 
5.9%
로 976
 
5.3%
역 969
 
5.2%
광 965
 
5.2%
호 528
 
2.9%
Other values (215) 6486
35.1%
Common
ValueCountFrequency (%)
4212
34.0%
1 1438
 
11.6%
, 925
 
7.5%
( 906
 
7.3%
) 906
 
7.3%
0 746
 
6.0%
2 678
 
5.5%
3 580
 
4.7%
4 460
 
3.7%
5 410
 
3.3%
Other values (7) 1137
 
9.2%
Latin
ValueCountFrequency (%)
B 21
21.2%
S 18
18.2%
K 11
11.1%
A 11
11.1%
e 8
 
8.1%
T 6
 
6.1%
X 6
 
6.1%
N 5
 
5.1%
C 5
 
5.1%
F 4
 
4.0%
Other values (3) 4
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18474
59.6%
ASCII 12497
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4212
33.7%
1 1438
 
11.5%
, 925
 
7.4%
( 906
 
7.2%
) 906
 
7.2%
0 746
 
6.0%
2 678
 
5.4%
3 580
 
4.6%
4 460
 
3.7%
5 410
 
3.3%
Other values (20) 1236
 
9.9%
Hangul
ValueCountFrequency (%)
구 2235
 
12.1%
동 1433
 
7.8%
대 1283
 
6.9%
수 1255
 
6.8%
성 1254
 
6.8%
시 1090
 
5.9%
로 976
 
5.3%
역 969
 
5.2%
광 965
 
5.2%
호 528
 
2.9%
Other values (215) 6486
35.1%

전화
Text

MISSING 

Distinct730
Distinct (%)98.6%
Missing225
Missing (%)23.3%
Memory size7.7 KiB
2024-04-21T06:00:18.167917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters8880
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

Unique720 ?
Unique (%)97.3%

Sample

1st row053-763-4507
2nd row053-792-5500
3rd row053-783-4848
4th row053-762-5244
5th row053-762-0722
ValueCountFrequency (%)
053-742-0200 2
 
0.3%
053-745-0660 2
 
0.3%
053-743-5600 2
 
0.3%
053-744-8899 2
 
0.3%
053-761-0088 2
 
0.3%
053-764-7789 2
 
0.3%
053-755-0077 2
 
0.3%
053-792-0076 2
 
0.3%
053-741-8272 2
 
0.3%
053-793-4500 2
 
0.3%
Other values (720) 720
97.3%
2024-04-21T06:00:19.467104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1490
16.8%
- 1480
16.7%
5 1227
13.8%
3 1090
12.3%
7 947
10.7%
4 568
 
6.4%
9 491
 
5.5%
8 432
 
4.9%
1 406
 
4.6%
6 398
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7400
83.3%
Dash Punctuation 1480
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1490
20.1%
5 1227
16.6%
3 1090
14.7%
7 947
12.8%
4 568
 
7.7%
9 491
 
6.6%
8 432
 
5.8%
1 406
 
5.5%
6 398
 
5.4%
2 351
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 1480
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8880
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1490
16.8%
- 1480
16.7%
5 1227
13.8%
3 1090
12.3%
7 947
10.7%
4 568
 
6.4%
9 491
 
5.5%
8 432
 
4.9%
1 406
 
4.6%
6 398
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1490
16.8%
- 1480
16.7%
5 1227
13.8%
3 1090
12.3%
7 947
10.7%
4 568
 
6.4%
9 491
 
5.5%
8 432
 
4.9%
1 406
 
4.6%
6 398
 
4.5%

Interactions

2024-04-21T06:00:05.976193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-21T06:00:06.303382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T06:00:06.516237image/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.
2024-04-21T06:00:06.722527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번등록번호행정처분상태상호명대 표 자소재지전화
01가-16-0513영업중상영공인중개사사무소장찬희대구광역시 수성구 무학로37길 42(지산동)053-763-4507
12가-16-0597영업중달구벌공인중개사사무소임재환대구광역시 수성구 달구벌대로 3188(신매동,아레나스포츠타운)053-792-5500
23가-16-0682영업중장원공인중개사사무소장원태대구광역시 수성구 지범로 256, 1층(범물동)053-783-4848
34가-16-0786영업중앞집공인중개사사무소최근영대구광역시 수성구 수성로 294(수성동2가)053-762-5244
45가-16-0797영업중동양공인중개사사무소김창수대구광역시 수성구 수성로 56(상동)053-762-0722
56가-16-0837영업중권오인공인중개사사무소권오인대구광역시 수성구 동대구로 386, 킹덤오피스텔 1115호<NA>
67가-16-949영업중대진공인중개사사무소김하정대구광역시 수성구 들안로 253(수성동2가)053-761-1313
78가-16-0967영업중영광공인중개사사무소정보영대구광역시 수성구 달구벌대로625길 21, 상가 109호(시지동,시지대백맨션)053-791-5757
89가-16-0971영업중금탑공인중개사정태룡대구광역시 수성구 노변공원로 17(시지동)053-792-8008
910가-16-0990영업중극동공인중개사사무소신의식대구광역시 수성구 청수로 256(황금동)053-766-0049
연번등록번호행정처분상태상호명대 표 자소재지전화
95595627260-2018-00149영업중참우리공인중개사사무소문미란대구광역시 수성구 수성로 71, 상가2동 B101호<NA>
95695727260-2018-00155영업중희망드림부동산중개이미자대구광역시 수성구 수성로51길 15(중동)053-768-7766
95795827260-2018-00151영업중수성별공인중개사사무소구가율대구광역시 수성구 수성로15길 38(상동)<NA>
95895927260-2018-00154영업중진여사부동산중개진정숙대구광역시 수성구 수성로 412, 118동 104호 (수성동4가, 수성보성타운 상가)<NA>
95996027260-2018-00152영업중팰리스공인중개사사무소김나영대구광역시 수성구 동대구로 274, 7동 104호 (범어동, 궁전맨션 상가)<NA>
96096127260-2018-00158영업중조은수성연합공인중개사사무소하동흥대구광역시 수성구 시지로 14053-793-7600
96196227260-2018-00157영업중정다운공인중개사사무소강보윤대구광역시 수성구 달구벌대로454길 6(수성동1가)053-741-0191
96296327260-2018-00161영업중안병철부동산중개(주)안병철대구광역시 수성구 들안로 324<NA>
96396427260-2018-00159영업중하늘채사랑방공인중개사사무소안성례대구광역시 수성구 파동로 242053-768-3232
96496527260-2018-00160영업중올모아공인중개사사무소이성희대구광역시 수성구 수성로 120(상동)<NA>