Overview

Dataset statistics

Number of variables11
Number of observations326
Missing cells84
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.5 KiB
Average record size in memory89.4 B

Variable types

Numeric1
Categorical6
Text4

Dataset

Description대구광역시 남구_부동산중개업소_20230713
Author대구광역시 남구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3075430&dataSetDetailId=3075430183c0f32fc824&provdMethod=FILE

Alerts

시군구 has constant value ""Constant
행정처분상태 has constant value ""Constant
직위 has constant value ""Constant
중개업자구분 is highly overall correlated with 중개업소종별High correlation
중개업소종별 is highly overall correlated with 중개업자구분High correlation
중개업소종별 is highly imbalanced (88.3%)Imbalance
중개업자구분 is highly imbalanced (88.3%)Imbalance
사무소전화번호 has 84 (25.8%) missing valuesMissing
연번 has unique valuesUnique
사무소명 has unique valuesUnique

Reproduction

Analysis started2024-04-17 14:46:00.987602
Analysis finished2024-04-17 14:46:01.867133
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct326
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean163.5
Minimum1
Maximum326
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-04-17T23:46:01.921075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.25
Q182.25
median163.5
Q3244.75
95-th percentile309.75
Maximum326
Range325
Interquartile range (IQR)162.5

Descriptive statistics

Standard deviation94.252321
Coefficient of variation (CV)0.57646679
Kurtosis-1.2
Mean163.5
Median Absolute Deviation (MAD)81.5
Skewness0
Sum53301
Variance8883.5
MonotonicityStrictly increasing
2024-04-17T23:46:02.027353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
206 1
 
0.3%
224 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
220 1
 
0.3%
219 1
 
0.3%
218 1
 
0.3%
217 1
 
0.3%
Other values (316) 316
96.9%
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 (%)
326 1
0.3%
325 1
0.3%
324 1
0.3%
323 1
0.3%
322 1
0.3%
321 1
0.3%
320 1
0.3%
319 1
0.3%
318 1
0.3%
317 1
0.3%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
대구광역시 남구
326 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시 남구
2nd row대구광역시 남구
3rd row대구광역시 남구
4th row대구광역시 남구
5th row대구광역시 남구

Common Values

ValueCountFrequency (%)
대구광역시 남구 326
100.0%

Length

2024-04-17T23:46:02.126961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:46:02.197718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 326
50.0%
남구 326
50.0%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
영업중
326 

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 326
100.0%

Length

2024-04-17T23:46:02.289861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:46:02.377266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 326
100.0%

사무소명
Text

UNIQUE 

Distinct326
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-04-17T23:46:02.512497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length10.996933
Min length7

Characters and Unicode

Total characters3585
Distinct characters256
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique326 ?
Unique (%)100.0%

Sample

1st row개나리 부동산중개 사무소
2nd row신평리부동산중개
3rd row태평양 부동산중개 사무소
4th row책임부동산중개
5th row동일부동산 중개사무소
ValueCountFrequency (%)
사무소 46
 
10.6%
공인중개사 33
 
7.6%
부동산중개 8
 
1.8%
부동산 8
 
1.8%
중개사무소 4
 
0.9%
중개 4
 
0.9%
개나리 1
 
0.2%
복길이공인중개사사무소 1
 
0.2%
시원공인중개사사무소 1
 
0.2%
기드온부동산중개 1
 
0.2%
Other values (328) 328
75.4%
2024-04-17T23:46:02.807032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 534
14.9%
중 329
 
9.2%
개 328
 
9.1%
소 283
 
7.9%
무 280
 
7.8%
인 256
 
7.1%
공 256
 
7.1%
산 114
 
3.2%
동 110
 
3.1%
109
 
3.0%
Other values (246) 986
27.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3425
95.5%
Space Separator 109
 
3.0%
Decimal Number 15
 
0.4%
Lowercase Letter 15
 
0.4%
Uppercase Letter 13
 
0.4%
Dash Punctuation 3
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 534
15.6%
중 329
 
9.6%
개 328
 
9.6%
소 283
 
8.3%
무 280
 
8.2%
인 256
 
7.5%
공 256
 
7.5%
산 114
 
3.3%
동 110
 
3.2%
부 104
 
3.0%
Other values (227) 831
24.3%
Uppercase Letter
ValueCountFrequency (%)
S 3
23.1%
B 2
15.4%
P 2
15.4%
O 2
15.4%
T 2
15.4%
U 1
 
7.7%
N 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
e 9
60.0%
h 2
 
13.3%
t 2
 
13.3%
n 1
 
6.7%
w 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 11
73.3%
4 4
 
26.7%
Space Separator
ValueCountFrequency (%)
109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3424
95.5%
Common 132
 
3.7%
Latin 28
 
0.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 534
15.6%
중 329
 
9.6%
개 328
 
9.6%
소 283
 
8.3%
무 280
 
8.2%
인 256
 
7.5%
공 256
 
7.5%
산 114
 
3.3%
동 110
 
3.2%
부 104
 
3.0%
Other values (226) 830
24.2%
Latin
ValueCountFrequency (%)
e 9
32.1%
S 3
 
10.7%
B 2
 
7.1%
P 2
 
7.1%
O 2
 
7.1%
T 2
 
7.1%
h 2
 
7.1%
t 2
 
7.1%
n 1
 
3.6%
w 1
 
3.6%
Other values (2) 2
 
7.1%
Common
ValueCountFrequency (%)
109
82.6%
1 11
 
8.3%
4 4
 
3.0%
- 3
 
2.3%
( 2
 
1.5%
) 2
 
1.5%
· 1
 
0.8%
Han
ValueCountFrequency (%)
樂 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3424
95.5%
ASCII 159
 
4.4%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 534
15.6%
중 329
 
9.6%
개 328
 
9.6%
소 283
 
8.3%
무 280
 
8.2%
인 256
 
7.5%
공 256
 
7.5%
산 114
 
3.3%
동 110
 
3.2%
부 104
 
3.0%
Other values (226) 830
24.2%
ASCII
ValueCountFrequency (%)
109
68.6%
1 11
 
6.9%
e 9
 
5.7%
4 4
 
2.5%
- 3
 
1.9%
S 3
 
1.9%
B 2
 
1.3%
P 2
 
1.3%
( 2
 
1.3%
O 2
 
1.3%
Other values (8) 12
 
7.5%
None
ValueCountFrequency (%)
· 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
樂 1
100.0%

중개업소종별
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
공인중개사
318 
중개인
 
6
법인
 
2

Length

Max length5
Median length5
Mean length4.9447853
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공인중개사 318
97.5%
중개인 6
 
1.8%
법인 2
 
0.6%

Length

2024-04-17T23:46:02.915771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:46:03.001399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공인중개사 318
97.5%
중개인 6
 
1.8%
법인 2
 
0.6%

중개업자명
Text

Distinct322
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-04-17T23:46:03.238895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0030675
Min length2

Characters and Unicode

Total characters979
Distinct characters157
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

Unique318 ?
Unique (%)97.5%

Sample

1st row심현석
2nd row이헌정
3rd row신문기
4th row전호일
5th row심원택
ValueCountFrequency (%)
김성태 2
 
0.6%
구본일 2
 
0.6%
김정순 2
 
0.6%
이재환 2
 
0.6%
하종수 1
 
0.3%
김현수 1
 
0.3%
이상규 1
 
0.3%
이창승 1
 
0.3%
류길하 1
 
0.3%
전효진 1
 
0.3%
Other values (312) 312
95.7%
2024-04-17T23:46:03.611144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 71
 
7.3%
이 55
 
5.6%
정 42
 
4.3%
박 32
 
3.3%
영 26
 
2.7%
희 24
 
2.5%
현 20
 
2.0%
진 19
 
1.9%
성 19
 
1.9%
수 18
 
1.8%
Other values (147) 653
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 979
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 71
 
7.3%
이 55
 
5.6%
정 42
 
4.3%
박 32
 
3.3%
영 26
 
2.7%
희 24
 
2.5%
현 20
 
2.0%
진 19
 
1.9%
성 19
 
1.9%
수 18
 
1.8%
Other values (147) 653
66.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 979
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 71
 
7.3%
이 55
 
5.6%
정 42
 
4.3%
박 32
 
3.3%
영 26
 
2.7%
희 24
 
2.5%
현 20
 
2.0%
진 19
 
1.9%
성 19
 
1.9%
수 18
 
1.8%
Other values (147) 653
66.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 979
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 71
 
7.3%
이 55
 
5.6%
정 42
 
4.3%
박 32
 
3.3%
영 26
 
2.7%
희 24
 
2.5%
현 20
 
2.0%
진 19
 
1.9%
성 19
 
1.9%
수 18
 
1.8%
Other values (147) 653
66.7%

직위
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
대표
326 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대표 326
100.0%

Length

2024-04-17T23:46:03.717819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:46:03.792212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대표 326
100.0%

중개업자구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
공인중개사
318 
중개인
 
6
법인
 
2

Length

Max length5
Median length5
Mean length4.9447853
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공인중개사 318
97.5%
중개인 6
 
1.8%
법인 2
 
0.6%

Length

2024-04-17T23:46:03.871089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:46:03.952988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공인중개사 318
97.5%
중개인 6
 
1.8%
법인 2
 
0.6%

사무소전화번호
Text

MISSING 

Distinct240
Distinct (%)99.2%
Missing84
Missing (%)25.8%
Memory size2.7 KiB
2024-04-17T23:46:04.129695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.004132
Min length12

Characters and Unicode

Total characters2905
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

Unique238 ?
Unique (%)98.3%

Sample

1st row053-625-6822
2nd row053-572-8401
3rd row053-626-4242
4th row053-471-7373
5th row053-476-2255
ValueCountFrequency (%)
053-471-4549 2
 
0.8%
053-621-4800 2
 
0.8%
053-657-8549 1
 
0.4%
053-625-6822 1
 
0.4%
053-241-7776 1
 
0.4%
053-477-4500 1
 
0.4%
053-472-2121 1
 
0.4%
053-657-2213 1
 
0.4%
053-474-9898 1
 
0.4%
053-621-7500 1
 
0.4%
Other values (230) 230
95.0%
2024-04-17T23:46:04.429967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 484
16.7%
0 458
15.8%
5 425
14.6%
3 331
11.4%
2 234
8.1%
7 213
7.3%
4 197
6.8%
6 190
 
6.5%
1 133
 
4.6%
9 121
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2421
83.3%
Dash Punctuation 484
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 458
18.9%
5 425
17.6%
3 331
13.7%
2 234
9.7%
7 213
8.8%
4 197
8.1%
6 190
7.8%
1 133
 
5.5%
9 121
 
5.0%
8 119
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 484
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2905
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 484
16.7%
0 458
15.8%
5 425
14.6%
3 331
11.4%
2 234
8.1%
7 213
7.3%
4 197
6.8%
6 190
 
6.5%
1 133
 
4.6%
9 121
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2905
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 484
16.7%
0 458
15.8%
5 425
14.6%
3 331
11.4%
2 234
8.1%
7 213
7.3%
4 197
6.8%
6 190
 
6.5%
1 133
 
4.6%
9 121
 
4.2%

사무소주소
Text

Distinct298
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-04-17T23:46:04.707842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length24.306748
Min length15

Characters and Unicode

Total characters7924
Distinct characters146
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

Unique277 ?
Unique (%)85.0%

Sample

1st row대구광역시 남구 대명로 117 개나리맨션 상가 13,14호(대명동)
2nd row대구광역시 남구 명덕로16길 55
3rd row대구광역시 남구 대명로 50 (우방코스모스 상가 22호)
4th row대구광역시 남구 중앙대로22길 164 (봉덕동)
5th row대구광역시 남구 봉덕로1길 140
ValueCountFrequency (%)
대구광역시 326
19.6%
남구 326
19.6%
대명동 84
 
5.0%
대명로 38
 
2.3%
봉덕동 37
 
2.2%
명덕로 25
 
1.5%
1층 22
 
1.3%
110-2 19
 
1.1%
봉덕로 16
 
1.0%
상가 14
 
0.8%
Other values (388) 760
45.6%
2024-04-17T23:46:05.100963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1440
18.2%
구 652
 
8.2%
대 574
 
7.2%
1 406
 
5.1%
남 337
 
4.3%
역 336
 
4.2%
시 332
 
4.2%
광 326
 
4.1%
로 263
 
3.3%
명 234
 
3.0%
Other values (136) 3024
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4593
58.0%
Space Separator 1440
 
18.2%
Decimal Number 1422
 
17.9%
Open Punctuation 180
 
2.3%
Close Punctuation 180
 
2.3%
Dash Punctuation 69
 
0.9%
Other Punctuation 35
 
0.4%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 652
14.2%
대 574
12.5%
남 337
 
7.3%
역 336
 
7.3%
시 332
 
7.2%
광 326
 
7.1%
로 263
 
5.7%
명 234
 
5.1%
동 229
 
5.0%
길 167
 
3.6%
Other values (119) 1143
24.9%
Decimal Number
ValueCountFrequency (%)
1 406
28.6%
2 205
14.4%
0 173
12.2%
4 127
 
8.9%
3 122
 
8.6%
6 97
 
6.8%
5 94
 
6.6%
7 76
 
5.3%
8 67
 
4.7%
9 55
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
B 4
80.0%
A 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1440
100.0%
Open Punctuation
ValueCountFrequency (%)
( 180
100.0%
Close Punctuation
ValueCountFrequency (%)
) 180
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Other Punctuation
ValueCountFrequency (%)
, 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4593
58.0%
Common 3326
42.0%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 652
14.2%
대 574
12.5%
남 337
 
7.3%
역 336
 
7.3%
시 332
 
7.2%
광 326
 
7.1%
로 263
 
5.7%
명 234
 
5.1%
동 229
 
5.0%
길 167
 
3.6%
Other values (119) 1143
24.9%
Common
ValueCountFrequency (%)
1440
43.3%
1 406
 
12.2%
2 205
 
6.2%
( 180
 
5.4%
) 180
 
5.4%
0 173
 
5.2%
4 127
 
3.8%
3 122
 
3.7%
6 97
 
2.9%
5 94
 
2.8%
Other values (5) 302
 
9.1%
Latin
ValueCountFrequency (%)
B 4
80.0%
A 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4593
58.0%
ASCII 3331
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1440
43.2%
1 406
 
12.2%
2 205
 
6.2%
( 180
 
5.4%
) 180
 
5.4%
0 173
 
5.2%
4 127
 
3.8%
3 122
 
3.7%
6 97
 
2.9%
5 94
 
2.8%
Other values (7) 307
 
9.2%
Hangul
ValueCountFrequency (%)
구 652
14.2%
대 574
12.5%
남 337
 
7.3%
역 336
 
7.3%
시 332
 
7.2%
광 326
 
7.1%
로 263
 
5.7%
명 234
 
5.1%
동 229
 
5.0%
길 167
 
3.6%
Other values (119) 1143
24.9%

행정동
Categorical

Distinct13
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
봉덕3동
40 
대명3동
39 
봉덕2동
33 
대명6동
30 
봉덕1동
27 
Other values (8)
157 

Length

Max length5
Median length4
Mean length4.0368098
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대명10동
2nd row대명3동
3rd row대명6동
4th row봉덕3동
5th row대명2동

Common Values

ValueCountFrequency (%)
봉덕3동 40
12.3%
대명3동 39
12.0%
봉덕2동 33
10.1%
대명6동 30
9.2%
봉덕1동 27
8.3%
대명2동 26
8.0%
대명9동 24
7.4%
이천동 23
7.1%
대명10동 18
 
5.5%
대명1동 18
 
5.5%
Other values (3) 48
14.7%

Length

2024-04-17T23:46:05.239058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
봉덕3동 40
12.3%
대명3동 39
12.0%
봉덕2동 33
10.1%
대명6동 30
9.2%
봉덕1동 27
8.3%
대명2동 26
8.0%
대명9동 24
7.4%
이천동 23
7.1%
대명10동 18
 
5.5%
대명1동 18
 
5.5%
Other values (3) 48
14.7%

Interactions

2024-04-17T23:46:01.600869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T23:46:05.311474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번중개업소종별중개업자구분행정동
연번1.0000.4360.4360.070
중개업소종별0.4361.0001.0000.000
중개업자구분0.4361.0001.0000.000
행정동0.0700.0000.0001.000
2024-04-17T23:46:05.386212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동중개업자구분중개업소종별
행정동1.0000.0000.000
중개업자구분0.0001.0001.000
중개업소종별0.0001.0001.000
2024-04-17T23:46:05.465308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번중개업소종별중개업자구분행정동
연번1.0000.2890.2890.015
중개업소종별0.2891.0001.0000.000
중개업자구분0.2891.0001.0000.000
행정동0.0150.0000.0001.000

Missing values

2024-04-17T23:46:01.706921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T23:46:01.822211image/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

연번시군구행정처분상태사무소명중개업소종별중개업자명직위중개업자구분사무소전화번호사무소주소행정동
01대구광역시 남구영업중개나리 부동산중개 사무소중개인심현석대표중개인053-625-6822대구광역시 남구 대명로 117 개나리맨션 상가 13,14호(대명동)대명10동
12대구광역시 남구영업중신평리부동산중개중개인이헌정대표중개인053-572-8401대구광역시 남구 명덕로16길 55대명3동
23대구광역시 남구영업중태평양 부동산중개 사무소중개인신문기대표중개인053-626-4242대구광역시 남구 대명로 50 (우방코스모스 상가 22호)대명6동
34대구광역시 남구영업중책임부동산중개중개인전호일대표중개인053-471-7373대구광역시 남구 중앙대로22길 164 (봉덕동)봉덕3동
45대구광역시 남구영업중동일부동산 중개사무소중개인심원택대표중개인053-476-2255대구광역시 남구 봉덕로1길 140대명2동
56대구광역시 남구영업중터 부동산 중개사무소중개인위무일대표중개인053-621-4800대구광역시 남구 큰골길 198대명9동
67대구광역시 남구영업중대화부동산중개공인중개사황선주대표공인중개사053-626-0567대구광역시 남구 명덕로26길 27대명2동
78대구광역시 남구영업중탑부동산중개사무소공인중개사임동균대표공인중개사053-474-2223대구광역시 남구 삼정길 42-1봉덕3동
89대구광역시 남구영업중수성공인중개사사무소공인중개사이성수대표공인중개사053-294-0885대구광역시 남구 봉덕로11길 27봉덕1동
910대구광역시 남구영업중중앙공인중개사사무소공인중개사박재석대표공인중개사053-472-7777대구광역시 남구 명덕로 238이천동
연번시군구행정처분상태사무소명중개업소종별중개업자명직위중개업자구분사무소전화번호사무소주소행정동
316317대구광역시 남구영업중청구공인중개사사무소공인중개사문덕채대표공인중개사053-626-3400대구광역시 남구 대명로 145 가동 1-2-가호대명10동
317318대구광역시 남구영업중신다온공인중개사사무소공인중개사채옥경대표공인중개사053-215-7279대구광역시 남구 대명로14길 114대명11동
318319대구광역시 남구영업중TOP부동산중개공인중개사신병철대표공인중개사053-471-0118대구광역시 남구 봉덕로11길 20 , 1층봉덕1동
319320대구광역시 남구영업중착한공인중개사사무소공인중개사차기욱대표공인중개사053-657-6003대구광역시 남구 대명로14길 12 ,1층(대명동)대명6동
320321대구광역시 남구영업중박미숙공인중개사사무소공인중개사박미숙대표공인중개사053-710-0001대구광역시 남구 명덕로 110-2 ,401호대명3동
321322대구광역시 남구영업중코오롱하늘채공인중개사사무소공인중개사이주향대표공인중개사<NA>대구광역시 남구 봉덕로 134 101동 101-1호봉덕1동
322323대구광역시 남구영업중대박공인중개사사무소공인중개사심혜원대표공인중개사053-267-0539대구광역시 남구 두류공원로20길 53대명4동
323324대구광역시 남구영업중파크공인중개사사무소공인중개사진옥희대표공인중개사053-622-8000대구광역시 남구 대명복개로 230 파크상가동 가호대명10동
324325대구광역시 남구영업중(주)온누리부동산중개법인법인김재봉대표법인<NA>대구광역시 남구 성당로 74-2 전진빌딩 4층(대명동)대명4동
325326대구광역시 남구영업중메디케이부동산중개법인정헌기대표법인<NA>대구광역시 남구 두류공원로12길 25-4 105호대명1동