Overview

Dataset statistics

Number of variables8
Number of observations1253
Missing cells227
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory79.7 KiB
Average record size in memory65.1 B

Variable types

Numeric1
Text5
Categorical2

Dataset

Description대구광역시 수성구 관내 영업 중인 부동산중개업소 현황에 관한 데이터로 사무소명,사무전화번호,사무소주소 등의 정보를 제공합니다.
Author대구광역시 수성구
URLhttps://www.data.go.kr/data/15054721/fileData.do

Alerts

행정처분상태 has constant value ""Constant
기타유의사항 is highly imbalanced (56.5%)Imbalance
전화번호 has 227 (18.1%) missing valuesMissing
연번 has unique valuesUnique
중개업등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:03:34.547845
Analysis finished2023-12-12 07:03:35.643686
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct1253
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean627
Minimum1
Maximum1253
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2023-12-12T16:03:35.738158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile63.6
Q1314
median627
Q3940
95-th percentile1190.4
Maximum1253
Range1252
Interquartile range (IQR)626

Descriptive statistics

Standard deviation361.85425
Coefficient of variation (CV)0.57712002
Kurtosis-1.2
Mean627
Median Absolute Deviation (MAD)313
Skewness0
Sum785631
Variance130938.5
MonotonicityStrictly increasing
2023-12-12T16:03:35.909893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
834 1
 
0.1%
841 1
 
0.1%
840 1
 
0.1%
839 1
 
0.1%
838 1
 
0.1%
837 1
 
0.1%
836 1
 
0.1%
835 1
 
0.1%
833 1
 
0.1%
Other values (1243) 1243
99.2%
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 (%)
1253 1
0.1%
1252 1
0.1%
1251 1
0.1%
1250 1
0.1%
1249 1
0.1%
1248 1
0.1%
1247 1
0.1%
1246 1
0.1%
1245 1
0.1%
1244 1
0.1%

중개업등록번호
Text

UNIQUE 

Distinct1253
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2023-12-12T16:03:36.173778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length13.893057
Min length8

Characters and Unicode

Total characters17408
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

Unique1253 ?
Unique (%)100.0%

Sample

1st row나-16-0048
2nd row나-16-0077
3rd row나-16-0241
4th row나-16-0243
5th row나-16-0244
ValueCountFrequency (%)
나-16-0048 1
 
0.1%
27260-2020-00041 1
 
0.1%
27260-2020-00052 1
 
0.1%
27260-2020-00040 1
 
0.1%
27260-2020-00051 1
 
0.1%
27260-2020-00048 1
 
0.1%
27260-2020-00047 1
 
0.1%
27260-2020-00045 1
 
0.1%
27260-2020-00063 1
 
0.1%
27260-2020-00038 1
 
0.1%
Other values (1243) 1243
99.2%
2023-12-12T16:03:36.578415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4377
25.1%
2 3673
21.1%
- 2506
14.4%
1 1668
 
9.6%
6 1616
 
9.3%
7 1278
 
7.3%
4 417
 
2.4%
8 380
 
2.2%
3 376
 
2.2%
가 371
 
2.1%
Other values (3) 746
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14525
83.4%
Dash Punctuation 2506
 
14.4%
Other Letter 377
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4377
30.1%
2 3673
25.3%
1 1668
 
11.5%
6 1616
 
11.1%
7 1278
 
8.8%
4 417
 
2.9%
8 380
 
2.6%
3 376
 
2.6%
9 371
 
2.6%
5 369
 
2.5%
Other Letter
ValueCountFrequency (%)
가 371
98.4%
나 6
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 2506
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17031
97.8%
Hangul 377
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4377
25.7%
2 3673
21.6%
- 2506
14.7%
1 1668
 
9.8%
6 1616
 
9.5%
7 1278
 
7.5%
4 417
 
2.4%
8 380
 
2.2%
3 376
 
2.2%
9 371
 
2.2%
Hangul
ValueCountFrequency (%)
가 371
98.4%
나 6
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17031
97.8%
Hangul 377
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4377
25.7%
2 3673
21.6%
- 2506
14.7%
1 1668
 
9.8%
6 1616
 
9.5%
7 1278
 
7.5%
4 417
 
2.4%
8 380
 
2.2%
3 376
 
2.2%
9 371
 
2.2%
Hangul
ValueCountFrequency (%)
가 371
98.4%
나 6
 
1.6%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
영업중
1253 

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 1253
100.0%

Length

2023-12-12T16:03:36.767750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:36.864225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 1253
100.0%

상호명
Text

Distinct1252
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2023-12-12T16:03:37.052386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length11.453312
Min length6

Characters and Unicode

Total characters14351
Distinct characters446
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1251 ?
Unique (%)99.8%

Sample

1st row합동부동산중개인사무소
2nd row만촌현대부동산중개
3rd row한양부동산중개인사무소
4th row신진부동산중개사무소
5th row신신부동산중개인사무소
ValueCountFrequency (%)
주식회사 10
 
0.8%
가람공인중개사사무소 2
 
0.2%
궁전공인중개사사무소 2
 
0.2%
명품부동산중개사무소 1
 
0.1%
해링턴1번지공인중개사사무소 1
 
0.1%
수성해링턴코끼리공인중개사사무소 1
 
0.1%
알파시티더원공인중개사사무소 1
 
0.1%
캐슬동해공인중개사사무소 1
 
0.1%
동아드림공인중개사사무소 1
 
0.1%
범어에일린공인중개사사무소 1
 
0.1%
Other values (1244) 1244
98.3%
2023-12-12T16:03:37.448961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 2260
15.7%
중 1257
 
8.8%
개 1255
 
8.7%
소 1157
 
8.1%
무 1147
 
8.0%
인 1124
 
7.8%
공 1091
 
7.6%
동 297
 
2.1%
산 273
 
1.9%
부 261
 
1.8%
Other values (436) 4229
29.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14059
98.0%
Uppercase Letter 148
 
1.0%
Lowercase Letter 53
 
0.4%
Decimal Number 49
 
0.3%
Dash Punctuation 12
 
0.1%
Space Separator 12
 
0.1%
Close Punctuation 6
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 2260
16.1%
중 1257
 
8.9%
개 1255
 
8.9%
소 1157
 
8.2%
무 1147
 
8.2%
인 1124
 
8.0%
공 1091
 
7.8%
동 297
 
2.1%
산 273
 
1.9%
부 261
 
1.9%
Other values (384) 3937
28.0%
Uppercase Letter
ValueCountFrequency (%)
K 23
15.5%
S 20
13.5%
B 10
 
6.8%
W 10
 
6.8%
O 10
 
6.8%
T 8
 
5.4%
D 7
 
4.7%
J 7
 
4.7%
A 7
 
4.7%
L 6
 
4.1%
Other values (13) 40
27.0%
Lowercase Letter
ValueCountFrequency (%)
e 32
60.4%
h 4
 
7.5%
a 3
 
5.7%
t 2
 
3.8%
u 2
 
3.8%
i 2
 
3.8%
d 1
 
1.9%
y 1
 
1.9%
p 1
 
1.9%
w 1
 
1.9%
Other values (4) 4
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 22
44.9%
4 8
 
16.3%
3 4
 
8.2%
2 4
 
8.2%
5 4
 
8.2%
6 3
 
6.1%
7 2
 
4.1%
0 1
 
2.0%
9 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
& 4
66.7%
. 2
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14058
98.0%
Latin 201
 
1.4%
Common 91
 
0.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 2260
16.1%
중 1257
 
8.9%
개 1255
 
8.9%
소 1157
 
8.2%
무 1147
 
8.2%
인 1124
 
8.0%
공 1091
 
7.8%
동 297
 
2.1%
산 273
 
1.9%
부 261
 
1.9%
Other values (383) 3936
28.0%
Latin
ValueCountFrequency (%)
e 32
15.9%
K 23
 
11.4%
S 20
 
10.0%
B 10
 
5.0%
W 10
 
5.0%
O 10
 
5.0%
T 8
 
4.0%
D 7
 
3.5%
J 7
 
3.5%
A 7
 
3.5%
Other values (27) 67
33.3%
Common
ValueCountFrequency (%)
1 22
24.2%
- 12
13.2%
12
13.2%
4 8
 
8.8%
) 6
 
6.6%
( 6
 
6.6%
3 4
 
4.4%
2 4
 
4.4%
& 4
 
4.4%
5 4
 
4.4%
Other values (5) 9
9.9%
Han
ValueCountFrequency (%)
秀 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14058
98.0%
ASCII 292
 
2.0%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 2260
16.1%
중 1257
 
8.9%
개 1255
 
8.9%
소 1157
 
8.2%
무 1147
 
8.2%
인 1124
 
8.0%
공 1091
 
7.8%
동 297
 
2.1%
산 273
 
1.9%
부 261
 
1.9%
Other values (383) 3936
28.0%
ASCII
ValueCountFrequency (%)
e 32
 
11.0%
K 23
 
7.9%
1 22
 
7.5%
S 20
 
6.8%
- 12
 
4.1%
12
 
4.1%
B 10
 
3.4%
W 10
 
3.4%
O 10
 
3.4%
T 8
 
2.7%
Other values (42) 133
45.5%
CJK
ValueCountFrequency (%)
秀 1
100.0%

대 표 자
Text

Distinct1181
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2023-12-12T16:03:37.826519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9952115
Min length2

Characters and Unicode

Total characters3753
Distinct characters207
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

Unique1123 ?
Unique (%)89.6%

Sample

1st row김구원
2nd row박창목
3rd row문무익
4th row조용한
5th row강차조
ValueCountFrequency (%)
김정희 5
 
0.4%
김미정 4
 
0.3%
이미경 3
 
0.2%
김동희 3
 
0.2%
이인숙 3
 
0.2%
김명자 3
 
0.2%
김명희 3
 
0.2%
박성호 3
 
0.2%
김영희 3
 
0.2%
이미화 3
 
0.2%
Other values (1171) 1220
97.4%
2023-12-12T16:03:38.417156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 258
 
6.9%
이 204
 
5.4%
정 167
 
4.4%
영 152
 
4.1%
박 119
 
3.2%
희 106
 
2.8%
경 91
 
2.4%
미 85
 
2.3%
숙 73
 
1.9%
현 68
 
1.8%
Other values (197) 2430
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3753
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 258
 
6.9%
이 204
 
5.4%
정 167
 
4.4%
영 152
 
4.1%
박 119
 
3.2%
희 106
 
2.8%
경 91
 
2.4%
미 85
 
2.3%
숙 73
 
1.9%
현 68
 
1.8%
Other values (197) 2430
64.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3753
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 258
 
6.9%
이 204
 
5.4%
정 167
 
4.4%
영 152
 
4.1%
박 119
 
3.2%
희 106
 
2.8%
경 91
 
2.4%
미 85
 
2.3%
숙 73
 
1.9%
현 68
 
1.8%
Other values (197) 2430
64.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3753
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 258
 
6.9%
이 204
 
5.4%
정 167
 
4.4%
영 152
 
4.1%
박 119
 
3.2%
희 106
 
2.8%
경 91
 
2.4%
미 85
 
2.3%
숙 73
 
1.9%
현 68
 
1.8%
Other values (197) 2430
64.7%

소재지
Text

Distinct1186
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2023-12-12T16:03:38.734902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length31.786911
Min length15

Characters and Unicode

Total characters39829
Distinct characters271
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

Unique1126 ?
Unique (%)89.9%

Sample

1st row대구광역시 수성구 달구벌대로496길 20
2nd row대구광역시 수성구 무열로 47, 상가301동101호(만촌동,태왕리더스)
3rd row대구광역시 수성구 수성로39안길 12
4th row대구광역시 수성구 수성로 127(상동)
5th row대구광역시 수성구 신천동로 22(상동)
ValueCountFrequency (%)
대구광역시 1253
 
17.8%
수성구 1253
 
17.8%
1층 146
 
2.1%
범어동 144
 
2.0%
동대구로 95
 
1.3%
달구벌대로 81
 
1.1%
청수로 52
 
0.7%
수성로 51
 
0.7%
상가 51
 
0.7%
상가동 50
 
0.7%
Other values (1465) 3879
55.0%
2023-12-12T16:03:39.270186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5802
 
14.6%
구 2826
 
7.1%
1 1960
 
4.9%
동 1649
 
4.1%
수 1610
 
4.0%
대 1589
 
4.0%
성 1585
 
4.0%
시 1422
 
3.6%
, 1275
 
3.2%
로 1266
 
3.2%
Other values (261) 18845
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23405
58.8%
Decimal Number 7037
 
17.7%
Space Separator 5802
 
14.6%
Other Punctuation 1277
 
3.2%
Open Punctuation 1025
 
2.6%
Close Punctuation 1024
 
2.6%
Dash Punctuation 134
 
0.3%
Uppercase Letter 116
 
0.3%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2826
 
12.1%
동 1649
 
7.0%
수 1610
 
6.9%
대 1589
 
6.8%
성 1585
 
6.8%
시 1422
 
6.1%
로 1266
 
5.4%
역 1261
 
5.4%
광 1254
 
5.4%
호 672
 
2.9%
Other values (230) 8271
35.3%
Uppercase Letter
ValueCountFrequency (%)
B 38
32.8%
A 18
15.5%
S 16
13.8%
K 11
 
9.5%
C 8
 
6.9%
T 6
 
5.2%
X 6
 
5.2%
F 4
 
3.4%
N 4
 
3.4%
D 3
 
2.6%
Other values (2) 2
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 1960
27.9%
0 952
13.5%
2 952
13.5%
3 712
 
10.1%
4 611
 
8.7%
5 520
 
7.4%
6 416
 
5.9%
7 355
 
5.0%
8 322
 
4.6%
9 237
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
e 7
77.8%
k 1
 
11.1%
s 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 1275
99.8%
/ 2
 
0.2%
Space Separator
ValueCountFrequency (%)
5802
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1025
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1024
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23405
58.8%
Common 16299
40.9%
Latin 125
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2826
 
12.1%
동 1649
 
7.0%
수 1610
 
6.9%
대 1589
 
6.8%
성 1585
 
6.8%
시 1422
 
6.1%
로 1266
 
5.4%
역 1261
 
5.4%
광 1254
 
5.4%
호 672
 
2.9%
Other values (230) 8271
35.3%
Common
ValueCountFrequency (%)
5802
35.6%
1 1960
 
12.0%
, 1275
 
7.8%
( 1025
 
6.3%
) 1024
 
6.3%
0 952
 
5.8%
2 952
 
5.8%
3 712
 
4.4%
4 611
 
3.7%
5 520
 
3.2%
Other values (6) 1466
 
9.0%
Latin
ValueCountFrequency (%)
B 38
30.4%
A 18
14.4%
S 16
12.8%
K 11
 
8.8%
C 8
 
6.4%
e 7
 
5.6%
T 6
 
4.8%
X 6
 
4.8%
F 4
 
3.2%
N 4
 
3.2%
Other values (5) 7
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23405
58.8%
ASCII 16424
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5802
35.3%
1 1960
 
11.9%
, 1275
 
7.8%
( 1025
 
6.2%
) 1024
 
6.2%
0 952
 
5.8%
2 952
 
5.8%
3 712
 
4.3%
4 611
 
3.7%
5 520
 
3.2%
Other values (21) 1591
 
9.7%
Hangul
ValueCountFrequency (%)
구 2826
 
12.1%
동 1649
 
7.0%
수 1610
 
6.9%
대 1589
 
6.8%
성 1585
 
6.8%
시 1422
 
6.1%
로 1266
 
5.4%
역 1261
 
5.4%
광 1254
 
5.4%
호 672
 
2.9%
Other values (230) 8271
35.3%

전화번호
Text

MISSING 

Distinct1000
Distinct (%)97.5%
Missing227
Missing (%)18.1%
Memory size9.9 KiB
2023-12-12T16:03:39.569583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.031189
Min length12

Characters and Unicode

Total characters12344
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

Unique976 ?
Unique (%)95.1%

Sample

1st row053-744-3660
2nd row053-742-1508
3rd row053-763-9294
4th row053-763-1155
5th row053-764-4990
ValueCountFrequency (%)
053-741-8272 3
 
0.3%
053-754-2600 3
 
0.3%
053-744-8899 2
 
0.2%
053-755-9909 2
 
0.2%
053-795-9500 2
 
0.2%
053-793-4500 2
 
0.2%
053-762-1119 2
 
0.2%
053-761-0054 2
 
0.2%
053-745-0660 2
 
0.2%
053-743-3444 2
 
0.2%
Other values (990) 1004
97.9%
2023-12-12T16:03:40.076482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2062
16.7%
- 2052
16.6%
5 1693
13.7%
3 1531
12.4%
7 1314
10.6%
4 790
 
6.4%
9 674
 
5.5%
1 589
 
4.8%
6 578
 
4.7%
8 566
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10292
83.4%
Dash Punctuation 2052
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2062
20.0%
5 1693
16.4%
3 1531
14.9%
7 1314
12.8%
4 790
 
7.7%
9 674
 
6.5%
1 589
 
5.7%
6 578
 
5.6%
8 566
 
5.5%
2 495
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 2052
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12344
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2062
16.7%
- 2052
16.6%
5 1693
13.7%
3 1531
12.4%
7 1314
10.6%
4 790
 
6.4%
9 674
 
5.5%
1 589
 
4.8%
6 578
 
4.7%
8 566
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2062
16.7%
- 2052
16.6%
5 1693
13.7%
3 1531
12.4%
7 1314
10.6%
4 790
 
6.4%
9 674
 
5.5%
1 589
 
4.8%
6 578
 
4.7%
8 566
 
4.6%

기타유의사항
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
<NA>
1026 
데이터 미집계
226 
개인정보 포함
 
1

Length

Max length7
Median length4
Mean length4.5434956
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1026
81.9%
데이터 미집계 226
 
18.0%
개인정보 포함 1
 
0.1%

Length

2023-12-12T16:03:40.255497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:40.384481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1026
69.3%
데이터 226
 
15.3%
미집계 226
 
15.3%
개인정보 1
 
0.1%
포함 1
 
0.1%

Interactions

2023-12-12T16:03:35.243669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:03:40.451460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기타유의사항
연번1.0000.419
기타유의사항0.4191.000
2023-12-12T16:03:40.539004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기타유의사항
연번1.0000.316
기타유의사항0.3161.000

Missing values

2023-12-12T16:03:35.412298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:03:35.577451image/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

연번중개업등록번호행정처분상태상호명대 표 자소재지전화번호기타유의사항
01나-16-0048영업중합동부동산중개인사무소김구원대구광역시 수성구 달구벌대로496길 20053-744-3660<NA>
12나-16-0077영업중만촌현대부동산중개박창목대구광역시 수성구 무열로 47, 상가301동101호(만촌동,태왕리더스)053-742-1508<NA>
23나-16-0241영업중한양부동산중개인사무소문무익대구광역시 수성구 수성로39안길 12053-763-9294<NA>
34나-16-0243영업중신진부동산중개사무소조용한대구광역시 수성구 수성로 127(상동)053-763-1155<NA>
45나-16-0244영업중신신부동산중개인사무소강차조대구광역시 수성구 신천동로 22(상동)053-764-4990<NA>
5627260-2018-00184영업중영남부동산중개박순도대구광역시 수성구 욱수천로 133, 201동 102호(사월동, 사월보성2차)053-791-1800<NA>
67가-16-0148영업중엘리트부동산중개사무소배용호대구광역시 수성구 무학로21길 41(두산동)053-766-3900<NA>
78가-16-0300영업중신도부동산중개인사무소도기은대구광역시 수성구 수성로25길 54053-763-3725<NA>
89가-16-1501영업중동남부동산중개컨설팅사무소심종섭대구광역시 수성구 동대구로 167, 2층(황금동)053-761-7501<NA>
910가-16-2832영업중메트로팔레스부동산중개합동사무소조재희대구광역시 수성구 동원로 123, 상가221동106호(만촌동,메트로팔래스2단지아파트)053-742-0660<NA>
연번중개업등록번호행정처분상태상호명대 표 자소재지전화번호기타유의사항
1243124427260-2021-00103영업중(주)우리나라부동산중개법인강규환대구광역시 수성구 범어로 153053-752-2999<NA>
1244124527260-2021-00137영업중재방부동산중개주식회사성정용대구광역시 수성구 교학로 49-1<NA>데이터 미집계
1245124627260-2021-00200영업중주식회사 범어에일린의뜰부동산중개법인이상인대구광역시 수성구 청솔로 53, 1층 (수성동3가)<NA>데이터 미집계
1246124727260-2021-00208영업중캐슬칸부동산중개법인 주식회사이상극대구광역시 수성구 범어천로 107, 상가302동 115-2호 (범어동, 범어STX KAN)053-755-6606<NA>
1247124827260-2021-00225영업중주식회사 은성컨설팅공인중개사사무소심은영대구광역시 수성구 동대구로73길 10, 2층 (범어동)<NA>데이터 미집계
1248124927260-2022-00041영업중주식회사 맨하탄부동산중개법인임인규대구광역시 수성구 동대구로 59, A동 4호 및 13호 (두산동, 대우트럼프월드 수성)<NA>데이터 미집계
1249125027260-2022-00047영업중주식회사 요이땅부동산중개법인허지수대구광역시 수성구 청솔로 16, 상가110동 104호 (황금동, 힐스테이트황금엘포레)053-217-0205<NA>
1250125127260-2022-00111영업중NS부동산중개법인최송원대구광역시 수성구 청수로26길 46, 1동 105호 (두산동)<NA>데이터 미집계
1251125227260-2022-00117영업중유한회사대광부동산중개법인박재목대구광역시 수성구 범어천로 5053-745-1010<NA>
12521253가-16-4676영업중주식회사 신한국부동산중개박성호대구광역시 수성구 화랑로 16(만촌동)053-754-2727<NA>