Overview

Dataset statistics

Number of variables8
Number of observations2478
Missing cells465
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory157.4 KiB
Average record size in memory65.1 B

Variable types

Numeric1
Categorical2
Text4
DateTime1

Dataset

Description성남시내 부동산중개업소현황 데이타로, 구, 동, 등록번호, 사무소명, 전화번호, 주소 항목으로 구성되어 있습니다
Author경기도 성남시
URLhttps://www.data.go.kr/data/15043670/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
구별 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 구별High correlation
연번 is highly overall correlated with 구별High correlation
전화번호 has 465 (18.8%) missing valuesMissing
연번 has unique valuesUnique
등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:15:39.246458
Analysis finished2023-12-12 12:15:40.551499
Duration1.31 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2478
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1239.5
Minimum1
Maximum2478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.9 KiB
2023-12-12T21:15:40.650723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile124.85
Q1620.25
median1239.5
Q31858.75
95-th percentile2354.15
Maximum2478
Range2477
Interquartile range (IQR)1238.5

Descriptive statistics

Standard deviation715.48131
Coefficient of variation (CV)0.57723381
Kurtosis-1.2
Mean1239.5
Median Absolute Deviation (MAD)619.5
Skewness0
Sum3071481
Variance511913.5
MonotonicityStrictly increasing
2023-12-12T21:15:40.804988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1656 1
 
< 0.1%
1649 1
 
< 0.1%
1650 1
 
< 0.1%
1651 1
 
< 0.1%
1652 1
 
< 0.1%
1653 1
 
< 0.1%
1654 1
 
< 0.1%
1655 1
 
< 0.1%
1657 1
 
< 0.1%
Other values (2468) 2468
99.6%
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 (%)
2478 1
< 0.1%
2477 1
< 0.1%
2476 1
< 0.1%
2475 1
< 0.1%
2474 1
< 0.1%
2473 1
< 0.1%
2472 1
< 0.1%
2471 1
< 0.1%
2470 1
< 0.1%
2469 1
< 0.1%

구별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.5 KiB
경기도 성남시분당구
1179 
경기도 성남시수정구
663 
경기도 성남시중원구
636 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 성남시수정구
2nd row경기도 성남시수정구
3rd row경기도 성남시수정구
4th row경기도 성남시수정구
5th row경기도 성남시수정구

Common Values

ValueCountFrequency (%)
경기도 성남시분당구 1179
47.6%
경기도 성남시수정구 663
26.8%
경기도 성남시중원구 636
25.7%

Length

2023-12-12T21:15:40.933567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:15:41.037923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 2478
50.0%
성남시분당구 1179
23.8%
성남시수정구 663
 
13.4%
성남시중원구 636
 
12.8%

등록번호
Text

UNIQUE 

Distinct2478
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size19.5 KiB
2023-12-12T21:15:41.281745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length14.730024
Min length7

Characters and Unicode

Total characters36501
Distinct characters14
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

Unique2478 ?
Unique (%)100.0%

Sample

1st row나-3604-1-2
2nd row나-36040000-50
3rd row나-36040000-1-0090
4th row나-36040000-1-0182
5th row가-3604-1-175
ValueCountFrequency (%)
나-3604-1-2 1
 
< 0.1%
가-3604-3-6866 1
 
< 0.1%
가-3604-3-6791 1
 
< 0.1%
가-3604-3-6800 1
 
< 0.1%
가-3604-3-6936 1
 
< 0.1%
가-3604-3-6807 1
 
< 0.1%
가-3604-3-6808 1
 
< 0.1%
가-3604-3-6809 1
 
< 0.1%
가-3604-3-6815 1
 
< 0.1%
가-3604-3-6871 1
 
< 0.1%
Other values (2468) 2468
99.6%
2023-12-12T21:15:41.679267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7532
20.6%
1 5977
16.4%
- 5684
15.6%
3 4112
11.3%
2 3405
9.3%
4 3223
8.8%
6 1852
 
5.1%
5 1386
 
3.8%
가 977
 
2.7%
7 886
 
2.4%
Other values (4) 1467
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29814
81.7%
Dash Punctuation 5684
 
15.6%
Other Letter 1003
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7532
25.3%
1 5977
20.0%
3 4112
13.8%
2 3405
11.4%
4 3223
10.8%
6 1852
 
6.2%
5 1386
 
4.6%
7 886
 
3.0%
9 729
 
2.4%
8 712
 
2.4%
Other Letter
ValueCountFrequency (%)
가 977
97.4%
나 25
 
2.5%
기 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 5684
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35498
97.3%
Hangul 1003
 
2.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7532
21.2%
1 5977
16.8%
- 5684
16.0%
3 4112
11.6%
2 3405
9.6%
4 3223
9.1%
6 1852
 
5.2%
5 1386
 
3.9%
7 886
 
2.5%
9 729
 
2.1%
Hangul
ValueCountFrequency (%)
가 977
97.4%
나 25
 
2.5%
기 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35498
97.3%
Hangul 1003
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7532
21.2%
1 5977
16.8%
- 5684
16.0%
3 4112
11.6%
2 3405
9.6%
4 3223
9.1%
6 1852
 
5.2%
5 1386
 
3.9%
7 886
 
2.5%
9 729
 
2.1%
Hangul
ValueCountFrequency (%)
가 977
97.4%
나 25
 
2.5%
기 1
 
0.1%

사무소명
Text

Distinct1700
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size19.5 KiB
2023-12-12T21:15:41.900249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length11.164245
Min length7

Characters and Unicode

Total characters27665
Distinct characters466
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1429 ?
Unique (%)57.7%

Sample

1st row대흥부동산중개인사무소
2nd row신흥부동산중개인사무소
3rd row충남부동산중개인
4th row산성부동산중개인
5th row하나부동산중개컨설팅
ValueCountFrequency (%)
사무소 55
 
2.1%
공인중개사 51
 
1.9%
공인중개사사무소 42
 
1.6%
삼성공인중개사사무소 30
 
1.1%
현대공인중개사사무소 29
 
1.1%
우리공인중개사사무소 21
 
0.8%
미래공인중개사사무소 19
 
0.7%
중앙공인중개사사무소 17
 
0.6%
하나공인중개사사무소 15
 
0.6%
행운공인중개사사무소 14
 
0.5%
Other values (1701) 2352
88.9%
2023-12-12T21:15:42.303565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 4765
17.2%
중 2515
 
9.1%
개 2484
 
9.0%
인 2442
 
8.8%
소 2391
 
8.6%
무 2390
 
8.6%
공 2367
 
8.6%
동 356
 
1.3%
산 332
 
1.2%
부 313
 
1.1%
Other values (456) 7310
26.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27128
98.1%
Space Separator 167
 
0.6%
Uppercase Letter 155
 
0.6%
Decimal Number 129
 
0.5%
Lowercase Letter 30
 
0.1%
Open Punctuation 24
 
0.1%
Close Punctuation 24
 
0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Letter Number 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 4765
17.6%
중 2515
 
9.3%
개 2484
 
9.2%
인 2442
 
9.0%
소 2391
 
8.8%
무 2390
 
8.8%
공 2367
 
8.7%
동 356
 
1.3%
산 332
 
1.2%
부 313
 
1.2%
Other values (407) 6773
25.0%
Uppercase Letter
ValueCountFrequency (%)
K 29
18.7%
L 20
12.9%
O 15
9.7%
A 12
7.7%
G 12
7.7%
S 11
 
7.1%
B 10
 
6.5%
E 9
 
5.8%
W 7
 
4.5%
T 6
 
3.9%
Other values (9) 24
15.5%
Lowercase Letter
ValueCountFrequency (%)
e 14
46.7%
s 3
 
10.0%
l 3
 
10.0%
a 2
 
6.7%
h 2
 
6.7%
t 1
 
3.3%
r 1
 
3.3%
o 1
 
3.3%
n 1
 
3.3%
i 1
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 63
48.8%
4 20
 
15.5%
2 14
 
10.9%
8 11
 
8.5%
9 7
 
5.4%
3 7
 
5.4%
6 2
 
1.6%
5 2
 
1.6%
0 2
 
1.6%
7 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
167
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%
Math Symbol
ValueCountFrequency (%)
∥ 1
100.0%
Other Symbol
ValueCountFrequency (%)
ⓝ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27127
98.1%
Common 351
 
1.3%
Latin 186
 
0.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 4765
17.6%
중 2515
 
9.3%
개 2484
 
9.2%
인 2442
 
9.0%
소 2391
 
8.8%
무 2390
 
8.8%
공 2367
 
8.7%
동 356
 
1.3%
산 332
 
1.2%
부 313
 
1.2%
Other values (406) 6772
25.0%
Latin
ValueCountFrequency (%)
K 29
15.6%
L 20
10.8%
O 15
 
8.1%
e 14
 
7.5%
A 12
 
6.5%
G 12
 
6.5%
S 11
 
5.9%
B 10
 
5.4%
E 9
 
4.8%
W 7
 
3.8%
Other values (21) 47
25.3%
Common
ValueCountFrequency (%)
167
47.6%
1 63
 
17.9%
( 24
 
6.8%
) 24
 
6.8%
4 20
 
5.7%
2 14
 
4.0%
8 11
 
3.1%
9 7
 
2.0%
3 7
 
2.0%
- 3
 
0.9%
Other values (8) 11
 
3.1%
Han
ValueCountFrequency (%)
大 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27127
98.1%
ASCII 534
 
1.9%
Number Forms 1
 
< 0.1%
Math Operators 1
 
< 0.1%
CJK 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 4765
17.6%
중 2515
 
9.3%
개 2484
 
9.2%
인 2442
 
9.0%
소 2391
 
8.8%
무 2390
 
8.8%
공 2367
 
8.7%
동 356
 
1.3%
산 332
 
1.2%
부 313
 
1.2%
Other values (406) 6772
25.0%
ASCII
ValueCountFrequency (%)
167
31.3%
1 63
 
11.8%
K 29
 
5.4%
( 24
 
4.5%
) 24
 
4.5%
4 20
 
3.7%
L 20
 
3.7%
O 15
 
2.8%
e 14
 
2.6%
2 14
 
2.6%
Other values (36) 144
27.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%
Math Operators
ValueCountFrequency (%)
∥ 1
100.0%
CJK
ValueCountFrequency (%)
大 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓝ 1
100.0%

전화번호
Text

MISSING 

Distinct1965
Distinct (%)97.6%
Missing465
Missing (%)18.8%
Memory size19.5 KiB
2023-12-12T21:15:42.611567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.046696
Min length9

Characters and Unicode

Total characters24250
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1917 ?
Unique (%)95.2%

Sample

1st row031-757-2449
2nd row031-757-3268
3rd row031-753-4564
4th row031-734-2517
5th row031-754-3636
ValueCountFrequency (%)
031-746-5100 2
 
0.1%
031-758-5115 2
 
0.1%
031-752-5558 2
 
0.1%
031-706-7000 2
 
0.1%
031-748-7771 2
 
0.1%
031-701-5252 2
 
0.1%
031-736-1110 2
 
0.1%
031-712-0033 2
 
0.1%
031-745-9400 2
 
0.1%
031-733-8882 2
 
0.1%
Other values (1957) 1995
99.0%
2023-12-12T21:15:43.090304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4550
18.8%
- 4023
16.6%
1 3494
14.4%
3 3047
12.6%
7 2694
11.1%
4 1290
 
5.3%
8 1264
 
5.2%
5 1247
 
5.1%
2 1011
 
4.2%
9 881
 
3.6%
Other values (3) 749
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20224
83.4%
Dash Punctuation 4023
 
16.6%
Space Separator 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4550
22.5%
1 3494
17.3%
3 3047
15.1%
7 2694
13.3%
4 1290
 
6.4%
8 1264
 
6.2%
5 1247
 
6.2%
2 1011
 
5.0%
9 881
 
4.4%
6 746
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 4023
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24250
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4550
18.8%
- 4023
16.6%
1 3494
14.4%
3 3047
12.6%
7 2694
11.1%
4 1290
 
5.3%
8 1264
 
5.2%
5 1247
 
5.1%
2 1011
 
4.2%
9 881
 
3.6%
Other values (3) 749
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4550
18.8%
- 4023
16.6%
1 3494
14.4%
3 3047
12.6%
7 2694
11.1%
4 1290
 
5.3%
8 1264
 
5.2%
5 1247
 
5.1%
2 1011
 
4.2%
9 881
 
3.6%
Other values (3) 749
 
3.1%

사무소주소
Text

Distinct2430
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size19.5 KiB
2023-12-12T21:15:43.374424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length51
Mean length32.0795
Min length17

Characters and Unicode

Total characters79493
Distinct characters387
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2383 ?
Unique (%)96.2%

Sample

1st row경기도 성남시 수정구 시민로145번길 5
2nd row경기도 성남시 수정구 시민로155번길 24
3rd row경기도 성남시 수정구 수정북로 49
4th row경기도 성남시 수정구 산성대로405번길 3
5th row경기도 성남시 수정구 시민로 193-1, 1층 (태평동)
ValueCountFrequency (%)
경기도 2478
 
15.6%
성남시 2478
 
15.6%
분당구 1179
 
7.4%
수정구 663
 
4.2%
중원구 636
 
4.0%
1층 163
 
1.0%
상가동 148
 
0.9%
101호 76
 
0.5%
102호 76
 
0.5%
위례광장로 75
 
0.5%
Other values (2728) 7941
49.9%
2023-12-12T21:15:43.807205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13435
 
16.9%
1 4312
 
5.4%
성 2964
 
3.7%
남 2879
 
3.6%
시 2631
 
3.3%
구 2542
 
3.2%
경 2502
 
3.1%
도 2502
 
3.1%
기 2499
 
3.1%
로 2488
 
3.1%
Other values (377) 40739
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46110
58.0%
Decimal Number 14084
 
17.7%
Space Separator 13435
 
16.9%
Other Punctuation 2398
 
3.0%
Open Punctuation 1346
 
1.7%
Close Punctuation 1345
 
1.7%
Dash Punctuation 442
 
0.6%
Uppercase Letter 291
 
0.4%
Lowercase Letter 33
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 2964
 
6.4%
남 2879
 
6.2%
시 2631
 
5.7%
구 2542
 
5.5%
경 2502
 
5.4%
도 2502
 
5.4%
기 2499
 
5.4%
로 2488
 
5.4%
동 1837
 
4.0%
호 1335
 
2.9%
Other values (319) 21931
47.6%
Uppercase Letter
ValueCountFrequency (%)
B 107
36.8%
A 44
15.1%
G 16
 
5.5%
K 15
 
5.2%
S 14
 
4.8%
C 12
 
4.1%
I 9
 
3.1%
D 8
 
2.7%
R 8
 
2.7%
T 8
 
2.7%
Other values (13) 50
17.2%
Decimal Number
ValueCountFrequency (%)
1 4312
30.6%
0 1921
13.6%
2 1703
 
12.1%
3 1327
 
9.4%
4 1093
 
7.8%
5 976
 
6.9%
6 838
 
6.0%
7 732
 
5.2%
9 617
 
4.4%
8 565
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
a 8
24.2%
b 8
24.2%
f 5
15.2%
k 3
 
9.1%
c 2
 
6.1%
d 2
 
6.1%
s 2
 
6.1%
n 2
 
6.1%
u 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 2387
99.5%
. 6
 
0.3%
/ 3
 
0.1%
@ 1
 
< 0.1%
' 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 3
60.0%
> 1
 
20.0%
< 1
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 1324
98.4%
[ 22
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 1323
98.4%
] 22
 
1.6%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅰ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
13435
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 442
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46110
58.0%
Common 33055
41.6%
Latin 328
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 2964
 
6.4%
남 2879
 
6.2%
시 2631
 
5.7%
구 2542
 
5.5%
경 2502
 
5.4%
도 2502
 
5.4%
기 2499
 
5.4%
로 2488
 
5.4%
동 1837
 
4.0%
호 1335
 
2.9%
Other values (319) 21931
47.6%
Latin
ValueCountFrequency (%)
B 107
32.6%
A 44
13.4%
G 16
 
4.9%
K 15
 
4.6%
S 14
 
4.3%
C 12
 
3.7%
I 9
 
2.7%
D 8
 
2.4%
R 8
 
2.4%
a 8
 
2.4%
Other values (24) 87
26.5%
Common
ValueCountFrequency (%)
13435
40.6%
1 4312
 
13.0%
, 2387
 
7.2%
0 1921
 
5.8%
2 1703
 
5.2%
3 1327
 
4.0%
( 1324
 
4.0%
) 1323
 
4.0%
4 1093
 
3.3%
5 976
 
3.0%
Other values (14) 3254
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46110
58.0%
ASCII 33379
42.0%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13435
40.2%
1 4312
 
12.9%
, 2387
 
7.2%
0 1921
 
5.8%
2 1703
 
5.1%
3 1327
 
4.0%
( 1324
 
4.0%
) 1323
 
4.0%
4 1093
 
3.3%
5 976
 
2.9%
Other values (46) 3578
 
10.7%
Hangul
ValueCountFrequency (%)
성 2964
 
6.4%
남 2879
 
6.2%
시 2631
 
5.7%
구 2542
 
5.5%
경 2502
 
5.4%
도 2502
 
5.4%
기 2499
 
5.4%
로 2488
 
5.4%
동 1837
 
4.0%
호 1335
 
2.9%
Other values (319) 21931
47.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅰ 1
 
25.0%

행정동
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size19.5 KiB
성남동
 
152
위례동
 
133
서현1동
 
125
운중동
 
104
금광2동
 
99
Other values (45)
1865 

Length

Max length5
Median length4
Mean length3.6545601
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신흥1동
2nd row신흥1동
3rd row태평3동
4th row단대동
5th row태평4동

Common Values

ValueCountFrequency (%)
성남동 152
 
6.1%
위례동 133
 
5.4%
서현1동 125
 
5.0%
운중동 104
 
4.2%
금광2동 99
 
4.0%
정자1동 95
 
3.8%
상대원1동 82
 
3.3%
금곡동 79
 
3.2%
삼평동 73
 
2.9%
구미동 70
 
2.8%
Other values (40) 1466
59.2%

Length

2023-12-12T21:15:44.001358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남동 152
 
6.1%
위례동 133
 
5.4%
서현1동 125
 
5.0%
운중동 104
 
4.2%
금광2동 99
 
4.0%
정자1동 95
 
3.8%
상대원1동 82
 
3.3%
금곡동 79
 
3.2%
삼평동 73
 
2.9%
구미동 70
 
2.8%
Other values (40) 1466
59.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.5 KiB
Minimum2022-04-30 00:00:00
Maximum2022-04-30 00:00:00
2023-12-12T21:15:44.121786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:44.237446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T21:15:40.105354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:15:44.316007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구별행정동
연번1.0000.9420.863
구별0.9421.0001.000
행정동0.8631.0001.000
2023-12-12T21:15:44.419563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구별행정동
구별1.0000.990
행정동0.9901.000
2023-12-12T21:15:44.872640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구별행정동
연번1.0000.9260.477
구별0.9261.0000.990
행정동0.4770.9901.000

Missing values

2023-12-12T21:15:40.291922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:15:40.461368image/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

연번구별등록번호사무소명전화번호사무소주소행정동데이터기준일자
01경기도 성남시수정구나-3604-1-2대흥부동산중개인사무소031-757-2449경기도 성남시 수정구 시민로145번길 5신흥1동2022-04-30
12경기도 성남시수정구나-36040000-50신흥부동산중개인사무소031-757-3268경기도 성남시 수정구 시민로155번길 24신흥1동2022-04-30
23경기도 성남시수정구나-36040000-1-0090충남부동산중개인031-753-4564경기도 성남시 수정구 수정북로 49태평3동2022-04-30
34경기도 성남시수정구나-36040000-1-0182산성부동산중개인031-734-2517경기도 성남시 수정구 산성대로405번길 3단대동2022-04-30
45경기도 성남시수정구가-3604-1-175하나부동산중개컨설팅031-754-3636경기도 성남시 수정구 시민로 193-1, 1층 (태평동)태평4동2022-04-30
56경기도 성남시수정구나-36040000-1-0210충남부동산중개인사무소031-751-1746경기도 성남시 수정구 성남대로 1282, 1층 (태평동)태평1동2022-04-30
67경기도 성남시수정구나-36040000-1-0270강원부동산중개인031-753-0623경기도 성남시 수정구 탄리로131번길 1태평3동2022-04-30
78경기도 성남시수정구나-36040000-1-0297신완사부동산중개인사무소031-721-1573경기도 성남시 수정구 탄리로17번길 25수진1동2022-04-30
89경기도 성남시수정구가-3604-1-1702산성공인중개사사무소031-743-5252경기도 성남시 수정구 수정로 356산성동2022-04-30
910경기도 성남시수정구가-3604-1-3150영동공인중개사사무소031-756-8824경기도 성남시 수정구 남문로 57태평3동2022-04-30
연번구별등록번호사무소명전화번호사무소주소행정동데이터기준일자
24682469경기도 성남시분당구41135-2022-00040정문부동산중개<NA>경기도 성남시 분당구 판교대장로5길 19, 상가 101호 일부(대장동, 힐스테이트 판교 엘포레 A4BL)운중동2022-04-30
24692470경기도 성남시분당구41135-2022-00042굿모닝파크공인중개사사무소031-706-4600경기도 성남시 분당구 성남대로779번길 48, 골든프라자 107호(이매동)이매2동2022-04-30
24702471경기도 성남시분당구41135-2022-00043파빌리온하늘땅공인중개사사무소031-785-4499경기도 성남시 분당구 성남대로 393, A-101 (정자동, 두산위브파빌리온)정자1동2022-04-30
24712472경기도 성남시분당구41135-2022-00044미금프라임공인중개사사무소031-713-8844경기도 성남시 분당구 미금로 251, 청솔마을 상가동 110호금곡동2022-04-30
24722473경기도 성남시분당구41135-2022-00045보화공인중개사사무소<NA>경기도 성남시 분당구 벌말로 33, 일심조합상가 지하3호 일부(야탑동)야탑3동2022-04-30
24732474경기도 성남시분당구41135-2022-00046가결부동산공인중개사사무소031-705-0015경기도 성남시 분당구 장미로 101, 장미마을근린상가 1동 1114호(야탑동, 장미마을)야탑1동2022-04-30
24742475경기도 성남시분당구41135-2022-00047점프부동산중개주식회사031-302-0056경기도 성남시 분당구 성남대로331번길 9-14, MOSON빌딩 2층 212호정자1동2022-04-30
24752476경기도 성남시분당구41135-2022-00048금성공인중개사사무소<NA>경기도 성남시 분당구 성남대로926번길 10, 탑빌딩 5층 R514호야탑1동2022-04-30
24762477경기도 성남시분당구41135-2022-00049세종공인중개사사무소031-717-4005경기도 성남시 분당구 구미로9번길 8, 세종그랑시아 1동 102호(구미동, 세종그랑시아)구미동2022-04-30
24772478경기도 성남시분당구41135-2022-00050NEW스마트공인중개사사무소<NA>경기도 성남시 분당구 양현로 138, 지층 B01호(이매동, 이매촌근린상가)이매1동2022-04-30